diff --git a/LICENSES/Strata-MIT.txt b/LICENSES/Strata-MIT.txt new file mode 100644 index 0000000000..6687a423dd --- /dev/null +++ b/LICENSES/Strata-MIT.txt @@ -0,0 +1,21 @@ +MIT License + +Copyright (c) 2026 Niko1221 and the Strata contributors + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. diff --git a/THIRD_PARTY_NOTICES.md b/THIRD_PARTY_NOTICES.md index 0cc42a93ea..1c938e215b 100644 --- a/THIRD_PARTY_NOTICES.md +++ b/THIRD_PARTY_NOTICES.md @@ -24,6 +24,14 @@ Copyright © 2026 Joshua Warren and mlx-omarchy contributors. Its arithmetic is unchanged; the native Vulkan path does not link MLX. See [the license text](LICENSES/mlx-omarchy-MIT.txt). +## Strata HIP kernels + +`zig/kernels/hip/common/tsum.hpp` ports `src/kernels/cuda/s26_tsum.cuh` from +[Strata](https://github.com/Niko1221/Strata) at 4b9e05a2, MIT License, +Copyright (c) 2026 Niko1221 and the Strata contributors. +The block layout of `zig/kernels/hip/tiles/dense_gemm.hpp` follows Strata's gfx11 WMMA kernels; its arithmetic is TensorFold's. +See [the license text](LICENSES/Strata-MIT.txt). + ## Qwen Flash Next The n-gram ID helpers translate Hugging Face transformers' `models/qwen4_exp/modeling_qwen4_exp.py` with renamed diff --git a/docs/kernel-contract.md b/docs/kernel-contract.md index 5beb7de44b..048ad75483 100644 --- a/docs/kernel-contract.md +++ b/docs/kernel-contract.md @@ -184,6 +184,36 @@ each row then L2-normed, against float64's ranges at their bf16 points and expf' CUDA also checks `dense_rows`' scaled epilogue (Dory's logits, fp32(bf16(x . w)) times a per-column scale), bit-equal to its unscaled tile's outputs rounded and scaled on the host. HIP: the RMS norm rows, a wave a row (fp32, fp16 and bf16 out) and a block a row (fp16 and bf16 out). +HIP also checks Qwen3.8-Flash-Next's gfx11 matrix-core prompt tiles: the dense tile (`affine_wmma_dense`) at K 320, +2560, 6144 and 10240, fp32 out and bf16 out, bit-equal to the matrix tile `affine_wmma_gemm` (then `tf_cast`). +Its routed expert tiles take a prompt's plan: gate and up with silu(g) u in bf16 (`affine_wmma_moe_gu`) and down in fp32 +(`affine_wmma_moe_down`), bit-equal to `affine_wmma_gemm` over the same plan (then `tf_moe_act`). +HIP also checks a prompt's MoE plan in three launches (`tf_route_count`, `tf_route_scan`, `tf_route_scatter`), +bit-equal to `tf_moe_route`, and its stated plan: the pairs stably sorted by expert, each expert's pairs cut into tiles. +HIP's MoE picks: `tf_select_rows`, bit-equal to `select_body`, and `tf_router_select_*` (router logits, picks and plan in +one launch), bit-equal to `tf_router_decode`, the pick and `tf_moe_route`, its logits' sums proven fp32. Both check the +pick's stated rule (a NaN below every number, ties to the lower id, every slot written) and carry a known finding at +gate 1: upstream's `select_body` ranks a NaN level with the top number, so slot 0 races, and a row of fewer than k +numbers leaves slots unwritten. Their bytes stay equal to upstream's. +HIP's top-k in parts (`tf_topk_part`, `tf_topk_join`) is bit-equal to `tf_topk` and checked against its key order: a +positive NaN above +Inf, a negative NaN below -Inf, -0 equal to +0, ties to the lower id. +`tf_moe_prefetch` writes nothing: gates 1 to 3 check that every buffer and guard stays as prepared, and gate 5 holds +its launch. It has no float output for gates 1 and 3 to class or bound, and no sums for gate 4. +HIP also checks Flash Next's hyper-connection kernels. On gfx11, `tf_affine_dense_hcmix` (hc up's dense K 320 tile +with the HC mix as its epilogue) is bit-equal to the tile's bf16 product then `tf_fn_hc_mix`, and its gate table +`tf_hc_gate_fill` holds, for all 65,536 bf16 g, float64's sigmoid rounded to bf16 within expf's 2^-20 and +`tf_fn_hc_mix`'s gate bit for bit. +`tf_fn_hc_mix8`, the bf16 mix at 8 outputs a thread, is bit-equal to `tf_fn_hc_mix` over fp32 and bf16 g. +`tf_fn_hc_norm_v` (bf16 streams of 2,560 in 16-byte accesses, with and without a branch) is bit-equal to +`tf_fn_hc_norm`, and the MoE combine inside the norm (`tf_fn_hc_norm_moe`, and `tf_fn_hc_norm_moe_v` a block a row) +to `tf_moe_combine` then `tf_fn_hc_norm`. +HIP also checks the DeltaNet prompt recurrence at half a value head a block (`tf_gdn_prompt_128`, its y and state), +bit-equal to the plain window scan `gated_delta_tile` on the same tokens. +Its prompt prework in one launch (`tf_gdn_prompt_prep`: conv, q and k head norms, v, gate, beta and the new conv state) +is bit-equal to the chain it replaces (`tf_conv_prefill`, `tf_copy_cols`, `tf_rms`, `tf_gdn_gate_prefill`). +A verify window that holds its state (`tf_gdn_hold_128` and `_16`: y only, the state an input left unchanged) and the +keep that replays it (`tf_gdn_keep_128` and `_16`: two layers' states after their kept rows) are each bit-equal to +`gated_delta_tile` over the same rows. RADIO's fused bias, activation and residual (`tf_vit_bias_act`) replaces `tf_vit_bias` then `tf_vit_pointwise`, byte for byte. @@ -207,6 +237,12 @@ CUDA also checks Nemotron's pocket (`nemotron_ops.cu`, the learned neurons the l shared expert): relu^2 up into act rows and down added into the shared expert's slot, a block row a row and tiled, the down to fp32 and bf16, against float64, the neurons past the count NaN so a read of one shows (two controls: the up's relu by `fmaxf`, and the down launched one neuron short). +HIP also checks Flash Next's index block scores over 4 heads of 128: `tf_fn_idx_scores_quad` (4 lanes a score) and +`tf_fn_idx_scores8` (8 rows a wave), each bit-equal to `tf_fn_idx_scores`. Their relu is `fmaxf(x, 0)`: a NaN head +dot scores 0 where float64 keeps the NaN, a known finding as `tf_glm_scores`'s is. +HIP also checks Flash Next's QSA decode prep, `tf_fn_qsa_prep`, bit-equal to the seven launches it replaces (`tf_qk_rope` +for q, the index q and k, `tf_kv_write_at` for v and the raw index key, `tf_copy_cols` and `tf_fn_idx_pool_at`) on 1 to +15 rows, its fp32 rows and its caches and pools each registered, the caches' earlier contents prepared. ## CUDA records per nvcc release diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/README.md b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/README.md new file mode 100644 index 0000000000..98cbe921b4 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/README.md @@ -0,0 +1,121 @@ +# gfx1151 Qwen3.8-Flash-Next HIP series: exactness, performance and memory + +Receipt for [#1667](https://github.com/ashhart/TensorFold/pull/1667), the HIP Qwen3.8-Flash-Next series on gfx1151. +Measured on 2026-10-31, on an AMD Strix Halo (gfx1151) machine with 192 GiB of unified memory (184.6 GiB reported by +the kernel), ROCm 7.15 (HIP 7.15.26333), zig 0.17.0, Python 3.13. +The tested source is the tip of the series' code commits, **`37aed1a0384625d4ff35c23e7df2b502d2a8b7f6`** (`new`). The comparison is +`main` at **`94b90c9db65dcb71bbc39715901d6fb1f00407d0`** (`base`), the commit the series is based on. +The receipt commit adds only this folder. This receipt does not qualify other checkpoints, other GPUs, multi-GPU runs, +other platforms or machines with less memory. + +## Checkpoint and binaries + +- Checkpoint `TensorFold/Qwen3.8-Flash-Next-MLX-4bit-MTP`, revision `2b170fa6309d5d1ee380b35636075fac7945f286`. + `perf/checkpoint.json` lists each file with its size and SHA-256. +- Binary SHA-256 values are in `perf/provenance.json` and `exactness/provenance.json`. Build: + `zig build native-hip tf-flashnext-hip-test -Dhip=true -Dhip-arch=gfx1151 -Doptimize=ReleaseFast` with the ROCm + `hipcc`, include and device-library paths. Every row of this receipt ran on these two binaries. +- `perf/logs/session-01.log` to `session-06.log` are the harness logs in time order: cold prefill at 2K to 32K, at 64K + and 128K, at the native window, the decode clients, the 16K decode, and the memory A/B. `new` and `base` alternate + in each round of each session. +- One server process ran at a time, under the machine's GPU lock. Each run started a fresh server and stopped it. + No limit of the machine was raised. + +## Exactness ([exactness/](exactness/)) + +Server: `--context 32768 --parallel 4 --prompt-cache-gib 1 --no-thinking`, `--metrics-open`. + +| Check | Result | +| --- | --- | +| `zig/tests/qwen35/serve_check.py` | 15 ok, 0 fail; 1,285 of 1,688 drafted tokens accepted | +| Token-hash audit (identical request bodies, `draft` ignored) | 11 groups, 0 differ | +| `zig/tests/qwen35/serve_cancel.py` | 3 ok, 0 fail | +| `zig/tests/flashnext_hip/rewind.py`, prompt cache on against off | 0 replies differ; up to 10,240 cached tokens | +| `tf-flashnext-hip-test generate --chat --max 64 --hash --chunk C`, 10,368-token prompt | `c8f6888043c972e0` for C = 512, 2,048, 8,192 and 20,480 | + +`serve_check.py` ran under `record_http.py`, which keeps each request and reply in `exactness/*-serve-check.jsonl` +and passes both on unchanged. `exactness/seam-corpus.json` names the public CPython library files of the seam prompt. + +## Performance ([perf/](perf/)) + +`new` and `base` alternate in each round, 2 rounds. Greedy, seed 1234, thinking off, prompt cache off. +Prompts: token arrays of exactly N tokens from the top-level `.py` files of the CPython standard library +(`perf/prompts/corpus.json` names each file and its SHA-256). `perf/summary.md` has every row and every round. + +- Cold prefill: `max_tokens` 1, a fresh server a run, `--context` N + 8,192 (262,144 for the 261,888-token row). + Prefill tok/s = prompt tokens / TTFT. +- 16,384-token prompt: 256 and 1,024 output tokens, 3 reps each in 2 rounds, after one unrecorded 16-token request. + Serial runs the server with `--no-drafts`; Default MTP runs the server defaults. + Decode tok/s = (output tokens - 1) / (last token time - first token time). +- `tools/bench_openai.py` and `tools/bench_concurrent.py --levels 1,4 --alone --serial`, 256 tokens, 3 reps. + +| Prompt tokens | 2,048 | 8,192 | 32,768 | 65,536 | 131,072 | 261,888 | +| --- | ---: | ---: | ---: | ---: | ---: | ---: | +| `new` prefill tok/s | 673.7 | 558.2 | 513.5 | 496.7 | 471.6 | 437.3 | +| `base` prefill tok/s | 293.2 | 261.3 | 260.4 | 259.3 | 258.0 | 244.8 | + +| 16,384-token prompt, 1,024 tokens | Prefill tok/s | Decode tok/s | TTFT (s) | Wall time (s) | Spec-decode hit rate (%) | +| --- | ---: | ---: | ---: | ---: | ---: | +| `new` serial | 533.5 | 35.71 | 30.75 | 59.39 | - | +| `base` serial | 353.3 | 29.99 | 46.55 | 80.70 | - | +| `new` Default MTP | 533.5 | 49.05 | 30.94 | 51.86 | 61.8 | +| `base` Default MTP | 353.3 | 38.26 | 46.54 | 73.32 | 68.1 | + +The Default MTP reply has the same token hash as the serial reply on both builds, and both builds give the same tokens. +Four concurrent streams, aggregate decode: 117.4 against 89.65 tok/s (code), 99.75 against 72.95 tok/s (chat); +concurrent equals alone and drafted equals plain on both builds. + +## Memory ([perf/memory-ab/](perf/memory-ab/)) + +`memory_ab.sh`: a fresh `new` server at `--context 20480 --parallel 1 --prompt-cache-gib 0` for each setting, +2 rounds, one cold 16,384-token prefill each. `perf/memory-ab/summary.txt` lists the load line, the GPU peak over idle +and the RSS peak (bytes) and the TTFT of each run. Round 1: + +| Setting | Load line, device | GPU peak over idle (GiB) | RSS peak (GiB) | 16K TTFT (s) | +| --- | ---: | ---: | ---: | ---: | +| `new` defaults (`prefill_step=4096`, resident n-gram rows) | 81.82 GiB | 82.73 | 104.4 | 30.74 | +| `new --policy prefill_step=20480` | 105.63 GiB | 106.5 | 104.5 | 29.69 | +| `new --policy prefill_step=1024` | 77.36 GiB | 78.27 | 102.6 | 33.90 | +| `new --policy rows=mapped`, rows not in the page cache | 81.82 GiB | 82.73 | 78.57 | 46.30 | +| `new --policy rows=mapped`, rows in the page cache | 81.82 GiB | 82.73 | 78.62 | 30.92 | +| `new --policy prefill_step=1024,rows=mapped` | 77.36 GiB | 78.27 | 78.62 | 34.13 | +| `base` | 76.58 GiB | 78.50 | 78.54 | 46.47 | + +The prompt chunk sets the GPU memory; the resident copy of the 29.80 GiB of n-gram tables sets the RSS. +The first `rows=mapped` run follows a run whose copy at load dropped the rows from the page cache; the second follows it. + +- Process: peak resident set of the server. Device: `mem_info_gtt_used` + `mem_info_vram_used` of the card, sampled at + 1 Hz, as the peak over the idle value read before the server started. The two overlap on unified memory: do not add them. +- Each server run has a summary in `perf/runs/*.json` with its load line, and its samples in `perf/memory/`. + +## Build, test and kernel contract ([checks/](checks/)) + +On `new`: + +- `contract.log`: `SUMMARY gfx1151 83 kernels: 83 pass gates 1-4, 0 fail, 4 known findings; 5 controls: 5 red as + planted, 0 missed; 0 limit problems`. +- `limits.log`: `PASS kernel-contract-limits: every registered launch fits gfx1030, gfx1100, gfx1151 and gfx1201, + every record current, every control red`. +- `test-hip.log` (`zig build test -Dhip=true`), `hip-kernel-test.log`, `test-cuda-host.log`: exit 0. + Zig prints a passing test's stderr under a `failed command:` line. +- `perf/hash-new.log` and `perf/hash-base.log`: `tf-flashnext-hip-test generate --chat --max 64 --hash`, logits hash + `243ecea88fe50d9f` on `new` and on `base`. + +`per-commit.tsv`: each of the 33 code commits, built and tested alone on an earlier `main` (`abf822585`): +`zig build native-hip tf-flashnext-hip-test`, `zig build test -Dhip=true`, `zig build hip-kernel-test`, then +`tf-flashnext-hip-test generate --chat --max 64 --hash`. Every exit code is 0 and every hash is `243ecea88fe50d9f`. +The table names the tested commit and the commit in this pull request. Their added and removed lines are the same, +with two exceptions: commits 19-33 ran before their gate-5 records were refreshed (`hip_records_*.zig` only), and +commit 5 ran with a 20,480-row default chunk, which this pull request sets to 4,096 rows. + +## Not run + +- Metal and CUDA device tests (no such hardware). HIP devices other than gfx1151: only the limits check. +- Sampled (temperature above 0) decode speed. Multi-GPU. Other checkpoints. +- No standard-server comparison: `mlx_lm` needs Metal. + +## Publication + +Each subfolder is a sanitized copy. Machine-local paths, the host name and the user name are replaced with +placeholders (`publication.json` counts the replacements per file). Request and reply values, token ids, token hashes +and telemetry are unchanged. No model weights or credentials are included. `SHA256SUMS` lists every file but itself. diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/SHA256SUMS b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/SHA256SUMS new file mode 100644 index 0000000000..600ba4fba5 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/SHA256SUMS @@ -0,0 +1,431 @@ +e47453f10418ed1e9a041c667baaf5b1fc9a2447dbb73ab62d9b7407b024ac83 README.md +7b992e60c62d672705deb6d0b49991643a18e59ca968e4fabef409c1d580675f checks/contract.log +7a51a52842949d986688172c6468ac9793966ed1409aaf0bb0c0ee2eb45f8a7f checks/hip-kernel-test.log +c407acfa1446fb90d0a8453343f842fbea20a24ac7e9e189f6fa2134c2a0a836 checks/limits.log +1da38be16d330686363ea8ee43c26e8021642b49c2f1a746b779cd93f6c99dfd checks/per-commit.tsv +9cc88349f54439a9062fb6bb97c9f81970b187d944a12cc98d498241989d75f6 checks/test-cuda-host.log +6e972545afa2ee513867d9af493543fe3281073f6a8cbc70d1f64cb632287019 checks/test-hip.log +406addc1e2b97f2608d3214052013337f1d38742058b6aa63d4712b040bb0fdd exactness/checkpoint.json +1390bd0210840927151b3d2309a42ce3c0884dce3be609cdf7b82a196c2cd0a5 exactness/environment.json +e39805354f4ab77cd16cbc0b95b8cd1e4f6d4786645ac99587057aca3391433c exactness/exactness/exact-rewind-nocache.json +d0071b802ef1d18d930b4553319c02758288bdb23e58cda2adccc2e47cf91942 exactness/exactness/exact-rewind-nocache.jsonl +5cd41a8c9f266125b5b5852ecfafa51361adaeede2c4e37cfba2dffd3f8e5be2 exactness/exactness/exact-rewind.json +11c6e787d8211652d312dc395ae805456d2fa4b2388b8f40008fbead318ad292 exactness/exactness/exact-rewind.jsonl +69a747670b8fc32ee72912de45fb62aa050005bc992e815780bac19ff94bc512 exactness/exactness/exact-serve-cancel.jsonl +4b2dc4753d9d13fbc4c87fab47cee753060705e67771bfc2961a946d57c06462 exactness/exactness/exact-serve-check.jsonl +e04eb7b415dd6768725d4a4541e89fa3633497b4a01423dc64bef3e918b72ed1 exactness/exactness/seam-corpus.json +2edb979e26829f7d4fea3bf00e2cbc968b842b19594c77a1477cf6459ec3248d exactness/logs/generate-exact-chunk2048.log +db576f58e0066a4b01e509f7f2544587a8a3b1bbaccad6c4c601dc4fc9cec619 exactness/logs/generate-exact-chunk20480.log +a088e2efc593403601ae3f4045e225232384726218022aba4e7293d37f9ab6ca exactness/logs/generate-exact-chunk512.log +55253f2644b06f4619b028078cddc9829bf8169f47eedcffdbb473083da87204 exactness/logs/generate-exact-chunk8192.log +e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855 exactness/logs/rewind-exact-nocache.log +d60b5348172a2e68f86404e88512a4fa00458b81232818a9d4081335d56fbcda exactness/logs/rewind-exact.log +23a5107d2fec0a44295a833dfb035b8f4e8e0de80ff5ffd4539325dc4c9171dc exactness/logs/serve-cancel-exact.log +d2321334bb8cdbb15dbc10dbbcbc4f6ad66ca3c08e101960b847a90dc5055c59 exactness/logs/serve-check-exact.log +e43be960ab14f51db80f085ebad59ee128968d56cac8505cc461fb93e4b39a06 exactness/logs/server-ex-exact-nocache.log +4e302e980bc7e77e76144c122c9ecc50f51d7ec66f92e56bdb567b66a91cf6b0 exactness/logs/server-ex-exact.log +8ed03a04f58b1eb54a504d0ee7bc42e30b29b3cf677c718198d3324f70e3c8fa exactness/memory/ex-exact-memory-endpoint.json +0ac2e66c1ffd2516599954baa19489a55c171f8a11fbbd18f4982f26cc16690f exactness/memory/ex-exact-metrics.txt +2f20c2c32c01a53bc9f808b4df8bf0bea32e9f581e53fedee32af28a1eb25e89 exactness/memory/ex-exact-nocache-memory-endpoint.json +8644816e0b879e7900a176f4b0c9e037d1679e66450eb270ffbbc46af85ceac2 exactness/memory/ex-exact-nocache-metrics.txt +e4adb34458d522ab03de35e6f93afe06903dc1b4b6ec8c6c90d76397ec431120 exactness/memory/ex-exact-nocache-samples.jsonl +ad2ab2f1b00469808f1cab165a7dcc77affa5ffe9770e4c7613d2bd6c07b6a9a exactness/memory/ex-exact-samples.jsonl +50e6a7b100f5a3b0abca83fef77d74b8279628206479882ec383d04cf41938db exactness/provenance.json +a2bc03de008f30e4f33ab99b4729d4196500cdb5a6ddfadfaea6c6cbebeee5ba exactness/publication.json 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nonfinite hip RMS norm tf_rms_rows (fp32): 260 non-finite and 1788 finite outputs match the float64 classes +PASS repeat hip RMS norm tf_rms_rows (fp32): five runs byte-identical (32768 bytes), inputs and guards untouched, no overlap +PASS shapes hip RMS norm tf_rms_rows (fp32): 12 shapes within the float64 bound (worst 0.245 of the bound), 0 edges refused by the kernel +PASS sums hip RMS norm tf_rms_rows (fp32): exact sums at k 1024, where fp16 sums would miss by 1864135x and bf16 by 2922x +PASS nonfinite hip RMS norm tf_rms_rows (fp16): 260 non-finite and 1788 finite outputs match the float64 classes +PASS repeat hip RMS norm tf_rms_rows (fp16): five runs byte-identical (16384 bytes), inputs and guards untouched, no overlap +PASS shapes hip RMS norm tf_rms_rows (fp16): 12 shapes within the float64 bound (worst 0.993 of the bound), 0 edges refused by the kernel +PASS sums hip RMS norm tf_rms_rows (fp16): within its bound at k 1024; fp16 sums would miss 2046x, bf16 0.2x (a 16-bit output follows the sum of squares as ss^-1/2: a bf16 sum's error is a few output ulps (the fp32-out form proves fp32 sums)) +PASS nonfinite hip RMS norm tf_rms_rows (bf16): 260 non-finite and 1788 finite outputs match the float64 classes +PASS repeat hip RMS norm tf_rms_rows (bf16): five runs byte-identical (16384 bytes), inputs and guards untouched, no overlap +PASS shapes hip RMS norm tf_rms_rows (bf16): 12 shapes within the float64 bound (worst 0.996 of the bound), 0 edges refused by the kernel +PASS sums hip RMS norm tf_rms_rows (bf16): within its bound at k 1024; fp16 sums would miss 256x, bf16 0.1x (a 16-bit output follows the sum of squares as ss^-1/2: a bf16 sum's error is a few output ulps (the fp32-out form proves fp32 sums)) +PASS nonfinite hip RMS norm rms_kernel<__half>: 2052 non-finite and 14332 finite outputs match the float64 classes +PASS repeat hip RMS norm rms_kernel<__half>: five runs byte-identical (69632 bytes), inputs and guards untouched, no overlap +PASS shapes hip RMS norm rms_kernel<__half>: 9 shapes within the float64 bound (worst 0.987 of the bound), 0 edges refused by the kernel +PASS sums hip RMS norm rms_kernel<__half>: within its bound at k 8192; fp16 sums would miss 2046x, bf16 3.1x (a 16-bit output follows the sum of squares as ss^-1/2: a bf16 sum's error is a few output ulps (the fp32-out form proves fp32 sums)) +PASS nonfinite hip RMS norm rms_kernel: 2052 non-finite and 14332 finite outputs match the float64 classes +PASS repeat hip RMS norm rms_kernel: five runs byte-identical (69632 bytes), inputs and guards untouched, no overlap +PASS shapes hip RMS norm rms_kernel: 9 shapes within the float64 bound (worst 0.993 of the bound), 0 edges refused by the kernel +PASS sums hip RMS norm rms_kernel: within its bound at k 8192; fp16 sums would miss 256x, bf16 0.2x (a 16-bit output follows the sum of squares as ss^-1/2: a bf16 sum's error is a few output ulps (the fp32-out form proves fp32 sums)) +FAIL nonfinite control: fmax row max: 1 of 8 outputs differ in class; first at 0: finite where float64 gives nan +CONTROL control: fmax row max: red at nonfinite, as planted +FAIL repeat control: atomic-add row sum: 4 of 4 repeats differ from the first run's bytes, first at byte 0 +CONTROL control: atomic-add row sum: red at repeat, as planted +FAIL repeat control: row sum writing its input: 4 of 4 repeats differ from the first run's bytes, first at byte 0 +CONTROL control: row sum writing its input: red at repeat, as planted +FAIL shapes control: row sum losing a tail input: at 8x1x1 output 0 is 0.000000e0 where float64 gives -3.203125e-1: 2396744.29 of its bound +CONTROL control: row sum losing a tail input: red at shapes, as planted +FAIL sums control: dot summed in half: 29826161.8x over its exact-sum bound at k 4096: not fp32 sums (fp16 would miss 29826162x, bf16 16777216x) +CONTROL control: dot summed in half: red at sums, as planted +PASS nonfinite hip mamba tf_mamba_conv (bf16): 11 non-finite and 49141 finite outputs match the float64 classes +PASS repeat hip mamba tf_mamba_conv (bf16): five runs byte-identical (49152 bytes), inputs and guards untouched, no overlap +PASS shapes hip mamba tf_mamba_conv (bf16): 7 shapes within the float64 bound (worst 0.536 of the bound), 0 edges refused by the kernel +PASS sums hip mamba tf_mamba_conv (bf16): within its bound at k 5; fp16 sums would miss infx, bf16 63.8x (five terms through silu, which squashes a sum's error below zero: the fp16 margin proves fp32 sums) +PASS nonfinite hip mamba tf_mamba_dt (bf16 in): 2 non-finite and 318 finite outputs match the float64 classes +PASS repeat hip mamba tf_mamba_dt (bf16 in): five runs byte-identical (256 bytes), inputs and guards untouched, no overlap +PASS shapes hip mamba tf_mamba_dt (bf16 in): 7 shapes within the float64 bound (worst 0.323 of the bound), 0 edges refused by the kernel +N/A sums hip mamba tf_mamba_dt (bf16 in): declares none sums +PASS nonfinite hip mamba tf_mamba_gnorm (bf16): 516 non-finite and 19964 finite outputs match the float64 classes +PASS repeat hip mamba tf_mamba_gnorm (bf16): five runs byte-identical (8192 bytes), inputs and guards untouched, no overlap +PASS shapes hip mamba tf_mamba_gnorm (bf16): 8 shapes within the float64 bound (worst 0.938 of the bound), 0 edges refused by the kernel +PASS sums hip mamba tf_mamba_gnorm (bf16): within its bound at k 1024; fp16 sums would miss 128x, bf16 0.2x (a 16-bit output follows the sum of squares as ss^-1/2: a bf16 sum's error is a few output ulps) +PASS nonfinite hip mamba tf_mamba_scan (y, bf16): 203 non-finite and 10037 finite outputs match the float64 classes +PASS repeat hip mamba tf_mamba_scan (y, bf16): five runs byte-identical (16384 bytes), inputs and guards untouched, no overlap +PASS shapes hip mamba tf_mamba_scan (y, bf16): 8 shapes within the float64 bound (worst 0.869 of the bound), 0 edges refused by the kernel +PASS sums hip mamba tf_mamba_scan (y, bf16): exact sums at k 128, where fp16 sums would miss by infx and bf16 by 2066x +PASS nonfinite hip mamba tf_mamba_scan (the state): 8321 non-finite and 253823 finite outputs match the float64 classes +PASS repeat hip mamba tf_mamba_scan (the state): five runs byte-identical (1048576 bytes), inputs and guards untouched, no overlap +PASS shapes hip mamba tf_mamba_scan (the state): 8 shapes within the float64 bound (worst 0.071 of the bound), 0 edges refused by the kernel +PASS sums hip mamba tf_mamba_scan (the state): exact sums at k 128, where fp16 sums would miss by 1438047x and bf16 by 13901122x +PASS nonfinite hip nemotron tf_nemo_select (a pick at a time): the stated rule holds: the top-k of sigmoid(logit) + bias, a NaN never ahead of a number, ties to the lower expert; weights within (k + 8) fp32 ulps of float64 +PASS repeat hip nemotron tf_nemo_select (a pick at a time): five runs byte-identical (560 bytes), inputs and guards untouched, no overlap +PASS shapes hip nemotron tf_nemo_select (a pick at a time): 7 shapes exact by its own check (worst 0.000 of the bound), 0 edges refused by the kernel +N/A sums hip nemotron tf_nemo_select (a pick at a time): declares none sums +PASS nonfinite hip nemotron tf_nemo_select_rank: the stated rule holds: the top-k of sigmoid(logit) + bias, a NaN never ahead of a number, ties to the lower expert; weights within (k + 8) fp32 ulps of float64 +PASS repeat hip nemotron tf_nemo_select_rank: five runs byte-identical (560 bytes), inputs and guards untouched, no overlap +PASS shapes hip nemotron tf_nemo_select_rank: 7 shapes bit-equal to the kernel it replaces (worst 0.000 of the bound), 0 edges refused by the kernel +N/A sums hip nemotron tf_nemo_select_rank: declares none sums +PASS nonfinite hip nemotron tf_nemo_localize: the stated rule holds: pick - first for the rank's own experts, else own +PASS repeat hip nemotron tf_nemo_localize: five runs byte-identical (24 bytes), inputs and guards untouched, no overlap +PASS shapes hip nemotron tf_nemo_localize: 7 shapes exact by its own check (worst 0.000 of the bound), 0 edges refused by the kernel +N/A sums hip nemotron tf_nemo_localize: declares none sums +PASS nonfinite hip nemotron tf_nemo_relu2 (bf16): 2 non-finite and 11134 finite outputs match the float64 classes +PASS repeat hip nemotron tf_nemo_relu2 (bf16): five runs byte-identical (22272 bytes), inputs and guards untouched, no overlap +PASS shapes hip nemotron tf_nemo_relu2 (bf16): 8 shapes within the float64 bound (worst 0.913 of the bound), 0 edges refused by the kernel +N/A sums hip nemotron tf_nemo_relu2 (bf16): declares none sums +PASS nonfinite hip nemotron tf_nemo_combine (bf16): 4 non-finite and 13436 finite outputs match the float64 classes +PASS repeat hip nemotron tf_nemo_combine (bf16): five runs byte-identical (5376 bytes), inputs and guards untouched, no overlap +PASS shapes hip nemotron tf_nemo_combine (bf16): 7 shapes within the float64 bound (worst 0.996 of the bound), 0 edges refused by the kernel +PASS sums hip nemotron tf_nemo_combine (bf16): exact sums at k 6, where fp16 sums would miss by infx and bf16 by 4987x +PASS nonfinite hip nemotron tf_nemo_combine (fp32): 4 non-finite and 13436 finite outputs match the float64 classes +PASS repeat hip nemotron tf_nemo_combine (fp32): five runs byte-identical (10752 bytes), inputs and guards untouched, no overlap +PASS shapes hip nemotron tf_nemo_combine (fp32): 7 shapes within the float64 bound (worst 0.253 of the bound), 0 edges refused by the kernel +PASS sums hip nemotron tf_nemo_combine (fp32): exact sums at k 6, where fp16 sums would miss by infx and bf16 by 326820168x +PASS nonfinite hip planned decode walk planCausal (bf16 cache): 5541 non-finite and 14939 finite outputs match the float64 classes +PASS repeat hip planned decode walk planCausal (bf16 cache): five runs byte-identical (16384 bytes), inputs and guards untouched, no overlap +PASS shapes hip planned decode walk planCausal (bf16 cache): 8 shapes within the float64 bound (worst 0.002 of the bound), 0 edges refused by the kernel +PASS sums hip planned decode walk planCausal (bf16 cache): exact sums at k 65536, where fp16 sums would miss by 2130706432x and bf16 by 16777216x +PASS nonfinite hip planned decode walk planCausalAs (q and rows bf16): 4525 non-finite and 15955 finite outputs match the float64 classes +PASS repeat hip planned decode walk planCausalAs (q and rows bf16): five runs byte-identical (8192 bytes), inputs and guards untouched, no overlap +PASS shapes hip planned decode walk planCausalAs (q and rows bf16): 8 shapes bit-equal to the kernel it replaces (worst 0.000 of the bound), 0 edges refused by the kernel +PASS sums hip planned decode walk planCausalAs (q and rows bf16): exact sums at k 65536, where fp16 sums would miss by 256x and bf16 by 256x +PASS nonfinite hip tf_plan_attend_bf16 (q and rows fp32): 4652 non-finite and 15828 finite outputs match the float64 classes +PASS repeat hip tf_plan_attend_bf16 (q and rows fp32): five runs byte-identical (16384 bytes), inputs and guards untouched, no overlap +PASS shapes hip tf_plan_attend_bf16 (q and rows fp32): 7 shapes bit-equal to the kernel it replaces (worst 0.000 of the bound), 0 edges refused by the kernel +PASS sums hip tf_plan_attend_bf16 (q and rows fp32): exact sums at k 4096, where fp16 sums would miss by 65011712x and bf16 by 780140544x +PASS nonfinite hip tf_plan_attend_bf16 (q and rows bf16): 5668 non-finite and 14812 finite outputs match the float64 classes +PASS repeat hip tf_plan_attend_bf16 (q and rows bf16): five runs byte-identical (8192 bytes), inputs and guards untouched, no overlap +PASS shapes hip tf_plan_attend_bf16 (q and rows bf16): 7 shapes bit-equal to the kernel it replaces (worst 0.000 of the bound), 0 edges refused by the kernel +PASS sums hip tf_plan_attend_bf16 (q and rows bf16): exact sums at k 4096, where fp16 sums would miss by 768x and bf16 by 9472x +PASS nonfinite hip tf_add_rms_bf16 (y bf16): 2695 non-finite and 24185 finite outputs match the float64 classes +PASS repeat hip tf_add_rms_bf16 (y bf16): five runs byte-identical (10752 bytes), inputs and guards untouched, no overlap +PASS shapes hip tf_add_rms_bf16 (y bf16): 8 shapes bit-equal to the kernel it replaces (worst 0.000 of the bound), 0 edges refused by the kernel +PASS sums hip tf_add_rms_bf16 (y bf16): within its bound at k 8192; fp16 sums would miss 85x, bf16 0.1x (a 16-bit output follows the sum of squares as ss^-1/2: a bf16 sum's error is a few output ulps; fp16's overflowing sums give 0, which the bound's residual roundings put at 51x) +PASS nonfinite hip tf_add_rms_bf16 (y fp32): 2695 non-finite and 24185 finite outputs match the float64 classes +PASS repeat hip tf_add_rms_bf16 (y fp32): five runs byte-identical (10752 bytes), inputs and guards untouched, no overlap +PASS shapes hip tf_add_rms_bf16 (y fp32): 8 shapes bit-equal to the kernel it replaces (worst 0.000 of the bound), 0 edges refused by the kernel +PASS sums hip tf_add_rms_bf16 (y fp32): within its bound at k 8192; fp16 sums would miss 85x, bf16 0.2x (a 16-bit output follows the sum of squares as ss^-1/2: a bf16 sum's error is a few output ulps; fp16's overflowing sums give 0, which the bound's residual roundings put at 51x) +PASS nonfinite hip tf_add_rms_bf16 (the MoE rows): 2693 non-finite and 24187 finite outputs match the float64 classes +PASS repeat hip tf_add_rms_bf16 (the MoE rows): five runs byte-identical (10752 bytes), inputs and guards untouched, no overlap +PASS shapes hip tf_add_rms_bf16 (the MoE rows): 8 shapes bit-equal to the kernel it replaces (worst 0.000 of the bound), 0 edges refused by the kernel +PASS sums hip tf_add_rms_bf16 (the MoE rows): within its bound at k 8192; fp16 sums would miss 51x, bf16 0.1x (a 16-bit output follows the sum of squares as ss^-1/2: a bf16 sum's error is a few output ulps; fp16's overflowing sums give 0, which the bound's residual roundings put at 51x) +PASS nonfinite hip mamba tf_mamba_conv_window (xc and tails, bf16): 17 non-finite and 122863 finite outputs match the float64 classes +PASS repeat hip mamba tf_mamba_conv_window (xc and tails, bf16): five runs byte-identical (98304 bytes), inputs and guards untouched, no overlap +PASS shapes hip mamba tf_mamba_conv_window (xc and tails, bf16): 7 shapes bit-equal to the kernel it replaces (worst 0.000 of the bound), 0 edges refused by the kernel +PASS sums hip mamba tf_mamba_conv_window (xc and tails, bf16): within its bound at k 5; fp16 sums would miss infx, bf16 63.8x (five terms through silu, which squashes a sum's error below zero: the fp16 margin proves fp32 sums) +PASS nonfinite hip mamba tf_mamba_conv_window (dt, bf16 in): 2 non-finite and 318 finite outputs match the float64 classes +PASS repeat hip mamba tf_mamba_conv_window (dt, bf16 in): five runs byte-identical (512 bytes), inputs and guards untouched, no overlap +PASS shapes hip mamba tf_mamba_conv_window (dt, bf16 in): 8 shapes bit-equal to the kernel it replaces (worst 0.000 of the bound), 0 edges refused by the kernel +N/A sums hip mamba tf_mamba_conv_window (dt, bf16 in): declares none sums +PASS nonfinite hip mamba tf_mamba_scan_snap (y, bf16): 203 non-finite and 20277 finite outputs match the float64 classes +PASS repeat hip mamba tf_mamba_scan_snap (y, bf16): five runs byte-identical (16384 bytes), inputs and guards untouched, no overlap +PASS shapes hip mamba tf_mamba_scan_snap (y, bf16): 7 shapes bit-equal to the kernel it replaces (worst 0.000 of the bound), 0 edges refused by the kernel +PASS sums hip mamba tf_mamba_scan_snap (y, bf16): exact sums at k 128, where fp16 sums would miss by infx and bf16 by 1931x +PASS nonfinite hip mamba tf_mamba_scan_snap (the state and its slots): 25221 non-finite and 2596219 finite outputs match the float64 classes +PASS repeat hip mamba tf_mamba_scan_snap (the state and its slots): five runs byte-identical (4194304 bytes), inputs and guards untouched, no overlap +PASS shapes hip mamba tf_mamba_scan_snap (the state and its slots): 7 shapes bit-equal to the kernel it replaces (worst 0.000 of the bound), 0 edges refused by the kernel +PASS sums hip mamba tf_mamba_scan_snap (the state and its slots): exact sums at k 128, where fp16 sums would miss by 15933x and bf16 by 126144x +PASS nonfinite hip affine_dot2_stream (2-bit, group 32, fp32 out): 131 non-finite and 29 finite outputs match the float64 classes +PASS repeat hip affine_dot2_stream (2-bit, group 32, fp32 out): five runs byte-identical (128 bytes), inputs and guards untouched, no overlap +PASS shapes hip affine_dot2_stream (2-bit, group 32, fp32 out): 13 shapes within the float64 bound (worst 0.032 of the bound), 0 edges refused by the kernel +PASS sums hip affine_dot2_stream (2-bit, group 32, fp32 out): exact sums at k 2048, where fp16 sums would miss by 83886080x and bf16 by 1996488704x +PASS nonfinite hip affine_dot2_stream (2-bit, group 64, fp32 out): 131 non-finite and 29 finite outputs match the float64 classes +PASS repeat hip affine_dot2_stream (2-bit, group 64, fp32 out): five runs byte-identical (128 bytes), inputs and guards untouched, no overlap +PASS shapes hip affine_dot2_stream (2-bit, group 64, fp32 out): 13 shapes within the float64 bound (worst 0.003 of the bound), 0 edges refused by the kernel +PASS sums hip affine_dot2_stream (2-bit, group 64, fp32 out): exact sums at k 2048, where fp16 sums would miss by 83886080x and bf16 by 1862270976x +PASS nonfinite hip affine_dot2_stream (2-bit, group 128, fp32 out): 131 non-finite and 29 finite outputs match the float64 classes +PASS repeat hip affine_dot2_stream (2-bit, group 128, fp32 out): five runs byte-identical (128 bytes), inputs and guards untouched, no overlap +PASS shapes hip affine_dot2_stream (2-bit, group 128, fp32 out): 13 shapes within the float64 bound (worst 0.002 of the bound), 0 edges refused by the kernel +PASS sums hip affine_dot2_stream (2-bit, group 128, fp32 out): exact sums at k 2048, where fp16 sums would miss by 83886080x and bf16 by 1996488704x +PASS nonfinite hip affine_dot2_stream (3-bit, group 32, fp32 out): 131 non-finite and 29 finite outputs match the float64 classes +PASS repeat hip affine_dot2_stream (3-bit, group 32, fp32 out): five runs byte-identical (128 bytes), inputs and guards untouched, no overlap +PASS shapes hip affine_dot2_stream (3-bit, group 32, fp32 out): 9 shapes within the float64 bound (worst 0.004 of the bound), 0 edges refused by the kernel +PASS sums hip affine_dot2_stream (3-bit, group 32, fp32 out): exact sums at k 512, where fp16 sums would miss by 13048946x and bf16 by 134217728x +PASS nonfinite hip affine_dot2_stream (3-bit, group 64, fp32 out): 131 non-finite and 29 finite outputs match the float64 classes +PASS repeat hip affine_dot2_stream (3-bit, group 64, fp32 out): five runs byte-identical (128 bytes), inputs and guards untouched, no overlap +PASS shapes hip affine_dot2_stream (3-bit, group 64, fp32 out): 9 shapes within the float64 bound (worst 0.008 of the bound), 0 edges refused by the kernel +PASS sums hip affine_dot2_stream (3-bit, group 64, fp32 out): exact sums at k 512, where fp16 sums would miss by 24403223x and bf16 by 123893287x +PASS nonfinite hip affine_dot2_stream (3-bit, group 128, fp32 out): 131 non-finite and 29 finite outputs match the float64 classes +PASS repeat hip affine_dot2_stream (3-bit, group 128, fp32 out): five runs byte-identical (128 bytes), inputs and guards untouched, no overlap +PASS shapes hip affine_dot2_stream (3-bit, group 128, fp32 out): 9 shapes within the float64 bound (worst 0.002 of the bound), 0 edges refused by the kernel +PASS sums hip affine_dot2_stream (3-bit, group 128, fp32 out): exact sums at k 512, where fp16 sums would miss by 13421773x and bf16 by 148757982x +PASS nonfinite hip affine_dot2_stream (4-bit, group 32, fp32 out): 131 non-finite and 29 finite outputs match the float64 classes +PASS repeat hip affine_dot2_stream (4-bit, group 32, fp32 out): five runs byte-identical (128 bytes), inputs and guards untouched, no overlap +PASS shapes hip affine_dot2_stream (4-bit, group 32, fp32 out): 9 shapes within the float64 bound (worst 0.007 of the bound), 0 edges refused by the kernel +PASS sums hip affine_dot2_stream (4-bit, group 32, fp32 out): exact sums at k 512, where fp16 sums would miss by 19173961x and bf16 by 128432481x +PASS nonfinite hip affine_dot2_stream (4-bit, group 64, fp32 out): 7427 non-finite and 1853 finite outputs match the float64 classes +PASS repeat hip affine_dot2_stream (4-bit, group 64, fp32 out): five runs byte-identical (7424 bytes), inputs and guards untouched, no overlap +PASS shapes hip affine_dot2_stream (4-bit, group 64, fp32 out): 12 shapes within the float64 bound (worst 0.012 of the bound), 0 edges refused by the kernel +PASS sums hip affine_dot2_stream (4-bit, group 64, fp32 out): exact sums at k 2688, where fp16 sums would miss by 344374434x and bf16 by 1892097138x +PASS nonfinite hip affine_dot2_stream (4-bit, group 128, fp32 out): 131 non-finite and 29 finite outputs match the float64 classes +PASS repeat hip affine_dot2_stream (4-bit, group 128, fp32 out): five runs byte-identical (128 bytes), inputs and guards untouched, no overlap +PASS shapes hip affine_dot2_stream (4-bit, group 128, fp32 out): 9 shapes within the float64 bound (worst 0.004 of the bound), 0 edges refused by the kernel +PASS sums hip affine_dot2_stream (4-bit, group 128, fp32 out): exact sums at k 512, where fp16 sums would miss by 22730422x and bf16 by 150265500x +PASS nonfinite hip affine_dot2_stream (5-bit, group 32, fp32 out): 131 non-finite and 29 finite outputs match the float64 classes +PASS repeat hip affine_dot2_stream (5-bit, group 32, fp32 out): five runs byte-identical (128 bytes), inputs and guards untouched, no overlap +PASS shapes hip affine_dot2_stream (5-bit, group 32, fp32 out): 9 shapes within the float64 bound (worst 0.007 of the bound), 0 edges refused by the kernel +PASS sums hip affine_dot2_stream (5-bit, group 32, fp32 out): exact sums at k 512, where fp16 sums would miss by 20771791x and bf16 by 16777216x +PASS nonfinite hip affine_dot2_stream (5-bit, group 64, fp32 out): 131 non-finite and 29 finite outputs match the float64 classes +PASS repeat hip affine_dot2_stream (5-bit, group 64, fp32 out): five runs byte-identical (128 bytes), inputs and guards untouched, no overlap +PASS shapes hip affine_dot2_stream (5-bit, group 64, fp32 out): 9 shapes within the float64 bound (worst 0.006 of the bound), 0 edges refused by the kernel +PASS sums hip affine_dot2_stream (5-bit, group 64, fp32 out): exact sums at k 512, where fp16 sums would miss by 18454938x and bf16 by 98104060x +PASS nonfinite hip affine_dot2_stream (5-bit, group 128, fp32 out): 131 non-finite and 29 finite outputs match the float64 classes +PASS repeat hip affine_dot2_stream (5-bit, group 128, fp32 out): five runs byte-identical (128 bytes), inputs and guards untouched, no overlap +PASS shapes hip affine_dot2_stream (5-bit, group 128, fp32 out): 9 shapes within the float64 bound (worst 0.002 of the bound), 0 edges refused by the kernel +PASS sums hip affine_dot2_stream (5-bit, group 128, fp32 out): exact sums at k 512, where fp16 sums would miss by 21996794x and bf16 by 181753173x +PASS nonfinite hip affine_dot2_stream (6-bit, group 32, fp32 out): 131 non-finite and 29 finite outputs match the float64 classes +PASS repeat hip affine_dot2_stream (6-bit, group 32, fp32 out): five runs byte-identical (128 bytes), inputs and guards untouched, no overlap +PASS shapes hip affine_dot2_stream (6-bit, group 32, fp32 out): 9 shapes within the float64 bound (worst 0.020 of the bound), 0 edges refused by the kernel +PASS sums hip affine_dot2_stream (6-bit, group 32, fp32 out): exact sums at k 512, where fp16 sums would miss by 23216955x and bf16 by 152422792x +PASS nonfinite hip affine_dot2_stream (6-bit, group 64, fp32 out): 131 non-finite and 29 finite outputs match the float64 classes +PASS repeat hip affine_dot2_stream (6-bit, group 64, fp32 out): five runs byte-identical (128 bytes), inputs and guards untouched, no overlap +PASS shapes hip affine_dot2_stream (6-bit, group 64, fp32 out): 9 shapes within the float64 bound (worst 0.006 of the bound), 0 edges refused by the kernel +PASS sums hip affine_dot2_stream (6-bit, group 64, fp32 out): exact sums at k 512, where fp16 sums would miss by 24254019x and bf16 by 168799336x +PASS nonfinite hip affine_dot2_stream (6-bit, group 128, fp32 out): 131 non-finite and 29 finite outputs match the float64 classes +PASS repeat hip affine_dot2_stream (6-bit, group 128, fp32 out): five runs byte-identical (128 bytes), inputs and guards untouched, no overlap +PASS shapes hip affine_dot2_stream (6-bit, group 128, fp32 out): 9 shapes within the float64 bound (worst 0.002 of the bound), 0 edges refused by the kernel +PASS sums hip affine_dot2_stream (6-bit, group 128, fp32 out): exact sums at k 512, where fp16 sums would miss by 30482547x and bf16 by 16777216x +PASS nonfinite hip affine_dot2_stream (8-bit, group 32, fp32 out): 131 non-finite and 29 finite outputs match the float64 classes +PASS repeat hip affine_dot2_stream (8-bit, group 32, fp32 out): five runs byte-identical (128 bytes), inputs and guards untouched, no overlap +PASS shapes hip affine_dot2_stream (8-bit, group 32, fp32 out): 9 shapes within the float64 bound (worst 0.026 of the bound), 0 edges refused by the kernel +PASS sums hip affine_dot2_stream (8-bit, group 32, fp32 out): exact sums at k 512, where fp16 sums would miss by infx and bf16 by 16777216x +PASS nonfinite hip affine_dot2_stream (8-bit, group 64, fp32 out): 131 non-finite and 29 finite outputs match the float64 classes +PASS repeat hip affine_dot2_stream (8-bit, group 64, fp32 out): five runs byte-identical (128 bytes), inputs and guards untouched, no overlap +PASS shapes hip affine_dot2_stream (8-bit, group 64, fp32 out): 9 shapes within the float64 bound (worst 0.007 of the bound), 0 edges refused by the kernel +PASS sums hip affine_dot2_stream (8-bit, group 64, fp32 out): exact sums at k 512, where fp16 sums would miss by infx and bf16 by 77266498x +PASS nonfinite hip affine_dot2_stream (8-bit, group 128, fp32 out): 131 non-finite and 29 finite outputs match the float64 classes +PASS repeat hip affine_dot2_stream (8-bit, group 128, fp32 out): five runs byte-identical (128 bytes), inputs and guards untouched, no overlap +PASS shapes hip affine_dot2_stream (8-bit, group 128, fp32 out): 9 shapes within the float64 bound (worst 0.003 of the bound), 0 edges refused by the kernel +PASS sums hip affine_dot2_stream (8-bit, group 128, fp32 out): exact sums at k 512, where fp16 sums would miss by infx and bf16 by 59170376x +PASS nonfinite hip affine_dot2_stream_relu2 (4-bit, bf16): the stated rule holds: the unfused bytes and every float64 output class +PASS repeat hip affine_dot2_stream_relu2 (4-bit, bf16): five runs byte-identical (3712 bytes), inputs and guards untouched, no overlap +PASS shapes hip affine_dot2_stream_relu2 (4-bit, bf16): 3 shapes bit-equal to the kernel it replaces (worst 0.000 of the bound), 0 edges refused by the kernel +PASS sums hip affine_dot2_stream_relu2 (4-bit, bf16): exact sums at k 2688, where fp16 sums would miss by 85x and bf16 by 1235148x +PASS nonfinite hip tf_plan_kv_write_act (bf16): 128518 non-finite and 2554 finite outputs match the float64 classes +PASS repeat hip tf_plan_kv_write_act (bf16): five runs byte-identical (262144 bytes), inputs and guards untouched, no overlap +PASS shapes hip tf_plan_kv_write_act (bf16): 6 shapes bit-equal to the kernel it replaces (worst 0.000 of the bound), 0 edges refused by the kernel +N/A sums hip tf_plan_kv_write_act (bf16): declares none sums +PASS nonfinite hip tf_argmax_part and tf_argmax_join (bf16): the stated rule holds: torch's argmax order: a NaN ahead of every value, then the larger value, then the lower index +PASS repeat hip tf_argmax_part and tf_argmax_join (bf16): five runs byte-identical (4 bytes), inputs and guards untouched, no overlap +PASS shapes hip tf_argmax_part and tf_argmax_join (bf16): 7 shapes bit-equal to the kernel it replaces (worst 0.000 of the bound), 0 edges refused by the kernel +N/A sums hip tf_argmax_part and tf_argmax_join (bf16): declares none sums +PASS nonfinite hip affine_dot2_stream_relu2_pair (4-bit, bf16): the stated rule holds: the separate launches' bytes and every float64 output class +PASS repeat hip affine_dot2_stream_relu2_pair (4-bit, bf16): five runs byte-identical (29696 bytes), inputs and guards untouched, no overlap +PASS shapes hip affine_dot2_stream_relu2_pair (4-bit, bf16): 2 shapes bit-equal to the kernel it replaces (worst 0.000 of the bound), 0 edges refused by the kernel +PASS sums hip affine_dot2_stream_relu2_pair (4-bit, bf16): exact sums at k 2688, where fp16 sums would miss by 85x and bf16 by 1586504x +PASS nonfinite hip affine_wmma_dense<320> (4-bit, group 32, fp32 out): 40972 non-finite and 40948 finite outputs match the float64 classes +PASS repeat hip affine_wmma_dense<320> (4-bit, group 32, fp32 out): five runs byte-identical (2621440 bytes), inputs and guards untouched, no overlap +PASS shapes hip affine_wmma_dense<320> (4-bit, group 32, fp32 out): 7 shapes bit-equal to the kernel it replaces (worst 0.000 of the bound), 0 edges refused by the kernel +PASS sums hip affine_wmma_dense<320> (4-bit, group 32, fp32 out): exact sums at k 320, where fp16 sums would miss by 17576131x and bf16 by 125829120x +PASS nonfinite hip affine_wmma_dense<320> (4-bit, group 32, bf16 out): 40972 non-finite and 40948 finite outputs match the float64 classes +PASS repeat hip affine_wmma_dense<320> (4-bit, group 32, bf16 out): five runs byte-identical (1310720 bytes), inputs and guards untouched, no overlap +PASS shapes hip affine_wmma_dense<320> (4-bit, group 32, bf16 out): 7 shapes bit-equal to the kernel it replaces (worst 0.000 of the bound), 0 edges refused by the kernel +PASS sums hip affine_wmma_dense<320> (4-bit, group 32, bf16 out): exact sums at k 320, where fp16 sums would miss by 256x and bf16 by 1772x +PASS nonfinite hip affine_wmma_dense<2560> (4-bit, group 32, fp32 out): 2572 non-finite and 2548 finite outputs match the float64 classes +PASS repeat hip affine_wmma_dense<2560> (4-bit, group 32, fp32 out): five runs byte-identical (163840 bytes), inputs and guards untouched, no overlap +PASS shapes hip affine_wmma_dense<2560> (4-bit, group 32, fp32 out): 7 shapes bit-equal to the kernel it replaces (worst 0.000 of the bound), 0 edges refused by the kernel +PASS sums hip affine_wmma_dense<2560> (4-bit, group 32, fp32 out): exact sums at k 2560, where fp16 sums would miss by 418311919x and bf16 by 2065631170x +PASS nonfinite hip affine_wmma_dense<2560> (4-bit, group 32, bf16 out): 2572 non-finite and 2548 finite outputs match the float64 classes +PASS repeat hip affine_wmma_dense<2560> (4-bit, group 32, bf16 out): five runs byte-identical (81920 bytes), inputs and guards untouched, no overlap +PASS shapes hip affine_wmma_dense<2560> (4-bit, group 32, bf16 out): 7 shapes bit-equal to the kernel it replaces (worst 0.000 of the bound), 0 edges refused by the kernel +PASS sums hip affine_wmma_dense<2560> (4-bit, group 32, bf16 out): exact sums at k 2560, where fp16 sums would miss by 3950x and bf16 by 28416x +PASS nonfinite hip affine_wmma_dense<6144> (4-bit, group 32, fp32 out): 10252 non-finite and 10228 finite outputs match the float64 classes +PASS repeat hip affine_wmma_dense<6144> (4-bit, group 32, fp32 out): five runs byte-identical (655360 bytes), inputs and guards untouched, no overlap +PASS shapes hip affine_wmma_dense<6144> (4-bit, group 32, fp32 out): 7 shapes bit-equal to the kernel it replaces (worst 0.000 of the bound), 0 edges refused by the kernel +PASS sums hip affine_wmma_dense<6144> (4-bit, group 32, fp32 out): exact sums at k 6144, where fp16 sums would miss by 696899742x and bf16 by 4783480350x +PASS nonfinite hip affine_wmma_dense<6144> (4-bit, group 32, bf16 out): 10252 non-finite and 10228 finite outputs match the float64 classes +PASS repeat hip affine_wmma_dense<6144> (4-bit, group 32, bf16 out): five runs byte-identical (327680 bytes), inputs and guards untouched, no overlap +PASS shapes hip affine_wmma_dense<6144> (4-bit, group 32, bf16 out): 7 shapes bit-equal to the kernel it replaces (worst 0.000 of the bound), 0 edges refused by the kernel +PASS sums hip affine_wmma_dense<6144> (4-bit, group 32, bf16 out): exact sums at k 6144, where fp16 sums would miss by 10320x and bf16 by 77416x +PASS nonfinite hip affine_wmma_dense<10240> (4-bit, group 32, fp32 out): 1308 non-finite and 1284 finite outputs match the float64 classes +PASS repeat hip affine_wmma_dense<10240> (4-bit, group 32, fp32 out): five runs byte-identical (82944 bytes), inputs and guards untouched, no overlap +PASS shapes hip affine_wmma_dense<10240> (4-bit, group 32, fp32 out): 8 shapes bit-equal to the kernel it replaces (worst 0.000 of the bound), 0 edges refused by the kernel +PASS sums hip affine_wmma_dense<10240> (4-bit, group 32, fp32 out): exact sums at k 10240, where fp16 sums would miss by 429496730x and bf16 by 16777216x +PASS nonfinite hip affine_wmma_dense<10240> (4-bit, group 32, bf16 out): 1308 non-finite and 1284 finite outputs match the float64 classes +PASS repeat hip affine_wmma_dense<10240> (4-bit, group 32, bf16 out): five runs byte-identical (41472 bytes), inputs and guards untouched, no overlap +PASS shapes hip affine_wmma_dense<10240> (4-bit, group 32, bf16 out): 8 shapes bit-equal to the kernel it replaces (worst 0.000 of the bound), 0 edges refused by the kernel +PASS sums hip affine_wmma_dense<10240> (4-bit, group 32, bf16 out): exact sums at k 10240, where fp16 sums would miss by 6434x and bf16 by 47034x +PASS nonfinite hip affine_wmma_moe_gu<4> (Flash Next's expert gate and up, silu(g) u, bf16 out): 5120 non-finite and 5120 finite outputs match the float64 classes +PASS repeat hip affine_wmma_moe_gu<4> (Flash Next's expert gate and up, silu(g) u, bf16 out): five runs byte-identical (163840 bytes), inputs and guards untouched, no overlap +PASS shapes hip affine_wmma_moe_gu<4> (Flash Next's expert gate and up, silu(g) u, bf16 out): 5 shapes bit-equal to the kernel it replaces (worst 0.000 of the bound), 0 edges refused by the kernel +PASS sums hip affine_wmma_moe_gu<4> (Flash Next's expert gate and up, silu(g) u, bf16 out): exact sums at k 2560, where fp16 sums would miss by 152142465291167150000000000x and bf16 by 256x +PASS nonfinite hip affine_wmma_moe_down<4> (Flash Next's expert down, fp32 out): 10240 non-finite and 30720 finite outputs match the float64 classes +PASS repeat hip affine_wmma_moe_down<4> (Flash Next's expert down, fp32 out): five runs byte-identical (1310720 bytes), inputs and guards untouched, no overlap +PASS shapes hip affine_wmma_moe_down<4> (Flash Next's expert down, fp32 out): 5 shapes bit-equal to the kernel it replaces (worst 0.000 of the bound), 0 edges refused by the kernel +PASS sums hip affine_wmma_moe_down<4> (Flash Next's expert down, fp32 out): exact sums at k 640, where fp16 sums would miss by 49344753x and bf16 by 359032422x +PASS nonfinite hip tf_route_count, tf_route_scan and tf_route_scatter: the stated rule holds: members: the pairs stably sorted by expert; items: each expert's pairs in tiles, experts in order, then dead items, as tf_moe_route cuts them +PASS repeat hip tf_route_count, tf_route_scan and tf_route_scatter: five runs byte-identical (10028 bytes), inputs and guards untouched, no overlap +PASS shapes hip tf_route_count, tf_route_scan and tf_route_scatter: 7 shapes bit-equal to the kernel it replaces (worst 0.000 of the bound), 0 edges refused by the kernel +N/A sums hip tf_route_count, tf_route_scan and tf_route_scatter: declares none sums +FAIL nonfinite hip tf_select_rows: row 0 slot 0 holds expert 7, the rule gives 114 +KNOWN nonfinite hip tf_select_rows: select_body (upstream): a NaN shares rank 0 with the top number (slot 0 races) and a row with fewer than k numbers leaves slots unwritten; bytes kept equal to upstream's +PASS repeat hip tf_select_rows: five runs byte-identical (88 bytes), inputs and guards untouched, no overlap +PASS shapes hip tf_select_rows: 7 shapes bit-equal to the kernel it replaces (worst 0.000 of the bound), 0 edges refused by the kernel +N/A sums hip tf_select_rows: declares none sums +FAIL nonfinite hip tf_router_select_bf16: row 0 slot 0 holds expert 3, the rule gives 1 +KNOWN nonfinite hip tf_router_select_bf16: select_body (upstream): a NaN shares rank 0 with the top number (slot 0 races) and a row with fewer than k numbers leaves slots unwritten; bytes kept equal to upstream's +PASS repeat hip tf_router_select_bf16: five runs byte-identical (4560 bytes), inputs and guards untouched, no overlap +PASS shapes hip tf_router_select_bf16: 6 shapes bit-equal to the kernel it replaces (worst 0.000 of the bound), 0 edges refused by the kernel +PASS sums hip tf_router_select_bf16: exact sums at k 2560, where fp16 sums would miss by 317206433x and bf16 by 1581350150x +PASS nonfinite hip tf_topk_part and tf_topk_join (bf16): the stated rule holds: each row's ks[r] largest by a 16-bit key of the value's bits (-0 equal to +0, a positive NaN above +Inf, a negative NaN below -Inf), ties to the lower id, as ids and the values' bits; no slot past ks[r] written +PASS repeat hip tf_topk_part and tf_topk_join (bf16): five runs byte-identical (384 bytes), inputs and guards untouched, no overlap +PASS shapes hip tf_topk_part and tf_topk_join (bf16): 5 shapes bit-equal to the kernel it replaces (worst 0.000 of the bound), 0 edges refused by the kernel +N/A sums hip tf_topk_part and tf_topk_join (bf16): declares none sums +PASS nonfinite hip tf_moe_prefetch: the stated rule holds: no output: every buffer as prepared and every guard intact after each run; with no output it has no float class or bound, so gates 1 and 3 check this, and no sums, so gate 4 has none +PASS repeat hip tf_moe_prefetch: five runs byte-identical (0 bytes), inputs and guards untouched, no overlap +PASS shapes hip tf_moe_prefetch: 1 shapes exact by its own check (worst 0.000 of the bound), 0 edges refused by the kernel +N/A sums hip tf_moe_prefetch: declares none sums +FAIL nonfinite hip flashnext tf_fn_idx_scores_quad (bf16 keys): 1658 of 8800 outputs differ in class; first at 0: finite where float64 gives nan +KNOWN nonfinite hip flashnext tf_fn_idx_scores_quad (bf16 keys): relu is fmaxf(x, 0): a NaN head dot scores 0 where float64 keeps the NaN +PASS repeat hip flashnext tf_fn_idx_scores_quad (bf16 keys): five runs byte-identical (140800 bytes), inputs and guards untouched, no overlap +PASS shapes hip flashnext tf_fn_idx_scores_quad (bf16 keys): 12 shapes bit-equal to the kernel it replaces (worst 0.000 of the bound), 0 edges refused by the kernel +PASS sums hip flashnext tf_fn_idx_scores_quad (bf16 keys): exact sums at k 128, where fp16 sums would miss by 269573x and bf16 by 2219692x +FAIL nonfinite hip flashnext tf_fn_idx_scores8 (bf16 keys): 1655 of 5500 outputs differ in class; first at 0: finite where float64 gives nan +KNOWN nonfinite hip flashnext tf_fn_idx_scores8 (bf16 keys): relu is fmaxf(x, 0): a NaN head dot scores 0 where float64 keeps the NaN +PASS repeat hip flashnext tf_fn_idx_scores8 (bf16 keys): five runs byte-identical (22000 bytes), inputs and guards untouched, no overlap +PASS shapes hip flashnext tf_fn_idx_scores8 (bf16 keys): 13 shapes bit-equal to the kernel it replaces (worst 0.000 of the bound), 0 edges refused by the kernel +PASS sums hip flashnext tf_fn_idx_scores8 (bf16 keys): exact sums at k 128, where fp16 sums would miss by 281431x and bf16 by 2223085x +PASS nonfinite hip flashnext tf_fn_qsa_prep (q and index q rows, bf16): 256 non-finite and 33024 finite outputs match the float64 classes +PASS repeat hip flashnext tf_fn_qsa_prep (q and index q rows, bf16): five runs byte-identical (26624 bytes), inputs and guards untouched, no overlap +PASS shapes hip flashnext tf_fn_qsa_prep (q and index q rows, bf16): 5 shapes bit-equal to the kernel it replaces (worst 0.000 of the bound), 0 edges refused by the kernel +PASS sums hip flashnext tf_fn_qsa_prep (q and index q rows, bf16): within its bound at k 256; fp16 sums would miss 126x, bf16 0.3x (the outputs pass two roundings to the activation kind: a bf16 sum of squares misses by a few of their ulps (fp16's overflows)) +PASS nonfinite hip flashnext tf_fn_qsa_prep (caches and pools, bf16): 9 non-finite and 1288183 finite outputs match the float64 classes +PASS repeat hip flashnext tf_fn_qsa_prep (caches and pools, bf16): five runs byte-identical (2576384 bytes), inputs and guards untouched, no overlap +PASS shapes hip flashnext tf_fn_qsa_prep (caches and pools, bf16): 5 shapes bit-equal to the kernel it replaces (worst 0.000 of the bound), 0 edges refused by the kernel +PASS sums hip flashnext tf_fn_qsa_prep (caches and pools, bf16): within its bound at k 256; fp16 sums would miss 126x, bf16 0.1x (the outputs pass two roundings to the activation kind: a bf16 sum of squares misses by a few of their ulps (fp16's overflows)) +PASS nonfinite hip tf_affine_dense_hcmix (hc up, 4-bit, K 320, the HC mix as its epilogue): the stated rule holds: the separate launches' bytes and every float64 output class +PASS repeat hip tf_affine_dense_hcmix (hc up, 4-bit, K 320, the HC mix as its epilogue): five runs byte-identical (327680 bytes), inputs and guards untouched, no overlap +PASS shapes hip tf_affine_dense_hcmix (hc up, 4-bit, K 320, the HC mix as its epilogue): 8 shapes bit-equal to the kernel it replaces (worst 0.000 of the bound), 0 edges refused by the kernel +PASS sums hip tf_affine_dense_hcmix (hc up, 4-bit, K 320, the HC mix as its epilogue): exact sums at k 320, where fp16 sums would miss by 195767622x and bf16 by 4114763975231118x +PASS nonfinite hip tf_hc_gate_fill (tf_affine_dense_hcmix's 65,536 gates): the stated rule holds: every bf16 g: NaN for NaN, else float64's 1 / (1 + e^-g) rounded to bf16 within expf's 2^-20 (2^-126 below fp32's normals); and tf_fn_hc_mix's gate of g, bit for bit +PASS repeat hip tf_hc_gate_fill (tf_affine_dense_hcmix's 65,536 gates): five runs byte-identical (131072 bytes), inputs and guards untouched, no overlap +PASS shapes hip tf_hc_gate_fill (tf_affine_dense_hcmix's 65,536 gates): 1 shapes exact by its own check (worst 0.000 of the bound), 0 edges refused by the kernel +N/A sums hip tf_hc_gate_fill (tf_affine_dense_hcmix's 65,536 gates): declares none sums +PASS nonfinite hip tf_fn_hc_mix8 (g fp32, bf16 x): the stated rule holds: the per-element kernel's bytes and every float64 output class +PASS repeat hip tf_fn_hc_mix8 (g fp32, bf16 x): five runs byte-identical (5120 bytes), inputs and guards untouched, no overlap +PASS shapes hip tf_fn_hc_mix8 (g fp32, bf16 x): 7 shapes bit-equal to the kernel it replaces (worst 0.000 of the bound), 0 edges refused by the kernel +PASS sums hip tf_fn_hc_mix8 (g fp32, bf16 x): exact sums at k 4, where fp16 sums would miss by infx and bf16 by 174224571863520500000000000000000000000000x +PASS nonfinite hip tf_fn_hc_mix8 (g bf16, bf16 x): the stated rule holds: the per-element kernel's bytes and every float64 output class +PASS repeat hip tf_fn_hc_mix8 (g bf16, bf16 x): five runs byte-identical (5120 bytes), inputs and guards untouched, no overlap +PASS shapes hip tf_fn_hc_mix8 (g bf16, bf16 x): 7 shapes bit-equal to the kernel it replaces (worst 0.000 of the bound), 0 edges refused by the kernel +PASS sums hip tf_fn_hc_mix8 (g bf16, bf16 x): exact sums at k 4, where fp16 sums would miss by infx and bf16 by 174224571863520500000000000000000000000000x +PASS nonfinite hip tf_fn_hc_norm_v (bf16, a branch added in place): the stated rule holds: the chain's bytes and every float64 output class +PASS repeat hip tf_fn_hc_norm_v (bf16, a branch added in place): five runs byte-identical (40960 bytes), inputs and guards untouched, no overlap +PASS shapes hip tf_fn_hc_norm_v (bf16, a branch added in place): 5 shapes bit-equal to the kernel it replaces (worst 0.000 of the bound), 0 edges refused by the kernel +PASS sums hip tf_fn_hc_norm_v (bf16, a branch added in place): within its bound at k 2560; fp16 sums would miss 256x, bf16 0.3x (a 16-bit output follows the sum of squares as ss^-1/2: a bf16 sum's error is a few output ulps) +PASS nonfinite hip tf_fn_hc_norm_v (bf16, no branch): the stated rule holds: the chain's bytes and every float64 output class +PASS repeat hip tf_fn_hc_norm_v (bf16, no branch): five runs byte-identical (20480 bytes), inputs and guards untouched, no overlap +PASS shapes hip tf_fn_hc_norm_v (bf16, no branch): 5 shapes bit-equal to the kernel it replaces (worst 0.000 of the bound), 0 edges refused by the kernel +PASS sums hip tf_fn_hc_norm_v (bf16, no branch): within its bound at k 2560; fp16 sums would miss 256x, bf16 0.4x (a 16-bit output follows the sum of squares as ss^-1/2: a bf16 sum's error is a few output ulps) +PASS nonfinite hip tf_fn_hc_norm_moe (bf16): the stated rule holds: the chain's bytes and every float64 output class +PASS repeat hip tf_fn_hc_norm_moe (bf16): five runs byte-identical (40960 bytes), inputs and guards untouched, no overlap +PASS shapes hip tf_fn_hc_norm_moe (bf16): 9 shapes bit-equal to the kernel it replaces (worst 0.000 of the bound), 0 edges refused by the kernel +PASS sums hip tf_fn_hc_norm_moe (bf16): within its bound at k 2560; fp16 sums would miss 256x, bf16 0.2x (a 16-bit output follows the sum of squares as ss^-1/2: a bf16 sum's error is a few output ulps) +PASS nonfinite hip tf_fn_hc_norm_moe_v (bf16, a prompt's rows): the stated rule holds: the chain's bytes and every float64 output class +PASS repeat hip tf_fn_hc_norm_moe_v (bf16, a prompt's rows): five runs byte-identical (40960 bytes), inputs and guards untouched, no overlap +PASS shapes hip tf_fn_hc_norm_moe_v (bf16, a prompt's rows): 5 shapes bit-equal to the kernel it replaces (worst 0.000 of the bound), 0 edges refused by the kernel +PASS sums hip tf_fn_hc_norm_moe_v (bf16, a prompt's rows): within its bound at k 2560; fp16 sums would miss 256x, bf16 0.6x (a 16-bit output follows the sum of squares as ss^-1/2: a bf16 sum's error is a few output ulps) +PASS nonfinite hip DeltaNet tf_gdn_prompt_128 (y): 1166 non-finite and 47986 finite outputs match the float64 classes +PASS repeat hip DeltaNet tf_gdn_prompt_128 (y): five runs byte-identical (1572864 bytes), inputs and guards untouched, no overlap +PASS shapes hip DeltaNet tf_gdn_prompt_128 (y): 7 shapes bit-equal to the kernel it replaces (worst 0.000 of the bound), 0 edges refused by the kernel +PASS sums hip DeltaNet tf_gdn_prompt_128 (y): exact sums at k 128, where fp16 sums would miss by infx and bf16 by 90637017916318400000000000000000x +PASS nonfinite hip DeltaNet tf_gdn_prompt_128 (the state): 16640 non-finite and 769792 finite outputs match the float64 classes +PASS repeat hip DeltaNet tf_gdn_prompt_128 (the state): five runs byte-identical (3145728 bytes), inputs and guards untouched, no overlap +PASS shapes hip DeltaNet tf_gdn_prompt_128 (the state): 7 shapes bit-equal to the kernel it replaces (worst 0.000 of the bound), 0 edges refused by the kernel +PASS sums hip DeltaNet tf_gdn_prompt_128 (the state): exact sums at k 128, where fp16 sums would miss by infx and bf16 by 1708648260329309700000000000000000000000000000000000000000000000000x +PASS nonfinite hip DeltaNet tf_gdn_prompt_prep (bf16 in): 777 non-finite and 112631 finite outputs match the float64 classes +PASS repeat hip DeltaNet tf_gdn_prompt_prep (bf16 in): five runs byte-identical (1776640 bytes), inputs and guards untouched, no overlap +PASS shapes hip DeltaNet tf_gdn_prompt_prep (bf16 in): 6 shapes bit-equal to the kernel it replaces (worst 0.000 of the bound), 0 edges refused by the kernel +PASS sums hip DeltaNet tf_gdn_prompt_prep (bf16 in): exact sums at k 128, where fp16 sums would miss by infx and bf16 by 24277617x +PASS nonfinite hip DeltaNet tf_gdn_hold_128 (y): 776 non-finite and 29944 finite outputs match the float64 classes +PASS repeat hip DeltaNet tf_gdn_hold_128 (y): five runs byte-identical (49152 bytes), inputs and guards untouched, no overlap +PASS shapes hip DeltaNet tf_gdn_hold_128 (y): 4 shapes bit-equal to the kernel it replaces (worst 0.000 of the bound), 0 edges refused by the kernel +PASS sums hip DeltaNet tf_gdn_hold_128 (y): exact sums at k 128, where fp16 sums would miss by infx and bf16 by 249031044995062170000x +PASS nonfinite hip DeltaNet tf_gdn_hold_16 (y): 104 non-finite and 3736 finite outputs match the float64 classes +PASS repeat hip DeltaNet tf_gdn_hold_16 (y): five runs byte-identical (6144 bytes), inputs and guards untouched, no overlap +PASS shapes hip DeltaNet tf_gdn_hold_16 (y): 4 shapes bit-equal to the kernel it replaces (worst 0.000 of the bound), 0 edges refused by the kernel +PASS sums hip DeltaNet tf_gdn_hold_16 (y): exact sums at k 16, where fp16 sums would miss by infx and bf16 by 3170534137652052000x +PASS nonfinite hip DeltaNet tf_gdn_keep_128 (the states): 33280 non-finite and 1539584 finite outputs match the float64 classes +PASS repeat hip DeltaNet tf_gdn_keep_128 (the states): five runs byte-identical (6291456 bytes), inputs and guards untouched, no overlap +PASS shapes hip DeltaNet tf_gdn_keep_128 (the states): 3 shapes bit-equal to the kernel it replaces (worst 0.000 of the bound), 0 edges refused by the kernel +PASS sums hip DeltaNet tf_gdn_keep_128 (the states): exact sums at k 128, where fp16 sums would miss by infx and bf16 by 3346951400137926300000000000000000000000000000000000000000000000000x +PASS nonfinite hip DeltaNet tf_gdn_keep_16 (the states): 576 non-finite and 24000 finite outputs match the float64 classes +PASS repeat hip DeltaNet tf_gdn_keep_16 (the states): five runs byte-identical (98304 bytes), inputs and guards untouched, no overlap +PASS shapes hip DeltaNet tf_gdn_keep_16 (the states): 3 shapes bit-equal to the kernel it replaces (worst 0.000 of the bound), 0 edges refused by the kernel +PASS sums hip DeltaNet tf_gdn_keep_16 (the states): exact sums at k 16, where fp16 sums would miss by infx and bf16 by 4616726528052754000000000000000000000000000000000000000000000000x +PASS limits: 199 registered HIP launches against gfx1030/1100/1151/1201, 0 problems +RED limits control: past its bounds: red on every chip +RED limits control: 72 KiB of LDS: red on every chip +PASS limits live gfx1151 threads a workgroup: the device says 1024, the table 1024 +PASS limits live gfx1151 LDS bytes a workgroup: the device says 65536, the table 65536 +PASS limits live gfx1151 wave size: the device says 32, the table 32 +PASS limits live swiglu stream work list 4-bit 4x2: 128 threads launched, the runtime allows 128; 163 VGPRs, 0 + 0 LDS bytes (recorded 163, 0) +PASS limits live plain stream work list 4-bit 4x4: 128 threads launched, the runtime allows 128; 220 VGPRs, 0 + 0 LDS bytes (recorded 220, 0) +PASS limits live RMS norm tf_rms_rows: 256 threads launched, the runtime allows 256; 42 VGPRs, 0 + 0 LDS bytes (recorded 42, 0) +PASS limits live RMS norm rms_kernel<__half>: 256 threads launched, the runtime allows 256; 10 VGPRs, 32772 + 0 LDS bytes (recorded 10, 32772) +PASS limits live RMS norm rms_kernel: 256 threads launched, the runtime allows 256; 10 VGPRs, 32772 + 0 LDS bytes (recorded 10, 32772) +PASS limits live mamba tf_mamba_conv: 256 threads launched, the runtime allows 256; 26 VGPRs, 0 + 0 LDS bytes (recorded 26, 0) +PASS limits live mamba tf_mamba_dt: 256 threads launched, the runtime allows 1024; 16 VGPRs, 0 + 0 LDS bytes (recorded 16, 0) +PASS limits live mamba tf_mamba_scan: 128 threads launched, the runtime allows 128; 125 VGPRs, 20544 + 0 LDS bytes (recorded 125, 20544) +PASS limits live mamba tf_mamba_gnorm: 128 threads launched, the runtime allows 128; 23 VGPRs, 16 + 0 LDS bytes (recorded 23, 16) +PASS limits live nemotron tf_nemo_select: 32 threads launched, the runtime allows 32; 27 VGPRs, 8320 + 0 LDS bytes (recorded 27, 8320) +PASS limits live nemotron tf_nemo_select_rank: 512 threads launched, the runtime allows 512; 27 VGPRs, 8320 + 0 LDS bytes (recorded 27, 8320) +PASS limits live nemotron tf_nemo_relu2: 256 threads launched, the runtime allows 1024; 8 VGPRs, 0 + 0 LDS bytes (recorded 8, 0) +PASS limits live nemotron tf_nemo_localize: 256 threads launched, the runtime allows 1024; 4 VGPRs, 0 + 0 LDS bytes (recorded 4, 0) +PASS limits live nemotron tf_nemo_combine: 256 threads launched, the runtime allows 1024; 9 VGPRs, 0 + 0 LDS bytes (recorded 9, 0) +PASS limits live planned walk tf_plan_score_f16: 128 threads launched, the runtime allows 128; 17 VGPRs, 0 + 8192 LDS bytes (recorded 17, 0) +PASS limits live planned walk tf_plan_score_bf16: 128 threads launched, the runtime allows 128; 17 VGPRs, 0 + 8192 LDS bytes (recorded 17, 0) +PASS limits live planned walk tf_softmax_stats: 256 threads launched, the runtime allows 1024; 9 VGPRs, 1024 + 0 LDS bytes (recorded 9, 1024) +PASS limits live planned walk tf_plan_apply_f16: 256 threads launched, the runtime allows 256; 57 VGPRs, 8192 + 0 LDS bytes (recorded 57, 8192) +PASS limits live planned walk tf_plan_apply_bf16: 256 threads launched, the runtime allows 256; 57 VGPRs, 8192 + 0 LDS bytes (recorded 57, 8192) +PASS limits live planned walk tf_sum_partials: 256 threads launched, the runtime allows 1024; 5 VGPRs, 0 + 0 LDS bytes (recorded 5, 0) +PASS limits live add rms tf_add_rms_f16: 1024 threads launched, the runtime allows 1024; 45 VGPRs, 32772 + 0 LDS bytes (recorded 45, 32772) +PASS limits live add rms tf_add_rms_bf16: 1024 threads launched, the runtime allows 1024; 45 VGPRs, 32772 + 0 LDS bytes (recorded 45, 32772) +PASS limits live mamba tf_mamba_conv_window: 256 threads launched, the runtime allows 256; 37 VGPRs, 0 + 0 LDS bytes (recorded 37, 0) +PASS limits live mamba tf_mamba_scan_snap: 128 threads launched, the runtime allows 128; 135 VGPRs, 20544 + 0 LDS bytes (recorded 135, 20544) +PASS limits live relu2 stream tile 4-bit 1x2: 128 threads launched, the runtime allows 128; 83 VGPRs, 0 + 0 LDS bytes (recorded 83, 0) +PASS limits live relu2 stream tile 4-bit 1x4: 128 threads launched, the runtime allows 128; 121 VGPRs, 0 + 0 LDS bytes (recorded 121, 0) +PASS limits live relu2 stream tile 4-bit 1x8: 128 threads launched, the runtime allows 128; 186 VGPRs, 0 + 0 LDS bytes (recorded 186, 0) +PASS limits live relu2 stream tile 4-bit 2x2: 128 threads launched, the runtime allows 128; 110 VGPRs, 0 + 0 LDS bytes (recorded 110, 0) +PASS limits live relu2 stream tile 4-bit 2x4: 128 threads launched, the runtime allows 128; 135 VGPRs, 0 + 0 LDS bytes (recorded 135, 0) +PASS limits live relu2 stream tile 4-bit 2x8: 128 threads launched, the runtime allows 128; 248 VGPRs, 0 + 0 LDS bytes (recorded 248, 0) +PASS limits live relu2 stream tile 4-bit 4x2: 128 threads launched, the runtime allows 128; 148 VGPRs, 0 + 0 LDS bytes (recorded 148, 0) +PASS limits live relu2 stream tile 4-bit 4x4: 128 threads launched, the runtime allows 128; 181 VGPRs, 0 + 0 LDS bytes (recorded 181, 0) +PASS limits live planned walk tf_plan_kv_write_act: 256 threads launched, the runtime allows 256; 20 VGPRs, 0 + 0 LDS bytes (recorded 20, 0) +PASS limits live planned walk tf_plan_score_act_f16: 128 threads launched, the runtime allows 128; 17 VGPRs, 0 + 8192 LDS bytes (recorded 17, 0) +PASS limits live planned walk tf_plan_score_act_bf16: 128 threads launched, the runtime allows 128; 17 VGPRs, 0 + 8192 LDS bytes (recorded 17, 0) +PASS limits live planned walk tf_sum_partials_act: 256 threads launched, the runtime allows 1024; 6 VGPRs, 0 + 0 LDS bytes (recorded 6, 0) +PASS limits live argmax tf_argmax_part: 256 threads launched, the runtime allows 256; 8 VGPRs, 2048 + 0 LDS bytes (recorded 8, 2048) +PASS limits live top-k tf_topk_part: 1024 threads launched, the runtime allows 1024; 78 VGPRs, 1296 + 0 LDS bytes (recorded 78, 1296) +PASS limits live top-k tf_topk_join: 1024 threads launched, the runtime allows 1024; 16 VGPRs, 33808 + 0 LDS bytes (recorded 16, 33808) +PASS limits live argmax tf_argmax_join: 256 threads launched, the runtime allows 256; 10 VGPRs, 2048 + 0 LDS bytes (recorded 10, 2048) +PASS limits live planned walk tf_plan_attend_f16: 1024 threads launched, the runtime allows 1024; 38 VGPRs, 50688 + 0 LDS bytes (recorded 38, 50688) +PASS limits live planned walk tf_plan_attend_bf16: 1024 threads launched, the runtime allows 1024; 36 VGPRs, 50688 + 0 LDS bytes (recorded 36, 50688) +PASS limits live MoE router (decode, fp32 rows) tf_router_decode_f16: 128 threads launched, the runtime allows 128; 90 VGPRs, 0 + 0 LDS bytes (recorded 90, 0) +PASS limits live MoE router (decode, fp32 rows) tf_router_decode_bf16: 128 threads launched, the runtime allows 128; 91 VGPRs, 0 + 0 LDS bytes (recorded 91, 0) +PASS limits live MoE router and pick in one launch (decode, bf16 rows) tf_router_select_f16: 128 threads launched, the runtime allows 128; 135 VGPRs, 5456 + 10240 LDS bytes (recorded 135, 5456) +PASS limits live MoE router and pick in one launch (decode, bf16 rows) tf_router_select_bf16: 128 threads launched, the runtime allows 128; 135 VGPRs, 5456 + 10240 LDS bytes (recorded 135, 5456) +PASS limits live MoE down codes read beside the gate and up (side stream) tf_moe_prefetch: 256 threads launched, the runtime allows 256; 11 VGPRs, 260 + 0 LDS bytes (recorded 11, 260) +PASS limits live prompt expert gate+up tile 4-bit: 256 threads launched, the runtime allows 256; 225 VGPRs, 36352 + 0 LDS bytes (recorded 225, 36352) +PASS limits live prompt expert down tile 4-bit: 256 threads launched, the runtime allows 256; 189 VGPRs, 32256 + 0 LDS bytes (recorded 189, 32256) +PASS limits live prompt dense tile 4-bit K 320: 256 threads launched, the runtime allows 256; 208 VGPRs, 39936 + 0 LDS bytes (recorded 208, 39936) +PASS limits live prompt dense tile 4-bit K 320 with the HC mix: 256 threads launched, the runtime allows 256; 215 VGPRs, 39936 + 0 LDS bytes (recorded 215, 39936) +PASS limits live prompt dense tile 4-bit K 2560: 256 threads launched, the runtime allows 256; 208 VGPRs, 39936 + 0 LDS bytes (recorded 208, 39936) +PASS limits live prompt dense tile 4-bit K 6144: 256 threads launched, the runtime allows 256; 208 VGPRs, 39936 + 0 LDS bytes (recorded 208, 39936) +PASS limits live prompt dense tile 4-bit K 10240: 256 threads launched, the runtime allows 256; 246 VGPRs, 39936 + 0 LDS bytes (recorded 246, 39936) +PASS limits live Flash Next QSA decode prep: 256 threads launched, the runtime allows 256; 34 VGPRs, 17440 + 0 LDS bytes (recorded 34, 17440) +PASS limits live relu2 pair tile 4-bit 1x2: 128 threads launched, the runtime allows 128; 83 VGPRs, 0 + 0 LDS bytes (recorded 83, 0) +PASS limits live relu2 pair tile 4-bit 1x4: 128 threads launched, the runtime allows 128; 121 VGPRs, 0 + 0 LDS bytes (recorded 121, 0) +PASS limits live relu2 pair tile 4-bit 1x8: 128 threads launched, the runtime allows 128; 186 VGPRs, 0 + 0 LDS bytes (recorded 186, 0) +PASS limits live relu2 pair tile 4-bit 2x2: 128 threads launched, the runtime allows 128; 109 VGPRs, 0 + 0 LDS bytes (recorded 109, 0) +PASS limits live relu2 pair tile 4-bit 2x4: 128 threads launched, the runtime allows 128; 135 VGPRs, 0 + 0 LDS bytes (recorded 135, 0) +PASS limits live relu2 pair tile 4-bit 2x8: 128 threads launched, the runtime allows 128; 248 VGPRs, 0 + 0 LDS bytes (recorded 248, 0) +PASS limits live relu2 pair tile 4-bit 4x2: 128 threads launched, the runtime allows 128; 148 VGPRs, 0 + 0 LDS bytes (recorded 148, 0) +PASS limits live relu2 pair tile 4-bit 4x4: 128 threads launched, the runtime allows 128; 181 VGPRs, 0 + 0 LDS bytes (recorded 181, 0) +PASS limits live plain stream tile 2-bit 1x1: 128 threads launched, the runtime allows 128; 56 VGPRs, 0 + 0 LDS bytes (recorded 56, 0) +PASS limits live plain stream tile 2-bit 1x2: 128 threads launched, the runtime allows 128; 73 VGPRs, 0 + 0 LDS bytes (recorded 73, 0) +PASS limits live plain stream tile 2-bit 1x4: 128 threads launched, the runtime allows 128; 94 VGPRs, 0 + 0 LDS bytes (recorded 94, 0) +PASS limits live plain stream tile 2-bit 1x8: 128 threads launched, the runtime allows 128; 154 VGPRs, 0 + 0 LDS bytes (recorded 154, 0) +PASS limits live plain stream tile 2-bit 2x1: 128 threads launched, the runtime allows 128; 69 VGPRs, 0 + 0 LDS bytes (recorded 69, 0) +PASS limits live plain stream tile 2-bit 2x2: 128 threads launched, the runtime allows 128; 108 VGPRs, 0 + 0 LDS bytes (recorded 108, 0) +PASS limits live plain stream tile 2-bit 2x4: 128 threads launched, the runtime allows 128; 130 VGPRs, 0 + 0 LDS bytes (recorded 130, 0) +PASS limits live plain stream tile 2-bit 2x8: 128 threads launched, the runtime allows 128; 175 VGPRs, 0 + 0 LDS bytes (recorded 175, 0) +PASS limits live plain stream tile 2-bit 4x1: 128 threads launched, the runtime allows 128; 119 VGPRs, 0 + 0 LDS bytes (recorded 119, 0) +PASS limits live plain stream tile 2-bit 4x2: 128 threads launched, the runtime allows 128; 147 VGPRs, 0 + 0 LDS bytes (recorded 147, 0) +PASS limits live plain stream tile 2-bit 4x4: 128 threads launched, the runtime allows 128; 173 VGPRs, 0 + 0 LDS bytes (recorded 173, 0) +PASS limits live plain stream tile 3-bit 1x1: 128 threads launched, the runtime allows 128; 58 VGPRs, 0 + 0 LDS bytes (recorded 58, 0) +PASS limits live plain stream tile 3-bit 1x2: 128 threads launched, the runtime allows 128; 77 VGPRs, 0 + 0 LDS bytes (recorded 77, 0) +PASS limits live plain stream tile 3-bit 1x4: 128 threads launched, the runtime allows 128; 97 VGPRs, 0 + 0 LDS bytes (recorded 97, 0) +PASS limits live plain stream tile 3-bit 1x8: 128 threads launched, the runtime allows 128; 165 VGPRs, 0 + 0 LDS bytes (recorded 165, 0) +PASS limits live plain stream tile 3-bit 2x1: 128 threads launched, the runtime allows 128; 96 VGPRs, 0 + 0 LDS bytes (recorded 96, 0) +PASS limits live plain stream tile 3-bit 2x2: 128 threads launched, the runtime allows 128; 109 VGPRs, 0 + 0 LDS bytes (recorded 109, 0) +PASS limits live plain stream tile 3-bit 2x4: 128 threads launched, the runtime allows 128; 133 VGPRs, 0 + 0 LDS bytes (recorded 133, 0) +PASS limits live plain stream tile 3-bit 2x8: 128 threads launched, the runtime allows 128; 180 VGPRs, 0 + 0 LDS bytes (recorded 180, 0) +PASS limits live plain stream tile 3-bit 4x1: 128 threads launched, the runtime allows 128; 132 VGPRs, 0 + 0 LDS bytes (recorded 132, 0) +PASS limits live plain stream tile 3-bit 4x2: 128 threads launched, the runtime allows 128; 146 VGPRs, 0 + 0 LDS bytes (recorded 146, 0) +PASS limits live plain stream tile 3-bit 4x4: 128 threads launched, the runtime allows 128; 174 VGPRs, 0 + 0 LDS bytes (recorded 174, 0) +PASS limits live plain stream tile 4-bit 1x1: 128 threads launched, the runtime allows 128; 60 VGPRs, 0 + 0 LDS bytes (recorded 60, 0) +PASS limits live plain stream tile 4-bit 1x2: 128 threads launched, the runtime allows 128; 83 VGPRs, 0 + 0 LDS bytes (recorded 83, 0) +PASS limits live plain stream tile 4-bit 1x4: 128 threads launched, the runtime allows 128; 121 VGPRs, 0 + 0 LDS bytes (recorded 121, 0) +PASS limits live plain stream tile 4-bit 1x8: 128 threads launched, the runtime allows 128; 186 VGPRs, 0 + 0 LDS bytes (recorded 186, 0) +PASS limits live plain stream tile 4-bit 2x1: 128 threads launched, the runtime allows 128; 98 VGPRs, 0 + 0 LDS bytes (recorded 98, 0) +PASS limits live plain stream tile 4-bit 2x2: 128 threads launched, the runtime allows 128; 110 VGPRs, 0 + 0 LDS bytes (recorded 110, 0) +PASS limits live plain stream tile 4-bit 2x4: 128 threads launched, the runtime allows 128; 135 VGPRs, 0 + 0 LDS bytes (recorded 135, 0) +PASS limits live plain stream tile 4-bit 2x8: 128 threads launched, the runtime allows 128; 188 VGPRs, 0 + 0 LDS bytes (recorded 188, 0) +PASS limits live plain stream tile 4-bit 4x1: 128 threads launched, the runtime allows 128; 134 VGPRs, 0 + 0 LDS bytes (recorded 134, 0) +PASS limits live plain stream tile 4-bit 4x2: 128 threads launched, the runtime allows 128; 148 VGPRs, 0 + 0 LDS bytes (recorded 148, 0) +PASS limits live plain stream tile 4-bit 4x4: 128 threads launched, the runtime allows 128; 181 VGPRs, 0 + 0 LDS bytes (recorded 181, 0) +PASS limits live plain stream tile 5-bit 1x1: 128 threads launched, the runtime allows 128; 62 VGPRs, 0 + 0 LDS bytes (recorded 62, 0) +PASS limits live plain stream tile 5-bit 1x2: 128 threads launched, the runtime allows 128; 80 VGPRs, 0 + 0 LDS bytes (recorded 80, 0) +PASS limits live plain stream tile 5-bit 1x4: 128 threads launched, the runtime allows 128; 113 VGPRs, 0 + 0 LDS bytes (recorded 113, 0) +PASS limits live plain stream tile 5-bit 1x8: 128 threads launched, the runtime allows 128; 197 VGPRs, 0 + 0 LDS bytes (recorded 197, 0) +PASS limits live plain stream tile 5-bit 2x1: 128 threads launched, the runtime allows 128; 96 VGPRs, 0 + 0 LDS bytes (recorded 96, 0) +PASS limits live plain stream tile 5-bit 2x2: 128 threads launched, the runtime allows 128; 113 VGPRs, 0 + 0 LDS bytes (recorded 113, 0) +PASS limits live plain stream tile 5-bit 2x4: 128 threads launched, the runtime allows 128; 141 VGPRs, 0 + 0 LDS bytes (recorded 141, 0) +PASS limits live plain stream tile 5-bit 2x8: 128 threads launched, the runtime allows 128; 194 VGPRs, 0 + 0 LDS bytes (recorded 194, 0) +PASS limits live plain stream tile 5-bit 4x1: 128 threads launched, the runtime allows 128; 132 VGPRs, 0 + 0 LDS bytes (recorded 132, 0) +PASS limits live plain stream tile 5-bit 4x2: 128 threads launched, the runtime allows 128; 149 VGPRs, 0 + 0 LDS bytes (recorded 149, 0) +PASS limits live plain stream tile 5-bit 4x4: 128 threads launched, the runtime allows 128; 180 VGPRs, 0 + 0 LDS bytes (recorded 180, 0) +PASS limits live plain stream tile 6-bit 1x1: 128 threads launched, the runtime allows 128; 64 VGPRs, 0 + 0 LDS bytes (recorded 64, 0) +PASS limits live plain stream tile 6-bit 1x2: 128 threads launched, the runtime allows 128; 85 VGPRs, 0 + 0 LDS bytes (recorded 85, 0) +PASS limits live plain stream tile 6-bit 1x4: 128 threads launched, the runtime allows 128; 121 VGPRs, 0 + 0 LDS bytes (recorded 121, 0) +PASS limits live plain stream tile 6-bit 1x8: 128 threads launched, the runtime allows 128; 213 VGPRs, 0 + 0 LDS bytes (recorded 213, 0) +PASS limits live plain stream tile 6-bit 2x1: 128 threads launched, the runtime allows 128; 98 VGPRs, 0 + 0 LDS bytes (recorded 98, 0) +PASS limits live plain stream tile 6-bit 2x2: 128 threads launched, the runtime allows 128; 113 VGPRs, 0 + 0 LDS bytes (recorded 113, 0) +PASS limits live plain stream tile 6-bit 2x4: 128 threads launched, the runtime allows 128; 143 VGPRs, 0 + 0 LDS bytes (recorded 143, 0) +PASS limits live plain stream tile 6-bit 2x8: 128 threads launched, the runtime allows 128; 200 VGPRs, 0 + 0 LDS bytes (recorded 200, 0) +PASS limits live plain stream tile 6-bit 4x1: 128 threads launched, the runtime allows 128; 134 VGPRs, 0 + 0 LDS bytes (recorded 134, 0) +PASS limits live plain stream tile 6-bit 4x2: 128 threads launched, the runtime allows 128; 148 VGPRs, 0 + 0 LDS bytes (recorded 148, 0) +PASS limits live plain stream tile 6-bit 4x4: 128 threads launched, the runtime allows 128; 182 VGPRs, 0 + 0 LDS bytes (recorded 182, 0) +PASS limits live plain stream tile 8-bit 1x1: 128 threads launched, the runtime allows 128; 68 VGPRs, 0 + 0 LDS bytes (recorded 68, 0) +PASS limits live plain stream tile 8-bit 1x2: 128 threads launched, the runtime allows 128; 95 VGPRs, 0 + 0 LDS bytes (recorded 95, 0) +PASS limits live plain stream tile 8-bit 1x4: 128 threads launched, the runtime allows 128; 137 VGPRs, 0 + 0 LDS bytes (recorded 137, 0) +PASS limits live plain stream tile 8-bit 1x8: 128 threads launched, the runtime allows 128; 256 VGPRs, 0 + 0 LDS bytes (recorded 256, 0) +PASS limits live plain stream tile 8-bit 2x1: 128 threads launched, the runtime allows 128; 96 VGPRs, 0 + 0 LDS bytes (recorded 96, 0) +PASS limits live plain stream tile 8-bit 2x2: 128 threads launched, the runtime allows 128; 105 VGPRs, 0 + 0 LDS bytes (recorded 105, 0) +PASS limits live plain stream tile 8-bit 2x4: 128 threads launched, the runtime allows 128; 141 VGPRs, 0 + 0 LDS bytes (recorded 141, 0) +PASS limits live plain stream tile 8-bit 2x8: 128 threads launched, the runtime allows 128; 205 VGPRs, 0 + 0 LDS bytes (recorded 205, 0) +PASS limits live plain stream tile 8-bit 4x1: 128 threads launched, the runtime allows 128; 132 VGPRs, 0 + 0 LDS bytes (recorded 132, 0) +PASS limits live plain stream tile 8-bit 4x2: 128 threads launched, the runtime allows 128; 155 VGPRs, 0 + 0 LDS bytes (recorded 155, 0) +PASS limits live plain stream tile 8-bit 4x4: 128 threads launched, the runtime allows 128; 195 VGPRs, 0 + 0 LDS bytes (recorded 195, 0) +PASS limits live swiglu stream tile 2-bit 1x2: 128 threads launched, the runtime allows 128; 72 VGPRs, 0 + 0 LDS bytes (recorded 72, 0) +PASS limits live swiglu stream tile 2-bit 1x4: 128 threads launched, the runtime allows 128; 91 VGPRs, 0 + 0 LDS bytes (recorded 91, 0) +PASS limits live swiglu stream tile 2-bit 1x8: 128 threads launched, the runtime allows 128; 158 VGPRs, 0 + 0 LDS bytes (recorded 158, 0) +PASS limits live swiglu stream tile 2-bit 2x2: 128 threads launched, the runtime allows 128; 105 VGPRs, 0 + 0 LDS bytes (recorded 105, 0) +PASS limits live swiglu stream tile 2-bit 2x4: 128 threads launched, the runtime allows 128; 128 VGPRs, 0 + 0 LDS bytes (recorded 128, 0) +PASS limits live swiglu stream tile 2-bit 2x8: 128 threads launched, the runtime allows 128; 171 VGPRs, 0 + 0 LDS bytes (recorded 171, 0) +PASS limits live swiglu stream tile 2-bit 4x2: 128 threads launched, the runtime allows 128; 144 VGPRs, 0 + 0 LDS bytes (recorded 144, 0) +PASS limits live swiglu stream tile 2-bit 4x4: 128 threads launched, the runtime allows 128; 171 VGPRs, 0 + 0 LDS bytes (recorded 171, 0) +PASS limits live swiglu stream tile 3-bit 1x2: 128 threads launched, the runtime allows 128; 74 VGPRs, 0 + 0 LDS bytes (recorded 74, 0) +PASS limits live swiglu stream tile 3-bit 1x4: 128 threads launched, the runtime allows 128; 96 VGPRs, 0 + 0 LDS bytes (recorded 96, 0) +PASS limits live swiglu stream tile 3-bit 1x8: 128 threads launched, the runtime allows 128; 169 VGPRs, 0 + 0 LDS bytes (recorded 169, 0) +PASS limits live swiglu stream tile 3-bit 2x2: 128 threads launched, the runtime allows 128; 109 VGPRs, 0 + 0 LDS bytes (recorded 109, 0) +PASS limits live swiglu stream tile 3-bit 2x4: 128 threads launched, the runtime allows 128; 94 VGPRs, 0 + 0 LDS bytes (recorded 94, 0) +PASS limits live swiglu stream tile 3-bit 2x8: 128 threads launched, the runtime allows 128; 176 VGPRs, 0 + 0 LDS bytes (recorded 176, 0) +PASS limits live swiglu stream tile 3-bit 4x2: 128 threads launched, the runtime allows 128; 144 VGPRs, 0 + 0 LDS bytes (recorded 144, 0) +PASS limits live swiglu stream tile 3-bit 4x4: 128 threads launched, the runtime allows 128; 138 VGPRs, 0 + 0 LDS bytes (recorded 138, 0) +PASS limits live swiglu stream tile 4-bit 1x2: 128 threads launched, the runtime allows 128; 75 VGPRs, 0 + 0 LDS bytes (recorded 75, 0) +PASS limits live swiglu stream tile 4-bit 1x4: 128 threads launched, the runtime allows 128; 119 VGPRs, 0 + 0 LDS bytes (recorded 119, 0) +PASS limits live swiglu stream tile 4-bit 1x8: 128 threads launched, the runtime allows 128; 190 VGPRs, 0 + 0 LDS bytes (recorded 190, 0) +PASS limits live swiglu stream tile 4-bit 2x2: 128 threads launched, the runtime allows 128; 106 VGPRs, 0 + 0 LDS bytes (recorded 106, 0) +PASS limits live swiglu stream tile 4-bit 2x4: 128 threads launched, the runtime allows 128; 134 VGPRs, 0 + 0 LDS bytes (recorded 134, 0) +PASS limits live swiglu stream tile 4-bit 2x8: 128 threads launched, the runtime allows 128; 184 VGPRs, 0 + 0 LDS bytes (recorded 184, 0) +PASS limits live swiglu stream tile 4-bit 4x2: 128 threads launched, the runtime allows 128; 145 VGPRs, 0 + 0 LDS bytes (recorded 145, 0) +PASS limits live swiglu stream tile 4-bit 4x4: 128 threads launched, the runtime allows 128; 179 VGPRs, 0 + 0 LDS bytes (recorded 179, 0) +PASS limits live swiglu stream tile 5-bit 1x2: 128 threads launched, the runtime allows 128; 76 VGPRs, 0 + 0 LDS bytes (recorded 76, 0) +PASS limits live swiglu stream tile 5-bit 1x4: 128 threads launched, the runtime allows 128; 112 VGPRs, 0 + 0 LDS bytes (recorded 112, 0) +PASS limits live swiglu stream tile 5-bit 1x8: 128 threads launched, the runtime allows 128; 201 VGPRs, 0 + 0 LDS bytes (recorded 201, 0) +PASS limits live swiglu stream tile 5-bit 2x2: 128 threads launched, the runtime allows 128; 75 VGPRs, 0 + 0 LDS bytes (recorded 75, 0) +PASS limits live swiglu stream tile 5-bit 2x4: 128 threads launched, the runtime allows 128; 104 VGPRs, 0 + 0 LDS bytes (recorded 104, 0) +PASS limits live swiglu stream tile 5-bit 2x8: 128 threads launched, the runtime allows 128; 190 VGPRs, 0 + 0 LDS bytes (recorded 190, 0) +PASS limits live swiglu stream tile 5-bit 4x2: 128 threads launched, the runtime allows 128; 113 VGPRs, 0 + 0 LDS bytes (recorded 113, 0) +PASS limits live swiglu stream tile 5-bit 4x4: 128 threads launched, the runtime allows 128; 143 VGPRs, 0 + 0 LDS bytes (recorded 143, 0) +PASS limits live swiglu stream tile 6-bit 1x2: 128 threads launched, the runtime allows 128; 82 VGPRs, 0 + 0 LDS bytes (recorded 82, 0) +PASS limits live swiglu stream tile 6-bit 1x4: 128 threads launched, the runtime allows 128; 121 VGPRs, 0 + 0 LDS bytes (recorded 121, 0) +PASS limits live swiglu stream tile 6-bit 1x8: 128 threads launched, the runtime allows 128; 217 VGPRs, 0 + 0 LDS bytes (recorded 217, 0) +PASS limits live swiglu stream tile 6-bit 2x2: 128 threads launched, the runtime allows 128; 108 VGPRs, 0 + 0 LDS bytes (recorded 108, 0) +PASS limits live swiglu stream tile 6-bit 2x4: 128 threads launched, the runtime allows 128; 141 VGPRs, 0 + 0 LDS bytes (recorded 141, 0) +PASS limits live swiglu stream tile 6-bit 2x8: 128 threads launched, the runtime allows 128; 196 VGPRs, 0 + 0 LDS bytes (recorded 196, 0) +PASS limits live swiglu stream tile 6-bit 4x2: 128 threads launched, the runtime allows 128; 145 VGPRs, 0 + 0 LDS bytes (recorded 145, 0) +PASS limits live swiglu stream tile 6-bit 4x4: 128 threads launched, the runtime allows 128; 180 VGPRs, 0 + 0 LDS bytes (recorded 180, 0) +PASS limits live swiglu stream tile 8-bit 1x2: 128 threads launched, the runtime allows 128; 94 VGPRs, 0 + 0 LDS bytes (recorded 94, 0) +PASS limits live swiglu stream tile 8-bit 1x4: 128 threads launched, the runtime allows 128; 137 VGPRs, 0 + 0 LDS bytes (recorded 137, 0) +PASS limits live swiglu stream tile 8-bit 1x8: 128 threads launched, the runtime allows 128; 235 VGPRs, 0 + 0 LDS bytes (recorded 235, 0) +PASS limits live swiglu stream tile 8-bit 2x2: 128 threads launched, the runtime allows 128; 102 VGPRs, 0 + 0 LDS bytes (recorded 102, 0) +PASS limits live swiglu stream tile 8-bit 2x4: 128 threads launched, the runtime allows 128; 139 VGPRs, 0 + 0 LDS bytes (recorded 139, 0) +PASS limits live swiglu stream tile 8-bit 2x8: 128 threads launched, the runtime allows 128; 201 VGPRs, 0 + 0 LDS bytes (recorded 201, 0) +PASS limits live swiglu stream tile 8-bit 4x2: 128 threads launched, the runtime allows 128; 152 VGPRs, 0 + 0 LDS bytes (recorded 152, 0) +PASS limits live swiglu stream tile 8-bit 4x4: 128 threads launched, the runtime allows 128; 193 VGPRs, 0 + 0 LDS bytes (recorded 193, 0) +PASS limits live held stream tile 4-bit 4x1: 128 threads launched, the runtime allows 128; 99 VGPRs, 0 + 0 LDS bytes (recorded 99, 0) +PASS limits live held stream tile 4-bit 4x2: 128 threads launched, the runtime allows 128; 128 VGPRs, 0 + 0 LDS bytes (recorded 128, 0) +PASS limits live held stream tile 4-bit 4x4: 128 threads launched, the runtime allows 128; 180 VGPRs, 0 + 0 LDS bytes (recorded 180, 0) +PASS limits live held stream tile 4-bit 8x2: 128 threads launched, the runtime allows 128; 200 VGPRs, 0 + 0 LDS bytes (recorded 200, 0) +PASS limits live held stream tile 4-bit 8x4: 128 threads launched, the runtime allows 128; 256 VGPRs, 0 + 0 LDS bytes (recorded 256, 0) +PASS limits live MoE plan count tf_route_count: 256 threads launched, the runtime allows 256; 7 VGPRs, 4096 + 0 LDS bytes (recorded 7, 4096) +PASS limits live MoE plan scan tf_route_scan: 1024 threads launched, the runtime allows 1024; 10 VGPRs, 20480 + 0 LDS bytes (recorded 10, 20480) +PASS limits live MoE plan scatter tf_route_scatter: 512 threads launched, the runtime allows 512; 14 VGPRs, 2048 + 0 LDS bytes (recorded 14, 2048) +PASS limits live MoE prompt picks a wave a row tf_select_rows: 128 threads launched, the runtime allows 128; 135 VGPRs, 5428 + 0 LDS bytes (recorded 135, 5428) +PASS limits live Flash Next index scores, 4 lanes a score: 128 threads launched, the runtime allows 128; 184 VGPRs, 32772 + 0 LDS bytes (recorded 184, 32772) +PASS limits live Flash Next index scores, 8 rows a wave: 256 threads launched, the runtime allows 256; 93 VGPRs, 0 + 0 LDS bytes (recorded 93, 0) +PASS limits live Flash Next HC gate table tf_hc_gate_fill: 256 threads launched, the runtime allows 256; 7 VGPRs, 0 + 0 LDS bytes (recorded 7, 0) +PASS limits live Flash Next HC mix tf_fn_hc_mix8: 256 threads launched, the runtime allows 1024; 68 VGPRs, 0 + 0 LDS bytes (recorded 68, 0) +PASS limits live Flash Next HC norm tf_fn_hc_norm_v: 128 threads launched, the runtime allows 128; 77 VGPRs, 128 + 0 LDS bytes (recorded 77, 128) +PASS limits live Flash Next HC norm with the MoE combine tf_fn_hc_norm_moe: 1024 threads launched, the runtime allows 1024; 19 VGPRs, 128 + 0 LDS bytes (recorded 19, 128) +PASS limits live Flash Next HC norm with the MoE combine, a block a row tf_fn_hc_norm_moe_v: 512 threads launched, the runtime allows 512; 59 VGPRs, 10752 + 0 LDS bytes (recorded 59, 10752) +PASS limits live DeltaNet tf_gdn_prompt_128: 128 threads launched, the runtime allows 128; 185 VGPRs, 20608 + 0 LDS bytes (recorded 185, 20608) +PASS limits live DeltaNet tf_gdn_prompt_prep: 256 threads launched, the runtime allows 256; 93 VGPRs, 0 + 0 LDS bytes (recorded 93, 0) +PASS limits live DeltaNet tf_gdn_hold_128: 256 threads launched, the runtime allows 256; 38 VGPRs, 17024 + 0 LDS bytes (recorded 38, 17024) +PASS limits live DeltaNet tf_gdn_hold_16: 256 threads launched, the runtime allows 256; 31 VGPRs, 2688 + 0 LDS bytes (recorded 31, 2688) +PASS limits live DeltaNet tf_gdn_keep_128: 256 threads launched, the runtime allows 256; 39 VGPRs, 8832 + 0 LDS bytes (recorded 39, 8832) +PASS limits live DeltaNet tf_gdn_keep_16: 256 threads launched, the runtime allows 256; 35 VGPRs, 1664 + 0 LDS bytes (recorded 35, 1664) +RED limits live control: past its bounds: 512 threads launched, the runtime allows 256; 4 VGPRs, 0 + 0 LDS bytes (recorded 4, 0) +RED limits live control: 72 KiB of LDS: 256 threads launched, the runtime allows 1024; 6 VGPRs, 40960 + 32768 LDS bytes (recorded 6, 40960) +SUMMARY gfx1151 83 kernels: 83 pass gates 1-4, 0 fail, 4 known findings; 5 controls: 5 red as planted, 0 missed; 0 limit problems; gates 134267 ms, limits 2432 ms diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/checks/hip-kernel-test.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/checks/hip-kernel-test.log new file mode 100644 index 0000000000..37e1ba16d5 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/checks/hip-kernel-test.log @@ -0,0 +1,84 @@ +hip-kernel-test ++- run test w + argmax in parts: 180 cases, the one-block argmax's ids +ORDER 27b gate_up m2048 n17408 k5120: 92c5bbcddf208589 92c5bbcddf208589 +ORDER 27b down m2048 n5120 k17408: cd67a9736943678c cd67a9736943678c +ORDER 27b linear qkv m2048 n10240 k5120: ab09bd787330b565 ab09bd787330b565 +ORDER 27b z m2048 n6144 k5120: b731da1432f3df50 b731da1432f3df50 +ORDER 27b out_proj m2048 n5120 k6144: f6bd1aee7bbe3bbe f6bd1aee7bbe3bbe +ORDER 27b q gate m2048 n12288 k5120: af06823f408f27d2 af06823f408f27d2 +ORDER 27b kv m2048 n1024 k5120: 35f71217190e92c1 35f71217190e92c1 +ORDER 27b b a m2048 n48 k5120: f4c5b05cb8940587 f4c5b05cb8940587 +ORDER edge rows m1000 n1024 k5120: 1367a2317b13dc43 1367a2317b13dc43 +ORDER edge band m1300 n6144 k5120: 675acd232e9db638 675acd232e9db638 +ORDER edge both m300 n1001 k2112: a037749cdf784c40 a037749cdf784c40 +ORDER edge column m2048 n130 k2048: 6de49bec6f65559f 6de49bec6f65559f +ORDER one row block m100 n1001 k2112: aea01224bcdbc03c aea01224bcdbc03c +ORDER one column block m300 n48 k2112: 6bbe77378a8650cf 6bbe77378a8650cf +ORDER 35b routed gate_up m2048 n1024 k2048: a26e492382043f24 a26e492382043f24 +ORDER 8-bit m1300 n4096 k2048: 7dcfc58f9684ef11 7dcfc58f9684ef11 + nemotron moe pick (bf16): pick 0.00e0, weight 3.22e-8, out 0.00e0 of bound 1.56e-2, bad 0 + nemotron moe pick (bf16): pick 0.00e0, weight 3.73e-8, out 0.00e0 of bound 1.56e-2, bad 0 + nemotron moe pick (bf16): pick 0.00e0, weight 8.02e-8, out 0.00e0 of bound 1.56e-2, bad 0 + nemotron moe pick (bf16): pick 0.00e0, weight 3.23e-8, out 0.00e0 of bound 1.56e-2, bad 0 + nemotron moe pick (bf16): pick 0.00e0, weight 1.27e-8, out 0.00e0 of bound 1.56e-2, bad 0 + nemotron moe layer (bf16): pick 0.00e0, weight 3.07e-8, out 5.47e-3 of bound 1.56e-2, bad 0 + nemotron moe layer (bf16): pick 0.00e0, weight 8.80e-8, out 5.51e-3 of bound 1.56e-2, bad 0 + nemotron moe layer lightning (bf16): pick 0.00e0, weight 2.17e-8, out 3.87e-3 of bound 1.56e-2, bad 0 + nemotron moe no bias (bf16): pick 2.03e-1, weight 3.00e-8, out 4.33e-3 of bound 1.56e-2, bad 0 + nemotron moe no norm (bf16): pick 0.00e0, weight 7.61e-1, out 3.69e0 of bound 1.56e-2, bad 0 + nemotron moe: prompt rows equal to decode rows: 13 of 16 + nemotron moe two ranks: worst 3.00e-3 of the row's largest + nemotron rank pick: 144 cases, the same bytes as the pass a pick at a time + nemotron pick, 1 rows: rank 3.72 us a launch, pass 5.22 us (back to back) + nemotron pick, 4 rows: rank 3.73 us a launch, pass 5.23 us (back to back) + nemotron pick, 16 rows: rank 3.74 us a launch, pass 5.24 us (back to back) + nemotron pick, 64 rows: rank 4.54 us a launch, pass 5.27 us (back to back) +nemotron attention q x1: 1 keys: planned 0.00e0, paged tile 0.00e0 of the float64 scale +nemotron attention q x1: 2 keys: planned 1.14e-7, paged tile 1.37e-3 of the float64 scale +nemotron attention q x1: 63 keys: planned 3.55e-7, paged tile 1.70e-3 of the float64 scale +nemotron attention q x1: 64 keys: planned 3.26e-7, paged tile 1.79e-3 of the float64 scale +nemotron attention q x1: 65 keys: planned 3.79e-7, paged tile 1.92e-3 of the float64 scale +nemotron attention q x1: 127 keys: planned 4.50e-7, paged tile 1.87e-3 of the float64 scale +nemotron attention q x1: 128 keys: planned 3.44e-7, paged tile 1.78e-3 of the float64 scale +nemotron attention q x1: 129 keys: planned 4.12e-7, paged tile 1.90e-3 of the float64 scale +nemotron attention q x1: 1000 keys: planned 3.13e-7, paged tile 1.78e-3 of the float64 scale +nemotron attention q x1: 4097 keys: planned 2.78e-7, paged tile 1.61e-3 of the float64 scale +nemotron attention q x1: 16385 keys: planned 6.60e-7, paged tile 2.47e-3 of the float64 scale +nemotron attention q x1: 65536 keys: planned 9.68e-7, paged tile 2.01e-3 of the float64 scale +nemotron attention q x16: 1 keys: planned 0.00e0, paged tile 0.00e0 of the float64 scale +nemotron attention q x16: 2 keys: planned 1.54e-7, paged tile 5.31e-4 of the float64 scale +nemotron attention q x16: 63 keys: planned 4.95e-7, paged tile 8.04e-4 of the float64 scale +nemotron attention q x16: 64 keys: planned 4.29e-7, paged tile 9.19e-4 of the float64 scale +nemotron attention q x16: 65 keys: planned 5.37e-7, paged tile 1.04e-3 of the float64 scale +nemotron attention q x16: 127 keys: planned 5.04e-7, paged tile 9.51e-4 of the float64 scale +nemotron attention q x16: 128 keys: planned 4.29e-7, paged tile 1.03e-3 of the float64 scale +nemotron attention q x16: 129 keys: planned 5.75e-7, paged tile 1.15e-3 of the float64 scale +nemotron attention q x16: 1000 keys: planned 5.21e-7, paged tile 8.50e-4 of the float64 scale +nemotron attention q x16: 4097 keys: planned 5.71e-7, paged tile 8.61e-4 of the float64 scale +nemotron attention q x16: 16385 keys: planned 7.64e-7, paged tile 1.05e-3 of the float64 scale +nemotron attention q x16: 65536 keys: planned 1.38e-6, paged tile 6.11e-4 of the float64 scale + nemotron planned walk in the activation type and in one block: the casts' bytes + nemotron planned key write from the activation type: the cast keys' bytes + nemotron moe sum + add + rms: 72 cases, the same bytes as tf_nemo_combine, tf_add and tf_rms + nemotron add + rms: 128 cases, the same bytes as tf_add and tf_rms + nemotron add + rms, 1 rows: 3.83 us merged, 8.09 us as tf_add and tf_rms, 2.13 and 5.95 alone (back to back) + nemotron add + rms, 4 rows: 3.85 us merged, 8.14 us as tf_add and tf_rms, 2.15 and 5.98 alone (back to back) + nemotron mamba window: 48 cases, the bytes of the mixer a row at a time + nemotron mamba window, 1 rows: 18.55 us the four launches, 16.09 us the window (back to back) + nemotron mamba window, 4 rows: 22.10 us the four launches, 19.64 us the window (back to back) + nemotron relu2 epilogue: 36 layers and 12 shared ups by the epilogue, the same bytes + nemotron moe layer, 1 rows: 228.0 us with the relu^2 epilogue, 241.8 us without (back to back) + nemotron moe layer, 2 rows: 404.9 us with the relu^2 epilogue, 404.9 us without (back to back) + nemotron moe layer, 3 rows: 519.3 us with the relu^2 epilogue, 518.7 us without (back to back) + nemotron moe layer, 4 rows: 643.8 us with the relu^2 epilogue, 644.1 us without (back to back) + nemotron moe layer, 8 rows: 1024.1 us with the relu^2 epilogue, 1023.9 us without (back to back) + nemotron fc1 and shared up in one launch: 8 rows, the bytes of two launches + prompt plan rows 8192 at the bound: 1212 live items, z 1212 (capacity 11777) + prompt plan rows 8192: 863 live items, z 1212 (capacity 11777) + prompt plan rows 17715 at the bound: 2031 live items, z 2031 (capacity 24871) + prompt plan rows 17715: 1790 live items, z 2031 (capacity 24871) + prompt plan rows 20480 at the bound: 2268 live items, z 2268 (capacity 28673) + prompt plan rows 20480: 1912 live items, z 2268 (capacity 28673) +failed command: ./.zig-cache/o/0f150f33db2bc1aaa5b5fb6753e51d3c/test --cache-dir=./.zig-cache --seed=0x279f6257 --listen=- + diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/checks/limits.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/checks/limits.log new file mode 100644 index 0000000000..2881e9e4a4 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/checks/limits.log @@ -0,0 +1,1006 @@ +PASS limits gfx1030 swiglu stream work list 4-bit 4x2: 161 VGPRs, 102 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 swiglu stream work list 4-bit 4x2: 163 VGPRs, 102 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 swiglu stream work list 4-bit 4x2: 163 VGPRs, 102 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 swiglu stream work list 4-bit 4x2: 163 VGPRs, 105 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD swiglu stream work list 4-bit 4x2: .usage = .{ .{ .vgprs = 161, .sgprs = 102, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 163, .sgprs = 102, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 163, .sgprs = 102, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 163, .sgprs = 105, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream work list 4-bit 4x4: 194 VGPRs, 107 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream work list 4-bit 4x4: 220 VGPRs, 107 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream work list 4-bit 4x4: 220 VGPRs, 107 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream work list 4-bit 4x4: 220 VGPRs, 107 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream work list 4-bit 4x4: .usage = .{ .{ .vgprs = 194, .sgprs = 107, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 220, .sgprs = 107, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 220, .sgprs = 107, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 220, .sgprs = 107, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 RMS norm tf_rms_rows: 58 VGPRs, 45 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1100 RMS norm tf_rms_rows: 43 VGPRs, 45 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1151 RMS norm tf_rms_rows: 42 VGPRs, 45 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1201 RMS norm tf_rms_rows: 42 VGPRs, 45 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +RECORD RMS norm tf_rms_rows: .usage = .{ .{ .vgprs = 58, .sgprs = 45, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 43, .sgprs = 45, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 42, .sgprs = 45, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 42, .sgprs = 45, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, } +PASS limits gfx1030 RMS norm rms_kernel<__half>: 11 VGPRs, 18 SGPRs, 32772 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1100 RMS norm rms_kernel<__half>: 11 VGPRs, 18 SGPRs, 32772 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1151 RMS norm rms_kernel<__half>: 10 VGPRs, 18 SGPRs, 32772 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1201 RMS norm rms_kernel<__half>: 10 VGPRs, 18 SGPRs, 32772 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +RECORD RMS norm rms_kernel<__half>: .usage = .{ .{ .vgprs = 11, .sgprs = 18, .lds = 32772, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 11, .sgprs = 18, .lds = 32772, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 10, .sgprs = 18, .lds = 32772, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 10, .sgprs = 18, .lds = 32772, .private = 0, .bound = 256, .wave = 32 }, } +PASS limits gfx1030 RMS norm rms_kernel: 11 VGPRs, 18 SGPRs, 32772 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1100 RMS norm rms_kernel: 11 VGPRs, 18 SGPRs, 32772 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1151 RMS norm rms_kernel: 10 VGPRs, 18 SGPRs, 32772 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1201 RMS norm rms_kernel: 10 VGPRs, 18 SGPRs, 32772 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +RECORD RMS norm rms_kernel: .usage = .{ .{ .vgprs = 11, .sgprs = 18, .lds = 32772, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 11, .sgprs = 18, .lds = 32772, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 10, .sgprs = 18, .lds = 32772, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 10, .sgprs = 18, .lds = 32772, .private = 0, .bound = 256, .wave = 32 }, } +PASS limits gfx1030 mamba tf_mamba_conv: 27 VGPRs, 26 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1100 mamba tf_mamba_conv: 26 VGPRs, 26 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1151 mamba tf_mamba_conv: 26 VGPRs, 26 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1201 mamba tf_mamba_conv: 26 VGPRs, 26 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +RECORD mamba tf_mamba_conv: .usage = .{ .{ .vgprs = 27, .sgprs = 26, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 26, .sgprs = 26, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 26, .sgprs = 26, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 26, .sgprs = 26, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, } +PASS limits gfx1030 mamba tf_mamba_dt: 16 VGPRs, 25 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +PASS limits gfx1100 mamba tf_mamba_dt: 16 VGPRs, 25 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +PASS limits gfx1151 mamba tf_mamba_dt: 16 VGPRs, 25 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +PASS limits gfx1201 mamba tf_mamba_dt: 16 VGPRs, 27 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +RECORD mamba tf_mamba_dt: .usage = .{ .{ .vgprs = 16, .sgprs = 25, .lds = 0, .private = 0, .bound = 1024, .wave = 32 }, .{ .vgprs = 16, .sgprs = 25, .lds = 0, .private = 0, .bound = 1024, .wave = 32 }, .{ .vgprs = 16, .sgprs = 25, .lds = 0, .private = 0, .bound = 1024, .wave = 32 }, .{ .vgprs = 16, .sgprs = 27, .lds = 0, .private = 0, .bound = 1024, .wave = 32 }, } +PASS limits gfx1030 mamba tf_mamba_scan: 127 VGPRs, 41 SGPRs, 20544 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 mamba tf_mamba_scan: 126 VGPRs, 41 SGPRs, 20544 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 mamba tf_mamba_scan: 125 VGPRs, 42 SGPRs, 20544 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 mamba tf_mamba_scan: 121 VGPRs, 42 SGPRs, 20544 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD mamba tf_mamba_scan: .usage = .{ .{ .vgprs = 127, .sgprs = 41, .lds = 20544, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 126, .sgprs = 41, .lds = 20544, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 125, .sgprs = 42, .lds = 20544, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 121, .sgprs = 42, .lds = 20544, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 mamba tf_mamba_gnorm: 23 VGPRs, 23 SGPRs, 16 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 mamba tf_mamba_gnorm: 23 VGPRs, 24 SGPRs, 16 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 mamba tf_mamba_gnorm: 23 VGPRs, 23 SGPRs, 16 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 mamba tf_mamba_gnorm: 23 VGPRs, 24 SGPRs, 16 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD mamba tf_mamba_gnorm: .usage = .{ .{ .vgprs = 23, .sgprs = 23, .lds = 16, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 23, .sgprs = 24, .lds = 16, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 23, .sgprs = 23, .lds = 16, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 23, .sgprs = 24, .lds = 16, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 nemotron tf_nemo_select: 27 VGPRs, 26 SGPRs, 8320 LDS bytes, 0 scratch bytes, bound 32, wave32 (record current) +PASS limits gfx1100 nemotron tf_nemo_select: 27 VGPRs, 26 SGPRs, 8320 LDS bytes, 0 scratch bytes, bound 32, wave32 (record current) +PASS limits gfx1151 nemotron tf_nemo_select: 27 VGPRs, 26 SGPRs, 8320 LDS bytes, 0 scratch bytes, bound 32, wave32 (record current) +PASS limits gfx1201 nemotron tf_nemo_select: 27 VGPRs, 26 SGPRs, 8320 LDS bytes, 0 scratch bytes, bound 32, wave32 (record current) +RECORD nemotron tf_nemo_select: .usage = .{ .{ .vgprs = 27, .sgprs = 26, .lds = 8320, .private = 0, .bound = 32, .wave = 32 }, .{ .vgprs = 27, .sgprs = 26, .lds = 8320, .private = 0, .bound = 32, .wave = 32 }, .{ .vgprs = 27, .sgprs = 26, .lds = 8320, .private = 0, .bound = 32, .wave = 32 }, .{ .vgprs = 27, .sgprs = 26, .lds = 8320, .private = 0, .bound = 32, .wave = 32 }, } +PASS limits gfx1030 nemotron tf_nemo_select_rank: 27 VGPRs, 30 SGPRs, 8320 LDS bytes, 0 scratch bytes, bound 512, wave32 (record current) +PASS limits gfx1100 nemotron tf_nemo_select_rank: 27 VGPRs, 30 SGPRs, 8320 LDS bytes, 0 scratch bytes, bound 512, wave32 (record current) +PASS limits gfx1151 nemotron tf_nemo_select_rank: 27 VGPRs, 30 SGPRs, 8320 LDS bytes, 0 scratch bytes, bound 512, wave32 (record current) +PASS limits gfx1201 nemotron tf_nemo_select_rank: 27 VGPRs, 29 SGPRs, 8320 LDS bytes, 0 scratch bytes, bound 512, wave32 (record current) +RECORD nemotron tf_nemo_select_rank: .usage = .{ .{ .vgprs = 27, .sgprs = 30, .lds = 8320, .private = 0, .bound = 512, .wave = 32 }, .{ .vgprs = 27, .sgprs = 30, .lds = 8320, .private = 0, .bound = 512, .wave = 32 }, .{ .vgprs = 27, .sgprs = 30, .lds = 8320, .private = 0, .bound = 512, .wave = 32 }, .{ .vgprs = 27, .sgprs = 29, .lds = 8320, .private = 0, .bound = 512, .wave = 32 }, } +PASS limits gfx1030 nemotron tf_nemo_relu2: 8 VGPRs, 9 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +PASS limits gfx1100 nemotron tf_nemo_relu2: 8 VGPRs, 18 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +PASS limits gfx1151 nemotron tf_nemo_relu2: 8 VGPRs, 10 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +PASS limits gfx1201 nemotron tf_nemo_relu2: 8 VGPRs, 10 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +RECORD nemotron tf_nemo_relu2: .usage = .{ .{ .vgprs = 8, .sgprs = 9, .lds = 0, .private = 0, .bound = 1024, .wave = 32 }, .{ .vgprs = 8, .sgprs = 18, .lds = 0, .private = 0, .bound = 1024, .wave = 32 }, .{ .vgprs = 8, .sgprs = 10, .lds = 0, .private = 0, .bound = 1024, .wave = 32 }, .{ .vgprs = 8, .sgprs = 10, .lds = 0, .private = 0, .bound = 1024, .wave = 32 }, } +PASS limits gfx1030 nemotron tf_nemo_localize: 4 VGPRs, 10 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +PASS limits gfx1100 nemotron tf_nemo_localize: 4 VGPRs, 18 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +PASS limits gfx1151 nemotron tf_nemo_localize: 4 VGPRs, 10 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +PASS limits gfx1201 nemotron tf_nemo_localize: 4 VGPRs, 9 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +RECORD nemotron tf_nemo_localize: .usage = .{ .{ .vgprs = 4, .sgprs = 10, .lds = 0, .private = 0, .bound = 1024, .wave = 32 }, .{ .vgprs = 4, .sgprs = 18, .lds = 0, .private = 0, .bound = 1024, .wave = 32 }, .{ .vgprs = 4, .sgprs = 10, .lds = 0, .private = 0, .bound = 1024, .wave = 32 }, .{ .vgprs = 4, .sgprs = 9, .lds = 0, .private = 0, .bound = 1024, .wave = 32 }, } +PASS limits gfx1030 nemotron tf_nemo_combine: 9 VGPRs, 20 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +PASS limits gfx1100 nemotron tf_nemo_combine: 10 VGPRs, 20 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +PASS limits gfx1151 nemotron tf_nemo_combine: 9 VGPRs, 20 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +PASS limits gfx1201 nemotron tf_nemo_combine: 9 VGPRs, 20 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +RECORD nemotron tf_nemo_combine: .usage = .{ .{ .vgprs = 9, .sgprs = 20, .lds = 0, .private = 0, .bound = 1024, .wave = 32 }, .{ .vgprs = 10, .sgprs = 20, .lds = 0, .private = 0, .bound = 1024, .wave = 32 }, .{ .vgprs = 9, .sgprs = 20, .lds = 0, .private = 0, .bound = 1024, .wave = 32 }, .{ .vgprs = 9, .sgprs = 20, .lds = 0, .private = 0, .bound = 1024, .wave = 32 }, } +PASS limits gfx1030 planned walk tf_plan_score_f16: 17 VGPRs, 34 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 planned walk tf_plan_score_f16: 17 VGPRs, 33 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 planned walk tf_plan_score_f16: 17 VGPRs, 34 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 planned walk tf_plan_score_f16: 17 VGPRs, 29 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD planned walk tf_plan_score_f16: .usage = .{ .{ .vgprs = 17, .sgprs = 34, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 17, .sgprs = 33, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 17, .sgprs = 34, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 17, .sgprs = 29, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 planned walk tf_plan_score_bf16: 17 VGPRs, 34 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 planned walk tf_plan_score_bf16: 17 VGPRs, 33 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 planned walk tf_plan_score_bf16: 17 VGPRs, 34 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 planned walk tf_plan_score_bf16: 17 VGPRs, 29 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD planned walk tf_plan_score_bf16: .usage = .{ .{ .vgprs = 17, .sgprs = 34, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 17, .sgprs = 33, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 17, .sgprs = 34, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 17, .sgprs = 29, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 planned walk tf_softmax_stats: 9 VGPRs, 16 SGPRs, 1024 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +PASS limits gfx1100 planned walk tf_softmax_stats: 9 VGPRs, 18 SGPRs, 1024 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +PASS limits gfx1151 planned walk tf_softmax_stats: 9 VGPRs, 16 SGPRs, 1024 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +PASS limits gfx1201 planned walk tf_softmax_stats: 9 VGPRs, 18 SGPRs, 1024 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +RECORD planned walk tf_softmax_stats: .usage = .{ .{ .vgprs = 9, .sgprs = 16, .lds = 1024, .private = 0, .bound = 1024, .wave = 32 }, .{ .vgprs = 9, .sgprs = 18, .lds = 1024, .private = 0, .bound = 1024, .wave = 32 }, .{ .vgprs = 9, .sgprs = 16, .lds = 1024, .private = 0, .bound = 1024, .wave = 32 }, .{ .vgprs = 9, .sgprs = 18, .lds = 1024, .private = 0, .bound = 1024, .wave = 32 }, } +PASS limits gfx1030 planned walk tf_plan_apply_f16: 57 VGPRs, 44 SGPRs, 8192 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1100 planned walk tf_plan_apply_f16: 57 VGPRs, 44 SGPRs, 8192 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1151 planned walk tf_plan_apply_f16: 57 VGPRs, 44 SGPRs, 8192 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1201 planned walk tf_plan_apply_f16: 57 VGPRs, 44 SGPRs, 8192 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +RECORD planned walk tf_plan_apply_f16: .usage = .{ .{ .vgprs = 57, .sgprs = 44, .lds = 8192, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 57, .sgprs = 44, .lds = 8192, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 57, .sgprs = 44, .lds = 8192, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 57, .sgprs = 44, .lds = 8192, .private = 0, .bound = 256, .wave = 32 }, } +PASS limits gfx1030 planned walk tf_plan_apply_bf16: 57 VGPRs, 44 SGPRs, 8192 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1100 planned walk tf_plan_apply_bf16: 57 VGPRs, 44 SGPRs, 8192 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1151 planned walk tf_plan_apply_bf16: 57 VGPRs, 44 SGPRs, 8192 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1201 planned walk tf_plan_apply_bf16: 57 VGPRs, 44 SGPRs, 8192 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +RECORD planned walk tf_plan_apply_bf16: .usage = .{ .{ .vgprs = 57, .sgprs = 44, .lds = 8192, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 57, .sgprs = 44, .lds = 8192, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 57, .sgprs = 44, .lds = 8192, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 57, .sgprs = 44, .lds = 8192, .private = 0, .bound = 256, .wave = 32 }, } +PASS limits gfx1030 planned walk tf_sum_partials: 5 VGPRs, 14 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +PASS limits gfx1100 planned walk tf_sum_partials: 5 VGPRs, 18 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +PASS limits gfx1151 planned walk tf_sum_partials: 5 VGPRs, 14 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +PASS limits gfx1201 planned walk tf_sum_partials: 5 VGPRs, 16 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +RECORD planned walk tf_sum_partials: .usage = .{ .{ .vgprs = 5, .sgprs = 14, .lds = 0, .private = 0, .bound = 1024, .wave = 32 }, .{ .vgprs = 5, .sgprs = 18, .lds = 0, .private = 0, .bound = 1024, .wave = 32 }, .{ .vgprs = 5, .sgprs = 14, .lds = 0, .private = 0, .bound = 1024, .wave = 32 }, .{ .vgprs = 5, .sgprs = 16, .lds = 0, .private = 0, .bound = 1024, .wave = 32 }, } +PASS limits gfx1030 add rms tf_add_rms_f16: 43 VGPRs, 40 SGPRs, 32772 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +PASS limits gfx1100 add rms tf_add_rms_f16: 45 VGPRs, 40 SGPRs, 32772 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +PASS limits gfx1151 add rms tf_add_rms_f16: 45 VGPRs, 40 SGPRs, 32772 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +PASS limits gfx1201 add rms tf_add_rms_f16: 44 VGPRs, 40 SGPRs, 32772 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +RECORD add rms tf_add_rms_f16: .usage = .{ .{ .vgprs = 43, .sgprs = 40, .lds = 32772, .private = 0, .bound = 1024, .wave = 32 }, .{ .vgprs = 45, .sgprs = 40, .lds = 32772, .private = 0, .bound = 1024, .wave = 32 }, .{ .vgprs = 45, .sgprs = 40, .lds = 32772, .private = 0, .bound = 1024, .wave = 32 }, .{ .vgprs = 44, .sgprs = 40, .lds = 32772, .private = 0, .bound = 1024, .wave = 32 }, } +PASS limits gfx1030 add rms tf_add_rms_bf16: 44 VGPRs, 40 SGPRs, 32772 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +PASS limits gfx1100 add rms tf_add_rms_bf16: 45 VGPRs, 40 SGPRs, 32772 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +PASS limits gfx1151 add rms tf_add_rms_bf16: 45 VGPRs, 40 SGPRs, 32772 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +PASS limits gfx1201 add rms tf_add_rms_bf16: 44 VGPRs, 40 SGPRs, 32772 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +RECORD add rms tf_add_rms_bf16: .usage = .{ .{ .vgprs = 44, .sgprs = 40, .lds = 32772, .private = 0, .bound = 1024, .wave = 32 }, .{ .vgprs = 45, .sgprs = 40, .lds = 32772, .private = 0, .bound = 1024, .wave = 32 }, .{ .vgprs = 45, .sgprs = 40, .lds = 32772, .private = 0, .bound = 1024, .wave = 32 }, .{ .vgprs = 44, .sgprs = 40, .lds = 32772, .private = 0, .bound = 1024, .wave = 32 }, } +PASS limits gfx1030 mamba tf_mamba_conv_window: 32 VGPRs, 42 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1100 mamba tf_mamba_conv_window: 38 VGPRs, 42 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1151 mamba tf_mamba_conv_window: 37 VGPRs, 42 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1201 mamba tf_mamba_conv_window: 37 VGPRs, 44 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +RECORD mamba tf_mamba_conv_window: .usage = .{ .{ .vgprs = 32, .sgprs = 42, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 38, .sgprs = 42, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 37, .sgprs = 42, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 37, .sgprs = 44, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, } +PASS limits gfx1030 mamba tf_mamba_scan_snap: 137 VGPRs, 50 SGPRs, 20544 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 mamba tf_mamba_scan_snap: 136 VGPRs, 50 SGPRs, 20544 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 mamba tf_mamba_scan_snap: 135 VGPRs, 51 SGPRs, 20544 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 mamba tf_mamba_scan_snap: 131 VGPRs, 52 SGPRs, 20544 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD mamba tf_mamba_scan_snap: .usage = .{ .{ .vgprs = 137, .sgprs = 50, .lds = 20544, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 136, .sgprs = 50, .lds = 20544, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 135, .sgprs = 51, .lds = 20544, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 131, .sgprs = 52, .lds = 20544, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 relu2 stream tile 4-bit 1x2: 79 VGPRs, 54 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 relu2 stream tile 4-bit 1x2: 83 VGPRs, 54 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 relu2 stream tile 4-bit 1x2: 83 VGPRs, 54 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 relu2 stream tile 4-bit 1x2: 83 VGPRs, 56 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD relu2 stream tile 4-bit 1x2: .usage = .{ .{ .vgprs = 79, .sgprs = 54, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 83, .sgprs = 54, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 83, .sgprs = 54, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 83, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 relu2 stream tile 4-bit 1x4: 112 VGPRs, 57 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 relu2 stream tile 4-bit 1x4: 121 VGPRs, 57 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 relu2 stream tile 4-bit 1x4: 121 VGPRs, 57 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 relu2 stream tile 4-bit 1x4: 121 VGPRs, 59 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD relu2 stream tile 4-bit 1x4: .usage = .{ .{ .vgprs = 112, .sgprs = 57, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 121, .sgprs = 57, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 121, .sgprs = 57, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 121, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 relu2 stream tile 4-bit 1x8: 187 VGPRs, 60 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 relu2 stream tile 4-bit 1x8: 186 VGPRs, 60 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 relu2 stream tile 4-bit 1x8: 186 VGPRs, 60 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 relu2 stream tile 4-bit 1x8: 186 VGPRs, 62 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD relu2 stream tile 4-bit 1x8: .usage = .{ .{ .vgprs = 187, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 186, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 186, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 186, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 relu2 stream tile 4-bit 2x2: 93 VGPRs, 59 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 relu2 stream tile 4-bit 2x2: 110 VGPRs, 60 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 relu2 stream tile 4-bit 2x2: 110 VGPRs, 60 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 relu2 stream tile 4-bit 2x2: 110 VGPRs, 62 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD relu2 stream tile 4-bit 2x2: .usage = .{ .{ .vgprs = 93, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 110, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 110, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 110, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 relu2 stream tile 4-bit 2x4: 112 VGPRs, 62 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 relu2 stream tile 4-bit 2x4: 135 VGPRs, 63 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 relu2 stream tile 4-bit 2x4: 135 VGPRs, 63 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 relu2 stream tile 4-bit 2x4: 135 VGPRs, 65 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD relu2 stream tile 4-bit 2x4: .usage = .{ .{ .vgprs = 112, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 135, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 135, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 135, .sgprs = 65, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 relu2 stream tile 4-bit 2x8: 164 VGPRs, 66 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 relu2 stream tile 4-bit 2x8: 248 VGPRs, 90 SGPRs, 0 LDS bytes, 304 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 relu2 stream tile 4-bit 2x8: 248 VGPRs, 90 SGPRs, 0 LDS bytes, 304 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 relu2 stream tile 4-bit 2x8: 248 VGPRs, 86 SGPRs, 0 LDS bytes, 304 scratch bytes, bound 128, wave32 (record current) +RECORD relu2 stream tile 4-bit 2x8: .usage = .{ .{ .vgprs = 164, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 248, .sgprs = 90, .lds = 0, .private = 304, .bound = 128, .wave = 32 }, .{ .vgprs = 248, .sgprs = 90, .lds = 0, .private = 304, .bound = 128, .wave = 32 }, .{ .vgprs = 248, .sgprs = 86, .lds = 0, .private = 304, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 relu2 stream tile 4-bit 4x2: 146 VGPRs, 67 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 relu2 stream tile 4-bit 4x2: 148 VGPRs, 68 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 relu2 stream tile 4-bit 4x2: 148 VGPRs, 68 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 relu2 stream tile 4-bit 4x2: 148 VGPRs, 70 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD relu2 stream tile 4-bit 4x2: .usage = .{ .{ .vgprs = 146, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 148, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 148, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 148, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 relu2 stream tile 4-bit 4x4: 176 VGPRs, 70 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 relu2 stream tile 4-bit 4x4: 181 VGPRs, 71 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 relu2 stream tile 4-bit 4x4: 181 VGPRs, 71 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 relu2 stream tile 4-bit 4x4: 181 VGPRs, 73 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD relu2 stream tile 4-bit 4x4: .usage = .{ .{ .vgprs = 176, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 181, .sgprs = 71, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 181, .sgprs = 71, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 181, .sgprs = 73, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 planned walk tf_plan_kv_write_act: 20 VGPRs, 26 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1100 planned walk tf_plan_kv_write_act: 20 VGPRs, 26 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1151 planned walk tf_plan_kv_write_act: 20 VGPRs, 26 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1201 planned walk tf_plan_kv_write_act: 20 VGPRs, 28 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +RECORD planned walk tf_plan_kv_write_act: .usage = .{ .{ .vgprs = 20, .sgprs = 26, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 20, .sgprs = 26, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 20, .sgprs = 26, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 20, .sgprs = 28, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, } +PASS limits gfx1030 planned walk tf_plan_score_act_f16: 17 VGPRs, 32 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 planned walk tf_plan_score_act_f16: 17 VGPRs, 32 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 planned walk tf_plan_score_act_f16: 17 VGPRs, 32 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 planned walk tf_plan_score_act_f16: 17 VGPRs, 28 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD planned walk tf_plan_score_act_f16: .usage = .{ .{ .vgprs = 17, .sgprs = 32, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 17, .sgprs = 32, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 17, .sgprs = 32, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 17, .sgprs = 28, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 planned walk tf_plan_score_act_bf16: 17 VGPRs, 32 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 planned walk tf_plan_score_act_bf16: 17 VGPRs, 32 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 planned walk tf_plan_score_act_bf16: 17 VGPRs, 32 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 planned walk tf_plan_score_act_bf16: 17 VGPRs, 28 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD planned walk tf_plan_score_act_bf16: .usage = .{ .{ .vgprs = 17, .sgprs = 32, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 17, .sgprs = 32, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 17, .sgprs = 32, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 17, .sgprs = 28, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 planned walk tf_sum_partials_act: 7 VGPRs, 16 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +PASS limits gfx1100 planned walk tf_sum_partials_act: 6 VGPRs, 18 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +PASS limits gfx1151 planned walk tf_sum_partials_act: 6 VGPRs, 16 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +PASS limits gfx1201 planned walk tf_sum_partials_act: 6 VGPRs, 18 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +RECORD planned walk tf_sum_partials_act: .usage = .{ .{ .vgprs = 7, .sgprs = 16, .lds = 0, .private = 0, .bound = 1024, .wave = 32 }, .{ .vgprs = 6, .sgprs = 18, .lds = 0, .private = 0, .bound = 1024, .wave = 32 }, .{ .vgprs = 6, .sgprs = 16, .lds = 0, .private = 0, .bound = 1024, .wave = 32 }, .{ .vgprs = 6, .sgprs = 18, .lds = 0, .private = 0, .bound = 1024, .wave = 32 }, } +PASS limits gfx1030 argmax tf_argmax_part: 8 VGPRs, 17 SGPRs, 2048 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1100 argmax tf_argmax_part: 8 VGPRs, 18 SGPRs, 2048 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1151 argmax tf_argmax_part: 8 VGPRs, 17 SGPRs, 2048 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1201 argmax tf_argmax_part: 8 VGPRs, 16 SGPRs, 2048 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +RECORD argmax tf_argmax_part: .usage = .{ .{ .vgprs = 8, .sgprs = 17, .lds = 2048, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 8, .sgprs = 18, .lds = 2048, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 8, .sgprs = 17, .lds = 2048, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 8, .sgprs = 16, .lds = 2048, .private = 0, .bound = 256, .wave = 32 }, } +PASS limits gfx1030 top-k tf_topk_part: 33 VGPRs, 36 SGPRs, 1296 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +PASS limits gfx1100 top-k tf_topk_part: 78 VGPRs, 36 SGPRs, 1296 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +PASS limits gfx1151 top-k tf_topk_part: 78 VGPRs, 36 SGPRs, 1296 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +PASS limits gfx1201 top-k tf_topk_part: 78 VGPRs, 36 SGPRs, 1296 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +RECORD top-k tf_topk_part: .usage = .{ .{ .vgprs = 33, .sgprs = 36, .lds = 1296, .private = 0, .bound = 1024, .wave = 32 }, .{ .vgprs = 78, .sgprs = 36, .lds = 1296, .private = 0, .bound = 1024, .wave = 32 }, .{ .vgprs = 78, .sgprs = 36, .lds = 1296, .private = 0, .bound = 1024, .wave = 32 }, .{ .vgprs = 78, .sgprs = 36, .lds = 1296, .private = 0, .bound = 1024, .wave = 32 }, } +PASS limits gfx1030 top-k tf_topk_join: 16 VGPRs, 36 SGPRs, 33808 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +PASS limits gfx1100 top-k tf_topk_join: 16 VGPRs, 36 SGPRs, 33808 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +PASS limits gfx1151 top-k tf_topk_join: 16 VGPRs, 36 SGPRs, 33808 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +PASS limits gfx1201 top-k tf_topk_join: 16 VGPRs, 37 SGPRs, 33808 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +RECORD top-k tf_topk_join: .usage = .{ .{ .vgprs = 16, .sgprs = 36, .lds = 33808, .private = 0, .bound = 1024, .wave = 32 }, .{ .vgprs = 16, .sgprs = 36, .lds = 33808, .private = 0, .bound = 1024, .wave = 32 }, .{ .vgprs = 16, .sgprs = 36, .lds = 33808, .private = 0, .bound = 1024, .wave = 32 }, .{ .vgprs = 16, .sgprs = 37, .lds = 33808, .private = 0, .bound = 1024, .wave = 32 }, } +PASS limits gfx1030 argmax tf_argmax_join: 10 VGPRs, 21 SGPRs, 2048 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1100 argmax tf_argmax_join: 10 VGPRs, 21 SGPRs, 2048 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1151 argmax tf_argmax_join: 10 VGPRs, 21 SGPRs, 2048 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1201 argmax tf_argmax_join: 10 VGPRs, 20 SGPRs, 2048 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +RECORD argmax tf_argmax_join: .usage = .{ .{ .vgprs = 10, .sgprs = 21, .lds = 2048, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 10, .sgprs = 21, .lds = 2048, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 10, .sgprs = 21, .lds = 2048, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 10, .sgprs = 20, .lds = 2048, .private = 0, .bound = 256, .wave = 32 }, } +PASS limits gfx1030 planned walk tf_plan_attend_f16: 38 VGPRs, 32 SGPRs, 50688 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +PASS limits gfx1100 planned walk tf_plan_attend_f16: 38 VGPRs, 32 SGPRs, 50688 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +PASS limits gfx1151 planned walk tf_plan_attend_f16: 38 VGPRs, 32 SGPRs, 50688 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +PASS limits gfx1201 planned walk tf_plan_attend_f16: 38 VGPRs, 32 SGPRs, 50688 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +RECORD planned walk tf_plan_attend_f16: .usage = .{ .{ .vgprs = 38, .sgprs = 32, .lds = 50688, .private = 0, .bound = 1024, .wave = 32 }, .{ .vgprs = 38, .sgprs = 32, .lds = 50688, .private = 0, .bound = 1024, .wave = 32 }, .{ .vgprs = 38, .sgprs = 32, .lds = 50688, .private = 0, .bound = 1024, .wave = 32 }, .{ .vgprs = 38, .sgprs = 32, .lds = 50688, .private = 0, .bound = 1024, .wave = 32 }, } +PASS limits gfx1030 planned walk tf_plan_attend_bf16: 36 VGPRs, 32 SGPRs, 50688 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +PASS limits gfx1100 planned walk tf_plan_attend_bf16: 37 VGPRs, 32 SGPRs, 50688 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +PASS limits gfx1151 planned walk tf_plan_attend_bf16: 36 VGPRs, 32 SGPRs, 50688 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +PASS limits gfx1201 planned walk tf_plan_attend_bf16: 36 VGPRs, 32 SGPRs, 50688 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +RECORD planned walk tf_plan_attend_bf16: .usage = .{ .{ .vgprs = 36, .sgprs = 32, .lds = 50688, .private = 0, .bound = 1024, .wave = 32 }, .{ .vgprs = 37, .sgprs = 32, .lds = 50688, .private = 0, .bound = 1024, .wave = 32 }, .{ .vgprs = 36, .sgprs = 32, .lds = 50688, .private = 0, .bound = 1024, .wave = 32 }, .{ .vgprs = 36, .sgprs = 32, .lds = 50688, .private = 0, .bound = 1024, .wave = 32 }, } +PASS limits gfx1030 MoE router (decode, fp32 rows) tf_router_decode_f16: 106 VGPRs, 75 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 MoE router (decode, fp32 rows) tf_router_decode_f16: 90 VGPRs, 75 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 MoE router (decode, fp32 rows) tf_router_decode_f16: 90 VGPRs, 75 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 MoE router (decode, fp32 rows) tf_router_decode_f16: 90 VGPRs, 76 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD MoE router (decode, fp32 rows) tf_router_decode_f16: .usage = .{ .{ .vgprs = 106, .sgprs = 75, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 90, .sgprs = 75, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 90, .sgprs = 75, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 90, .sgprs = 76, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 MoE router (decode, fp32 rows) tf_router_decode_bf16: 106 VGPRs, 75 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 MoE router (decode, fp32 rows) tf_router_decode_bf16: 91 VGPRs, 75 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 MoE router (decode, fp32 rows) tf_router_decode_bf16: 91 VGPRs, 75 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 MoE router (decode, fp32 rows) tf_router_decode_bf16: 91 VGPRs, 76 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD MoE router (decode, fp32 rows) tf_router_decode_bf16: .usage = .{ .{ .vgprs = 106, .sgprs = 75, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 91, .sgprs = 75, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 91, .sgprs = 75, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 91, .sgprs = 76, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 MoE router and pick in one launch (decode, bf16 rows) tf_router_select_f16: 135 VGPRs, 86 SGPRs, 5456 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 MoE router and pick in one launch (decode, bf16 rows) tf_router_select_f16: 135 VGPRs, 82 SGPRs, 5456 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 MoE router and pick in one launch (decode, bf16 rows) tf_router_select_f16: 135 VGPRs, 82 SGPRs, 5456 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 MoE router and pick in one launch (decode, bf16 rows) tf_router_select_f16: 135 VGPRs, 83 SGPRs, 5456 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD MoE router and pick in one launch (decode, bf16 rows) tf_router_select_f16: .usage = .{ .{ .vgprs = 135, .sgprs = 86, .lds = 5456, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 135, .sgprs = 82, .lds = 5456, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 135, .sgprs = 82, .lds = 5456, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 135, .sgprs = 83, .lds = 5456, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 MoE router and pick in one launch (decode, bf16 rows) tf_router_select_bf16: 135 VGPRs, 86 SGPRs, 5456 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 MoE router and pick in one launch (decode, bf16 rows) tf_router_select_bf16: 135 VGPRs, 82 SGPRs, 5456 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 MoE router and pick in one launch (decode, bf16 rows) tf_router_select_bf16: 135 VGPRs, 82 SGPRs, 5456 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 MoE router and pick in one launch (decode, bf16 rows) tf_router_select_bf16: 135 VGPRs, 83 SGPRs, 5456 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD MoE router and pick in one launch (decode, bf16 rows) tf_router_select_bf16: .usage = .{ .{ .vgprs = 135, .sgprs = 86, .lds = 5456, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 135, .sgprs = 82, .lds = 5456, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 135, .sgprs = 82, .lds = 5456, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 135, .sgprs = 83, .lds = 5456, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 MoE down codes read beside the gate and up (side stream) tf_moe_prefetch: 11 VGPRs, 20 SGPRs, 260 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1100 MoE down codes read beside the gate and up (side stream) tf_moe_prefetch: 11 VGPRs, 20 SGPRs, 260 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1151 MoE down codes read beside the gate and up (side stream) tf_moe_prefetch: 11 VGPRs, 20 SGPRs, 260 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1201 MoE down codes read beside the gate and up (side stream) tf_moe_prefetch: 11 VGPRs, 18 SGPRs, 260 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +RECORD MoE down codes read beside the gate and up (side stream) tf_moe_prefetch: .usage = .{ .{ .vgprs = 11, .sgprs = 20, .lds = 260, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 11, .sgprs = 20, .lds = 260, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 11, .sgprs = 20, .lds = 260, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 11, .sgprs = 18, .lds = 260, .private = 0, .bound = 256, .wave = 32 }, } +N/A limits gfx1030 prompt expert gate+up tile 4-bit: not launched on this chip +PASS limits gfx1100 prompt expert gate+up tile 4-bit: 226 VGPRs, 34 SGPRs, 36352 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1151 prompt expert gate+up tile 4-bit: 225 VGPRs, 36 SGPRs, 36352 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +N/A limits gfx1201 prompt expert gate+up tile 4-bit: not launched on this chip +RECORD prompt expert gate+up tile 4-bit: .usage = .{ .{ .vgprs = 0, .sgprs = 0, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 226, .sgprs = 34, .lds = 36352, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 225, .sgprs = 36, .lds = 36352, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 0, .sgprs = 0, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, } +N/A limits gfx1030 prompt expert down tile 4-bit: not launched on this chip +PASS limits gfx1100 prompt expert down tile 4-bit: 189 VGPRs, 33 SGPRs, 32256 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1151 prompt expert down tile 4-bit: 189 VGPRs, 34 SGPRs, 32256 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +N/A limits gfx1201 prompt expert down tile 4-bit: not launched on this chip +RECORD prompt expert down tile 4-bit: .usage = .{ .{ .vgprs = 0, .sgprs = 0, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 189, .sgprs = 33, .lds = 32256, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 189, .sgprs = 34, .lds = 32256, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 0, .sgprs = 0, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, } +N/A limits gfx1030 prompt dense tile 4-bit K 320: not launched on this chip +PASS limits gfx1100 prompt dense tile 4-bit K 320: 208 VGPRs, 22 SGPRs, 39936 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1151 prompt dense tile 4-bit K 320: 208 VGPRs, 22 SGPRs, 39936 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +N/A limits gfx1201 prompt dense tile 4-bit K 320: not launched on this chip +RECORD prompt dense tile 4-bit K 320: .usage = .{ .{ .vgprs = 0, .sgprs = 0, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 208, .sgprs = 22, .lds = 39936, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 208, .sgprs = 22, .lds = 39936, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 0, .sgprs = 0, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, } +N/A limits gfx1030 prompt dense tile 4-bit K 320 with the HC mix: not launched on this chip +PASS limits gfx1100 prompt dense tile 4-bit K 320 with the HC mix: 215 VGPRs, 23 SGPRs, 39936 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1151 prompt dense tile 4-bit K 320 with the HC mix: 215 VGPRs, 23 SGPRs, 39936 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +N/A limits gfx1201 prompt dense tile 4-bit K 320 with the HC mix: not launched on this chip +RECORD prompt dense tile 4-bit K 320 with the HC mix: .usage = .{ .{ .vgprs = 0, .sgprs = 0, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 215, .sgprs = 23, .lds = 39936, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 215, .sgprs = 23, .lds = 39936, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 0, .sgprs = 0, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, } +N/A limits gfx1030 prompt dense tile 4-bit K 2560: not launched on this chip +PASS limits gfx1100 prompt dense tile 4-bit K 2560: 208 VGPRs, 22 SGPRs, 39936 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1151 prompt dense tile 4-bit K 2560: 208 VGPRs, 22 SGPRs, 39936 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +N/A limits gfx1201 prompt dense tile 4-bit K 2560: not launched on this chip +RECORD prompt dense tile 4-bit K 2560: .usage = .{ .{ .vgprs = 0, .sgprs = 0, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 208, .sgprs = 22, .lds = 39936, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 208, .sgprs = 22, .lds = 39936, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 0, .sgprs = 0, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, } +N/A limits gfx1030 prompt dense tile 4-bit K 6144: not launched on this chip +PASS limits gfx1100 prompt dense tile 4-bit K 6144: 208 VGPRs, 22 SGPRs, 39936 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1151 prompt dense tile 4-bit K 6144: 208 VGPRs, 22 SGPRs, 39936 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +N/A limits gfx1201 prompt dense tile 4-bit K 6144: not launched on this chip +RECORD prompt dense tile 4-bit K 6144: .usage = .{ .{ .vgprs = 0, .sgprs = 0, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 208, .sgprs = 22, .lds = 39936, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 208, .sgprs = 22, .lds = 39936, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 0, .sgprs = 0, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, } +N/A limits gfx1030 prompt dense tile 4-bit K 10240: not launched on this chip +PASS limits gfx1100 prompt dense tile 4-bit K 10240: 246 VGPRs, 22 SGPRs, 39936 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1151 prompt dense tile 4-bit K 10240: 246 VGPRs, 22 SGPRs, 39936 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +N/A limits gfx1201 prompt dense tile 4-bit K 10240: not launched on this chip +RECORD prompt dense tile 4-bit K 10240: .usage = .{ .{ .vgprs = 0, .sgprs = 0, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 246, .sgprs = 22, .lds = 39936, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 246, .sgprs = 22, .lds = 39936, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 0, .sgprs = 0, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, } +PASS limits gfx1030 Flash Next QSA decode prep: 36 VGPRs, 50 SGPRs, 17440 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1100 Flash Next QSA decode prep: 43 VGPRs, 50 SGPRs, 17440 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1151 Flash Next QSA decode prep: 34 VGPRs, 52 SGPRs, 17440 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1201 Flash Next QSA decode prep: 34 VGPRs, 51 SGPRs, 17440 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +RECORD Flash Next QSA decode prep: .usage = .{ .{ .vgprs = 36, .sgprs = 50, .lds = 17440, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 43, .sgprs = 50, .lds = 17440, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 34, .sgprs = 52, .lds = 17440, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 34, .sgprs = 51, .lds = 17440, .private = 0, .bound = 256, .wave = 32 }, } +PASS limits gfx1030 relu2 pair tile 4-bit 1x2: 81 VGPRs, 62 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 relu2 pair tile 4-bit 1x2: 83 VGPRs, 61 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 relu2 pair tile 4-bit 1x2: 83 VGPRs, 61 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 relu2 pair tile 4-bit 1x2: 83 VGPRs, 61 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD relu2 pair tile 4-bit 1x2: .usage = .{ .{ .vgprs = 81, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 83, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 83, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 83, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 relu2 pair tile 4-bit 1x4: 113 VGPRs, 65 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 relu2 pair tile 4-bit 1x4: 121 VGPRs, 64 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 relu2 pair tile 4-bit 1x4: 121 VGPRs, 64 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 relu2 pair tile 4-bit 1x4: 121 VGPRs, 64 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD relu2 pair tile 4-bit 1x4: .usage = .{ .{ .vgprs = 113, .sgprs = 65, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 121, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 121, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 121, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 relu2 pair tile 4-bit 1x8: 187 VGPRs, 68 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 relu2 pair tile 4-bit 1x8: 186 VGPRs, 67 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 relu2 pair tile 4-bit 1x8: 186 VGPRs, 67 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 relu2 pair tile 4-bit 1x8: 186 VGPRs, 67 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD relu2 pair tile 4-bit 1x8: .usage = .{ .{ .vgprs = 187, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 186, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 186, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 186, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 relu2 pair tile 4-bit 2x2: 93 VGPRs, 67 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 relu2 pair tile 4-bit 2x2: 109 VGPRs, 68 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 relu2 pair tile 4-bit 2x2: 109 VGPRs, 68 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 relu2 pair tile 4-bit 2x2: 109 VGPRs, 67 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD relu2 pair tile 4-bit 2x2: .usage = .{ .{ .vgprs = 93, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 109, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 109, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 109, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 relu2 pair tile 4-bit 2x4: 119 VGPRs, 70 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 relu2 pair tile 4-bit 2x4: 135 VGPRs, 71 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 relu2 pair tile 4-bit 2x4: 135 VGPRs, 71 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 relu2 pair tile 4-bit 2x4: 135 VGPRs, 70 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD relu2 pair tile 4-bit 2x4: .usage = .{ .{ .vgprs = 119, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 135, .sgprs = 71, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 135, .sgprs = 71, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 135, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 relu2 pair tile 4-bit 2x8: 164 VGPRs, 74 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 relu2 pair tile 4-bit 2x8: 248 VGPRs, 74 SGPRs, 0 LDS bytes, 416 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 relu2 pair tile 4-bit 2x8: 248 VGPRs, 74 SGPRs, 0 LDS bytes, 416 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 relu2 pair tile 4-bit 2x8: 248 VGPRs, 74 SGPRs, 0 LDS bytes, 416 scratch bytes, bound 128, wave32 (record current) +RECORD relu2 pair tile 4-bit 2x8: .usage = .{ .{ .vgprs = 164, .sgprs = 74, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 248, .sgprs = 74, .lds = 0, .private = 416, .bound = 128, .wave = 32 }, .{ .vgprs = 248, .sgprs = 74, .lds = 0, .private = 416, .bound = 128, .wave = 32 }, .{ .vgprs = 248, .sgprs = 74, .lds = 0, .private = 416, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 relu2 pair tile 4-bit 4x2: 146 VGPRs, 75 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 relu2 pair tile 4-bit 4x2: 148 VGPRs, 76 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 relu2 pair tile 4-bit 4x2: 148 VGPRs, 76 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 relu2 pair tile 4-bit 4x2: 148 VGPRs, 75 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD relu2 pair tile 4-bit 4x2: .usage = .{ .{ .vgprs = 146, .sgprs = 75, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 148, .sgprs = 76, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 148, .sgprs = 76, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 148, .sgprs = 75, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 relu2 pair tile 4-bit 4x4: 177 VGPRs, 78 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 relu2 pair tile 4-bit 4x4: 181 VGPRs, 79 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 relu2 pair tile 4-bit 4x4: 181 VGPRs, 79 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 relu2 pair tile 4-bit 4x4: 181 VGPRs, 78 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD relu2 pair tile 4-bit 4x4: .usage = .{ .{ .vgprs = 177, .sgprs = 78, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 181, .sgprs = 79, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 181, .sgprs = 79, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 181, .sgprs = 78, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 2-bit 1x1: 57 VGPRs, 55 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 2-bit 1x1: 56 VGPRs, 54 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 2-bit 1x1: 56 VGPRs, 54 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 2-bit 1x1: 56 VGPRs, 56 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 2-bit 1x1: .usage = .{ .{ .vgprs = 57, .sgprs = 55, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 56, .sgprs = 54, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 56, .sgprs = 54, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 56, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 2-bit 1x2: 59 VGPRs, 57 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 2-bit 1x2: 73 VGPRs, 57 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 2-bit 1x2: 73 VGPRs, 57 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 2-bit 1x2: 73 VGPRs, 59 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 2-bit 1x2: .usage = .{ .{ .vgprs = 59, .sgprs = 57, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 73, .sgprs = 57, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 73, .sgprs = 57, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 73, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 2-bit 1x4: 94 VGPRs, 58 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 2-bit 1x4: 94 VGPRs, 58 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 2-bit 1x4: 94 VGPRs, 58 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 2-bit 1x4: 94 VGPRs, 60 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 2-bit 1x4: .usage = .{ .{ .vgprs = 94, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 94, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 94, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 94, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 2-bit 1x8: 154 VGPRs, 62 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 2-bit 1x8: 154 VGPRs, 62 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 2-bit 1x8: 154 VGPRs, 62 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 2-bit 1x8: 154 VGPRs, 64 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 2-bit 1x8: .usage = .{ .{ .vgprs = 154, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 154, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 154, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 154, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 2-bit 2x1: 74 VGPRs, 62 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 2-bit 2x1: 69 VGPRs, 64 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 2-bit 2x1: 69 VGPRs, 64 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 2-bit 2x1: 69 VGPRs, 67 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 2-bit 2x1: .usage = .{ .{ .vgprs = 74, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 69, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 69, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 69, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 2-bit 2x2: 85 VGPRs, 62 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 2-bit 2x2: 108 VGPRs, 63 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 2-bit 2x2: 108 VGPRs, 63 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 2-bit 2x2: 108 VGPRs, 66 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 2-bit 2x2: .usage = .{ .{ .vgprs = 85, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 108, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 108, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 108, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 2-bit 2x4: 112 VGPRs, 63 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 2-bit 2x4: 130 VGPRs, 64 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 2-bit 2x4: 130 VGPRs, 64 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 2-bit 2x4: 130 VGPRs, 67 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 2-bit 2x4: .usage = .{ .{ .vgprs = 112, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 130, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 130, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 130, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 2-bit 2x8: 151 VGPRs, 68 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 2-bit 2x8: 175 VGPRs, 69 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 2-bit 2x8: 175 VGPRs, 69 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 2-bit 2x8: 175 VGPRs, 72 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 2-bit 2x8: .usage = .{ .{ .vgprs = 151, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 175, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 175, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 175, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 2-bit 4x1: 128 VGPRs, 70 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 2-bit 4x1: 119 VGPRs, 72 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 2-bit 4x1: 119 VGPRs, 72 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 2-bit 4x1: 119 VGPRs, 75 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 2-bit 4x1: .usage = .{ .{ .vgprs = 128, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 119, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 119, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 119, .sgprs = 75, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 2-bit 4x2: 143 VGPRs, 70 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 2-bit 4x2: 147 VGPRs, 71 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 2-bit 4x2: 147 VGPRs, 71 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 2-bit 4x2: 147 VGPRs, 74 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 2-bit 4x2: .usage = .{ .{ .vgprs = 143, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 147, .sgprs = 71, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 147, .sgprs = 71, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 147, .sgprs = 74, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 2-bit 4x4: 149 VGPRs, 71 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 2-bit 4x4: 173 VGPRs, 72 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 2-bit 4x4: 173 VGPRs, 72 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 2-bit 4x4: 173 VGPRs, 75 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 2-bit 4x4: .usage = .{ .{ .vgprs = 149, .sgprs = 71, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 173, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 173, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 173, .sgprs = 75, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 3-bit 1x1: 71 VGPRs, 51 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 3-bit 1x1: 58 VGPRs, 50 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 3-bit 1x1: 58 VGPRs, 50 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 3-bit 1x1: 58 VGPRs, 50 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 3-bit 1x1: .usage = .{ .{ .vgprs = 71, .sgprs = 51, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 58, .sgprs = 50, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 58, .sgprs = 50, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 58, .sgprs = 50, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 3-bit 1x2: 70 VGPRs, 53 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 3-bit 1x2: 77 VGPRs, 54 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 3-bit 1x2: 77 VGPRs, 54 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 3-bit 1x2: 77 VGPRs, 54 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 3-bit 1x2: .usage = .{ .{ .vgprs = 70, .sgprs = 53, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 77, .sgprs = 54, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 77, .sgprs = 54, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 77, .sgprs = 54, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 3-bit 1x4: 95 VGPRs, 55 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 3-bit 1x4: 97 VGPRs, 56 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 3-bit 1x4: 97 VGPRs, 56 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 3-bit 1x4: 97 VGPRs, 56 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 3-bit 1x4: .usage = .{ .{ .vgprs = 95, .sgprs = 55, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 97, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 97, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 97, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 3-bit 1x8: 171 VGPRs, 58 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 3-bit 1x8: 165 VGPRs, 59 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 3-bit 1x8: 165 VGPRs, 59 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 3-bit 1x8: 165 VGPRs, 59 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 3-bit 1x8: .usage = .{ .{ .vgprs = 171, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 165, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 165, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 165, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 3-bit 2x1: 83 VGPRs, 57 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 3-bit 2x1: 96 VGPRs, 60 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 3-bit 2x1: 96 VGPRs, 60 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 3-bit 2x1: 96 VGPRs, 61 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 3-bit 2x1: .usage = .{ .{ .vgprs = 83, .sgprs = 57, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 96, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 96, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 96, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 3-bit 2x2: 76 VGPRs, 58 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 3-bit 2x2: 109 VGPRs, 60 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 3-bit 2x2: 109 VGPRs, 60 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 3-bit 2x2: 109 VGPRs, 61 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 3-bit 2x2: .usage = .{ .{ .vgprs = 76, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 109, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 109, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 109, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 3-bit 2x4: 95 VGPRs, 60 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 3-bit 2x4: 133 VGPRs, 62 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 3-bit 2x4: 133 VGPRs, 62 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 3-bit 2x4: 133 VGPRs, 63 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 3-bit 2x4: .usage = .{ .{ .vgprs = 95, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 133, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 133, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 133, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 3-bit 2x8: 143 VGPRs, 64 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 3-bit 2x8: 180 VGPRs, 66 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 3-bit 2x8: 180 VGPRs, 66 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 3-bit 2x8: 180 VGPRs, 67 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 3-bit 2x8: .usage = .{ .{ .vgprs = 143, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 180, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 180, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 180, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 3-bit 4x1: 124 VGPRs, 65 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 3-bit 4x1: 132 VGPRs, 68 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 3-bit 4x1: 132 VGPRs, 68 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 3-bit 4x1: 132 VGPRs, 69 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 3-bit 4x1: .usage = .{ .{ .vgprs = 124, .sgprs = 65, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 132, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 132, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 132, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 3-bit 4x2: 108 VGPRs, 66 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 3-bit 4x2: 146 VGPRs, 68 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 3-bit 4x2: 146 VGPRs, 68 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 3-bit 4x2: 146 VGPRs, 69 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 3-bit 4x2: .usage = .{ .{ .vgprs = 108, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 146, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 146, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 146, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 3-bit 4x4: 142 VGPRs, 68 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 3-bit 4x4: 174 VGPRs, 70 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 3-bit 4x4: 174 VGPRs, 70 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 3-bit 4x4: 174 VGPRs, 71 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 3-bit 4x4: .usage = .{ .{ .vgprs = 142, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 174, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 174, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 174, .sgprs = 71, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 4-bit 1x1: 59 VGPRs, 55 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 4-bit 1x1: 60 VGPRs, 54 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 4-bit 1x1: 60 VGPRs, 54 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 4-bit 1x1: 60 VGPRs, 56 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 4-bit 1x1: .usage = .{ .{ .vgprs = 59, .sgprs = 55, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 60, .sgprs = 54, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 60, .sgprs = 54, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 60, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 4-bit 1x2: 79 VGPRs, 56 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 4-bit 1x2: 83 VGPRs, 56 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 4-bit 1x2: 83 VGPRs, 56 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 4-bit 1x2: 83 VGPRs, 58 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 4-bit 1x2: .usage = .{ .{ .vgprs = 79, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 83, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 83, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 83, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 4-bit 1x4: 112 VGPRs, 59 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 4-bit 1x4: 121 VGPRs, 59 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 4-bit 1x4: 121 VGPRs, 59 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 4-bit 1x4: 121 VGPRs, 61 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 4-bit 1x4: .usage = .{ .{ .vgprs = 112, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 121, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 121, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 121, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 4-bit 1x8: 187 VGPRs, 62 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 4-bit 1x8: 186 VGPRs, 62 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 4-bit 1x8: 186 VGPRs, 62 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 4-bit 1x8: 186 VGPRs, 64 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 4-bit 1x8: .usage = .{ .{ .vgprs = 187, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 186, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 186, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 186, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 4-bit 2x1: 75 VGPRs, 62 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 4-bit 2x1: 98 VGPRs, 64 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 4-bit 2x1: 98 VGPRs, 64 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 4-bit 2x1: 98 VGPRs, 67 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 4-bit 2x1: .usage = .{ .{ .vgprs = 75, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 98, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 98, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 98, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 4-bit 2x2: 88 VGPRs, 61 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 4-bit 2x2: 110 VGPRs, 62 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 4-bit 2x2: 110 VGPRs, 62 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 4-bit 2x2: 110 VGPRs, 65 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 4-bit 2x2: .usage = .{ .{ .vgprs = 88, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 110, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 110, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 110, .sgprs = 65, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 4-bit 2x4: 114 VGPRs, 64 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 4-bit 2x4: 135 VGPRs, 65 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 4-bit 2x4: 135 VGPRs, 65 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 4-bit 2x4: 135 VGPRs, 68 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 4-bit 2x4: .usage = .{ .{ .vgprs = 114, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 135, .sgprs = 65, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 135, .sgprs = 65, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 135, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 4-bit 2x8: 164 VGPRs, 68 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 4-bit 2x8: 188 VGPRs, 69 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 4-bit 2x8: 188 VGPRs, 69 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 4-bit 2x8: 188 VGPRs, 72 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 4-bit 2x8: .usage = .{ .{ .vgprs = 164, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 188, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 188, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 188, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 4-bit 4x1: 126 VGPRs, 70 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 4-bit 4x1: 134 VGPRs, 72 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 4-bit 4x1: 134 VGPRs, 72 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 4-bit 4x1: 134 VGPRs, 75 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 4-bit 4x1: .usage = .{ .{ .vgprs = 126, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 134, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 134, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 134, .sgprs = 75, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 4-bit 4x2: 146 VGPRs, 69 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 4-bit 4x2: 148 VGPRs, 70 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 4-bit 4x2: 148 VGPRs, 70 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 4-bit 4x2: 148 VGPRs, 73 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 4-bit 4x2: .usage = .{ .{ .vgprs = 146, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 148, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 148, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 148, .sgprs = 73, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 4-bit 4x4: 180 VGPRs, 72 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 4-bit 4x4: 181 VGPRs, 73 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 4-bit 4x4: 181 VGPRs, 73 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 4-bit 4x4: 181 VGPRs, 76 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 4-bit 4x4: .usage = .{ .{ .vgprs = 180, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 181, .sgprs = 73, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 181, .sgprs = 73, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 181, .sgprs = 76, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 5-bit 1x1: 74 VGPRs, 51 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 5-bit 1x1: 62 VGPRs, 50 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 5-bit 1x1: 62 VGPRs, 50 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 5-bit 1x1: 62 VGPRs, 50 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 5-bit 1x1: .usage = .{ .{ .vgprs = 74, .sgprs = 51, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 62, .sgprs = 50, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 62, .sgprs = 50, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 62, .sgprs = 50, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 5-bit 1x2: 71 VGPRs, 53 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 5-bit 1x2: 80 VGPRs, 54 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 5-bit 1x2: 80 VGPRs, 54 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 5-bit 1x2: 80 VGPRs, 54 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 5-bit 1x2: .usage = .{ .{ .vgprs = 71, .sgprs = 53, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 80, .sgprs = 54, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 80, .sgprs = 54, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 80, .sgprs = 54, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 5-bit 1x4: 111 VGPRs, 55 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 5-bit 1x4: 113 VGPRs, 56 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 5-bit 1x4: 113 VGPRs, 56 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 5-bit 1x4: 113 VGPRs, 56 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 5-bit 1x4: .usage = .{ .{ .vgprs = 111, .sgprs = 55, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 113, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 113, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 113, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 5-bit 1x8: 202 VGPRs, 58 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 5-bit 1x8: 197 VGPRs, 59 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 5-bit 1x8: 197 VGPRs, 59 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 5-bit 1x8: 197 VGPRs, 59 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 5-bit 1x8: .usage = .{ .{ .vgprs = 202, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 197, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 197, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 197, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 5-bit 2x1: 83 VGPRs, 57 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 5-bit 2x1: 96 VGPRs, 60 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 5-bit 2x1: 96 VGPRs, 60 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 5-bit 2x1: 96 VGPRs, 61 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 5-bit 2x1: .usage = .{ .{ .vgprs = 83, .sgprs = 57, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 96, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 96, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 96, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 5-bit 2x2: 78 VGPRs, 58 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 5-bit 2x2: 113 VGPRs, 60 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 5-bit 2x2: 113 VGPRs, 60 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 5-bit 2x2: 113 VGPRs, 61 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 5-bit 2x2: .usage = .{ .{ .vgprs = 78, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 113, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 113, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 113, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 5-bit 2x4: 106 VGPRs, 60 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 5-bit 2x4: 141 VGPRs, 62 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 5-bit 2x4: 141 VGPRs, 62 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 5-bit 2x4: 141 VGPRs, 63 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 5-bit 2x4: .usage = .{ .{ .vgprs = 106, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 141, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 141, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 141, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 5-bit 2x8: 157 VGPRs, 64 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 5-bit 2x8: 194 VGPRs, 66 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 5-bit 2x8: 194 VGPRs, 66 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 5-bit 2x8: 194 VGPRs, 67 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 5-bit 2x8: .usage = .{ .{ .vgprs = 157, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 194, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 194, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 194, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 5-bit 4x1: 124 VGPRs, 65 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 5-bit 4x1: 132 VGPRs, 68 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 5-bit 4x1: 132 VGPRs, 68 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 5-bit 4x1: 132 VGPRs, 69 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 5-bit 4x1: .usage = .{ .{ .vgprs = 124, .sgprs = 65, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 132, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 132, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 132, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 5-bit 4x2: 115 VGPRs, 66 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 5-bit 4x2: 149 VGPRs, 68 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 5-bit 4x2: 149 VGPRs, 68 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 5-bit 4x2: 149 VGPRs, 69 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 5-bit 4x2: .usage = .{ .{ .vgprs = 115, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 149, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 149, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 149, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 5-bit 4x4: 147 VGPRs, 68 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 5-bit 4x4: 180 VGPRs, 70 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 5-bit 4x4: 180 VGPRs, 70 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 5-bit 4x4: 181 VGPRs, 71 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 5-bit 4x4: .usage = .{ .{ .vgprs = 147, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 180, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 180, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 181, .sgprs = 71, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 6-bit 1x1: 64 VGPRs, 58 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 6-bit 1x1: 64 VGPRs, 57 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 6-bit 1x1: 64 VGPRs, 57 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 6-bit 1x1: 64 VGPRs, 57 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 6-bit 1x1: .usage = .{ .{ .vgprs = 64, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 64, .sgprs = 57, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 64, .sgprs = 57, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 64, .sgprs = 57, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 6-bit 1x2: 74 VGPRs, 60 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 6-bit 1x2: 85 VGPRs, 61 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 6-bit 1x2: 85 VGPRs, 61 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 6-bit 1x2: 85 VGPRs, 61 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 6-bit 1x2: .usage = .{ .{ .vgprs = 74, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 85, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 85, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 85, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 6-bit 1x4: 127 VGPRs, 62 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 6-bit 1x4: 121 VGPRs, 63 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 6-bit 1x4: 121 VGPRs, 63 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 6-bit 1x4: 121 VGPRs, 63 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 6-bit 1x4: .usage = .{ .{ .vgprs = 127, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 121, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 121, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 121, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 6-bit 1x8: 219 VGPRs, 65 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 6-bit 1x8: 213 VGPRs, 66 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 6-bit 1x8: 213 VGPRs, 66 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 6-bit 1x8: 213 VGPRs, 66 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 6-bit 1x8: .usage = .{ .{ .vgprs = 219, .sgprs = 65, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 213, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 213, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 213, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 6-bit 2x1: 86 VGPRs, 65 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 6-bit 2x1: 98 VGPRs, 68 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 6-bit 2x1: 98 VGPRs, 68 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 6-bit 2x1: 98 VGPRs, 69 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 6-bit 2x1: .usage = .{ .{ .vgprs = 86, .sgprs = 65, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 98, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 98, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 98, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 6-bit 2x2: 107 VGPRs, 65 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 6-bit 2x2: 113 VGPRs, 67 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 6-bit 2x2: 113 VGPRs, 67 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 6-bit 2x2: 113 VGPRs, 68 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 6-bit 2x2: .usage = .{ .{ .vgprs = 107, .sgprs = 65, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 113, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 113, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 113, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 6-bit 2x4: 133 VGPRs, 67 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 6-bit 2x4: 143 VGPRs, 69 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 6-bit 2x4: 143 VGPRs, 69 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 6-bit 2x4: 143 VGPRs, 70 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 6-bit 2x4: .usage = .{ .{ .vgprs = 133, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 143, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 143, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 143, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 6-bit 2x8: 193 VGPRs, 71 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 6-bit 2x8: 200 VGPRs, 73 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 6-bit 2x8: 200 VGPRs, 73 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 6-bit 2x8: 200 VGPRs, 74 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 6-bit 2x8: .usage = .{ .{ .vgprs = 193, .sgprs = 71, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 200, .sgprs = 73, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 200, .sgprs = 73, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 200, .sgprs = 74, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 6-bit 4x1: 123 VGPRs, 73 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 6-bit 4x1: 134 VGPRs, 76 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 6-bit 4x1: 134 VGPRs, 76 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 6-bit 4x1: 134 VGPRs, 77 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 6-bit 4x1: .usage = .{ .{ .vgprs = 123, .sgprs = 73, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 134, .sgprs = 76, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 134, .sgprs = 76, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 134, .sgprs = 77, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 6-bit 4x2: 141 VGPRs, 73 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 6-bit 4x2: 148 VGPRs, 75 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 6-bit 4x2: 148 VGPRs, 75 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 6-bit 4x2: 148 VGPRs, 76 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 6-bit 4x2: .usage = .{ .{ .vgprs = 141, .sgprs = 73, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 148, .sgprs = 75, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 148, .sgprs = 75, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 148, .sgprs = 76, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 6-bit 4x4: 175 VGPRs, 75 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 6-bit 4x4: 182 VGPRs, 77 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 6-bit 4x4: 182 VGPRs, 77 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 6-bit 4x4: 182 VGPRs, 78 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 6-bit 4x4: .usage = .{ .{ .vgprs = 175, .sgprs = 75, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 182, .sgprs = 77, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 182, .sgprs = 77, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 182, .sgprs = 78, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 8-bit 1x1: 64 VGPRs, 55 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 8-bit 1x1: 68 VGPRs, 54 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 8-bit 1x1: 68 VGPRs, 54 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 8-bit 1x1: 68 VGPRs, 56 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 8-bit 1x1: .usage = .{ .{ .vgprs = 64, .sgprs = 55, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 68, .sgprs = 54, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 68, .sgprs = 54, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 68, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 8-bit 1x2: 78 VGPRs, 57 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 8-bit 1x2: 95 VGPRs, 57 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 8-bit 1x2: 95 VGPRs, 57 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 8-bit 1x2: 95 VGPRs, 59 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 8-bit 1x2: .usage = .{ .{ .vgprs = 78, .sgprs = 57, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 95, .sgprs = 57, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 95, .sgprs = 57, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 95, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 8-bit 1x4: 136 VGPRs, 59 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 8-bit 1x4: 137 VGPRs, 59 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 8-bit 1x4: 137 VGPRs, 59 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 8-bit 1x4: 137 VGPRs, 61 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 8-bit 1x4: .usage = .{ .{ .vgprs = 136, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 137, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 137, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 137, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 8-bit 1x8: 250 VGPRs, 62 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 8-bit 1x8: 256 VGPRs, 62 SGPRs, 0 LDS bytes, 132 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 8-bit 1x8: 256 VGPRs, 62 SGPRs, 0 LDS bytes, 132 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 8-bit 1x8: 256 VGPRs, 64 SGPRs, 0 LDS bytes, 132 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 8-bit 1x8: .usage = .{ .{ .vgprs = 250, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 256, .sgprs = 62, .lds = 0, .private = 132, .bound = 128, .wave = 32 }, .{ .vgprs = 256, .sgprs = 62, .lds = 0, .private = 132, .bound = 128, .wave = 32 }, .{ .vgprs = 256, .sgprs = 64, .lds = 0, .private = 132, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 8-bit 2x1: 78 VGPRs, 62 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 8-bit 2x1: 96 VGPRs, 64 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 8-bit 2x1: 96 VGPRs, 64 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 8-bit 2x1: 96 VGPRs, 67 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 8-bit 2x1: .usage = .{ .{ .vgprs = 78, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 96, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 96, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 96, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 8-bit 2x2: 98 VGPRs, 62 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 8-bit 2x2: 105 VGPRs, 63 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 8-bit 2x2: 105 VGPRs, 63 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 8-bit 2x2: 105 VGPRs, 66 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 8-bit 2x2: .usage = .{ .{ .vgprs = 98, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 105, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 105, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 105, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 8-bit 2x4: 134 VGPRs, 64 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 8-bit 2x4: 141 VGPRs, 65 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 8-bit 2x4: 141 VGPRs, 65 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 8-bit 2x4: 141 VGPRs, 68 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 8-bit 2x4: .usage = .{ .{ .vgprs = 134, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 141, .sgprs = 65, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 141, .sgprs = 65, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 141, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 8-bit 2x8: 195 VGPRs, 68 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 8-bit 2x8: 205 VGPRs, 69 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 8-bit 2x8: 205 VGPRs, 69 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 8-bit 2x8: 205 VGPRs, 72 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 8-bit 2x8: .usage = .{ .{ .vgprs = 195, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 205, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 205, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 205, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 8-bit 4x1: 114 VGPRs, 70 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 8-bit 4x1: 132 VGPRs, 72 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 8-bit 4x1: 132 VGPRs, 72 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 8-bit 4x1: 132 VGPRs, 75 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 8-bit 4x1: .usage = .{ .{ .vgprs = 114, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 132, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 132, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 132, .sgprs = 75, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 8-bit 4x2: 131 VGPRs, 70 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 8-bit 4x2: 155 VGPRs, 71 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 8-bit 4x2: 155 VGPRs, 71 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 8-bit 4x2: 155 VGPRs, 74 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 8-bit 4x2: .usage = .{ .{ .vgprs = 131, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 155, .sgprs = 71, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 155, .sgprs = 71, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 155, .sgprs = 74, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 plain stream tile 8-bit 4x4: 193 VGPRs, 72 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 plain stream tile 8-bit 4x4: 195 VGPRs, 73 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 plain stream tile 8-bit 4x4: 195 VGPRs, 73 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 plain stream tile 8-bit 4x4: 195 VGPRs, 76 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD plain stream tile 8-bit 4x4: .usage = .{ .{ .vgprs = 193, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 195, .sgprs = 73, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 195, .sgprs = 73, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 195, .sgprs = 76, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 swiglu stream tile 2-bit 1x2: 59 VGPRs, 55 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 swiglu stream tile 2-bit 1x2: 72 VGPRs, 56 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 swiglu stream tile 2-bit 1x2: 72 VGPRs, 56 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 swiglu stream tile 2-bit 1x2: 72 VGPRs, 58 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD swiglu stream tile 2-bit 1x2: .usage = .{ .{ .vgprs = 59, .sgprs = 55, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 72, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 72, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 72, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 swiglu stream tile 2-bit 1x4: 96 VGPRs, 57 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 swiglu stream tile 2-bit 1x4: 91 VGPRs, 58 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 swiglu stream tile 2-bit 1x4: 91 VGPRs, 58 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 swiglu stream tile 2-bit 1x4: 91 VGPRs, 60 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD swiglu stream tile 2-bit 1x4: .usage = .{ .{ .vgprs = 96, .sgprs = 57, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 91, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 91, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 91, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 swiglu stream tile 2-bit 1x8: 158 VGPRs, 59 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 swiglu stream tile 2-bit 1x8: 158 VGPRs, 60 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 swiglu stream tile 2-bit 1x8: 158 VGPRs, 60 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 swiglu stream tile 2-bit 1x8: 158 VGPRs, 62 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD swiglu stream tile 2-bit 1x8: .usage = .{ .{ .vgprs = 158, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 158, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 158, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 158, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 swiglu stream tile 2-bit 2x2: 82 VGPRs, 61 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 swiglu stream tile 2-bit 2x2: 105 VGPRs, 62 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 swiglu stream tile 2-bit 2x2: 105 VGPRs, 62 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 swiglu stream tile 2-bit 2x2: 105 VGPRs, 66 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD swiglu stream tile 2-bit 2x2: .usage = .{ .{ .vgprs = 82, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 105, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 105, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 105, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 swiglu stream tile 2-bit 2x4: 110 VGPRs, 62 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 swiglu stream tile 2-bit 2x4: 128 VGPRs, 63 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 swiglu stream tile 2-bit 2x4: 128 VGPRs, 63 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 swiglu stream tile 2-bit 2x4: 128 VGPRs, 67 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD swiglu stream tile 2-bit 2x4: .usage = .{ .{ .vgprs = 110, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 128, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 128, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 128, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 swiglu stream tile 2-bit 2x8: 147 VGPRs, 65 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 swiglu stream tile 2-bit 2x8: 171 VGPRs, 66 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 swiglu stream tile 2-bit 2x8: 171 VGPRs, 66 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 swiglu stream tile 2-bit 2x8: 171 VGPRs, 70 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD swiglu stream tile 2-bit 2x8: .usage = .{ .{ .vgprs = 147, .sgprs = 65, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 171, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 171, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 171, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 swiglu stream tile 2-bit 4x2: 140 VGPRs, 69 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 swiglu stream tile 2-bit 4x2: 144 VGPRs, 70 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 swiglu stream tile 2-bit 4x2: 144 VGPRs, 70 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 swiglu stream tile 2-bit 4x2: 144 VGPRs, 74 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD swiglu stream tile 2-bit 4x2: .usage = .{ .{ .vgprs = 140, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 144, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 144, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 144, .sgprs = 74, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 swiglu stream tile 2-bit 4x4: 147 VGPRs, 70 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 swiglu stream tile 2-bit 4x4: 171 VGPRs, 71 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 swiglu stream tile 2-bit 4x4: 171 VGPRs, 71 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 swiglu stream tile 2-bit 4x4: 171 VGPRs, 75 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD swiglu stream tile 2-bit 4x4: .usage = .{ .{ .vgprs = 147, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 171, .sgprs = 71, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 171, .sgprs = 71, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 171, .sgprs = 75, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 swiglu stream tile 3-bit 1x2: 67 VGPRs, 52 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 swiglu stream tile 3-bit 1x2: 74 VGPRs, 53 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 swiglu stream tile 3-bit 1x2: 74 VGPRs, 53 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 swiglu stream tile 3-bit 1x2: 74 VGPRs, 53 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD swiglu stream tile 3-bit 1x2: .usage = .{ .{ .vgprs = 67, .sgprs = 52, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 74, .sgprs = 53, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 74, .sgprs = 53, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 74, .sgprs = 53, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 swiglu stream tile 3-bit 1x4: 95 VGPRs, 53 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 swiglu stream tile 3-bit 1x4: 96 VGPRs, 53 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 swiglu stream tile 3-bit 1x4: 96 VGPRs, 53 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 swiglu stream tile 3-bit 1x4: 96 VGPRs, 53 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD swiglu stream tile 3-bit 1x4: .usage = .{ .{ .vgprs = 95, .sgprs = 53, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 96, .sgprs = 53, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 96, .sgprs = 53, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 96, .sgprs = 53, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 swiglu stream tile 3-bit 1x8: 175 VGPRs, 55 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 swiglu stream tile 3-bit 1x8: 169 VGPRs, 56 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 swiglu stream tile 3-bit 1x8: 169 VGPRs, 56 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 swiglu stream tile 3-bit 1x8: 169 VGPRs, 56 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD swiglu stream tile 3-bit 1x8: .usage = .{ .{ .vgprs = 175, .sgprs = 55, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 169, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 169, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 169, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 swiglu stream tile 3-bit 2x2: 73 VGPRs, 58 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 swiglu stream tile 3-bit 2x2: 109 VGPRs, 59 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 swiglu stream tile 3-bit 2x2: 109 VGPRs, 59 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 swiglu stream tile 3-bit 2x2: 109 VGPRs, 61 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD swiglu stream tile 3-bit 2x2: .usage = .{ .{ .vgprs = 73, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 109, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 109, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 109, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 swiglu stream tile 3-bit 2x4: 93 VGPRs, 60 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 swiglu stream tile 3-bit 2x4: 94 VGPRs, 61 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 swiglu stream tile 3-bit 2x4: 94 VGPRs, 61 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 swiglu stream tile 3-bit 2x4: 94 VGPRs, 63 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD swiglu stream tile 3-bit 2x4: .usage = .{ .{ .vgprs = 93, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 94, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 94, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 94, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 swiglu stream tile 3-bit 2x8: 142 VGPRs, 62 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 swiglu stream tile 3-bit 2x8: 176 VGPRs, 63 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 swiglu stream tile 3-bit 2x8: 176 VGPRs, 63 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 swiglu stream tile 3-bit 2x8: 176 VGPRs, 65 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD swiglu stream tile 3-bit 2x8: .usage = .{ .{ .vgprs = 142, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 176, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 176, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 176, .sgprs = 65, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 swiglu stream tile 3-bit 4x2: 111 VGPRs, 66 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 swiglu stream tile 3-bit 4x2: 144 VGPRs, 67 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 swiglu stream tile 3-bit 4x2: 144 VGPRs, 67 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 swiglu stream tile 3-bit 4x2: 144 VGPRs, 69 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD swiglu stream tile 3-bit 4x2: .usage = .{ .{ .vgprs = 111, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 144, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 144, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 144, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 swiglu stream tile 3-bit 4x4: 140 VGPRs, 68 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 swiglu stream tile 3-bit 4x4: 138 VGPRs, 69 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 swiglu stream tile 3-bit 4x4: 138 VGPRs, 69 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 swiglu stream tile 3-bit 4x4: 138 VGPRs, 71 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD swiglu stream tile 3-bit 4x4: .usage = .{ .{ .vgprs = 140, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 138, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 138, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 138, .sgprs = 71, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 swiglu stream tile 4-bit 1x2: 59 VGPRs, 55 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 swiglu stream tile 4-bit 1x2: 75 VGPRs, 56 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 swiglu stream tile 4-bit 1x2: 75 VGPRs, 56 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 swiglu stream tile 4-bit 1x2: 75 VGPRs, 58 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD swiglu stream tile 4-bit 1x2: .usage = .{ .{ .vgprs = 59, .sgprs = 55, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 75, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 75, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 75, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 swiglu stream tile 4-bit 1x4: 112 VGPRs, 57 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 swiglu stream tile 4-bit 1x4: 119 VGPRs, 58 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 swiglu stream tile 4-bit 1x4: 119 VGPRs, 58 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 swiglu stream tile 4-bit 1x4: 119 VGPRs, 60 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD swiglu stream tile 4-bit 1x4: .usage = .{ .{ .vgprs = 112, .sgprs = 57, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 119, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 119, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 119, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 swiglu stream tile 4-bit 1x8: 191 VGPRs, 59 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 swiglu stream tile 4-bit 1x8: 190 VGPRs, 60 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 swiglu stream tile 4-bit 1x8: 190 VGPRs, 60 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 swiglu stream tile 4-bit 1x8: 190 VGPRs, 62 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD swiglu stream tile 4-bit 1x8: .usage = .{ .{ .vgprs = 191, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 190, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 190, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 190, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 swiglu stream tile 4-bit 2x2: 83 VGPRs, 60 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 swiglu stream tile 4-bit 2x2: 106 VGPRs, 61 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 swiglu stream tile 4-bit 2x2: 106 VGPRs, 61 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 swiglu stream tile 4-bit 2x2: 106 VGPRs, 65 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD swiglu stream tile 4-bit 2x2: .usage = .{ .{ .vgprs = 83, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 106, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 106, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 106, .sgprs = 65, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 swiglu stream tile 4-bit 2x4: 116 VGPRs, 63 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 swiglu stream tile 4-bit 2x4: 134 VGPRs, 64 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 swiglu stream tile 4-bit 2x4: 134 VGPRs, 64 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 swiglu stream tile 4-bit 2x4: 134 VGPRs, 68 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD swiglu stream tile 4-bit 2x4: .usage = .{ .{ .vgprs = 116, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 134, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 134, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 134, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 swiglu stream tile 4-bit 2x8: 163 VGPRs, 65 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 swiglu stream tile 4-bit 2x8: 184 VGPRs, 66 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 swiglu stream tile 4-bit 2x8: 184 VGPRs, 66 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 swiglu stream tile 4-bit 2x8: 184 VGPRs, 70 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD swiglu stream tile 4-bit 2x8: .usage = .{ .{ .vgprs = 163, .sgprs = 65, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 184, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 184, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 184, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 swiglu stream tile 4-bit 4x2: 143 VGPRs, 68 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 swiglu stream tile 4-bit 4x2: 145 VGPRs, 69 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 swiglu stream tile 4-bit 4x2: 145 VGPRs, 69 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 swiglu stream tile 4-bit 4x2: 145 VGPRs, 73 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD swiglu stream tile 4-bit 4x2: .usage = .{ .{ .vgprs = 143, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 145, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 145, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 145, .sgprs = 73, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 swiglu stream tile 4-bit 4x4: 174 VGPRs, 71 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 swiglu stream tile 4-bit 4x4: 179 VGPRs, 72 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 swiglu stream tile 4-bit 4x4: 179 VGPRs, 72 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 swiglu stream tile 4-bit 4x4: 179 VGPRs, 76 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD swiglu stream tile 4-bit 4x4: .usage = .{ .{ .vgprs = 174, .sgprs = 71, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 179, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 179, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 179, .sgprs = 76, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 swiglu stream tile 5-bit 1x2: 64 VGPRs, 52 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 swiglu stream tile 5-bit 1x2: 76 VGPRs, 53 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 swiglu stream tile 5-bit 1x2: 76 VGPRs, 53 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 swiglu stream tile 5-bit 1x2: 76 VGPRs, 53 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD swiglu stream tile 5-bit 1x2: .usage = .{ .{ .vgprs = 64, .sgprs = 52, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 76, .sgprs = 53, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 76, .sgprs = 53, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 76, .sgprs = 53, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 swiglu stream tile 5-bit 1x4: 111 VGPRs, 53 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 swiglu stream tile 5-bit 1x4: 112 VGPRs, 53 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 swiglu stream tile 5-bit 1x4: 112 VGPRs, 53 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 swiglu stream tile 5-bit 1x4: 112 VGPRs, 53 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD swiglu stream tile 5-bit 1x4: .usage = .{ .{ .vgprs = 111, .sgprs = 53, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 112, .sgprs = 53, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 112, .sgprs = 53, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 112, .sgprs = 53, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 swiglu stream tile 5-bit 1x8: 206 VGPRs, 55 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 swiglu stream tile 5-bit 1x8: 201 VGPRs, 56 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 swiglu stream tile 5-bit 1x8: 201 VGPRs, 56 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 swiglu stream tile 5-bit 1x8: 201 VGPRs, 56 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD swiglu stream tile 5-bit 1x8: .usage = .{ .{ .vgprs = 206, .sgprs = 55, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 201, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 201, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 201, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 swiglu stream tile 5-bit 2x2: 75 VGPRs, 58 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 swiglu stream tile 5-bit 2x2: 75 VGPRs, 59 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 swiglu stream tile 5-bit 2x2: 75 VGPRs, 59 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 swiglu stream tile 5-bit 2x2: 75 VGPRs, 61 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD swiglu stream tile 5-bit 2x2: .usage = .{ .{ .vgprs = 75, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 75, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 75, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 75, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 swiglu stream tile 5-bit 2x4: 104 VGPRs, 60 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 swiglu stream tile 5-bit 2x4: 104 VGPRs, 61 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 swiglu stream tile 5-bit 2x4: 104 VGPRs, 61 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 swiglu stream tile 5-bit 2x4: 104 VGPRs, 63 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD swiglu stream tile 5-bit 2x4: .usage = .{ .{ .vgprs = 104, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 104, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 104, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 104, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 swiglu stream tile 5-bit 2x8: 158 VGPRs, 62 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 swiglu stream tile 5-bit 2x8: 190 VGPRs, 63 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 swiglu stream tile 5-bit 2x8: 190 VGPRs, 63 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 swiglu stream tile 5-bit 2x8: 190 VGPRs, 65 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD swiglu stream tile 5-bit 2x8: .usage = .{ .{ .vgprs = 158, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 190, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 190, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 190, .sgprs = 65, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 swiglu stream tile 5-bit 4x2: 109 VGPRs, 66 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 swiglu stream tile 5-bit 4x2: 113 VGPRs, 67 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 swiglu stream tile 5-bit 4x2: 113 VGPRs, 67 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 swiglu stream tile 5-bit 4x2: 113 VGPRs, 69 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD swiglu stream tile 5-bit 4x2: .usage = .{ .{ .vgprs = 109, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 113, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 113, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 113, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 swiglu stream tile 5-bit 4x4: 142 VGPRs, 68 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 swiglu stream tile 5-bit 4x4: 143 VGPRs, 69 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 swiglu stream tile 5-bit 4x4: 143 VGPRs, 69 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 swiglu stream tile 5-bit 4x4: 143 VGPRs, 71 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD swiglu stream tile 5-bit 4x4: .usage = .{ .{ .vgprs = 142, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 143, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 143, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 143, .sgprs = 71, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 swiglu stream tile 6-bit 1x2: 71 VGPRs, 59 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 swiglu stream tile 6-bit 1x2: 82 VGPRs, 60 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 swiglu stream tile 6-bit 1x2: 82 VGPRs, 60 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 swiglu stream tile 6-bit 1x2: 82 VGPRs, 60 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD swiglu stream tile 6-bit 1x2: .usage = .{ .{ .vgprs = 71, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 82, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 82, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 82, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 swiglu stream tile 6-bit 1x4: 127 VGPRs, 61 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 swiglu stream tile 6-bit 1x4: 121 VGPRs, 62 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 swiglu stream tile 6-bit 1x4: 121 VGPRs, 62 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 swiglu stream tile 6-bit 1x4: 121 VGPRs, 63 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD swiglu stream tile 6-bit 1x4: .usage = .{ .{ .vgprs = 127, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 121, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 121, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 121, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 swiglu stream tile 6-bit 1x8: 223 VGPRs, 63 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 swiglu stream tile 6-bit 1x8: 217 VGPRs, 64 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 swiglu stream tile 6-bit 1x8: 217 VGPRs, 64 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 swiglu stream tile 6-bit 1x8: 217 VGPRs, 64 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD swiglu stream tile 6-bit 1x8: .usage = .{ .{ .vgprs = 223, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 217, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 217, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 217, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 swiglu stream tile 6-bit 2x2: 100 VGPRs, 65 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 swiglu stream tile 6-bit 2x2: 108 VGPRs, 66 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 swiglu stream tile 6-bit 2x2: 108 VGPRs, 66 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 swiglu stream tile 6-bit 2x2: 108 VGPRs, 68 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD swiglu stream tile 6-bit 2x2: .usage = .{ .{ .vgprs = 100, .sgprs = 65, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 108, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 108, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 108, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 swiglu stream tile 6-bit 2x4: 133 VGPRs, 67 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 swiglu stream tile 6-bit 2x4: 141 VGPRs, 68 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 swiglu stream tile 6-bit 2x4: 141 VGPRs, 68 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 swiglu stream tile 6-bit 2x4: 141 VGPRs, 70 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD swiglu stream tile 6-bit 2x4: .usage = .{ .{ .vgprs = 133, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 141, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 141, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 141, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 swiglu stream tile 6-bit 2x8: 189 VGPRs, 69 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 swiglu stream tile 6-bit 2x8: 196 VGPRs, 70 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 swiglu stream tile 6-bit 2x8: 196 VGPRs, 70 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 swiglu stream tile 6-bit 2x8: 196 VGPRs, 72 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD swiglu stream tile 6-bit 2x8: .usage = .{ .{ .vgprs = 189, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 196, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 196, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 196, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 swiglu stream tile 6-bit 4x2: 138 VGPRs, 73 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 swiglu stream tile 6-bit 4x2: 145 VGPRs, 74 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 swiglu stream tile 6-bit 4x2: 145 VGPRs, 74 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 swiglu stream tile 6-bit 4x2: 145 VGPRs, 76 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD swiglu stream tile 6-bit 4x2: .usage = .{ .{ .vgprs = 138, .sgprs = 73, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 145, .sgprs = 74, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 145, .sgprs = 74, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 145, .sgprs = 76, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 swiglu stream tile 6-bit 4x4: 173 VGPRs, 75 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 swiglu stream tile 6-bit 4x4: 180 VGPRs, 76 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 swiglu stream tile 6-bit 4x4: 180 VGPRs, 76 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 swiglu stream tile 6-bit 4x4: 180 VGPRs, 78 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD swiglu stream tile 6-bit 4x4: .usage = .{ .{ .vgprs = 173, .sgprs = 75, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 180, .sgprs = 76, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 180, .sgprs = 76, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 180, .sgprs = 78, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 swiglu stream tile 8-bit 1x2: 75 VGPRs, 55 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 swiglu stream tile 8-bit 1x2: 94 VGPRs, 56 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 swiglu stream tile 8-bit 1x2: 94 VGPRs, 56 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 swiglu stream tile 8-bit 1x2: 94 VGPRs, 58 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD swiglu stream tile 8-bit 1x2: .usage = .{ .{ .vgprs = 75, .sgprs = 55, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 94, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 94, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 94, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 swiglu stream tile 8-bit 1x4: 136 VGPRs, 57 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 swiglu stream tile 8-bit 1x4: 137 VGPRs, 58 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 swiglu stream tile 8-bit 1x4: 137 VGPRs, 58 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 swiglu stream tile 8-bit 1x4: 137 VGPRs, 60 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD swiglu stream tile 8-bit 1x4: .usage = .{ .{ .vgprs = 136, .sgprs = 57, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 137, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 137, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 137, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 swiglu stream tile 8-bit 1x8: 254 VGPRs, 59 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 swiglu stream tile 8-bit 1x8: 235 VGPRs, 60 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 swiglu stream tile 8-bit 1x8: 235 VGPRs, 60 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 swiglu stream tile 8-bit 1x8: 235 VGPRs, 62 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD swiglu stream tile 8-bit 1x8: .usage = .{ .{ .vgprs = 254, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 235, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 235, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 235, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 swiglu stream tile 8-bit 2x2: 95 VGPRs, 61 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 swiglu stream tile 8-bit 2x2: 102 VGPRs, 62 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 swiglu stream tile 8-bit 2x2: 102 VGPRs, 62 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 swiglu stream tile 8-bit 2x2: 102 VGPRs, 66 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD swiglu stream tile 8-bit 2x2: .usage = .{ .{ .vgprs = 95, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 102, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 102, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 102, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 swiglu stream tile 8-bit 2x4: 132 VGPRs, 63 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 swiglu stream tile 8-bit 2x4: 139 VGPRs, 64 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 swiglu stream tile 8-bit 2x4: 139 VGPRs, 64 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 swiglu stream tile 8-bit 2x4: 139 VGPRs, 68 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD swiglu stream tile 8-bit 2x4: .usage = .{ .{ .vgprs = 132, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 139, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 139, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 139, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 swiglu stream tile 8-bit 2x8: 191 VGPRs, 65 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 swiglu stream tile 8-bit 2x8: 201 VGPRs, 66 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 swiglu stream tile 8-bit 2x8: 201 VGPRs, 66 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 swiglu stream tile 8-bit 2x8: 201 VGPRs, 70 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD swiglu stream tile 8-bit 2x8: .usage = .{ .{ .vgprs = 191, .sgprs = 65, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 201, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 201, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 201, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 swiglu stream tile 8-bit 4x2: 128 VGPRs, 69 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 swiglu stream tile 8-bit 4x2: 152 VGPRs, 70 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 swiglu stream tile 8-bit 4x2: 152 VGPRs, 70 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 swiglu stream tile 8-bit 4x2: 152 VGPRs, 74 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD swiglu stream tile 8-bit 4x2: .usage = .{ .{ .vgprs = 128, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 152, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 152, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 152, .sgprs = 74, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 swiglu stream tile 8-bit 4x4: 191 VGPRs, 71 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 swiglu stream tile 8-bit 4x4: 193 VGPRs, 72 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 swiglu stream tile 8-bit 4x4: 193 VGPRs, 72 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 swiglu stream tile 8-bit 4x4: 193 VGPRs, 76 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD swiglu stream tile 8-bit 4x4: .usage = .{ .{ .vgprs = 191, .sgprs = 71, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 193, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 193, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 193, .sgprs = 76, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 held stream tile 4-bit 4x1: 100 VGPRs, 70 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 held stream tile 4-bit 4x1: 99 VGPRs, 72 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 held stream tile 4-bit 4x1: 99 VGPRs, 72 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 held stream tile 4-bit 4x1: 99 VGPRs, 75 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD held stream tile 4-bit 4x1: .usage = .{ .{ .vgprs = 100, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 99, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 99, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 99, .sgprs = 75, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 held stream tile 4-bit 4x2: 126 VGPRs, 70 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 held stream tile 4-bit 4x2: 128 VGPRs, 71 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 held stream tile 4-bit 4x2: 128 VGPRs, 71 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 held stream tile 4-bit 4x2: 128 VGPRs, 74 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD held stream tile 4-bit 4x2: .usage = .{ .{ .vgprs = 126, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 128, .sgprs = 71, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 128, .sgprs = 71, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 128, .sgprs = 74, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 held stream tile 4-bit 4x4: 180 VGPRs, 72 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 held stream tile 4-bit 4x4: 180 VGPRs, 73 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 held stream tile 4-bit 4x4: 180 VGPRs, 73 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 held stream tile 4-bit 4x4: 180 VGPRs, 76 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD held stream tile 4-bit 4x4: .usage = .{ .{ .vgprs = 180, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 180, .sgprs = 73, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 180, .sgprs = 73, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 180, .sgprs = 76, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 held stream tile 4-bit 8x2: 201 VGPRs, 91 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 held stream tile 4-bit 8x2: 200 VGPRs, 90 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 held stream tile 4-bit 8x2: 200 VGPRs, 90 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 held stream tile 4-bit 8x2: 200 VGPRs, 91 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD held stream tile 4-bit 8x2: .usage = .{ .{ .vgprs = 201, .sgprs = 91, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 200, .sgprs = 90, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 200, .sgprs = 90, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 200, .sgprs = 91, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 held stream tile 4-bit 8x4: 256 VGPRs, 98 SGPRs, 0 LDS bytes, 68 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 held stream tile 4-bit 8x4: 256 VGPRs, 92 SGPRs, 0 LDS bytes, 60 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 held stream tile 4-bit 8x4: 256 VGPRs, 92 SGPRs, 0 LDS bytes, 60 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 held stream tile 4-bit 8x4: 256 VGPRs, 94 SGPRs, 0 LDS bytes, 60 scratch bytes, bound 128, wave32 (record current) +RECORD held stream tile 4-bit 8x4: .usage = .{ .{ .vgprs = 256, .sgprs = 98, .lds = 0, .private = 68, .bound = 128, .wave = 32 }, .{ .vgprs = 256, .sgprs = 92, .lds = 0, .private = 60, .bound = 128, .wave = 32 }, .{ .vgprs = 256, .sgprs = 92, .lds = 0, .private = 60, .bound = 128, .wave = 32 }, .{ .vgprs = 256, .sgprs = 94, .lds = 0, .private = 60, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 MoE plan count tf_route_count: 7 VGPRs, 13 SGPRs, 4096 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1100 MoE plan count tf_route_count: 7 VGPRs, 18 SGPRs, 4096 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1151 MoE plan count tf_route_count: 7 VGPRs, 13 SGPRs, 4096 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1201 MoE plan count tf_route_count: 7 VGPRs, 12 SGPRs, 4096 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +RECORD MoE plan count tf_route_count: .usage = .{ .{ .vgprs = 7, .sgprs = 13, .lds = 4096, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 7, .sgprs = 18, .lds = 4096, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 7, .sgprs = 13, .lds = 4096, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 7, .sgprs = 12, .lds = 4096, .private = 0, .bound = 256, .wave = 32 }, } +PASS limits gfx1030 MoE plan scan tf_route_scan: 11 VGPRs, 15 SGPRs, 20480 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +PASS limits gfx1100 MoE plan scan tf_route_scan: 11 VGPRs, 15 SGPRs, 20480 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +PASS limits gfx1151 MoE plan scan tf_route_scan: 10 VGPRs, 16 SGPRs, 20480 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +PASS limits gfx1201 MoE plan scan tf_route_scan: 10 VGPRs, 16 SGPRs, 20480 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +RECORD MoE plan scan tf_route_scan: .usage = .{ .{ .vgprs = 11, .sgprs = 15, .lds = 20480, .private = 0, .bound = 1024, .wave = 32 }, .{ .vgprs = 11, .sgprs = 15, .lds = 20480, .private = 0, .bound = 1024, .wave = 32 }, .{ .vgprs = 10, .sgprs = 16, .lds = 20480, .private = 0, .bound = 1024, .wave = 32 }, .{ .vgprs = 10, .sgprs = 16, .lds = 20480, .private = 0, .bound = 1024, .wave = 32 }, } +PASS limits gfx1030 MoE plan scatter tf_route_scatter: 14 VGPRs, 14 SGPRs, 2048 LDS bytes, 0 scratch bytes, bound 512, wave32 (record current) +PASS limits gfx1100 MoE plan scatter tf_route_scatter: 14 VGPRs, 18 SGPRs, 2048 LDS bytes, 0 scratch bytes, bound 512, wave32 (record current) +PASS limits gfx1151 MoE plan scatter tf_route_scatter: 14 VGPRs, 14 SGPRs, 2048 LDS bytes, 0 scratch bytes, bound 512, wave32 (record current) +PASS limits gfx1201 MoE plan scatter tf_route_scatter: 14 VGPRs, 12 SGPRs, 2048 LDS bytes, 0 scratch bytes, bound 512, wave32 (record current) +RECORD MoE plan scatter tf_route_scatter: .usage = .{ .{ .vgprs = 14, .sgprs = 14, .lds = 2048, .private = 0, .bound = 512, .wave = 32 }, .{ .vgprs = 14, .sgprs = 18, .lds = 2048, .private = 0, .bound = 512, .wave = 32 }, .{ .vgprs = 14, .sgprs = 14, .lds = 2048, .private = 0, .bound = 512, .wave = 32 }, .{ .vgprs = 14, .sgprs = 12, .lds = 2048, .private = 0, .bound = 512, .wave = 32 }, } +PASS limits gfx1030 MoE prompt picks a wave a row tf_select_rows: 135 VGPRs, 49 SGPRs, 5428 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 MoE prompt picks a wave a row tf_select_rows: 135 VGPRs, 46 SGPRs, 5428 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 MoE prompt picks a wave a row tf_select_rows: 135 VGPRs, 50 SGPRs, 5428 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 MoE prompt picks a wave a row tf_select_rows: 135 VGPRs, 52 SGPRs, 5428 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD MoE prompt picks a wave a row tf_select_rows: .usage = .{ .{ .vgprs = 135, .sgprs = 49, .lds = 5428, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 135, .sgprs = 46, .lds = 5428, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 135, .sgprs = 50, .lds = 5428, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 135, .sgprs = 52, .lds = 5428, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 Flash Next index scores, 4 lanes a score: 184 VGPRs, 22 SGPRs, 32772 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 Flash Next index scores, 4 lanes a score: 184 VGPRs, 22 SGPRs, 32772 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 Flash Next index scores, 4 lanes a score: 184 VGPRs, 20 SGPRs, 32772 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 Flash Next index scores, 4 lanes a score: 184 VGPRs, 20 SGPRs, 32772 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD Flash Next index scores, 4 lanes a score: .usage = .{ .{ .vgprs = 184, .sgprs = 22, .lds = 32772, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 184, .sgprs = 22, .lds = 32772, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 184, .sgprs = 20, .lds = 32772, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 184, .sgprs = 20, .lds = 32772, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 Flash Next index scores, 8 rows a wave: 79 VGPRs, 26 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1100 Flash Next index scores, 8 rows a wave: 93 VGPRs, 26 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1151 Flash Next index scores, 8 rows a wave: 93 VGPRs, 26 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1201 Flash Next index scores, 8 rows a wave: 93 VGPRs, 44 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +RECORD Flash Next index scores, 8 rows a wave: .usage = .{ .{ .vgprs = 79, .sgprs = 26, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 93, .sgprs = 26, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 93, .sgprs = 26, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 93, .sgprs = 44, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, } +N/A limits gfx1030 Flash Next HC gate table tf_hc_gate_fill: not launched on this chip +PASS limits gfx1100 Flash Next HC gate table tf_hc_gate_fill: 7 VGPRs, 18 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1151 Flash Next HC gate table tf_hc_gate_fill: 7 VGPRs, 4 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +N/A limits gfx1201 Flash Next HC gate table tf_hc_gate_fill: not launched on this chip +RECORD Flash Next HC gate table tf_hc_gate_fill: .usage = .{ .{ .vgprs = 0, .sgprs = 0, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 7, .sgprs = 18, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 7, .sgprs = 4, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 0, .sgprs = 0, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, } +N/A limits gfx1030 Flash Next HC mix tf_fn_hc_mix8: not launched on this chip +PASS limits gfx1100 Flash Next HC mix tf_fn_hc_mix8: 68 VGPRs, 26 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +PASS limits gfx1151 Flash Next HC mix tf_fn_hc_mix8: 68 VGPRs, 26 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +PASS limits gfx1201 Flash Next HC mix tf_fn_hc_mix8: 68 VGPRs, 28 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +RECORD Flash Next HC mix tf_fn_hc_mix8: .usage = .{ .{ .vgprs = 0, .sgprs = 0, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 68, .sgprs = 26, .lds = 0, .private = 0, .bound = 1024, .wave = 32 }, .{ .vgprs = 68, .sgprs = 26, .lds = 0, .private = 0, .bound = 1024, .wave = 32 }, .{ .vgprs = 68, .sgprs = 28, .lds = 0, .private = 0, .bound = 1024, .wave = 32 }, } +N/A limits gfx1030 Flash Next HC norm tf_fn_hc_norm_v: not launched on this chip +PASS limits gfx1100 Flash Next HC norm tf_fn_hc_norm_v: 77 VGPRs, 22 SGPRs, 128 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 Flash Next HC norm tf_fn_hc_norm_v: 77 VGPRs, 22 SGPRs, 128 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 Flash Next HC norm tf_fn_hc_norm_v: 77 VGPRs, 23 SGPRs, 128 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD Flash Next HC norm tf_fn_hc_norm_v: .usage = .{ .{ .vgprs = 0, .sgprs = 0, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 77, .sgprs = 22, .lds = 128, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 77, .sgprs = 22, .lds = 128, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 77, .sgprs = 23, .lds = 128, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 Flash Next HC norm with the MoE combine tf_fn_hc_norm_moe: 19 VGPRs, 40 SGPRs, 128 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +PASS limits gfx1100 Flash Next HC norm with the MoE combine tf_fn_hc_norm_moe: 19 VGPRs, 40 SGPRs, 128 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +PASS limits gfx1151 Flash Next HC norm with the MoE combine tf_fn_hc_norm_moe: 19 VGPRs, 40 SGPRs, 128 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +PASS limits gfx1201 Flash Next HC norm with the MoE combine tf_fn_hc_norm_moe: 16 VGPRs, 42 SGPRs, 128 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current) +RECORD Flash Next HC norm with the MoE combine tf_fn_hc_norm_moe: .usage = .{ .{ .vgprs = 19, .sgprs = 40, .lds = 128, .private = 0, .bound = 1024, .wave = 32 }, .{ .vgprs = 19, .sgprs = 40, .lds = 128, .private = 0, .bound = 1024, .wave = 32 }, .{ .vgprs = 19, .sgprs = 40, .lds = 128, .private = 0, .bound = 1024, .wave = 32 }, .{ .vgprs = 16, .sgprs = 42, .lds = 128, .private = 0, .bound = 1024, .wave = 32 }, } +N/A limits gfx1030 Flash Next HC norm with the MoE combine, a block a row tf_fn_hc_norm_moe_v: not launched on this chip +PASS limits gfx1100 Flash Next HC norm with the MoE combine, a block a row tf_fn_hc_norm_moe_v: 51 VGPRs, 30 SGPRs, 10752 LDS bytes, 0 scratch bytes, bound 512, wave32 (record current) +PASS limits gfx1151 Flash Next HC norm with the MoE combine, a block a row tf_fn_hc_norm_moe_v: 59 VGPRs, 27 SGPRs, 10752 LDS bytes, 0 scratch bytes, bound 512, wave32 (record current) +PASS limits gfx1201 Flash Next HC norm with the MoE combine, a block a row tf_fn_hc_norm_moe_v: 59 VGPRs, 30 SGPRs, 10752 LDS bytes, 0 scratch bytes, bound 512, wave32 (record current) +RECORD Flash Next HC norm with the MoE combine, a block a row tf_fn_hc_norm_moe_v: .usage = .{ .{ .vgprs = 0, .sgprs = 0, .lds = 0, .private = 0, .bound = 512, .wave = 32 }, .{ .vgprs = 51, .sgprs = 30, .lds = 10752, .private = 0, .bound = 512, .wave = 32 }, .{ .vgprs = 59, .sgprs = 27, .lds = 10752, .private = 0, .bound = 512, .wave = 32 }, .{ .vgprs = 59, .sgprs = 30, .lds = 10752, .private = 0, .bound = 512, .wave = 32 }, } +PASS limits gfx1030 DeltaNet tf_gdn_prompt_128: 175 VGPRs, 40 SGPRs, 20608 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1100 DeltaNet tf_gdn_prompt_128: 185 VGPRs, 39 SGPRs, 20608 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1151 DeltaNet tf_gdn_prompt_128: 185 VGPRs, 38 SGPRs, 20608 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +PASS limits gfx1201 DeltaNet tf_gdn_prompt_128: 185 VGPRs, 38 SGPRs, 20608 LDS bytes, 0 scratch bytes, bound 128, wave32 (record current) +RECORD DeltaNet tf_gdn_prompt_128: .usage = .{ .{ .vgprs = 175, .sgprs = 40, .lds = 20608, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 185, .sgprs = 39, .lds = 20608, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 185, .sgprs = 38, .lds = 20608, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 185, .sgprs = 38, .lds = 20608, .private = 0, .bound = 128, .wave = 32 }, } +PASS limits gfx1030 DeltaNet tf_gdn_prompt_prep: 92 VGPRs, 59 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1100 DeltaNet tf_gdn_prompt_prep: 93 VGPRs, 59 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1151 DeltaNet tf_gdn_prompt_prep: 93 VGPRs, 59 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1201 DeltaNet tf_gdn_prompt_prep: 93 VGPRs, 60 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +RECORD DeltaNet tf_gdn_prompt_prep: .usage = .{ .{ .vgprs = 92, .sgprs = 59, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 93, .sgprs = 59, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 93, .sgprs = 59, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 93, .sgprs = 60, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, } +PASS limits gfx1030 DeltaNet tf_gdn_hold_128: 38 VGPRs, 42 SGPRs, 17024 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1100 DeltaNet tf_gdn_hold_128: 38 VGPRs, 42 SGPRs, 17024 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1151 DeltaNet tf_gdn_hold_128: 38 VGPRs, 38 SGPRs, 17024 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1201 DeltaNet tf_gdn_hold_128: 38 VGPRs, 40 SGPRs, 17024 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +RECORD DeltaNet tf_gdn_hold_128: .usage = .{ .{ .vgprs = 38, .sgprs = 42, .lds = 17024, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 38, .sgprs = 42, .lds = 17024, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 38, .sgprs = 38, .lds = 17024, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 38, .sgprs = 40, .lds = 17024, .private = 0, .bound = 256, .wave = 32 }, } +PASS limits gfx1030 DeltaNet tf_gdn_hold_16: 31 VGPRs, 36 SGPRs, 2688 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1100 DeltaNet tf_gdn_hold_16: 31 VGPRs, 38 SGPRs, 2688 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1151 DeltaNet tf_gdn_hold_16: 31 VGPRs, 36 SGPRs, 2688 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1201 DeltaNet tf_gdn_hold_16: 31 VGPRs, 38 SGPRs, 2688 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +RECORD DeltaNet tf_gdn_hold_16: .usage = .{ .{ .vgprs = 31, .sgprs = 36, .lds = 2688, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 31, .sgprs = 38, .lds = 2688, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 31, .sgprs = 36, .lds = 2688, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 31, .sgprs = 38, .lds = 2688, .private = 0, .bound = 256, .wave = 32 }, } +PASS limits gfx1030 DeltaNet tf_gdn_keep_128: 39 VGPRs, 31 SGPRs, 8832 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1100 DeltaNet tf_gdn_keep_128: 39 VGPRs, 31 SGPRs, 8832 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1151 DeltaNet tf_gdn_keep_128: 39 VGPRs, 31 SGPRs, 8832 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1201 DeltaNet tf_gdn_keep_128: 39 VGPRs, 34 SGPRs, 8832 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +RECORD DeltaNet tf_gdn_keep_128: .usage = .{ .{ .vgprs = 39, .sgprs = 31, .lds = 8832, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 39, .sgprs = 31, .lds = 8832, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 39, .sgprs = 31, .lds = 8832, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 39, .sgprs = 34, .lds = 8832, .private = 0, .bound = 256, .wave = 32 }, } +PASS limits gfx1030 DeltaNet tf_gdn_keep_16: 40 VGPRs, 29 SGPRs, 1664 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1100 DeltaNet tf_gdn_keep_16: 35 VGPRs, 28 SGPRs, 1664 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1151 DeltaNet tf_gdn_keep_16: 35 VGPRs, 28 SGPRs, 1664 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +PASS limits gfx1201 DeltaNet tf_gdn_keep_16: 35 VGPRs, 31 SGPRs, 1664 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current) +RECORD DeltaNet tf_gdn_keep_16: .usage = .{ .{ .vgprs = 40, .sgprs = 29, .lds = 1664, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 35, .sgprs = 28, .lds = 1664, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 35, .sgprs = 28, .lds = 1664, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 35, .sgprs = 31, .lds = 1664, .private = 0, .bound = 256, .wave = 32 }, } +RED limits gfx1030 control: past its bounds: 4 VGPRs, 10 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current): control: past its bounds on gfx1030: launched at 512 threads past its bound 256 +RED limits gfx1100 control: past its bounds: 4 VGPRs, 18 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current): control: past its bounds on gfx1100: launched at 512 threads past its bound 256 +RED limits gfx1151 control: past its bounds: 4 VGPRs, 10 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current): control: past its bounds on gfx1151: launched at 512 threads past its bound 256 +RED limits gfx1201 control: past its bounds: 4 VGPRs, 7 SGPRs, 0 LDS bytes, 0 scratch bytes, bound 256, wave32 (record current): control: past its bounds on gfx1201: launched at 512 threads past its bound 256 +RECORD control: past its bounds: .usage = .{ .{ .vgprs = 4, .sgprs = 10, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 4, .sgprs = 18, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 4, .sgprs = 10, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, .{ .vgprs = 4, .sgprs = 7, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, } +RED limits gfx1030 control: 72 KiB of LDS: 6 VGPRs, 9 SGPRs, 40960 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current): control: 72 KiB of LDS on gfx1030: 73728 LDS bytes, the most a workgroup takes is 65536 +RED limits gfx1100 control: 72 KiB of LDS: 6 VGPRs, 8 SGPRs, 40960 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current): control: 72 KiB of LDS on gfx1100: 73728 LDS bytes, the most a workgroup takes is 65536 +RED limits gfx1151 control: 72 KiB of LDS: 6 VGPRs, 8 SGPRs, 40960 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current): control: 72 KiB of LDS on gfx1151: 73728 LDS bytes, the most a workgroup takes is 65536 +RED limits gfx1201 control: 72 KiB of LDS: 6 VGPRs, 8 SGPRs, 40960 LDS bytes, 0 scratch bytes, bound 1024, wave32 (record current): control: 72 KiB of LDS on gfx1201: 73728 LDS bytes, the most a workgroup takes is 65536 +RECORD control: 72 KiB of LDS: .usage = .{ .{ .vgprs = 6, .sgprs = 9, .lds = 40960, .private = 0, .bound = 1024, .wave = 32 }, .{ .vgprs = 6, .sgprs = 8, .lds = 40960, .private = 0, .bound = 1024, .wave = 32 }, .{ .vgprs = 6, .sgprs = 8, .lds = 40960, .private = 0, .bound = 1024, .wave = 32 }, .{ .vgprs = 6, .sgprs = 8, .lds = 40960, .private = 0, .bound = 1024, .wave = 32 }, } +PASS kernel-contract-limits: every registered launch fits gfx1030, gfx1100, gfx1151 and gfx1201, every record current, every control red diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/checks/per-commit.tsv b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/checks/per-commit.tsv new file mode 100644 index 0000000000..5db97299b8 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/checks/per-commit.tsv @@ -0,0 +1,34 @@ +# tested_commit series_on_abf822585 in_this_pr build test hip_kernel_test logits_hash +1 09dc16427 09dc16427 4ee2e85be 0 0 0 243ecea88fe50d9f +2 ef5a274e3 ef5a274e3 f7ac354c5 0 0 0 243ecea88fe50d9f +3 1b8d5ad20 1b8d5ad20 88aa18df9 0 0 0 243ecea88fe50d9f +4 1c5d3736d 1c5d3736d 9411438ec 0 0 0 243ecea88fe50d9f +5 1fa520bb7 1fa520bb7 daf7ec74f 0 0 0 243ecea88fe50d9f +6 198188545 198188545 12a6370ed 0 0 0 243ecea88fe50d9f +7 c982be350 c982be350 4115368ff 0 0 0 243ecea88fe50d9f +8 423095b23 423095b23 eb50c0b43 0 0 0 243ecea88fe50d9f +9 b6b5fe7be b6b5fe7be bff7fc1a8 0 0 0 243ecea88fe50d9f +10 0c86d520b 0c86d520b c0a9e6270 0 0 0 243ecea88fe50d9f +11 4004d2247 4004d2247 fd4797d56 0 0 0 243ecea88fe50d9f +12 a64402783 a64402783 461d8e001 0 0 0 243ecea88fe50d9f +13 f16d15679 f16d15679 fc3d43bc7 0 0 0 243ecea88fe50d9f +14 597b2deca 597b2deca e432e36fc 0 0 0 243ecea88fe50d9f +15 a50afd4db a50afd4db 61088491a 0 0 0 243ecea88fe50d9f +16 a21895d20 a21895d20 7821dc4c4 0 0 0 243ecea88fe50d9f +17 3d480d423 3d480d423 9bcd8a63b 0 0 0 243ecea88fe50d9f +18 a48ddd8ea a48ddd8ea 72f868fa8 0 0 0 243ecea88fe50d9f +19 31a561b25 00d64db75 adb89effe 0 0 0 243ecea88fe50d9f +20 3cf4b6ae2 2fff35c2f 42ccbbbfc 0 0 0 243ecea88fe50d9f +21 334627996 600417484 1b6c01697 0 0 0 243ecea88fe50d9f +22 455e50aaa 51a86fb03 9701c7ca4 0 0 0 243ecea88fe50d9f +23 6e0b6e6ca ef2498b93 dd7dbafae 0 0 0 243ecea88fe50d9f +24 566fed6f8 57aea264b e2750fb5c 0 0 0 243ecea88fe50d9f +25 0b472ec0d 19c85f7fd 2a1260918 0 0 0 243ecea88fe50d9f +26 f81e47b1c 76e63cb9e 61529bc14 0 0 0 243ecea88fe50d9f +27 fb0e0adb3 875b63291 f132d54ae 0 0 0 243ecea88fe50d9f +28 b9d50897e 3708da825 c99b0d0bd 0 0 0 243ecea88fe50d9f +29 76fb0b3be 354a55c65 8d9e3346a 0 0 0 243ecea88fe50d9f +30 22281b66a 147e333a3 4ee89c6cb 0 0 0 243ecea88fe50d9f +31 d90e72322 de6c8180a 6e4727c66 0 0 0 243ecea88fe50d9f +32 45d9b2efe 321832cde d5a1fc781 0 0 0 243ecea88fe50d9f +33 e143a9e24 db2b2c621 37aed1a03 0 0 0 243ecea88fe50d9f diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/checks/test-cuda-host.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/checks/test-cuda-host.log new file mode 100644 index 0000000000..445cbf0e33 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/checks/test-cuda-host.log @@ -0,0 +1,78 @@ +discovery verbs: retained through TLS, atexit and destructor; child exit 0 +discovery grammar: retained through TLS, atexit and destructor; child exit 0 +test-cuda-host ++- run test w +tf_h3_forward: BadH3Dimensions +tf_h3_forward_host: BadH3Dimensions +tf_h3_forward: BadH3Dimensions +tf_h3_forward_host: BadH3Dimensions +tf_h3_forward: BadH3Dimensions +tf_h3_forward_host: BadH3Dimensions +tf_h3_forward: BadH3Rotary +tf_h3_forward_host: BadH3Rotary +tf_h3_forward: BadH3Rotary +tf_h3_forward_host: BadH3Rotary +tf_h3_forward: BadH3Keep +tf_h3_forward_host: BadH3Keep +tf_h3_forward: BadH3Keep +tf_h3_forward_host: BadH3Keep +tf_h3_forward: BadH3Blocks +tf_h3_forward_host: BadH3Blocks +tf_h3_forward: BadH3Scalar +tf_h3_forward_host: BadH3Scalar +tf_h3_forward: BadH3Scalar +tf_h3_forward_host: BadH3Scalar +tf_h3_forward: BadH3Address +tf_h3_forward_host: BadH3Address +tf_h3_forward: BadH3Address +tf_h3_forward_host: BadH3Address +tf_h3_forward: BadH3Address +tf_h3_forward_host: BadH3Address +tf_h3_forward: BadH3Address +tf_h3_forward_host: BadH3Address +tf_h3_forward: BadH3Address +tf_h3_forward_host: BadH3Address +tf_h3_forward_host: BadH3Address +tf_h3_forward_host: BadH3Scalar +H3 model retained at close: NotReady +H3 geometry retained: NotReady +tensor blocks.0.norm1.weight: MissingTensor +tensor blocks.1.attn.qkv_proj.weight: MissingTensor +tensor blocks.1.norm1.weight: MissingTensor +failed command: ./.zig-cache/o/bf2bd03339780b7ca9191ed10e787a73/test --cache-dir=./.zig-cache --seed=0xf404ce8 --listen=- + +1/7 qwen_cuda_weights_test.test.Qwen tower weights: existing MLX names and every byte match HF in one shard...OK +2/7 qwen_cuda_weights_test.test.Qwen tower weights: indexed MLX fallback and sharded HF preserve every tensor...OK +3/7 qwen_cuda_weights_test.test.Qwen tower weights: malformed selected shape and dtype fail without a fallback...model.visual.patch_embed.proj.weight: f16 { 2, 3, 2, 16, 16 }, expected bf16 { 2, 3, 2, 16, 16 } +model.visual.patch_embed.proj.weight: bf16 { 2, 3, 2, 8, 32 }, expected bf16 { 2, 3, 2, 16, 16 } +vision_tower.patch_embed.proj.weight: f16 { 2, 2, 16, 16, 3 }, expected bf16 { 2, 2, 16, 16, 3 } +vision_tower.patch_embed.proj.weight: bf16 { 2, 2, 16, 8, 6 }, expected bf16 { 2, 2, 16, 16, 3 } +OK +4/7 qwen_cuda_weights_test.test.Qwen tower weights: missing selected tensor and unused selected tensors fail closed...checkpoint has no tensor vision_tower.blocks.0.mlp.linear_fc1.bias +unused checkpoint tensor vision_tower.extra +checkpoint has no tensor model.visual.blocks.0.mlp.linear_fc1.bias +unused checkpoint tensor model.visual.extra +OK +5/7 qwen_cuda_weights_test.test.Qwen tower weights: HF patch keeps the authored precedence when both namespaces exist...OK +6/7 qwen_cuda_weights_test.test.Qwen tower weights: every copy refusal and MLX retry release their host owners...OK +7/7 qwen_cuda_weights_test.test.Qwen tower weights: allocation failures balance the fallback reader and transpose scratch...OK +7 passed; 0 skipped; 0 failed. +test-cuda-host ++- run test w +DEEPSEEK_CHAT_GOLDENS 178 committed encoding.py cases +failed command: ./.zig-cache/o/97e76f409d40c53d69952d552e6a660c/test --cache-dir=./.zig-cache --seed=0xf404ce8 --listen=- + +test-cuda-host ++- run test w +[default] (warn): Drama readback drain failed: retaining its buffers and engine owner +[default] (warn): Drama readback drain failed: retaining its buffers and engine owner +codec requested 1, actual sizes { 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 } +codec requested 1, actual sizes { 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 } +codec requested 4, actual sizes { 4, 4, 4, 4, 1 } +codec requested 16, actual sizes { 16, 1 } +codec requested 1, actual sizes { 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 } +Drama replay passed: eager/graphs, poison/reset, codec chunks and interleaved state +[default] (warn): drama3: config hidden_size = 4096, the kernels need 2048 +[default] (warn): codec.pth pickle names os.system, outside the tensor state-dict allow-list +failed command: ./.zig-cache/o/d14961ea7e83ae92076ad4dac5a6e25b/test --cache-dir=./.zig-cache --seed=0xf404ce8 --listen=- + diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/checks/test-hip.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/checks/test-hip.log new file mode 100644 index 0000000000..46951f6073 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/checks/test-hip.log @@ -0,0 +1,575 @@ +test ++- run test w +[default] (warn): gemma4: layers.0.self_attn.q_proj is 4-bit in groups of 32; the kernels read bits 2-6 and 8 in groups of 64 +[default] (warn): gemma4: layers.0.self_attn.q_proj is 4-bit in groups of 128; the kernels read bits 2-6 and 8 in groups of 64 +[default] (warn): gemma4: layers.3.mlp.up_proj's width is not MLX affine bits 2-6 or 8 +[default] (warn): gemma4: layers.3.mlp.up_proj's width is not MLX affine bits 2-6 or 8 +[default] (warn): gemma4: layers.3.mlp.up_proj is not a width table (false or {} marks a module unquantized); every linear is affine +[default] (warn): gemma4: layers.3.mlp.up_proj is not a width table (false or {} marks a module unquantized); every linear is affine +[default] (warn): model.layers.3.mlp.up_proj: another spelling of module layers.3.mlp.up_proj declares a different width +[default] (warn): gemma4: layers.3.per_layer_input_gate is not a width table (false or {} marks a module unquantized); every linear is affine +[default] (warn): gemma4: layers.3.self_attn.q_proj is not a width table (false or {} marks a module unquantized); every linear is affine +[default] (warn): gemma4: layers.3.mlp.up_proj is not a width table (false or {} marks a module unquantized); every linear is affine +[default] (warn): gemma4: embed_tokens is not a width table (false or {} marks a module unquantized); every linear is affine +[default] (warn): gemma4: layers.3.per_layer_projection_norm is not a width table (false or {} marks a module unquantized); every linear is affine +[default] (warn): gemma4: layers.3.per_layer_input_gate's width is not MLX affine bits 2-6 or 8 +failed command: ./.zig-cache/o/7aac17140cda6705a0943ab6237e381c/test --cache-dir=./.zig-cache --seed=0x96c3cd6f --listen=- + +test ++- run test w +[default] (warn): XPU: a command list did not drain at close; its memory and context stay until the process ends +failed command: ./.zig-cache/o/2a5e435485dbc59ce34936698dc1122c/test --cache-dir=./.zig-cache --seed=0x96c3cd6f --listen=- + +test ++- run test w +[default] (warn): lm_head is 8-bit in groups of 64: CUDA reads Nemotron MLX checkpoints at 4-bit in groups of 64 only; mixed and 6- or 8-bit (oQ) checkpoints serve on Macs +[default] (warn): backbone.embeddings is 8-bit in groups of 64: the Intel GPU engine reads Nemotron MLX checkpoints at 4-bit in groups of 64 only; mixed and 6- or 8-bit (oQ) checkpoints serve on Macs +failed command: ./.zig-cache/o/9a9faf992d20377993c59606a3c6ce05/test --cache-dir=./.zig-cache --seed=0x96c3cd6f --listen=- + +test ++- run test w +[default] (warn): flash next: rotary cache table unavailable: OutOfMemory +failed command: ./.zig-cache/o/6b1d31c5bf7e83666bda0ae47a17bf91/test --cache-dir=./.zig-cache --seed=0x96c3cd6f --listen=- + +test ++- run test w +[default] (warn): a round could not be recorded: OutOfDeviceMemory +failed command: ./.zig-cache/o/c147c3f454e5ceea60895f8577e46bb1/test --cache-dir=./.zig-cache --seed=0x96c3cd6f --listen=- + +test ++- run test w +[default] (warn): lm_head is 8-bit in groups of 64: CUDA reads Nemotron MLX checkpoints at 4-bit in groups of 64 only; mixed and 6- or 8-bit (oQ) checkpoints serve on Macs +[default] (warn): backbone.embeddings is 8-bit in groups of 64: the Intel GPU engine reads Nemotron MLX checkpoints at 4-bit in groups of 64 only; mixed and 6- or 8-bit (oQ) checkpoints serve on Macs +failed command: ./.zig-cache/o/263b4362a92d07509f791ca789703c3d/test --cache-dir=./.zig-cache --seed=0x96c3cd6f --listen=- + +test ++- test-quant-geometry-host + +- run test w +[default] (warn): model.layers.0.mlp.up_proj.weight: another spelling of module layers.0.mlp.up_proj declares a different width +[default] (warn): layers.0.mlp.up_proj: another spelling of module layers.0.mlp.up_proj declares a different width +[default] (warn): model.layers.0.mlp.up_proj: another spelling of module layers.0.mlp.up_proj declares a different width +failed command: ./.zig-cache/o/2a4c78126df534ef1b666da9a82cb9a1/test --cache-dir=./.zig-cache --seed=0x96c3cd6f --listen=- + +test ++- run test w +[default] (warn): lane host: a round failed (GpuFailed): every admitted stream fails +[default] (warn): lane host: stopping at a round boundary: 2 running and 1 queued request(s) end (server restarting: retry shortly) +[default] (warn): lane host: stopping at a round boundary: 1 running and 0 queued request(s) end (server restarting: retry shortly) +[default] (warn): lane host: a round failed (the planner refused): every admitted stream fails +[default] (warn): lane host: a round failed (PlannerFull): every admitted stream fails +[default] (warn): lane host: a decision score failed (EmptyLabels) +[default] (warn): lane host: stopping at a round boundary: 1 running and 1 queued request(s) end (drain deadline) +[default] (warn): lane host: stopping at a round boundary: 0 running and 1 queued request(s) end (NoContext) +[default] (warn): lane host: a round failed (OutOfMemory): every admitted stream fails +[default] (warn): lane host: a round failed (AdmittedFailed): every admitted stream fails +[default] (warn): lane host: a round failed (FinalsFailed): every admitted stream fails +[default] (warn): lane host: a round failed (GpuFailed): every admitted stream fails +[default] (warn): lane host: a round failed (GpuFailed): every admitted stream fails +[default] (warn): 4 prompts together: SamplingRefused; each goes alone +failed command: ./.zig-cache/o/7c94fb940935effb78e691f24df8930a/test --cache-dir=./.zig-cache --seed=0x96c3cd6f --listen=- + +test ++- test-cuda-host + +- run test w +[default] (warn): lm_head is 8-bit in groups of 64: CUDA reads Nemotron MLX checkpoints at 4-bit in groups of 64 only; mixed and 6- or 8-bit (oQ) checkpoints serve on Macs +[default] (warn): backbone.embeddings is 8-bit in groups of 64: the Intel GPU engine reads Nemotron MLX checkpoints at 4-bit in groups of 64 only; mixed and 6- or 8-bit (oQ) checkpoints serve on Macs +failed command: ./.zig-cache/o/d8c6f7e4c05065adb3e7d2d8e91c857f/test --cache-dir=./.zig-cache --seed=0x96c3cd6f --listen=- + +test ++- test-cuda-host + +- run test w +GLM_KV_BYTES context=8192 capacity=8256 main_layers=11 bf16=296101376 fp8=245772800 +GLM_KV_BYTES context=65536 capacity=65600 main_layers=11 bf16=1044784640 fp8=644887040 +GLM_KV_BYTES context=199307 capacity=199360 main_layers=11 bf16=2791155200 fp8=1575856640 +GLM_KV_BYTES context=245760 capacity=245824 main_layers=11 bf16=3397789184 fp8=1899246080 +failed command: ./.zig-cache/o/31a640857b8a14cdde4b9fb220974b85/test --cache-dir=./.zig-cache --seed=0x96c3cd6f --listen=- + +discovery verbs: retained through TLS, atexit and destructor; child exit 0 +discovery grammar: retained through TLS, atexit and destructor; child exit 0 +test ++- test-cuda-host + +- run test w +[default] (warn): libcublasLt.so.13 is required for CUDA vision towers (--vision) and CUDA cuBLASLt projections; install the NVIDIA CUDA 13 cuBLAS runtime; on Linux, add its directory to LD_LIBRARY_PATH; a driver-only host does not include it +[default] (warn): libnccl.so.2 is required for CUDA ranks (including the GLM pair); install the NVIDIA NCCL 2 runtime compatible with CUDA 13; on Linux, add its directory to LD_LIBRARY_PATH +[default] (warn): libibverbs.so.1 is required for RoCE/RDMA gathers; install rdma-core's libibverbs runtime and the provider for the network adapter +[default] (warn): libmcdma-rpc.so is required for MCDMA mailbox and Metal speed-up communication; build and install MCDMA's RPC helper and set MCDMA_RPC_LIBRARY to its file +[default] (warn): libmcdma-rpc.so is required for MCDMA mailbox and Metal speed-up communication; build and install MCDMA's RPC helper and set MCDMA_RPC_LIBRARY to its file +[default] (warn): libmcdma-rpc.so is required for MCDMA mailbox and Metal speed-up communication; build and install MCDMA's RPC helper and set MCDMA_RPC_LIBRARY to its file +failed command: ./.zig-cache/o/da1ff98eacecf9e3352a0a57ec05f4e4/test --cache-dir=./.zig-cache --seed=0x96c3cd6f --listen=- + +1/7 qwen_cuda_weights_test.test.Qwen tower weights: existing MLX names and every byte match HF in one shard...OK +2/7 qwen_cuda_weights_test.test.Qwen tower weights: indexed MLX fallback and sharded HF preserve every tensor...OK +3/7 qwen_cuda_weights_test.test.Qwen tower weights: malformed selected shape and dtype fail without a fallback...model.visual.patch_embed.proj.weight: f16 { 2, 3, 2, 16, 16 }, expected bf16 { 2, 3, 2, 16, 16 } +model.visual.patch_embed.proj.weight: bf16 { 2, 3, 2, 8, 32 }, expected bf16 { 2, 3, 2, 16, 16 } +vision_tower.patch_embed.proj.weight: f16 { 2, 2, 16, 16, 3 }, expected bf16 { 2, 2, 16, 16, 3 } +vision_tower.patch_embed.proj.weight: bf16 { 2, 2, 16, 8, 6 }, expected bf16 { 2, 2, 16, 16, 3 } +OK +4/7 qwen_cuda_weights_test.test.Qwen tower weights: missing selected tensor and unused selected tensors fail closed...checkpoint has no tensor vision_tower.blocks.0.mlp.linear_fc1.bias +unused checkpoint tensor vision_tower.extra +checkpoint has no tensor model.visual.blocks.0.mlp.linear_fc1.bias +unused checkpoint tensor model.visual.extra +OK +5/7 qwen_cuda_weights_test.test.Qwen tower weights: HF patch keeps the authored precedence when both namespaces exist...OK +6/7 qwen_cuda_weights_test.test.Qwen tower weights: every copy refusal and MLX retry release their host owners...OK +7/7 qwen_cuda_weights_test.test.Qwen tower weights: allocation failures balance the fallback reader and transpose scratch...OK +7 passed; 0 skipped; 0 failed. +test ++- test-cuda-host + +- run test w +[default] (warn): .zig-cache/o/798fb84b28b783eedda8dc96ee39d37e/libpicture-codec-wrong.so is not libjpeg-turbo 3.1.4.1; JPEG images are refused until it is +[default] (warn): .zig-cache/o/798fb84b28b783eedda8dc96ee39d37e/libpicture-codec-wrong.so is not libwebp 1.6.0; WebP images are refused until it is +failed command: ./.zig-cache/o/1fc5b01ba92aebe4a4d2d5cb2d452913/test --cache-dir=./.zig-cache --seed=0x96c3cd6f --listen=- + +test ++- test-cuda-host + +- run test w +tf_h3_forward: BadH3Dimensions +tf_h3_forward_host: BadH3Dimensions +tf_h3_forward: BadH3Dimensions +tf_h3_forward_host: BadH3Dimensions +tf_h3_forward: BadH3Dimensions +tf_h3_forward_host: BadH3Dimensions +tf_h3_forward: BadH3Rotary +tf_h3_forward_host: BadH3Rotary +tf_h3_forward: BadH3Rotary +tf_h3_forward_host: BadH3Rotary +tf_h3_forward: BadH3Keep +tf_h3_forward_host: BadH3Keep +tf_h3_forward: BadH3Keep +tf_h3_forward_host: BadH3Keep +tf_h3_forward: BadH3Blocks +tf_h3_forward_host: BadH3Blocks +tf_h3_forward: BadH3Scalar +tf_h3_forward_host: BadH3Scalar +tf_h3_forward: BadH3Scalar +tf_h3_forward_host: BadH3Scalar +tf_h3_forward: BadH3Address +tf_h3_forward_host: BadH3Address +tf_h3_forward: BadH3Address +tf_h3_forward_host: BadH3Address +tf_h3_forward: BadH3Address +tf_h3_forward_host: BadH3Address +tf_h3_forward: BadH3Address +tf_h3_forward_host: BadH3Address +tf_h3_forward: BadH3Address +tf_h3_forward_host: BadH3Address +tf_h3_forward_host: BadH3Address +tf_h3_forward_host: BadH3Scalar +H3 model retained at close: NotReady +H3 geometry retained: NotReady +tensor blocks.0.norm1.weight: MissingTensor +tensor blocks.1.attn.qkv_proj.weight: MissingTensor +tensor blocks.1.norm1.weight: MissingTensor +failed command: ./.zig-cache/o/bf2bd03339780b7ca9191ed10e787a73/test --cache-dir=./.zig-cache --seed=0x96c3cd6f --listen=- + +test ++- test-cuda-host + +- run test w +VISION_LFM2 markers=104; every omitted entry refused +VISION_LFM2_AUTO valid stays enabled; missing and non-added disable pictures with warning +libjpeg-turbo 3.1.4.1 not found: LFM2's JPEG cases skipped +libjpeg-turbo 3.1.4.1 not found: LFM2's JPEG cases skipped +failed command: ./.zig-cache/o/3dc36e7d53eef43a67c42ff1b1834a57/test --cache-dir=./.zig-cache --seed=0x96c3cd6f --listen=- + +test ++- test-cuda-host + +- run test w +[default] (err): rank 0: another rank's process ended (its line closed); this rank stops instead of waiting on it +[default] (err): rank 0: rank 1 stopped (peer OOM); this rank stops too +failed command: ./.zig-cache/o/639c7028cb0056c2e69fcbb59d390140/test --cache-dir=./.zig-cache --seed=0x96c3cd6f --listen=- + +test ++- test-cuda-host + +- run test w +FAIL kernel-contract: unknown image name: unknown_image +FAIL kernel-contract: unknown image name: glm_glu +FAIL kernel-contract: unknown image name: +FAIL kernel-contract: unknown image name: contract_control +FAIL kernel-contract: unknown image name: GLM_GLUE +failed command: ./.zig-cache/o/865f010ba389242ae5bf5e40409c7ef9/test --cache-dir=./.zig-cache --seed=0x96c3cd6f --listen=- + +test ++- test-cuda-host + +- run test w +[default] (warn): qwen3_5: a failed restore's stream did not drain: its kept state's host copy stays +[default] (warn): qwen3_5: a kept state's host copy goes to the copy-source quarantine: a restore's copies did not drain +[default] (warn): qwen3_5: a failed restore's stream did not drain: its kept state's host copy stays +[default] (warn): qwen3_5: a lane's table did not take the kept pages: NotReady +failed command: ./.zig-cache/o/f3e5e26ec3a0a4aa0fba93977402f456/test --cache-dir=./.zig-cache --seed=0x96c3cd6f --listen=- + +test ++- test-cuda-host + +- run test w +page deinit: context_waits=1, unsafe_frees=0 +all-on-pages third opening: capped=false, error=LaneMemory, allocations=3->3, slots=2 +all-on-pages third opening: capped=true, error=LaneMemory, allocations=3->3, slots=2 +failed command: ./.zig-cache/o/f87f94b999c9b9045b8fd98d7079f1f6/test --cache-dir=./.zig-cache --seed=0x96c3cd6f --listen=- + +test ++- test-cuda-host + +- run test w +[default] (warn): qwen3_5: a failed restore's stream did not drain: its kept state's host copy stays +[default] (warn): qwen3_5: a kept state's host copy goes to the copy-source quarantine: a restore's copies did not drain +[default] (warn): qwen3_5: a failed restore's stream did not drain: its kept state's host copy stays +failed command: ./.zig-cache/o/d197e339e6a4852d330f7ea3659bc129/test --cache-dir=./.zig-cache --seed=0x96c3cd6f --listen=- + +test ++- test-cuda-host + +- test-glm-contract-host + +- run test w +GLM 64-sums width=512 hc=false BF16 minimum=32832.12524461839x +GLM 64-sums width=1536 hc=false BF16 minimum=32832.12524461839x +GLM 64-sums width=4096 hc=false BF16 minimum=32832.12524461839x +GLM 64-sums width=4096 hc=true BF16 minimum=32832.12524461839x +failed command: ./.zig-cache/o/e0f0114fd36a6fe1335dd3a2eff8c29e/test --cache-dir=./.zig-cache --seed=0x96c3cd6f --listen=- + +test ++- test-cuda-host + +- run test w +[default] (warn): lm_head is 8-bit in groups of 64: CUDA reads Nemotron MLX checkpoints at 4-bit in groups of 64 only; mixed and 6- or 8-bit (oQ) checkpoints serve on Macs +[default] (warn): backbone.embeddings is 8-bit in groups of 64: the Intel GPU engine reads Nemotron MLX checkpoints at 4-bit in groups of 64 only; mixed and 6- or 8-bit (oQ) checkpoints serve on Macs +fake target: proposed=68 verified=68 accepted=68 +failed command: ./.zig-cache/o/32f54fa9da629f5479b671555ff569b7/test --cache-dir=./.zig-cache --seed=0x96c3cd6f --listen=- + +test ++- test-cuda-host + +- run test w +RESULT CPU reference comparison: largest difference 1.000 of its tolerance (element 1) +RESULT CPU reference comparison: largest difference 1.000 of its tolerance (element 1) +RESULT CPU reference comparison: largest difference 2.000 of its tolerance (element 0) +FAIL CPU reference comparison within its float64 tolerance +RESULT CPU reference comparison: largest difference 2.000 of its tolerance (element 0) +FAIL CPU reference comparison within its float64 tolerance +FAIL CPU reference comparison: non-finite error at element 0 (got nan, reference 0e0, tolerance 1e0) +FAIL CPU reference comparison: non-finite error at element 1 (got nan, reference 0e0, tolerance 1e0) +FAIL CPU reference comparison: non-finite error at element 2 (got nan, reference 0e0, tolerance 1e0) +FAIL CPU reference comparison: non-finite error at element 0 (got -nan, reference 0e0, tolerance 1e0) +FAIL CPU reference comparison: non-finite error at element 1 (got -nan, reference 0e0, tolerance 1e0) +FAIL CPU reference comparison: non-finite error at element 2 (got -nan, reference 0e0, tolerance 1e0) +FAIL CPU reference comparison: non-finite error at element 0 (got nan, reference 0e0, tolerance 1e0) +FAIL CPU reference comparison: non-finite error at element 1 (got nan, reference 0e0, tolerance 1e0) +FAIL CPU reference comparison: non-finite error at element 2 (got nan, reference 0e0, tolerance 1e0) +FAIL CPU reference comparison: non-finite error at element 0 (got -nan, reference 0e0, tolerance 1e0) +FAIL CPU reference comparison: non-finite error at element 1 (got -nan, reference 0e0, tolerance 1e0) +FAIL CPU reference comparison: non-finite error at element 2 (got -nan, reference 0e0, tolerance 1e0) +FAIL CPU reference comparison: non-finite error at element 1 (got inf, reference 0e0, tolerance 1e0) +FAIL CPU reference comparison: non-finite error at element 1 (got -inf, reference 0e0, tolerance 1e0) +FAIL CPU reference comparison: non-finite error at element 1 (got inf, reference 0e0, tolerance 1e0) +FAIL CPU reference comparison: non-finite error at element 1 (got -inf, reference 0e0, tolerance 1e0) +FAIL CPU reference comparison: non-finite error at element 1 (got nan, reference 0e0, tolerance 1e0) +FAIL CPU reference comparison: non-finite error at element 0 (got inf, reference 0e0, tolerance 1e0) +FAIL CPU reference comparison: non-finite error at element 1 (got -nan, reference 0e0, tolerance 1e0) +FAIL CPU reference comparison: non-finite error at element 0 (got inf, reference 0e0, tolerance 1e0) +failed command: ./.zig-cache/o/3140c5edaf17a19eeaf766115f2cf648/test --cache-dir=./.zig-cache --seed=0x96c3cd6f --listen=- + +test ++- test-cuda-host + +- run test w +RESULT valid stale prefix: largest difference 0.000 of its tolerance (element 0) +FAIL no-op projection: non-finite error at element 0 (got -nan, reference 0e0, tolerance 1e0) +RESULT valid stale prefix: largest difference 0.000 of its tolerance (element 0) +FAIL no-op projection: non-finite error at element 0 (got -nan, reference 0e0, tolerance 1e0) +RESULT valid stale prefix: largest difference 0.000 of its tolerance (element 0) +FAIL no-op projection: non-finite error at element 0 (got -nan, reference 0e0, tolerance 1e0) +RESULT valid stale prefix: largest difference 0.000 of its tolerance (element 0) +FAIL no-op projection: non-finite error at element 0 (got -nan, reference 0e0, tolerance 1e0) +RESULT valid stale prefix: largest difference 0.000 of its tolerance (element 0) +FAIL no-op projection: non-finite error at element 0 (got -nan, reference 0e0, tolerance 1e0) +RESULT valid stale prefix: largest difference 0.000 of its tolerance (element 0) +FAIL no-op projection: non-finite error at element 0 (got -nan, reference 0e0, tolerance 1e0) +RESULT valid stale prefix: largest difference 0.000 of its tolerance (element 0) +FAIL no-op projection: non-finite error at element 0 (got -nan, reference 0e0, tolerance 1e0) +RESULT valid stale prefix: largest difference 0.000 of its tolerance (element 0) +FAIL no-op projection: non-finite error at element 0 (got -nan, reference 0e0, tolerance 1e0) +RESULT valid stale prefix: largest difference 0.000 of its tolerance (element 0) +FAIL no-op projection: non-finite error at element 0 (got -nan, reference 0e0, tolerance 1e0) +RESULT valid stale prefix: largest difference 0.000 of its tolerance (element 0) +FAIL no-op projection: non-finite error at element 0 (got -nan, reference 0e0, tolerance 1e0) +RESULT valid stale prefix: largest difference 0.000 of its tolerance (element 0) +FAIL no-op projection: non-finite error at element 0 (got -nan, reference 0e0, tolerance 1e0) +RESULT valid stale prefix: largest difference 0.000 of its tolerance (element 0) +FAIL no-op projection: non-finite error at element 0 (got -nan, reference 0e0, tolerance 1e0) +RESULT valid stale prefix: largest difference 0.000 of its tolerance (element 0) +FAIL no-op projection: non-finite error at element 0 (got -nan, reference 0e0, tolerance 1e0) +RESULT valid stale prefix: largest difference 0.000 of its tolerance (element 0) +FAIL no-op projection: non-finite error at element 0 (got -nan, reference 0e0, tolerance 1e0) +RESULT valid stale prefix: largest difference 0.000 of its tolerance (element 0) +FAIL no-op projection: non-finite error at element 0 (got -nan, reference 0e0, tolerance 1e0) +RESULT valid stale prefix: largest difference 0.000 of its tolerance (element 0) +FAIL no-op projection: non-finite error at element 0 (got -nan, reference 0e0, tolerance 1e0) +RESULT valid stale prefix: largest difference 0.000 of its tolerance (element 0) +FAIL no-op projection: non-finite error at element 0 (got -nan, reference 0e0, tolerance 1e0) +RESULT valid stale prefix: largest difference 0.000 of its tolerance (element 0) +FAIL no-op projection: non-finite error at element 0 (got -nan, reference 0e0, tolerance 1e0) +RESULT valid stale prefix: largest difference 0.000 of its tolerance (element 0) +FAIL no-op projection: non-finite error at element 0 (got -nan, reference 0e0, tolerance 1e0) +RESULT valid stale prefix: largest difference 0.000 of its tolerance (element 0) +FAIL no-op projection: non-finite error at element 0 (got -nan, reference 0e0, tolerance 1e0) +failed command: ./.zig-cache/o/f18a54ac0f3af38a150ef4b7d8494bc9/test --cache-dir=./.zig-cache --seed=0x96c3cd6f --listen=- + +test ++- test-cuda-host + +- run test w +TOWER_SUM qkv f32 sequential worst=0e0 +TOWER_SUM qkv f16 sequential worst=3.390625e30 +TOWER_SUM qkv bf16 sequential worst=4.6875e28 +TOWER_SUM qkv f32 pairwise worst=0e0 +TOWER_SUM qkv f16 pairwise worst=3.390625e30 +TOWER_SUM qkv bf16 pairwise worst=1.5624999999999998e28 +TOWER_SUM qkv f32 strided worst=0e0 +TOWER_SUM qkv f16 strided worst=3.390625e30 +TOWER_SUM qkv bf16 strided worst=1.5624999999999998e28 +TOWER_SUM pool f32 sequential worst=0e0 +TOWER_SUM pool f16 sequential worst=inf +TOWER_SUM pool bf16 sequential worst=2.38e32 +TOWER_SUM pool f32 pairwise worst=0e0 +TOWER_SUM pool f16 pairwise worst=inf +TOWER_SUM pool bf16 pairwise worst=2.38e32 +TOWER_SUM pool f32 strided worst=0e0 +TOWER_SUM pool f16 strided worst=inf +TOWER_SUM pool bf16 strided worst=2.38e32 +failed command: ./.zig-cache/o/135fd8af9d814f7d417576f0e14388d8/test --cache-dir=./.zig-cache --seed=0x96c3cd6f --listen=- + +test ++- test-cuda-host + +- run test w +[default] (warn): Drama readback drain failed: retaining its buffers and engine owner +[default] (warn): Drama readback drain failed: retaining its buffers and engine owner +codec requested 1, actual sizes { 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 } +codec requested 1, actual sizes { 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 } +codec requested 4, actual sizes { 4, 4, 4, 4, 1 } +codec requested 16, actual sizes { 16, 1 } +codec requested 1, actual sizes { 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 } +Drama replay passed: eager/graphs, poison/reset, codec chunks and interleaved state +[default] (warn): drama3: config hidden_size = 4096, the kernels need 2048 +[default] (warn): codec.pth pickle names os.system, outside the tensor state-dict allow-list +failed command: ./.zig-cache/o/d14961ea7e83ae92076ad4dac5a6e25b/test --cache-dir=./.zig-cache --seed=0x96c3cd6f --listen=- + +test ++- test-cuda-host + +- run test w +[default] (warn): lane host: stopping at a round boundary: 2 running and 1 queued request(s) end (server restarting: retry shortly) +[default] (warn): lane host: stopping at a round boundary: 1 running and 0 queued request(s) end (server restarting: retry shortly) +[default] (warn): lane host: a round failed (GpuFailed): every admitted stream fails +[default] (warn): lane host: a round failed (GpuFailed): every admitted stream fails +[default] (warn): 4 prompts together: SamplingRefused; each goes alone +[default] (warn): lane host: a round failed (GpuFailed): every admitted stream fails +[default] (warn): lane host: a round failed (the planner refused): every admitted stream fails +[default] (warn): lane host: a round failed (PlannerFull): every admitted stream fails +[default] (warn): lane host: a decision score failed (EmptyLabels) +[default] (warn): lane host: stopping at a round boundary: 1 running and 1 queued request(s) end (drain deadline) +[default] (warn): lane host: stopping at a round boundary: 0 running and 1 queued request(s) end (NoContext) +[default] (warn): lane host: a round failed (OutOfMemory): every admitted stream fails +[default] (warn): lane host: a round failed (AdmittedFailed): every admitted stream fails +[default] (warn): lane host: a round failed (FinalsFailed): every admitted stream fails +failed command: ./.zig-cache/o/907d7dc137dfef22b48a8a542ae7b0f8/test --cache-dir=./.zig-cache --seed=0x96c3cd6f --listen=- + +test ++- test-cuda-host + +- run test w +[default] (warn): slide pocket: a deleted fact's 1 layers are put back in memory, but not all on the device (UploadFailed): replies are refused until they are +[default] (warn): slide pocket: a deleted fact's 1 layers are put back in memory, but not all on the device (UploadFailed): replies are refused until they are +[default] (warn): slide pocket: a deleted fact's 2 layers are put back in memory, but not all on the device (UploadFailed): replies are refused until they are +[default] (warn): slide pocket: a delete failed (UploadFailed), and its put-back did not reach the device (PutBackNotOnDevice) +[default] (warn): slide pocket: a deleted fact's 2 layers are put back in memory, but not all on the device (UploadFailed): replies are refused until they are +[default] (warn): slide pocket: a delete failed (UploadFailed), and its put-back did not reach the device (PutBackNotOnDevice) +[default] (warn): slide pocket: a deleted fact's 2 layers are put back in memory, but not all on the device (UploadFailed): replies are refused until they are +failed command: ./.zig-cache/o/04761e520da520286bbf3ecfa0281c20/test --cache-dir=./.zig-cache --seed=0x96c3cd6f --listen=- + +test ++- test-cuda-host + +- run test w +DEEPSEEK_CHAT_GOLDENS 178 committed encoding.py cases +failed command: ./.zig-cache/o/97e76f409d40c53d69952d552e6a660c/test --cache-dir=./.zig-cache --seed=0x96c3cd6f --listen=- + +test ++- test-cuda-host + +- run test w +GLM_KV_BYTES context=8192 capacity=8256 main_layers=11 bf16=296101376 fp8=245772800 +GLM_KV_BYTES context=65536 capacity=65600 main_layers=11 bf16=1044784640 fp8=644887040 +GLM_KV_BYTES context=199307 capacity=199360 main_layers=11 bf16=2791155200 fp8=1575856640 +GLM_KV_BYTES context=245760 capacity=245824 main_layers=11 bf16=3397789184 fp8=1899246080 +REFUSE TF_GLM_PREFILL_REDUCE=split: rank 0 cannot exchange with rank 2; split sends every rank's rows to every other, and a fabric where some ranks reach only their neighbours (a ring of four without a switch) needs TF_GLM_PREFILL_REDUCE=ring or gather +REFUSE TF_GLM_PREFILL_REDUCE=split: rank 1 cannot exchange with rank 3; split sends every rank's rows to every other, and a fabric where some ranks reach only their neighbours (a ring of four without a switch) needs TF_GLM_PREFILL_REDUCE=ring or gather +REFUSE TF_GLM_PREFILL_REDUCE=split: rank 2 cannot exchange with rank 0; split sends every rank's rows to every other, and a fabric where some ranks reach only their neighbours (a ring of four without a switch) needs TF_GLM_PREFILL_REDUCE=ring or gather +REFUSE TF_GLM_PREFILL_REDUCE=split: rank 3 cannot exchange with rank 1; split sends every rank's rows to every other, and a fabric where some ranks reach only their neighbours (a ring of four without a switch) needs TF_GLM_PREFILL_REDUCE=ring or gather +failed command: ./.zig-cache/o/04a49c87cd05a46988782ea69b57a2be/test --cache-dir=./.zig-cache --seed=0x96c3cd6f --listen=- + +test ++- run test w +[default] (warn): glm: restoring 1500 tokens failed (PoolMoveNotDrained); pool relocation aborted +failed command: ./.zig-cache/o/9f4cd11285c752f0817ab542583de05d/test --cache-dir=./.zig-cache --seed=0x96c3cd6f --listen=- + +test ++- test-cuda-host + +- run test w +libjpeg-turbo 3.1.4.1 not found: JPEG pixel cases skipped +libjpeg-turbo 3.1.4.1 not found: JPEG pixel cases skipped +libwebp 1.6.0 not found: WebP pixel cases skipped +libjpeg-turbo 3.1.4.1 not found: JPEG pixel cases skipped +[default] (warn): model.layers.0.mlp.up_proj.weight: another spelling of module layers.0.mlp.up_proj declares a different width +[default] (warn): layers.0.mlp.up_proj: another spelling of module layers.0.mlp.up_proj declares a different width +[default] (warn): model.layers.0.mlp.up_proj: another spelling of module layers.0.mlp.up_proj declares a different width +failed command: ./.zig-cache/o/8f7de78b7d95287989da16c12245717e/test --cache-dir=./.zig-cache --seed=0x96c3cd6f --listen=- + +test ++- test-cuda-host + +- run test w +RESULT CPU reference comparison: largest difference 1.000 of its tolerance (element 1) +RESULT CPU reference comparison: largest difference 1.000 of its tolerance (element 1) +RESULT CPU reference comparison: largest difference 2.000 of its tolerance (element 0) +FAIL CPU reference comparison within its float64 tolerance +RESULT CPU reference comparison: largest difference 2.000 of its tolerance (element 0) +FAIL CPU reference comparison within its float64 tolerance +FAIL CPU reference comparison: non-finite error at element 0 (got nan, reference 0e0, tolerance 1e0) +FAIL CPU reference comparison: non-finite error at element 1 (got nan, reference 0e0, tolerance 1e0) +FAIL CPU reference comparison: non-finite error at element 2 (got nan, reference 0e0, tolerance 1e0) +FAIL CPU reference comparison: non-finite error at element 0 (got -nan, reference 0e0, tolerance 1e0) +FAIL CPU reference comparison: non-finite error at element 1 (got -nan, reference 0e0, tolerance 1e0) +FAIL CPU reference comparison: non-finite error at element 2 (got -nan, reference 0e0, tolerance 1e0) +FAIL CPU reference comparison: non-finite error at element 0 (got nan, reference 0e0, tolerance 1e0) +FAIL CPU reference comparison: non-finite error at element 1 (got nan, reference 0e0, tolerance 1e0) +FAIL CPU reference comparison: non-finite error at element 2 (got nan, reference 0e0, tolerance 1e0) +FAIL CPU reference comparison: non-finite error at element 0 (got -nan, reference 0e0, tolerance 1e0) +FAIL CPU reference comparison: non-finite error at element 1 (got -nan, reference 0e0, tolerance 1e0) +FAIL CPU reference comparison: non-finite error at element 2 (got -nan, reference 0e0, tolerance 1e0) +FAIL CPU reference comparison: non-finite error at element 1 (got inf, reference 0e0, tolerance 1e0) +FAIL CPU reference comparison: non-finite error at element 1 (got -inf, reference 0e0, tolerance 1e0) +FAIL CPU reference comparison: non-finite error at element 1 (got inf, reference 0e0, tolerance 1e0) +FAIL CPU reference comparison: non-finite error at element 1 (got -inf, reference 0e0, tolerance 1e0) +FAIL CPU reference comparison: non-finite error at element 1 (got nan, reference 0e0, tolerance 1e0) +FAIL CPU reference comparison: non-finite error at element 0 (got inf, reference 0e0, tolerance 1e0) +FAIL CPU reference comparison: non-finite error at element 1 (got -nan, reference 0e0, tolerance 1e0) +FAIL CPU reference comparison: non-finite error at element 0 (got inf, reference 0e0, tolerance 1e0) +failed command: ./.zig-cache/o/14a1793a004a3050c6d072cdb75ef1d7/test --cache-dir=./.zig-cache --seed=0x96c3cd6f --listen=- + +test ++- test-cuda-host + +- run test w +RESULT valid stale prefix: largest difference 0.000 of its tolerance (element 0) +FAIL no-op projection: non-finite error at element 0 (got -nan, reference 0e0, tolerance 1e0) +RESULT valid stale prefix: largest difference 0.000 of its tolerance (element 0) +FAIL no-op projection: non-finite error at element 0 (got -nan, reference 0e0, tolerance 1e0) +RESULT valid stale prefix: largest difference 0.000 of its tolerance (element 0) +FAIL no-op projection: non-finite error at element 0 (got -nan, reference 0e0, tolerance 1e0) +RESULT valid stale prefix: largest difference 0.000 of its tolerance (element 0) +FAIL no-op projection: non-finite error at element 0 (got -nan, reference 0e0, tolerance 1e0) +RESULT valid stale prefix: largest difference 0.000 of its tolerance (element 0) +FAIL no-op projection: non-finite error at element 0 (got -nan, reference 0e0, tolerance 1e0) +RESULT valid stale prefix: largest difference 0.000 of its tolerance (element 0) +FAIL no-op projection: non-finite error at element 0 (got -nan, reference 0e0, tolerance 1e0) +RESULT valid stale prefix: largest difference 0.000 of its tolerance (element 0) +FAIL no-op projection: non-finite error at element 0 (got -nan, reference 0e0, tolerance 1e0) +RESULT valid stale prefix: largest difference 0.000 of its tolerance (element 0) +FAIL no-op projection: non-finite error at element 0 (got -nan, reference 0e0, tolerance 1e0) +RESULT valid stale prefix: largest difference 0.000 of its tolerance (element 0) +FAIL no-op projection: non-finite error at element 0 (got -nan, reference 0e0, tolerance 1e0) +RESULT valid stale prefix: largest difference 0.000 of its tolerance (element 0) +FAIL no-op projection: non-finite error at element 0 (got -nan, reference 0e0, tolerance 1e0) +RESULT valid stale prefix: largest difference 0.000 of its tolerance (element 0) +FAIL no-op projection: non-finite error at element 0 (got -nan, reference 0e0, tolerance 1e0) +RESULT valid stale prefix: largest difference 0.000 of its tolerance (element 0) +FAIL no-op projection: non-finite error at element 0 (got -nan, reference 0e0, tolerance 1e0) +RESULT valid stale prefix: largest difference 0.000 of its tolerance (element 0) +FAIL no-op projection: non-finite error at element 0 (got -nan, reference 0e0, tolerance 1e0) +RESULT valid stale prefix: largest difference 0.000 of its tolerance (element 0) +FAIL no-op projection: non-finite error at element 0 (got -nan, reference 0e0, tolerance 1e0) +RESULT valid stale prefix: largest difference 0.000 of its tolerance (element 0) +FAIL no-op projection: non-finite error at element 0 (got -nan, reference 0e0, tolerance 1e0) +RESULT valid stale prefix: largest difference 0.000 of its tolerance (element 0) +FAIL no-op projection: non-finite error at element 0 (got -nan, reference 0e0, tolerance 1e0) +RESULT valid stale prefix: largest difference 0.000 of its tolerance (element 0) +FAIL no-op projection: non-finite error at element 0 (got -nan, reference 0e0, tolerance 1e0) +RESULT valid stale prefix: largest difference 0.000 of its tolerance (element 0) +FAIL no-op projection: non-finite error at element 0 (got -nan, reference 0e0, tolerance 1e0) +RESULT valid stale prefix: largest difference 0.000 of its tolerance (element 0) +FAIL no-op projection: non-finite error at element 0 (got -nan, reference 0e0, tolerance 1e0) +RESULT valid stale prefix: largest difference 0.000 of its tolerance (element 0) +FAIL no-op projection: non-finite error at element 0 (got -nan, reference 0e0, tolerance 1e0) +failed command: ./.zig-cache/o/1a3f914dbf2b7eb7b7e300fe13f7fdc6/test --cache-dir=./.zig-cache --seed=0x96c3cd6f --listen=- + +test ++- test-cuda-host + +- run test w +DEPTH_REPLAY n=2 intercept=50 slope=3 head=1 probe=false deepest=6 crossed={ 62, 62 } last={ 6, 6 } trimmed=0 +DEPTH_REPLAY n=2 intercept=50 slope=3 head=1 probe=true deepest=8 crossed={ 59, 57 } last={ 7, 8 } trimmed=11 +DEPTH_REPLAY n=4 intercept=50 slope=3 head=1 probe=false deepest=4 crossed={ 83, 83, 83, 83 } last={ 4, 4, 4, 4 } trimmed=0 +DEPTH_REPLAY n=4 intercept=50 slope=3 head=1 probe=true deepest=5 crossed={ 75, 83, 83, 76 } last={ 5, 5, 5, 5 } trimmed=9 +DEPTH_REPLAY n=2 intercept=55 slope=2.8 head=1 probe=false deepest=6 crossed={ 61, 61 } last={ 6, 6 } trimmed=0 +DEPTH_REPLAY n=2 intercept=55 slope=2.8 head=1 probe=true deepest=8 crossed={ 54, 56 } last={ 8, 8 } trimmed=2 +DEPTH_REPLAY n=4 intercept=55 slope=2.8 head=1 probe=false deepest=4 crossed={ 82, 82, 82, 82 } last={ 4, 4, 4, 4 } trimmed=0 +DEPTH_REPLAY n=4 intercept=55 slope=2.8 head=1 probe=true deepest=6 crossed={ 75, 71, 72, 74 } last={ 5, 6, 5, 5 } trimmed=9 +DEPTH_REPLAY n=8 intercept=100 slope=0 head=0 probe=false deepest=3 crossed={ 100, 100, 100, 100, 100, 100, 100, 100 } last={ 3, 3, 3, 3, 3, 3, 3, 3 } trimmed=0 +DEPTH_REPLAY n=8 intercept=100 slope=0 head=0 probe=true deepest=3 crossed={ 100, 100, 100, 100, 100, 100, 100, 100 } last={ 3, 3, 3, 3, 3, 3, 3, 3 } trimmed=0 +failed command: ./.zig-cache/o/d5e10a2852cdc646679fc7faec52a469/test --cache-dir=./.zig-cache --seed=0x96c3cd6f --listen=- + +test ++- run test w +[default] (warn): lane host: stopping at a round boundary: 2 running and 1 queued request(s) end (server restarting: retry shortly) +[default] (warn): lane host: stopping at a round boundary: 1 running and 0 queued request(s) end (server restarting: retry shortly) +[default] (warn): lane host: a round failed (GpuFailed): every admitted stream fails +[default] (warn): lane host: a round failed (GpuFailed): every admitted stream fails +[default] (warn): 4 prompts together: SamplingRefused; each goes alone +[default] (warn): lane host: a round failed (GpuFailed): every admitted stream fails +[default] (warn): lane host: a round failed (the planner refused): every admitted stream fails +[default] (warn): lane host: a round failed (PlannerFull): every admitted stream fails +[default] (warn): lane host: a decision score failed (EmptyLabels) +[default] (warn): lane host: stopping at a round boundary: 1 running and 1 queued request(s) end (drain deadline) +[default] (warn): lane host: stopping at a round boundary: 0 running and 1 queued request(s) end (NoContext) +[default] (warn): lane host: a round failed (OutOfMemory): every admitted stream fails +[default] (warn): lane host: a round failed (AdmittedFailed): every admitted stream fails +[default] (warn): lane host: a round failed (FinalsFailed): every admitted stream fails +failed command: ./.zig-cache/o/d7844fa7bbf1f1a119ccb9808b51db1c/test --cache-dir=./.zig-cache --seed=0x96c3cd6f --listen=- + +test ++- test-cuda-host + +- run test w +PROVENANCE_FIELDS fixtures=3 fields=14 plus decision labels +PROVENANCE_TIMING mode=raw one=0 bytes=409600 added=1000 rounds=12 ns_per=3160047 +PROVENANCE_TIMING mode=masked one=0 bytes=409600 added=1000 rounds=12 ns_per=3313287 +PROVENANCE_MASK_WORK one=0 spans=3 matcher=3 output=409603 +PROVENANCE_TIMING mode=raw one=1 bytes=409600 added=1000 rounds=12 ns_per=3040461 +PROVENANCE_TIMING mode=masked one=1 bytes=409600 added=1000 rounds=12 ns_per=2991920 +PROVENANCE_MASK_WORK one=1 spans=3 matcher=3 output=409603 +[default] (warn): TENSORFOLD_REQUEST_LOG .zig-cache/tmp/605Bg5IuDWkAO9WA/taken.jsonl gets no requests: it is not a regular file only its owner can read +DEEPSEEK_CHAT_GOLDENS 178 committed encoding.py cases +VISION_MARKERS all 8 fields refuse plain vocabulary; unflagged additions pass +[default] (warn): libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[default] (warn): libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[default] (warn): libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[default] (warn): libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +invalid output: first-write inflight=0 +Busy: first-write inflight=0 +Closed: first-write inflight=0 +InvalidRequest: first-write inflight=0 +Unsupported: first-write inflight=0 +completed stream: first-write inflight=0 +[default] (warn): libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +failed command: ./.zig-cache/o/3a395392f7ca02792f318db94d496e31/test --cache-dir=./.zig-cache --seed=0x96c3cd6f --listen=- + +test ++- test-qwen4-host + +- run test w +QWEN4_FIRST_DIFFERENCE row=1 name=second values=1 +QWEN4_FIRST_DIFFERENCE row=1 name=second values=1 +QWEN4_FIRST_DIFFERENCE row=1 name=model.layers.1.self_attn.attention values=42 +PASS qwen4 binary64: 384 logits and 12 GPU token picks +PASS qwen4 prompt cuts and resumed == fresh: 11 cuts, every logit and token +PASS qwen4 concurrent == solo: unequal histories, single rows and packed prompts +PASS qwen4 copied drafted == plain: 8 tokens, 15 proposed +N/A qwen4 learned MTP: no declared head; positive MTP configs refuse admission +PASS qwen4 device: binary64, tokens, repeats, cuts, resume, concurrency, rollback and copied drafts +FAIL qwen4 binary64 row=11 col=31: expected 0xbf18, got 0xbf19 +FAIL qwen4 binary64: 1/384 logits differ +FAIL qwen4 binary64 token picks: expected 12 values, got 12; first difference 11 +FAIL qwen4 binary64 row=11 col=31: expected 0xbf18, got 0xbe18 +FAIL qwen4 binary64: 1/384 logits differ +PASS qwen4 binary64: 384 logits and 12 GPU token picks +PASS qwen4 prompt cuts and resumed == fresh: 11 cuts, every logit and token +PASS qwen4 concurrent == solo: unequal histories, single rows and packed prompts +PASS qwen4 copied drafted == plain: 8 tokens, 15 proposed +N/A qwen4 learned MTP: no declared head; positive MTP configs refuse admission +PASS qwen4 device: binary64, tokens, repeats, cuts, resume, concurrency, rollback and copied drafts +QWEN4_FIRST_DIFFERENCE row=1 name=model.layers.1.self_attn.attention values=24 +failed command: ./.zig-cache/o/2a82a82532baa3238ae2220706e1c1fa/test --cache-dir=./.zig-cache --seed=0x96c3cd6f --listen=- + diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/checkpoint.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/checkpoint.json new file mode 100644 index 0000000000..3a0bc87b38 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/checkpoint.json @@ -0,0 +1,146 @@ +{ + "repo_id": "TensorFold/Qwen3.8-Flash-Next-MLX-4bit-MTP", + "revision": "2b170fa6309d5d1ee380b35636075fac7945f286", + "files": { + ".gitattributes": { + "bytes": 1570, + "sha256": "34448b82c17d60fec9b65b1f093c115ddbaadc04beb1b0140b6bfed2e012a930" + }, + "LICENSE": { + "bytes": 3235, + "sha256": "a0dc422560841fd68e06d974907f8b4c709bca44a67daad2b528437bdf676c08" + }, + "README.md": { + "bytes": 10306, + "sha256": 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"bytes": 17928, + "sha256": "b11349aafa7cdc6a320767cf7ceb29ed82f7eda5d65e8e0819e76f0ce947bf27" + }, + "vocab.json": { + "bytes": 6722759, + "sha256": "ce99b4cb2983d118806ce0a8b777a35b093e2000a503ebde25853284c9dfa003" + } + } +} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/environment.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/environment.json new file mode 100644 index 0000000000..23b3ef40d1 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/environment.json @@ -0,0 +1,7 @@ +{ + "gpu_arch": "gfx1151", + "rocm": "7.15.26333-0000000", + "python": "3.13.5", + "mem_total_kib": 193548104, + "native_window_tokens": 262144 +} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/exactness/exact-rewind-nocache.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/exactness/exact-rewind-nocache.json new file mode 100644 index 0000000000..b00c3bbcce --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/exactness/exact-rewind-nocache.json @@ -0,0 +1,66 @@ +{ + "turn 1, drafts on": [ + "The first note is **note0x0**.", + 0 + ], + "turn 2, drafts on": [ + "The second note is **note1x828**.", + 0 + ], + "turn 3, drafts on": [ + "No, **note5x5** is not listed in the provided reference notes.\n\nThe list contains notes with hex suffixes (e.g., `note5x88`, `note5x587`, `note5", + 0 + ], + "regenerate turn 3, drafts on": [ + "No, **note5x5** is not listed in the provided reference notes.\n\nThe list contains notes with hex suffixes (e.g., `note5x88`, `note5x587`, `note5", + 0 + ], + "edit turn 3, drafts on": [ + "No, **note7x7** is not listed in the provided reference notes.\n\nThe notes follow a pattern where the second part (after the 'x') is a hexadecimal number (e.g., `note1x828", + 0 + ], + "delete turn 3, then turn 4, drafts on": [ + "The last note is **note75x247**.", + 0 + ], + "edit turn 1, drafts on": [ + "The third note is **note2x643**.", + 0 + ], + "turn 2 again, drafts on": [ + "The second note is **note1x828**.", + 0 + ], + "turn 1, drafts off": [ + "The first note is **note0x0**.", + 0 + ], + "turn 2, drafts off": [ + "The second note is **note1x828**.", + 0 + ], + "turn 3, drafts off": [ + "No, **note5x5** is not listed in the provided reference notes.\n\nThe list contains notes with hex suffixes (e.g., `note5x88`, `note5x587`, `note5", + 0 + ], + "regenerate turn 3, drafts off": [ + "No, **note5x5** is not listed in the provided reference notes.\n\nThe list contains notes with hex suffixes (e.g., `note5x88`, `note5x587`, `note5", + 0 + ], + "edit turn 3, drafts off": [ + "No, **note7x7** is not listed in the provided reference notes.\n\nThe notes follow a pattern where the second part (after the 'x') is a hexadecimal number (e.g., `note1x828", + 0 + ], + "delete turn 3, then turn 4, drafts off": [ + "The last note is **note75x247**.", + 0 + ], + "edit turn 1, drafts off": [ + "The third note is **note2x643**.", + 0 + ], + "turn 2 again, drafts off": [ + "The second note is **note1x828**.", + 0 + ] +} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/exactness/exact-rewind-nocache.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/exactness/exact-rewind-nocache.jsonl new file mode 100644 index 0000000000..98ece37f85 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/exactness/exact-rewind-nocache.jsonl @@ -0,0 +1,16 @@ +{"url": "http://127.0.0.1:30461/v1/chat/completions", "request": {"model": "flashnext", "messages": [{"role": "system", "content": "You are a careful assistant. Reference notes: note0x0 note1x828 note2x643 note3x458 note4x273 note5x88 note6x916 note7x731 note8x546 note9x361 note10x176 note11x1004 note12x819 note13x634 note14x449 note15x264 note16x79 note17x907 note18x722 note19x537 note20x352 note21x167 note22x995 note23x810 note24x625 note25x440 note26x255 note27x70 note28x898 note29x713 note30x528 note31x343 note32x158 note33x986 note34x801 note35x616 note36x431 note37x246 note38x61 note39x889 note40x704 note41x519 note42x334 note43x149 note44x977 note45x792 note46x607 note47x422 note48x237 note49x52 note50x880 note51x695 note52x510 note53x325 note54x140 note55x968 note56x783 note57x598 note58x413 note59x228 note60x43 note61x871 note62x686 note63x501 note64x316 note65x131 note66x959 note67x774 note68x589 note69x404 note70x219 note71x34 note72x862 note73x677 note74x492 note75x307 note76x122 note77x950 note78x765 note79x580 note80x395 note81x210 note82x25 note83x853 note84x668 note85x483 note86x298 note87x113 note88x941 note0x756 note1x571 note2x386 note3x201 note4x16 note5x844 note6x659 note7x474 note8x289 note9x104 note10x932 note11x747 note12x562 note13x377 note14x192 note15x7 note16x835 note17x650 note18x465 note19x280 note20x95 note21x923 note22x738 note23x553 note24x368 note25x183 note26x1011 note27x826 note28x641 note29x456 note30x271 note31x86 note32x914 note33x729 note34x544 note35x359 note36x174 note37x1002 note38x817 note39x632 note40x447 note41x262 note42x77 note43x905 note44x720 note45x535 note46x350 note47x165 note48x993 note49x808 note50x623 note51x438 note52x253 note53x68 note54x896 note55x711 note56x526 note57x341 note58x156 note59x984 note60x799 note61x614 note62x429 note63x244 note64x59 note65x887 note66x702 note67x517 note68x332 note69x147 note70x975 note71x790 note72x605 note73x420 note74x235 note75x50 note76x878 note77x693 note78x508 note79x323 note80x138 note81x966 note82x781 note83x596 note84x411 note85x226 note86x41 note87x869 note88x684 note0x499 note1x314 note2x129 note3x957 note4x772 note5x587 note6x402 note7x217 note8x32 note9x860 note10x675 note11x490 note12x305 note13x120 note14x948 note15x763 note16x578 note17x393 note18x208 note19x23 note20x851 note21x666 note22x481 note23x296 note24x111 note25x939 note26x754 note27x569 note28x384 note29x199 note30x14 note31x842 note32x657 note33x472 note34x287 note35x102 note36x930 note37x745 note38x560 note39x375 note40x190 note41x5 note42x833 note43x648 note44x463 note45x278 note46x93 note47x921 note48x736 note49x551 note50x366 note51x181 note52x1009 note53x824 note54x639 note55x454 note56x269 note57x84 note58x912 note59x727 note60x542 note61x357 note62x172 note63x1000 note64x815 note65x630 note66x445 note67x260 note68x75 note69x903 note70x718 note71x533 note72x348 note73x163 note74x991 note75x806 note76x621 note77x436 note78x251 note79x66 note80x894 note81x709 note82x524 note83x339 note84x154 note85x982 note86x797 note87x612 note88x427 note0x242 note1x57 note2x885 note3x700 note4x515 note5x330 note6x145 note7x973 note8x788 note9x603 note10x418 note11x233 note12x48 note13x876 note14x691 note15x506 note16x321 note17x136 note18x964 note19x779 note20x594 note21x409 note22x224 note23x39 note24x867 note25x682 note26x497 note27x312 note28x127 note29x955 note30x770 note31x585 note32x400 note33x215 note34x30 note35x858 note36x673 note37x488 note38x303 note39x118 note40x946 note41x761 note42x576 note43x391 note44x206 note45x21 note46x849 note47x664 note48x479 note49x294 note50x109 note51x937 note52x752 note53x567 note54x382 note55x197 note56x12 note57x840 note58x655 note59x470 note60x285 note61x100 note62x928 note63x743 note64x558 note65x373 note66x188 note67x3 note68x831 note69x646 note70x461 note71x276 note72x91 note73x919 note74x734 note75x549 note76x364 note77x179 note78x1007 note79x822 note80x637 note81x452 note82x267 note83x82 note84x910 note85x725 note86x540 note87x355 note88x170 note0x998 note1x813 note2x628 note3x443 note4x258 note5x73 note6x901 note7x716 note8x531 note9x346 note10x161 note11x989 note12x804 note13x619 note14x434 note15x249 note16x64 note17x892 note18x707 note19x522 note20x337 note21x152 note22x980 note23x795 note24x610 note25x425 note26x240 note27x55 note28x883 note29x698 note30x513 note31x328 note32x143 note33x971 note34x786 note35x601 note36x416 note37x231 note38x46 note39x874 note40x689 note41x504 note42x319 note43x134 note44x962 note45x777 note46x592 note47x407 note48x222 note49x37 note50x865 note51x680 note52x495 note53x310 note54x125 note55x953 note56x768 note57x583 note58x398 note59x213 note60x28 note61x856 note62x671 note63x486 note64x301 note65x116 note66x944 note67x759 note68x574 note69x389 note70x204 note71x19 note72x847 note73x662 note74x477 note75x292 note76x107 note77x935 note78x750 note79x565 note80x380 note81x195 note82x10 note83x838 note84x653 note85x468 note86x283 note87x98 note88x926 note0x741 note1x556 note2x371 note3x186 note4x1 note5x829 note6x644 note7x459 note8x274 note9x89 note10x917 note11x732 note12x547 note13x362 note14x177 note15x1005 note16x820 note17x635 note18x450 note19x265 note20x80 note21x908 note22x723 note23x538 note24x353 note25x168 note26x996 note27x811 note28x626 note29x441 note30x256 note31x71 note32x899 note33x714 note34x529 note35x344 note36x159 note37x987 note38x802 note39x617 note40x432 note41x247 note42x62 note43x890 note44x705 note45x520 note46x335 note47x150 note48x978 note49x793 note50x608 note51x423 note52x238 note53x53 note54x881 note55x696 note56x511 note57x326 note58x141 note59x969 note60x784 note61x599 note62x414 note63x229 note64x44 note65x872 note66x687 note67x502 note68x317 note69x132 note70x960 note71x775 note72x590 note73x405 note74x220 note75x35 note76x863 note77x678 note78x493 note79x308 note80x123 note81x951 note82x766 note83x581 note84x396 note85x211 note86x26 note87x854 note88x669 note0x484 note1x299 note2x114 note3x942 note4x757 note5x572 note6x387 note7x202 note8x17 note9x845 note10x660 note11x475 note12x290 note13x105 note14x933 note15x748 note16x563 note17x378 note18x193 note19x8 note20x836 note21x651 note22x466 note23x281 note24x96 note25x924 note26x739 note27x554 note28x369 note29x184 note30x1012 note31x827 note32x642 note33x457 note34x272 note35x87 note36x915 note37x730 note38x545 note39x360 note40x175 note41x1003 note42x818 note43x633 note44x448 note45x263 note46x78 note47x906 note48x721 note49x536 note50x351 note51x166 note52x994 note53x809 note54x624 note55x439 note56x254 note57x69 note58x897 note59x712 note60x527 note61x342 note62x157 note63x985 note64x800 note65x615 note66x430 note67x245 note68x60 note69x888 note70x703 note71x518 note72x333 note73x148 note74x976 note75x791 note76x606 note77x421 note78x236 note79x51 note80x879 note81x694 note82x509 note83x324 note84x139 note85x967 note86x782 note87x597 note88x412 note0x227 note1x42 note2x870 note3x685 note4x500 note5x315 note6x130 note7x958 note8x773 note9x588 note10x403 note11x218 note12x33 note13x861 note14x676 note15x491 note16x306 note17x121 note18x949 note19x764 note20x579 note21x394 note22x209 note23x24 note24x852 note25x667 note26x482 note27x297 note28x112 note29x940 note30x755 note31x570 note32x385 note33x200 note34x15 note35x843 note36x658 note37x473 note38x288 note39x103 note40x931 note41x746 note42x561 note43x376 note44x191 note45x6 note46x834 note47x649 note48x464 note49x279 note50x94 note51x922 note52x737 note53x552 note54x367 note55x182 note56x1010 note57x825 note58x640 note59x455 note60x270 note61x85 note62x913 note63x728 note64x543 note65x358 note66x173 note67x1001 note68x816 note69x631 note70x446 note71x261 note72x76 note73x904 note74x719 note75x534 note76x349 note77x164 note78x992 note79x807 note80x622 note81x437 note82x252 note83x67 note84x895 note85x710 note86x525 note87x340 note88x155 note0x983 note1x798 note2x613 note3x428 note4x243 note5x58 note6x886 note7x701 note8x516 note9x331 note10x146 note11x974 note12x789 note13x604 note14x419 note15x234 note16x49 note17x877 note18x692 note19x507 note20x322 note21x137 note22x965 note23x780 note24x595 note25x410 note26x225 note27x40 note28x868 note29x683 note30x498 note31x313 note32x128 note33x956 note34x771 note35x586 note36x401 note37x216 note38x31 note39x859 note40x674 note41x489 note42x304 note43x119 note44x947 note45x762 note46x577 note47x392 note48x207 note49x22 note50x850 note51x665 note52x480 note53x295 note54x110 note55x938 note56x753 note57x568 note58x383 note59x198 note60x13 note61x841 note62x656 note63x471 note64x286 note65x101 note66x929 note67x744 note68x559 note69x374 note70x189 note71x4 note72x832 note73x647 note74x462 note75x277 note76x92 note77x920 note78x735 note79x550 note80x365 note81x180 note82x1008 note83x823 note84x638 note85x453 note86x268 note87x83 note88x911 note0x726 note1x541 note2x356 note3x171 note4x999 note5x814 note6x629 note7x444 note8x259 note9x74 note10x902 note11x717 note12x532 note13x347 note14x162 note15x990 note16x805 note17x620 note18x435 note19x250 note20x65 note21x893 note22x708 note23x523 note24x338 note25x153 note26x981 note27x796 note28x611 note29x426 note30x241 note31x56 note32x884 note33x699 note34x514 note35x329 note36x144 note37x972 note38x787 note39x602 note40x417 note41x232 note42x47 note43x875 note44x690 note45x505 note46x320 note47x135 note48x963 note49x778 note50x593 note51x408 note52x223 note53x38 note54x866 note55x681 note56x496 note57x311 note58x126 note59x954 note60x769 note61x584 note62x399 note63x214 note64x29 note65x857 note66x672 note67x487 note68x302 note69x117 note70x945 note71x760 note72x575 note73x390 note74x205 note75x20 note76x848 note77x663 note78x478 note79x293 note80x108 note81x936 note82x751 note83x566 note84x381 note85x196 note86x11 note87x839 note88x654 note0x469 note1x284 note2x99 note3x927 note4x742 note5x557 note6x372 note7x187 note8x2 note9x830 note10x645 note11x460 note12x275 note13x90 note14x918 note15x733 note16x548 note17x363 note18x178 note19x1006 note20x821 note21x636 note22x451 note23x266 note24x81 note25x909 note26x724 note27x539 note28x354 note29x169 note30x997 note31x812 note32x627 note33x442 note34x257 note35x72 note36x900 note37x715 note38x530 note39x345 note40x160 note41x988 note42x803 note43x618 note44x433 note45x248 note46x63 note47x891 note48x706 note49x521 note50x336 note51x151 note52x979 note53x794 note54x609 note55x424 note56x239 note57x54 note58x882 note59x697 note60x512 note61x327 note62x142 note63x970 note64x785 note65x600 note66x415 note67x230 note68x45 note69x873 note70x688 note71x503 note72x318 note73x133 note74x961 note75x776 note76x591 note77x406 note78x221 note79x36 note80x864 note81x679 note82x494 note83x309 note84x124 note85x952 note86x767 note87x582 note88x397 note0x212 note1x27 note2x855 note3x670 note4x485 note5x300 note6x115 note7x943 note8x758 note9x573 note10x388 note11x203 note12x18 note13x846 note14x661 note15x476 note16x291 note17x106 note18x934 note19x749 note20x564 note21x379 note22x194 note23x9 note24x837 note25x652 note26x467 note27x282 note28x97 note29x925 note30x740 note31x555 note32x370 note33x185 note34x0 note35x828 note36x643 note37x458 note38x273 note39x88 note40x916 note41x731 note42x546 note43x361 note44x176 note45x1004 note46x819 note47x634 note48x449 note49x264 note50x79 note51x907 note52x722 note53x537 note54x352 note55x167 note56x995 note57x810 note58x625 note59x440 note60x255 note61x70 note62x898 note63x713 note64x528 note65x343 note66x158 note67x986 note68x801 note69x616 note70x431 note71x246 note72x61 note73x889 note74x704 note75x519 note76x334 note77x149 note78x977 note79x792 note80x607 note81x422 note82x237 note83x52 note84x880 note85x695 note86x510 note87x325 note88x140 note0x968 note1x783 note2x598 note3x413 note4x228 note5x43 note6x871 note7x686 note8x501 note9x316 note10x131 note11x959 note12x774 note13x589 note14x404 note15x219 note16x34 note17x862 note18x677 note19x492 note20x307 note21x122 note22x950 note23x765 note24x580 note25x395 note26x210 note27x25 note28x853 note29x668 note30x483 note31x298 note32x113 note33x941 note34x756 note35x571 note36x386 note37x201 note38x16 note39x844 note40x659 note41x474 note42x289 note43x104 note44x932 note45x747 note46x562 note47x377 note48x192 note49x7 note50x835 note51x650 note52x465 note53x280 note54x95 note55x923 note56x738 note57x553 note58x368 note59x183 note60x1011 note61x826 note62x641 note63x456 note64x271 note65x86 note66x914 note67x729 note68x544 note69x359 note70x174 note71x1002 note72x817 note73x632 note74x447 note75x262 note76x77 note77x905 note78x720 note79x535 note80x350 note81x165 note82x993 note83x808 note84x623 note85x438 note86x253 note87x68 note88x896 note0x711 note1x526 note2x341 note3x156 note4x984 note5x799 note6x614 note7x429 note8x244 note9x59 note10x887 note11x702 note12x517 note13x332 note14x147 note15x975 note16x790 note17x605 note18x420 note19x235 note20x50 note21x878 note22x693 note23x508 note24x323 note25x138 note26x966 note27x781 note28x596 note29x411 note30x226 note31x41 note32x869 note33x684 note34x499 note35x314 note36x129 note37x957 note38x772 note39x587 note40x402 note41x217 note42x32 note43x860 note44x675 note45x490 note46x305 note47x120 note48x948 note49x763 note50x578 note51x393 note52x208 note53x23 note54x851 note55x666 note56x481 note57x296 note58x111 note59x939 note60x754 note61x569 note62x384 note63x199 note64x14 note65x842 note66x657 note67x472 note68x287 note69x102 note70x930 note71x745 note72x560 note73x375 note74x190 note75x5 note76x833 note77x648 note78x463 note79x278 note80x93 note81x921 note82x736 note83x551 note84x366 note85x181 note86x1009 note87x824 note88x639 note0x454 note1x269 note2x84 note3x912 note4x727 note5x542 note6x357 note7x172 note8x1000 note9x815 note10x630 note11x445 note12x260 note13x75 note14x903 note15x718 note16x533 note17x348 note18x163 note19x991 note20x806 note21x621 note22x436 note23x251 note24x66 note25x894 note26x709 note27x524 note28x339 note29x154 note30x982 note31x797 note32x612 note33x427 note34x242 note35x57 note36x885 note37x700 note38x515 note39x330 note40x145 note41x973 note42x788 note43x603 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"reasoning_effort": "none", "engine": "lanes", "tokens_per_second": 53.13503310639343, "seconds": 0.188199751, "prefill_seconds": 18.554445011, "prefill_widths": [], "prefill_raised": [], "time_to_first_token": 18.557694872, "sampling": "greedy", "drafts": true, "token_sha": "eea964a89e62", "token_sha256": "eea964a89e62f6e2059b2da5a676da894801486bd2b3f05aad65bbf32aacef96", "min_rows": 3}, "speculative": {"rounds": 3, "drafted": 12, "accepted": 11, "acceptance_rate": 0.9166666666666666, "tokens_per_round": 3.6666666666666665}}, "seconds": 18.752445459365845} +{"url": "http://127.0.0.1:30461/v1/chat/completions", "request": {"model": "flashnext", "messages": [{"role": "system", "content": "You are a careful assistant. 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note41x217 note42x32 note43x860 note44x675 note45x490 note46x305 note47x120 note48x948 note49x763 note50x578 note51x393 note52x208 note53x23 note54x851 note55x666 note56x481 note57x296 note58x111 note59x939 note60x754 note61x569 note62x384 note63x199 note64x14 note65x842 note66x657 note67x472 note68x287 note69x102 note70x930 note71x745 note72x560 note73x375 note74x190 note75x5 note76x833 note77x648 note78x463 note79x278 note80x93 note81x921 note82x736 note83x551 note84x366 note85x181 note86x1009 note87x824 note88x639 note0x454 note1x269 note2x84 note3x912 note4x727 note5x542 note6x357 note7x172 note8x1000 note9x815 note10x630 note11x445 note12x260 note13x75 note14x903 note15x718 note16x533 note17x348 note18x163 note19x991 note20x806 note21x621 note22x436 note23x251 note24x66 note25x894 note26x709 note27x524 note28x339 note29x154 note30x982 note31x797 note32x612 note33x427 note34x242 note35x57 note36x885 note37x700 note38x515 note39x330 note40x145 note41x973 note42x788 note43x603 note44x418 note45x233 note46x48 note47x876 note48x691 note49x506 note50x321 note51x136 note52x964 note53x779 note54x594 note55x409 note56x224 note57x39 note58x867 note59x682 note60x497 note61x312 note62x127 note63x955 note64x770 note65x585 note66x400 note67x215 note68x30 note69x858 note70x673 note71x488 note72x303 note73x118 note74x946 note75x761 note76x576 note77x391 note78x206 note79x21 note80x849 note81x664 note82x479 note83x294 note84x109 note85x937 note86x752 note87x567 note88x382 note0x197 note1x12 note2x840 note3x655 note4x470 note5x285 note6x100 note7x928 note8x743 note9x558 note10x373 note11x188 note12x3 note13x831 note14x646 note15x461 note16x276 note17x91 note18x919 note19x734 note20x549 note21x364 note22x179 note23x1007 note24x822 note25x637 note26x452 note27x267 note28x82 note29x910 note30x725 note31x540 note32x355 note33x170 note34x998 note35x813 note36x628 note37x443 note38x258 note39x73 note40x901 note41x716 note42x531 note43x346 note44x161 note45x989 note46x804 note47x619 note48x434 note49x249 note50x64 note51x892 note52x707 note53x522 note54x337 note55x152 note56x980 note57x795 note58x610 note59x425 note60x240 note61x55 note62x883 note63x698 note64x513 note65x328 note66x143 note67x971 note68x786 note69x601 note70x416 note71x231 note72x46 note73x874 note74x689 note75x504 note76x319 note77x134 note78x962 note79x777 note80x592 note81x407 note82x222 note83x37 note84x865 note85x680 note86x495 note87x310 note88x125 note0x953 note1x768 note2x583 note3x398 note4x213 note5x28 note6x856 note7x671 note8x486 note9x301 note10x116 note11x944 note12x759 note13x574 note14x389 note15x204 note16x19 note17x847 note18x662 note19x477 note20x292 note21x107 note22x935 note23x750 note24x565 note25x380 note26x195 note27x10 note28x838 note29x653 note30x468 note31x283 note32x98 note33x926 note34x741 note35x556 note36x371 note37x186 note38x1 note39x829 note40x644 note41x459 note42x274 note43x89 note44x917 note45x732 note46x547 note47x362 note48x177 note49x1005 note50x820 note51x635 note52x450 note53x265 note54x80 note55x908 note56x723 note57x538 note58x353 note59x168 note60x996 note61x811 note62x626 note63x441 note64x256 note65x71 note66x899 note67x714 note68x529 note69x344 note70x159 note71x987 note72x802 note73x617 note74x432 note75x247"}, {"role": "user", "content": "What is the first note?"}, {"role": "assistant", "content": "The first note is **note0x0**."}, {"role": "user", "content": "And the second one?"}], "max_tokens": 48, "temperature": 0.0, "draft": true, "chat_template_kwargs": {"enable_thinking": false}}, "status": 200, "response": {"id": "chatcmpl-bcb27e22d5fc24ea74991246e68e5500", "object": "chat.completion", "created": 1793474078, "model": "flashnext", "choices": [{"index": 0, "message": {"role": "assistant", "content": "The second note is **note1x828**."}, "finish_reason": "stop"}], "usage": {"prompt_tokens": 10248, "completion_tokens": 13, "total_tokens": 10261, "prompt_tokens_details": {"cached_tokens": 0}, "completion_tokens_details": {"reasoning_tokens": 0}}, "exact_mode": "exact", "tensorfold": {"enable_thinking": false, "reasoning_effort": "none", "engine": "lanes", "tokens_per_second": 54.70092052897103, "seconds": 0.219374736, "prefill_seconds": 18.606844665, "prefill_widths": [], "prefill_raised": [], "time_to_first_token": 18.607786737, "sampling": "greedy", "drafts": true, "token_sha": "7e4bf5aba972", "token_sha256": "7e4bf5aba9727191d8505e971356abb0485616846741651f36545f4775ef04fc", "min_rows": 5}, "speculative": {"rounds": 3, "drafted": 16, "accepted": 9, "acceptance_rate": 0.5625, "tokens_per_round": 4.333333333333333}}, "seconds": 18.8285710811615} +{"url": "http://127.0.0.1:30461/v1/chat/completions", "request": {"model": "flashnext", "messages": [{"role": "system", "content": "You are a careful assistant. 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note2x386 note3x201 note4x16 note5x844 note6x659 note7x474 note8x289 note9x104 note10x932 note11x747 note12x562 note13x377 note14x192 note15x7 note16x835 note17x650 note18x465 note19x280 note20x95 note21x923 note22x738 note23x553 note24x368 note25x183 note26x1011 note27x826 note28x641 note29x456 note30x271 note31x86 note32x914 note33x729 note34x544 note35x359 note36x174 note37x1002 note38x817 note39x632 note40x447 note41x262 note42x77 note43x905 note44x720 note45x535 note46x350 note47x165 note48x993 note49x808 note50x623 note51x438 note52x253 note53x68 note54x896 note55x711 note56x526 note57x341 note58x156 note59x984 note60x799 note61x614 note62x429 note63x244 note64x59 note65x887 note66x702 note67x517 note68x332 note69x147 note70x975 note71x790 note72x605 note73x420 note74x235 note75x50 note76x878 note77x693 note78x508 note79x323 note80x138 note81x966 note82x781 note83x596 note84x411 note85x226 note86x41 note87x869 note88x684 note0x499 note1x314 note2x129 note3x957 note4x772 note5x587 note6x402 note7x217 note8x32 note9x860 note10x675 note11x490 note12x305 note13x120 note14x948 note15x763 note16x578 note17x393 note18x208 note19x23 note20x851 note21x666 note22x481 note23x296 note24x111 note25x939 note26x754 note27x569 note28x384 note29x199 note30x14 note31x842 note32x657 note33x472 note34x287 note35x102 note36x930 note37x745 note38x560 note39x375 note40x190 note41x5 note42x833 note43x648 note44x463 note45x278 note46x93 note47x921 note48x736 note49x551 note50x366 note51x181 note52x1009 note53x824 note54x639 note55x454 note56x269 note57x84 note58x912 note59x727 note60x542 note61x357 note62x172 note63x1000 note64x815 note65x630 note66x445 note67x260 note68x75 note69x903 note70x718 note71x533 note72x348 note73x163 note74x991 note75x806 note76x621 note77x436 note78x251 note79x66 note80x894 note81x709 note82x524 note83x339 note84x154 note85x982 note86x797 note87x612 note88x427 note0x242 note1x57 note2x885 note3x700 note4x515 note5x330 note6x145 note7x973 note8x788 note9x603 note10x418 note11x233 note12x48 note13x876 note14x691 note15x506 note16x321 note17x136 note18x964 note19x779 note20x594 note21x409 note22x224 note23x39 note24x867 note25x682 note26x497 note27x312 note28x127 note29x955 note30x770 note31x585 note32x400 note33x215 note34x30 note35x858 note36x673 note37x488 note38x303 note39x118 note40x946 note41x761 note42x576 note43x391 note44x206 note45x21 note46x849 note47x664 note48x479 note49x294 note50x109 note51x937 note52x752 note53x567 note54x382 note55x197 note56x12 note57x840 note58x655 note59x470 note60x285 note61x100 note62x928 note63x743 note64x558 note65x373 note66x188 note67x3 note68x831 note69x646 note70x461 note71x276 note72x91 note73x919 note74x734 note75x549 note76x364 note77x179 note78x1007 note79x822 note80x637 note81x452 note82x267 note83x82 note84x910 note85x725 note86x540 note87x355 note88x170 note0x998 note1x813 note2x628 note3x443 note4x258 note5x73 note6x901 note7x716 note8x531 note9x346 note10x161 note11x989 note12x804 note13x619 note14x434 note15x249 note16x64 note17x892 note18x707 note19x522 note20x337 note21x152 note22x980 note23x795 note24x610 note25x425 note26x240 note27x55 note28x883 note29x698 note30x513 note31x328 note32x143 note33x971 note34x786 note35x601 note36x416 note37x231 note38x46 note39x874 note40x689 note41x504 note42x319 note43x134 note44x962 note45x777 note46x592 note47x407 note48x222 note49x37 note50x865 note51x680 note52x495 note53x310 note54x125 note55x953 note56x768 note57x583 note58x398 note59x213 note60x28 note61x856 note62x671 note63x486 note64x301 note65x116 note66x944 note67x759 note68x574 note69x389 note70x204 note71x19 note72x847 note73x662 note74x477 note75x292 note76x107 note77x935 note78x750 note79x565 note80x380 note81x195 note82x10 note83x838 note84x653 note85x468 note86x283 note87x98 note88x926 note0x741 note1x556 note2x371 note3x186 note4x1 note5x829 note6x644 note7x459 note8x274 note9x89 note10x917 note11x732 note12x547 note13x362 note14x177 note15x1005 note16x820 note17x635 note18x450 note19x265 note20x80 note21x908 note22x723 note23x538 note24x353 note25x168 note26x996 note27x811 note28x626 note29x441 note30x256 note31x71 note32x899 note33x714 note34x529 note35x344 note36x159 note37x987 note38x802 note39x617 note40x432 note41x247 note42x62 note43x890 note44x705 note45x520 note46x335 note47x150 note48x978 note49x793 note50x608 note51x423 note52x238 note53x53 note54x881 note55x696 note56x511 note57x326 note58x141 note59x969 note60x784 note61x599 note62x414 note63x229 note64x44 note65x872 note66x687 note67x502 note68x317 note69x132 note70x960 note71x775 note72x590 note73x405 note74x220 note75x35 note76x863 note77x678 note78x493 note79x308 note80x123 note81x951 note82x766 note83x581 note84x396 note85x211 note86x26 note87x854 note88x669 note0x484 note1x299 note2x114 note3x942 note4x757 note5x572 note6x387 note7x202 note8x17 note9x845 note10x660 note11x475 note12x290 note13x105 note14x933 note15x748 note16x563 note17x378 note18x193 note19x8 note20x836 note21x651 note22x466 note23x281 note24x96 note25x924 note26x739 note27x554 note28x369 note29x184 note30x1012 note31x827 note32x642 note33x457 note34x272 note35x87 note36x915 note37x730 note38x545 note39x360 note40x175 note41x1003 note42x818 note43x633 note44x448 note45x263 note46x78 note47x906 note48x721 note49x536 note50x351 note51x166 note52x994 note53x809 note54x624 note55x439 note56x254 note57x69 note58x897 note59x712 note60x527 note61x342 note62x157 note63x985 note64x800 note65x615 note66x430 note67x245 note68x60 note69x888 note70x703 note71x518 note72x333 note73x148 note74x976 note75x791 note76x606 note77x421 note78x236 note79x51 note80x879 note81x694 note82x509 note83x324 note84x139 note85x967 note86x782 note87x597 note88x412 note0x227 note1x42 note2x870 note3x685 note4x500 note5x315 note6x130 note7x958 note8x773 note9x588 note10x403 note11x218 note12x33 note13x861 note14x676 note15x491 note16x306 note17x121 note18x949 note19x764 note20x579 note21x394 note22x209 note23x24 note24x852 note25x667 note26x482 note27x297 note28x112 note29x940 note30x755 note31x570 note32x385 note33x200 note34x15 note35x843 note36x658 note37x473 note38x288 note39x103 note40x931 note41x746 note42x561 note43x376 note44x191 note45x6 note46x834 note47x649 note48x464 note49x279 note50x94 note51x922 note52x737 note53x552 note54x367 note55x182 note56x1010 note57x825 note58x640 note59x455 note60x270 note61x85 note62x913 note63x728 note64x543 note65x358 note66x173 note67x1001 note68x816 note69x631 note70x446 note71x261 note72x76 note73x904 note74x719 note75x534 note76x349 note77x164 note78x992 note79x807 note80x622 note81x437 note82x252 note83x67 note84x895 note85x710 note86x525 note87x340 note88x155 note0x983 note1x798 note2x613 note3x428 note4x243 note5x58 note6x886 note7x701 note8x516 note9x331 note10x146 note11x974 note12x789 note13x604 note14x419 note15x234 note16x49 note17x877 note18x692 note19x507 note20x322 note21x137 note22x965 note23x780 note24x595 note25x410 note26x225 note27x40 note28x868 note29x683 note30x498 note31x313 note32x128 note33x956 note34x771 note35x586 note36x401 note37x216 note38x31 note39x859 note40x674 note41x489 note42x304 note43x119 note44x947 note45x762 note46x577 note47x392 note48x207 note49x22 note50x850 note51x665 note52x480 note53x295 note54x110 note55x938 note56x753 note57x568 note58x383 note59x198 note60x13 note61x841 note62x656 note63x471 note64x286 note65x101 note66x929 note67x744 note68x559 note69x374 note70x189 note71x4 note72x832 note73x647 note74x462 note75x277 note76x92 note77x920 note78x735 note79x550 note80x365 note81x180 note82x1008 note83x823 note84x638 note85x453 note86x268 note87x83 note88x911 note0x726 note1x541 note2x356 note3x171 note4x999 note5x814 note6x629 note7x444 note8x259 note9x74 note10x902 note11x717 note12x532 note13x347 note14x162 note15x990 note16x805 note17x620 note18x435 note19x250 note20x65 note21x893 note22x708 note23x523 note24x338 note25x153 note26x981 note27x796 note28x611 note29x426 note30x241 note31x56 note32x884 note33x699 note34x514 note35x329 note36x144 note37x972 note38x787 note39x602 note40x417 note41x232 note42x47 note43x875 note44x690 note45x505 note46x320 note47x135 note48x963 note49x778 note50x593 note51x408 note52x223 note53x38 note54x866 note55x681 note56x496 note57x311 note58x126 note59x954 note60x769 note61x584 note62x399 note63x214 note64x29 note65x857 note66x672 note67x487 note68x302 note69x117 note70x945 note71x760 note72x575 note73x390 note74x205 note75x20 note76x848 note77x663 note78x478 note79x293 note80x108 note81x936 note82x751 note83x566 note84x381 note85x196 note86x11 note87x839 note88x654 note0x469 note1x284 note2x99 note3x927 note4x742 note5x557 note6x372 note7x187 note8x2 note9x830 note10x645 note11x460 note12x275 note13x90 note14x918 note15x733 note16x548 note17x363 note18x178 note19x1006 note20x821 note21x636 note22x451 note23x266 note24x81 note25x909 note26x724 note27x539 note28x354 note29x169 note30x997 note31x812 note32x627 note33x442 note34x257 note35x72 note36x900 note37x715 note38x530 note39x345 note40x160 note41x988 note42x803 note43x618 note44x433 note45x248 note46x63 note47x891 note48x706 note49x521 note50x336 note51x151 note52x979 note53x794 note54x609 note55x424 note56x239 note57x54 note58x882 note59x697 note60x512 note61x327 note62x142 note63x970 note64x785 note65x600 note66x415 note67x230 note68x45 note69x873 note70x688 note71x503 note72x318 note73x133 note74x961 note75x776 note76x591 note77x406 note78x221 note79x36 note80x864 note81x679 note82x494 note83x309 note84x124 note85x952 note86x767 note87x582 note88x397 note0x212 note1x27 note2x855 note3x670 note4x485 note5x300 note6x115 note7x943 note8x758 note9x573 note10x388 note11x203 note12x18 note13x846 note14x661 note15x476 note16x291 note17x106 note18x934 note19x749 note20x564 note21x379 note22x194 note23x9 note24x837 note25x652 note26x467 note27x282 note28x97 note29x925 note30x740 note31x555 note32x370 note33x185 note34x0 note35x828 note36x643 note37x458 note38x273 note39x88 note40x916 note41x731 note42x546 note43x361 note44x176 note45x1004 note46x819 note47x634 note48x449 note49x264 note50x79 note51x907 note52x722 note53x537 note54x352 note55x167 note56x995 note57x810 note58x625 note59x440 note60x255 note61x70 note62x898 note63x713 note64x528 note65x343 note66x158 note67x986 note68x801 note69x616 note70x431 note71x246 note72x61 note73x889 note74x704 note75x519 note76x334 note77x149 note78x977 note79x792 note80x607 note81x422 note82x237 note83x52 note84x880 note85x695 note86x510 note87x325 note88x140 note0x968 note1x783 note2x598 note3x413 note4x228 note5x43 note6x871 note7x686 note8x501 note9x316 note10x131 note11x959 note12x774 note13x589 note14x404 note15x219 note16x34 note17x862 note18x677 note19x492 note20x307 note21x122 note22x950 note23x765 note24x580 note25x395 note26x210 note27x25 note28x853 note29x668 note30x483 note31x298 note32x113 note33x941 note34x756 note35x571 note36x386 note37x201 note38x16 note39x844 note40x659 note41x474 note42x289 note43x104 note44x932 note45x747 note46x562 note47x377 note48x192 note49x7 note50x835 note51x650 note52x465 note53x280 note54x95 note55x923 note56x738 note57x553 note58x368 note59x183 note60x1011 note61x826 note62x641 note63x456 note64x271 note65x86 note66x914 note67x729 note68x544 note69x359 note70x174 note71x1002 note72x817 note73x632 note74x447 note75x262 note76x77 note77x905 note78x720 note79x535 note80x350 note81x165 note82x993 note83x808 note84x623 note85x438 note86x253 note87x68 note88x896 note0x711 note1x526 note2x341 note3x156 note4x984 note5x799 note6x614 note7x429 note8x244 note9x59 note10x887 note11x702 note12x517 note13x332 note14x147 note15x975 note16x790 note17x605 note18x420 note19x235 note20x50 note21x878 note22x693 note23x508 note24x323 note25x138 note26x966 note27x781 note28x596 note29x411 note30x226 note31x41 note32x869 note33x684 note34x499 note35x314 note36x129 note37x957 note38x772 note39x587 note40x402 note41x217 note42x32 note43x860 note44x675 note45x490 note46x305 note47x120 note48x948 note49x763 note50x578 note51x393 note52x208 note53x23 note54x851 note55x666 note56x481 note57x296 note58x111 note59x939 note60x754 note61x569 note62x384 note63x199 note64x14 note65x842 note66x657 note67x472 note68x287 note69x102 note70x930 note71x745 note72x560 note73x375 note74x190 note75x5 note76x833 note77x648 note78x463 note79x278 note80x93 note81x921 note82x736 note83x551 note84x366 note85x181 note86x1009 note87x824 note88x639 note0x454 note1x269 note2x84 note3x912 note4x727 note5x542 note6x357 note7x172 note8x1000 note9x815 note10x630 note11x445 note12x260 note13x75 note14x903 note15x718 note16x533 note17x348 note18x163 note19x991 note20x806 note21x621 note22x436 note23x251 note24x66 note25x894 note26x709 note27x524 note28x339 note29x154 note30x982 note31x797 note32x612 note33x427 note34x242 note35x57 note36x885 note37x700 note38x515 note39x330 note40x145 note41x973 note42x788 note43x603 note44x418 note45x233 note46x48 note47x876 note48x691 note49x506 note50x321 note51x136 note52x964 note53x779 note54x594 note55x409 note56x224 note57x39 note58x867 note59x682 note60x497 note61x312 note62x127 note63x955 note64x770 note65x585 note66x400 note67x215 note68x30 note69x858 note70x673 note71x488 note72x303 note73x118 note74x946 note75x761 note76x576 note77x391 note78x206 note79x21 note80x849 note81x664 note82x479 note83x294 note84x109 note85x937 note86x752 note87x567 note88x382 note0x197 note1x12 note2x840 note3x655 note4x470 note5x285 note6x100 note7x928 note8x743 note9x558 note10x373 note11x188 note12x3 note13x831 note14x646 note15x461 note16x276 note17x91 note18x919 note19x734 note20x549 note21x364 note22x179 note23x1007 note24x822 note25x637 note26x452 note27x267 note28x82 note29x910 note30x725 note31x540 note32x355 note33x170 note34x998 note35x813 note36x628 note37x443 note38x258 note39x73 note40x901 note41x716 note42x531 note43x346 note44x161 note45x989 note46x804 note47x619 note48x434 note49x249 note50x64 note51x892 note52x707 note53x522 note54x337 note55x152 note56x980 note57x795 note58x610 note59x425 note60x240 note61x55 note62x883 note63x698 note64x513 note65x328 note66x143 note67x971 note68x786 note69x601 note70x416 note71x231 note72x46 note73x874 note74x689 note75x504 note76x319 note77x134 note78x962 note79x777 note80x592 note81x407 note82x222 note83x37 note84x865 note85x680 note86x495 note87x310 note88x125 note0x953 note1x768 note2x583 note3x398 note4x213 note5x28 note6x856 note7x671 note8x486 note9x301 note10x116 note11x944 note12x759 note13x574 note14x389 note15x204 note16x19 note17x847 note18x662 note19x477 note20x292 note21x107 note22x935 note23x750 note24x565 note25x380 note26x195 note27x10 note28x838 note29x653 note30x468 note31x283 note32x98 note33x926 note34x741 note35x556 note36x371 note37x186 note38x1 note39x829 note40x644 note41x459 note42x274 note43x89 note44x917 note45x732 note46x547 note47x362 note48x177 note49x1005 note50x820 note51x635 note52x450 note53x265 note54x80 note55x908 note56x723 note57x538 note58x353 note59x168 note60x996 note61x811 note62x626 note63x441 note64x256 note65x71 note66x899 note67x714 note68x529 note69x344 note70x159 note71x987 note72x802 note73x617 note74x432 note75x247"}, {"role": "user", "content": "What is the first note?"}, {"role": "assistant", "content": "The first note is **note0x0**."}, {"role": "user", "content": "And the second one?"}, {"role": "assistant", "content": "The second note is **note1x828**."}, {"role": "user", "content": "Is note5x5 listed?"}], "max_tokens": 48, "temperature": 0.0, "draft": true, "chat_template_kwargs": {"enable_thinking": false}}, "status": 200, "response": {"id": "chatcmpl-38e6d8e8b792a1843ba44640d6d7d6c8", "object": "chat.completion", "created": 1793474096, "model": "flashnext", "choices": [{"index": 0, "message": {"role": "assistant", "content": "No, **note5x5** is not listed in the provided reference notes.\n\nThe list contains notes with hex suffixes (e.g., `note5x88`, `note5x587`, `note5"}, "finish_reason": "length"}], "usage": {"prompt_tokens": 10281, "completion_tokens": 48, "total_tokens": 10329, "prompt_tokens_details": {"cached_tokens": 0}, "completion_tokens_details": {"reasoning_tokens": 0}}, "exact_mode": "exact", "tensorfold": {"enable_thinking": false, "reasoning_effort": "none", "engine": "lanes", "tokens_per_second": 47.93399318615636, "seconds": 0.980515014, "prefill_seconds": 18.69590376, "prefill_widths": [], "prefill_raised": [], "time_to_first_token": 18.696886389, "sampling": "greedy", "drafts": true, "token_sha": "e7287d6bf366", "token_sha256": "e7287d6bf36620acbd71b1537e7b5ea9b239198191676c8c2261aad653c64a81", "min_rows": 2}, "speculative": {"rounds": 17, "drafted": 40, "accepted": 31, "acceptance_rate": 0.775, "tokens_per_round": 2.823529411764706}}, "seconds": 19.678483963012695} +{"url": "http://127.0.0.1:30461/v1/chat/completions", "request": {"model": "flashnext", "messages": [{"role": "system", "content": "You are a careful assistant. Reference notes: note0x0 note1x828 note2x643 note3x458 note4x273 note5x88 note6x916 note7x731 note8x546 note9x361 note10x176 note11x1004 note12x819 note13x634 note14x449 note15x264 note16x79 note17x907 note18x722 note19x537 note20x352 note21x167 note22x995 note23x810 note24x625 note25x440 note26x255 note27x70 note28x898 note29x713 note30x528 note31x343 note32x158 note33x986 note34x801 note35x616 note36x431 note37x246 note38x61 note39x889 note40x704 note41x519 note42x334 note43x149 note44x977 note45x792 note46x607 note47x422 note48x237 note49x52 note50x880 note51x695 note52x510 note53x325 note54x140 note55x968 note56x783 note57x598 note58x413 note59x228 note60x43 note61x871 note62x686 note63x501 note64x316 note65x131 note66x959 note67x774 note68x589 note69x404 note70x219 note71x34 note72x862 note73x677 note74x492 note75x307 note76x122 note77x950 note78x765 note79x580 note80x395 note81x210 note82x25 note83x853 note84x668 note85x483 note86x298 note87x113 note88x941 note0x756 note1x571 note2x386 note3x201 note4x16 note5x844 note6x659 note7x474 note8x289 note9x104 note10x932 note11x747 note12x562 note13x377 note14x192 note15x7 note16x835 note17x650 note18x465 note19x280 note20x95 note21x923 note22x738 note23x553 note24x368 note25x183 note26x1011 note27x826 note28x641 note29x456 note30x271 note31x86 note32x914 note33x729 note34x544 note35x359 note36x174 note37x1002 note38x817 note39x632 note40x447 note41x262 note42x77 note43x905 note44x720 note45x535 note46x350 note47x165 note48x993 note49x808 note50x623 note51x438 note52x253 note53x68 note54x896 note55x711 note56x526 note57x341 note58x156 note59x984 note60x799 note61x614 note62x429 note63x244 note64x59 note65x887 note66x702 note67x517 note68x332 note69x147 note70x975 note71x790 note72x605 note73x420 note74x235 note75x50 note76x878 note77x693 note78x508 note79x323 note80x138 note81x966 note82x781 note83x596 note84x411 note85x226 note86x41 note87x869 note88x684 note0x499 note1x314 note2x129 note3x957 note4x772 note5x587 note6x402 note7x217 note8x32 note9x860 note10x675 note11x490 note12x305 note13x120 note14x948 note15x763 note16x578 note17x393 note18x208 note19x23 note20x851 note21x666 note22x481 note23x296 note24x111 note25x939 note26x754 note27x569 note28x384 note29x199 note30x14 note31x842 note32x657 note33x472 note34x287 note35x102 note36x930 note37x745 note38x560 note39x375 note40x190 note41x5 note42x833 note43x648 note44x463 note45x278 note46x93 note47x921 note48x736 note49x551 note50x366 note51x181 note52x1009 note53x824 note54x639 note55x454 note56x269 note57x84 note58x912 note59x727 note60x542 note61x357 note62x172 note63x1000 note64x815 note65x630 note66x445 note67x260 note68x75 note69x903 note70x718 note71x533 note72x348 note73x163 note74x991 note75x806 note76x621 note77x436 note78x251 note79x66 note80x894 note81x709 note82x524 note83x339 note84x154 note85x982 note86x797 note87x612 note88x427 note0x242 note1x57 note2x885 note3x700 note4x515 note5x330 note6x145 note7x973 note8x788 note9x603 note10x418 note11x233 note12x48 note13x876 note14x691 note15x506 note16x321 note17x136 note18x964 note19x779 note20x594 note21x409 note22x224 note23x39 note24x867 note25x682 note26x497 note27x312 note28x127 note29x955 note30x770 note31x585 note32x400 note33x215 note34x30 note35x858 note36x673 note37x488 note38x303 note39x118 note40x946 note41x761 note42x576 note43x391 note44x206 note45x21 note46x849 note47x664 note48x479 note49x294 note50x109 note51x937 note52x752 note53x567 note54x382 note55x197 note56x12 note57x840 note58x655 note59x470 note60x285 note61x100 note62x928 note63x743 note64x558 note65x373 note66x188 note67x3 note68x831 note69x646 note70x461 note71x276 note72x91 note73x919 note74x734 note75x549 note76x364 note77x179 note78x1007 note79x822 note80x637 note81x452 note82x267 note83x82 note84x910 note85x725 note86x540 note87x355 note88x170 note0x998 note1x813 note2x628 note3x443 note4x258 note5x73 note6x901 note7x716 note8x531 note9x346 note10x161 note11x989 note12x804 note13x619 note14x434 note15x249 note16x64 note17x892 note18x707 note19x522 note20x337 note21x152 note22x980 note23x795 note24x610 note25x425 note26x240 note27x55 note28x883 note29x698 note30x513 note31x328 note32x143 note33x971 note34x786 note35x601 note36x416 note37x231 note38x46 note39x874 note40x689 note41x504 note42x319 note43x134 note44x962 note45x777 note46x592 note47x407 note48x222 note49x37 note50x865 note51x680 note52x495 note53x310 note54x125 note55x953 note56x768 note57x583 note58x398 note59x213 note60x28 note61x856 note62x671 note63x486 note64x301 note65x116 note66x944 note67x759 note68x574 note69x389 note70x204 note71x19 note72x847 note73x662 note74x477 note75x292 note76x107 note77x935 note78x750 note79x565 note80x380 note81x195 note82x10 note83x838 note84x653 note85x468 note86x283 note87x98 note88x926 note0x741 note1x556 note2x371 note3x186 note4x1 note5x829 note6x644 note7x459 note8x274 note9x89 note10x917 note11x732 note12x547 note13x362 note14x177 note15x1005 note16x820 note17x635 note18x450 note19x265 note20x80 note21x908 note22x723 note23x538 note24x353 note25x168 note26x996 note27x811 note28x626 note29x441 note30x256 note31x71 note32x899 note33x714 note34x529 note35x344 note36x159 note37x987 note38x802 note39x617 note40x432 note41x247 note42x62 note43x890 note44x705 note45x520 note46x335 note47x150 note48x978 note49x793 note50x608 note51x423 note52x238 note53x53 note54x881 note55x696 note56x511 note57x326 note58x141 note59x969 note60x784 note61x599 note62x414 note63x229 note64x44 note65x872 note66x687 note67x502 note68x317 note69x132 note70x960 note71x775 note72x590 note73x405 note74x220 note75x35 note76x863 note77x678 note78x493 note79x308 note80x123 note81x951 note82x766 note83x581 note84x396 note85x211 note86x26 note87x854 note88x669 note0x484 note1x299 note2x114 note3x942 note4x757 note5x572 note6x387 note7x202 note8x17 note9x845 note10x660 note11x475 note12x290 note13x105 note14x933 note15x748 note16x563 note17x378 note18x193 note19x8 note20x836 note21x651 note22x466 note23x281 note24x96 note25x924 note26x739 note27x554 note28x369 note29x184 note30x1012 note31x827 note32x642 note33x457 note34x272 note35x87 note36x915 note37x730 note38x545 note39x360 note40x175 note41x1003 note42x818 note43x633 note44x448 note45x263 note46x78 note47x906 note48x721 note49x536 note50x351 note51x166 note52x994 note53x809 note54x624 note55x439 note56x254 note57x69 note58x897 note59x712 note60x527 note61x342 note62x157 note63x985 note64x800 note65x615 note66x430 note67x245 note68x60 note69x888 note70x703 note71x518 note72x333 note73x148 note74x976 note75x791 note76x606 note77x421 note78x236 note79x51 note80x879 note81x694 note82x509 note83x324 note84x139 note85x967 note86x782 note87x597 note88x412 note0x227 note1x42 note2x870 note3x685 note4x500 note5x315 note6x130 note7x958 note8x773 note9x588 note10x403 note11x218 note12x33 note13x861 note14x676 note15x491 note16x306 note17x121 note18x949 note19x764 note20x579 note21x394 note22x209 note23x24 note24x852 note25x667 note26x482 note27x297 note28x112 note29x940 note30x755 note31x570 note32x385 note33x200 note34x15 note35x843 note36x658 note37x473 note38x288 note39x103 note40x931 note41x746 note42x561 note43x376 note44x191 note45x6 note46x834 note47x649 note48x464 note49x279 note50x94 note51x922 note52x737 note53x552 note54x367 note55x182 note56x1010 note57x825 note58x640 note59x455 note60x270 note61x85 note62x913 note63x728 note64x543 note65x358 note66x173 note67x1001 note68x816 note69x631 note70x446 note71x261 note72x76 note73x904 note74x719 note75x534 note76x349 note77x164 note78x992 note79x807 note80x622 note81x437 note82x252 note83x67 note84x895 note85x710 note86x525 note87x340 note88x155 note0x983 note1x798 note2x613 note3x428 note4x243 note5x58 note6x886 note7x701 note8x516 note9x331 note10x146 note11x974 note12x789 note13x604 note14x419 note15x234 note16x49 note17x877 note18x692 note19x507 note20x322 note21x137 note22x965 note23x780 note24x595 note25x410 note26x225 note27x40 note28x868 note29x683 note30x498 note31x313 note32x128 note33x956 note34x771 note35x586 note36x401 note37x216 note38x31 note39x859 note40x674 note41x489 note42x304 note43x119 note44x947 note45x762 note46x577 note47x392 note48x207 note49x22 note50x850 note51x665 note52x480 note53x295 note54x110 note55x938 note56x753 note57x568 note58x383 note59x198 note60x13 note61x841 note62x656 note63x471 note64x286 note65x101 note66x929 note67x744 note68x559 note69x374 note70x189 note71x4 note72x832 note73x647 note74x462 note75x277 note76x92 note77x920 note78x735 note79x550 note80x365 note81x180 note82x1008 note83x823 note84x638 note85x453 note86x268 note87x83 note88x911 note0x726 note1x541 note2x356 note3x171 note4x999 note5x814 note6x629 note7x444 note8x259 note9x74 note10x902 note11x717 note12x532 note13x347 note14x162 note15x990 note16x805 note17x620 note18x435 note19x250 note20x65 note21x893 note22x708 note23x523 note24x338 note25x153 note26x981 note27x796 note28x611 note29x426 note30x241 note31x56 note32x884 note33x699 note34x514 note35x329 note36x144 note37x972 note38x787 note39x602 note40x417 note41x232 note42x47 note43x875 note44x690 note45x505 note46x320 note47x135 note48x963 note49x778 note50x593 note51x408 note52x223 note53x38 note54x866 note55x681 note56x496 note57x311 note58x126 note59x954 note60x769 note61x584 note62x399 note63x214 note64x29 note65x857 note66x672 note67x487 note68x302 note69x117 note70x945 note71x760 note72x575 note73x390 note74x205 note75x20 note76x848 note77x663 note78x478 note79x293 note80x108 note81x936 note82x751 note83x566 note84x381 note85x196 note86x11 note87x839 note88x654 note0x469 note1x284 note2x99 note3x927 note4x742 note5x557 note6x372 note7x187 note8x2 note9x830 note10x645 note11x460 note12x275 note13x90 note14x918 note15x733 note16x548 note17x363 note18x178 note19x1006 note20x821 note21x636 note22x451 note23x266 note24x81 note25x909 note26x724 note27x539 note28x354 note29x169 note30x997 note31x812 note32x627 note33x442 note34x257 note35x72 note36x900 note37x715 note38x530 note39x345 note40x160 note41x988 note42x803 note43x618 note44x433 note45x248 note46x63 note47x891 note48x706 note49x521 note50x336 note51x151 note52x979 note53x794 note54x609 note55x424 note56x239 note57x54 note58x882 note59x697 note60x512 note61x327 note62x142 note63x970 note64x785 note65x600 note66x415 note67x230 note68x45 note69x873 note70x688 note71x503 note72x318 note73x133 note74x961 note75x776 note76x591 note77x406 note78x221 note79x36 note80x864 note81x679 note82x494 note83x309 note84x124 note85x952 note86x767 note87x582 note88x397 note0x212 note1x27 note2x855 note3x670 note4x485 note5x300 note6x115 note7x943 note8x758 note9x573 note10x388 note11x203 note12x18 note13x846 note14x661 note15x476 note16x291 note17x106 note18x934 note19x749 note20x564 note21x379 note22x194 note23x9 note24x837 note25x652 note26x467 note27x282 note28x97 note29x925 note30x740 note31x555 note32x370 note33x185 note34x0 note35x828 note36x643 note37x458 note38x273 note39x88 note40x916 note41x731 note42x546 note43x361 note44x176 note45x1004 note46x819 note47x634 note48x449 note49x264 note50x79 note51x907 note52x722 note53x537 note54x352 note55x167 note56x995 note57x810 note58x625 note59x440 note60x255 note61x70 note62x898 note63x713 note64x528 note65x343 note66x158 note67x986 note68x801 note69x616 note70x431 note71x246 note72x61 note73x889 note74x704 note75x519 note76x334 note77x149 note78x977 note79x792 note80x607 note81x422 note82x237 note83x52 note84x880 note85x695 note86x510 note87x325 note88x140 note0x968 note1x783 note2x598 note3x413 note4x228 note5x43 note6x871 note7x686 note8x501 note9x316 note10x131 note11x959 note12x774 note13x589 note14x404 note15x219 note16x34 note17x862 note18x677 note19x492 note20x307 note21x122 note22x950 note23x765 note24x580 note25x395 note26x210 note27x25 note28x853 note29x668 note30x483 note31x298 note32x113 note33x941 note34x756 note35x571 note36x386 note37x201 note38x16 note39x844 note40x659 note41x474 note42x289 note43x104 note44x932 note45x747 note46x562 note47x377 note48x192 note49x7 note50x835 note51x650 note52x465 note53x280 note54x95 note55x923 note56x738 note57x553 note58x368 note59x183 note60x1011 note61x826 note62x641 note63x456 note64x271 note65x86 note66x914 note67x729 note68x544 note69x359 note70x174 note71x1002 note72x817 note73x632 note74x447 note75x262 note76x77 note77x905 note78x720 note79x535 note80x350 note81x165 note82x993 note83x808 note84x623 note85x438 note86x253 note87x68 note88x896 note0x711 note1x526 note2x341 note3x156 note4x984 note5x799 note6x614 note7x429 note8x244 note9x59 note10x887 note11x702 note12x517 note13x332 note14x147 note15x975 note16x790 note17x605 note18x420 note19x235 note20x50 note21x878 note22x693 note23x508 note24x323 note25x138 note26x966 note27x781 note28x596 note29x411 note30x226 note31x41 note32x869 note33x684 note34x499 note35x314 note36x129 note37x957 note38x772 note39x587 note40x402 note41x217 note42x32 note43x860 note44x675 note45x490 note46x305 note47x120 note48x948 note49x763 note50x578 note51x393 note52x208 note53x23 note54x851 note55x666 note56x481 note57x296 note58x111 note59x939 note60x754 note61x569 note62x384 note63x199 note64x14 note65x842 note66x657 note67x472 note68x287 note69x102 note70x930 note71x745 note72x560 note73x375 note74x190 note75x5 note76x833 note77x648 note78x463 note79x278 note80x93 note81x921 note82x736 note83x551 note84x366 note85x181 note86x1009 note87x824 note88x639 note0x454 note1x269 note2x84 note3x912 note4x727 note5x542 note6x357 note7x172 note8x1000 note9x815 note10x630 note11x445 note12x260 note13x75 note14x903 note15x718 note16x533 note17x348 note18x163 note19x991 note20x806 note21x621 note22x436 note23x251 note24x66 note25x894 note26x709 note27x524 note28x339 note29x154 note30x982 note31x797 note32x612 note33x427 note34x242 note35x57 note36x885 note37x700 note38x515 note39x330 note40x145 note41x973 note42x788 note43x603 note44x418 note45x233 note46x48 note47x876 note48x691 note49x506 note50x321 note51x136 note52x964 note53x779 note54x594 note55x409 note56x224 note57x39 note58x867 note59x682 note60x497 note61x312 note62x127 note63x955 note64x770 note65x585 note66x400 note67x215 note68x30 note69x858 note70x673 note71x488 note72x303 note73x118 note74x946 note75x761 note76x576 note77x391 note78x206 note79x21 note80x849 note81x664 note82x479 note83x294 note84x109 note85x937 note86x752 note87x567 note88x382 note0x197 note1x12 note2x840 note3x655 note4x470 note5x285 note6x100 note7x928 note8x743 note9x558 note10x373 note11x188 note12x3 note13x831 note14x646 note15x461 note16x276 note17x91 note18x919 note19x734 note20x549 note21x364 note22x179 note23x1007 note24x822 note25x637 note26x452 note27x267 note28x82 note29x910 note30x725 note31x540 note32x355 note33x170 note34x998 note35x813 note36x628 note37x443 note38x258 note39x73 note40x901 note41x716 note42x531 note43x346 note44x161 note45x989 note46x804 note47x619 note48x434 note49x249 note50x64 note51x892 note52x707 note53x522 note54x337 note55x152 note56x980 note57x795 note58x610 note59x425 note60x240 note61x55 note62x883 note63x698 note64x513 note65x328 note66x143 note67x971 note68x786 note69x601 note70x416 note71x231 note72x46 note73x874 note74x689 note75x504 note76x319 note77x134 note78x962 note79x777 note80x592 note81x407 note82x222 note83x37 note84x865 note85x680 note86x495 note87x310 note88x125 note0x953 note1x768 note2x583 note3x398 note4x213 note5x28 note6x856 note7x671 note8x486 note9x301 note10x116 note11x944 note12x759 note13x574 note14x389 note15x204 note16x19 note17x847 note18x662 note19x477 note20x292 note21x107 note22x935 note23x750 note24x565 note25x380 note26x195 note27x10 note28x838 note29x653 note30x468 note31x283 note32x98 note33x926 note34x741 note35x556 note36x371 note37x186 note38x1 note39x829 note40x644 note41x459 note42x274 note43x89 note44x917 note45x732 note46x547 note47x362 note48x177 note49x1005 note50x820 note51x635 note52x450 note53x265 note54x80 note55x908 note56x723 note57x538 note58x353 note59x168 note60x996 note61x811 note62x626 note63x441 note64x256 note65x71 note66x899 note67x714 note68x529 note69x344 note70x159 note71x987 note72x802 note73x617 note74x432 note75x247"}, {"role": "user", "content": "What is the first note?"}, {"role": "assistant", "content": "The first note is **note0x0**."}, {"role": "user", "content": "And the second one?"}, {"role": "assistant", "content": "The second note is **note1x828**."}, {"role": "user", "content": "Is note5x5 listed?"}], "max_tokens": 48, "temperature": 0.0, "draft": true, "chat_template_kwargs": {"enable_thinking": false}}, "status": 200, "response": {"id": "chatcmpl-14510cd468aa8f1fe4d89689b97ecc5e", "object": "chat.completion", "created": 1793474116, "model": "flashnext", "choices": [{"index": 0, "message": {"role": "assistant", "content": "No, **note5x5** is not listed in the provided reference notes.\n\nThe list contains notes with hex suffixes (e.g., `note5x88`, `note5x587`, `note5"}, "finish_reason": "length"}], "usage": {"prompt_tokens": 10281, "completion_tokens": 48, "total_tokens": 10329, "prompt_tokens_details": {"cached_tokens": 0}, "completion_tokens_details": {"reasoning_tokens": 0}}, "exact_mode": "exact", "tensorfold": {"enable_thinking": false, "reasoning_effort": "none", "engine": "lanes", "tokens_per_second": 46.47305448991743, "seconds": 1.011338732, "prefill_seconds": 18.712641787, "prefill_widths": [], "prefill_raised": [], "time_to_first_token": 18.714197679, "sampling": "greedy", "drafts": true, "token_sha": "e7287d6bf366", "token_sha256": "e7287d6bf36620acbd71b1537e7b5ea9b239198191676c8c2261aad653c64a81", "min_rows": 2}, "speculative": {"rounds": 17, "drafted": 40, "accepted": 31, "acceptance_rate": 0.775, "tokens_per_round": 2.823529411764706}}, "seconds": 19.72614336013794} +{"url": "http://127.0.0.1:30461/v1/chat/completions", "request": {"model": "flashnext", "messages": [{"role": "system", "content": "You are a careful assistant. Reference notes: note0x0 note1x828 note2x643 note3x458 note4x273 note5x88 note6x916 note7x731 note8x546 note9x361 note10x176 note11x1004 note12x819 note13x634 note14x449 note15x264 note16x79 note17x907 note18x722 note19x537 note20x352 note21x167 note22x995 note23x810 note24x625 note25x440 note26x255 note27x70 note28x898 note29x713 note30x528 note31x343 note32x158 note33x986 note34x801 note35x616 note36x431 note37x246 note38x61 note39x889 note40x704 note41x519 note42x334 note43x149 note44x977 note45x792 note46x607 note47x422 note48x237 note49x52 note50x880 note51x695 note52x510 note53x325 note54x140 note55x968 note56x783 note57x598 note58x413 note59x228 note60x43 note61x871 note62x686 note63x501 note64x316 note65x131 note66x959 note67x774 note68x589 note69x404 note70x219 note71x34 note72x862 note73x677 note74x492 note75x307 note76x122 note77x950 note78x765 note79x580 note80x395 note81x210 note82x25 note83x853 note84x668 note85x483 note86x298 note87x113 note88x941 note0x756 note1x571 note2x386 note3x201 note4x16 note5x844 note6x659 note7x474 note8x289 note9x104 note10x932 note11x747 note12x562 note13x377 note14x192 note15x7 note16x835 note17x650 note18x465 note19x280 note20x95 note21x923 note22x738 note23x553 note24x368 note25x183 note26x1011 note27x826 note28x641 note29x456 note30x271 note31x86 note32x914 note33x729 note34x544 note35x359 note36x174 note37x1002 note38x817 note39x632 note40x447 note41x262 note42x77 note43x905 note44x720 note45x535 note46x350 note47x165 note48x993 note49x808 note50x623 note51x438 note52x253 note53x68 note54x896 note55x711 note56x526 note57x341 note58x156 note59x984 note60x799 note61x614 note62x429 note63x244 note64x59 note65x887 note66x702 note67x517 note68x332 note69x147 note70x975 note71x790 note72x605 note73x420 note74x235 note75x50 note76x878 note77x693 note78x508 note79x323 note80x138 note81x966 note82x781 note83x596 note84x411 note85x226 note86x41 note87x869 note88x684 note0x499 note1x314 note2x129 note3x957 note4x772 note5x587 note6x402 note7x217 note8x32 note9x860 note10x675 note11x490 note12x305 note13x120 note14x948 note15x763 note16x578 note17x393 note18x208 note19x23 note20x851 note21x666 note22x481 note23x296 note24x111 note25x939 note26x754 note27x569 note28x384 note29x199 note30x14 note31x842 note32x657 note33x472 note34x287 note35x102 note36x930 note37x745 note38x560 note39x375 note40x190 note41x5 note42x833 note43x648 note44x463 note45x278 note46x93 note47x921 note48x736 note49x551 note50x366 note51x181 note52x1009 note53x824 note54x639 note55x454 note56x269 note57x84 note58x912 note59x727 note60x542 note61x357 note62x172 note63x1000 note64x815 note65x630 note66x445 note67x260 note68x75 note69x903 note70x718 note71x533 note72x348 note73x163 note74x991 note75x806 note76x621 note77x436 note78x251 note79x66 note80x894 note81x709 note82x524 note83x339 note84x154 note85x982 note86x797 note87x612 note88x427 note0x242 note1x57 note2x885 note3x700 note4x515 note5x330 note6x145 note7x973 note8x788 note9x603 note10x418 note11x233 note12x48 note13x876 note14x691 note15x506 note16x321 note17x136 note18x964 note19x779 note20x594 note21x409 note22x224 note23x39 note24x867 note25x682 note26x497 note27x312 note28x127 note29x955 note30x770 note31x585 note32x400 note33x215 note34x30 note35x858 note36x673 note37x488 note38x303 note39x118 note40x946 note41x761 note42x576 note43x391 note44x206 note45x21 note46x849 note47x664 note48x479 note49x294 note50x109 note51x937 note52x752 note53x567 note54x382 note55x197 note56x12 note57x840 note58x655 note59x470 note60x285 note61x100 note62x928 note63x743 note64x558 note65x373 note66x188 note67x3 note68x831 note69x646 note70x461 note71x276 note72x91 note73x919 note74x734 note75x549 note76x364 note77x179 note78x1007 note79x822 note80x637 note81x452 note82x267 note83x82 note84x910 note85x725 note86x540 note87x355 note88x170 note0x998 note1x813 note2x628 note3x443 note4x258 note5x73 note6x901 note7x716 note8x531 note9x346 note10x161 note11x989 note12x804 note13x619 note14x434 note15x249 note16x64 note17x892 note18x707 note19x522 note20x337 note21x152 note22x980 note23x795 note24x610 note25x425 note26x240 note27x55 note28x883 note29x698 note30x513 note31x328 note32x143 note33x971 note34x786 note35x601 note36x416 note37x231 note38x46 note39x874 note40x689 note41x504 note42x319 note43x134 note44x962 note45x777 note46x592 note47x407 note48x222 note49x37 note50x865 note51x680 note52x495 note53x310 note54x125 note55x953 note56x768 note57x583 note58x398 note59x213 note60x28 note61x856 note62x671 note63x486 note64x301 note65x116 note66x944 note67x759 note68x574 note69x389 note70x204 note71x19 note72x847 note73x662 note74x477 note75x292 note76x107 note77x935 note78x750 note79x565 note80x380 note81x195 note82x10 note83x838 note84x653 note85x468 note86x283 note87x98 note88x926 note0x741 note1x556 note2x371 note3x186 note4x1 note5x829 note6x644 note7x459 note8x274 note9x89 note10x917 note11x732 note12x547 note13x362 note14x177 note15x1005 note16x820 note17x635 note18x450 note19x265 note20x80 note21x908 note22x723 note23x538 note24x353 note25x168 note26x996 note27x811 note28x626 note29x441 note30x256 note31x71 note32x899 note33x714 note34x529 note35x344 note36x159 note37x987 note38x802 note39x617 note40x432 note41x247 note42x62 note43x890 note44x705 note45x520 note46x335 note47x150 note48x978 note49x793 note50x608 note51x423 note52x238 note53x53 note54x881 note55x696 note56x511 note57x326 note58x141 note59x969 note60x784 note61x599 note62x414 note63x229 note64x44 note65x872 note66x687 note67x502 note68x317 note69x132 note70x960 note71x775 note72x590 note73x405 note74x220 note75x35 note76x863 note77x678 note78x493 note79x308 note80x123 note81x951 note82x766 note83x581 note84x396 note85x211 note86x26 note87x854 note88x669 note0x484 note1x299 note2x114 note3x942 note4x757 note5x572 note6x387 note7x202 note8x17 note9x845 note10x660 note11x475 note12x290 note13x105 note14x933 note15x748 note16x563 note17x378 note18x193 note19x8 note20x836 note21x651 note22x466 note23x281 note24x96 note25x924 note26x739 note27x554 note28x369 note29x184 note30x1012 note31x827 note32x642 note33x457 note34x272 note35x87 note36x915 note37x730 note38x545 note39x360 note40x175 note41x1003 note42x818 note43x633 note44x448 note45x263 note46x78 note47x906 note48x721 note49x536 note50x351 note51x166 note52x994 note53x809 note54x624 note55x439 note56x254 note57x69 note58x897 note59x712 note60x527 note61x342 note62x157 note63x985 note64x800 note65x615 note66x430 note67x245 note68x60 note69x888 note70x703 note71x518 note72x333 note73x148 note74x976 note75x791 note76x606 note77x421 note78x236 note79x51 note80x879 note81x694 note82x509 note83x324 note84x139 note85x967 note86x782 note87x597 note88x412 note0x227 note1x42 note2x870 note3x685 note4x500 note5x315 note6x130 note7x958 note8x773 note9x588 note10x403 note11x218 note12x33 note13x861 note14x676 note15x491 note16x306 note17x121 note18x949 note19x764 note20x579 note21x394 note22x209 note23x24 note24x852 note25x667 note26x482 note27x297 note28x112 note29x940 note30x755 note31x570 note32x385 note33x200 note34x15 note35x843 note36x658 note37x473 note38x288 note39x103 note40x931 note41x746 note42x561 note43x376 note44x191 note45x6 note46x834 note47x649 note48x464 note49x279 note50x94 note51x922 note52x737 note53x552 note54x367 note55x182 note56x1010 note57x825 note58x640 note59x455 note60x270 note61x85 note62x913 note63x728 note64x543 note65x358 note66x173 note67x1001 note68x816 note69x631 note70x446 note71x261 note72x76 note73x904 note74x719 note75x534 note76x349 note77x164 note78x992 note79x807 note80x622 note81x437 note82x252 note83x67 note84x895 note85x710 note86x525 note87x340 note88x155 note0x983 note1x798 note2x613 note3x428 note4x243 note5x58 note6x886 note7x701 note8x516 note9x331 note10x146 note11x974 note12x789 note13x604 note14x419 note15x234 note16x49 note17x877 note18x692 note19x507 note20x322 note21x137 note22x965 note23x780 note24x595 note25x410 note26x225 note27x40 note28x868 note29x683 note30x498 note31x313 note32x128 note33x956 note34x771 note35x586 note36x401 note37x216 note38x31 note39x859 note40x674 note41x489 note42x304 note43x119 note44x947 note45x762 note46x577 note47x392 note48x207 note49x22 note50x850 note51x665 note52x480 note53x295 note54x110 note55x938 note56x753 note57x568 note58x383 note59x198 note60x13 note61x841 note62x656 note63x471 note64x286 note65x101 note66x929 note67x744 note68x559 note69x374 note70x189 note71x4 note72x832 note73x647 note74x462 note75x277 note76x92 note77x920 note78x735 note79x550 note80x365 note81x180 note82x1008 note83x823 note84x638 note85x453 note86x268 note87x83 note88x911 note0x726 note1x541 note2x356 note3x171 note4x999 note5x814 note6x629 note7x444 note8x259 note9x74 note10x902 note11x717 note12x532 note13x347 note14x162 note15x990 note16x805 note17x620 note18x435 note19x250 note20x65 note21x893 note22x708 note23x523 note24x338 note25x153 note26x981 note27x796 note28x611 note29x426 note30x241 note31x56 note32x884 note33x699 note34x514 note35x329 note36x144 note37x972 note38x787 note39x602 note40x417 note41x232 note42x47 note43x875 note44x690 note45x505 note46x320 note47x135 note48x963 note49x778 note50x593 note51x408 note52x223 note53x38 note54x866 note55x681 note56x496 note57x311 note58x126 note59x954 note60x769 note61x584 note62x399 note63x214 note64x29 note65x857 note66x672 note67x487 note68x302 note69x117 note70x945 note71x760 note72x575 note73x390 note74x205 note75x20 note76x848 note77x663 note78x478 note79x293 note80x108 note81x936 note82x751 note83x566 note84x381 note85x196 note86x11 note87x839 note88x654 note0x469 note1x284 note2x99 note3x927 note4x742 note5x557 note6x372 note7x187 note8x2 note9x830 note10x645 note11x460 note12x275 note13x90 note14x918 note15x733 note16x548 note17x363 note18x178 note19x1006 note20x821 note21x636 note22x451 note23x266 note24x81 note25x909 note26x724 note27x539 note28x354 note29x169 note30x997 note31x812 note32x627 note33x442 note34x257 note35x72 note36x900 note37x715 note38x530 note39x345 note40x160 note41x988 note42x803 note43x618 note44x433 note45x248 note46x63 note47x891 note48x706 note49x521 note50x336 note51x151 note52x979 note53x794 note54x609 note55x424 note56x239 note57x54 note58x882 note59x697 note60x512 note61x327 note62x142 note63x970 note64x785 note65x600 note66x415 note67x230 note68x45 note69x873 note70x688 note71x503 note72x318 note73x133 note74x961 note75x776 note76x591 note77x406 note78x221 note79x36 note80x864 note81x679 note82x494 note83x309 note84x124 note85x952 note86x767 note87x582 note88x397 note0x212 note1x27 note2x855 note3x670 note4x485 note5x300 note6x115 note7x943 note8x758 note9x573 note10x388 note11x203 note12x18 note13x846 note14x661 note15x476 note16x291 note17x106 note18x934 note19x749 note20x564 note21x379 note22x194 note23x9 note24x837 note25x652 note26x467 note27x282 note28x97 note29x925 note30x740 note31x555 note32x370 note33x185 note34x0 note35x828 note36x643 note37x458 note38x273 note39x88 note40x916 note41x731 note42x546 note43x361 note44x176 note45x1004 note46x819 note47x634 note48x449 note49x264 note50x79 note51x907 note52x722 note53x537 note54x352 note55x167 note56x995 note57x810 note58x625 note59x440 note60x255 note61x70 note62x898 note63x713 note64x528 note65x343 note66x158 note67x986 note68x801 note69x616 note70x431 note71x246 note72x61 note73x889 note74x704 note75x519 note76x334 note77x149 note78x977 note79x792 note80x607 note81x422 note82x237 note83x52 note84x880 note85x695 note86x510 note87x325 note88x140 note0x968 note1x783 note2x598 note3x413 note4x228 note5x43 note6x871 note7x686 note8x501 note9x316 note10x131 note11x959 note12x774 note13x589 note14x404 note15x219 note16x34 note17x862 note18x677 note19x492 note20x307 note21x122 note22x950 note23x765 note24x580 note25x395 note26x210 note27x25 note28x853 note29x668 note30x483 note31x298 note32x113 note33x941 note34x756 note35x571 note36x386 note37x201 note38x16 note39x844 note40x659 note41x474 note42x289 note43x104 note44x932 note45x747 note46x562 note47x377 note48x192 note49x7 note50x835 note51x650 note52x465 note53x280 note54x95 note55x923 note56x738 note57x553 note58x368 note59x183 note60x1011 note61x826 note62x641 note63x456 note64x271 note65x86 note66x914 note67x729 note68x544 note69x359 note70x174 note71x1002 note72x817 note73x632 note74x447 note75x262 note76x77 note77x905 note78x720 note79x535 note80x350 note81x165 note82x993 note83x808 note84x623 note85x438 note86x253 note87x68 note88x896 note0x711 note1x526 note2x341 note3x156 note4x984 note5x799 note6x614 note7x429 note8x244 note9x59 note10x887 note11x702 note12x517 note13x332 note14x147 note15x975 note16x790 note17x605 note18x420 note19x235 note20x50 note21x878 note22x693 note23x508 note24x323 note25x138 note26x966 note27x781 note28x596 note29x411 note30x226 note31x41 note32x869 note33x684 note34x499 note35x314 note36x129 note37x957 note38x772 note39x587 note40x402 note41x217 note42x32 note43x860 note44x675 note45x490 note46x305 note47x120 note48x948 note49x763 note50x578 note51x393 note52x208 note53x23 note54x851 note55x666 note56x481 note57x296 note58x111 note59x939 note60x754 note61x569 note62x384 note63x199 note64x14 note65x842 note66x657 note67x472 note68x287 note69x102 note70x930 note71x745 note72x560 note73x375 note74x190 note75x5 note76x833 note77x648 note78x463 note79x278 note80x93 note81x921 note82x736 note83x551 note84x366 note85x181 note86x1009 note87x824 note88x639 note0x454 note1x269 note2x84 note3x912 note4x727 note5x542 note6x357 note7x172 note8x1000 note9x815 note10x630 note11x445 note12x260 note13x75 note14x903 note15x718 note16x533 note17x348 note18x163 note19x991 note20x806 note21x621 note22x436 note23x251 note24x66 note25x894 note26x709 note27x524 note28x339 note29x154 note30x982 note31x797 note32x612 note33x427 note34x242 note35x57 note36x885 note37x700 note38x515 note39x330 note40x145 note41x973 note42x788 note43x603 note44x418 note45x233 note46x48 note47x876 note48x691 note49x506 note50x321 note51x136 note52x964 note53x779 note54x594 note55x409 note56x224 note57x39 note58x867 note59x682 note60x497 note61x312 note62x127 note63x955 note64x770 note65x585 note66x400 note67x215 note68x30 note69x858 note70x673 note71x488 note72x303 note73x118 note74x946 note75x761 note76x576 note77x391 note78x206 note79x21 note80x849 note81x664 note82x479 note83x294 note84x109 note85x937 note86x752 note87x567 note88x382 note0x197 note1x12 note2x840 note3x655 note4x470 note5x285 note6x100 note7x928 note8x743 note9x558 note10x373 note11x188 note12x3 note13x831 note14x646 note15x461 note16x276 note17x91 note18x919 note19x734 note20x549 note21x364 note22x179 note23x1007 note24x822 note25x637 note26x452 note27x267 note28x82 note29x910 note30x725 note31x540 note32x355 note33x170 note34x998 note35x813 note36x628 note37x443 note38x258 note39x73 note40x901 note41x716 note42x531 note43x346 note44x161 note45x989 note46x804 note47x619 note48x434 note49x249 note50x64 note51x892 note52x707 note53x522 note54x337 note55x152 note56x980 note57x795 note58x610 note59x425 note60x240 note61x55 note62x883 note63x698 note64x513 note65x328 note66x143 note67x971 note68x786 note69x601 note70x416 note71x231 note72x46 note73x874 note74x689 note75x504 note76x319 note77x134 note78x962 note79x777 note80x592 note81x407 note82x222 note83x37 note84x865 note85x680 note86x495 note87x310 note88x125 note0x953 note1x768 note2x583 note3x398 note4x213 note5x28 note6x856 note7x671 note8x486 note9x301 note10x116 note11x944 note12x759 note13x574 note14x389 note15x204 note16x19 note17x847 note18x662 note19x477 note20x292 note21x107 note22x935 note23x750 note24x565 note25x380 note26x195 note27x10 note28x838 note29x653 note30x468 note31x283 note32x98 note33x926 note34x741 note35x556 note36x371 note37x186 note38x1 note39x829 note40x644 note41x459 note42x274 note43x89 note44x917 note45x732 note46x547 note47x362 note48x177 note49x1005 note50x820 note51x635 note52x450 note53x265 note54x80 note55x908 note56x723 note57x538 note58x353 note59x168 note60x996 note61x811 note62x626 note63x441 note64x256 note65x71 note66x899 note67x714 note68x529 note69x344 note70x159 note71x987 note72x802 note73x617 note74x432 note75x247"}, {"role": "user", "content": "What is the first note?"}, {"role": "assistant", "content": "The first note is **note0x0**."}, {"role": "user", "content": "And the second one?"}, {"role": "assistant", "content": "The second note is **note1x828**."}, {"role": "user", "content": "Is note7x7 listed?"}], "max_tokens": 48, "temperature": 0.0, "draft": true, "chat_template_kwargs": {"enable_thinking": false}}, "status": 200, "response": {"id": "chatcmpl-6ba85ee47971a938ce56431d7338e6eb", "object": "chat.completion", "created": 1793474136, "model": "flashnext", "choices": [{"index": 0, "message": {"role": "assistant", "content": "No, **note7x7** is not listed in the provided reference notes.\n\nThe notes follow a pattern where the second part (after the 'x') is a hexadecimal number (e.g., `note1x828"}, "finish_reason": "length"}], "usage": {"prompt_tokens": 10281, "completion_tokens": 48, "total_tokens": 10329, "prompt_tokens_details": {"cached_tokens": 0}, "completion_tokens_details": {"reasoning_tokens": 0}}, "exact_mode": "exact", "tensorfold": {"enable_thinking": false, "reasoning_effort": "none", "engine": "lanes", "tokens_per_second": 42.84885510712705, "seconds": 1.096878782, "prefill_seconds": 18.752611162, "prefill_widths": [], "prefill_raised": [], "time_to_first_token": 18.753368539, "sampling": "greedy", "drafts": true, "token_sha": "55e1d46d0689", "token_sha256": "55e1d46d06891dff37e5a39f83ae22514ba7952a98a301c70166bbb637c3f3b6", "min_rows": 2}, "speculative": {"rounds": 21, "drafted": 41, "accepted": 27, "acceptance_rate": 0.6585365853658537, "tokens_per_round": 2.2857142857142856}}, "seconds": 19.851150512695312} +{"url": "http://127.0.0.1:30461/v1/chat/completions", "request": {"model": "flashnext", "messages": [{"role": "system", "content": "You are a careful assistant. Reference notes: note0x0 note1x828 note2x643 note3x458 note4x273 note5x88 note6x916 note7x731 note8x546 note9x361 note10x176 note11x1004 note12x819 note13x634 note14x449 note15x264 note16x79 note17x907 note18x722 note19x537 note20x352 note21x167 note22x995 note23x810 note24x625 note25x440 note26x255 note27x70 note28x898 note29x713 note30x528 note31x343 note32x158 note33x986 note34x801 note35x616 note36x431 note37x246 note38x61 note39x889 note40x704 note41x519 note42x334 note43x149 note44x977 note45x792 note46x607 note47x422 note48x237 note49x52 note50x880 note51x695 note52x510 note53x325 note54x140 note55x968 note56x783 note57x598 note58x413 note59x228 note60x43 note61x871 note62x686 note63x501 note64x316 note65x131 note66x959 note67x774 note68x589 note69x404 note70x219 note71x34 note72x862 note73x677 note74x492 note75x307 note76x122 note77x950 note78x765 note79x580 note80x395 note81x210 note82x25 note83x853 note84x668 note85x483 note86x298 note87x113 note88x941 note0x756 note1x571 note2x386 note3x201 note4x16 note5x844 note6x659 note7x474 note8x289 note9x104 note10x932 note11x747 note12x562 note13x377 note14x192 note15x7 note16x835 note17x650 note18x465 note19x280 note20x95 note21x923 note22x738 note23x553 note24x368 note25x183 note26x1011 note27x826 note28x641 note29x456 note30x271 note31x86 note32x914 note33x729 note34x544 note35x359 note36x174 note37x1002 note38x817 note39x632 note40x447 note41x262 note42x77 note43x905 note44x720 note45x535 note46x350 note47x165 note48x993 note49x808 note50x623 note51x438 note52x253 note53x68 note54x896 note55x711 note56x526 note57x341 note58x156 note59x984 note60x799 note61x614 note62x429 note63x244 note64x59 note65x887 note66x702 note67x517 note68x332 note69x147 note70x975 note71x790 note72x605 note73x420 note74x235 note75x50 note76x878 note77x693 note78x508 note79x323 note80x138 note81x966 note82x781 note83x596 note84x411 note85x226 note86x41 note87x869 note88x684 note0x499 note1x314 note2x129 note3x957 note4x772 note5x587 note6x402 note7x217 note8x32 note9x860 note10x675 note11x490 note12x305 note13x120 note14x948 note15x763 note16x578 note17x393 note18x208 note19x23 note20x851 note21x666 note22x481 note23x296 note24x111 note25x939 note26x754 note27x569 note28x384 note29x199 note30x14 note31x842 note32x657 note33x472 note34x287 note35x102 note36x930 note37x745 note38x560 note39x375 note40x190 note41x5 note42x833 note43x648 note44x463 note45x278 note46x93 note47x921 note48x736 note49x551 note50x366 note51x181 note52x1009 note53x824 note54x639 note55x454 note56x269 note57x84 note58x912 note59x727 note60x542 note61x357 note62x172 note63x1000 note64x815 note65x630 note66x445 note67x260 note68x75 note69x903 note70x718 note71x533 note72x348 note73x163 note74x991 note75x806 note76x621 note77x436 note78x251 note79x66 note80x894 note81x709 note82x524 note83x339 note84x154 note85x982 note86x797 note87x612 note88x427 note0x242 note1x57 note2x885 note3x700 note4x515 note5x330 note6x145 note7x973 note8x788 note9x603 note10x418 note11x233 note12x48 note13x876 note14x691 note15x506 note16x321 note17x136 note18x964 note19x779 note20x594 note21x409 note22x224 note23x39 note24x867 note25x682 note26x497 note27x312 note28x127 note29x955 note30x770 note31x585 note32x400 note33x215 note34x30 note35x858 note36x673 note37x488 note38x303 note39x118 note40x946 note41x761 note42x576 note43x391 note44x206 note45x21 note46x849 note47x664 note48x479 note49x294 note50x109 note51x937 note52x752 note53x567 note54x382 note55x197 note56x12 note57x840 note58x655 note59x470 note60x285 note61x100 note62x928 note63x743 note64x558 note65x373 note66x188 note67x3 note68x831 note69x646 note70x461 note71x276 note72x91 note73x919 note74x734 note75x549 note76x364 note77x179 note78x1007 note79x822 note80x637 note81x452 note82x267 note83x82 note84x910 note85x725 note86x540 note87x355 note88x170 note0x998 note1x813 note2x628 note3x443 note4x258 note5x73 note6x901 note7x716 note8x531 note9x346 note10x161 note11x989 note12x804 note13x619 note14x434 note15x249 note16x64 note17x892 note18x707 note19x522 note20x337 note21x152 note22x980 note23x795 note24x610 note25x425 note26x240 note27x55 note28x883 note29x698 note30x513 note31x328 note32x143 note33x971 note34x786 note35x601 note36x416 note37x231 note38x46 note39x874 note40x689 note41x504 note42x319 note43x134 note44x962 note45x777 note46x592 note47x407 note48x222 note49x37 note50x865 note51x680 note52x495 note53x310 note54x125 note55x953 note56x768 note57x583 note58x398 note59x213 note60x28 note61x856 note62x671 note63x486 note64x301 note65x116 note66x944 note67x759 note68x574 note69x389 note70x204 note71x19 note72x847 note73x662 note74x477 note75x292 note76x107 note77x935 note78x750 note79x565 note80x380 note81x195 note82x10 note83x838 note84x653 note85x468 note86x283 note87x98 note88x926 note0x741 note1x556 note2x371 note3x186 note4x1 note5x829 note6x644 note7x459 note8x274 note9x89 note10x917 note11x732 note12x547 note13x362 note14x177 note15x1005 note16x820 note17x635 note18x450 note19x265 note20x80 note21x908 note22x723 note23x538 note24x353 note25x168 note26x996 note27x811 note28x626 note29x441 note30x256 note31x71 note32x899 note33x714 note34x529 note35x344 note36x159 note37x987 note38x802 note39x617 note40x432 note41x247 note42x62 note43x890 note44x705 note45x520 note46x335 note47x150 note48x978 note49x793 note50x608 note51x423 note52x238 note53x53 note54x881 note55x696 note56x511 note57x326 note58x141 note59x969 note60x784 note61x599 note62x414 note63x229 note64x44 note65x872 note66x687 note67x502 note68x317 note69x132 note70x960 note71x775 note72x590 note73x405 note74x220 note75x35 note76x863 note77x678 note78x493 note79x308 note80x123 note81x951 note82x766 note83x581 note84x396 note85x211 note86x26 note87x854 note88x669 note0x484 note1x299 note2x114 note3x942 note4x757 note5x572 note6x387 note7x202 note8x17 note9x845 note10x660 note11x475 note12x290 note13x105 note14x933 note15x748 note16x563 note17x378 note18x193 note19x8 note20x836 note21x651 note22x466 note23x281 note24x96 note25x924 note26x739 note27x554 note28x369 note29x184 note30x1012 note31x827 note32x642 note33x457 note34x272 note35x87 note36x915 note37x730 note38x545 note39x360 note40x175 note41x1003 note42x818 note43x633 note44x448 note45x263 note46x78 note47x906 note48x721 note49x536 note50x351 note51x166 note52x994 note53x809 note54x624 note55x439 note56x254 note57x69 note58x897 note59x712 note60x527 note61x342 note62x157 note63x985 note64x800 note65x615 note66x430 note67x245 note68x60 note69x888 note70x703 note71x518 note72x333 note73x148 note74x976 note75x791 note76x606 note77x421 note78x236 note79x51 note80x879 note81x694 note82x509 note83x324 note84x139 note85x967 note86x782 note87x597 note88x412 note0x227 note1x42 note2x870 note3x685 note4x500 note5x315 note6x130 note7x958 note8x773 note9x588 note10x403 note11x218 note12x33 note13x861 note14x676 note15x491 note16x306 note17x121 note18x949 note19x764 note20x579 note21x394 note22x209 note23x24 note24x852 note25x667 note26x482 note27x297 note28x112 note29x940 note30x755 note31x570 note32x385 note33x200 note34x15 note35x843 note36x658 note37x473 note38x288 note39x103 note40x931 note41x746 note42x561 note43x376 note44x191 note45x6 note46x834 note47x649 note48x464 note49x279 note50x94 note51x922 note52x737 note53x552 note54x367 note55x182 note56x1010 note57x825 note58x640 note59x455 note60x270 note61x85 note62x913 note63x728 note64x543 note65x358 note66x173 note67x1001 note68x816 note69x631 note70x446 note71x261 note72x76 note73x904 note74x719 note75x534 note76x349 note77x164 note78x992 note79x807 note80x622 note81x437 note82x252 note83x67 note84x895 note85x710 note86x525 note87x340 note88x155 note0x983 note1x798 note2x613 note3x428 note4x243 note5x58 note6x886 note7x701 note8x516 note9x331 note10x146 note11x974 note12x789 note13x604 note14x419 note15x234 note16x49 note17x877 note18x692 note19x507 note20x322 note21x137 note22x965 note23x780 note24x595 note25x410 note26x225 note27x40 note28x868 note29x683 note30x498 note31x313 note32x128 note33x956 note34x771 note35x586 note36x401 note37x216 note38x31 note39x859 note40x674 note41x489 note42x304 note43x119 note44x947 note45x762 note46x577 note47x392 note48x207 note49x22 note50x850 note51x665 note52x480 note53x295 note54x110 note55x938 note56x753 note57x568 note58x383 note59x198 note60x13 note61x841 note62x656 note63x471 note64x286 note65x101 note66x929 note67x744 note68x559 note69x374 note70x189 note71x4 note72x832 note73x647 note74x462 note75x277 note76x92 note77x920 note78x735 note79x550 note80x365 note81x180 note82x1008 note83x823 note84x638 note85x453 note86x268 note87x83 note88x911 note0x726 note1x541 note2x356 note3x171 note4x999 note5x814 note6x629 note7x444 note8x259 note9x74 note10x902 note11x717 note12x532 note13x347 note14x162 note15x990 note16x805 note17x620 note18x435 note19x250 note20x65 note21x893 note22x708 note23x523 note24x338 note25x153 note26x981 note27x796 note28x611 note29x426 note30x241 note31x56 note32x884 note33x699 note34x514 note35x329 note36x144 note37x972 note38x787 note39x602 note40x417 note41x232 note42x47 note43x875 note44x690 note45x505 note46x320 note47x135 note48x963 note49x778 note50x593 note51x408 note52x223 note53x38 note54x866 note55x681 note56x496 note57x311 note58x126 note59x954 note60x769 note61x584 note62x399 note63x214 note64x29 note65x857 note66x672 note67x487 note68x302 note69x117 note70x945 note71x760 note72x575 note73x390 note74x205 note75x20 note76x848 note77x663 note78x478 note79x293 note80x108 note81x936 note82x751 note83x566 note84x381 note85x196 note86x11 note87x839 note88x654 note0x469 note1x284 note2x99 note3x927 note4x742 note5x557 note6x372 note7x187 note8x2 note9x830 note10x645 note11x460 note12x275 note13x90 note14x918 note15x733 note16x548 note17x363 note18x178 note19x1006 note20x821 note21x636 note22x451 note23x266 note24x81 note25x909 note26x724 note27x539 note28x354 note29x169 note30x997 note31x812 note32x627 note33x442 note34x257 note35x72 note36x900 note37x715 note38x530 note39x345 note40x160 note41x988 note42x803 note43x618 note44x433 note45x248 note46x63 note47x891 note48x706 note49x521 note50x336 note51x151 note52x979 note53x794 note54x609 note55x424 note56x239 note57x54 note58x882 note59x697 note60x512 note61x327 note62x142 note63x970 note64x785 note65x600 note66x415 note67x230 note68x45 note69x873 note70x688 note71x503 note72x318 note73x133 note74x961 note75x776 note76x591 note77x406 note78x221 note79x36 note80x864 note81x679 note82x494 note83x309 note84x124 note85x952 note86x767 note87x582 note88x397 note0x212 note1x27 note2x855 note3x670 note4x485 note5x300 note6x115 note7x943 note8x758 note9x573 note10x388 note11x203 note12x18 note13x846 note14x661 note15x476 note16x291 note17x106 note18x934 note19x749 note20x564 note21x379 note22x194 note23x9 note24x837 note25x652 note26x467 note27x282 note28x97 note29x925 note30x740 note31x555 note32x370 note33x185 note34x0 note35x828 note36x643 note37x458 note38x273 note39x88 note40x916 note41x731 note42x546 note43x361 note44x176 note45x1004 note46x819 note47x634 note48x449 note49x264 note50x79 note51x907 note52x722 note53x537 note54x352 note55x167 note56x995 note57x810 note58x625 note59x440 note60x255 note61x70 note62x898 note63x713 note64x528 note65x343 note66x158 note67x986 note68x801 note69x616 note70x431 note71x246 note72x61 note73x889 note74x704 note75x519 note76x334 note77x149 note78x977 note79x792 note80x607 note81x422 note82x237 note83x52 note84x880 note85x695 note86x510 note87x325 note88x140 note0x968 note1x783 note2x598 note3x413 note4x228 note5x43 note6x871 note7x686 note8x501 note9x316 note10x131 note11x959 note12x774 note13x589 note14x404 note15x219 note16x34 note17x862 note18x677 note19x492 note20x307 note21x122 note22x950 note23x765 note24x580 note25x395 note26x210 note27x25 note28x853 note29x668 note30x483 note31x298 note32x113 note33x941 note34x756 note35x571 note36x386 note37x201 note38x16 note39x844 note40x659 note41x474 note42x289 note43x104 note44x932 note45x747 note46x562 note47x377 note48x192 note49x7 note50x835 note51x650 note52x465 note53x280 note54x95 note55x923 note56x738 note57x553 note58x368 note59x183 note60x1011 note61x826 note62x641 note63x456 note64x271 note65x86 note66x914 note67x729 note68x544 note69x359 note70x174 note71x1002 note72x817 note73x632 note74x447 note75x262 note76x77 note77x905 note78x720 note79x535 note80x350 note81x165 note82x993 note83x808 note84x623 note85x438 note86x253 note87x68 note88x896 note0x711 note1x526 note2x341 note3x156 note4x984 note5x799 note6x614 note7x429 note8x244 note9x59 note10x887 note11x702 note12x517 note13x332 note14x147 note15x975 note16x790 note17x605 note18x420 note19x235 note20x50 note21x878 note22x693 note23x508 note24x323 note25x138 note26x966 note27x781 note28x596 note29x411 note30x226 note31x41 note32x869 note33x684 note34x499 note35x314 note36x129 note37x957 note38x772 note39x587 note40x402 note41x217 note42x32 note43x860 note44x675 note45x490 note46x305 note47x120 note48x948 note49x763 note50x578 note51x393 note52x208 note53x23 note54x851 note55x666 note56x481 note57x296 note58x111 note59x939 note60x754 note61x569 note62x384 note63x199 note64x14 note65x842 note66x657 note67x472 note68x287 note69x102 note70x930 note71x745 note72x560 note73x375 note74x190 note75x5 note76x833 note77x648 note78x463 note79x278 note80x93 note81x921 note82x736 note83x551 note84x366 note85x181 note86x1009 note87x824 note88x639 note0x454 note1x269 note2x84 note3x912 note4x727 note5x542 note6x357 note7x172 note8x1000 note9x815 note10x630 note11x445 note12x260 note13x75 note14x903 note15x718 note16x533 note17x348 note18x163 note19x991 note20x806 note21x621 note22x436 note23x251 note24x66 note25x894 note26x709 note27x524 note28x339 note29x154 note30x982 note31x797 note32x612 note33x427 note34x242 note35x57 note36x885 note37x700 note38x515 note39x330 note40x145 note41x973 note42x788 note43x603 note44x418 note45x233 note46x48 note47x876 note48x691 note49x506 note50x321 note51x136 note52x964 note53x779 note54x594 note55x409 note56x224 note57x39 note58x867 note59x682 note60x497 note61x312 note62x127 note63x955 note64x770 note65x585 note66x400 note67x215 note68x30 note69x858 note70x673 note71x488 note72x303 note73x118 note74x946 note75x761 note76x576 note77x391 note78x206 note79x21 note80x849 note81x664 note82x479 note83x294 note84x109 note85x937 note86x752 note87x567 note88x382 note0x197 note1x12 note2x840 note3x655 note4x470 note5x285 note6x100 note7x928 note8x743 note9x558 note10x373 note11x188 note12x3 note13x831 note14x646 note15x461 note16x276 note17x91 note18x919 note19x734 note20x549 note21x364 note22x179 note23x1007 note24x822 note25x637 note26x452 note27x267 note28x82 note29x910 note30x725 note31x540 note32x355 note33x170 note34x998 note35x813 note36x628 note37x443 note38x258 note39x73 note40x901 note41x716 note42x531 note43x346 note44x161 note45x989 note46x804 note47x619 note48x434 note49x249 note50x64 note51x892 note52x707 note53x522 note54x337 note55x152 note56x980 note57x795 note58x610 note59x425 note60x240 note61x55 note62x883 note63x698 note64x513 note65x328 note66x143 note67x971 note68x786 note69x601 note70x416 note71x231 note72x46 note73x874 note74x689 note75x504 note76x319 note77x134 note78x962 note79x777 note80x592 note81x407 note82x222 note83x37 note84x865 note85x680 note86x495 note87x310 note88x125 note0x953 note1x768 note2x583 note3x398 note4x213 note5x28 note6x856 note7x671 note8x486 note9x301 note10x116 note11x944 note12x759 note13x574 note14x389 note15x204 note16x19 note17x847 note18x662 note19x477 note20x292 note21x107 note22x935 note23x750 note24x565 note25x380 note26x195 note27x10 note28x838 note29x653 note30x468 note31x283 note32x98 note33x926 note34x741 note35x556 note36x371 note37x186 note38x1 note39x829 note40x644 note41x459 note42x274 note43x89 note44x917 note45x732 note46x547 note47x362 note48x177 note49x1005 note50x820 note51x635 note52x450 note53x265 note54x80 note55x908 note56x723 note57x538 note58x353 note59x168 note60x996 note61x811 note62x626 note63x441 note64x256 note65x71 note66x899 note67x714 note68x529 note69x344 note70x159 note71x987 note72x802 note73x617 note74x432 note75x247"}, {"role": "user", "content": "What is the first note?"}, {"role": "assistant", "content": "The first note is **note0x0**."}, {"role": "user", "content": "And the second one?"}, {"role": "assistant", "content": "The second note is **note1x828**."}, {"role": "user", "content": "Name the last note."}], "max_tokens": 48, "temperature": 0.0, "draft": true, "chat_template_kwargs": {"enable_thinking": false}}, "status": 200, "response": {"id": "chatcmpl-f83e24455a034904467619e2aa2fa844", "object": "chat.completion", "created": 1793474156, "model": "flashnext", "choices": [{"index": 0, "message": {"role": "assistant", "content": "The last note is **note75x247**."}, "finish_reason": "stop"}], "usage": {"prompt_tokens": 10279, "completion_tokens": 14, "total_tokens": 10293, "prompt_tokens_details": {"cached_tokens": 0}, "completion_tokens_details": {"reasoning_tokens": 0}}, "exact_mode": "exact", "tensorfold": {"enable_thinking": false, "reasoning_effort": "none", "engine": "lanes", "tokens_per_second": 35.072036276356044, "seconds": 0.370665675, "prefill_seconds": 18.743695657, "prefill_widths": [], "prefill_raised": [], "time_to_first_token": 18.744768083, "sampling": "greedy", "drafts": true, "token_sha": "9537be85f86c", "token_sha256": "9537be85f86c467fa028c7e7cd58d5b693a814bcc9988a99dec273e8e81523c1", "min_rows": 3}, "speculative": {"rounds": 4, "drafted": 20, "accepted": 12, "acceptance_rate": 0.6, "tokens_per_round": 3.5}}, "seconds": 19.1166934967041} +{"url": "http://127.0.0.1:30461/v1/chat/completions", "request": {"model": "flashnext", "messages": [{"role": "system", "content": "You are a careful assistant. 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note2x386 note3x201 note4x16 note5x844 note6x659 note7x474 note8x289 note9x104 note10x932 note11x747 note12x562 note13x377 note14x192 note15x7 note16x835 note17x650 note18x465 note19x280 note20x95 note21x923 note22x738 note23x553 note24x368 note25x183 note26x1011 note27x826 note28x641 note29x456 note30x271 note31x86 note32x914 note33x729 note34x544 note35x359 note36x174 note37x1002 note38x817 note39x632 note40x447 note41x262 note42x77 note43x905 note44x720 note45x535 note46x350 note47x165 note48x993 note49x808 note50x623 note51x438 note52x253 note53x68 note54x896 note55x711 note56x526 note57x341 note58x156 note59x984 note60x799 note61x614 note62x429 note63x244 note64x59 note65x887 note66x702 note67x517 note68x332 note69x147 note70x975 note71x790 note72x605 note73x420 note74x235 note75x50 note76x878 note77x693 note78x508 note79x323 note80x138 note81x966 note82x781 note83x596 note84x411 note85x226 note86x41 note87x869 note88x684 note0x499 note1x314 note2x129 note3x957 note4x772 note5x587 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"reasoning_effort": "none", "engine": "lanes", "tokens_per_second": 45.77780490367039, "seconds": 0.262135767, "prefill_seconds": 18.654015441, "prefill_widths": [], "prefill_raised": [], "time_to_first_token": 18.655231146, "sampling": "greedy", "drafts": true, "token_sha": "86effbb58f5b", "token_sha256": "86effbb58f5b1a059c85bb7445693561cdba823838fe7776eaafd0a10e14cf56", "min_rows": 2}, "speculative": {"rounds": 5, "drafted": 13, "accepted": 11, "acceptance_rate": 0.8461538461538461, "tokens_per_round": 2.6}}, "seconds": 18.918565034866333} +{"url": "http://127.0.0.1:30461/v1/chat/completions", "request": {"model": "flashnext", "messages": [{"role": "system", "content": "You are a careful assistant. 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note13x619 note14x434 note15x249 note16x64 note17x892 note18x707 note19x522 note20x337 note21x152 note22x980 note23x795 note24x610 note25x425 note26x240 note27x55 note28x883 note29x698 note30x513 note31x328 note32x143 note33x971 note34x786 note35x601 note36x416 note37x231 note38x46 note39x874 note40x689 note41x504 note42x319 note43x134 note44x962 note45x777 note46x592 note47x407 note48x222 note49x37 note50x865 note51x680 note52x495 note53x310 note54x125 note55x953 note56x768 note57x583 note58x398 note59x213 note60x28 note61x856 note62x671 note63x486 note64x301 note65x116 note66x944 note67x759 note68x574 note69x389 note70x204 note71x19 note72x847 note73x662 note74x477 note75x292 note76x107 note77x935 note78x750 note79x565 note80x380 note81x195 note82x10 note83x838 note84x653 note85x468 note86x283 note87x98 note88x926 note0x741 note1x556 note2x371 note3x186 note4x1 note5x829 note6x644 note7x459 note8x274 note9x89 note10x917 note11x732 note12x547 note13x362 note14x177 note15x1005 note16x820 note17x635 note18x450 note19x265 note20x80 note21x908 note22x723 note23x538 note24x353 note25x168 note26x996 note27x811 note28x626 note29x441 note30x256 note31x71 note32x899 note33x714 note34x529 note35x344 note36x159 note37x987 note38x802 note39x617 note40x432 note41x247 note42x62 note43x890 note44x705 note45x520 note46x335 note47x150 note48x978 note49x793 note50x608 note51x423 note52x238 note53x53 note54x881 note55x696 note56x511 note57x326 note58x141 note59x969 note60x784 note61x599 note62x414 note63x229 note64x44 note65x872 note66x687 note67x502 note68x317 note69x132 note70x960 note71x775 note72x590 note73x405 note74x220 note75x35 note76x863 note77x678 note78x493 note79x308 note80x123 note81x951 note82x766 note83x581 note84x396 note85x211 note86x26 note87x854 note88x669 note0x484 note1x299 note2x114 note3x942 note4x757 note5x572 note6x387 note7x202 note8x17 note9x845 note10x660 note11x475 note12x290 note13x105 note14x933 note15x748 note16x563 note17x378 note18x193 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note22x209 note23x24 note24x852 note25x667 note26x482 note27x297 note28x112 note29x940 note30x755 note31x570 note32x385 note33x200 note34x15 note35x843 note36x658 note37x473 note38x288 note39x103 note40x931 note41x746 note42x561 note43x376 note44x191 note45x6 note46x834 note47x649 note48x464 note49x279 note50x94 note51x922 note52x737 note53x552 note54x367 note55x182 note56x1010 note57x825 note58x640 note59x455 note60x270 note61x85 note62x913 note63x728 note64x543 note65x358 note66x173 note67x1001 note68x816 note69x631 note70x446 note71x261 note72x76 note73x904 note74x719 note75x534 note76x349 note77x164 note78x992 note79x807 note80x622 note81x437 note82x252 note83x67 note84x895 note85x710 note86x525 note87x340 note88x155 note0x983 note1x798 note2x613 note3x428 note4x243 note5x58 note6x886 note7x701 note8x516 note9x331 note10x146 note11x974 note12x789 note13x604 note14x419 note15x234 note16x49 note17x877 note18x692 note19x507 note20x322 note21x137 note22x965 note23x780 note24x595 note25x410 note26x225 note27x40 note28x868 note29x683 note30x498 note31x313 note32x128 note33x956 note34x771 note35x586 note36x401 note37x216 note38x31 note39x859 note40x674 note41x489 note42x304 note43x119 note44x947 note45x762 note46x577 note47x392 note48x207 note49x22 note50x850 note51x665 note52x480 note53x295 note54x110 note55x938 note56x753 note57x568 note58x383 note59x198 note60x13 note61x841 note62x656 note63x471 note64x286 note65x101 note66x929 note67x744 note68x559 note69x374 note70x189 note71x4 note72x832 note73x647 note74x462 note75x277 note76x92 note77x920 note78x735 note79x550 note80x365 note81x180 note82x1008 note83x823 note84x638 note85x453 note86x268 note87x83 note88x911 note0x726 note1x541 note2x356 note3x171 note4x999 note5x814 note6x629 note7x444 note8x259 note9x74 note10x902 note11x717 note12x532 note13x347 note14x162 note15x990 note16x805 note17x620 note18x435 note19x250 note20x65 note21x893 note22x708 note23x523 note24x338 note25x153 note26x981 note27x796 note28x611 note29x426 note30x241 note31x56 note32x884 note33x699 note34x514 note35x329 note36x144 note37x972 note38x787 note39x602 note40x417 note41x232 note42x47 note43x875 note44x690 note45x505 note46x320 note47x135 note48x963 note49x778 note50x593 note51x408 note52x223 note53x38 note54x866 note55x681 note56x496 note57x311 note58x126 note59x954 note60x769 note61x584 note62x399 note63x214 note64x29 note65x857 note66x672 note67x487 note68x302 note69x117 note70x945 note71x760 note72x575 note73x390 note74x205 note75x20 note76x848 note77x663 note78x478 note79x293 note80x108 note81x936 note82x751 note83x566 note84x381 note85x196 note86x11 note87x839 note88x654 note0x469 note1x284 note2x99 note3x927 note4x742 note5x557 note6x372 note7x187 note8x2 note9x830 note10x645 note11x460 note12x275 note13x90 note14x918 note15x733 note16x548 note17x363 note18x178 note19x1006 note20x821 note21x636 note22x451 note23x266 note24x81 note25x909 note26x724 note27x539 note28x354 note29x169 note30x997 note31x812 note32x627 note33x442 note34x257 note35x72 note36x900 note37x715 note38x530 note39x345 note40x160 note41x988 note42x803 note43x618 note44x433 note45x248 note46x63 note47x891 note48x706 note49x521 note50x336 note51x151 note52x979 note53x794 note54x609 note55x424 note56x239 note57x54 note58x882 note59x697 note60x512 note61x327 note62x142 note63x970 note64x785 note65x600 note66x415 note67x230 note68x45 note69x873 note70x688 note71x503 note72x318 note73x133 note74x961 note75x776 note76x591 note77x406 note78x221 note79x36 note80x864 note81x679 note82x494 note83x309 note84x124 note85x952 note86x767 note87x582 note88x397 note0x212 note1x27 note2x855 note3x670 note4x485 note5x300 note6x115 note7x943 note8x758 note9x573 note10x388 note11x203 note12x18 note13x846 note14x661 note15x476 note16x291 note17x106 note18x934 note19x749 note20x564 note21x379 note22x194 note23x9 note24x837 note25x652 note26x467 note27x282 note28x97 note29x925 note30x740 note31x555 note32x370 note33x185 note34x0 note35x828 note36x643 note37x458 note38x273 note39x88 note40x916 note41x731 note42x546 note43x361 note44x176 note45x1004 note46x819 note47x634 note48x449 note49x264 note50x79 note51x907 note52x722 note53x537 note54x352 note55x167 note56x995 note57x810 note58x625 note59x440 note60x255 note61x70 note62x898 note63x713 note64x528 note65x343 note66x158 note67x986 note68x801 note69x616 note70x431 note71x246 note72x61 note73x889 note74x704 note75x519 note76x334 note77x149 note78x977 note79x792 note80x607 note81x422 note82x237 note83x52 note84x880 note85x695 note86x510 note87x325 note88x140 note0x968 note1x783 note2x598 note3x413 note4x228 note5x43 note6x871 note7x686 note8x501 note9x316 note10x131 note11x959 note12x774 note13x589 note14x404 note15x219 note16x34 note17x862 note18x677 note19x492 note20x307 note21x122 note22x950 note23x765 note24x580 note25x395 note26x210 note27x25 note28x853 note29x668 note30x483 note31x298 note32x113 note33x941 note34x756 note35x571 note36x386 note37x201 note38x16 note39x844 note40x659 note41x474 note42x289 note43x104 note44x932 note45x747 note46x562 note47x377 note48x192 note49x7 note50x835 note51x650 note52x465 note53x280 note54x95 note55x923 note56x738 note57x553 note58x368 note59x183 note60x1011 note61x826 note62x641 note63x456 note64x271 note65x86 note66x914 note67x729 note68x544 note69x359 note70x174 note71x1002 note72x817 note73x632 note74x447 note75x262 note76x77 note77x905 note78x720 note79x535 note80x350 note81x165 note82x993 note83x808 note84x623 note85x438 note86x253 note87x68 note88x896 note0x711 note1x526 note2x341 note3x156 note4x984 note5x799 note6x614 note7x429 note8x244 note9x59 note10x887 note11x702 note12x517 note13x332 note14x147 note15x975 note16x790 note17x605 note18x420 note19x235 note20x50 note21x878 note22x693 note23x508 note24x323 note25x138 note26x966 note27x781 note28x596 note29x411 note30x226 note31x41 note32x869 note33x684 note34x499 note35x314 note36x129 note37x957 note38x772 note39x587 note40x402 note41x217 note42x32 note43x860 note44x675 note45x490 note46x305 note47x120 note48x948 note49x763 note50x578 note51x393 note52x208 note53x23 note54x851 note55x666 note56x481 note57x296 note58x111 note59x939 note60x754 note61x569 note62x384 note63x199 note64x14 note65x842 note66x657 note67x472 note68x287 note69x102 note70x930 note71x745 note72x560 note73x375 note74x190 note75x5 note76x833 note77x648 note78x463 note79x278 note80x93 note81x921 note82x736 note83x551 note84x366 note85x181 note86x1009 note87x824 note88x639 note0x454 note1x269 note2x84 note3x912 note4x727 note5x542 note6x357 note7x172 note8x1000 note9x815 note10x630 note11x445 note12x260 note13x75 note14x903 note15x718 note16x533 note17x348 note18x163 note19x991 note20x806 note21x621 note22x436 note23x251 note24x66 note25x894 note26x709 note27x524 note28x339 note29x154 note30x982 note31x797 note32x612 note33x427 note34x242 note35x57 note36x885 note37x700 note38x515 note39x330 note40x145 note41x973 note42x788 note43x603 note44x418 note45x233 note46x48 note47x876 note48x691 note49x506 note50x321 note51x136 note52x964 note53x779 note54x594 note55x409 note56x224 note57x39 note58x867 note59x682 note60x497 note61x312 note62x127 note63x955 note64x770 note65x585 note66x400 note67x215 note68x30 note69x858 note70x673 note71x488 note72x303 note73x118 note74x946 note75x761 note76x576 note77x391 note78x206 note79x21 note80x849 note81x664 note82x479 note83x294 note84x109 note85x937 note86x752 note87x567 note88x382 note0x197 note1x12 note2x840 note3x655 note4x470 note5x285 note6x100 note7x928 note8x743 note9x558 note10x373 note11x188 note12x3 note13x831 note14x646 note15x461 note16x276 note17x91 note18x919 note19x734 note20x549 note21x364 note22x179 note23x1007 note24x822 note25x637 note26x452 note27x267 note28x82 note29x910 note30x725 note31x540 note32x355 note33x170 note34x998 note35x813 note36x628 note37x443 note38x258 note39x73 note40x901 note41x716 note42x531 note43x346 note44x161 note45x989 note46x804 note47x619 note48x434 note49x249 note50x64 note51x892 note52x707 note53x522 note54x337 note55x152 note56x980 note57x795 note58x610 note59x425 note60x240 note61x55 note62x883 note63x698 note64x513 note65x328 note66x143 note67x971 note68x786 note69x601 note70x416 note71x231 note72x46 note73x874 note74x689 note75x504 note76x319 note77x134 note78x962 note79x777 note80x592 note81x407 note82x222 note83x37 note84x865 note85x680 note86x495 note87x310 note88x125 note0x953 note1x768 note2x583 note3x398 note4x213 note5x28 note6x856 note7x671 note8x486 note9x301 note10x116 note11x944 note12x759 note13x574 note14x389 note15x204 note16x19 note17x847 note18x662 note19x477 note20x292 note21x107 note22x935 note23x750 note24x565 note25x380 note26x195 note27x10 note28x838 note29x653 note30x468 note31x283 note32x98 note33x926 note34x741 note35x556 note36x371 note37x186 note38x1 note39x829 note40x644 note41x459 note42x274 note43x89 note44x917 note45x732 note46x547 note47x362 note48x177 note49x1005 note50x820 note51x635 note52x450 note53x265 note54x80 note55x908 note56x723 note57x538 note58x353 note59x168 note60x996 note61x811 note62x626 note63x441 note64x256 note65x71 note66x899 note67x714 note68x529 note69x344 note70x159 note71x987 note72x802 note73x617 note74x432 note75x247"}, {"role": "user", "content": "What is the first note?"}, {"role": "assistant", "content": "The first note is **note0x0**."}, {"role": "user", "content": "And the second one?"}], "max_tokens": 48, "temperature": 0.0, "draft": true, "chat_template_kwargs": {"enable_thinking": false}}, "status": 200, "response": {"id": "chatcmpl-fd6899ec32eae079ec10362c3a655592", "object": "chat.completion", "created": 1793474194, "model": "flashnext", "choices": [{"index": 0, "message": {"role": "assistant", "content": "The second note is **note1x828**."}, "finish_reason": "stop"}], "usage": {"prompt_tokens": 10248, "completion_tokens": 13, "total_tokens": 10261, "prompt_tokens_details": {"cached_tokens": 0}, "completion_tokens_details": {"reasoning_tokens": 0}}, "exact_mode": "exact", "tensorfold": {"enable_thinking": false, "reasoning_effort": "none", "engine": "lanes", "tokens_per_second": 37.712303889616535, "seconds": 0.318198539, "prefill_seconds": 18.770189031, "prefill_widths": [], "prefill_raised": [], "time_to_first_token": 18.771603808, "sampling": "greedy", "drafts": true, "token_sha": "7e4bf5aba972", "token_sha256": "7e4bf5aba9727191d8505e971356abb0485616846741651f36545f4775ef04fc", "min_rows": 5}, "speculative": {"rounds": 3, "drafted": 16, "accepted": 9, "acceptance_rate": 0.5625, "tokens_per_round": 4.333333333333333}}, "seconds": 19.090394020080566} +{"url": "http://127.0.0.1:30461/v1/chat/completions", "request": {"model": "flashnext", "messages": [{"role": "system", "content": "You are a careful assistant. 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note2x386 note3x201 note4x16 note5x844 note6x659 note7x474 note8x289 note9x104 note10x932 note11x747 note12x562 note13x377 note14x192 note15x7 note16x835 note17x650 note18x465 note19x280 note20x95 note21x923 note22x738 note23x553 note24x368 note25x183 note26x1011 note27x826 note28x641 note29x456 note30x271 note31x86 note32x914 note33x729 note34x544 note35x359 note36x174 note37x1002 note38x817 note39x632 note40x447 note41x262 note42x77 note43x905 note44x720 note45x535 note46x350 note47x165 note48x993 note49x808 note50x623 note51x438 note52x253 note53x68 note54x896 note55x711 note56x526 note57x341 note58x156 note59x984 note60x799 note61x614 note62x429 note63x244 note64x59 note65x887 note66x702 note67x517 note68x332 note69x147 note70x975 note71x790 note72x605 note73x420 note74x235 note75x50 note76x878 note77x693 note78x508 note79x323 note80x138 note81x966 note82x781 note83x596 note84x411 note85x226 note86x41 note87x869 note88x684 note0x499 note1x314 note2x129 note3x957 note4x772 note5x587 note6x402 note7x217 note8x32 note9x860 note10x675 note11x490 note12x305 note13x120 note14x948 note15x763 note16x578 note17x393 note18x208 note19x23 note20x851 note21x666 note22x481 note23x296 note24x111 note25x939 note26x754 note27x569 note28x384 note29x199 note30x14 note31x842 note32x657 note33x472 note34x287 note35x102 note36x930 note37x745 note38x560 note39x375 note40x190 note41x5 note42x833 note43x648 note44x463 note45x278 note46x93 note47x921 note48x736 note49x551 note50x366 note51x181 note52x1009 note53x824 note54x639 note55x454 note56x269 note57x84 note58x912 note59x727 note60x542 note61x357 note62x172 note63x1000 note64x815 note65x630 note66x445 note67x260 note68x75 note69x903 note70x718 note71x533 note72x348 note73x163 note74x991 note75x806 note76x621 note77x436 note78x251 note79x66 note80x894 note81x709 note82x524 note83x339 note84x154 note85x982 note86x797 note87x612 note88x427 note0x242 note1x57 note2x885 note3x700 note4x515 note5x330 note6x145 note7x973 note8x788 note9x603 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"reasoning_effort": "none", "engine": "lanes", "tokens_per_second": 36.129063622753556, "seconds": 0.276785474, "prefill_seconds": 18.553155, "prefill_widths": [], "prefill_raised": [], "time_to_first_token": 18.554365776, "sampling": "greedy", "drafts": false, "token_sha": "eea964a89e62", "token_sha256": "eea964a89e62f6e2059b2da5a676da894801486bd2b3f05aad65bbf32aacef96", "min_rows": 1}, "speculative": {"rounds": 10, "drafted": 0, "accepted": 0, "acceptance_rate": 0.0, "tokens_per_round": 1.1}}, "seconds": 18.83234143257141} +{"url": "http://127.0.0.1:30461/v1/chat/completions", "request": {"model": "flashnext", "messages": [{"role": "system", "content": "You are a careful assistant. 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note13x619 note14x434 note15x249 note16x64 note17x892 note18x707 note19x522 note20x337 note21x152 note22x980 note23x795 note24x610 note25x425 note26x240 note27x55 note28x883 note29x698 note30x513 note31x328 note32x143 note33x971 note34x786 note35x601 note36x416 note37x231 note38x46 note39x874 note40x689 note41x504 note42x319 note43x134 note44x962 note45x777 note46x592 note47x407 note48x222 note49x37 note50x865 note51x680 note52x495 note53x310 note54x125 note55x953 note56x768 note57x583 note58x398 note59x213 note60x28 note61x856 note62x671 note63x486 note64x301 note65x116 note66x944 note67x759 note68x574 note69x389 note70x204 note71x19 note72x847 note73x662 note74x477 note75x292 note76x107 note77x935 note78x750 note79x565 note80x380 note81x195 note82x10 note83x838 note84x653 note85x468 note86x283 note87x98 note88x926 note0x741 note1x556 note2x371 note3x186 note4x1 note5x829 note6x644 note7x459 note8x274 note9x89 note10x917 note11x732 note12x547 note13x362 note14x177 note15x1005 note16x820 note17x635 note18x450 note19x265 note20x80 note21x908 note22x723 note23x538 note24x353 note25x168 note26x996 note27x811 note28x626 note29x441 note30x256 note31x71 note32x899 note33x714 note34x529 note35x344 note36x159 note37x987 note38x802 note39x617 note40x432 note41x247 note42x62 note43x890 note44x705 note45x520 note46x335 note47x150 note48x978 note49x793 note50x608 note51x423 note52x238 note53x53 note54x881 note55x696 note56x511 note57x326 note58x141 note59x969 note60x784 note61x599 note62x414 note63x229 note64x44 note65x872 note66x687 note67x502 note68x317 note69x132 note70x960 note71x775 note72x590 note73x405 note74x220 note75x35 note76x863 note77x678 note78x493 note79x308 note80x123 note81x951 note82x766 note83x581 note84x396 note85x211 note86x26 note87x854 note88x669 note0x484 note1x299 note2x114 note3x942 note4x757 note5x572 note6x387 note7x202 note8x17 note9x845 note10x660 note11x475 note12x290 note13x105 note14x933 note15x748 note16x563 note17x378 note18x193 note19x8 note20x836 note21x651 note22x466 note23x281 note24x96 note25x924 note26x739 note27x554 note28x369 note29x184 note30x1012 note31x827 note32x642 note33x457 note34x272 note35x87 note36x915 note37x730 note38x545 note39x360 note40x175 note41x1003 note42x818 note43x633 note44x448 note45x263 note46x78 note47x906 note48x721 note49x536 note50x351 note51x166 note52x994 note53x809 note54x624 note55x439 note56x254 note57x69 note58x897 note59x712 note60x527 note61x342 note62x157 note63x985 note64x800 note65x615 note66x430 note67x245 note68x60 note69x888 note70x703 note71x518 note72x333 note73x148 note74x976 note75x791 note76x606 note77x421 note78x236 note79x51 note80x879 note81x694 note82x509 note83x324 note84x139 note85x967 note86x782 note87x597 note88x412 note0x227 note1x42 note2x870 note3x685 note4x500 note5x315 note6x130 note7x958 note8x773 note9x588 note10x403 note11x218 note12x33 note13x861 note14x676 note15x491 note16x306 note17x121 note18x949 note19x764 note20x579 note21x394 note22x209 note23x24 note24x852 note25x667 note26x482 note27x297 note28x112 note29x940 note30x755 note31x570 note32x385 note33x200 note34x15 note35x843 note36x658 note37x473 note38x288 note39x103 note40x931 note41x746 note42x561 note43x376 note44x191 note45x6 note46x834 note47x649 note48x464 note49x279 note50x94 note51x922 note52x737 note53x552 note54x367 note55x182 note56x1010 note57x825 note58x640 note59x455 note60x270 note61x85 note62x913 note63x728 note64x543 note65x358 note66x173 note67x1001 note68x816 note69x631 note70x446 note71x261 note72x76 note73x904 note74x719 note75x534 note76x349 note77x164 note78x992 note79x807 note80x622 note81x437 note82x252 note83x67 note84x895 note85x710 note86x525 note87x340 note88x155 note0x983 note1x798 note2x613 note3x428 note4x243 note5x58 note6x886 note7x701 note8x516 note9x331 note10x146 note11x974 note12x789 note13x604 note14x419 note15x234 note16x49 note17x877 note18x692 note19x507 note20x322 note21x137 note22x965 note23x780 note24x595 note25x410 note26x225 note27x40 note28x868 note29x683 note30x498 note31x313 note32x128 note33x956 note34x771 note35x586 note36x401 note37x216 note38x31 note39x859 note40x674 note41x489 note42x304 note43x119 note44x947 note45x762 note46x577 note47x392 note48x207 note49x22 note50x850 note51x665 note52x480 note53x295 note54x110 note55x938 note56x753 note57x568 note58x383 note59x198 note60x13 note61x841 note62x656 note63x471 note64x286 note65x101 note66x929 note67x744 note68x559 note69x374 note70x189 note71x4 note72x832 note73x647 note74x462 note75x277 note76x92 note77x920 note78x735 note79x550 note80x365 note81x180 note82x1008 note83x823 note84x638 note85x453 note86x268 note87x83 note88x911 note0x726 note1x541 note2x356 note3x171 note4x999 note5x814 note6x629 note7x444 note8x259 note9x74 note10x902 note11x717 note12x532 note13x347 note14x162 note15x990 note16x805 note17x620 note18x435 note19x250 note20x65 note21x893 note22x708 note23x523 note24x338 note25x153 note26x981 note27x796 note28x611 note29x426 note30x241 note31x56 note32x884 note33x699 note34x514 note35x329 note36x144 note37x972 note38x787 note39x602 note40x417 note41x232 note42x47 note43x875 note44x690 note45x505 note46x320 note47x135 note48x963 note49x778 note50x593 note51x408 note52x223 note53x38 note54x866 note55x681 note56x496 note57x311 note58x126 note59x954 note60x769 note61x584 note62x399 note63x214 note64x29 note65x857 note66x672 note67x487 note68x302 note69x117 note70x945 note71x760 note72x575 note73x390 note74x205 note75x20 note76x848 note77x663 note78x478 note79x293 note80x108 note81x936 note82x751 note83x566 note84x381 note85x196 note86x11 note87x839 note88x654 note0x469 note1x284 note2x99 note3x927 note4x742 note5x557 note6x372 note7x187 note8x2 note9x830 note10x645 note11x460 note12x275 note13x90 note14x918 note15x733 note16x548 note17x363 note18x178 note19x1006 note20x821 note21x636 note22x451 note23x266 note24x81 note25x909 note26x724 note27x539 note28x354 note29x169 note30x997 note31x812 note32x627 note33x442 note34x257 note35x72 note36x900 note37x715 note38x530 note39x345 note40x160 note41x988 note42x803 note43x618 note44x433 note45x248 note46x63 note47x891 note48x706 note49x521 note50x336 note51x151 note52x979 note53x794 note54x609 note55x424 note56x239 note57x54 note58x882 note59x697 note60x512 note61x327 note62x142 note63x970 note64x785 note65x600 note66x415 note67x230 note68x45 note69x873 note70x688 note71x503 note72x318 note73x133 note74x961 note75x776 note76x591 note77x406 note78x221 note79x36 note80x864 note81x679 note82x494 note83x309 note84x124 note85x952 note86x767 note87x582 note88x397 note0x212 note1x27 note2x855 note3x670 note4x485 note5x300 note6x115 note7x943 note8x758 note9x573 note10x388 note11x203 note12x18 note13x846 note14x661 note15x476 note16x291 note17x106 note18x934 note19x749 note20x564 note21x379 note22x194 note23x9 note24x837 note25x652 note26x467 note27x282 note28x97 note29x925 note30x740 note31x555 note32x370 note33x185 note34x0 note35x828 note36x643 note37x458 note38x273 note39x88 note40x916 note41x731 note42x546 note43x361 note44x176 note45x1004 note46x819 note47x634 note48x449 note49x264 note50x79 note51x907 note52x722 note53x537 note54x352 note55x167 note56x995 note57x810 note58x625 note59x440 note60x255 note61x70 note62x898 note63x713 note64x528 note65x343 note66x158 note67x986 note68x801 note69x616 note70x431 note71x246 note72x61 note73x889 note74x704 note75x519 note76x334 note77x149 note78x977 note79x792 note80x607 note81x422 note82x237 note83x52 note84x880 note85x695 note86x510 note87x325 note88x140 note0x968 note1x783 note2x598 note3x413 note4x228 note5x43 note6x871 note7x686 note8x501 note9x316 note10x131 note11x959 note12x774 note13x589 note14x404 note15x219 note16x34 note17x862 note18x677 note19x492 note20x307 note21x122 note22x950 note23x765 note24x580 note25x395 note26x210 note27x25 note28x853 note29x668 note30x483 note31x298 note32x113 note33x941 note34x756 note35x571 note36x386 note37x201 note38x16 note39x844 note40x659 note41x474 note42x289 note43x104 note44x932 note45x747 note46x562 note47x377 note48x192 note49x7 note50x835 note51x650 note52x465 note53x280 note54x95 note55x923 note56x738 note57x553 note58x368 note59x183 note60x1011 note61x826 note62x641 note63x456 note64x271 note65x86 note66x914 note67x729 note68x544 note69x359 note70x174 note71x1002 note72x817 note73x632 note74x447 note75x262 note76x77 note77x905 note78x720 note79x535 note80x350 note81x165 note82x993 note83x808 note84x623 note85x438 note86x253 note87x68 note88x896 note0x711 note1x526 note2x341 note3x156 note4x984 note5x799 note6x614 note7x429 note8x244 note9x59 note10x887 note11x702 note12x517 note13x332 note14x147 note15x975 note16x790 note17x605 note18x420 note19x235 note20x50 note21x878 note22x693 note23x508 note24x323 note25x138 note26x966 note27x781 note28x596 note29x411 note30x226 note31x41 note32x869 note33x684 note34x499 note35x314 note36x129 note37x957 note38x772 note39x587 note40x402 note41x217 note42x32 note43x860 note44x675 note45x490 note46x305 note47x120 note48x948 note49x763 note50x578 note51x393 note52x208 note53x23 note54x851 note55x666 note56x481 note57x296 note58x111 note59x939 note60x754 note61x569 note62x384 note63x199 note64x14 note65x842 note66x657 note67x472 note68x287 note69x102 note70x930 note71x745 note72x560 note73x375 note74x190 note75x5 note76x833 note77x648 note78x463 note79x278 note80x93 note81x921 note82x736 note83x551 note84x366 note85x181 note86x1009 note87x824 note88x639 note0x454 note1x269 note2x84 note3x912 note4x727 note5x542 note6x357 note7x172 note8x1000 note9x815 note10x630 note11x445 note12x260 note13x75 note14x903 note15x718 note16x533 note17x348 note18x163 note19x991 note20x806 note21x621 note22x436 note23x251 note24x66 note25x894 note26x709 note27x524 note28x339 note29x154 note30x982 note31x797 note32x612 note33x427 note34x242 note35x57 note36x885 note37x700 note38x515 note39x330 note40x145 note41x973 note42x788 note43x603 note44x418 note45x233 note46x48 note47x876 note48x691 note49x506 note50x321 note51x136 note52x964 note53x779 note54x594 note55x409 note56x224 note57x39 note58x867 note59x682 note60x497 note61x312 note62x127 note63x955 note64x770 note65x585 note66x400 note67x215 note68x30 note69x858 note70x673 note71x488 note72x303 note73x118 note74x946 note75x761 note76x576 note77x391 note78x206 note79x21 note80x849 note81x664 note82x479 note83x294 note84x109 note85x937 note86x752 note87x567 note88x382 note0x197 note1x12 note2x840 note3x655 note4x470 note5x285 note6x100 note7x928 note8x743 note9x558 note10x373 note11x188 note12x3 note13x831 note14x646 note15x461 note16x276 note17x91 note18x919 note19x734 note20x549 note21x364 note22x179 note23x1007 note24x822 note25x637 note26x452 note27x267 note28x82 note29x910 note30x725 note31x540 note32x355 note33x170 note34x998 note35x813 note36x628 note37x443 note38x258 note39x73 note40x901 note41x716 note42x531 note43x346 note44x161 note45x989 note46x804 note47x619 note48x434 note49x249 note50x64 note51x892 note52x707 note53x522 note54x337 note55x152 note56x980 note57x795 note58x610 note59x425 note60x240 note61x55 note62x883 note63x698 note64x513 note65x328 note66x143 note67x971 note68x786 note69x601 note70x416 note71x231 note72x46 note73x874 note74x689 note75x504 note76x319 note77x134 note78x962 note79x777 note80x592 note81x407 note82x222 note83x37 note84x865 note85x680 note86x495 note87x310 note88x125 note0x953 note1x768 note2x583 note3x398 note4x213 note5x28 note6x856 note7x671 note8x486 note9x301 note10x116 note11x944 note12x759 note13x574 note14x389 note15x204 note16x19 note17x847 note18x662 note19x477 note20x292 note21x107 note22x935 note23x750 note24x565 note25x380 note26x195 note27x10 note28x838 note29x653 note30x468 note31x283 note32x98 note33x926 note34x741 note35x556 note36x371 note37x186 note38x1 note39x829 note40x644 note41x459 note42x274 note43x89 note44x917 note45x732 note46x547 note47x362 note48x177 note49x1005 note50x820 note51x635 note52x450 note53x265 note54x80 note55x908 note56x723 note57x538 note58x353 note59x168 note60x996 note61x811 note62x626 note63x441 note64x256 note65x71 note66x899 note67x714 note68x529 note69x344 note70x159 note71x987 note72x802 note73x617 note74x432 note75x247"}, {"role": "user", "content": "What is the first note?"}, {"role": "assistant", "content": "The first note is **note0x0**."}, {"role": "user", "content": "And the second one?"}], "max_tokens": 48, "temperature": 0.0, "draft": false, "chat_template_kwargs": {"enable_thinking": false}}, "status": 200, "response": {"id": "chatcmpl-f84d708b00f6047db996fbbff37e91a8", "object": "chat.completion", "created": 1793474232, "model": "flashnext", "choices": [{"index": 0, "message": {"role": "assistant", "content": "The second note is **note1x828**."}, "finish_reason": "stop"}], "usage": {"prompt_tokens": 10248, "completion_tokens": 13, "total_tokens": 10261, "prompt_tokens_details": {"cached_tokens": 0}, "completion_tokens_details": {"reasoning_tokens": 0}}, "exact_mode": "exact", "tensorfold": {"enable_thinking": false, "reasoning_effort": "none", "engine": "lanes", "tokens_per_second": 36.09438797958703, "seconds": 0.332461656, "prefill_seconds": 18.646138248, "prefill_widths": [], "prefill_raised": [], "time_to_first_token": 18.647147256, "sampling": "greedy", "drafts": false, "token_sha": "7e4bf5aba972", "token_sha256": "7e4bf5aba9727191d8505e971356abb0485616846741651f36545f4775ef04fc", "min_rows": 1}, "speculative": {"rounds": 12, "drafted": 0, "accepted": 0, "acceptance_rate": 0.0, "tokens_per_round": 1.0833333333333333}}, "seconds": 18.98059344291687} +{"url": "http://127.0.0.1:30461/v1/chat/completions", "request": {"model": "flashnext", "messages": [{"role": "system", "content": "You are a careful assistant. 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note2x386 note3x201 note4x16 note5x844 note6x659 note7x474 note8x289 note9x104 note10x932 note11x747 note12x562 note13x377 note14x192 note15x7 note16x835 note17x650 note18x465 note19x280 note20x95 note21x923 note22x738 note23x553 note24x368 note25x183 note26x1011 note27x826 note28x641 note29x456 note30x271 note31x86 note32x914 note33x729 note34x544 note35x359 note36x174 note37x1002 note38x817 note39x632 note40x447 note41x262 note42x77 note43x905 note44x720 note45x535 note46x350 note47x165 note48x993 note49x808 note50x623 note51x438 note52x253 note53x68 note54x896 note55x711 note56x526 note57x341 note58x156 note59x984 note60x799 note61x614 note62x429 note63x244 note64x59 note65x887 note66x702 note67x517 note68x332 note69x147 note70x975 note71x790 note72x605 note73x420 note74x235 note75x50 note76x878 note77x693 note78x508 note79x323 note80x138 note81x966 note82x781 note83x596 note84x411 note85x226 note86x41 note87x869 note88x684 note0x499 note1x314 note2x129 note3x957 note4x772 note5x587 note6x402 note7x217 note8x32 note9x860 note10x675 note11x490 note12x305 note13x120 note14x948 note15x763 note16x578 note17x393 note18x208 note19x23 note20x851 note21x666 note22x481 note23x296 note24x111 note25x939 note26x754 note27x569 note28x384 note29x199 note30x14 note31x842 note32x657 note33x472 note34x287 note35x102 note36x930 note37x745 note38x560 note39x375 note40x190 note41x5 note42x833 note43x648 note44x463 note45x278 note46x93 note47x921 note48x736 note49x551 note50x366 note51x181 note52x1009 note53x824 note54x639 note55x454 note56x269 note57x84 note58x912 note59x727 note60x542 note61x357 note62x172 note63x1000 note64x815 note65x630 note66x445 note67x260 note68x75 note69x903 note70x718 note71x533 note72x348 note73x163 note74x991 note75x806 note76x621 note77x436 note78x251 note79x66 note80x894 note81x709 note82x524 note83x339 note84x154 note85x982 note86x797 note87x612 note88x427 note0x242 note1x57 note2x885 note3x700 note4x515 note5x330 note6x145 note7x973 note8x788 note9x603 note10x418 note11x233 note12x48 note13x876 note14x691 note15x506 note16x321 note17x136 note18x964 note19x779 note20x594 note21x409 note22x224 note23x39 note24x867 note25x682 note26x497 note27x312 note28x127 note29x955 note30x770 note31x585 note32x400 note33x215 note34x30 note35x858 note36x673 note37x488 note38x303 note39x118 note40x946 note41x761 note42x576 note43x391 note44x206 note45x21 note46x849 note47x664 note48x479 note49x294 note50x109 note51x937 note52x752 note53x567 note54x382 note55x197 note56x12 note57x840 note58x655 note59x470 note60x285 note61x100 note62x928 note63x743 note64x558 note65x373 note66x188 note67x3 note68x831 note69x646 note70x461 note71x276 note72x91 note73x919 note74x734 note75x549 note76x364 note77x179 note78x1007 note79x822 note80x637 note81x452 note82x267 note83x82 note84x910 note85x725 note86x540 note87x355 note88x170 note0x998 note1x813 note2x628 note3x443 note4x258 note5x73 note6x901 note7x716 note8x531 note9x346 note10x161 note11x989 note12x804 note13x619 note14x434 note15x249 note16x64 note17x892 note18x707 note19x522 note20x337 note21x152 note22x980 note23x795 note24x610 note25x425 note26x240 note27x55 note28x883 note29x698 note30x513 note31x328 note32x143 note33x971 note34x786 note35x601 note36x416 note37x231 note38x46 note39x874 note40x689 note41x504 note42x319 note43x134 note44x962 note45x777 note46x592 note47x407 note48x222 note49x37 note50x865 note51x680 note52x495 note53x310 note54x125 note55x953 note56x768 note57x583 note58x398 note59x213 note60x28 note61x856 note62x671 note63x486 note64x301 note65x116 note66x944 note67x759 note68x574 note69x389 note70x204 note71x19 note72x847 note73x662 note74x477 note75x292 note76x107 note77x935 note78x750 note79x565 note80x380 note81x195 note82x10 note83x838 note84x653 note85x468 note86x283 note87x98 note88x926 note0x741 note1x556 note2x371 note3x186 note4x1 note5x829 note6x644 note7x459 note8x274 note9x89 note10x917 note11x732 note12x547 note13x362 note14x177 note15x1005 note16x820 note17x635 note18x450 note19x265 note20x80 note21x908 note22x723 note23x538 note24x353 note25x168 note26x996 note27x811 note28x626 note29x441 note30x256 note31x71 note32x899 note33x714 note34x529 note35x344 note36x159 note37x987 note38x802 note39x617 note40x432 note41x247 note42x62 note43x890 note44x705 note45x520 note46x335 note47x150 note48x978 note49x793 note50x608 note51x423 note52x238 note53x53 note54x881 note55x696 note56x511 note57x326 note58x141 note59x969 note60x784 note61x599 note62x414 note63x229 note64x44 note65x872 note66x687 note67x502 note68x317 note69x132 note70x960 note71x775 note72x590 note73x405 note74x220 note75x35 note76x863 note77x678 note78x493 note79x308 note80x123 note81x951 note82x766 note83x581 note84x396 note85x211 note86x26 note87x854 note88x669 note0x484 note1x299 note2x114 note3x942 note4x757 note5x572 note6x387 note7x202 note8x17 note9x845 note10x660 note11x475 note12x290 note13x105 note14x933 note15x748 note16x563 note17x378 note18x193 note19x8 note20x836 note21x651 note22x466 note23x281 note24x96 note25x924 note26x739 note27x554 note28x369 note29x184 note30x1012 note31x827 note32x642 note33x457 note34x272 note35x87 note36x915 note37x730 note38x545 note39x360 note40x175 note41x1003 note42x818 note43x633 note44x448 note45x263 note46x78 note47x906 note48x721 note49x536 note50x351 note51x166 note52x994 note53x809 note54x624 note55x439 note56x254 note57x69 note58x897 note59x712 note60x527 note61x342 note62x157 note63x985 note64x800 note65x615 note66x430 note67x245 note68x60 note69x888 note70x703 note71x518 note72x333 note73x148 note74x976 note75x791 note76x606 note77x421 note78x236 note79x51 note80x879 note81x694 note82x509 note83x324 note84x139 note85x967 note86x782 note87x597 note88x412 note0x227 note1x42 note2x870 note3x685 note4x500 note5x315 note6x130 note7x958 note8x773 note9x588 note10x403 note11x218 note12x33 note13x861 note14x676 note15x491 note16x306 note17x121 note18x949 note19x764 note20x579 note21x394 note22x209 note23x24 note24x852 note25x667 note26x482 note27x297 note28x112 note29x940 note30x755 note31x570 note32x385 note33x200 note34x15 note35x843 note36x658 note37x473 note38x288 note39x103 note40x931 note41x746 note42x561 note43x376 note44x191 note45x6 note46x834 note47x649 note48x464 note49x279 note50x94 note51x922 note52x737 note53x552 note54x367 note55x182 note56x1010 note57x825 note58x640 note59x455 note60x270 note61x85 note62x913 note63x728 note64x543 note65x358 note66x173 note67x1001 note68x816 note69x631 note70x446 note71x261 note72x76 note73x904 note74x719 note75x534 note76x349 note77x164 note78x992 note79x807 note80x622 note81x437 note82x252 note83x67 note84x895 note85x710 note86x525 note87x340 note88x155 note0x983 note1x798 note2x613 note3x428 note4x243 note5x58 note6x886 note7x701 note8x516 note9x331 note10x146 note11x974 note12x789 note13x604 note14x419 note15x234 note16x49 note17x877 note18x692 note19x507 note20x322 note21x137 note22x965 note23x780 note24x595 note25x410 note26x225 note27x40 note28x868 note29x683 note30x498 note31x313 note32x128 note33x956 note34x771 note35x586 note36x401 note37x216 note38x31 note39x859 note40x674 note41x489 note42x304 note43x119 note44x947 note45x762 note46x577 note47x392 note48x207 note49x22 note50x850 note51x665 note52x480 note53x295 note54x110 note55x938 note56x753 note57x568 note58x383 note59x198 note60x13 note61x841 note62x656 note63x471 note64x286 note65x101 note66x929 note67x744 note68x559 note69x374 note70x189 note71x4 note72x832 note73x647 note74x462 note75x277 note76x92 note77x920 note78x735 note79x550 note80x365 note81x180 note82x1008 note83x823 note84x638 note85x453 note86x268 note87x83 note88x911 note0x726 note1x541 note2x356 note3x171 note4x999 note5x814 note6x629 note7x444 note8x259 note9x74 note10x902 note11x717 note12x532 note13x347 note14x162 note15x990 note16x805 note17x620 note18x435 note19x250 note20x65 note21x893 note22x708 note23x523 note24x338 note25x153 note26x981 note27x796 note28x611 note29x426 note30x241 note31x56 note32x884 note33x699 note34x514 note35x329 note36x144 note37x972 note38x787 note39x602 note40x417 note41x232 note42x47 note43x875 note44x690 note45x505 note46x320 note47x135 note48x963 note49x778 note50x593 note51x408 note52x223 note53x38 note54x866 note55x681 note56x496 note57x311 note58x126 note59x954 note60x769 note61x584 note62x399 note63x214 note64x29 note65x857 note66x672 note67x487 note68x302 note69x117 note70x945 note71x760 note72x575 note73x390 note74x205 note75x20 note76x848 note77x663 note78x478 note79x293 note80x108 note81x936 note82x751 note83x566 note84x381 note85x196 note86x11 note87x839 note88x654 note0x469 note1x284 note2x99 note3x927 note4x742 note5x557 note6x372 note7x187 note8x2 note9x830 note10x645 note11x460 note12x275 note13x90 note14x918 note15x733 note16x548 note17x363 note18x178 note19x1006 note20x821 note21x636 note22x451 note23x266 note24x81 note25x909 note26x724 note27x539 note28x354 note29x169 note30x997 note31x812 note32x627 note33x442 note34x257 note35x72 note36x900 note37x715 note38x530 note39x345 note40x160 note41x988 note42x803 note43x618 note44x433 note45x248 note46x63 note47x891 note48x706 note49x521 note50x336 note51x151 note52x979 note53x794 note54x609 note55x424 note56x239 note57x54 note58x882 note59x697 note60x512 note61x327 note62x142 note63x970 note64x785 note65x600 note66x415 note67x230 note68x45 note69x873 note70x688 note71x503 note72x318 note73x133 note74x961 note75x776 note76x591 note77x406 note78x221 note79x36 note80x864 note81x679 note82x494 note83x309 note84x124 note85x952 note86x767 note87x582 note88x397 note0x212 note1x27 note2x855 note3x670 note4x485 note5x300 note6x115 note7x943 note8x758 note9x573 note10x388 note11x203 note12x18 note13x846 note14x661 note15x476 note16x291 note17x106 note18x934 note19x749 note20x564 note21x379 note22x194 note23x9 note24x837 note25x652 note26x467 note27x282 note28x97 note29x925 note30x740 note31x555 note32x370 note33x185 note34x0 note35x828 note36x643 note37x458 note38x273 note39x88 note40x916 note41x731 note42x546 note43x361 note44x176 note45x1004 note46x819 note47x634 note48x449 note49x264 note50x79 note51x907 note52x722 note53x537 note54x352 note55x167 note56x995 note57x810 note58x625 note59x440 note60x255 note61x70 note62x898 note63x713 note64x528 note65x343 note66x158 note67x986 note68x801 note69x616 note70x431 note71x246 note72x61 note73x889 note74x704 note75x519 note76x334 note77x149 note78x977 note79x792 note80x607 note81x422 note82x237 note83x52 note84x880 note85x695 note86x510 note87x325 note88x140 note0x968 note1x783 note2x598 note3x413 note4x228 note5x43 note6x871 note7x686 note8x501 note9x316 note10x131 note11x959 note12x774 note13x589 note14x404 note15x219 note16x34 note17x862 note18x677 note19x492 note20x307 note21x122 note22x950 note23x765 note24x580 note25x395 note26x210 note27x25 note28x853 note29x668 note30x483 note31x298 note32x113 note33x941 note34x756 note35x571 note36x386 note37x201 note38x16 note39x844 note40x659 note41x474 note42x289 note43x104 note44x932 note45x747 note46x562 note47x377 note48x192 note49x7 note50x835 note51x650 note52x465 note53x280 note54x95 note55x923 note56x738 note57x553 note58x368 note59x183 note60x1011 note61x826 note62x641 note63x456 note64x271 note65x86 note66x914 note67x729 note68x544 note69x359 note70x174 note71x1002 note72x817 note73x632 note74x447 note75x262 note76x77 note77x905 note78x720 note79x535 note80x350 note81x165 note82x993 note83x808 note84x623 note85x438 note86x253 note87x68 note88x896 note0x711 note1x526 note2x341 note3x156 note4x984 note5x799 note6x614 note7x429 note8x244 note9x59 note10x887 note11x702 note12x517 note13x332 note14x147 note15x975 note16x790 note17x605 note18x420 note19x235 note20x50 note21x878 note22x693 note23x508 note24x323 note25x138 note26x966 note27x781 note28x596 note29x411 note30x226 note31x41 note32x869 note33x684 note34x499 note35x314 note36x129 note37x957 note38x772 note39x587 note40x402 note41x217 note42x32 note43x860 note44x675 note45x490 note46x305 note47x120 note48x948 note49x763 note50x578 note51x393 note52x208 note53x23 note54x851 note55x666 note56x481 note57x296 note58x111 note59x939 note60x754 note61x569 note62x384 note63x199 note64x14 note65x842 note66x657 note67x472 note68x287 note69x102 note70x930 note71x745 note72x560 note73x375 note74x190 note75x5 note76x833 note77x648 note78x463 note79x278 note80x93 note81x921 note82x736 note83x551 note84x366 note85x181 note86x1009 note87x824 note88x639 note0x454 note1x269 note2x84 note3x912 note4x727 note5x542 note6x357 note7x172 note8x1000 note9x815 note10x630 note11x445 note12x260 note13x75 note14x903 note15x718 note16x533 note17x348 note18x163 note19x991 note20x806 note21x621 note22x436 note23x251 note24x66 note25x894 note26x709 note27x524 note28x339 note29x154 note30x982 note31x797 note32x612 note33x427 note34x242 note35x57 note36x885 note37x700 note38x515 note39x330 note40x145 note41x973 note42x788 note43x603 note44x418 note45x233 note46x48 note47x876 note48x691 note49x506 note50x321 note51x136 note52x964 note53x779 note54x594 note55x409 note56x224 note57x39 note58x867 note59x682 note60x497 note61x312 note62x127 note63x955 note64x770 note65x585 note66x400 note67x215 note68x30 note69x858 note70x673 note71x488 note72x303 note73x118 note74x946 note75x761 note76x576 note77x391 note78x206 note79x21 note80x849 note81x664 note82x479 note83x294 note84x109 note85x937 note86x752 note87x567 note88x382 note0x197 note1x12 note2x840 note3x655 note4x470 note5x285 note6x100 note7x928 note8x743 note9x558 note10x373 note11x188 note12x3 note13x831 note14x646 note15x461 note16x276 note17x91 note18x919 note19x734 note20x549 note21x364 note22x179 note23x1007 note24x822 note25x637 note26x452 note27x267 note28x82 note29x910 note30x725 note31x540 note32x355 note33x170 note34x998 note35x813 note36x628 note37x443 note38x258 note39x73 note40x901 note41x716 note42x531 note43x346 note44x161 note45x989 note46x804 note47x619 note48x434 note49x249 note50x64 note51x892 note52x707 note53x522 note54x337 note55x152 note56x980 note57x795 note58x610 note59x425 note60x240 note61x55 note62x883 note63x698 note64x513 note65x328 note66x143 note67x971 note68x786 note69x601 note70x416 note71x231 note72x46 note73x874 note74x689 note75x504 note76x319 note77x134 note78x962 note79x777 note80x592 note81x407 note82x222 note83x37 note84x865 note85x680 note86x495 note87x310 note88x125 note0x953 note1x768 note2x583 note3x398 note4x213 note5x28 note6x856 note7x671 note8x486 note9x301 note10x116 note11x944 note12x759 note13x574 note14x389 note15x204 note16x19 note17x847 note18x662 note19x477 note20x292 note21x107 note22x935 note23x750 note24x565 note25x380 note26x195 note27x10 note28x838 note29x653 note30x468 note31x283 note32x98 note33x926 note34x741 note35x556 note36x371 note37x186 note38x1 note39x829 note40x644 note41x459 note42x274 note43x89 note44x917 note45x732 note46x547 note47x362 note48x177 note49x1005 note50x820 note51x635 note52x450 note53x265 note54x80 note55x908 note56x723 note57x538 note58x353 note59x168 note60x996 note61x811 note62x626 note63x441 note64x256 note65x71 note66x899 note67x714 note68x529 note69x344 note70x159 note71x987 note72x802 note73x617 note74x432 note75x247"}, {"role": "user", "content": "What is the first note?"}, {"role": "assistant", "content": "The first note is **note0x0**."}, {"role": "user", "content": "And the second one?"}, {"role": "assistant", "content": "The second note is **note1x828**."}, {"role": "user", "content": "Is note5x5 listed?"}], "max_tokens": 48, "temperature": 0.0, "draft": false, "chat_template_kwargs": {"enable_thinking": false}}, "status": 200, "response": {"id": "chatcmpl-20fed9a2eebe185e54afb09e3e15ad32", "object": "chat.completion", "created": 1793474251, "model": "flashnext", "choices": [{"index": 0, "message": {"role": "assistant", "content": "No, **note5x5** is not listed in the provided reference notes.\n\nThe list contains notes with hex suffixes (e.g., `note5x88`, `note5x587`, `note5"}, "finish_reason": "length"}], "usage": {"prompt_tokens": 10281, "completion_tokens": 48, "total_tokens": 10329, "prompt_tokens_details": {"cached_tokens": 0}, "completion_tokens_details": {"reasoning_tokens": 0}}, "exact_mode": "exact", "tensorfold": {"enable_thinking": false, "reasoning_effort": "none", "engine": "lanes", "tokens_per_second": 34.722554056559744, "seconds": 1.353587064, "prefill_seconds": 18.706405986, "prefill_widths": [], "prefill_raised": [], "time_to_first_token": 18.707529579, "sampling": "greedy", "drafts": false, "token_sha": "e7287d6bf366", "token_sha256": "e7287d6bf36620acbd71b1537e7b5ea9b239198191676c8c2261aad653c64a81", "min_rows": 1}, "speculative": {"rounds": 47, "drafted": 0, "accepted": 0, "acceptance_rate": 0.0, "tokens_per_round": 1.0212765957446808}}, "seconds": 20.06229329109192} +{"url": "http://127.0.0.1:30461/v1/chat/completions", "request": {"model": "flashnext", "messages": [{"role": "system", "content": "You are a careful assistant. Reference notes: note0x0 note1x828 note2x643 note3x458 note4x273 note5x88 note6x916 note7x731 note8x546 note9x361 note10x176 note11x1004 note12x819 note13x634 note14x449 note15x264 note16x79 note17x907 note18x722 note19x537 note20x352 note21x167 note22x995 note23x810 note24x625 note25x440 note26x255 note27x70 note28x898 note29x713 note30x528 note31x343 note32x158 note33x986 note34x801 note35x616 note36x431 note37x246 note38x61 note39x889 note40x704 note41x519 note42x334 note43x149 note44x977 note45x792 note46x607 note47x422 note48x237 note49x52 note50x880 note51x695 note52x510 note53x325 note54x140 note55x968 note56x783 note57x598 note58x413 note59x228 note60x43 note61x871 note62x686 note63x501 note64x316 note65x131 note66x959 note67x774 note68x589 note69x404 note70x219 note71x34 note72x862 note73x677 note74x492 note75x307 note76x122 note77x950 note78x765 note79x580 note80x395 note81x210 note82x25 note83x853 note84x668 note85x483 note86x298 note87x113 note88x941 note0x756 note1x571 note2x386 note3x201 note4x16 note5x844 note6x659 note7x474 note8x289 note9x104 note10x932 note11x747 note12x562 note13x377 note14x192 note15x7 note16x835 note17x650 note18x465 note19x280 note20x95 note21x923 note22x738 note23x553 note24x368 note25x183 note26x1011 note27x826 note28x641 note29x456 note30x271 note31x86 note32x914 note33x729 note34x544 note35x359 note36x174 note37x1002 note38x817 note39x632 note40x447 note41x262 note42x77 note43x905 note44x720 note45x535 note46x350 note47x165 note48x993 note49x808 note50x623 note51x438 note52x253 note53x68 note54x896 note55x711 note56x526 note57x341 note58x156 note59x984 note60x799 note61x614 note62x429 note63x244 note64x59 note65x887 note66x702 note67x517 note68x332 note69x147 note70x975 note71x790 note72x605 note73x420 note74x235 note75x50 note76x878 note77x693 note78x508 note79x323 note80x138 note81x966 note82x781 note83x596 note84x411 note85x226 note86x41 note87x869 note88x684 note0x499 note1x314 note2x129 note3x957 note4x772 note5x587 note6x402 note7x217 note8x32 note9x860 note10x675 note11x490 note12x305 note13x120 note14x948 note15x763 note16x578 note17x393 note18x208 note19x23 note20x851 note21x666 note22x481 note23x296 note24x111 note25x939 note26x754 note27x569 note28x384 note29x199 note30x14 note31x842 note32x657 note33x472 note34x287 note35x102 note36x930 note37x745 note38x560 note39x375 note40x190 note41x5 note42x833 note43x648 note44x463 note45x278 note46x93 note47x921 note48x736 note49x551 note50x366 note51x181 note52x1009 note53x824 note54x639 note55x454 note56x269 note57x84 note58x912 note59x727 note60x542 note61x357 note62x172 note63x1000 note64x815 note65x630 note66x445 note67x260 note68x75 note69x903 note70x718 note71x533 note72x348 note73x163 note74x991 note75x806 note76x621 note77x436 note78x251 note79x66 note80x894 note81x709 note82x524 note83x339 note84x154 note85x982 note86x797 note87x612 note88x427 note0x242 note1x57 note2x885 note3x700 note4x515 note5x330 note6x145 note7x973 note8x788 note9x603 note10x418 note11x233 note12x48 note13x876 note14x691 note15x506 note16x321 note17x136 note18x964 note19x779 note20x594 note21x409 note22x224 note23x39 note24x867 note25x682 note26x497 note27x312 note28x127 note29x955 note30x770 note31x585 note32x400 note33x215 note34x30 note35x858 note36x673 note37x488 note38x303 note39x118 note40x946 note41x761 note42x576 note43x391 note44x206 note45x21 note46x849 note47x664 note48x479 note49x294 note50x109 note51x937 note52x752 note53x567 note54x382 note55x197 note56x12 note57x840 note58x655 note59x470 note60x285 note61x100 note62x928 note63x743 note64x558 note65x373 note66x188 note67x3 note68x831 note69x646 note70x461 note71x276 note72x91 note73x919 note74x734 note75x549 note76x364 note77x179 note78x1007 note79x822 note80x637 note81x452 note82x267 note83x82 note84x910 note85x725 note86x540 note87x355 note88x170 note0x998 note1x813 note2x628 note3x443 note4x258 note5x73 note6x901 note7x716 note8x531 note9x346 note10x161 note11x989 note12x804 note13x619 note14x434 note15x249 note16x64 note17x892 note18x707 note19x522 note20x337 note21x152 note22x980 note23x795 note24x610 note25x425 note26x240 note27x55 note28x883 note29x698 note30x513 note31x328 note32x143 note33x971 note34x786 note35x601 note36x416 note37x231 note38x46 note39x874 note40x689 note41x504 note42x319 note43x134 note44x962 note45x777 note46x592 note47x407 note48x222 note49x37 note50x865 note51x680 note52x495 note53x310 note54x125 note55x953 note56x768 note57x583 note58x398 note59x213 note60x28 note61x856 note62x671 note63x486 note64x301 note65x116 note66x944 note67x759 note68x574 note69x389 note70x204 note71x19 note72x847 note73x662 note74x477 note75x292 note76x107 note77x935 note78x750 note79x565 note80x380 note81x195 note82x10 note83x838 note84x653 note85x468 note86x283 note87x98 note88x926 note0x741 note1x556 note2x371 note3x186 note4x1 note5x829 note6x644 note7x459 note8x274 note9x89 note10x917 note11x732 note12x547 note13x362 note14x177 note15x1005 note16x820 note17x635 note18x450 note19x265 note20x80 note21x908 note22x723 note23x538 note24x353 note25x168 note26x996 note27x811 note28x626 note29x441 note30x256 note31x71 note32x899 note33x714 note34x529 note35x344 note36x159 note37x987 note38x802 note39x617 note40x432 note41x247 note42x62 note43x890 note44x705 note45x520 note46x335 note47x150 note48x978 note49x793 note50x608 note51x423 note52x238 note53x53 note54x881 note55x696 note56x511 note57x326 note58x141 note59x969 note60x784 note61x599 note62x414 note63x229 note64x44 note65x872 note66x687 note67x502 note68x317 note69x132 note70x960 note71x775 note72x590 note73x405 note74x220 note75x35 note76x863 note77x678 note78x493 note79x308 note80x123 note81x951 note82x766 note83x581 note84x396 note85x211 note86x26 note87x854 note88x669 note0x484 note1x299 note2x114 note3x942 note4x757 note5x572 note6x387 note7x202 note8x17 note9x845 note10x660 note11x475 note12x290 note13x105 note14x933 note15x748 note16x563 note17x378 note18x193 note19x8 note20x836 note21x651 note22x466 note23x281 note24x96 note25x924 note26x739 note27x554 note28x369 note29x184 note30x1012 note31x827 note32x642 note33x457 note34x272 note35x87 note36x915 note37x730 note38x545 note39x360 note40x175 note41x1003 note42x818 note43x633 note44x448 note45x263 note46x78 note47x906 note48x721 note49x536 note50x351 note51x166 note52x994 note53x809 note54x624 note55x439 note56x254 note57x69 note58x897 note59x712 note60x527 note61x342 note62x157 note63x985 note64x800 note65x615 note66x430 note67x245 note68x60 note69x888 note70x703 note71x518 note72x333 note73x148 note74x976 note75x791 note76x606 note77x421 note78x236 note79x51 note80x879 note81x694 note82x509 note83x324 note84x139 note85x967 note86x782 note87x597 note88x412 note0x227 note1x42 note2x870 note3x685 note4x500 note5x315 note6x130 note7x958 note8x773 note9x588 note10x403 note11x218 note12x33 note13x861 note14x676 note15x491 note16x306 note17x121 note18x949 note19x764 note20x579 note21x394 note22x209 note23x24 note24x852 note25x667 note26x482 note27x297 note28x112 note29x940 note30x755 note31x570 note32x385 note33x200 note34x15 note35x843 note36x658 note37x473 note38x288 note39x103 note40x931 note41x746 note42x561 note43x376 note44x191 note45x6 note46x834 note47x649 note48x464 note49x279 note50x94 note51x922 note52x737 note53x552 note54x367 note55x182 note56x1010 note57x825 note58x640 note59x455 note60x270 note61x85 note62x913 note63x728 note64x543 note65x358 note66x173 note67x1001 note68x816 note69x631 note70x446 note71x261 note72x76 note73x904 note74x719 note75x534 note76x349 note77x164 note78x992 note79x807 note80x622 note81x437 note82x252 note83x67 note84x895 note85x710 note86x525 note87x340 note88x155 note0x983 note1x798 note2x613 note3x428 note4x243 note5x58 note6x886 note7x701 note8x516 note9x331 note10x146 note11x974 note12x789 note13x604 note14x419 note15x234 note16x49 note17x877 note18x692 note19x507 note20x322 note21x137 note22x965 note23x780 note24x595 note25x410 note26x225 note27x40 note28x868 note29x683 note30x498 note31x313 note32x128 note33x956 note34x771 note35x586 note36x401 note37x216 note38x31 note39x859 note40x674 note41x489 note42x304 note43x119 note44x947 note45x762 note46x577 note47x392 note48x207 note49x22 note50x850 note51x665 note52x480 note53x295 note54x110 note55x938 note56x753 note57x568 note58x383 note59x198 note60x13 note61x841 note62x656 note63x471 note64x286 note65x101 note66x929 note67x744 note68x559 note69x374 note70x189 note71x4 note72x832 note73x647 note74x462 note75x277 note76x92 note77x920 note78x735 note79x550 note80x365 note81x180 note82x1008 note83x823 note84x638 note85x453 note86x268 note87x83 note88x911 note0x726 note1x541 note2x356 note3x171 note4x999 note5x814 note6x629 note7x444 note8x259 note9x74 note10x902 note11x717 note12x532 note13x347 note14x162 note15x990 note16x805 note17x620 note18x435 note19x250 note20x65 note21x893 note22x708 note23x523 note24x338 note25x153 note26x981 note27x796 note28x611 note29x426 note30x241 note31x56 note32x884 note33x699 note34x514 note35x329 note36x144 note37x972 note38x787 note39x602 note40x417 note41x232 note42x47 note43x875 note44x690 note45x505 note46x320 note47x135 note48x963 note49x778 note50x593 note51x408 note52x223 note53x38 note54x866 note55x681 note56x496 note57x311 note58x126 note59x954 note60x769 note61x584 note62x399 note63x214 note64x29 note65x857 note66x672 note67x487 note68x302 note69x117 note70x945 note71x760 note72x575 note73x390 note74x205 note75x20 note76x848 note77x663 note78x478 note79x293 note80x108 note81x936 note82x751 note83x566 note84x381 note85x196 note86x11 note87x839 note88x654 note0x469 note1x284 note2x99 note3x927 note4x742 note5x557 note6x372 note7x187 note8x2 note9x830 note10x645 note11x460 note12x275 note13x90 note14x918 note15x733 note16x548 note17x363 note18x178 note19x1006 note20x821 note21x636 note22x451 note23x266 note24x81 note25x909 note26x724 note27x539 note28x354 note29x169 note30x997 note31x812 note32x627 note33x442 note34x257 note35x72 note36x900 note37x715 note38x530 note39x345 note40x160 note41x988 note42x803 note43x618 note44x433 note45x248 note46x63 note47x891 note48x706 note49x521 note50x336 note51x151 note52x979 note53x794 note54x609 note55x424 note56x239 note57x54 note58x882 note59x697 note60x512 note61x327 note62x142 note63x970 note64x785 note65x600 note66x415 note67x230 note68x45 note69x873 note70x688 note71x503 note72x318 note73x133 note74x961 note75x776 note76x591 note77x406 note78x221 note79x36 note80x864 note81x679 note82x494 note83x309 note84x124 note85x952 note86x767 note87x582 note88x397 note0x212 note1x27 note2x855 note3x670 note4x485 note5x300 note6x115 note7x943 note8x758 note9x573 note10x388 note11x203 note12x18 note13x846 note14x661 note15x476 note16x291 note17x106 note18x934 note19x749 note20x564 note21x379 note22x194 note23x9 note24x837 note25x652 note26x467 note27x282 note28x97 note29x925 note30x740 note31x555 note32x370 note33x185 note34x0 note35x828 note36x643 note37x458 note38x273 note39x88 note40x916 note41x731 note42x546 note43x361 note44x176 note45x1004 note46x819 note47x634 note48x449 note49x264 note50x79 note51x907 note52x722 note53x537 note54x352 note55x167 note56x995 note57x810 note58x625 note59x440 note60x255 note61x70 note62x898 note63x713 note64x528 note65x343 note66x158 note67x986 note68x801 note69x616 note70x431 note71x246 note72x61 note73x889 note74x704 note75x519 note76x334 note77x149 note78x977 note79x792 note80x607 note81x422 note82x237 note83x52 note84x880 note85x695 note86x510 note87x325 note88x140 note0x968 note1x783 note2x598 note3x413 note4x228 note5x43 note6x871 note7x686 note8x501 note9x316 note10x131 note11x959 note12x774 note13x589 note14x404 note15x219 note16x34 note17x862 note18x677 note19x492 note20x307 note21x122 note22x950 note23x765 note24x580 note25x395 note26x210 note27x25 note28x853 note29x668 note30x483 note31x298 note32x113 note33x941 note34x756 note35x571 note36x386 note37x201 note38x16 note39x844 note40x659 note41x474 note42x289 note43x104 note44x932 note45x747 note46x562 note47x377 note48x192 note49x7 note50x835 note51x650 note52x465 note53x280 note54x95 note55x923 note56x738 note57x553 note58x368 note59x183 note60x1011 note61x826 note62x641 note63x456 note64x271 note65x86 note66x914 note67x729 note68x544 note69x359 note70x174 note71x1002 note72x817 note73x632 note74x447 note75x262 note76x77 note77x905 note78x720 note79x535 note80x350 note81x165 note82x993 note83x808 note84x623 note85x438 note86x253 note87x68 note88x896 note0x711 note1x526 note2x341 note3x156 note4x984 note5x799 note6x614 note7x429 note8x244 note9x59 note10x887 note11x702 note12x517 note13x332 note14x147 note15x975 note16x790 note17x605 note18x420 note19x235 note20x50 note21x878 note22x693 note23x508 note24x323 note25x138 note26x966 note27x781 note28x596 note29x411 note30x226 note31x41 note32x869 note33x684 note34x499 note35x314 note36x129 note37x957 note38x772 note39x587 note40x402 note41x217 note42x32 note43x860 note44x675 note45x490 note46x305 note47x120 note48x948 note49x763 note50x578 note51x393 note52x208 note53x23 note54x851 note55x666 note56x481 note57x296 note58x111 note59x939 note60x754 note61x569 note62x384 note63x199 note64x14 note65x842 note66x657 note67x472 note68x287 note69x102 note70x930 note71x745 note72x560 note73x375 note74x190 note75x5 note76x833 note77x648 note78x463 note79x278 note80x93 note81x921 note82x736 note83x551 note84x366 note85x181 note86x1009 note87x824 note88x639 note0x454 note1x269 note2x84 note3x912 note4x727 note5x542 note6x357 note7x172 note8x1000 note9x815 note10x630 note11x445 note12x260 note13x75 note14x903 note15x718 note16x533 note17x348 note18x163 note19x991 note20x806 note21x621 note22x436 note23x251 note24x66 note25x894 note26x709 note27x524 note28x339 note29x154 note30x982 note31x797 note32x612 note33x427 note34x242 note35x57 note36x885 note37x700 note38x515 note39x330 note40x145 note41x973 note42x788 note43x603 note44x418 note45x233 note46x48 note47x876 note48x691 note49x506 note50x321 note51x136 note52x964 note53x779 note54x594 note55x409 note56x224 note57x39 note58x867 note59x682 note60x497 note61x312 note62x127 note63x955 note64x770 note65x585 note66x400 note67x215 note68x30 note69x858 note70x673 note71x488 note72x303 note73x118 note74x946 note75x761 note76x576 note77x391 note78x206 note79x21 note80x849 note81x664 note82x479 note83x294 note84x109 note85x937 note86x752 note87x567 note88x382 note0x197 note1x12 note2x840 note3x655 note4x470 note5x285 note6x100 note7x928 note8x743 note9x558 note10x373 note11x188 note12x3 note13x831 note14x646 note15x461 note16x276 note17x91 note18x919 note19x734 note20x549 note21x364 note22x179 note23x1007 note24x822 note25x637 note26x452 note27x267 note28x82 note29x910 note30x725 note31x540 note32x355 note33x170 note34x998 note35x813 note36x628 note37x443 note38x258 note39x73 note40x901 note41x716 note42x531 note43x346 note44x161 note45x989 note46x804 note47x619 note48x434 note49x249 note50x64 note51x892 note52x707 note53x522 note54x337 note55x152 note56x980 note57x795 note58x610 note59x425 note60x240 note61x55 note62x883 note63x698 note64x513 note65x328 note66x143 note67x971 note68x786 note69x601 note70x416 note71x231 note72x46 note73x874 note74x689 note75x504 note76x319 note77x134 note78x962 note79x777 note80x592 note81x407 note82x222 note83x37 note84x865 note85x680 note86x495 note87x310 note88x125 note0x953 note1x768 note2x583 note3x398 note4x213 note5x28 note6x856 note7x671 note8x486 note9x301 note10x116 note11x944 note12x759 note13x574 note14x389 note15x204 note16x19 note17x847 note18x662 note19x477 note20x292 note21x107 note22x935 note23x750 note24x565 note25x380 note26x195 note27x10 note28x838 note29x653 note30x468 note31x283 note32x98 note33x926 note34x741 note35x556 note36x371 note37x186 note38x1 note39x829 note40x644 note41x459 note42x274 note43x89 note44x917 note45x732 note46x547 note47x362 note48x177 note49x1005 note50x820 note51x635 note52x450 note53x265 note54x80 note55x908 note56x723 note57x538 note58x353 note59x168 note60x996 note61x811 note62x626 note63x441 note64x256 note65x71 note66x899 note67x714 note68x529 note69x344 note70x159 note71x987 note72x802 note73x617 note74x432 note75x247"}, {"role": "user", "content": "What is the first note?"}, {"role": "assistant", "content": "The first note is **note0x0**."}, {"role": "user", "content": "And the second one?"}, {"role": "assistant", "content": "The second note is **note1x828**."}, {"role": "user", "content": "Is note5x5 listed?"}], "max_tokens": 48, "temperature": 0.0, "draft": false, "chat_template_kwargs": {"enable_thinking": false}}, "status": 200, "response": {"id": "chatcmpl-408c8b4ef358471d9cd738c294098094", "object": "chat.completion", "created": 1793474271, "model": "flashnext", "choices": [{"index": 0, "message": {"role": "assistant", "content": "No, **note5x5** is not listed in the provided reference notes.\n\nThe list contains notes with hex suffixes (e.g., `note5x88`, `note5x587`, `note5"}, "finish_reason": "length"}], "usage": {"prompt_tokens": 10281, "completion_tokens": 48, "total_tokens": 10329, "prompt_tokens_details": {"cached_tokens": 0}, "completion_tokens_details": {"reasoning_tokens": 0}}, "exact_mode": "exact", "tensorfold": {"enable_thinking": false, "reasoning_effort": "none", "engine": "lanes", "tokens_per_second": 35.989554557084155, "seconds": 1.305934474, "prefill_seconds": 18.725236535, "prefill_widths": [], "prefill_raised": [], "time_to_first_token": 18.726510418, "sampling": "greedy", "drafts": false, "token_sha": "e7287d6bf366", "token_sha256": "e7287d6bf36620acbd71b1537e7b5ea9b239198191676c8c2261aad653c64a81", "min_rows": 1}, "speculative": {"rounds": 47, "drafted": 0, "accepted": 0, "acceptance_rate": 0.0, "tokens_per_round": 1.0212765957446808}}, "seconds": 20.063921213150024} +{"url": "http://127.0.0.1:30461/v1/chat/completions", "request": {"model": "flashnext", "messages": [{"role": "system", "content": "You are a careful assistant. Reference notes: note0x0 note1x828 note2x643 note3x458 note4x273 note5x88 note6x916 note7x731 note8x546 note9x361 note10x176 note11x1004 note12x819 note13x634 note14x449 note15x264 note16x79 note17x907 note18x722 note19x537 note20x352 note21x167 note22x995 note23x810 note24x625 note25x440 note26x255 note27x70 note28x898 note29x713 note30x528 note31x343 note32x158 note33x986 note34x801 note35x616 note36x431 note37x246 note38x61 note39x889 note40x704 note41x519 note42x334 note43x149 note44x977 note45x792 note46x607 note47x422 note48x237 note49x52 note50x880 note51x695 note52x510 note53x325 note54x140 note55x968 note56x783 note57x598 note58x413 note59x228 note60x43 note61x871 note62x686 note63x501 note64x316 note65x131 note66x959 note67x774 note68x589 note69x404 note70x219 note71x34 note72x862 note73x677 note74x492 note75x307 note76x122 note77x950 note78x765 note79x580 note80x395 note81x210 note82x25 note83x853 note84x668 note85x483 note86x298 note87x113 note88x941 note0x756 note1x571 note2x386 note3x201 note4x16 note5x844 note6x659 note7x474 note8x289 note9x104 note10x932 note11x747 note12x562 note13x377 note14x192 note15x7 note16x835 note17x650 note18x465 note19x280 note20x95 note21x923 note22x738 note23x553 note24x368 note25x183 note26x1011 note27x826 note28x641 note29x456 note30x271 note31x86 note32x914 note33x729 note34x544 note35x359 note36x174 note37x1002 note38x817 note39x632 note40x447 note41x262 note42x77 note43x905 note44x720 note45x535 note46x350 note47x165 note48x993 note49x808 note50x623 note51x438 note52x253 note53x68 note54x896 note55x711 note56x526 note57x341 note58x156 note59x984 note60x799 note61x614 note62x429 note63x244 note64x59 note65x887 note66x702 note67x517 note68x332 note69x147 note70x975 note71x790 note72x605 note73x420 note74x235 note75x50 note76x878 note77x693 note78x508 note79x323 note80x138 note81x966 note82x781 note83x596 note84x411 note85x226 note86x41 note87x869 note88x684 note0x499 note1x314 note2x129 note3x957 note4x772 note5x587 note6x402 note7x217 note8x32 note9x860 note10x675 note11x490 note12x305 note13x120 note14x948 note15x763 note16x578 note17x393 note18x208 note19x23 note20x851 note21x666 note22x481 note23x296 note24x111 note25x939 note26x754 note27x569 note28x384 note29x199 note30x14 note31x842 note32x657 note33x472 note34x287 note35x102 note36x930 note37x745 note38x560 note39x375 note40x190 note41x5 note42x833 note43x648 note44x463 note45x278 note46x93 note47x921 note48x736 note49x551 note50x366 note51x181 note52x1009 note53x824 note54x639 note55x454 note56x269 note57x84 note58x912 note59x727 note60x542 note61x357 note62x172 note63x1000 note64x815 note65x630 note66x445 note67x260 note68x75 note69x903 note70x718 note71x533 note72x348 note73x163 note74x991 note75x806 note76x621 note77x436 note78x251 note79x66 note80x894 note81x709 note82x524 note83x339 note84x154 note85x982 note86x797 note87x612 note88x427 note0x242 note1x57 note2x885 note3x700 note4x515 note5x330 note6x145 note7x973 note8x788 note9x603 note10x418 note11x233 note12x48 note13x876 note14x691 note15x506 note16x321 note17x136 note18x964 note19x779 note20x594 note21x409 note22x224 note23x39 note24x867 note25x682 note26x497 note27x312 note28x127 note29x955 note30x770 note31x585 note32x400 note33x215 note34x30 note35x858 note36x673 note37x488 note38x303 note39x118 note40x946 note41x761 note42x576 note43x391 note44x206 note45x21 note46x849 note47x664 note48x479 note49x294 note50x109 note51x937 note52x752 note53x567 note54x382 note55x197 note56x12 note57x840 note58x655 note59x470 note60x285 note61x100 note62x928 note63x743 note64x558 note65x373 note66x188 note67x3 note68x831 note69x646 note70x461 note71x276 note72x91 note73x919 note74x734 note75x549 note76x364 note77x179 note78x1007 note79x822 note80x637 note81x452 note82x267 note83x82 note84x910 note85x725 note86x540 note87x355 note88x170 note0x998 note1x813 note2x628 note3x443 note4x258 note5x73 note6x901 note7x716 note8x531 note9x346 note10x161 note11x989 note12x804 note13x619 note14x434 note15x249 note16x64 note17x892 note18x707 note19x522 note20x337 note21x152 note22x980 note23x795 note24x610 note25x425 note26x240 note27x55 note28x883 note29x698 note30x513 note31x328 note32x143 note33x971 note34x786 note35x601 note36x416 note37x231 note38x46 note39x874 note40x689 note41x504 note42x319 note43x134 note44x962 note45x777 note46x592 note47x407 note48x222 note49x37 note50x865 note51x680 note52x495 note53x310 note54x125 note55x953 note56x768 note57x583 note58x398 note59x213 note60x28 note61x856 note62x671 note63x486 note64x301 note65x116 note66x944 note67x759 note68x574 note69x389 note70x204 note71x19 note72x847 note73x662 note74x477 note75x292 note76x107 note77x935 note78x750 note79x565 note80x380 note81x195 note82x10 note83x838 note84x653 note85x468 note86x283 note87x98 note88x926 note0x741 note1x556 note2x371 note3x186 note4x1 note5x829 note6x644 note7x459 note8x274 note9x89 note10x917 note11x732 note12x547 note13x362 note14x177 note15x1005 note16x820 note17x635 note18x450 note19x265 note20x80 note21x908 note22x723 note23x538 note24x353 note25x168 note26x996 note27x811 note28x626 note29x441 note30x256 note31x71 note32x899 note33x714 note34x529 note35x344 note36x159 note37x987 note38x802 note39x617 note40x432 note41x247 note42x62 note43x890 note44x705 note45x520 note46x335 note47x150 note48x978 note49x793 note50x608 note51x423 note52x238 note53x53 note54x881 note55x696 note56x511 note57x326 note58x141 note59x969 note60x784 note61x599 note62x414 note63x229 note64x44 note65x872 note66x687 note67x502 note68x317 note69x132 note70x960 note71x775 note72x590 note73x405 note74x220 note75x35 note76x863 note77x678 note78x493 note79x308 note80x123 note81x951 note82x766 note83x581 note84x396 note85x211 note86x26 note87x854 note88x669 note0x484 note1x299 note2x114 note3x942 note4x757 note5x572 note6x387 note7x202 note8x17 note9x845 note10x660 note11x475 note12x290 note13x105 note14x933 note15x748 note16x563 note17x378 note18x193 note19x8 note20x836 note21x651 note22x466 note23x281 note24x96 note25x924 note26x739 note27x554 note28x369 note29x184 note30x1012 note31x827 note32x642 note33x457 note34x272 note35x87 note36x915 note37x730 note38x545 note39x360 note40x175 note41x1003 note42x818 note43x633 note44x448 note45x263 note46x78 note47x906 note48x721 note49x536 note50x351 note51x166 note52x994 note53x809 note54x624 note55x439 note56x254 note57x69 note58x897 note59x712 note60x527 note61x342 note62x157 note63x985 note64x800 note65x615 note66x430 note67x245 note68x60 note69x888 note70x703 note71x518 note72x333 note73x148 note74x976 note75x791 note76x606 note77x421 note78x236 note79x51 note80x879 note81x694 note82x509 note83x324 note84x139 note85x967 note86x782 note87x597 note88x412 note0x227 note1x42 note2x870 note3x685 note4x500 note5x315 note6x130 note7x958 note8x773 note9x588 note10x403 note11x218 note12x33 note13x861 note14x676 note15x491 note16x306 note17x121 note18x949 note19x764 note20x579 note21x394 note22x209 note23x24 note24x852 note25x667 note26x482 note27x297 note28x112 note29x940 note30x755 note31x570 note32x385 note33x200 note34x15 note35x843 note36x658 note37x473 note38x288 note39x103 note40x931 note41x746 note42x561 note43x376 note44x191 note45x6 note46x834 note47x649 note48x464 note49x279 note50x94 note51x922 note52x737 note53x552 note54x367 note55x182 note56x1010 note57x825 note58x640 note59x455 note60x270 note61x85 note62x913 note63x728 note64x543 note65x358 note66x173 note67x1001 note68x816 note69x631 note70x446 note71x261 note72x76 note73x904 note74x719 note75x534 note76x349 note77x164 note78x992 note79x807 note80x622 note81x437 note82x252 note83x67 note84x895 note85x710 note86x525 note87x340 note88x155 note0x983 note1x798 note2x613 note3x428 note4x243 note5x58 note6x886 note7x701 note8x516 note9x331 note10x146 note11x974 note12x789 note13x604 note14x419 note15x234 note16x49 note17x877 note18x692 note19x507 note20x322 note21x137 note22x965 note23x780 note24x595 note25x410 note26x225 note27x40 note28x868 note29x683 note30x498 note31x313 note32x128 note33x956 note34x771 note35x586 note36x401 note37x216 note38x31 note39x859 note40x674 note41x489 note42x304 note43x119 note44x947 note45x762 note46x577 note47x392 note48x207 note49x22 note50x850 note51x665 note52x480 note53x295 note54x110 note55x938 note56x753 note57x568 note58x383 note59x198 note60x13 note61x841 note62x656 note63x471 note64x286 note65x101 note66x929 note67x744 note68x559 note69x374 note70x189 note71x4 note72x832 note73x647 note74x462 note75x277 note76x92 note77x920 note78x735 note79x550 note80x365 note81x180 note82x1008 note83x823 note84x638 note85x453 note86x268 note87x83 note88x911 note0x726 note1x541 note2x356 note3x171 note4x999 note5x814 note6x629 note7x444 note8x259 note9x74 note10x902 note11x717 note12x532 note13x347 note14x162 note15x990 note16x805 note17x620 note18x435 note19x250 note20x65 note21x893 note22x708 note23x523 note24x338 note25x153 note26x981 note27x796 note28x611 note29x426 note30x241 note31x56 note32x884 note33x699 note34x514 note35x329 note36x144 note37x972 note38x787 note39x602 note40x417 note41x232 note42x47 note43x875 note44x690 note45x505 note46x320 note47x135 note48x963 note49x778 note50x593 note51x408 note52x223 note53x38 note54x866 note55x681 note56x496 note57x311 note58x126 note59x954 note60x769 note61x584 note62x399 note63x214 note64x29 note65x857 note66x672 note67x487 note68x302 note69x117 note70x945 note71x760 note72x575 note73x390 note74x205 note75x20 note76x848 note77x663 note78x478 note79x293 note80x108 note81x936 note82x751 note83x566 note84x381 note85x196 note86x11 note87x839 note88x654 note0x469 note1x284 note2x99 note3x927 note4x742 note5x557 note6x372 note7x187 note8x2 note9x830 note10x645 note11x460 note12x275 note13x90 note14x918 note15x733 note16x548 note17x363 note18x178 note19x1006 note20x821 note21x636 note22x451 note23x266 note24x81 note25x909 note26x724 note27x539 note28x354 note29x169 note30x997 note31x812 note32x627 note33x442 note34x257 note35x72 note36x900 note37x715 note38x530 note39x345 note40x160 note41x988 note42x803 note43x618 note44x433 note45x248 note46x63 note47x891 note48x706 note49x521 note50x336 note51x151 note52x979 note53x794 note54x609 note55x424 note56x239 note57x54 note58x882 note59x697 note60x512 note61x327 note62x142 note63x970 note64x785 note65x600 note66x415 note67x230 note68x45 note69x873 note70x688 note71x503 note72x318 note73x133 note74x961 note75x776 note76x591 note77x406 note78x221 note79x36 note80x864 note81x679 note82x494 note83x309 note84x124 note85x952 note86x767 note87x582 note88x397 note0x212 note1x27 note2x855 note3x670 note4x485 note5x300 note6x115 note7x943 note8x758 note9x573 note10x388 note11x203 note12x18 note13x846 note14x661 note15x476 note16x291 note17x106 note18x934 note19x749 note20x564 note21x379 note22x194 note23x9 note24x837 note25x652 note26x467 note27x282 note28x97 note29x925 note30x740 note31x555 note32x370 note33x185 note34x0 note35x828 note36x643 note37x458 note38x273 note39x88 note40x916 note41x731 note42x546 note43x361 note44x176 note45x1004 note46x819 note47x634 note48x449 note49x264 note50x79 note51x907 note52x722 note53x537 note54x352 note55x167 note56x995 note57x810 note58x625 note59x440 note60x255 note61x70 note62x898 note63x713 note64x528 note65x343 note66x158 note67x986 note68x801 note69x616 note70x431 note71x246 note72x61 note73x889 note74x704 note75x519 note76x334 note77x149 note78x977 note79x792 note80x607 note81x422 note82x237 note83x52 note84x880 note85x695 note86x510 note87x325 note88x140 note0x968 note1x783 note2x598 note3x413 note4x228 note5x43 note6x871 note7x686 note8x501 note9x316 note10x131 note11x959 note12x774 note13x589 note14x404 note15x219 note16x34 note17x862 note18x677 note19x492 note20x307 note21x122 note22x950 note23x765 note24x580 note25x395 note26x210 note27x25 note28x853 note29x668 note30x483 note31x298 note32x113 note33x941 note34x756 note35x571 note36x386 note37x201 note38x16 note39x844 note40x659 note41x474 note42x289 note43x104 note44x932 note45x747 note46x562 note47x377 note48x192 note49x7 note50x835 note51x650 note52x465 note53x280 note54x95 note55x923 note56x738 note57x553 note58x368 note59x183 note60x1011 note61x826 note62x641 note63x456 note64x271 note65x86 note66x914 note67x729 note68x544 note69x359 note70x174 note71x1002 note72x817 note73x632 note74x447 note75x262 note76x77 note77x905 note78x720 note79x535 note80x350 note81x165 note82x993 note83x808 note84x623 note85x438 note86x253 note87x68 note88x896 note0x711 note1x526 note2x341 note3x156 note4x984 note5x799 note6x614 note7x429 note8x244 note9x59 note10x887 note11x702 note12x517 note13x332 note14x147 note15x975 note16x790 note17x605 note18x420 note19x235 note20x50 note21x878 note22x693 note23x508 note24x323 note25x138 note26x966 note27x781 note28x596 note29x411 note30x226 note31x41 note32x869 note33x684 note34x499 note35x314 note36x129 note37x957 note38x772 note39x587 note40x402 note41x217 note42x32 note43x860 note44x675 note45x490 note46x305 note47x120 note48x948 note49x763 note50x578 note51x393 note52x208 note53x23 note54x851 note55x666 note56x481 note57x296 note58x111 note59x939 note60x754 note61x569 note62x384 note63x199 note64x14 note65x842 note66x657 note67x472 note68x287 note69x102 note70x930 note71x745 note72x560 note73x375 note74x190 note75x5 note76x833 note77x648 note78x463 note79x278 note80x93 note81x921 note82x736 note83x551 note84x366 note85x181 note86x1009 note87x824 note88x639 note0x454 note1x269 note2x84 note3x912 note4x727 note5x542 note6x357 note7x172 note8x1000 note9x815 note10x630 note11x445 note12x260 note13x75 note14x903 note15x718 note16x533 note17x348 note18x163 note19x991 note20x806 note21x621 note22x436 note23x251 note24x66 note25x894 note26x709 note27x524 note28x339 note29x154 note30x982 note31x797 note32x612 note33x427 note34x242 note35x57 note36x885 note37x700 note38x515 note39x330 note40x145 note41x973 note42x788 note43x603 note44x418 note45x233 note46x48 note47x876 note48x691 note49x506 note50x321 note51x136 note52x964 note53x779 note54x594 note55x409 note56x224 note57x39 note58x867 note59x682 note60x497 note61x312 note62x127 note63x955 note64x770 note65x585 note66x400 note67x215 note68x30 note69x858 note70x673 note71x488 note72x303 note73x118 note74x946 note75x761 note76x576 note77x391 note78x206 note79x21 note80x849 note81x664 note82x479 note83x294 note84x109 note85x937 note86x752 note87x567 note88x382 note0x197 note1x12 note2x840 note3x655 note4x470 note5x285 note6x100 note7x928 note8x743 note9x558 note10x373 note11x188 note12x3 note13x831 note14x646 note15x461 note16x276 note17x91 note18x919 note19x734 note20x549 note21x364 note22x179 note23x1007 note24x822 note25x637 note26x452 note27x267 note28x82 note29x910 note30x725 note31x540 note32x355 note33x170 note34x998 note35x813 note36x628 note37x443 note38x258 note39x73 note40x901 note41x716 note42x531 note43x346 note44x161 note45x989 note46x804 note47x619 note48x434 note49x249 note50x64 note51x892 note52x707 note53x522 note54x337 note55x152 note56x980 note57x795 note58x610 note59x425 note60x240 note61x55 note62x883 note63x698 note64x513 note65x328 note66x143 note67x971 note68x786 note69x601 note70x416 note71x231 note72x46 note73x874 note74x689 note75x504 note76x319 note77x134 note78x962 note79x777 note80x592 note81x407 note82x222 note83x37 note84x865 note85x680 note86x495 note87x310 note88x125 note0x953 note1x768 note2x583 note3x398 note4x213 note5x28 note6x856 note7x671 note8x486 note9x301 note10x116 note11x944 note12x759 note13x574 note14x389 note15x204 note16x19 note17x847 note18x662 note19x477 note20x292 note21x107 note22x935 note23x750 note24x565 note25x380 note26x195 note27x10 note28x838 note29x653 note30x468 note31x283 note32x98 note33x926 note34x741 note35x556 note36x371 note37x186 note38x1 note39x829 note40x644 note41x459 note42x274 note43x89 note44x917 note45x732 note46x547 note47x362 note48x177 note49x1005 note50x820 note51x635 note52x450 note53x265 note54x80 note55x908 note56x723 note57x538 note58x353 note59x168 note60x996 note61x811 note62x626 note63x441 note64x256 note65x71 note66x899 note67x714 note68x529 note69x344 note70x159 note71x987 note72x802 note73x617 note74x432 note75x247"}, {"role": "user", "content": "What is the first note?"}, {"role": "assistant", "content": "The first note is **note0x0**."}, {"role": "user", "content": "And the second one?"}, {"role": "assistant", "content": "The second note is **note1x828**."}, {"role": "user", "content": "Is note7x7 listed?"}], "max_tokens": 48, "temperature": 0.0, "draft": false, "chat_template_kwargs": {"enable_thinking": false}}, "status": 200, "response": {"id": "chatcmpl-67eb654abfc3a94aa1375adb9b2a6eeb", "object": "chat.completion", "created": 1793474291, "model": "flashnext", "choices": [{"index": 0, "message": {"role": "assistant", "content": "No, **note7x7** is not listed in the provided reference notes.\n\nThe notes follow a pattern where the second part (after the 'x') is a hexadecimal number (e.g., `note1x828"}, "finish_reason": "length"}], "usage": {"prompt_tokens": 10281, "completion_tokens": 48, "total_tokens": 10329, "prompt_tokens_details": {"cached_tokens": 0}, "completion_tokens_details": {"reasoning_tokens": 0}}, "exact_mode": "exact", "tensorfold": {"enable_thinking": false, "reasoning_effort": "none", "engine": "lanes", "tokens_per_second": 36.05742731732144, "seconds": 1.303476246, "prefill_seconds": 18.799743253, "prefill_widths": [], "prefill_raised": [], "time_to_first_token": 18.800836098, "sampling": "greedy", "drafts": false, "token_sha": "55e1d46d0689", "token_sha256": "55e1d46d06891dff37e5a39f83ae22514ba7952a98a301c70166bbb637c3f3b6", "min_rows": 1}, "speculative": {"rounds": 47, "drafted": 0, "accepted": 0, "acceptance_rate": 0.0, "tokens_per_round": 1.0212765957446808}}, "seconds": 20.105543851852417} +{"url": "http://127.0.0.1:30461/v1/chat/completions", "request": {"model": "flashnext", "messages": [{"role": "system", "content": "You are a careful assistant. Reference notes: note0x0 note1x828 note2x643 note3x458 note4x273 note5x88 note6x916 note7x731 note8x546 note9x361 note10x176 note11x1004 note12x819 note13x634 note14x449 note15x264 note16x79 note17x907 note18x722 note19x537 note20x352 note21x167 note22x995 note23x810 note24x625 note25x440 note26x255 note27x70 note28x898 note29x713 note30x528 note31x343 note32x158 note33x986 note34x801 note35x616 note36x431 note37x246 note38x61 note39x889 note40x704 note41x519 note42x334 note43x149 note44x977 note45x792 note46x607 note47x422 note48x237 note49x52 note50x880 note51x695 note52x510 note53x325 note54x140 note55x968 note56x783 note57x598 note58x413 note59x228 note60x43 note61x871 note62x686 note63x501 note64x316 note65x131 note66x959 note67x774 note68x589 note69x404 note70x219 note71x34 note72x862 note73x677 note74x492 note75x307 note76x122 note77x950 note78x765 note79x580 note80x395 note81x210 note82x25 note83x853 note84x668 note85x483 note86x298 note87x113 note88x941 note0x756 note1x571 note2x386 note3x201 note4x16 note5x844 note6x659 note7x474 note8x289 note9x104 note10x932 note11x747 note12x562 note13x377 note14x192 note15x7 note16x835 note17x650 note18x465 note19x280 note20x95 note21x923 note22x738 note23x553 note24x368 note25x183 note26x1011 note27x826 note28x641 note29x456 note30x271 note31x86 note32x914 note33x729 note34x544 note35x359 note36x174 note37x1002 note38x817 note39x632 note40x447 note41x262 note42x77 note43x905 note44x720 note45x535 note46x350 note47x165 note48x993 note49x808 note50x623 note51x438 note52x253 note53x68 note54x896 note55x711 note56x526 note57x341 note58x156 note59x984 note60x799 note61x614 note62x429 note63x244 note64x59 note65x887 note66x702 note67x517 note68x332 note69x147 note70x975 note71x790 note72x605 note73x420 note74x235 note75x50 note76x878 note77x693 note78x508 note79x323 note80x138 note81x966 note82x781 note83x596 note84x411 note85x226 note86x41 note87x869 note88x684 note0x499 note1x314 note2x129 note3x957 note4x772 note5x587 note6x402 note7x217 note8x32 note9x860 note10x675 note11x490 note12x305 note13x120 note14x948 note15x763 note16x578 note17x393 note18x208 note19x23 note20x851 note21x666 note22x481 note23x296 note24x111 note25x939 note26x754 note27x569 note28x384 note29x199 note30x14 note31x842 note32x657 note33x472 note34x287 note35x102 note36x930 note37x745 note38x560 note39x375 note40x190 note41x5 note42x833 note43x648 note44x463 note45x278 note46x93 note47x921 note48x736 note49x551 note50x366 note51x181 note52x1009 note53x824 note54x639 note55x454 note56x269 note57x84 note58x912 note59x727 note60x542 note61x357 note62x172 note63x1000 note64x815 note65x630 note66x445 note67x260 note68x75 note69x903 note70x718 note71x533 note72x348 note73x163 note74x991 note75x806 note76x621 note77x436 note78x251 note79x66 note80x894 note81x709 note82x524 note83x339 note84x154 note85x982 note86x797 note87x612 note88x427 note0x242 note1x57 note2x885 note3x700 note4x515 note5x330 note6x145 note7x973 note8x788 note9x603 note10x418 note11x233 note12x48 note13x876 note14x691 note15x506 note16x321 note17x136 note18x964 note19x779 note20x594 note21x409 note22x224 note23x39 note24x867 note25x682 note26x497 note27x312 note28x127 note29x955 note30x770 note31x585 note32x400 note33x215 note34x30 note35x858 note36x673 note37x488 note38x303 note39x118 note40x946 note41x761 note42x576 note43x391 note44x206 note45x21 note46x849 note47x664 note48x479 note49x294 note50x109 note51x937 note52x752 note53x567 note54x382 note55x197 note56x12 note57x840 note58x655 note59x470 note60x285 note61x100 note62x928 note63x743 note64x558 note65x373 note66x188 note67x3 note68x831 note69x646 note70x461 note71x276 note72x91 note73x919 note74x734 note75x549 note76x364 note77x179 note78x1007 note79x822 note80x637 note81x452 note82x267 note83x82 note84x910 note85x725 note86x540 note87x355 note88x170 note0x998 note1x813 note2x628 note3x443 note4x258 note5x73 note6x901 note7x716 note8x531 note9x346 note10x161 note11x989 note12x804 note13x619 note14x434 note15x249 note16x64 note17x892 note18x707 note19x522 note20x337 note21x152 note22x980 note23x795 note24x610 note25x425 note26x240 note27x55 note28x883 note29x698 note30x513 note31x328 note32x143 note33x971 note34x786 note35x601 note36x416 note37x231 note38x46 note39x874 note40x689 note41x504 note42x319 note43x134 note44x962 note45x777 note46x592 note47x407 note48x222 note49x37 note50x865 note51x680 note52x495 note53x310 note54x125 note55x953 note56x768 note57x583 note58x398 note59x213 note60x28 note61x856 note62x671 note63x486 note64x301 note65x116 note66x944 note67x759 note68x574 note69x389 note70x204 note71x19 note72x847 note73x662 note74x477 note75x292 note76x107 note77x935 note78x750 note79x565 note80x380 note81x195 note82x10 note83x838 note84x653 note85x468 note86x283 note87x98 note88x926 note0x741 note1x556 note2x371 note3x186 note4x1 note5x829 note6x644 note7x459 note8x274 note9x89 note10x917 note11x732 note12x547 note13x362 note14x177 note15x1005 note16x820 note17x635 note18x450 note19x265 note20x80 note21x908 note22x723 note23x538 note24x353 note25x168 note26x996 note27x811 note28x626 note29x441 note30x256 note31x71 note32x899 note33x714 note34x529 note35x344 note36x159 note37x987 note38x802 note39x617 note40x432 note41x247 note42x62 note43x890 note44x705 note45x520 note46x335 note47x150 note48x978 note49x793 note50x608 note51x423 note52x238 note53x53 note54x881 note55x696 note56x511 note57x326 note58x141 note59x969 note60x784 note61x599 note62x414 note63x229 note64x44 note65x872 note66x687 note67x502 note68x317 note69x132 note70x960 note71x775 note72x590 note73x405 note74x220 note75x35 note76x863 note77x678 note78x493 note79x308 note80x123 note81x951 note82x766 note83x581 note84x396 note85x211 note86x26 note87x854 note88x669 note0x484 note1x299 note2x114 note3x942 note4x757 note5x572 note6x387 note7x202 note8x17 note9x845 note10x660 note11x475 note12x290 note13x105 note14x933 note15x748 note16x563 note17x378 note18x193 note19x8 note20x836 note21x651 note22x466 note23x281 note24x96 note25x924 note26x739 note27x554 note28x369 note29x184 note30x1012 note31x827 note32x642 note33x457 note34x272 note35x87 note36x915 note37x730 note38x545 note39x360 note40x175 note41x1003 note42x818 note43x633 note44x448 note45x263 note46x78 note47x906 note48x721 note49x536 note50x351 note51x166 note52x994 note53x809 note54x624 note55x439 note56x254 note57x69 note58x897 note59x712 note60x527 note61x342 note62x157 note63x985 note64x800 note65x615 note66x430 note67x245 note68x60 note69x888 note70x703 note71x518 note72x333 note73x148 note74x976 note75x791 note76x606 note77x421 note78x236 note79x51 note80x879 note81x694 note82x509 note83x324 note84x139 note85x967 note86x782 note87x597 note88x412 note0x227 note1x42 note2x870 note3x685 note4x500 note5x315 note6x130 note7x958 note8x773 note9x588 note10x403 note11x218 note12x33 note13x861 note14x676 note15x491 note16x306 note17x121 note18x949 note19x764 note20x579 note21x394 note22x209 note23x24 note24x852 note25x667 note26x482 note27x297 note28x112 note29x940 note30x755 note31x570 note32x385 note33x200 note34x15 note35x843 note36x658 note37x473 note38x288 note39x103 note40x931 note41x746 note42x561 note43x376 note44x191 note45x6 note46x834 note47x649 note48x464 note49x279 note50x94 note51x922 note52x737 note53x552 note54x367 note55x182 note56x1010 note57x825 note58x640 note59x455 note60x270 note61x85 note62x913 note63x728 note64x543 note65x358 note66x173 note67x1001 note68x816 note69x631 note70x446 note71x261 note72x76 note73x904 note74x719 note75x534 note76x349 note77x164 note78x992 note79x807 note80x622 note81x437 note82x252 note83x67 note84x895 note85x710 note86x525 note87x340 note88x155 note0x983 note1x798 note2x613 note3x428 note4x243 note5x58 note6x886 note7x701 note8x516 note9x331 note10x146 note11x974 note12x789 note13x604 note14x419 note15x234 note16x49 note17x877 note18x692 note19x507 note20x322 note21x137 note22x965 note23x780 note24x595 note25x410 note26x225 note27x40 note28x868 note29x683 note30x498 note31x313 note32x128 note33x956 note34x771 note35x586 note36x401 note37x216 note38x31 note39x859 note40x674 note41x489 note42x304 note43x119 note44x947 note45x762 note46x577 note47x392 note48x207 note49x22 note50x850 note51x665 note52x480 note53x295 note54x110 note55x938 note56x753 note57x568 note58x383 note59x198 note60x13 note61x841 note62x656 note63x471 note64x286 note65x101 note66x929 note67x744 note68x559 note69x374 note70x189 note71x4 note72x832 note73x647 note74x462 note75x277 note76x92 note77x920 note78x735 note79x550 note80x365 note81x180 note82x1008 note83x823 note84x638 note85x453 note86x268 note87x83 note88x911 note0x726 note1x541 note2x356 note3x171 note4x999 note5x814 note6x629 note7x444 note8x259 note9x74 note10x902 note11x717 note12x532 note13x347 note14x162 note15x990 note16x805 note17x620 note18x435 note19x250 note20x65 note21x893 note22x708 note23x523 note24x338 note25x153 note26x981 note27x796 note28x611 note29x426 note30x241 note31x56 note32x884 note33x699 note34x514 note35x329 note36x144 note37x972 note38x787 note39x602 note40x417 note41x232 note42x47 note43x875 note44x690 note45x505 note46x320 note47x135 note48x963 note49x778 note50x593 note51x408 note52x223 note53x38 note54x866 note55x681 note56x496 note57x311 note58x126 note59x954 note60x769 note61x584 note62x399 note63x214 note64x29 note65x857 note66x672 note67x487 note68x302 note69x117 note70x945 note71x760 note72x575 note73x390 note74x205 note75x20 note76x848 note77x663 note78x478 note79x293 note80x108 note81x936 note82x751 note83x566 note84x381 note85x196 note86x11 note87x839 note88x654 note0x469 note1x284 note2x99 note3x927 note4x742 note5x557 note6x372 note7x187 note8x2 note9x830 note10x645 note11x460 note12x275 note13x90 note14x918 note15x733 note16x548 note17x363 note18x178 note19x1006 note20x821 note21x636 note22x451 note23x266 note24x81 note25x909 note26x724 note27x539 note28x354 note29x169 note30x997 note31x812 note32x627 note33x442 note34x257 note35x72 note36x900 note37x715 note38x530 note39x345 note40x160 note41x988 note42x803 note43x618 note44x433 note45x248 note46x63 note47x891 note48x706 note49x521 note50x336 note51x151 note52x979 note53x794 note54x609 note55x424 note56x239 note57x54 note58x882 note59x697 note60x512 note61x327 note62x142 note63x970 note64x785 note65x600 note66x415 note67x230 note68x45 note69x873 note70x688 note71x503 note72x318 note73x133 note74x961 note75x776 note76x591 note77x406 note78x221 note79x36 note80x864 note81x679 note82x494 note83x309 note84x124 note85x952 note86x767 note87x582 note88x397 note0x212 note1x27 note2x855 note3x670 note4x485 note5x300 note6x115 note7x943 note8x758 note9x573 note10x388 note11x203 note12x18 note13x846 note14x661 note15x476 note16x291 note17x106 note18x934 note19x749 note20x564 note21x379 note22x194 note23x9 note24x837 note25x652 note26x467 note27x282 note28x97 note29x925 note30x740 note31x555 note32x370 note33x185 note34x0 note35x828 note36x643 note37x458 note38x273 note39x88 note40x916 note41x731 note42x546 note43x361 note44x176 note45x1004 note46x819 note47x634 note48x449 note49x264 note50x79 note51x907 note52x722 note53x537 note54x352 note55x167 note56x995 note57x810 note58x625 note59x440 note60x255 note61x70 note62x898 note63x713 note64x528 note65x343 note66x158 note67x986 note68x801 note69x616 note70x431 note71x246 note72x61 note73x889 note74x704 note75x519 note76x334 note77x149 note78x977 note79x792 note80x607 note81x422 note82x237 note83x52 note84x880 note85x695 note86x510 note87x325 note88x140 note0x968 note1x783 note2x598 note3x413 note4x228 note5x43 note6x871 note7x686 note8x501 note9x316 note10x131 note11x959 note12x774 note13x589 note14x404 note15x219 note16x34 note17x862 note18x677 note19x492 note20x307 note21x122 note22x950 note23x765 note24x580 note25x395 note26x210 note27x25 note28x853 note29x668 note30x483 note31x298 note32x113 note33x941 note34x756 note35x571 note36x386 note37x201 note38x16 note39x844 note40x659 note41x474 note42x289 note43x104 note44x932 note45x747 note46x562 note47x377 note48x192 note49x7 note50x835 note51x650 note52x465 note53x280 note54x95 note55x923 note56x738 note57x553 note58x368 note59x183 note60x1011 note61x826 note62x641 note63x456 note64x271 note65x86 note66x914 note67x729 note68x544 note69x359 note70x174 note71x1002 note72x817 note73x632 note74x447 note75x262 note76x77 note77x905 note78x720 note79x535 note80x350 note81x165 note82x993 note83x808 note84x623 note85x438 note86x253 note87x68 note88x896 note0x711 note1x526 note2x341 note3x156 note4x984 note5x799 note6x614 note7x429 note8x244 note9x59 note10x887 note11x702 note12x517 note13x332 note14x147 note15x975 note16x790 note17x605 note18x420 note19x235 note20x50 note21x878 note22x693 note23x508 note24x323 note25x138 note26x966 note27x781 note28x596 note29x411 note30x226 note31x41 note32x869 note33x684 note34x499 note35x314 note36x129 note37x957 note38x772 note39x587 note40x402 note41x217 note42x32 note43x860 note44x675 note45x490 note46x305 note47x120 note48x948 note49x763 note50x578 note51x393 note52x208 note53x23 note54x851 note55x666 note56x481 note57x296 note58x111 note59x939 note60x754 note61x569 note62x384 note63x199 note64x14 note65x842 note66x657 note67x472 note68x287 note69x102 note70x930 note71x745 note72x560 note73x375 note74x190 note75x5 note76x833 note77x648 note78x463 note79x278 note80x93 note81x921 note82x736 note83x551 note84x366 note85x181 note86x1009 note87x824 note88x639 note0x454 note1x269 note2x84 note3x912 note4x727 note5x542 note6x357 note7x172 note8x1000 note9x815 note10x630 note11x445 note12x260 note13x75 note14x903 note15x718 note16x533 note17x348 note18x163 note19x991 note20x806 note21x621 note22x436 note23x251 note24x66 note25x894 note26x709 note27x524 note28x339 note29x154 note30x982 note31x797 note32x612 note33x427 note34x242 note35x57 note36x885 note37x700 note38x515 note39x330 note40x145 note41x973 note42x788 note43x603 note44x418 note45x233 note46x48 note47x876 note48x691 note49x506 note50x321 note51x136 note52x964 note53x779 note54x594 note55x409 note56x224 note57x39 note58x867 note59x682 note60x497 note61x312 note62x127 note63x955 note64x770 note65x585 note66x400 note67x215 note68x30 note69x858 note70x673 note71x488 note72x303 note73x118 note74x946 note75x761 note76x576 note77x391 note78x206 note79x21 note80x849 note81x664 note82x479 note83x294 note84x109 note85x937 note86x752 note87x567 note88x382 note0x197 note1x12 note2x840 note3x655 note4x470 note5x285 note6x100 note7x928 note8x743 note9x558 note10x373 note11x188 note12x3 note13x831 note14x646 note15x461 note16x276 note17x91 note18x919 note19x734 note20x549 note21x364 note22x179 note23x1007 note24x822 note25x637 note26x452 note27x267 note28x82 note29x910 note30x725 note31x540 note32x355 note33x170 note34x998 note35x813 note36x628 note37x443 note38x258 note39x73 note40x901 note41x716 note42x531 note43x346 note44x161 note45x989 note46x804 note47x619 note48x434 note49x249 note50x64 note51x892 note52x707 note53x522 note54x337 note55x152 note56x980 note57x795 note58x610 note59x425 note60x240 note61x55 note62x883 note63x698 note64x513 note65x328 note66x143 note67x971 note68x786 note69x601 note70x416 note71x231 note72x46 note73x874 note74x689 note75x504 note76x319 note77x134 note78x962 note79x777 note80x592 note81x407 note82x222 note83x37 note84x865 note85x680 note86x495 note87x310 note88x125 note0x953 note1x768 note2x583 note3x398 note4x213 note5x28 note6x856 note7x671 note8x486 note9x301 note10x116 note11x944 note12x759 note13x574 note14x389 note15x204 note16x19 note17x847 note18x662 note19x477 note20x292 note21x107 note22x935 note23x750 note24x565 note25x380 note26x195 note27x10 note28x838 note29x653 note30x468 note31x283 note32x98 note33x926 note34x741 note35x556 note36x371 note37x186 note38x1 note39x829 note40x644 note41x459 note42x274 note43x89 note44x917 note45x732 note46x547 note47x362 note48x177 note49x1005 note50x820 note51x635 note52x450 note53x265 note54x80 note55x908 note56x723 note57x538 note58x353 note59x168 note60x996 note61x811 note62x626 note63x441 note64x256 note65x71 note66x899 note67x714 note68x529 note69x344 note70x159 note71x987 note72x802 note73x617 note74x432 note75x247"}, {"role": "user", "content": "What is the first note?"}, {"role": "assistant", "content": "The first note is **note0x0**."}, {"role": "user", "content": "And the second one?"}, {"role": "assistant", "content": "The second note is **note1x828**."}, {"role": "user", "content": "Name the last note."}], "max_tokens": 48, "temperature": 0.0, "draft": false, "chat_template_kwargs": {"enable_thinking": false}}, "status": 200, "response": {"id": "chatcmpl-fd77dd60307c0984e43ab25a012bbbca", "object": "chat.completion", "created": 1793474311, "model": "flashnext", "choices": [{"index": 0, "message": {"role": "assistant", "content": "The last note is **note75x247**."}, "finish_reason": "stop"}], "usage": {"prompt_tokens": 10279, "completion_tokens": 14, "total_tokens": 10293, "prompt_tokens_details": {"cached_tokens": 0}, "completion_tokens_details": {"reasoning_tokens": 0}}, "exact_mode": "exact", "tensorfold": {"enable_thinking": false, "reasoning_effort": "none", "engine": "lanes", "tokens_per_second": 36.15267272579714, "seconds": 0.359586139, "prefill_seconds": 18.754570103, "prefill_widths": [], "prefill_raised": [], "time_to_first_token": 18.755862562, "sampling": "greedy", "drafts": false, "token_sha": "9537be85f86c", "token_sha256": "9537be85f86c467fa028c7e7cd58d5b693a814bcc9988a99dec273e8e81523c1", "min_rows": 1}, "speculative": {"rounds": 13, "drafted": 0, "accepted": 0, "acceptance_rate": 0.0, "tokens_per_round": 1.0769230769230769}}, "seconds": 19.1166250705719} +{"url": "http://127.0.0.1:30461/v1/chat/completions", "request": {"model": "flashnext", "messages": [{"role": "system", "content": "You are a careful assistant. Reference notes: note0x0 note1x828 note2x643 note3x458 note4x273 note5x88 note6x916 note7x731 note8x546 note9x361 note10x176 note11x1004 note12x819 note13x634 note14x449 note15x264 note16x79 note17x907 note18x722 note19x537 note20x352 note21x167 note22x995 note23x810 note24x625 note25x440 note26x255 note27x70 note28x898 note29x713 note30x528 note31x343 note32x158 note33x986 note34x801 note35x616 note36x431 note37x246 note38x61 note39x889 note40x704 note41x519 note42x334 note43x149 note44x977 note45x792 note46x607 note47x422 note48x237 note49x52 note50x880 note51x695 note52x510 note53x325 note54x140 note55x968 note56x783 note57x598 note58x413 note59x228 note60x43 note61x871 note62x686 note63x501 note64x316 note65x131 note66x959 note67x774 note68x589 note69x404 note70x219 note71x34 note72x862 note73x677 note74x492 note75x307 note76x122 note77x950 note78x765 note79x580 note80x395 note81x210 note82x25 note83x853 note84x668 note85x483 note86x298 note87x113 note88x941 note0x756 note1x571 note2x386 note3x201 note4x16 note5x844 note6x659 note7x474 note8x289 note9x104 note10x932 note11x747 note12x562 note13x377 note14x192 note15x7 note16x835 note17x650 note18x465 note19x280 note20x95 note21x923 note22x738 note23x553 note24x368 note25x183 note26x1011 note27x826 note28x641 note29x456 note30x271 note31x86 note32x914 note33x729 note34x544 note35x359 note36x174 note37x1002 note38x817 note39x632 note40x447 note41x262 note42x77 note43x905 note44x720 note45x535 note46x350 note47x165 note48x993 note49x808 note50x623 note51x438 note52x253 note53x68 note54x896 note55x711 note56x526 note57x341 note58x156 note59x984 note60x799 note61x614 note62x429 note63x244 note64x59 note65x887 note66x702 note67x517 note68x332 note69x147 note70x975 note71x790 note72x605 note73x420 note74x235 note75x50 note76x878 note77x693 note78x508 note79x323 note80x138 note81x966 note82x781 note83x596 note84x411 note85x226 note86x41 note87x869 note88x684 note0x499 note1x314 note2x129 note3x957 note4x772 note5x587 note6x402 note7x217 note8x32 note9x860 note10x675 note11x490 note12x305 note13x120 note14x948 note15x763 note16x578 note17x393 note18x208 note19x23 note20x851 note21x666 note22x481 note23x296 note24x111 note25x939 note26x754 note27x569 note28x384 note29x199 note30x14 note31x842 note32x657 note33x472 note34x287 note35x102 note36x930 note37x745 note38x560 note39x375 note40x190 note41x5 note42x833 note43x648 note44x463 note45x278 note46x93 note47x921 note48x736 note49x551 note50x366 note51x181 note52x1009 note53x824 note54x639 note55x454 note56x269 note57x84 note58x912 note59x727 note60x542 note61x357 note62x172 note63x1000 note64x815 note65x630 note66x445 note67x260 note68x75 note69x903 note70x718 note71x533 note72x348 note73x163 note74x991 note75x806 note76x621 note77x436 note78x251 note79x66 note80x894 note81x709 note82x524 note83x339 note84x154 note85x982 note86x797 note87x612 note88x427 note0x242 note1x57 note2x885 note3x700 note4x515 note5x330 note6x145 note7x973 note8x788 note9x603 note10x418 note11x233 note12x48 note13x876 note14x691 note15x506 note16x321 note17x136 note18x964 note19x779 note20x594 note21x409 note22x224 note23x39 note24x867 note25x682 note26x497 note27x312 note28x127 note29x955 note30x770 note31x585 note32x400 note33x215 note34x30 note35x858 note36x673 note37x488 note38x303 note39x118 note40x946 note41x761 note42x576 note43x391 note44x206 note45x21 note46x849 note47x664 note48x479 note49x294 note50x109 note51x937 note52x752 note53x567 note54x382 note55x197 note56x12 note57x840 note58x655 note59x470 note60x285 note61x100 note62x928 note63x743 note64x558 note65x373 note66x188 note67x3 note68x831 note69x646 note70x461 note71x276 note72x91 note73x919 note74x734 note75x549 note76x364 note77x179 note78x1007 note79x822 note80x637 note81x452 note82x267 note83x82 note84x910 note85x725 note86x540 note87x355 note88x170 note0x998 note1x813 note2x628 note3x443 note4x258 note5x73 note6x901 note7x716 note8x531 note9x346 note10x161 note11x989 note12x804 note13x619 note14x434 note15x249 note16x64 note17x892 note18x707 note19x522 note20x337 note21x152 note22x980 note23x795 note24x610 note25x425 note26x240 note27x55 note28x883 note29x698 note30x513 note31x328 note32x143 note33x971 note34x786 note35x601 note36x416 note37x231 note38x46 note39x874 note40x689 note41x504 note42x319 note43x134 note44x962 note45x777 note46x592 note47x407 note48x222 note49x37 note50x865 note51x680 note52x495 note53x310 note54x125 note55x953 note56x768 note57x583 note58x398 note59x213 note60x28 note61x856 note62x671 note63x486 note64x301 note65x116 note66x944 note67x759 note68x574 note69x389 note70x204 note71x19 note72x847 note73x662 note74x477 note75x292 note76x107 note77x935 note78x750 note79x565 note80x380 note81x195 note82x10 note83x838 note84x653 note85x468 note86x283 note87x98 note88x926 note0x741 note1x556 note2x371 note3x186 note4x1 note5x829 note6x644 note7x459 note8x274 note9x89 note10x917 note11x732 note12x547 note13x362 note14x177 note15x1005 note16x820 note17x635 note18x450 note19x265 note20x80 note21x908 note22x723 note23x538 note24x353 note25x168 note26x996 note27x811 note28x626 note29x441 note30x256 note31x71 note32x899 note33x714 note34x529 note35x344 note36x159 note37x987 note38x802 note39x617 note40x432 note41x247 note42x62 note43x890 note44x705 note45x520 note46x335 note47x150 note48x978 note49x793 note50x608 note51x423 note52x238 note53x53 note54x881 note55x696 note56x511 note57x326 note58x141 note59x969 note60x784 note61x599 note62x414 note63x229 note64x44 note65x872 note66x687 note67x502 note68x317 note69x132 note70x960 note71x775 note72x590 note73x405 note74x220 note75x35 note76x863 note77x678 note78x493 note79x308 note80x123 note81x951 note82x766 note83x581 note84x396 note85x211 note86x26 note87x854 note88x669 note0x484 note1x299 note2x114 note3x942 note4x757 note5x572 note6x387 note7x202 note8x17 note9x845 note10x660 note11x475 note12x290 note13x105 note14x933 note15x748 note16x563 note17x378 note18x193 note19x8 note20x836 note21x651 note22x466 note23x281 note24x96 note25x924 note26x739 note27x554 note28x369 note29x184 note30x1012 note31x827 note32x642 note33x457 note34x272 note35x87 note36x915 note37x730 note38x545 note39x360 note40x175 note41x1003 note42x818 note43x633 note44x448 note45x263 note46x78 note47x906 note48x721 note49x536 note50x351 note51x166 note52x994 note53x809 note54x624 note55x439 note56x254 note57x69 note58x897 note59x712 note60x527 note61x342 note62x157 note63x985 note64x800 note65x615 note66x430 note67x245 note68x60 note69x888 note70x703 note71x518 note72x333 note73x148 note74x976 note75x791 note76x606 note77x421 note78x236 note79x51 note80x879 note81x694 note82x509 note83x324 note84x139 note85x967 note86x782 note87x597 note88x412 note0x227 note1x42 note2x870 note3x685 note4x500 note5x315 note6x130 note7x958 note8x773 note9x588 note10x403 note11x218 note12x33 note13x861 note14x676 note15x491 note16x306 note17x121 note18x949 note19x764 note20x579 note21x394 note22x209 note23x24 note24x852 note25x667 note26x482 note27x297 note28x112 note29x940 note30x755 note31x570 note32x385 note33x200 note34x15 note35x843 note36x658 note37x473 note38x288 note39x103 note40x931 note41x746 note42x561 note43x376 note44x191 note45x6 note46x834 note47x649 note48x464 note49x279 note50x94 note51x922 note52x737 note53x552 note54x367 note55x182 note56x1010 note57x825 note58x640 note59x455 note60x270 note61x85 note62x913 note63x728 note64x543 note65x358 note66x173 note67x1001 note68x816 note69x631 note70x446 note71x261 note72x76 note73x904 note74x719 note75x534 note76x349 note77x164 note78x992 note79x807 note80x622 note81x437 note82x252 note83x67 note84x895 note85x710 note86x525 note87x340 note88x155 note0x983 note1x798 note2x613 note3x428 note4x243 note5x58 note6x886 note7x701 note8x516 note9x331 note10x146 note11x974 note12x789 note13x604 note14x419 note15x234 note16x49 note17x877 note18x692 note19x507 note20x322 note21x137 note22x965 note23x780 note24x595 note25x410 note26x225 note27x40 note28x868 note29x683 note30x498 note31x313 note32x128 note33x956 note34x771 note35x586 note36x401 note37x216 note38x31 note39x859 note40x674 note41x489 note42x304 note43x119 note44x947 note45x762 note46x577 note47x392 note48x207 note49x22 note50x850 note51x665 note52x480 note53x295 note54x110 note55x938 note56x753 note57x568 note58x383 note59x198 note60x13 note61x841 note62x656 note63x471 note64x286 note65x101 note66x929 note67x744 note68x559 note69x374 note70x189 note71x4 note72x832 note73x647 note74x462 note75x277 note76x92 note77x920 note78x735 note79x550 note80x365 note81x180 note82x1008 note83x823 note84x638 note85x453 note86x268 note87x83 note88x911 note0x726 note1x541 note2x356 note3x171 note4x999 note5x814 note6x629 note7x444 note8x259 note9x74 note10x902 note11x717 note12x532 note13x347 note14x162 note15x990 note16x805 note17x620 note18x435 note19x250 note20x65 note21x893 note22x708 note23x523 note24x338 note25x153 note26x981 note27x796 note28x611 note29x426 note30x241 note31x56 note32x884 note33x699 note34x514 note35x329 note36x144 note37x972 note38x787 note39x602 note40x417 note41x232 note42x47 note43x875 note44x690 note45x505 note46x320 note47x135 note48x963 note49x778 note50x593 note51x408 note52x223 note53x38 note54x866 note55x681 note56x496 note57x311 note58x126 note59x954 note60x769 note61x584 note62x399 note63x214 note64x29 note65x857 note66x672 note67x487 note68x302 note69x117 note70x945 note71x760 note72x575 note73x390 note74x205 note75x20 note76x848 note77x663 note78x478 note79x293 note80x108 note81x936 note82x751 note83x566 note84x381 note85x196 note86x11 note87x839 note88x654 note0x469 note1x284 note2x99 note3x927 note4x742 note5x557 note6x372 note7x187 note8x2 note9x830 note10x645 note11x460 note12x275 note13x90 note14x918 note15x733 note16x548 note17x363 note18x178 note19x1006 note20x821 note21x636 note22x451 note23x266 note24x81 note25x909 note26x724 note27x539 note28x354 note29x169 note30x997 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note50x820 note51x635 note52x450 note53x265 note54x80 note55x908 note56x723 note57x538 note58x353 note59x168 note60x996 note61x811 note62x626 note63x441 note64x256 note65x71 note66x899 note67x714 note68x529 note69x344 note70x159 note71x987 note72x802 note73x617 note74x432 note75x247"}, {"role": "user", "content": "What is the third note?"}], "max_tokens": 48, "temperature": 0.0, "draft": false, "chat_template_kwargs": {"enable_thinking": false}}, "status": 200, "response": {"id": "chatcmpl-72e349dea9964107b9568d2d023c4165", "object": "chat.completion", "created": 1793474330, "model": "flashnext", "choices": [{"index": 0, "message": {"role": "assistant", "content": "The third note is **note2x643**."}, "finish_reason": "stop"}], "usage": {"prompt_tokens": 10219, "completion_tokens": 13, "total_tokens": 10232, "prompt_tokens_details": {"cached_tokens": 0}, "completion_tokens_details": {"reasoning_tokens": 0}}, "exact_mode": "exact", "tensorfold": {"enable_thinking": false, "reasoning_effort": "none", "engine": "lanes", "tokens_per_second": 36.012781620439945, "seconds": 0.333215027, "prefill_seconds": 18.578413595, "prefill_widths": [], "prefill_raised": [], "time_to_first_token": 18.807535787, "sampling": "greedy", "drafts": false, "token_sha": "86effbb58f5b", "token_sha256": "86effbb58f5b1a059c85bb7445693561cdba823838fe7776eaafd0a10e14cf56", "min_rows": 1}, "speculative": {"rounds": 12, "drafted": 0, "accepted": 0, "acceptance_rate": 0.0, "tokens_per_round": 1.0833333333333333}}, "seconds": 19.142286777496338} +{"url": "http://127.0.0.1:30461/v1/chat/completions", "request": {"model": "flashnext", "messages": [{"role": "system", "content": "You are a careful assistant. 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note28x611 note29x426 note30x241 note31x56 note32x884 note33x699 note34x514 note35x329 note36x144 note37x972 note38x787 note39x602 note40x417 note41x232 note42x47 note43x875 note44x690 note45x505 note46x320 note47x135 note48x963 note49x778 note50x593 note51x408 note52x223 note53x38 note54x866 note55x681 note56x496 note57x311 note58x126 note59x954 note60x769 note61x584 note62x399 note63x214 note64x29 note65x857 note66x672 note67x487 note68x302 note69x117 note70x945 note71x760 note72x575 note73x390 note74x205 note75x20 note76x848 note77x663 note78x478 note79x293 note80x108 note81x936 note82x751 note83x566 note84x381 note85x196 note86x11 note87x839 note88x654 note0x469 note1x284 note2x99 note3x927 note4x742 note5x557 note6x372 note7x187 note8x2 note9x830 note10x645 note11x460 note12x275 note13x90 note14x918 note15x733 note16x548 note17x363 note18x178 note19x1006 note20x821 note21x636 note22x451 note23x266 note24x81 note25x909 note26x724 note27x539 note28x354 note29x169 note30x997 note31x812 note32x627 note33x442 note34x257 note35x72 note36x900 note37x715 note38x530 note39x345 note40x160 note41x988 note42x803 note43x618 note44x433 note45x248 note46x63 note47x891 note48x706 note49x521 note50x336 note51x151 note52x979 note53x794 note54x609 note55x424 note56x239 note57x54 note58x882 note59x697 note60x512 note61x327 note62x142 note63x970 note64x785 note65x600 note66x415 note67x230 note68x45 note69x873 note70x688 note71x503 note72x318 note73x133 note74x961 note75x776 note76x591 note77x406 note78x221 note79x36 note80x864 note81x679 note82x494 note83x309 note84x124 note85x952 note86x767 note87x582 note88x397 note0x212 note1x27 note2x855 note3x670 note4x485 note5x300 note6x115 note7x943 note8x758 note9x573 note10x388 note11x203 note12x18 note13x846 note14x661 note15x476 note16x291 note17x106 note18x934 note19x749 note20x564 note21x379 note22x194 note23x9 note24x837 note25x652 note26x467 note27x282 note28x97 note29x925 note30x740 note31x555 note32x370 note33x185 note34x0 note35x828 note36x643 note37x458 note38x273 note39x88 note40x916 note41x731 note42x546 note43x361 note44x176 note45x1004 note46x819 note47x634 note48x449 note49x264 note50x79 note51x907 note52x722 note53x537 note54x352 note55x167 note56x995 note57x810 note58x625 note59x440 note60x255 note61x70 note62x898 note63x713 note64x528 note65x343 note66x158 note67x986 note68x801 note69x616 note70x431 note71x246 note72x61 note73x889 note74x704 note75x519 note76x334 note77x149 note78x977 note79x792 note80x607 note81x422 note82x237 note83x52 note84x880 note85x695 note86x510 note87x325 note88x140 note0x968 note1x783 note2x598 note3x413 note4x228 note5x43 note6x871 note7x686 note8x501 note9x316 note10x131 note11x959 note12x774 note13x589 note14x404 note15x219 note16x34 note17x862 note18x677 note19x492 note20x307 note21x122 note22x950 note23x765 note24x580 note25x395 note26x210 note27x25 note28x853 note29x668 note30x483 note31x298 note32x113 note33x941 note34x756 note35x571 note36x386 note37x201 note38x16 note39x844 note40x659 note41x474 note42x289 note43x104 note44x932 note45x747 note46x562 note47x377 note48x192 note49x7 note50x835 note51x650 note52x465 note53x280 note54x95 note55x923 note56x738 note57x553 note58x368 note59x183 note60x1011 note61x826 note62x641 note63x456 note64x271 note65x86 note66x914 note67x729 note68x544 note69x359 note70x174 note71x1002 note72x817 note73x632 note74x447 note75x262 note76x77 note77x905 note78x720 note79x535 note80x350 note81x165 note82x993 note83x808 note84x623 note85x438 note86x253 note87x68 note88x896 note0x711 note1x526 note2x341 note3x156 note4x984 note5x799 note6x614 note7x429 note8x244 note9x59 note10x887 note11x702 note12x517 note13x332 note14x147 note15x975 note16x790 note17x605 note18x420 note19x235 note20x50 note21x878 note22x693 note23x508 note24x323 note25x138 note26x966 note27x781 note28x596 note29x411 note30x226 note31x41 note32x869 note33x684 note34x499 note35x314 note36x129 note37x957 note38x772 note39x587 note40x402 note41x217 note42x32 note43x860 note44x675 note45x490 note46x305 note47x120 note48x948 note49x763 note50x578 note51x393 note52x208 note53x23 note54x851 note55x666 note56x481 note57x296 note58x111 note59x939 note60x754 note61x569 note62x384 note63x199 note64x14 note65x842 note66x657 note67x472 note68x287 note69x102 note70x930 note71x745 note72x560 note73x375 note74x190 note75x5 note76x833 note77x648 note78x463 note79x278 note80x93 note81x921 note82x736 note83x551 note84x366 note85x181 note86x1009 note87x824 note88x639 note0x454 note1x269 note2x84 note3x912 note4x727 note5x542 note6x357 note7x172 note8x1000 note9x815 note10x630 note11x445 note12x260 note13x75 note14x903 note15x718 note16x533 note17x348 note18x163 note19x991 note20x806 note21x621 note22x436 note23x251 note24x66 note25x894 note26x709 note27x524 note28x339 note29x154 note30x982 note31x797 note32x612 note33x427 note34x242 note35x57 note36x885 note37x700 note38x515 note39x330 note40x145 note41x973 note42x788 note43x603 note44x418 note45x233 note46x48 note47x876 note48x691 note49x506 note50x321 note51x136 note52x964 note53x779 note54x594 note55x409 note56x224 note57x39 note58x867 note59x682 note60x497 note61x312 note62x127 note63x955 note64x770 note65x585 note66x400 note67x215 note68x30 note69x858 note70x673 note71x488 note72x303 note73x118 note74x946 note75x761 note76x576 note77x391 note78x206 note79x21 note80x849 note81x664 note82x479 note83x294 note84x109 note85x937 note86x752 note87x567 note88x382 note0x197 note1x12 note2x840 note3x655 note4x470 note5x285 note6x100 note7x928 note8x743 note9x558 note10x373 note11x188 note12x3 note13x831 note14x646 note15x461 note16x276 note17x91 note18x919 note19x734 note20x549 note21x364 note22x179 note23x1007 note24x822 note25x637 note26x452 note27x267 note28x82 note29x910 note30x725 note31x540 note32x355 note33x170 note34x998 note35x813 note36x628 note37x443 note38x258 note39x73 note40x901 note41x716 note42x531 note43x346 note44x161 note45x989 note46x804 note47x619 note48x434 note49x249 note50x64 note51x892 note52x707 note53x522 note54x337 note55x152 note56x980 note57x795 note58x610 note59x425 note60x240 note61x55 note62x883 note63x698 note64x513 note65x328 note66x143 note67x971 note68x786 note69x601 note70x416 note71x231 note72x46 note73x874 note74x689 note75x504 note76x319 note77x134 note78x962 note79x777 note80x592 note81x407 note82x222 note83x37 note84x865 note85x680 note86x495 note87x310 note88x125 note0x953 note1x768 note2x583 note3x398 note4x213 note5x28 note6x856 note7x671 note8x486 note9x301 note10x116 note11x944 note12x759 note13x574 note14x389 note15x204 note16x19 note17x847 note18x662 note19x477 note20x292 note21x107 note22x935 note23x750 note24x565 note25x380 note26x195 note27x10 note28x838 note29x653 note30x468 note31x283 note32x98 note33x926 note34x741 note35x556 note36x371 note37x186 note38x1 note39x829 note40x644 note41x459 note42x274 note43x89 note44x917 note45x732 note46x547 note47x362 note48x177 note49x1005 note50x820 note51x635 note52x450 note53x265 note54x80 note55x908 note56x723 note57x538 note58x353 note59x168 note60x996 note61x811 note62x626 note63x441 note64x256 note65x71 note66x899 note67x714 note68x529 note69x344 note70x159 note71x987 note72x802 note73x617 note74x432 note75x247"}, {"role": "user", "content": "What is the first note?"}, {"role": "assistant", "content": "The first note is **note0x0**."}, {"role": "user", "content": "And the second one?"}], "max_tokens": 48, "temperature": 0.0, "draft": false, "chat_template_kwargs": {"enable_thinking": false}}, "status": 200, "response": {"id": "chatcmpl-8f9f4dda5d2ec4ad89541adbb00447d3", "object": "chat.completion", "created": 1793474349, "model": "flashnext", "choices": [{"index": 0, "message": {"role": "assistant", "content": "The second note is **note1x828**."}, "finish_reason": "stop"}], "usage": {"prompt_tokens": 10248, "completion_tokens": 13, "total_tokens": 10261, "prompt_tokens_details": {"cached_tokens": 0}, "completion_tokens_details": {"reasoning_tokens": 0}}, "exact_mode": "exact", "tensorfold": {"enable_thinking": false, "reasoning_effort": "none", "engine": "lanes", "tokens_per_second": 34.073259819915606, "seconds": 0.352182329, "prefill_seconds": 18.670626146, "prefill_widths": [], "prefill_raised": [], "time_to_first_token": 18.671852651, "sampling": "greedy", "drafts": false, "token_sha": "7e4bf5aba972", "token_sha256": "7e4bf5aba9727191d8505e971356abb0485616846741651f36545f4775ef04fc", "min_rows": 1}, "speculative": {"rounds": 12, "drafted": 0, "accepted": 0, "acceptance_rate": 0.0, "tokens_per_round": 1.0833333333333333}}, "seconds": 19.025251626968384} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/exactness/exact-rewind.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/exactness/exact-rewind.json new file mode 100644 index 0000000000..6d05ce533e --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/exactness/exact-rewind.json @@ -0,0 +1,66 @@ +{ + "turn 1, drafts on": [ + "The first note is **note0x0**.", + 0 + ], + "turn 2, drafts on": [ + "The second note is **note1x828**.", + 10176 + ], + "turn 3, drafts on": [ + "No, **note5x5** is not listed in the provided reference notes.\n\nThe list contains notes with hex suffixes (e.g., `note5x88`, `note5x587`, `note5", + 10240 + ], + "regenerate turn 3, drafts on": [ + "No, **note5x5** is not listed in the provided reference notes.\n\nThe list contains notes with hex suffixes (e.g., `note5x88`, `note5x587`, `note5", + 10240 + ], + "edit turn 3, drafts on": [ + "No, **note7x7** is not listed in the provided reference notes.\n\nThe notes follow a pattern where the second part (after the 'x') is a hexadecimal number (e.g., `note1x828", + 10240 + ], + "delete turn 3, then turn 4, drafts on": [ + "The last note is **note75x247**.", + 10240 + ], + "edit turn 1, drafts on": [ + "The third note is **note2x643**.", + 10176 + ], + "turn 2 again, drafts on": [ + "The second note is **note1x828**.", + 10240 + ], + "turn 1, drafts off": [ + "The first note is **note0x0**.", + 10176 + ], + "turn 2, drafts off": [ + "The second note is **note1x828**.", + 10240 + ], + "turn 3, drafts off": [ + "No, **note5x5** is not listed in the provided reference notes.\n\nThe list contains notes with hex suffixes (e.g., `note5x88`, `note5x587`, `note5", + 10240 + ], + "regenerate turn 3, drafts off": [ + "No, **note5x5** is not listed in the provided reference notes.\n\nThe list contains notes with hex suffixes (e.g., `note5x88`, `note5x587`, `note5", + 10240 + ], + "edit turn 3, drafts off": [ + "No, **note7x7** is not listed in the provided reference notes.\n\nThe notes follow a pattern where the second part (after the 'x') is a hexadecimal number (e.g., `note1x828", + 10240 + ], + "delete turn 3, then turn 4, drafts off": [ + "The last note is **note75x247**.", + 10240 + ], + "edit turn 1, drafts off": [ + "The third note is **note2x643**.", + 10176 + ], + "turn 2 again, drafts off": [ + "The second note is **note1x828**.", + 10240 + ] +} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/exactness/exact-rewind.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/exactness/exact-rewind.jsonl new file mode 100644 index 0000000000..e25a1ed806 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/exactness/exact-rewind.jsonl @@ -0,0 +1,16 @@ +{"url": "http://127.0.0.1:30461/v1/chat/completions", "request": {"model": "flashnext", "messages": [{"role": "system", "content": "You are a careful assistant. Reference notes: note0x0 note1x828 note2x643 note3x458 note4x273 note5x88 note6x916 note7x731 note8x546 note9x361 note10x176 note11x1004 note12x819 note13x634 note14x449 note15x264 note16x79 note17x907 note18x722 note19x537 note20x352 note21x167 note22x995 note23x810 note24x625 note25x440 note26x255 note27x70 note28x898 note29x713 note30x528 note31x343 note32x158 note33x986 note34x801 note35x616 note36x431 note37x246 note38x61 note39x889 note40x704 note41x519 note42x334 note43x149 note44x977 note45x792 note46x607 note47x422 note48x237 note49x52 note50x880 note51x695 note52x510 note53x325 note54x140 note55x968 note56x783 note57x598 note58x413 note59x228 note60x43 note61x871 note62x686 note63x501 note64x316 note65x131 note66x959 note67x774 note68x589 note69x404 note70x219 note71x34 note72x862 note73x677 note74x492 note75x307 note76x122 note77x950 note78x765 note79x580 note80x395 note81x210 note82x25 note83x853 note84x668 note85x483 note86x298 note87x113 note88x941 note0x756 note1x571 note2x386 note3x201 note4x16 note5x844 note6x659 note7x474 note8x289 note9x104 note10x932 note11x747 note12x562 note13x377 note14x192 note15x7 note16x835 note17x650 note18x465 note19x280 note20x95 note21x923 note22x738 note23x553 note24x368 note25x183 note26x1011 note27x826 note28x641 note29x456 note30x271 note31x86 note32x914 note33x729 note34x544 note35x359 note36x174 note37x1002 note38x817 note39x632 note40x447 note41x262 note42x77 note43x905 note44x720 note45x535 note46x350 note47x165 note48x993 note49x808 note50x623 note51x438 note52x253 note53x68 note54x896 note55x711 note56x526 note57x341 note58x156 note59x984 note60x799 note61x614 note62x429 note63x244 note64x59 note65x887 note66x702 note67x517 note68x332 note69x147 note70x975 note71x790 note72x605 note73x420 note74x235 note75x50 note76x878 note77x693 note78x508 note79x323 note80x138 note81x966 note82x781 note83x596 note84x411 note85x226 note86x41 note87x869 note88x684 note0x499 note1x314 note2x129 note3x957 note4x772 note5x587 note6x402 note7x217 note8x32 note9x860 note10x675 note11x490 note12x305 note13x120 note14x948 note15x763 note16x578 note17x393 note18x208 note19x23 note20x851 note21x666 note22x481 note23x296 note24x111 note25x939 note26x754 note27x569 note28x384 note29x199 note30x14 note31x842 note32x657 note33x472 note34x287 note35x102 note36x930 note37x745 note38x560 note39x375 note40x190 note41x5 note42x833 note43x648 note44x463 note45x278 note46x93 note47x921 note48x736 note49x551 note50x366 note51x181 note52x1009 note53x824 note54x639 note55x454 note56x269 note57x84 note58x912 note59x727 note60x542 note61x357 note62x172 note63x1000 note64x815 note65x630 note66x445 note67x260 note68x75 note69x903 note70x718 note71x533 note72x348 note73x163 note74x991 note75x806 note76x621 note77x436 note78x251 note79x66 note80x894 note81x709 note82x524 note83x339 note84x154 note85x982 note86x797 note87x612 note88x427 note0x242 note1x57 note2x885 note3x700 note4x515 note5x330 note6x145 note7x973 note8x788 note9x603 note10x418 note11x233 note12x48 note13x876 note14x691 note15x506 note16x321 note17x136 note18x964 note19x779 note20x594 note21x409 note22x224 note23x39 note24x867 note25x682 note26x497 note27x312 note28x127 note29x955 note30x770 note31x585 note32x400 note33x215 note34x30 note35x858 note36x673 note37x488 note38x303 note39x118 note40x946 note41x761 note42x576 note43x391 note44x206 note45x21 note46x849 note47x664 note48x479 note49x294 note50x109 note51x937 note52x752 note53x567 note54x382 note55x197 note56x12 note57x840 note58x655 note59x470 note60x285 note61x100 note62x928 note63x743 note64x558 note65x373 note66x188 note67x3 note68x831 note69x646 note70x461 note71x276 note72x91 note73x919 note74x734 note75x549 note76x364 note77x179 note78x1007 note79x822 note80x637 note81x452 note82x267 note83x82 note84x910 note85x725 note86x540 note87x355 note88x170 note0x998 note1x813 note2x628 note3x443 note4x258 note5x73 note6x901 note7x716 note8x531 note9x346 note10x161 note11x989 note12x804 note13x619 note14x434 note15x249 note16x64 note17x892 note18x707 note19x522 note20x337 note21x152 note22x980 note23x795 note24x610 note25x425 note26x240 note27x55 note28x883 note29x698 note30x513 note31x328 note32x143 note33x971 note34x786 note35x601 note36x416 note37x231 note38x46 note39x874 note40x689 note41x504 note42x319 note43x134 note44x962 note45x777 note46x592 note47x407 note48x222 note49x37 note50x865 note51x680 note52x495 note53x310 note54x125 note55x953 note56x768 note57x583 note58x398 note59x213 note60x28 note61x856 note62x671 note63x486 note64x301 note65x116 note66x944 note67x759 note68x574 note69x389 note70x204 note71x19 note72x847 note73x662 note74x477 note75x292 note76x107 note77x935 note78x750 note79x565 note80x380 note81x195 note82x10 note83x838 note84x653 note85x468 note86x283 note87x98 note88x926 note0x741 note1x556 note2x371 note3x186 note4x1 note5x829 note6x644 note7x459 note8x274 note9x89 note10x917 note11x732 note12x547 note13x362 note14x177 note15x1005 note16x820 note17x635 note18x450 note19x265 note20x80 note21x908 note22x723 note23x538 note24x353 note25x168 note26x996 note27x811 note28x626 note29x441 note30x256 note31x71 note32x899 note33x714 note34x529 note35x344 note36x159 note37x987 note38x802 note39x617 note40x432 note41x247 note42x62 note43x890 note44x705 note45x520 note46x335 note47x150 note48x978 note49x793 note50x608 note51x423 note52x238 note53x53 note54x881 note55x696 note56x511 note57x326 note58x141 note59x969 note60x784 note61x599 note62x414 note63x229 note64x44 note65x872 note66x687 note67x502 note68x317 note69x132 note70x960 note71x775 note72x590 note73x405 note74x220 note75x35 note76x863 note77x678 note78x493 note79x308 note80x123 note81x951 note82x766 note83x581 note84x396 note85x211 note86x26 note87x854 note88x669 note0x484 note1x299 note2x114 note3x942 note4x757 note5x572 note6x387 note7x202 note8x17 note9x845 note10x660 note11x475 note12x290 note13x105 note14x933 note15x748 note16x563 note17x378 note18x193 note19x8 note20x836 note21x651 note22x466 note23x281 note24x96 note25x924 note26x739 note27x554 note28x369 note29x184 note30x1012 note31x827 note32x642 note33x457 note34x272 note35x87 note36x915 note37x730 note38x545 note39x360 note40x175 note41x1003 note42x818 note43x633 note44x448 note45x263 note46x78 note47x906 note48x721 note49x536 note50x351 note51x166 note52x994 note53x809 note54x624 note55x439 note56x254 note57x69 note58x897 note59x712 note60x527 note61x342 note62x157 note63x985 note64x800 note65x615 note66x430 note67x245 note68x60 note69x888 note70x703 note71x518 note72x333 note73x148 note74x976 note75x791 note76x606 note77x421 note78x236 note79x51 note80x879 note81x694 note82x509 note83x324 note84x139 note85x967 note86x782 note87x597 note88x412 note0x227 note1x42 note2x870 note3x685 note4x500 note5x315 note6x130 note7x958 note8x773 note9x588 note10x403 note11x218 note12x33 note13x861 note14x676 note15x491 note16x306 note17x121 note18x949 note19x764 note20x579 note21x394 note22x209 note23x24 note24x852 note25x667 note26x482 note27x297 note28x112 note29x940 note30x755 note31x570 note32x385 note33x200 note34x15 note35x843 note36x658 note37x473 note38x288 note39x103 note40x931 note41x746 note42x561 note43x376 note44x191 note45x6 note46x834 note47x649 note48x464 note49x279 note50x94 note51x922 note52x737 note53x552 note54x367 note55x182 note56x1010 note57x825 note58x640 note59x455 note60x270 note61x85 note62x913 note63x728 note64x543 note65x358 note66x173 note67x1001 note68x816 note69x631 note70x446 note71x261 note72x76 note73x904 note74x719 note75x534 note76x349 note77x164 note78x992 note79x807 note80x622 note81x437 note82x252 note83x67 note84x895 note85x710 note86x525 note87x340 note88x155 note0x983 note1x798 note2x613 note3x428 note4x243 note5x58 note6x886 note7x701 note8x516 note9x331 note10x146 note11x974 note12x789 note13x604 note14x419 note15x234 note16x49 note17x877 note18x692 note19x507 note20x322 note21x137 note22x965 note23x780 note24x595 note25x410 note26x225 note27x40 note28x868 note29x683 note30x498 note31x313 note32x128 note33x956 note34x771 note35x586 note36x401 note37x216 note38x31 note39x859 note40x674 note41x489 note42x304 note43x119 note44x947 note45x762 note46x577 note47x392 note48x207 note49x22 note50x850 note51x665 note52x480 note53x295 note54x110 note55x938 note56x753 note57x568 note58x383 note59x198 note60x13 note61x841 note62x656 note63x471 note64x286 note65x101 note66x929 note67x744 note68x559 note69x374 note70x189 note71x4 note72x832 note73x647 note74x462 note75x277 note76x92 note77x920 note78x735 note79x550 note80x365 note81x180 note82x1008 note83x823 note84x638 note85x453 note86x268 note87x83 note88x911 note0x726 note1x541 note2x356 note3x171 note4x999 note5x814 note6x629 note7x444 note8x259 note9x74 note10x902 note11x717 note12x532 note13x347 note14x162 note15x990 note16x805 note17x620 note18x435 note19x250 note20x65 note21x893 note22x708 note23x523 note24x338 note25x153 note26x981 note27x796 note28x611 note29x426 note30x241 note31x56 note32x884 note33x699 note34x514 note35x329 note36x144 note37x972 note38x787 note39x602 note40x417 note41x232 note42x47 note43x875 note44x690 note45x505 note46x320 note47x135 note48x963 note49x778 note50x593 note51x408 note52x223 note53x38 note54x866 note55x681 note56x496 note57x311 note58x126 note59x954 note60x769 note61x584 note62x399 note63x214 note64x29 note65x857 note66x672 note67x487 note68x302 note69x117 note70x945 note71x760 note72x575 note73x390 note74x205 note75x20 note76x848 note77x663 note78x478 note79x293 note80x108 note81x936 note82x751 note83x566 note84x381 note85x196 note86x11 note87x839 note88x654 note0x469 note1x284 note2x99 note3x927 note4x742 note5x557 note6x372 note7x187 note8x2 note9x830 note10x645 note11x460 note12x275 note13x90 note14x918 note15x733 note16x548 note17x363 note18x178 note19x1006 note20x821 note21x636 note22x451 note23x266 note24x81 note25x909 note26x724 note27x539 note28x354 note29x169 note30x997 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note50x820 note51x635 note52x450 note53x265 note54x80 note55x908 note56x723 note57x538 note58x353 note59x168 note60x996 note61x811 note62x626 note63x441 note64x256 note65x71 note66x899 note67x714 note68x529 note69x344 note70x159 note71x987 note72x802 note73x617 note74x432 note75x247"}, {"role": "user", "content": "What is the first note?"}], "max_tokens": 48, "temperature": 0.0, "draft": true, "chat_template_kwargs": {"enable_thinking": false}}, "status": 200, "response": {"id": "chatcmpl-0aba9c2d85e653b4dbc91a6d0a41f078", "object": "chat.completion", "created": 1793474475, "model": "flashnext", "choices": [{"index": 0, "message": {"role": "assistant", "content": "The first note is **note0x0**."}, "finish_reason": "stop"}], "usage": {"prompt_tokens": 10219, "completion_tokens": 11, "total_tokens": 10230, "prompt_tokens_details": {"cached_tokens": 0}, "completion_tokens_details": {"reasoning_tokens": 0}}, "exact_mode": "exact", "tensorfold": {"enable_thinking": false, "reasoning_effort": "none", "engine": "lanes", "tokens_per_second": 39.04420473975093, "seconds": 0.256119956, "prefill_seconds": 19.004701788, "prefill_widths": [], "prefill_raised": [], "time_to_first_token": 19.008381364, "sampling": "greedy", "drafts": true, "token_sha": "eea964a89e62", "token_sha256": "eea964a89e62f6e2059b2da5a676da894801486bd2b3f05aad65bbf32aacef96", "min_rows": 3}, "speculative": {"rounds": 3, "drafted": 12, "accepted": 11, "acceptance_rate": 0.9166666666666666, "tokens_per_round": 3.6666666666666665}}, "seconds": 19.271049976348877} +{"url": "http://127.0.0.1:30461/v1/chat/completions", "request": {"model": "flashnext", "messages": [{"role": "system", "content": "You are a careful assistant. 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note28x611 note29x426 note30x241 note31x56 note32x884 note33x699 note34x514 note35x329 note36x144 note37x972 note38x787 note39x602 note40x417 note41x232 note42x47 note43x875 note44x690 note45x505 note46x320 note47x135 note48x963 note49x778 note50x593 note51x408 note52x223 note53x38 note54x866 note55x681 note56x496 note57x311 note58x126 note59x954 note60x769 note61x584 note62x399 note63x214 note64x29 note65x857 note66x672 note67x487 note68x302 note69x117 note70x945 note71x760 note72x575 note73x390 note74x205 note75x20 note76x848 note77x663 note78x478 note79x293 note80x108 note81x936 note82x751 note83x566 note84x381 note85x196 note86x11 note87x839 note88x654 note0x469 note1x284 note2x99 note3x927 note4x742 note5x557 note6x372 note7x187 note8x2 note9x830 note10x645 note11x460 note12x275 note13x90 note14x918 note15x733 note16x548 note17x363 note18x178 note19x1006 note20x821 note21x636 note22x451 note23x266 note24x81 note25x909 note26x724 note27x539 note28x354 note29x169 note30x997 note31x812 note32x627 note33x442 note34x257 note35x72 note36x900 note37x715 note38x530 note39x345 note40x160 note41x988 note42x803 note43x618 note44x433 note45x248 note46x63 note47x891 note48x706 note49x521 note50x336 note51x151 note52x979 note53x794 note54x609 note55x424 note56x239 note57x54 note58x882 note59x697 note60x512 note61x327 note62x142 note63x970 note64x785 note65x600 note66x415 note67x230 note68x45 note69x873 note70x688 note71x503 note72x318 note73x133 note74x961 note75x776 note76x591 note77x406 note78x221 note79x36 note80x864 note81x679 note82x494 note83x309 note84x124 note85x952 note86x767 note87x582 note88x397 note0x212 note1x27 note2x855 note3x670 note4x485 note5x300 note6x115 note7x943 note8x758 note9x573 note10x388 note11x203 note12x18 note13x846 note14x661 note15x476 note16x291 note17x106 note18x934 note19x749 note20x564 note21x379 note22x194 note23x9 note24x837 note25x652 note26x467 note27x282 note28x97 note29x925 note30x740 note31x555 note32x370 note33x185 note34x0 note35x828 note36x643 note37x458 note38x273 note39x88 note40x916 note41x731 note42x546 note43x361 note44x176 note45x1004 note46x819 note47x634 note48x449 note49x264 note50x79 note51x907 note52x722 note53x537 note54x352 note55x167 note56x995 note57x810 note58x625 note59x440 note60x255 note61x70 note62x898 note63x713 note64x528 note65x343 note66x158 note67x986 note68x801 note69x616 note70x431 note71x246 note72x61 note73x889 note74x704 note75x519 note76x334 note77x149 note78x977 note79x792 note80x607 note81x422 note82x237 note83x52 note84x880 note85x695 note86x510 note87x325 note88x140 note0x968 note1x783 note2x598 note3x413 note4x228 note5x43 note6x871 note7x686 note8x501 note9x316 note10x131 note11x959 note12x774 note13x589 note14x404 note15x219 note16x34 note17x862 note18x677 note19x492 note20x307 note21x122 note22x950 note23x765 note24x580 note25x395 note26x210 note27x25 note28x853 note29x668 note30x483 note31x298 note32x113 note33x941 note34x756 note35x571 note36x386 note37x201 note38x16 note39x844 note40x659 note41x474 note42x289 note43x104 note44x932 note45x747 note46x562 note47x377 note48x192 note49x7 note50x835 note51x650 note52x465 note53x280 note54x95 note55x923 note56x738 note57x553 note58x368 note59x183 note60x1011 note61x826 note62x641 note63x456 note64x271 note65x86 note66x914 note67x729 note68x544 note69x359 note70x174 note71x1002 note72x817 note73x632 note74x447 note75x262 note76x77 note77x905 note78x720 note79x535 note80x350 note81x165 note82x993 note83x808 note84x623 note85x438 note86x253 note87x68 note88x896 note0x711 note1x526 note2x341 note3x156 note4x984 note5x799 note6x614 note7x429 note8x244 note9x59 note10x887 note11x702 note12x517 note13x332 note14x147 note15x975 note16x790 note17x605 note18x420 note19x235 note20x50 note21x878 note22x693 note23x508 note24x323 note25x138 note26x966 note27x781 note28x596 note29x411 note30x226 note31x41 note32x869 note33x684 note34x499 note35x314 note36x129 note37x957 note38x772 note39x587 note40x402 note41x217 note42x32 note43x860 note44x675 note45x490 note46x305 note47x120 note48x948 note49x763 note50x578 note51x393 note52x208 note53x23 note54x851 note55x666 note56x481 note57x296 note58x111 note59x939 note60x754 note61x569 note62x384 note63x199 note64x14 note65x842 note66x657 note67x472 note68x287 note69x102 note70x930 note71x745 note72x560 note73x375 note74x190 note75x5 note76x833 note77x648 note78x463 note79x278 note80x93 note81x921 note82x736 note83x551 note84x366 note85x181 note86x1009 note87x824 note88x639 note0x454 note1x269 note2x84 note3x912 note4x727 note5x542 note6x357 note7x172 note8x1000 note9x815 note10x630 note11x445 note12x260 note13x75 note14x903 note15x718 note16x533 note17x348 note18x163 note19x991 note20x806 note21x621 note22x436 note23x251 note24x66 note25x894 note26x709 note27x524 note28x339 note29x154 note30x982 note31x797 note32x612 note33x427 note34x242 note35x57 note36x885 note37x700 note38x515 note39x330 note40x145 note41x973 note42x788 note43x603 note44x418 note45x233 note46x48 note47x876 note48x691 note49x506 note50x321 note51x136 note52x964 note53x779 note54x594 note55x409 note56x224 note57x39 note58x867 note59x682 note60x497 note61x312 note62x127 note63x955 note64x770 note65x585 note66x400 note67x215 note68x30 note69x858 note70x673 note71x488 note72x303 note73x118 note74x946 note75x761 note76x576 note77x391 note78x206 note79x21 note80x849 note81x664 note82x479 note83x294 note84x109 note85x937 note86x752 note87x567 note88x382 note0x197 note1x12 note2x840 note3x655 note4x470 note5x285 note6x100 note7x928 note8x743 note9x558 note10x373 note11x188 note12x3 note13x831 note14x646 note15x461 note16x276 note17x91 note18x919 note19x734 note20x549 note21x364 note22x179 note23x1007 note24x822 note25x637 note26x452 note27x267 note28x82 note29x910 note30x725 note31x540 note32x355 note33x170 note34x998 note35x813 note36x628 note37x443 note38x258 note39x73 note40x901 note41x716 note42x531 note43x346 note44x161 note45x989 note46x804 note47x619 note48x434 note49x249 note50x64 note51x892 note52x707 note53x522 note54x337 note55x152 note56x980 note57x795 note58x610 note59x425 note60x240 note61x55 note62x883 note63x698 note64x513 note65x328 note66x143 note67x971 note68x786 note69x601 note70x416 note71x231 note72x46 note73x874 note74x689 note75x504 note76x319 note77x134 note78x962 note79x777 note80x592 note81x407 note82x222 note83x37 note84x865 note85x680 note86x495 note87x310 note88x125 note0x953 note1x768 note2x583 note3x398 note4x213 note5x28 note6x856 note7x671 note8x486 note9x301 note10x116 note11x944 note12x759 note13x574 note14x389 note15x204 note16x19 note17x847 note18x662 note19x477 note20x292 note21x107 note22x935 note23x750 note24x565 note25x380 note26x195 note27x10 note28x838 note29x653 note30x468 note31x283 note32x98 note33x926 note34x741 note35x556 note36x371 note37x186 note38x1 note39x829 note40x644 note41x459 note42x274 note43x89 note44x917 note45x732 note46x547 note47x362 note48x177 note49x1005 note50x820 note51x635 note52x450 note53x265 note54x80 note55x908 note56x723 note57x538 note58x353 note59x168 note60x996 note61x811 note62x626 note63x441 note64x256 note65x71 note66x899 note67x714 note68x529 note69x344 note70x159 note71x987 note72x802 note73x617 note74x432 note75x247"}, {"role": "user", "content": "What is the first note?"}, {"role": "assistant", "content": "The first note is **note0x0**."}, {"role": "user", "content": "And the second one?"}], "max_tokens": 48, "temperature": 0.0, "draft": true, "chat_template_kwargs": {"enable_thinking": false}}, "status": 200, "response": {"id": "chatcmpl-2f0c0ab18b174f36f4248a1f71b61682", "object": "chat.completion", "created": 1793474494, "model": "flashnext", "choices": [{"index": 0, "message": {"role": "assistant", "content": "The second note is **note1x828**."}, "finish_reason": "stop"}], "usage": {"prompt_tokens": 10248, "completion_tokens": 13, "total_tokens": 10261, "prompt_tokens_details": {"cached_tokens": 10176}, "completion_tokens_details": {"reasoning_tokens": 0}}, "exact_mode": "exact", "tensorfold": {"enable_thinking": false, "reasoning_effort": "none", "engine": "lanes", "tokens_per_second": 41.47639872803637, "seconds": 0.289321165, "prefill_seconds": 0.440993123, "prefill_widths": [], "prefill_raised": [], "time_to_first_token": 0.442062865, "sampling": "greedy", "drafts": true, "token_sha": "7e4bf5aba972", "token_sha256": "7e4bf5aba9727191d8505e971356abb0485616846741651f36545f4775ef04fc", "min_rows": 5}, "speculative": {"rounds": 4, "drafted": 21, "accepted": 10, "acceptance_rate": 0.47619047619047616, "tokens_per_round": 3.25}}, "seconds": 0.7633087635040283} +{"url": "http://127.0.0.1:30461/v1/chat/completions", "request": {"model": "flashnext", "messages": [{"role": "system", "content": "You are a careful assistant. 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note2x386 note3x201 note4x16 note5x844 note6x659 note7x474 note8x289 note9x104 note10x932 note11x747 note12x562 note13x377 note14x192 note15x7 note16x835 note17x650 note18x465 note19x280 note20x95 note21x923 note22x738 note23x553 note24x368 note25x183 note26x1011 note27x826 note28x641 note29x456 note30x271 note31x86 note32x914 note33x729 note34x544 note35x359 note36x174 note37x1002 note38x817 note39x632 note40x447 note41x262 note42x77 note43x905 note44x720 note45x535 note46x350 note47x165 note48x993 note49x808 note50x623 note51x438 note52x253 note53x68 note54x896 note55x711 note56x526 note57x341 note58x156 note59x984 note60x799 note61x614 note62x429 note63x244 note64x59 note65x887 note66x702 note67x517 note68x332 note69x147 note70x975 note71x790 note72x605 note73x420 note74x235 note75x50 note76x878 note77x693 note78x508 note79x323 note80x138 note81x966 note82x781 note83x596 note84x411 note85x226 note86x41 note87x869 note88x684 note0x499 note1x314 note2x129 note3x957 note4x772 note5x587 note6x402 note7x217 note8x32 note9x860 note10x675 note11x490 note12x305 note13x120 note14x948 note15x763 note16x578 note17x393 note18x208 note19x23 note20x851 note21x666 note22x481 note23x296 note24x111 note25x939 note26x754 note27x569 note28x384 note29x199 note30x14 note31x842 note32x657 note33x472 note34x287 note35x102 note36x930 note37x745 note38x560 note39x375 note40x190 note41x5 note42x833 note43x648 note44x463 note45x278 note46x93 note47x921 note48x736 note49x551 note50x366 note51x181 note52x1009 note53x824 note54x639 note55x454 note56x269 note57x84 note58x912 note59x727 note60x542 note61x357 note62x172 note63x1000 note64x815 note65x630 note66x445 note67x260 note68x75 note69x903 note70x718 note71x533 note72x348 note73x163 note74x991 note75x806 note76x621 note77x436 note78x251 note79x66 note80x894 note81x709 note82x524 note83x339 note84x154 note85x982 note86x797 note87x612 note88x427 note0x242 note1x57 note2x885 note3x700 note4x515 note5x330 note6x145 note7x973 note8x788 note9x603 note10x418 note11x233 note12x48 note13x876 note14x691 note15x506 note16x321 note17x136 note18x964 note19x779 note20x594 note21x409 note22x224 note23x39 note24x867 note25x682 note26x497 note27x312 note28x127 note29x955 note30x770 note31x585 note32x400 note33x215 note34x30 note35x858 note36x673 note37x488 note38x303 note39x118 note40x946 note41x761 note42x576 note43x391 note44x206 note45x21 note46x849 note47x664 note48x479 note49x294 note50x109 note51x937 note52x752 note53x567 note54x382 note55x197 note56x12 note57x840 note58x655 note59x470 note60x285 note61x100 note62x928 note63x743 note64x558 note65x373 note66x188 note67x3 note68x831 note69x646 note70x461 note71x276 note72x91 note73x919 note74x734 note75x549 note76x364 note77x179 note78x1007 note79x822 note80x637 note81x452 note82x267 note83x82 note84x910 note85x725 note86x540 note87x355 note88x170 note0x998 note1x813 note2x628 note3x443 note4x258 note5x73 note6x901 note7x716 note8x531 note9x346 note10x161 note11x989 note12x804 note13x619 note14x434 note15x249 note16x64 note17x892 note18x707 note19x522 note20x337 note21x152 note22x980 note23x795 note24x610 note25x425 note26x240 note27x55 note28x883 note29x698 note30x513 note31x328 note32x143 note33x971 note34x786 note35x601 note36x416 note37x231 note38x46 note39x874 note40x689 note41x504 note42x319 note43x134 note44x962 note45x777 note46x592 note47x407 note48x222 note49x37 note50x865 note51x680 note52x495 note53x310 note54x125 note55x953 note56x768 note57x583 note58x398 note59x213 note60x28 note61x856 note62x671 note63x486 note64x301 note65x116 note66x944 note67x759 note68x574 note69x389 note70x204 note71x19 note72x847 note73x662 note74x477 note75x292 note76x107 note77x935 note78x750 note79x565 note80x380 note81x195 note82x10 note83x838 note84x653 note85x468 note86x283 note87x98 note88x926 note0x741 note1x556 note2x371 note3x186 note4x1 note5x829 note6x644 note7x459 note8x274 note9x89 note10x917 note11x732 note12x547 note13x362 note14x177 note15x1005 note16x820 note17x635 note18x450 note19x265 note20x80 note21x908 note22x723 note23x538 note24x353 note25x168 note26x996 note27x811 note28x626 note29x441 note30x256 note31x71 note32x899 note33x714 note34x529 note35x344 note36x159 note37x987 note38x802 note39x617 note40x432 note41x247 note42x62 note43x890 note44x705 note45x520 note46x335 note47x150 note48x978 note49x793 note50x608 note51x423 note52x238 note53x53 note54x881 note55x696 note56x511 note57x326 note58x141 note59x969 note60x784 note61x599 note62x414 note63x229 note64x44 note65x872 note66x687 note67x502 note68x317 note69x132 note70x960 note71x775 note72x590 note73x405 note74x220 note75x35 note76x863 note77x678 note78x493 note79x308 note80x123 note81x951 note82x766 note83x581 note84x396 note85x211 note86x26 note87x854 note88x669 note0x484 note1x299 note2x114 note3x942 note4x757 note5x572 note6x387 note7x202 note8x17 note9x845 note10x660 note11x475 note12x290 note13x105 note14x933 note15x748 note16x563 note17x378 note18x193 note19x8 note20x836 note21x651 note22x466 note23x281 note24x96 note25x924 note26x739 note27x554 note28x369 note29x184 note30x1012 note31x827 note32x642 note33x457 note34x272 note35x87 note36x915 note37x730 note38x545 note39x360 note40x175 note41x1003 note42x818 note43x633 note44x448 note45x263 note46x78 note47x906 note48x721 note49x536 note50x351 note51x166 note52x994 note53x809 note54x624 note55x439 note56x254 note57x69 note58x897 note59x712 note60x527 note61x342 note62x157 note63x985 note64x800 note65x615 note66x430 note67x245 note68x60 note69x888 note70x703 note71x518 note72x333 note73x148 note74x976 note75x791 note76x606 note77x421 note78x236 note79x51 note80x879 note81x694 note82x509 note83x324 note84x139 note85x967 note86x782 note87x597 note88x412 note0x227 note1x42 note2x870 note3x685 note4x500 note5x315 note6x130 note7x958 note8x773 note9x588 note10x403 note11x218 note12x33 note13x861 note14x676 note15x491 note16x306 note17x121 note18x949 note19x764 note20x579 note21x394 note22x209 note23x24 note24x852 note25x667 note26x482 note27x297 note28x112 note29x940 note30x755 note31x570 note32x385 note33x200 note34x15 note35x843 note36x658 note37x473 note38x288 note39x103 note40x931 note41x746 note42x561 note43x376 note44x191 note45x6 note46x834 note47x649 note48x464 note49x279 note50x94 note51x922 note52x737 note53x552 note54x367 note55x182 note56x1010 note57x825 note58x640 note59x455 note60x270 note61x85 note62x913 note63x728 note64x543 note65x358 note66x173 note67x1001 note68x816 note69x631 note70x446 note71x261 note72x76 note73x904 note74x719 note75x534 note76x349 note77x164 note78x992 note79x807 note80x622 note81x437 note82x252 note83x67 note84x895 note85x710 note86x525 note87x340 note88x155 note0x983 note1x798 note2x613 note3x428 note4x243 note5x58 note6x886 note7x701 note8x516 note9x331 note10x146 note11x974 note12x789 note13x604 note14x419 note15x234 note16x49 note17x877 note18x692 note19x507 note20x322 note21x137 note22x965 note23x780 note24x595 note25x410 note26x225 note27x40 note28x868 note29x683 note30x498 note31x313 note32x128 note33x956 note34x771 note35x586 note36x401 note37x216 note38x31 note39x859 note40x674 note41x489 note42x304 note43x119 note44x947 note45x762 note46x577 note47x392 note48x207 note49x22 note50x850 note51x665 note52x480 note53x295 note54x110 note55x938 note56x753 note57x568 note58x383 note59x198 note60x13 note61x841 note62x656 note63x471 note64x286 note65x101 note66x929 note67x744 note68x559 note69x374 note70x189 note71x4 note72x832 note73x647 note74x462 note75x277 note76x92 note77x920 note78x735 note79x550 note80x365 note81x180 note82x1008 note83x823 note84x638 note85x453 note86x268 note87x83 note88x911 note0x726 note1x541 note2x356 note3x171 note4x999 note5x814 note6x629 note7x444 note8x259 note9x74 note10x902 note11x717 note12x532 note13x347 note14x162 note15x990 note16x805 note17x620 note18x435 note19x250 note20x65 note21x893 note22x708 note23x523 note24x338 note25x153 note26x981 note27x796 note28x611 note29x426 note30x241 note31x56 note32x884 note33x699 note34x514 note35x329 note36x144 note37x972 note38x787 note39x602 note40x417 note41x232 note42x47 note43x875 note44x690 note45x505 note46x320 note47x135 note48x963 note49x778 note50x593 note51x408 note52x223 note53x38 note54x866 note55x681 note56x496 note57x311 note58x126 note59x954 note60x769 note61x584 note62x399 note63x214 note64x29 note65x857 note66x672 note67x487 note68x302 note69x117 note70x945 note71x760 note72x575 note73x390 note74x205 note75x20 note76x848 note77x663 note78x478 note79x293 note80x108 note81x936 note82x751 note83x566 note84x381 note85x196 note86x11 note87x839 note88x654 note0x469 note1x284 note2x99 note3x927 note4x742 note5x557 note6x372 note7x187 note8x2 note9x830 note10x645 note11x460 note12x275 note13x90 note14x918 note15x733 note16x548 note17x363 note18x178 note19x1006 note20x821 note21x636 note22x451 note23x266 note24x81 note25x909 note26x724 note27x539 note28x354 note29x169 note30x997 note31x812 note32x627 note33x442 note34x257 note35x72 note36x900 note37x715 note38x530 note39x345 note40x160 note41x988 note42x803 note43x618 note44x433 note45x248 note46x63 note47x891 note48x706 note49x521 note50x336 note51x151 note52x979 note53x794 note54x609 note55x424 note56x239 note57x54 note58x882 note59x697 note60x512 note61x327 note62x142 note63x970 note64x785 note65x600 note66x415 note67x230 note68x45 note69x873 note70x688 note71x503 note72x318 note73x133 note74x961 note75x776 note76x591 note77x406 note78x221 note79x36 note80x864 note81x679 note82x494 note83x309 note84x124 note85x952 note86x767 note87x582 note88x397 note0x212 note1x27 note2x855 note3x670 note4x485 note5x300 note6x115 note7x943 note8x758 note9x573 note10x388 note11x203 note12x18 note13x846 note14x661 note15x476 note16x291 note17x106 note18x934 note19x749 note20x564 note21x379 note22x194 note23x9 note24x837 note25x652 note26x467 note27x282 note28x97 note29x925 note30x740 note31x555 note32x370 note33x185 note34x0 note35x828 note36x643 note37x458 note38x273 note39x88 note40x916 note41x731 note42x546 note43x361 note44x176 note45x1004 note46x819 note47x634 note48x449 note49x264 note50x79 note51x907 note52x722 note53x537 note54x352 note55x167 note56x995 note57x810 note58x625 note59x440 note60x255 note61x70 note62x898 note63x713 note64x528 note65x343 note66x158 note67x986 note68x801 note69x616 note70x431 note71x246 note72x61 note73x889 note74x704 note75x519 note76x334 note77x149 note78x977 note79x792 note80x607 note81x422 note82x237 note83x52 note84x880 note85x695 note86x510 note87x325 note88x140 note0x968 note1x783 note2x598 note3x413 note4x228 note5x43 note6x871 note7x686 note8x501 note9x316 note10x131 note11x959 note12x774 note13x589 note14x404 note15x219 note16x34 note17x862 note18x677 note19x492 note20x307 note21x122 note22x950 note23x765 note24x580 note25x395 note26x210 note27x25 note28x853 note29x668 note30x483 note31x298 note32x113 note33x941 note34x756 note35x571 note36x386 note37x201 note38x16 note39x844 note40x659 note41x474 note42x289 note43x104 note44x932 note45x747 note46x562 note47x377 note48x192 note49x7 note50x835 note51x650 note52x465 note53x280 note54x95 note55x923 note56x738 note57x553 note58x368 note59x183 note60x1011 note61x826 note62x641 note63x456 note64x271 note65x86 note66x914 note67x729 note68x544 note69x359 note70x174 note71x1002 note72x817 note73x632 note74x447 note75x262 note76x77 note77x905 note78x720 note79x535 note80x350 note81x165 note82x993 note83x808 note84x623 note85x438 note86x253 note87x68 note88x896 note0x711 note1x526 note2x341 note3x156 note4x984 note5x799 note6x614 note7x429 note8x244 note9x59 note10x887 note11x702 note12x517 note13x332 note14x147 note15x975 note16x790 note17x605 note18x420 note19x235 note20x50 note21x878 note22x693 note23x508 note24x323 note25x138 note26x966 note27x781 note28x596 note29x411 note30x226 note31x41 note32x869 note33x684 note34x499 note35x314 note36x129 note37x957 note38x772 note39x587 note40x402 note41x217 note42x32 note43x860 note44x675 note45x490 note46x305 note47x120 note48x948 note49x763 note50x578 note51x393 note52x208 note53x23 note54x851 note55x666 note56x481 note57x296 note58x111 note59x939 note60x754 note61x569 note62x384 note63x199 note64x14 note65x842 note66x657 note67x472 note68x287 note69x102 note70x930 note71x745 note72x560 note73x375 note74x190 note75x5 note76x833 note77x648 note78x463 note79x278 note80x93 note81x921 note82x736 note83x551 note84x366 note85x181 note86x1009 note87x824 note88x639 note0x454 note1x269 note2x84 note3x912 note4x727 note5x542 note6x357 note7x172 note8x1000 note9x815 note10x630 note11x445 note12x260 note13x75 note14x903 note15x718 note16x533 note17x348 note18x163 note19x991 note20x806 note21x621 note22x436 note23x251 note24x66 note25x894 note26x709 note27x524 note28x339 note29x154 note30x982 note31x797 note32x612 note33x427 note34x242 note35x57 note36x885 note37x700 note38x515 note39x330 note40x145 note41x973 note42x788 note43x603 note44x418 note45x233 note46x48 note47x876 note48x691 note49x506 note50x321 note51x136 note52x964 note53x779 note54x594 note55x409 note56x224 note57x39 note58x867 note59x682 note60x497 note61x312 note62x127 note63x955 note64x770 note65x585 note66x400 note67x215 note68x30 note69x858 note70x673 note71x488 note72x303 note73x118 note74x946 note75x761 note76x576 note77x391 note78x206 note79x21 note80x849 note81x664 note82x479 note83x294 note84x109 note85x937 note86x752 note87x567 note88x382 note0x197 note1x12 note2x840 note3x655 note4x470 note5x285 note6x100 note7x928 note8x743 note9x558 note10x373 note11x188 note12x3 note13x831 note14x646 note15x461 note16x276 note17x91 note18x919 note19x734 note20x549 note21x364 note22x179 note23x1007 note24x822 note25x637 note26x452 note27x267 note28x82 note29x910 note30x725 note31x540 note32x355 note33x170 note34x998 note35x813 note36x628 note37x443 note38x258 note39x73 note40x901 note41x716 note42x531 note43x346 note44x161 note45x989 note46x804 note47x619 note48x434 note49x249 note50x64 note51x892 note52x707 note53x522 note54x337 note55x152 note56x980 note57x795 note58x610 note59x425 note60x240 note61x55 note62x883 note63x698 note64x513 note65x328 note66x143 note67x971 note68x786 note69x601 note70x416 note71x231 note72x46 note73x874 note74x689 note75x504 note76x319 note77x134 note78x962 note79x777 note80x592 note81x407 note82x222 note83x37 note84x865 note85x680 note86x495 note87x310 note88x125 note0x953 note1x768 note2x583 note3x398 note4x213 note5x28 note6x856 note7x671 note8x486 note9x301 note10x116 note11x944 note12x759 note13x574 note14x389 note15x204 note16x19 note17x847 note18x662 note19x477 note20x292 note21x107 note22x935 note23x750 note24x565 note25x380 note26x195 note27x10 note28x838 note29x653 note30x468 note31x283 note32x98 note33x926 note34x741 note35x556 note36x371 note37x186 note38x1 note39x829 note40x644 note41x459 note42x274 note43x89 note44x917 note45x732 note46x547 note47x362 note48x177 note49x1005 note50x820 note51x635 note52x450 note53x265 note54x80 note55x908 note56x723 note57x538 note58x353 note59x168 note60x996 note61x811 note62x626 note63x441 note64x256 note65x71 note66x899 note67x714 note68x529 note69x344 note70x159 note71x987 note72x802 note73x617 note74x432 note75x247"}, {"role": "user", "content": "What is the first note?"}, {"role": "assistant", "content": "The first note is **note0x0**."}, {"role": "user", "content": "And the second one?"}, {"role": "assistant", "content": "The second note is **note1x828**."}, {"role": "user", "content": "Is note5x5 listed?"}], "max_tokens": 48, "temperature": 0.0, "draft": true, "chat_template_kwargs": {"enable_thinking": false}}, "status": 200, "response": {"id": "chatcmpl-fa75006f715fb7ae6d4c6ceecf61e462", "object": "chat.completion", "created": 1793474495, "model": "flashnext", "choices": [{"index": 0, "message": {"role": "assistant", "content": "No, **note5x5** is not listed in the provided reference notes.\n\nThe list contains notes with hex suffixes (e.g., `note5x88`, `note5x587`, `note5"}, "finish_reason": "length"}], "usage": {"prompt_tokens": 10281, "completion_tokens": 48, "total_tokens": 10329, "prompt_tokens_details": {"cached_tokens": 10240}, "completion_tokens_details": {"reasoning_tokens": 0}}, "exact_mode": "exact", "tensorfold": {"enable_thinking": false, "reasoning_effort": "none", "engine": "lanes", "tokens_per_second": 55.13171770288171, "seconds": 0.852503821, "prefill_seconds": 0.256298261, "prefill_widths": [], "prefill_raised": [], "time_to_first_token": 0.257579189, "sampling": "greedy", "drafts": true, "token_sha": "e7287d6bf366", "token_sha256": "e7287d6bf36620acbd71b1537e7b5ea9b239198191676c8c2261aad653c64a81", "min_rows": 2}, "speculative": {"rounds": 17, "drafted": 40, "accepted": 31, "acceptance_rate": 0.775, "tokens_per_round": 2.823529411764706}}, "seconds": 1.1112897396087646} +{"url": "http://127.0.0.1:30461/v1/chat/completions", "request": {"model": "flashnext", "messages": [{"role": "system", "content": "You are a careful assistant. Reference notes: note0x0 note1x828 note2x643 note3x458 note4x273 note5x88 note6x916 note7x731 note8x546 note9x361 note10x176 note11x1004 note12x819 note13x634 note14x449 note15x264 note16x79 note17x907 note18x722 note19x537 note20x352 note21x167 note22x995 note23x810 note24x625 note25x440 note26x255 note27x70 note28x898 note29x713 note30x528 note31x343 note32x158 note33x986 note34x801 note35x616 note36x431 note37x246 note38x61 note39x889 note40x704 note41x519 note42x334 note43x149 note44x977 note45x792 note46x607 note47x422 note48x237 note49x52 note50x880 note51x695 note52x510 note53x325 note54x140 note55x968 note56x783 note57x598 note58x413 note59x228 note60x43 note61x871 note62x686 note63x501 note64x316 note65x131 note66x959 note67x774 note68x589 note69x404 note70x219 note71x34 note72x862 note73x677 note74x492 note75x307 note76x122 note77x950 note78x765 note79x580 note80x395 note81x210 note82x25 note83x853 note84x668 note85x483 note86x298 note87x113 note88x941 note0x756 note1x571 note2x386 note3x201 note4x16 note5x844 note6x659 note7x474 note8x289 note9x104 note10x932 note11x747 note12x562 note13x377 note14x192 note15x7 note16x835 note17x650 note18x465 note19x280 note20x95 note21x923 note22x738 note23x553 note24x368 note25x183 note26x1011 note27x826 note28x641 note29x456 note30x271 note31x86 note32x914 note33x729 note34x544 note35x359 note36x174 note37x1002 note38x817 note39x632 note40x447 note41x262 note42x77 note43x905 note44x720 note45x535 note46x350 note47x165 note48x993 note49x808 note50x623 note51x438 note52x253 note53x68 note54x896 note55x711 note56x526 note57x341 note58x156 note59x984 note60x799 note61x614 note62x429 note63x244 note64x59 note65x887 note66x702 note67x517 note68x332 note69x147 note70x975 note71x790 note72x605 note73x420 note74x235 note75x50 note76x878 note77x693 note78x508 note79x323 note80x138 note81x966 note82x781 note83x596 note84x411 note85x226 note86x41 note87x869 note88x684 note0x499 note1x314 note2x129 note3x957 note4x772 note5x587 note6x402 note7x217 note8x32 note9x860 note10x675 note11x490 note12x305 note13x120 note14x948 note15x763 note16x578 note17x393 note18x208 note19x23 note20x851 note21x666 note22x481 note23x296 note24x111 note25x939 note26x754 note27x569 note28x384 note29x199 note30x14 note31x842 note32x657 note33x472 note34x287 note35x102 note36x930 note37x745 note38x560 note39x375 note40x190 note41x5 note42x833 note43x648 note44x463 note45x278 note46x93 note47x921 note48x736 note49x551 note50x366 note51x181 note52x1009 note53x824 note54x639 note55x454 note56x269 note57x84 note58x912 note59x727 note60x542 note61x357 note62x172 note63x1000 note64x815 note65x630 note66x445 note67x260 note68x75 note69x903 note70x718 note71x533 note72x348 note73x163 note74x991 note75x806 note76x621 note77x436 note78x251 note79x66 note80x894 note81x709 note82x524 note83x339 note84x154 note85x982 note86x797 note87x612 note88x427 note0x242 note1x57 note2x885 note3x700 note4x515 note5x330 note6x145 note7x973 note8x788 note9x603 note10x418 note11x233 note12x48 note13x876 note14x691 note15x506 note16x321 note17x136 note18x964 note19x779 note20x594 note21x409 note22x224 note23x39 note24x867 note25x682 note26x497 note27x312 note28x127 note29x955 note30x770 note31x585 note32x400 note33x215 note34x30 note35x858 note36x673 note37x488 note38x303 note39x118 note40x946 note41x761 note42x576 note43x391 note44x206 note45x21 note46x849 note47x664 note48x479 note49x294 note50x109 note51x937 note52x752 note53x567 note54x382 note55x197 note56x12 note57x840 note58x655 note59x470 note60x285 note61x100 note62x928 note63x743 note64x558 note65x373 note66x188 note67x3 note68x831 note69x646 note70x461 note71x276 note72x91 note73x919 note74x734 note75x549 note76x364 note77x179 note78x1007 note79x822 note80x637 note81x452 note82x267 note83x82 note84x910 note85x725 note86x540 note87x355 note88x170 note0x998 note1x813 note2x628 note3x443 note4x258 note5x73 note6x901 note7x716 note8x531 note9x346 note10x161 note11x989 note12x804 note13x619 note14x434 note15x249 note16x64 note17x892 note18x707 note19x522 note20x337 note21x152 note22x980 note23x795 note24x610 note25x425 note26x240 note27x55 note28x883 note29x698 note30x513 note31x328 note32x143 note33x971 note34x786 note35x601 note36x416 note37x231 note38x46 note39x874 note40x689 note41x504 note42x319 note43x134 note44x962 note45x777 note46x592 note47x407 note48x222 note49x37 note50x865 note51x680 note52x495 note53x310 note54x125 note55x953 note56x768 note57x583 note58x398 note59x213 note60x28 note61x856 note62x671 note63x486 note64x301 note65x116 note66x944 note67x759 note68x574 note69x389 note70x204 note71x19 note72x847 note73x662 note74x477 note75x292 note76x107 note77x935 note78x750 note79x565 note80x380 note81x195 note82x10 note83x838 note84x653 note85x468 note86x283 note87x98 note88x926 note0x741 note1x556 note2x371 note3x186 note4x1 note5x829 note6x644 note7x459 note8x274 note9x89 note10x917 note11x732 note12x547 note13x362 note14x177 note15x1005 note16x820 note17x635 note18x450 note19x265 note20x80 note21x908 note22x723 note23x538 note24x353 note25x168 note26x996 note27x811 note28x626 note29x441 note30x256 note31x71 note32x899 note33x714 note34x529 note35x344 note36x159 note37x987 note38x802 note39x617 note40x432 note41x247 note42x62 note43x890 note44x705 note45x520 note46x335 note47x150 note48x978 note49x793 note50x608 note51x423 note52x238 note53x53 note54x881 note55x696 note56x511 note57x326 note58x141 note59x969 note60x784 note61x599 note62x414 note63x229 note64x44 note65x872 note66x687 note67x502 note68x317 note69x132 note70x960 note71x775 note72x590 note73x405 note74x220 note75x35 note76x863 note77x678 note78x493 note79x308 note80x123 note81x951 note82x766 note83x581 note84x396 note85x211 note86x26 note87x854 note88x669 note0x484 note1x299 note2x114 note3x942 note4x757 note5x572 note6x387 note7x202 note8x17 note9x845 note10x660 note11x475 note12x290 note13x105 note14x933 note15x748 note16x563 note17x378 note18x193 note19x8 note20x836 note21x651 note22x466 note23x281 note24x96 note25x924 note26x739 note27x554 note28x369 note29x184 note30x1012 note31x827 note32x642 note33x457 note34x272 note35x87 note36x915 note37x730 note38x545 note39x360 note40x175 note41x1003 note42x818 note43x633 note44x448 note45x263 note46x78 note47x906 note48x721 note49x536 note50x351 note51x166 note52x994 note53x809 note54x624 note55x439 note56x254 note57x69 note58x897 note59x712 note60x527 note61x342 note62x157 note63x985 note64x800 note65x615 note66x430 note67x245 note68x60 note69x888 note70x703 note71x518 note72x333 note73x148 note74x976 note75x791 note76x606 note77x421 note78x236 note79x51 note80x879 note81x694 note82x509 note83x324 note84x139 note85x967 note86x782 note87x597 note88x412 note0x227 note1x42 note2x870 note3x685 note4x500 note5x315 note6x130 note7x958 note8x773 note9x588 note10x403 note11x218 note12x33 note13x861 note14x676 note15x491 note16x306 note17x121 note18x949 note19x764 note20x579 note21x394 note22x209 note23x24 note24x852 note25x667 note26x482 note27x297 note28x112 note29x940 note30x755 note31x570 note32x385 note33x200 note34x15 note35x843 note36x658 note37x473 note38x288 note39x103 note40x931 note41x746 note42x561 note43x376 note44x191 note45x6 note46x834 note47x649 note48x464 note49x279 note50x94 note51x922 note52x737 note53x552 note54x367 note55x182 note56x1010 note57x825 note58x640 note59x455 note60x270 note61x85 note62x913 note63x728 note64x543 note65x358 note66x173 note67x1001 note68x816 note69x631 note70x446 note71x261 note72x76 note73x904 note74x719 note75x534 note76x349 note77x164 note78x992 note79x807 note80x622 note81x437 note82x252 note83x67 note84x895 note85x710 note86x525 note87x340 note88x155 note0x983 note1x798 note2x613 note3x428 note4x243 note5x58 note6x886 note7x701 note8x516 note9x331 note10x146 note11x974 note12x789 note13x604 note14x419 note15x234 note16x49 note17x877 note18x692 note19x507 note20x322 note21x137 note22x965 note23x780 note24x595 note25x410 note26x225 note27x40 note28x868 note29x683 note30x498 note31x313 note32x128 note33x956 note34x771 note35x586 note36x401 note37x216 note38x31 note39x859 note40x674 note41x489 note42x304 note43x119 note44x947 note45x762 note46x577 note47x392 note48x207 note49x22 note50x850 note51x665 note52x480 note53x295 note54x110 note55x938 note56x753 note57x568 note58x383 note59x198 note60x13 note61x841 note62x656 note63x471 note64x286 note65x101 note66x929 note67x744 note68x559 note69x374 note70x189 note71x4 note72x832 note73x647 note74x462 note75x277 note76x92 note77x920 note78x735 note79x550 note80x365 note81x180 note82x1008 note83x823 note84x638 note85x453 note86x268 note87x83 note88x911 note0x726 note1x541 note2x356 note3x171 note4x999 note5x814 note6x629 note7x444 note8x259 note9x74 note10x902 note11x717 note12x532 note13x347 note14x162 note15x990 note16x805 note17x620 note18x435 note19x250 note20x65 note21x893 note22x708 note23x523 note24x338 note25x153 note26x981 note27x796 note28x611 note29x426 note30x241 note31x56 note32x884 note33x699 note34x514 note35x329 note36x144 note37x972 note38x787 note39x602 note40x417 note41x232 note42x47 note43x875 note44x690 note45x505 note46x320 note47x135 note48x963 note49x778 note50x593 note51x408 note52x223 note53x38 note54x866 note55x681 note56x496 note57x311 note58x126 note59x954 note60x769 note61x584 note62x399 note63x214 note64x29 note65x857 note66x672 note67x487 note68x302 note69x117 note70x945 note71x760 note72x575 note73x390 note74x205 note75x20 note76x848 note77x663 note78x478 note79x293 note80x108 note81x936 note82x751 note83x566 note84x381 note85x196 note86x11 note87x839 note88x654 note0x469 note1x284 note2x99 note3x927 note4x742 note5x557 note6x372 note7x187 note8x2 note9x830 note10x645 note11x460 note12x275 note13x90 note14x918 note15x733 note16x548 note17x363 note18x178 note19x1006 note20x821 note21x636 note22x451 note23x266 note24x81 note25x909 note26x724 note27x539 note28x354 note29x169 note30x997 note31x812 note32x627 note33x442 note34x257 note35x72 note36x900 note37x715 note38x530 note39x345 note40x160 note41x988 note42x803 note43x618 note44x433 note45x248 note46x63 note47x891 note48x706 note49x521 note50x336 note51x151 note52x979 note53x794 note54x609 note55x424 note56x239 note57x54 note58x882 note59x697 note60x512 note61x327 note62x142 note63x970 note64x785 note65x600 note66x415 note67x230 note68x45 note69x873 note70x688 note71x503 note72x318 note73x133 note74x961 note75x776 note76x591 note77x406 note78x221 note79x36 note80x864 note81x679 note82x494 note83x309 note84x124 note85x952 note86x767 note87x582 note88x397 note0x212 note1x27 note2x855 note3x670 note4x485 note5x300 note6x115 note7x943 note8x758 note9x573 note10x388 note11x203 note12x18 note13x846 note14x661 note15x476 note16x291 note17x106 note18x934 note19x749 note20x564 note21x379 note22x194 note23x9 note24x837 note25x652 note26x467 note27x282 note28x97 note29x925 note30x740 note31x555 note32x370 note33x185 note34x0 note35x828 note36x643 note37x458 note38x273 note39x88 note40x916 note41x731 note42x546 note43x361 note44x176 note45x1004 note46x819 note47x634 note48x449 note49x264 note50x79 note51x907 note52x722 note53x537 note54x352 note55x167 note56x995 note57x810 note58x625 note59x440 note60x255 note61x70 note62x898 note63x713 note64x528 note65x343 note66x158 note67x986 note68x801 note69x616 note70x431 note71x246 note72x61 note73x889 note74x704 note75x519 note76x334 note77x149 note78x977 note79x792 note80x607 note81x422 note82x237 note83x52 note84x880 note85x695 note86x510 note87x325 note88x140 note0x968 note1x783 note2x598 note3x413 note4x228 note5x43 note6x871 note7x686 note8x501 note9x316 note10x131 note11x959 note12x774 note13x589 note14x404 note15x219 note16x34 note17x862 note18x677 note19x492 note20x307 note21x122 note22x950 note23x765 note24x580 note25x395 note26x210 note27x25 note28x853 note29x668 note30x483 note31x298 note32x113 note33x941 note34x756 note35x571 note36x386 note37x201 note38x16 note39x844 note40x659 note41x474 note42x289 note43x104 note44x932 note45x747 note46x562 note47x377 note48x192 note49x7 note50x835 note51x650 note52x465 note53x280 note54x95 note55x923 note56x738 note57x553 note58x368 note59x183 note60x1011 note61x826 note62x641 note63x456 note64x271 note65x86 note66x914 note67x729 note68x544 note69x359 note70x174 note71x1002 note72x817 note73x632 note74x447 note75x262 note76x77 note77x905 note78x720 note79x535 note80x350 note81x165 note82x993 note83x808 note84x623 note85x438 note86x253 note87x68 note88x896 note0x711 note1x526 note2x341 note3x156 note4x984 note5x799 note6x614 note7x429 note8x244 note9x59 note10x887 note11x702 note12x517 note13x332 note14x147 note15x975 note16x790 note17x605 note18x420 note19x235 note20x50 note21x878 note22x693 note23x508 note24x323 note25x138 note26x966 note27x781 note28x596 note29x411 note30x226 note31x41 note32x869 note33x684 note34x499 note35x314 note36x129 note37x957 note38x772 note39x587 note40x402 note41x217 note42x32 note43x860 note44x675 note45x490 note46x305 note47x120 note48x948 note49x763 note50x578 note51x393 note52x208 note53x23 note54x851 note55x666 note56x481 note57x296 note58x111 note59x939 note60x754 note61x569 note62x384 note63x199 note64x14 note65x842 note66x657 note67x472 note68x287 note69x102 note70x930 note71x745 note72x560 note73x375 note74x190 note75x5 note76x833 note77x648 note78x463 note79x278 note80x93 note81x921 note82x736 note83x551 note84x366 note85x181 note86x1009 note87x824 note88x639 note0x454 note1x269 note2x84 note3x912 note4x727 note5x542 note6x357 note7x172 note8x1000 note9x815 note10x630 note11x445 note12x260 note13x75 note14x903 note15x718 note16x533 note17x348 note18x163 note19x991 note20x806 note21x621 note22x436 note23x251 note24x66 note25x894 note26x709 note27x524 note28x339 note29x154 note30x982 note31x797 note32x612 note33x427 note34x242 note35x57 note36x885 note37x700 note38x515 note39x330 note40x145 note41x973 note42x788 note43x603 note44x418 note45x233 note46x48 note47x876 note48x691 note49x506 note50x321 note51x136 note52x964 note53x779 note54x594 note55x409 note56x224 note57x39 note58x867 note59x682 note60x497 note61x312 note62x127 note63x955 note64x770 note65x585 note66x400 note67x215 note68x30 note69x858 note70x673 note71x488 note72x303 note73x118 note74x946 note75x761 note76x576 note77x391 note78x206 note79x21 note80x849 note81x664 note82x479 note83x294 note84x109 note85x937 note86x752 note87x567 note88x382 note0x197 note1x12 note2x840 note3x655 note4x470 note5x285 note6x100 note7x928 note8x743 note9x558 note10x373 note11x188 note12x3 note13x831 note14x646 note15x461 note16x276 note17x91 note18x919 note19x734 note20x549 note21x364 note22x179 note23x1007 note24x822 note25x637 note26x452 note27x267 note28x82 note29x910 note30x725 note31x540 note32x355 note33x170 note34x998 note35x813 note36x628 note37x443 note38x258 note39x73 note40x901 note41x716 note42x531 note43x346 note44x161 note45x989 note46x804 note47x619 note48x434 note49x249 note50x64 note51x892 note52x707 note53x522 note54x337 note55x152 note56x980 note57x795 note58x610 note59x425 note60x240 note61x55 note62x883 note63x698 note64x513 note65x328 note66x143 note67x971 note68x786 note69x601 note70x416 note71x231 note72x46 note73x874 note74x689 note75x504 note76x319 note77x134 note78x962 note79x777 note80x592 note81x407 note82x222 note83x37 note84x865 note85x680 note86x495 note87x310 note88x125 note0x953 note1x768 note2x583 note3x398 note4x213 note5x28 note6x856 note7x671 note8x486 note9x301 note10x116 note11x944 note12x759 note13x574 note14x389 note15x204 note16x19 note17x847 note18x662 note19x477 note20x292 note21x107 note22x935 note23x750 note24x565 note25x380 note26x195 note27x10 note28x838 note29x653 note30x468 note31x283 note32x98 note33x926 note34x741 note35x556 note36x371 note37x186 note38x1 note39x829 note40x644 note41x459 note42x274 note43x89 note44x917 note45x732 note46x547 note47x362 note48x177 note49x1005 note50x820 note51x635 note52x450 note53x265 note54x80 note55x908 note56x723 note57x538 note58x353 note59x168 note60x996 note61x811 note62x626 note63x441 note64x256 note65x71 note66x899 note67x714 note68x529 note69x344 note70x159 note71x987 note72x802 note73x617 note74x432 note75x247"}, {"role": "user", "content": "What is the first note?"}, {"role": "assistant", "content": "The first note is **note0x0**."}, {"role": "user", "content": "And the second one?"}, {"role": "assistant", "content": "The second note is **note1x828**."}, {"role": "user", "content": "Is note5x5 listed?"}], "max_tokens": 48, "temperature": 0.0, "draft": true, "chat_template_kwargs": {"enable_thinking": false}}, "status": 200, "response": {"id": "chatcmpl-877f0e40877a72d37d30bab565dc7805", "object": "chat.completion", "created": 1793474496, "model": "flashnext", "choices": [{"index": 0, "message": {"role": "assistant", "content": "No, **note5x5** is not listed in the provided reference notes.\n\nThe list contains notes with hex suffixes (e.g., `note5x88`, `note5x587`, `note5"}, "finish_reason": "length"}], "usage": {"prompt_tokens": 10281, "completion_tokens": 48, "total_tokens": 10329, "prompt_tokens_details": {"cached_tokens": 10240}, "completion_tokens_details": {"reasoning_tokens": 0}}, "exact_mode": "exact", "tensorfold": {"enable_thinking": false, "reasoning_effort": "none", "engine": "lanes", "tokens_per_second": 52.216713939087356, "seconds": 0.90009494, "prefill_seconds": 0.256253668, "prefill_widths": [], "prefill_raised": [], "time_to_first_token": 0.257270982, "sampling": "greedy", "drafts": true, "token_sha": "e7287d6bf366", "token_sha256": "e7287d6bf36620acbd71b1537e7b5ea9b239198191676c8c2261aad653c64a81", "min_rows": 2}, "speculative": {"rounds": 17, "drafted": 40, "accepted": 31, "acceptance_rate": 0.775, "tokens_per_round": 2.823529411764706}}, "seconds": 1.158210039138794} +{"url": "http://127.0.0.1:30461/v1/chat/completions", "request": {"model": "flashnext", "messages": [{"role": "system", "content": "You are a careful assistant. Reference notes: note0x0 note1x828 note2x643 note3x458 note4x273 note5x88 note6x916 note7x731 note8x546 note9x361 note10x176 note11x1004 note12x819 note13x634 note14x449 note15x264 note16x79 note17x907 note18x722 note19x537 note20x352 note21x167 note22x995 note23x810 note24x625 note25x440 note26x255 note27x70 note28x898 note29x713 note30x528 note31x343 note32x158 note33x986 note34x801 note35x616 note36x431 note37x246 note38x61 note39x889 note40x704 note41x519 note42x334 note43x149 note44x977 note45x792 note46x607 note47x422 note48x237 note49x52 note50x880 note51x695 note52x510 note53x325 note54x140 note55x968 note56x783 note57x598 note58x413 note59x228 note60x43 note61x871 note62x686 note63x501 note64x316 note65x131 note66x959 note67x774 note68x589 note69x404 note70x219 note71x34 note72x862 note73x677 note74x492 note75x307 note76x122 note77x950 note78x765 note79x580 note80x395 note81x210 note82x25 note83x853 note84x668 note85x483 note86x298 note87x113 note88x941 note0x756 note1x571 note2x386 note3x201 note4x16 note5x844 note6x659 note7x474 note8x289 note9x104 note10x932 note11x747 note12x562 note13x377 note14x192 note15x7 note16x835 note17x650 note18x465 note19x280 note20x95 note21x923 note22x738 note23x553 note24x368 note25x183 note26x1011 note27x826 note28x641 note29x456 note30x271 note31x86 note32x914 note33x729 note34x544 note35x359 note36x174 note37x1002 note38x817 note39x632 note40x447 note41x262 note42x77 note43x905 note44x720 note45x535 note46x350 note47x165 note48x993 note49x808 note50x623 note51x438 note52x253 note53x68 note54x896 note55x711 note56x526 note57x341 note58x156 note59x984 note60x799 note61x614 note62x429 note63x244 note64x59 note65x887 note66x702 note67x517 note68x332 note69x147 note70x975 note71x790 note72x605 note73x420 note74x235 note75x50 note76x878 note77x693 note78x508 note79x323 note80x138 note81x966 note82x781 note83x596 note84x411 note85x226 note86x41 note87x869 note88x684 note0x499 note1x314 note2x129 note3x957 note4x772 note5x587 note6x402 note7x217 note8x32 note9x860 note10x675 note11x490 note12x305 note13x120 note14x948 note15x763 note16x578 note17x393 note18x208 note19x23 note20x851 note21x666 note22x481 note23x296 note24x111 note25x939 note26x754 note27x569 note28x384 note29x199 note30x14 note31x842 note32x657 note33x472 note34x287 note35x102 note36x930 note37x745 note38x560 note39x375 note40x190 note41x5 note42x833 note43x648 note44x463 note45x278 note46x93 note47x921 note48x736 note49x551 note50x366 note51x181 note52x1009 note53x824 note54x639 note55x454 note56x269 note57x84 note58x912 note59x727 note60x542 note61x357 note62x172 note63x1000 note64x815 note65x630 note66x445 note67x260 note68x75 note69x903 note70x718 note71x533 note72x348 note73x163 note74x991 note75x806 note76x621 note77x436 note78x251 note79x66 note80x894 note81x709 note82x524 note83x339 note84x154 note85x982 note86x797 note87x612 note88x427 note0x242 note1x57 note2x885 note3x700 note4x515 note5x330 note6x145 note7x973 note8x788 note9x603 note10x418 note11x233 note12x48 note13x876 note14x691 note15x506 note16x321 note17x136 note18x964 note19x779 note20x594 note21x409 note22x224 note23x39 note24x867 note25x682 note26x497 note27x312 note28x127 note29x955 note30x770 note31x585 note32x400 note33x215 note34x30 note35x858 note36x673 note37x488 note38x303 note39x118 note40x946 note41x761 note42x576 note43x391 note44x206 note45x21 note46x849 note47x664 note48x479 note49x294 note50x109 note51x937 note52x752 note53x567 note54x382 note55x197 note56x12 note57x840 note58x655 note59x470 note60x285 note61x100 note62x928 note63x743 note64x558 note65x373 note66x188 note67x3 note68x831 note69x646 note70x461 note71x276 note72x91 note73x919 note74x734 note75x549 note76x364 note77x179 note78x1007 note79x822 note80x637 note81x452 note82x267 note83x82 note84x910 note85x725 note86x540 note87x355 note88x170 note0x998 note1x813 note2x628 note3x443 note4x258 note5x73 note6x901 note7x716 note8x531 note9x346 note10x161 note11x989 note12x804 note13x619 note14x434 note15x249 note16x64 note17x892 note18x707 note19x522 note20x337 note21x152 note22x980 note23x795 note24x610 note25x425 note26x240 note27x55 note28x883 note29x698 note30x513 note31x328 note32x143 note33x971 note34x786 note35x601 note36x416 note37x231 note38x46 note39x874 note40x689 note41x504 note42x319 note43x134 note44x962 note45x777 note46x592 note47x407 note48x222 note49x37 note50x865 note51x680 note52x495 note53x310 note54x125 note55x953 note56x768 note57x583 note58x398 note59x213 note60x28 note61x856 note62x671 note63x486 note64x301 note65x116 note66x944 note67x759 note68x574 note69x389 note70x204 note71x19 note72x847 note73x662 note74x477 note75x292 note76x107 note77x935 note78x750 note79x565 note80x380 note81x195 note82x10 note83x838 note84x653 note85x468 note86x283 note87x98 note88x926 note0x741 note1x556 note2x371 note3x186 note4x1 note5x829 note6x644 note7x459 note8x274 note9x89 note10x917 note11x732 note12x547 note13x362 note14x177 note15x1005 note16x820 note17x635 note18x450 note19x265 note20x80 note21x908 note22x723 note23x538 note24x353 note25x168 note26x996 note27x811 note28x626 note29x441 note30x256 note31x71 note32x899 note33x714 note34x529 note35x344 note36x159 note37x987 note38x802 note39x617 note40x432 note41x247 note42x62 note43x890 note44x705 note45x520 note46x335 note47x150 note48x978 note49x793 note50x608 note51x423 note52x238 note53x53 note54x881 note55x696 note56x511 note57x326 note58x141 note59x969 note60x784 note61x599 note62x414 note63x229 note64x44 note65x872 note66x687 note67x502 note68x317 note69x132 note70x960 note71x775 note72x590 note73x405 note74x220 note75x35 note76x863 note77x678 note78x493 note79x308 note80x123 note81x951 note82x766 note83x581 note84x396 note85x211 note86x26 note87x854 note88x669 note0x484 note1x299 note2x114 note3x942 note4x757 note5x572 note6x387 note7x202 note8x17 note9x845 note10x660 note11x475 note12x290 note13x105 note14x933 note15x748 note16x563 note17x378 note18x193 note19x8 note20x836 note21x651 note22x466 note23x281 note24x96 note25x924 note26x739 note27x554 note28x369 note29x184 note30x1012 note31x827 note32x642 note33x457 note34x272 note35x87 note36x915 note37x730 note38x545 note39x360 note40x175 note41x1003 note42x818 note43x633 note44x448 note45x263 note46x78 note47x906 note48x721 note49x536 note50x351 note51x166 note52x994 note53x809 note54x624 note55x439 note56x254 note57x69 note58x897 note59x712 note60x527 note61x342 note62x157 note63x985 note64x800 note65x615 note66x430 note67x245 note68x60 note69x888 note70x703 note71x518 note72x333 note73x148 note74x976 note75x791 note76x606 note77x421 note78x236 note79x51 note80x879 note81x694 note82x509 note83x324 note84x139 note85x967 note86x782 note87x597 note88x412 note0x227 note1x42 note2x870 note3x685 note4x500 note5x315 note6x130 note7x958 note8x773 note9x588 note10x403 note11x218 note12x33 note13x861 note14x676 note15x491 note16x306 note17x121 note18x949 note19x764 note20x579 note21x394 note22x209 note23x24 note24x852 note25x667 note26x482 note27x297 note28x112 note29x940 note30x755 note31x570 note32x385 note33x200 note34x15 note35x843 note36x658 note37x473 note38x288 note39x103 note40x931 note41x746 note42x561 note43x376 note44x191 note45x6 note46x834 note47x649 note48x464 note49x279 note50x94 note51x922 note52x737 note53x552 note54x367 note55x182 note56x1010 note57x825 note58x640 note59x455 note60x270 note61x85 note62x913 note63x728 note64x543 note65x358 note66x173 note67x1001 note68x816 note69x631 note70x446 note71x261 note72x76 note73x904 note74x719 note75x534 note76x349 note77x164 note78x992 note79x807 note80x622 note81x437 note82x252 note83x67 note84x895 note85x710 note86x525 note87x340 note88x155 note0x983 note1x798 note2x613 note3x428 note4x243 note5x58 note6x886 note7x701 note8x516 note9x331 note10x146 note11x974 note12x789 note13x604 note14x419 note15x234 note16x49 note17x877 note18x692 note19x507 note20x322 note21x137 note22x965 note23x780 note24x595 note25x410 note26x225 note27x40 note28x868 note29x683 note30x498 note31x313 note32x128 note33x956 note34x771 note35x586 note36x401 note37x216 note38x31 note39x859 note40x674 note41x489 note42x304 note43x119 note44x947 note45x762 note46x577 note47x392 note48x207 note49x22 note50x850 note51x665 note52x480 note53x295 note54x110 note55x938 note56x753 note57x568 note58x383 note59x198 note60x13 note61x841 note62x656 note63x471 note64x286 note65x101 note66x929 note67x744 note68x559 note69x374 note70x189 note71x4 note72x832 note73x647 note74x462 note75x277 note76x92 note77x920 note78x735 note79x550 note80x365 note81x180 note82x1008 note83x823 note84x638 note85x453 note86x268 note87x83 note88x911 note0x726 note1x541 note2x356 note3x171 note4x999 note5x814 note6x629 note7x444 note8x259 note9x74 note10x902 note11x717 note12x532 note13x347 note14x162 note15x990 note16x805 note17x620 note18x435 note19x250 note20x65 note21x893 note22x708 note23x523 note24x338 note25x153 note26x981 note27x796 note28x611 note29x426 note30x241 note31x56 note32x884 note33x699 note34x514 note35x329 note36x144 note37x972 note38x787 note39x602 note40x417 note41x232 note42x47 note43x875 note44x690 note45x505 note46x320 note47x135 note48x963 note49x778 note50x593 note51x408 note52x223 note53x38 note54x866 note55x681 note56x496 note57x311 note58x126 note59x954 note60x769 note61x584 note62x399 note63x214 note64x29 note65x857 note66x672 note67x487 note68x302 note69x117 note70x945 note71x760 note72x575 note73x390 note74x205 note75x20 note76x848 note77x663 note78x478 note79x293 note80x108 note81x936 note82x751 note83x566 note84x381 note85x196 note86x11 note87x839 note88x654 note0x469 note1x284 note2x99 note3x927 note4x742 note5x557 note6x372 note7x187 note8x2 note9x830 note10x645 note11x460 note12x275 note13x90 note14x918 note15x733 note16x548 note17x363 note18x178 note19x1006 note20x821 note21x636 note22x451 note23x266 note24x81 note25x909 note26x724 note27x539 note28x354 note29x169 note30x997 note31x812 note32x627 note33x442 note34x257 note35x72 note36x900 note37x715 note38x530 note39x345 note40x160 note41x988 note42x803 note43x618 note44x433 note45x248 note46x63 note47x891 note48x706 note49x521 note50x336 note51x151 note52x979 note53x794 note54x609 note55x424 note56x239 note57x54 note58x882 note59x697 note60x512 note61x327 note62x142 note63x970 note64x785 note65x600 note66x415 note67x230 note68x45 note69x873 note70x688 note71x503 note72x318 note73x133 note74x961 note75x776 note76x591 note77x406 note78x221 note79x36 note80x864 note81x679 note82x494 note83x309 note84x124 note85x952 note86x767 note87x582 note88x397 note0x212 note1x27 note2x855 note3x670 note4x485 note5x300 note6x115 note7x943 note8x758 note9x573 note10x388 note11x203 note12x18 note13x846 note14x661 note15x476 note16x291 note17x106 note18x934 note19x749 note20x564 note21x379 note22x194 note23x9 note24x837 note25x652 note26x467 note27x282 note28x97 note29x925 note30x740 note31x555 note32x370 note33x185 note34x0 note35x828 note36x643 note37x458 note38x273 note39x88 note40x916 note41x731 note42x546 note43x361 note44x176 note45x1004 note46x819 note47x634 note48x449 note49x264 note50x79 note51x907 note52x722 note53x537 note54x352 note55x167 note56x995 note57x810 note58x625 note59x440 note60x255 note61x70 note62x898 note63x713 note64x528 note65x343 note66x158 note67x986 note68x801 note69x616 note70x431 note71x246 note72x61 note73x889 note74x704 note75x519 note76x334 note77x149 note78x977 note79x792 note80x607 note81x422 note82x237 note83x52 note84x880 note85x695 note86x510 note87x325 note88x140 note0x968 note1x783 note2x598 note3x413 note4x228 note5x43 note6x871 note7x686 note8x501 note9x316 note10x131 note11x959 note12x774 note13x589 note14x404 note15x219 note16x34 note17x862 note18x677 note19x492 note20x307 note21x122 note22x950 note23x765 note24x580 note25x395 note26x210 note27x25 note28x853 note29x668 note30x483 note31x298 note32x113 note33x941 note34x756 note35x571 note36x386 note37x201 note38x16 note39x844 note40x659 note41x474 note42x289 note43x104 note44x932 note45x747 note46x562 note47x377 note48x192 note49x7 note50x835 note51x650 note52x465 note53x280 note54x95 note55x923 note56x738 note57x553 note58x368 note59x183 note60x1011 note61x826 note62x641 note63x456 note64x271 note65x86 note66x914 note67x729 note68x544 note69x359 note70x174 note71x1002 note72x817 note73x632 note74x447 note75x262 note76x77 note77x905 note78x720 note79x535 note80x350 note81x165 note82x993 note83x808 note84x623 note85x438 note86x253 note87x68 note88x896 note0x711 note1x526 note2x341 note3x156 note4x984 note5x799 note6x614 note7x429 note8x244 note9x59 note10x887 note11x702 note12x517 note13x332 note14x147 note15x975 note16x790 note17x605 note18x420 note19x235 note20x50 note21x878 note22x693 note23x508 note24x323 note25x138 note26x966 note27x781 note28x596 note29x411 note30x226 note31x41 note32x869 note33x684 note34x499 note35x314 note36x129 note37x957 note38x772 note39x587 note40x402 note41x217 note42x32 note43x860 note44x675 note45x490 note46x305 note47x120 note48x948 note49x763 note50x578 note51x393 note52x208 note53x23 note54x851 note55x666 note56x481 note57x296 note58x111 note59x939 note60x754 note61x569 note62x384 note63x199 note64x14 note65x842 note66x657 note67x472 note68x287 note69x102 note70x930 note71x745 note72x560 note73x375 note74x190 note75x5 note76x833 note77x648 note78x463 note79x278 note80x93 note81x921 note82x736 note83x551 note84x366 note85x181 note86x1009 note87x824 note88x639 note0x454 note1x269 note2x84 note3x912 note4x727 note5x542 note6x357 note7x172 note8x1000 note9x815 note10x630 note11x445 note12x260 note13x75 note14x903 note15x718 note16x533 note17x348 note18x163 note19x991 note20x806 note21x621 note22x436 note23x251 note24x66 note25x894 note26x709 note27x524 note28x339 note29x154 note30x982 note31x797 note32x612 note33x427 note34x242 note35x57 note36x885 note37x700 note38x515 note39x330 note40x145 note41x973 note42x788 note43x603 note44x418 note45x233 note46x48 note47x876 note48x691 note49x506 note50x321 note51x136 note52x964 note53x779 note54x594 note55x409 note56x224 note57x39 note58x867 note59x682 note60x497 note61x312 note62x127 note63x955 note64x770 note65x585 note66x400 note67x215 note68x30 note69x858 note70x673 note71x488 note72x303 note73x118 note74x946 note75x761 note76x576 note77x391 note78x206 note79x21 note80x849 note81x664 note82x479 note83x294 note84x109 note85x937 note86x752 note87x567 note88x382 note0x197 note1x12 note2x840 note3x655 note4x470 note5x285 note6x100 note7x928 note8x743 note9x558 note10x373 note11x188 note12x3 note13x831 note14x646 note15x461 note16x276 note17x91 note18x919 note19x734 note20x549 note21x364 note22x179 note23x1007 note24x822 note25x637 note26x452 note27x267 note28x82 note29x910 note30x725 note31x540 note32x355 note33x170 note34x998 note35x813 note36x628 note37x443 note38x258 note39x73 note40x901 note41x716 note42x531 note43x346 note44x161 note45x989 note46x804 note47x619 note48x434 note49x249 note50x64 note51x892 note52x707 note53x522 note54x337 note55x152 note56x980 note57x795 note58x610 note59x425 note60x240 note61x55 note62x883 note63x698 note64x513 note65x328 note66x143 note67x971 note68x786 note69x601 note70x416 note71x231 note72x46 note73x874 note74x689 note75x504 note76x319 note77x134 note78x962 note79x777 note80x592 note81x407 note82x222 note83x37 note84x865 note85x680 note86x495 note87x310 note88x125 note0x953 note1x768 note2x583 note3x398 note4x213 note5x28 note6x856 note7x671 note8x486 note9x301 note10x116 note11x944 note12x759 note13x574 note14x389 note15x204 note16x19 note17x847 note18x662 note19x477 note20x292 note21x107 note22x935 note23x750 note24x565 note25x380 note26x195 note27x10 note28x838 note29x653 note30x468 note31x283 note32x98 note33x926 note34x741 note35x556 note36x371 note37x186 note38x1 note39x829 note40x644 note41x459 note42x274 note43x89 note44x917 note45x732 note46x547 note47x362 note48x177 note49x1005 note50x820 note51x635 note52x450 note53x265 note54x80 note55x908 note56x723 note57x538 note58x353 note59x168 note60x996 note61x811 note62x626 note63x441 note64x256 note65x71 note66x899 note67x714 note68x529 note69x344 note70x159 note71x987 note72x802 note73x617 note74x432 note75x247"}, {"role": "user", "content": "What is the first note?"}, {"role": "assistant", "content": "The first note is **note0x0**."}, {"role": "user", "content": "And the second one?"}, {"role": "assistant", "content": "The second note is **note1x828**."}, {"role": "user", "content": "Is note7x7 listed?"}], "max_tokens": 48, "temperature": 0.0, "draft": true, "chat_template_kwargs": {"enable_thinking": false}}, "status": 200, "response": {"id": "chatcmpl-97ce141868346f553bb93c1abfea9db8", "object": "chat.completion", "created": 1793474497, "model": "flashnext", "choices": [{"index": 0, "message": {"role": "assistant", "content": "No, **note7x7** is not listed in the provided reference notes.\n\nThe notes follow a pattern where the second part (after the 'x') is a hexadecimal number (e.g., `note1x828"}, "finish_reason": "length"}], "usage": {"prompt_tokens": 10281, "completion_tokens": 48, "total_tokens": 10329, "prompt_tokens_details": {"cached_tokens": 10240}, "completion_tokens_details": {"reasoning_tokens": 0}}, "exact_mode": "exact", "tensorfold": {"enable_thinking": false, "reasoning_effort": "none", "engine": "lanes", "tokens_per_second": 48.49789967927338, "seconds": 0.969114133, "prefill_seconds": 0.256325342, "prefill_widths": [], "prefill_raised": [], "time_to_first_token": 0.257073943, "sampling": "greedy", "drafts": true, "token_sha": "55e1d46d0689", "token_sha256": "55e1d46d06891dff37e5a39f83ae22514ba7952a98a301c70166bbb637c3f3b6", "min_rows": 2}, "speculative": {"rounds": 21, "drafted": 41, "accepted": 27, "acceptance_rate": 0.6585365853658537, "tokens_per_round": 2.2857142857142856}}, "seconds": 1.2270569801330566} +{"url": "http://127.0.0.1:30461/v1/chat/completions", "request": {"model": "flashnext", "messages": [{"role": "system", "content": "You are a careful assistant. Reference notes: note0x0 note1x828 note2x643 note3x458 note4x273 note5x88 note6x916 note7x731 note8x546 note9x361 note10x176 note11x1004 note12x819 note13x634 note14x449 note15x264 note16x79 note17x907 note18x722 note19x537 note20x352 note21x167 note22x995 note23x810 note24x625 note25x440 note26x255 note27x70 note28x898 note29x713 note30x528 note31x343 note32x158 note33x986 note34x801 note35x616 note36x431 note37x246 note38x61 note39x889 note40x704 note41x519 note42x334 note43x149 note44x977 note45x792 note46x607 note47x422 note48x237 note49x52 note50x880 note51x695 note52x510 note53x325 note54x140 note55x968 note56x783 note57x598 note58x413 note59x228 note60x43 note61x871 note62x686 note63x501 note64x316 note65x131 note66x959 note67x774 note68x589 note69x404 note70x219 note71x34 note72x862 note73x677 note74x492 note75x307 note76x122 note77x950 note78x765 note79x580 note80x395 note81x210 note82x25 note83x853 note84x668 note85x483 note86x298 note87x113 note88x941 note0x756 note1x571 note2x386 note3x201 note4x16 note5x844 note6x659 note7x474 note8x289 note9x104 note10x932 note11x747 note12x562 note13x377 note14x192 note15x7 note16x835 note17x650 note18x465 note19x280 note20x95 note21x923 note22x738 note23x553 note24x368 note25x183 note26x1011 note27x826 note28x641 note29x456 note30x271 note31x86 note32x914 note33x729 note34x544 note35x359 note36x174 note37x1002 note38x817 note39x632 note40x447 note41x262 note42x77 note43x905 note44x720 note45x535 note46x350 note47x165 note48x993 note49x808 note50x623 note51x438 note52x253 note53x68 note54x896 note55x711 note56x526 note57x341 note58x156 note59x984 note60x799 note61x614 note62x429 note63x244 note64x59 note65x887 note66x702 note67x517 note68x332 note69x147 note70x975 note71x790 note72x605 note73x420 note74x235 note75x50 note76x878 note77x693 note78x508 note79x323 note80x138 note81x966 note82x781 note83x596 note84x411 note85x226 note86x41 note87x869 note88x684 note0x499 note1x314 note2x129 note3x957 note4x772 note5x587 note6x402 note7x217 note8x32 note9x860 note10x675 note11x490 note12x305 note13x120 note14x948 note15x763 note16x578 note17x393 note18x208 note19x23 note20x851 note21x666 note22x481 note23x296 note24x111 note25x939 note26x754 note27x569 note28x384 note29x199 note30x14 note31x842 note32x657 note33x472 note34x287 note35x102 note36x930 note37x745 note38x560 note39x375 note40x190 note41x5 note42x833 note43x648 note44x463 note45x278 note46x93 note47x921 note48x736 note49x551 note50x366 note51x181 note52x1009 note53x824 note54x639 note55x454 note56x269 note57x84 note58x912 note59x727 note60x542 note61x357 note62x172 note63x1000 note64x815 note65x630 note66x445 note67x260 note68x75 note69x903 note70x718 note71x533 note72x348 note73x163 note74x991 note75x806 note76x621 note77x436 note78x251 note79x66 note80x894 note81x709 note82x524 note83x339 note84x154 note85x982 note86x797 note87x612 note88x427 note0x242 note1x57 note2x885 note3x700 note4x515 note5x330 note6x145 note7x973 note8x788 note9x603 note10x418 note11x233 note12x48 note13x876 note14x691 note15x506 note16x321 note17x136 note18x964 note19x779 note20x594 note21x409 note22x224 note23x39 note24x867 note25x682 note26x497 note27x312 note28x127 note29x955 note30x770 note31x585 note32x400 note33x215 note34x30 note35x858 note36x673 note37x488 note38x303 note39x118 note40x946 note41x761 note42x576 note43x391 note44x206 note45x21 note46x849 note47x664 note48x479 note49x294 note50x109 note51x937 note52x752 note53x567 note54x382 note55x197 note56x12 note57x840 note58x655 note59x470 note60x285 note61x100 note62x928 note63x743 note64x558 note65x373 note66x188 note67x3 note68x831 note69x646 note70x461 note71x276 note72x91 note73x919 note74x734 note75x549 note76x364 note77x179 note78x1007 note79x822 note80x637 note81x452 note82x267 note83x82 note84x910 note85x725 note86x540 note87x355 note88x170 note0x998 note1x813 note2x628 note3x443 note4x258 note5x73 note6x901 note7x716 note8x531 note9x346 note10x161 note11x989 note12x804 note13x619 note14x434 note15x249 note16x64 note17x892 note18x707 note19x522 note20x337 note21x152 note22x980 note23x795 note24x610 note25x425 note26x240 note27x55 note28x883 note29x698 note30x513 note31x328 note32x143 note33x971 note34x786 note35x601 note36x416 note37x231 note38x46 note39x874 note40x689 note41x504 note42x319 note43x134 note44x962 note45x777 note46x592 note47x407 note48x222 note49x37 note50x865 note51x680 note52x495 note53x310 note54x125 note55x953 note56x768 note57x583 note58x398 note59x213 note60x28 note61x856 note62x671 note63x486 note64x301 note65x116 note66x944 note67x759 note68x574 note69x389 note70x204 note71x19 note72x847 note73x662 note74x477 note75x292 note76x107 note77x935 note78x750 note79x565 note80x380 note81x195 note82x10 note83x838 note84x653 note85x468 note86x283 note87x98 note88x926 note0x741 note1x556 note2x371 note3x186 note4x1 note5x829 note6x644 note7x459 note8x274 note9x89 note10x917 note11x732 note12x547 note13x362 note14x177 note15x1005 note16x820 note17x635 note18x450 note19x265 note20x80 note21x908 note22x723 note23x538 note24x353 note25x168 note26x996 note27x811 note28x626 note29x441 note30x256 note31x71 note32x899 note33x714 note34x529 note35x344 note36x159 note37x987 note38x802 note39x617 note40x432 note41x247 note42x62 note43x890 note44x705 note45x520 note46x335 note47x150 note48x978 note49x793 note50x608 note51x423 note52x238 note53x53 note54x881 note55x696 note56x511 note57x326 note58x141 note59x969 note60x784 note61x599 note62x414 note63x229 note64x44 note65x872 note66x687 note67x502 note68x317 note69x132 note70x960 note71x775 note72x590 note73x405 note74x220 note75x35 note76x863 note77x678 note78x493 note79x308 note80x123 note81x951 note82x766 note83x581 note84x396 note85x211 note86x26 note87x854 note88x669 note0x484 note1x299 note2x114 note3x942 note4x757 note5x572 note6x387 note7x202 note8x17 note9x845 note10x660 note11x475 note12x290 note13x105 note14x933 note15x748 note16x563 note17x378 note18x193 note19x8 note20x836 note21x651 note22x466 note23x281 note24x96 note25x924 note26x739 note27x554 note28x369 note29x184 note30x1012 note31x827 note32x642 note33x457 note34x272 note35x87 note36x915 note37x730 note38x545 note39x360 note40x175 note41x1003 note42x818 note43x633 note44x448 note45x263 note46x78 note47x906 note48x721 note49x536 note50x351 note51x166 note52x994 note53x809 note54x624 note55x439 note56x254 note57x69 note58x897 note59x712 note60x527 note61x342 note62x157 note63x985 note64x800 note65x615 note66x430 note67x245 note68x60 note69x888 note70x703 note71x518 note72x333 note73x148 note74x976 note75x791 note76x606 note77x421 note78x236 note79x51 note80x879 note81x694 note82x509 note83x324 note84x139 note85x967 note86x782 note87x597 note88x412 note0x227 note1x42 note2x870 note3x685 note4x500 note5x315 note6x130 note7x958 note8x773 note9x588 note10x403 note11x218 note12x33 note13x861 note14x676 note15x491 note16x306 note17x121 note18x949 note19x764 note20x579 note21x394 note22x209 note23x24 note24x852 note25x667 note26x482 note27x297 note28x112 note29x940 note30x755 note31x570 note32x385 note33x200 note34x15 note35x843 note36x658 note37x473 note38x288 note39x103 note40x931 note41x746 note42x561 note43x376 note44x191 note45x6 note46x834 note47x649 note48x464 note49x279 note50x94 note51x922 note52x737 note53x552 note54x367 note55x182 note56x1010 note57x825 note58x640 note59x455 note60x270 note61x85 note62x913 note63x728 note64x543 note65x358 note66x173 note67x1001 note68x816 note69x631 note70x446 note71x261 note72x76 note73x904 note74x719 note75x534 note76x349 note77x164 note78x992 note79x807 note80x622 note81x437 note82x252 note83x67 note84x895 note85x710 note86x525 note87x340 note88x155 note0x983 note1x798 note2x613 note3x428 note4x243 note5x58 note6x886 note7x701 note8x516 note9x331 note10x146 note11x974 note12x789 note13x604 note14x419 note15x234 note16x49 note17x877 note18x692 note19x507 note20x322 note21x137 note22x965 note23x780 note24x595 note25x410 note26x225 note27x40 note28x868 note29x683 note30x498 note31x313 note32x128 note33x956 note34x771 note35x586 note36x401 note37x216 note38x31 note39x859 note40x674 note41x489 note42x304 note43x119 note44x947 note45x762 note46x577 note47x392 note48x207 note49x22 note50x850 note51x665 note52x480 note53x295 note54x110 note55x938 note56x753 note57x568 note58x383 note59x198 note60x13 note61x841 note62x656 note63x471 note64x286 note65x101 note66x929 note67x744 note68x559 note69x374 note70x189 note71x4 note72x832 note73x647 note74x462 note75x277 note76x92 note77x920 note78x735 note79x550 note80x365 note81x180 note82x1008 note83x823 note84x638 note85x453 note86x268 note87x83 note88x911 note0x726 note1x541 note2x356 note3x171 note4x999 note5x814 note6x629 note7x444 note8x259 note9x74 note10x902 note11x717 note12x532 note13x347 note14x162 note15x990 note16x805 note17x620 note18x435 note19x250 note20x65 note21x893 note22x708 note23x523 note24x338 note25x153 note26x981 note27x796 note28x611 note29x426 note30x241 note31x56 note32x884 note33x699 note34x514 note35x329 note36x144 note37x972 note38x787 note39x602 note40x417 note41x232 note42x47 note43x875 note44x690 note45x505 note46x320 note47x135 note48x963 note49x778 note50x593 note51x408 note52x223 note53x38 note54x866 note55x681 note56x496 note57x311 note58x126 note59x954 note60x769 note61x584 note62x399 note63x214 note64x29 note65x857 note66x672 note67x487 note68x302 note69x117 note70x945 note71x760 note72x575 note73x390 note74x205 note75x20 note76x848 note77x663 note78x478 note79x293 note80x108 note81x936 note82x751 note83x566 note84x381 note85x196 note86x11 note87x839 note88x654 note0x469 note1x284 note2x99 note3x927 note4x742 note5x557 note6x372 note7x187 note8x2 note9x830 note10x645 note11x460 note12x275 note13x90 note14x918 note15x733 note16x548 note17x363 note18x178 note19x1006 note20x821 note21x636 note22x451 note23x266 note24x81 note25x909 note26x724 note27x539 note28x354 note29x169 note30x997 note31x812 note32x627 note33x442 note34x257 note35x72 note36x900 note37x715 note38x530 note39x345 note40x160 note41x988 note42x803 note43x618 note44x433 note45x248 note46x63 note47x891 note48x706 note49x521 note50x336 note51x151 note52x979 note53x794 note54x609 note55x424 note56x239 note57x54 note58x882 note59x697 note60x512 note61x327 note62x142 note63x970 note64x785 note65x600 note66x415 note67x230 note68x45 note69x873 note70x688 note71x503 note72x318 note73x133 note74x961 note75x776 note76x591 note77x406 note78x221 note79x36 note80x864 note81x679 note82x494 note83x309 note84x124 note85x952 note86x767 note87x582 note88x397 note0x212 note1x27 note2x855 note3x670 note4x485 note5x300 note6x115 note7x943 note8x758 note9x573 note10x388 note11x203 note12x18 note13x846 note14x661 note15x476 note16x291 note17x106 note18x934 note19x749 note20x564 note21x379 note22x194 note23x9 note24x837 note25x652 note26x467 note27x282 note28x97 note29x925 note30x740 note31x555 note32x370 note33x185 note34x0 note35x828 note36x643 note37x458 note38x273 note39x88 note40x916 note41x731 note42x546 note43x361 note44x176 note45x1004 note46x819 note47x634 note48x449 note49x264 note50x79 note51x907 note52x722 note53x537 note54x352 note55x167 note56x995 note57x810 note58x625 note59x440 note60x255 note61x70 note62x898 note63x713 note64x528 note65x343 note66x158 note67x986 note68x801 note69x616 note70x431 note71x246 note72x61 note73x889 note74x704 note75x519 note76x334 note77x149 note78x977 note79x792 note80x607 note81x422 note82x237 note83x52 note84x880 note85x695 note86x510 note87x325 note88x140 note0x968 note1x783 note2x598 note3x413 note4x228 note5x43 note6x871 note7x686 note8x501 note9x316 note10x131 note11x959 note12x774 note13x589 note14x404 note15x219 note16x34 note17x862 note18x677 note19x492 note20x307 note21x122 note22x950 note23x765 note24x580 note25x395 note26x210 note27x25 note28x853 note29x668 note30x483 note31x298 note32x113 note33x941 note34x756 note35x571 note36x386 note37x201 note38x16 note39x844 note40x659 note41x474 note42x289 note43x104 note44x932 note45x747 note46x562 note47x377 note48x192 note49x7 note50x835 note51x650 note52x465 note53x280 note54x95 note55x923 note56x738 note57x553 note58x368 note59x183 note60x1011 note61x826 note62x641 note63x456 note64x271 note65x86 note66x914 note67x729 note68x544 note69x359 note70x174 note71x1002 note72x817 note73x632 note74x447 note75x262 note76x77 note77x905 note78x720 note79x535 note80x350 note81x165 note82x993 note83x808 note84x623 note85x438 note86x253 note87x68 note88x896 note0x711 note1x526 note2x341 note3x156 note4x984 note5x799 note6x614 note7x429 note8x244 note9x59 note10x887 note11x702 note12x517 note13x332 note14x147 note15x975 note16x790 note17x605 note18x420 note19x235 note20x50 note21x878 note22x693 note23x508 note24x323 note25x138 note26x966 note27x781 note28x596 note29x411 note30x226 note31x41 note32x869 note33x684 note34x499 note35x314 note36x129 note37x957 note38x772 note39x587 note40x402 note41x217 note42x32 note43x860 note44x675 note45x490 note46x305 note47x120 note48x948 note49x763 note50x578 note51x393 note52x208 note53x23 note54x851 note55x666 note56x481 note57x296 note58x111 note59x939 note60x754 note61x569 note62x384 note63x199 note64x14 note65x842 note66x657 note67x472 note68x287 note69x102 note70x930 note71x745 note72x560 note73x375 note74x190 note75x5 note76x833 note77x648 note78x463 note79x278 note80x93 note81x921 note82x736 note83x551 note84x366 note85x181 note86x1009 note87x824 note88x639 note0x454 note1x269 note2x84 note3x912 note4x727 note5x542 note6x357 note7x172 note8x1000 note9x815 note10x630 note11x445 note12x260 note13x75 note14x903 note15x718 note16x533 note17x348 note18x163 note19x991 note20x806 note21x621 note22x436 note23x251 note24x66 note25x894 note26x709 note27x524 note28x339 note29x154 note30x982 note31x797 note32x612 note33x427 note34x242 note35x57 note36x885 note37x700 note38x515 note39x330 note40x145 note41x973 note42x788 note43x603 note44x418 note45x233 note46x48 note47x876 note48x691 note49x506 note50x321 note51x136 note52x964 note53x779 note54x594 note55x409 note56x224 note57x39 note58x867 note59x682 note60x497 note61x312 note62x127 note63x955 note64x770 note65x585 note66x400 note67x215 note68x30 note69x858 note70x673 note71x488 note72x303 note73x118 note74x946 note75x761 note76x576 note77x391 note78x206 note79x21 note80x849 note81x664 note82x479 note83x294 note84x109 note85x937 note86x752 note87x567 note88x382 note0x197 note1x12 note2x840 note3x655 note4x470 note5x285 note6x100 note7x928 note8x743 note9x558 note10x373 note11x188 note12x3 note13x831 note14x646 note15x461 note16x276 note17x91 note18x919 note19x734 note20x549 note21x364 note22x179 note23x1007 note24x822 note25x637 note26x452 note27x267 note28x82 note29x910 note30x725 note31x540 note32x355 note33x170 note34x998 note35x813 note36x628 note37x443 note38x258 note39x73 note40x901 note41x716 note42x531 note43x346 note44x161 note45x989 note46x804 note47x619 note48x434 note49x249 note50x64 note51x892 note52x707 note53x522 note54x337 note55x152 note56x980 note57x795 note58x610 note59x425 note60x240 note61x55 note62x883 note63x698 note64x513 note65x328 note66x143 note67x971 note68x786 note69x601 note70x416 note71x231 note72x46 note73x874 note74x689 note75x504 note76x319 note77x134 note78x962 note79x777 note80x592 note81x407 note82x222 note83x37 note84x865 note85x680 note86x495 note87x310 note88x125 note0x953 note1x768 note2x583 note3x398 note4x213 note5x28 note6x856 note7x671 note8x486 note9x301 note10x116 note11x944 note12x759 note13x574 note14x389 note15x204 note16x19 note17x847 note18x662 note19x477 note20x292 note21x107 note22x935 note23x750 note24x565 note25x380 note26x195 note27x10 note28x838 note29x653 note30x468 note31x283 note32x98 note33x926 note34x741 note35x556 note36x371 note37x186 note38x1 note39x829 note40x644 note41x459 note42x274 note43x89 note44x917 note45x732 note46x547 note47x362 note48x177 note49x1005 note50x820 note51x635 note52x450 note53x265 note54x80 note55x908 note56x723 note57x538 note58x353 note59x168 note60x996 note61x811 note62x626 note63x441 note64x256 note65x71 note66x899 note67x714 note68x529 note69x344 note70x159 note71x987 note72x802 note73x617 note74x432 note75x247"}, {"role": "user", "content": "What is the first note?"}, {"role": "assistant", "content": "The first note is **note0x0**."}, {"role": "user", "content": "And the second one?"}, {"role": "assistant", "content": "The second note is **note1x828**."}, {"role": "user", "content": "Name the last note."}], "max_tokens": 48, "temperature": 0.0, "draft": true, "chat_template_kwargs": {"enable_thinking": false}}, "status": 200, "response": {"id": "chatcmpl-406f89a58b638dd08cb1e4da4edb314b", "object": "chat.completion", "created": 1793474499, "model": "flashnext", "choices": [{"index": 0, "message": {"role": "assistant", "content": "The last note is **note75x247**."}, "finish_reason": "stop"}], "usage": {"prompt_tokens": 10279, "completion_tokens": 14, "total_tokens": 10293, "prompt_tokens_details": {"cached_tokens": 10240}, "completion_tokens_details": {"reasoning_tokens": 0}}, "exact_mode": "exact", "tensorfold": {"enable_thinking": false, "reasoning_effort": "none", "engine": "lanes", "tokens_per_second": 44.8706877517388, "seconds": 0.289721434, "prefill_seconds": 0.252732609, "prefill_widths": [], "prefill_raised": [], "time_to_first_token": 0.25421279, "sampling": "greedy", "drafts": true, "token_sha": "9537be85f86c", "token_sha256": "9537be85f86c467fa028c7e7cd58d5b693a814bcc9988a99dec273e8e81523c1", "min_rows": 3}, "speculative": {"rounds": 4, "drafted": 20, "accepted": 12, "acceptance_rate": 0.6, "tokens_per_round": 3.5}}, "seconds": 0.5461852550506592} +{"url": "http://127.0.0.1:30461/v1/chat/completions", "request": {"model": "flashnext", "messages": [{"role": "system", "content": "You are a careful assistant. Reference notes: note0x0 note1x828 note2x643 note3x458 note4x273 note5x88 note6x916 note7x731 note8x546 note9x361 note10x176 note11x1004 note12x819 note13x634 note14x449 note15x264 note16x79 note17x907 note18x722 note19x537 note20x352 note21x167 note22x995 note23x810 note24x625 note25x440 note26x255 note27x70 note28x898 note29x713 note30x528 note31x343 note32x158 note33x986 note34x801 note35x616 note36x431 note37x246 note38x61 note39x889 note40x704 note41x519 note42x334 note43x149 note44x977 note45x792 note46x607 note47x422 note48x237 note49x52 note50x880 note51x695 note52x510 note53x325 note54x140 note55x968 note56x783 note57x598 note58x413 note59x228 note60x43 note61x871 note62x686 note63x501 note64x316 note65x131 note66x959 note67x774 note68x589 note69x404 note70x219 note71x34 note72x862 note73x677 note74x492 note75x307 note76x122 note77x950 note78x765 note79x580 note80x395 note81x210 note82x25 note83x853 note84x668 note85x483 note86x298 note87x113 note88x941 note0x756 note1x571 note2x386 note3x201 note4x16 note5x844 note6x659 note7x474 note8x289 note9x104 note10x932 note11x747 note12x562 note13x377 note14x192 note15x7 note16x835 note17x650 note18x465 note19x280 note20x95 note21x923 note22x738 note23x553 note24x368 note25x183 note26x1011 note27x826 note28x641 note29x456 note30x271 note31x86 note32x914 note33x729 note34x544 note35x359 note36x174 note37x1002 note38x817 note39x632 note40x447 note41x262 note42x77 note43x905 note44x720 note45x535 note46x350 note47x165 note48x993 note49x808 note50x623 note51x438 note52x253 note53x68 note54x896 note55x711 note56x526 note57x341 note58x156 note59x984 note60x799 note61x614 note62x429 note63x244 note64x59 note65x887 note66x702 note67x517 note68x332 note69x147 note70x975 note71x790 note72x605 note73x420 note74x235 note75x50 note76x878 note77x693 note78x508 note79x323 note80x138 note81x966 note82x781 note83x596 note84x411 note85x226 note86x41 note87x869 note88x684 note0x499 note1x314 note2x129 note3x957 note4x772 note5x587 note6x402 note7x217 note8x32 note9x860 note10x675 note11x490 note12x305 note13x120 note14x948 note15x763 note16x578 note17x393 note18x208 note19x23 note20x851 note21x666 note22x481 note23x296 note24x111 note25x939 note26x754 note27x569 note28x384 note29x199 note30x14 note31x842 note32x657 note33x472 note34x287 note35x102 note36x930 note37x745 note38x560 note39x375 note40x190 note41x5 note42x833 note43x648 note44x463 note45x278 note46x93 note47x921 note48x736 note49x551 note50x366 note51x181 note52x1009 note53x824 note54x639 note55x454 note56x269 note57x84 note58x912 note59x727 note60x542 note61x357 note62x172 note63x1000 note64x815 note65x630 note66x445 note67x260 note68x75 note69x903 note70x718 note71x533 note72x348 note73x163 note74x991 note75x806 note76x621 note77x436 note78x251 note79x66 note80x894 note81x709 note82x524 note83x339 note84x154 note85x982 note86x797 note87x612 note88x427 note0x242 note1x57 note2x885 note3x700 note4x515 note5x330 note6x145 note7x973 note8x788 note9x603 note10x418 note11x233 note12x48 note13x876 note14x691 note15x506 note16x321 note17x136 note18x964 note19x779 note20x594 note21x409 note22x224 note23x39 note24x867 note25x682 note26x497 note27x312 note28x127 note29x955 note30x770 note31x585 note32x400 note33x215 note34x30 note35x858 note36x673 note37x488 note38x303 note39x118 note40x946 note41x761 note42x576 note43x391 note44x206 note45x21 note46x849 note47x664 note48x479 note49x294 note50x109 note51x937 note52x752 note53x567 note54x382 note55x197 note56x12 note57x840 note58x655 note59x470 note60x285 note61x100 note62x928 note63x743 note64x558 note65x373 note66x188 note67x3 note68x831 note69x646 note70x461 note71x276 note72x91 note73x919 note74x734 note75x549 note76x364 note77x179 note78x1007 note79x822 note80x637 note81x452 note82x267 note83x82 note84x910 note85x725 note86x540 note87x355 note88x170 note0x998 note1x813 note2x628 note3x443 note4x258 note5x73 note6x901 note7x716 note8x531 note9x346 note10x161 note11x989 note12x804 note13x619 note14x434 note15x249 note16x64 note17x892 note18x707 note19x522 note20x337 note21x152 note22x980 note23x795 note24x610 note25x425 note26x240 note27x55 note28x883 note29x698 note30x513 note31x328 note32x143 note33x971 note34x786 note35x601 note36x416 note37x231 note38x46 note39x874 note40x689 note41x504 note42x319 note43x134 note44x962 note45x777 note46x592 note47x407 note48x222 note49x37 note50x865 note51x680 note52x495 note53x310 note54x125 note55x953 note56x768 note57x583 note58x398 note59x213 note60x28 note61x856 note62x671 note63x486 note64x301 note65x116 note66x944 note67x759 note68x574 note69x389 note70x204 note71x19 note72x847 note73x662 note74x477 note75x292 note76x107 note77x935 note78x750 note79x565 note80x380 note81x195 note82x10 note83x838 note84x653 note85x468 note86x283 note87x98 note88x926 note0x741 note1x556 note2x371 note3x186 note4x1 note5x829 note6x644 note7x459 note8x274 note9x89 note10x917 note11x732 note12x547 note13x362 note14x177 note15x1005 note16x820 note17x635 note18x450 note19x265 note20x80 note21x908 note22x723 note23x538 note24x353 note25x168 note26x996 note27x811 note28x626 note29x441 note30x256 note31x71 note32x899 note33x714 note34x529 note35x344 note36x159 note37x987 note38x802 note39x617 note40x432 note41x247 note42x62 note43x890 note44x705 note45x520 note46x335 note47x150 note48x978 note49x793 note50x608 note51x423 note52x238 note53x53 note54x881 note55x696 note56x511 note57x326 note58x141 note59x969 note60x784 note61x599 note62x414 note63x229 note64x44 note65x872 note66x687 note67x502 note68x317 note69x132 note70x960 note71x775 note72x590 note73x405 note74x220 note75x35 note76x863 note77x678 note78x493 note79x308 note80x123 note81x951 note82x766 note83x581 note84x396 note85x211 note86x26 note87x854 note88x669 note0x484 note1x299 note2x114 note3x942 note4x757 note5x572 note6x387 note7x202 note8x17 note9x845 note10x660 note11x475 note12x290 note13x105 note14x933 note15x748 note16x563 note17x378 note18x193 note19x8 note20x836 note21x651 note22x466 note23x281 note24x96 note25x924 note26x739 note27x554 note28x369 note29x184 note30x1012 note31x827 note32x642 note33x457 note34x272 note35x87 note36x915 note37x730 note38x545 note39x360 note40x175 note41x1003 note42x818 note43x633 note44x448 note45x263 note46x78 note47x906 note48x721 note49x536 note50x351 note51x166 note52x994 note53x809 note54x624 note55x439 note56x254 note57x69 note58x897 note59x712 note60x527 note61x342 note62x157 note63x985 note64x800 note65x615 note66x430 note67x245 note68x60 note69x888 note70x703 note71x518 note72x333 note73x148 note74x976 note75x791 note76x606 note77x421 note78x236 note79x51 note80x879 note81x694 note82x509 note83x324 note84x139 note85x967 note86x782 note87x597 note88x412 note0x227 note1x42 note2x870 note3x685 note4x500 note5x315 note6x130 note7x958 note8x773 note9x588 note10x403 note11x218 note12x33 note13x861 note14x676 note15x491 note16x306 note17x121 note18x949 note19x764 note20x579 note21x394 note22x209 note23x24 note24x852 note25x667 note26x482 note27x297 note28x112 note29x940 note30x755 note31x570 note32x385 note33x200 note34x15 note35x843 note36x658 note37x473 note38x288 note39x103 note40x931 note41x746 note42x561 note43x376 note44x191 note45x6 note46x834 note47x649 note48x464 note49x279 note50x94 note51x922 note52x737 note53x552 note54x367 note55x182 note56x1010 note57x825 note58x640 note59x455 note60x270 note61x85 note62x913 note63x728 note64x543 note65x358 note66x173 note67x1001 note68x816 note69x631 note70x446 note71x261 note72x76 note73x904 note74x719 note75x534 note76x349 note77x164 note78x992 note79x807 note80x622 note81x437 note82x252 note83x67 note84x895 note85x710 note86x525 note87x340 note88x155 note0x983 note1x798 note2x613 note3x428 note4x243 note5x58 note6x886 note7x701 note8x516 note9x331 note10x146 note11x974 note12x789 note13x604 note14x419 note15x234 note16x49 note17x877 note18x692 note19x507 note20x322 note21x137 note22x965 note23x780 note24x595 note25x410 note26x225 note27x40 note28x868 note29x683 note30x498 note31x313 note32x128 note33x956 note34x771 note35x586 note36x401 note37x216 note38x31 note39x859 note40x674 note41x489 note42x304 note43x119 note44x947 note45x762 note46x577 note47x392 note48x207 note49x22 note50x850 note51x665 note52x480 note53x295 note54x110 note55x938 note56x753 note57x568 note58x383 note59x198 note60x13 note61x841 note62x656 note63x471 note64x286 note65x101 note66x929 note67x744 note68x559 note69x374 note70x189 note71x4 note72x832 note73x647 note74x462 note75x277 note76x92 note77x920 note78x735 note79x550 note80x365 note81x180 note82x1008 note83x823 note84x638 note85x453 note86x268 note87x83 note88x911 note0x726 note1x541 note2x356 note3x171 note4x999 note5x814 note6x629 note7x444 note8x259 note9x74 note10x902 note11x717 note12x532 note13x347 note14x162 note15x990 note16x805 note17x620 note18x435 note19x250 note20x65 note21x893 note22x708 note23x523 note24x338 note25x153 note26x981 note27x796 note28x611 note29x426 note30x241 note31x56 note32x884 note33x699 note34x514 note35x329 note36x144 note37x972 note38x787 note39x602 note40x417 note41x232 note42x47 note43x875 note44x690 note45x505 note46x320 note47x135 note48x963 note49x778 note50x593 note51x408 note52x223 note53x38 note54x866 note55x681 note56x496 note57x311 note58x126 note59x954 note60x769 note61x584 note62x399 note63x214 note64x29 note65x857 note66x672 note67x487 note68x302 note69x117 note70x945 note71x760 note72x575 note73x390 note74x205 note75x20 note76x848 note77x663 note78x478 note79x293 note80x108 note81x936 note82x751 note83x566 note84x381 note85x196 note86x11 note87x839 note88x654 note0x469 note1x284 note2x99 note3x927 note4x742 note5x557 note6x372 note7x187 note8x2 note9x830 note10x645 note11x460 note12x275 note13x90 note14x918 note15x733 note16x548 note17x363 note18x178 note19x1006 note20x821 note21x636 note22x451 note23x266 note24x81 note25x909 note26x724 note27x539 note28x354 note29x169 note30x997 note31x812 note32x627 note33x442 note34x257 note35x72 note36x900 note37x715 note38x530 note39x345 note40x160 note41x988 note42x803 note43x618 note44x433 note45x248 note46x63 note47x891 note48x706 note49x521 note50x336 note51x151 note52x979 note53x794 note54x609 note55x424 note56x239 note57x54 note58x882 note59x697 note60x512 note61x327 note62x142 note63x970 note64x785 note65x600 note66x415 note67x230 note68x45 note69x873 note70x688 note71x503 note72x318 note73x133 note74x961 note75x776 note76x591 note77x406 note78x221 note79x36 note80x864 note81x679 note82x494 note83x309 note84x124 note85x952 note86x767 note87x582 note88x397 note0x212 note1x27 note2x855 note3x670 note4x485 note5x300 note6x115 note7x943 note8x758 note9x573 note10x388 note11x203 note12x18 note13x846 note14x661 note15x476 note16x291 note17x106 note18x934 note19x749 note20x564 note21x379 note22x194 note23x9 note24x837 note25x652 note26x467 note27x282 note28x97 note29x925 note30x740 note31x555 note32x370 note33x185 note34x0 note35x828 note36x643 note37x458 note38x273 note39x88 note40x916 note41x731 note42x546 note43x361 note44x176 note45x1004 note46x819 note47x634 note48x449 note49x264 note50x79 note51x907 note52x722 note53x537 note54x352 note55x167 note56x995 note57x810 note58x625 note59x440 note60x255 note61x70 note62x898 note63x713 note64x528 note65x343 note66x158 note67x986 note68x801 note69x616 note70x431 note71x246 note72x61 note73x889 note74x704 note75x519 note76x334 note77x149 note78x977 note79x792 note80x607 note81x422 note82x237 note83x52 note84x880 note85x695 note86x510 note87x325 note88x140 note0x968 note1x783 note2x598 note3x413 note4x228 note5x43 note6x871 note7x686 note8x501 note9x316 note10x131 note11x959 note12x774 note13x589 note14x404 note15x219 note16x34 note17x862 note18x677 note19x492 note20x307 note21x122 note22x950 note23x765 note24x580 note25x395 note26x210 note27x25 note28x853 note29x668 note30x483 note31x298 note32x113 note33x941 note34x756 note35x571 note36x386 note37x201 note38x16 note39x844 note40x659 note41x474 note42x289 note43x104 note44x932 note45x747 note46x562 note47x377 note48x192 note49x7 note50x835 note51x650 note52x465 note53x280 note54x95 note55x923 note56x738 note57x553 note58x368 note59x183 note60x1011 note61x826 note62x641 note63x456 note64x271 note65x86 note66x914 note67x729 note68x544 note69x359 note70x174 note71x1002 note72x817 note73x632 note74x447 note75x262 note76x77 note77x905 note78x720 note79x535 note80x350 note81x165 note82x993 note83x808 note84x623 note85x438 note86x253 note87x68 note88x896 note0x711 note1x526 note2x341 note3x156 note4x984 note5x799 note6x614 note7x429 note8x244 note9x59 note10x887 note11x702 note12x517 note13x332 note14x147 note15x975 note16x790 note17x605 note18x420 note19x235 note20x50 note21x878 note22x693 note23x508 note24x323 note25x138 note26x966 note27x781 note28x596 note29x411 note30x226 note31x41 note32x869 note33x684 note34x499 note35x314 note36x129 note37x957 note38x772 note39x587 note40x402 note41x217 note42x32 note43x860 note44x675 note45x490 note46x305 note47x120 note48x948 note49x763 note50x578 note51x393 note52x208 note53x23 note54x851 note55x666 note56x481 note57x296 note58x111 note59x939 note60x754 note61x569 note62x384 note63x199 note64x14 note65x842 note66x657 note67x472 note68x287 note69x102 note70x930 note71x745 note72x560 note73x375 note74x190 note75x5 note76x833 note77x648 note78x463 note79x278 note80x93 note81x921 note82x736 note83x551 note84x366 note85x181 note86x1009 note87x824 note88x639 note0x454 note1x269 note2x84 note3x912 note4x727 note5x542 note6x357 note7x172 note8x1000 note9x815 note10x630 note11x445 note12x260 note13x75 note14x903 note15x718 note16x533 note17x348 note18x163 note19x991 note20x806 note21x621 note22x436 note23x251 note24x66 note25x894 note26x709 note27x524 note28x339 note29x154 note30x982 note31x797 note32x612 note33x427 note34x242 note35x57 note36x885 note37x700 note38x515 note39x330 note40x145 note41x973 note42x788 note43x603 note44x418 note45x233 note46x48 note47x876 note48x691 note49x506 note50x321 note51x136 note52x964 note53x779 note54x594 note55x409 note56x224 note57x39 note58x867 note59x682 note60x497 note61x312 note62x127 note63x955 note64x770 note65x585 note66x400 note67x215 note68x30 note69x858 note70x673 note71x488 note72x303 note73x118 note74x946 note75x761 note76x576 note77x391 note78x206 note79x21 note80x849 note81x664 note82x479 note83x294 note84x109 note85x937 note86x752 note87x567 note88x382 note0x197 note1x12 note2x840 note3x655 note4x470 note5x285 note6x100 note7x928 note8x743 note9x558 note10x373 note11x188 note12x3 note13x831 note14x646 note15x461 note16x276 note17x91 note18x919 note19x734 note20x549 note21x364 note22x179 note23x1007 note24x822 note25x637 note26x452 note27x267 note28x82 note29x910 note30x725 note31x540 note32x355 note33x170 note34x998 note35x813 note36x628 note37x443 note38x258 note39x73 note40x901 note41x716 note42x531 note43x346 note44x161 note45x989 note46x804 note47x619 note48x434 note49x249 note50x64 note51x892 note52x707 note53x522 note54x337 note55x152 note56x980 note57x795 note58x610 note59x425 note60x240 note61x55 note62x883 note63x698 note64x513 note65x328 note66x143 note67x971 note68x786 note69x601 note70x416 note71x231 note72x46 note73x874 note74x689 note75x504 note76x319 note77x134 note78x962 note79x777 note80x592 note81x407 note82x222 note83x37 note84x865 note85x680 note86x495 note87x310 note88x125 note0x953 note1x768 note2x583 note3x398 note4x213 note5x28 note6x856 note7x671 note8x486 note9x301 note10x116 note11x944 note12x759 note13x574 note14x389 note15x204 note16x19 note17x847 note18x662 note19x477 note20x292 note21x107 note22x935 note23x750 note24x565 note25x380 note26x195 note27x10 note28x838 note29x653 note30x468 note31x283 note32x98 note33x926 note34x741 note35x556 note36x371 note37x186 note38x1 note39x829 note40x644 note41x459 note42x274 note43x89 note44x917 note45x732 note46x547 note47x362 note48x177 note49x1005 note50x820 note51x635 note52x450 note53x265 note54x80 note55x908 note56x723 note57x538 note58x353 note59x168 note60x996 note61x811 note62x626 note63x441 note64x256 note65x71 note66x899 note67x714 note68x529 note69x344 note70x159 note71x987 note72x802 note73x617 note74x432 note75x247"}, {"role": "user", "content": "What is the third note?"}], "max_tokens": 48, "temperature": 0.0, "draft": true, "chat_template_kwargs": {"enable_thinking": false}}, "status": 200, "response": {"id": "chatcmpl-e58a6fda3aa48f02164327a092709d60", "object": "chat.completion", "created": 1793474499, "model": "flashnext", "choices": [{"index": 0, "message": {"role": "assistant", "content": "The third note is **note2x643**."}, "finish_reason": "stop"}], "usage": {"prompt_tokens": 10219, "completion_tokens": 13, "total_tokens": 10232, "prompt_tokens_details": {"cached_tokens": 10176}, "completion_tokens_details": {"reasoning_tokens": 0}}, "exact_mode": "exact", "tensorfold": {"enable_thinking": false, "reasoning_effort": "none", "engine": "lanes", "tokens_per_second": 45.2051905413473, "seconds": 0.265456242, "prefill_seconds": 0.274315783, "prefill_widths": [], "prefill_raised": [], "time_to_first_token": 0.27695956, "sampling": "greedy", "drafts": true, "token_sha": "86effbb58f5b", "token_sha256": "86effbb58f5b1a059c85bb7445693561cdba823838fe7776eaafd0a10e14cf56", "min_rows": 2}, "speculative": {"rounds": 5, "drafted": 13, "accepted": 11, "acceptance_rate": 0.8461538461538461, "tokens_per_round": 2.6}}, "seconds": 0.7094597816467285} +{"url": "http://127.0.0.1:30461/v1/chat/completions", "request": {"model": "flashnext", "messages": [{"role": "system", "content": "You are a careful assistant. 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note2x386 note3x201 note4x16 note5x844 note6x659 note7x474 note8x289 note9x104 note10x932 note11x747 note12x562 note13x377 note14x192 note15x7 note16x835 note17x650 note18x465 note19x280 note20x95 note21x923 note22x738 note23x553 note24x368 note25x183 note26x1011 note27x826 note28x641 note29x456 note30x271 note31x86 note32x914 note33x729 note34x544 note35x359 note36x174 note37x1002 note38x817 note39x632 note40x447 note41x262 note42x77 note43x905 note44x720 note45x535 note46x350 note47x165 note48x993 note49x808 note50x623 note51x438 note52x253 note53x68 note54x896 note55x711 note56x526 note57x341 note58x156 note59x984 note60x799 note61x614 note62x429 note63x244 note64x59 note65x887 note66x702 note67x517 note68x332 note69x147 note70x975 note71x790 note72x605 note73x420 note74x235 note75x50 note76x878 note77x693 note78x508 note79x323 note80x138 note81x966 note82x781 note83x596 note84x411 note85x226 note86x41 note87x869 note88x684 note0x499 note1x314 note2x129 note3x957 note4x772 note5x587 note6x402 note7x217 note8x32 note9x860 note10x675 note11x490 note12x305 note13x120 note14x948 note15x763 note16x578 note17x393 note18x208 note19x23 note20x851 note21x666 note22x481 note23x296 note24x111 note25x939 note26x754 note27x569 note28x384 note29x199 note30x14 note31x842 note32x657 note33x472 note34x287 note35x102 note36x930 note37x745 note38x560 note39x375 note40x190 note41x5 note42x833 note43x648 note44x463 note45x278 note46x93 note47x921 note48x736 note49x551 note50x366 note51x181 note52x1009 note53x824 note54x639 note55x454 note56x269 note57x84 note58x912 note59x727 note60x542 note61x357 note62x172 note63x1000 note64x815 note65x630 note66x445 note67x260 note68x75 note69x903 note70x718 note71x533 note72x348 note73x163 note74x991 note75x806 note76x621 note77x436 note78x251 note79x66 note80x894 note81x709 note82x524 note83x339 note84x154 note85x982 note86x797 note87x612 note88x427 note0x242 note1x57 note2x885 note3x700 note4x515 note5x330 note6x145 note7x973 note8x788 note9x603 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note35x828 note36x643 note37x458 note38x273 note39x88 note40x916 note41x731 note42x546 note43x361 note44x176 note45x1004 note46x819 note47x634 note48x449 note49x264 note50x79 note51x907 note52x722 note53x537 note54x352 note55x167 note56x995 note57x810 note58x625 note59x440 note60x255 note61x70 note62x898 note63x713 note64x528 note65x343 note66x158 note67x986 note68x801 note69x616 note70x431 note71x246 note72x61 note73x889 note74x704 note75x519 note76x334 note77x149 note78x977 note79x792 note80x607 note81x422 note82x237 note83x52 note84x880 note85x695 note86x510 note87x325 note88x140 note0x968 note1x783 note2x598 note3x413 note4x228 note5x43 note6x871 note7x686 note8x501 note9x316 note10x131 note11x959 note12x774 note13x589 note14x404 note15x219 note16x34 note17x862 note18x677 note19x492 note20x307 note21x122 note22x950 note23x765 note24x580 note25x395 note26x210 note27x25 note28x853 note29x668 note30x483 note31x298 note32x113 note33x941 note34x756 note35x571 note36x386 note37x201 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note44x418 note45x233 note46x48 note47x876 note48x691 note49x506 note50x321 note51x136 note52x964 note53x779 note54x594 note55x409 note56x224 note57x39 note58x867 note59x682 note60x497 note61x312 note62x127 note63x955 note64x770 note65x585 note66x400 note67x215 note68x30 note69x858 note70x673 note71x488 note72x303 note73x118 note74x946 note75x761 note76x576 note77x391 note78x206 note79x21 note80x849 note81x664 note82x479 note83x294 note84x109 note85x937 note86x752 note87x567 note88x382 note0x197 note1x12 note2x840 note3x655 note4x470 note5x285 note6x100 note7x928 note8x743 note9x558 note10x373 note11x188 note12x3 note13x831 note14x646 note15x461 note16x276 note17x91 note18x919 note19x734 note20x549 note21x364 note22x179 note23x1007 note24x822 note25x637 note26x452 note27x267 note28x82 note29x910 note30x725 note31x540 note32x355 note33x170 note34x998 note35x813 note36x628 note37x443 note38x258 note39x73 note40x901 note41x716 note42x531 note43x346 note44x161 note45x989 note46x804 note47x619 note48x434 note49x249 note50x64 note51x892 note52x707 note53x522 note54x337 note55x152 note56x980 note57x795 note58x610 note59x425 note60x240 note61x55 note62x883 note63x698 note64x513 note65x328 note66x143 note67x971 note68x786 note69x601 note70x416 note71x231 note72x46 note73x874 note74x689 note75x504 note76x319 note77x134 note78x962 note79x777 note80x592 note81x407 note82x222 note83x37 note84x865 note85x680 note86x495 note87x310 note88x125 note0x953 note1x768 note2x583 note3x398 note4x213 note5x28 note6x856 note7x671 note8x486 note9x301 note10x116 note11x944 note12x759 note13x574 note14x389 note15x204 note16x19 note17x847 note18x662 note19x477 note20x292 note21x107 note22x935 note23x750 note24x565 note25x380 note26x195 note27x10 note28x838 note29x653 note30x468 note31x283 note32x98 note33x926 note34x741 note35x556 note36x371 note37x186 note38x1 note39x829 note40x644 note41x459 note42x274 note43x89 note44x917 note45x732 note46x547 note47x362 note48x177 note49x1005 note50x820 note51x635 note52x450 note53x265 note54x80 note55x908 note56x723 note57x538 note58x353 note59x168 note60x996 note61x811 note62x626 note63x441 note64x256 note65x71 note66x899 note67x714 note68x529 note69x344 note70x159 note71x987 note72x802 note73x617 note74x432 note75x247"}, {"role": "user", "content": "What is the first note?"}, {"role": "assistant", "content": "The first note is **note0x0**."}, {"role": "user", "content": "And the second one?"}], "max_tokens": 48, "temperature": 0.0, "draft": true, "chat_template_kwargs": {"enable_thinking": false}}, "status": 200, "response": {"id": "chatcmpl-bf81efa19a2fd894ea36d9da9dd23cb0", "object": "chat.completion", "created": 1793474500, "model": "flashnext", "choices": [{"index": 0, "message": {"role": "assistant", "content": "The second note is **note1x828**."}, "finish_reason": "stop"}], "usage": {"prompt_tokens": 10248, "completion_tokens": 13, "total_tokens": 10261, "prompt_tokens_details": {"cached_tokens": 10240}, "completion_tokens_details": {"reasoning_tokens": 0}}, "exact_mode": "exact", "tensorfold": {"enable_thinking": false, "reasoning_effort": "none", "engine": "lanes", "tokens_per_second": 41.573069951952654, "seconds": 0.288648397, "prefill_seconds": 0.097949116, "prefill_widths": [], "prefill_raised": [], "time_to_first_token": 0.0986459, "sampling": "greedy", "drafts": true, "token_sha": "7e4bf5aba972", "token_sha256": "7e4bf5aba9727191d8505e971356abb0485616846741651f36545f4775ef04fc", "min_rows": 5}, "speculative": {"rounds": 4, "drafted": 21, "accepted": 10, "acceptance_rate": 0.47619047619047616, "tokens_per_round": 3.25}}, "seconds": 0.38818860054016113} +{"url": "http://127.0.0.1:30461/v1/chat/completions", "request": {"model": "flashnext", "messages": [{"role": "system", "content": "You are a careful assistant. 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note2x386 note3x201 note4x16 note5x844 note6x659 note7x474 note8x289 note9x104 note10x932 note11x747 note12x562 note13x377 note14x192 note15x7 note16x835 note17x650 note18x465 note19x280 note20x95 note21x923 note22x738 note23x553 note24x368 note25x183 note26x1011 note27x826 note28x641 note29x456 note30x271 note31x86 note32x914 note33x729 note34x544 note35x359 note36x174 note37x1002 note38x817 note39x632 note40x447 note41x262 note42x77 note43x905 note44x720 note45x535 note46x350 note47x165 note48x993 note49x808 note50x623 note51x438 note52x253 note53x68 note54x896 note55x711 note56x526 note57x341 note58x156 note59x984 note60x799 note61x614 note62x429 note63x244 note64x59 note65x887 note66x702 note67x517 note68x332 note69x147 note70x975 note71x790 note72x605 note73x420 note74x235 note75x50 note76x878 note77x693 note78x508 note79x323 note80x138 note81x966 note82x781 note83x596 note84x411 note85x226 note86x41 note87x869 note88x684 note0x499 note1x314 note2x129 note3x957 note4x772 note5x587 note6x402 note7x217 note8x32 note9x860 note10x675 note11x490 note12x305 note13x120 note14x948 note15x763 note16x578 note17x393 note18x208 note19x23 note20x851 note21x666 note22x481 note23x296 note24x111 note25x939 note26x754 note27x569 note28x384 note29x199 note30x14 note31x842 note32x657 note33x472 note34x287 note35x102 note36x930 note37x745 note38x560 note39x375 note40x190 note41x5 note42x833 note43x648 note44x463 note45x278 note46x93 note47x921 note48x736 note49x551 note50x366 note51x181 note52x1009 note53x824 note54x639 note55x454 note56x269 note57x84 note58x912 note59x727 note60x542 note61x357 note62x172 note63x1000 note64x815 note65x630 note66x445 note67x260 note68x75 note69x903 note70x718 note71x533 note72x348 note73x163 note74x991 note75x806 note76x621 note77x436 note78x251 note79x66 note80x894 note81x709 note82x524 note83x339 note84x154 note85x982 note86x797 note87x612 note88x427 note0x242 note1x57 note2x885 note3x700 note4x515 note5x330 note6x145 note7x973 note8x788 note9x603 note10x418 note11x233 note12x48 note13x876 note14x691 note15x506 note16x321 note17x136 note18x964 note19x779 note20x594 note21x409 note22x224 note23x39 note24x867 note25x682 note26x497 note27x312 note28x127 note29x955 note30x770 note31x585 note32x400 note33x215 note34x30 note35x858 note36x673 note37x488 note38x303 note39x118 note40x946 note41x761 note42x576 note43x391 note44x206 note45x21 note46x849 note47x664 note48x479 note49x294 note50x109 note51x937 note52x752 note53x567 note54x382 note55x197 note56x12 note57x840 note58x655 note59x470 note60x285 note61x100 note62x928 note63x743 note64x558 note65x373 note66x188 note67x3 note68x831 note69x646 note70x461 note71x276 note72x91 note73x919 note74x734 note75x549 note76x364 note77x179 note78x1007 note79x822 note80x637 note81x452 note82x267 note83x82 note84x910 note85x725 note86x540 note87x355 note88x170 note0x998 note1x813 note2x628 note3x443 note4x258 note5x73 note6x901 note7x716 note8x531 note9x346 note10x161 note11x989 note12x804 note13x619 note14x434 note15x249 note16x64 note17x892 note18x707 note19x522 note20x337 note21x152 note22x980 note23x795 note24x610 note25x425 note26x240 note27x55 note28x883 note29x698 note30x513 note31x328 note32x143 note33x971 note34x786 note35x601 note36x416 note37x231 note38x46 note39x874 note40x689 note41x504 note42x319 note43x134 note44x962 note45x777 note46x592 note47x407 note48x222 note49x37 note50x865 note51x680 note52x495 note53x310 note54x125 note55x953 note56x768 note57x583 note58x398 note59x213 note60x28 note61x856 note62x671 note63x486 note64x301 note65x116 note66x944 note67x759 note68x574 note69x389 note70x204 note71x19 note72x847 note73x662 note74x477 note75x292 note76x107 note77x935 note78x750 note79x565 note80x380 note81x195 note82x10 note83x838 note84x653 note85x468 note86x283 note87x98 note88x926 note0x741 note1x556 note2x371 note3x186 note4x1 note5x829 note6x644 note7x459 note8x274 note9x89 note10x917 note11x732 note12x547 note13x362 note14x177 note15x1005 note16x820 note17x635 note18x450 note19x265 note20x80 note21x908 note22x723 note23x538 note24x353 note25x168 note26x996 note27x811 note28x626 note29x441 note30x256 note31x71 note32x899 note33x714 note34x529 note35x344 note36x159 note37x987 note38x802 note39x617 note40x432 note41x247 note42x62 note43x890 note44x705 note45x520 note46x335 note47x150 note48x978 note49x793 note50x608 note51x423 note52x238 note53x53 note54x881 note55x696 note56x511 note57x326 note58x141 note59x969 note60x784 note61x599 note62x414 note63x229 note64x44 note65x872 note66x687 note67x502 note68x317 note69x132 note70x960 note71x775 note72x590 note73x405 note74x220 note75x35 note76x863 note77x678 note78x493 note79x308 note80x123 note81x951 note82x766 note83x581 note84x396 note85x211 note86x26 note87x854 note88x669 note0x484 note1x299 note2x114 note3x942 note4x757 note5x572 note6x387 note7x202 note8x17 note9x845 note10x660 note11x475 note12x290 note13x105 note14x933 note15x748 note16x563 note17x378 note18x193 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note25x410 note26x225 note27x40 note28x868 note29x683 note30x498 note31x313 note32x128 note33x956 note34x771 note35x586 note36x401 note37x216 note38x31 note39x859 note40x674 note41x489 note42x304 note43x119 note44x947 note45x762 note46x577 note47x392 note48x207 note49x22 note50x850 note51x665 note52x480 note53x295 note54x110 note55x938 note56x753 note57x568 note58x383 note59x198 note60x13 note61x841 note62x656 note63x471 note64x286 note65x101 note66x929 note67x744 note68x559 note69x374 note70x189 note71x4 note72x832 note73x647 note74x462 note75x277 note76x92 note77x920 note78x735 note79x550 note80x365 note81x180 note82x1008 note83x823 note84x638 note85x453 note86x268 note87x83 note88x911 note0x726 note1x541 note2x356 note3x171 note4x999 note5x814 note6x629 note7x444 note8x259 note9x74 note10x902 note11x717 note12x532 note13x347 note14x162 note15x990 note16x805 note17x620 note18x435 note19x250 note20x65 note21x893 note22x708 note23x523 note24x338 note25x153 note26x981 note27x796 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note31x812 note32x627 note33x442 note34x257 note35x72 note36x900 note37x715 note38x530 note39x345 note40x160 note41x988 note42x803 note43x618 note44x433 note45x248 note46x63 note47x891 note48x706 note49x521 note50x336 note51x151 note52x979 note53x794 note54x609 note55x424 note56x239 note57x54 note58x882 note59x697 note60x512 note61x327 note62x142 note63x970 note64x785 note65x600 note66x415 note67x230 note68x45 note69x873 note70x688 note71x503 note72x318 note73x133 note74x961 note75x776 note76x591 note77x406 note78x221 note79x36 note80x864 note81x679 note82x494 note83x309 note84x124 note85x952 note86x767 note87x582 note88x397 note0x212 note1x27 note2x855 note3x670 note4x485 note5x300 note6x115 note7x943 note8x758 note9x573 note10x388 note11x203 note12x18 note13x846 note14x661 note15x476 note16x291 note17x106 note18x934 note19x749 note20x564 note21x379 note22x194 note23x9 note24x837 note25x652 note26x467 note27x282 note28x97 note29x925 note30x740 note31x555 note32x370 note33x185 note34x0 note35x828 note36x643 note37x458 note38x273 note39x88 note40x916 note41x731 note42x546 note43x361 note44x176 note45x1004 note46x819 note47x634 note48x449 note49x264 note50x79 note51x907 note52x722 note53x537 note54x352 note55x167 note56x995 note57x810 note58x625 note59x440 note60x255 note61x70 note62x898 note63x713 note64x528 note65x343 note66x158 note67x986 note68x801 note69x616 note70x431 note71x246 note72x61 note73x889 note74x704 note75x519 note76x334 note77x149 note78x977 note79x792 note80x607 note81x422 note82x237 note83x52 note84x880 note85x695 note86x510 note87x325 note88x140 note0x968 note1x783 note2x598 note3x413 note4x228 note5x43 note6x871 note7x686 note8x501 note9x316 note10x131 note11x959 note12x774 note13x589 note14x404 note15x219 note16x34 note17x862 note18x677 note19x492 note20x307 note21x122 note22x950 note23x765 note24x580 note25x395 note26x210 note27x25 note28x853 note29x668 note30x483 note31x298 note32x113 note33x941 note34x756 note35x571 note36x386 note37x201 note38x16 note39x844 note40x659 note41x474 note42x289 note43x104 note44x932 note45x747 note46x562 note47x377 note48x192 note49x7 note50x835 note51x650 note52x465 note53x280 note54x95 note55x923 note56x738 note57x553 note58x368 note59x183 note60x1011 note61x826 note62x641 note63x456 note64x271 note65x86 note66x914 note67x729 note68x544 note69x359 note70x174 note71x1002 note72x817 note73x632 note74x447 note75x262 note76x77 note77x905 note78x720 note79x535 note80x350 note81x165 note82x993 note83x808 note84x623 note85x438 note86x253 note87x68 note88x896 note0x711 note1x526 note2x341 note3x156 note4x984 note5x799 note6x614 note7x429 note8x244 note9x59 note10x887 note11x702 note12x517 note13x332 note14x147 note15x975 note16x790 note17x605 note18x420 note19x235 note20x50 note21x878 note22x693 note23x508 note24x323 note25x138 note26x966 note27x781 note28x596 note29x411 note30x226 note31x41 note32x869 note33x684 note34x499 note35x314 note36x129 note37x957 note38x772 note39x587 note40x402 note41x217 note42x32 note43x860 note44x675 note45x490 note46x305 note47x120 note48x948 note49x763 note50x578 note51x393 note52x208 note53x23 note54x851 note55x666 note56x481 note57x296 note58x111 note59x939 note60x754 note61x569 note62x384 note63x199 note64x14 note65x842 note66x657 note67x472 note68x287 note69x102 note70x930 note71x745 note72x560 note73x375 note74x190 note75x5 note76x833 note77x648 note78x463 note79x278 note80x93 note81x921 note82x736 note83x551 note84x366 note85x181 note86x1009 note87x824 note88x639 note0x454 note1x269 note2x84 note3x912 note4x727 note5x542 note6x357 note7x172 note8x1000 note9x815 note10x630 note11x445 note12x260 note13x75 note14x903 note15x718 note16x533 note17x348 note18x163 note19x991 note20x806 note21x621 note22x436 note23x251 note24x66 note25x894 note26x709 note27x524 note28x339 note29x154 note30x982 note31x797 note32x612 note33x427 note34x242 note35x57 note36x885 note37x700 note38x515 note39x330 note40x145 note41x973 note42x788 note43x603 note44x418 note45x233 note46x48 note47x876 note48x691 note49x506 note50x321 note51x136 note52x964 note53x779 note54x594 note55x409 note56x224 note57x39 note58x867 note59x682 note60x497 note61x312 note62x127 note63x955 note64x770 note65x585 note66x400 note67x215 note68x30 note69x858 note70x673 note71x488 note72x303 note73x118 note74x946 note75x761 note76x576 note77x391 note78x206 note79x21 note80x849 note81x664 note82x479 note83x294 note84x109 note85x937 note86x752 note87x567 note88x382 note0x197 note1x12 note2x840 note3x655 note4x470 note5x285 note6x100 note7x928 note8x743 note9x558 note10x373 note11x188 note12x3 note13x831 note14x646 note15x461 note16x276 note17x91 note18x919 note19x734 note20x549 note21x364 note22x179 note23x1007 note24x822 note25x637 note26x452 note27x267 note28x82 note29x910 note30x725 note31x540 note32x355 note33x170 note34x998 note35x813 note36x628 note37x443 note38x258 note39x73 note40x901 note41x716 note42x531 note43x346 note44x161 note45x989 note46x804 note47x619 note48x434 note49x249 note50x64 note51x892 note52x707 note53x522 note54x337 note55x152 note56x980 note57x795 note58x610 note59x425 note60x240 note61x55 note62x883 note63x698 note64x513 note65x328 note66x143 note67x971 note68x786 note69x601 note70x416 note71x231 note72x46 note73x874 note74x689 note75x504 note76x319 note77x134 note78x962 note79x777 note80x592 note81x407 note82x222 note83x37 note84x865 note85x680 note86x495 note87x310 note88x125 note0x953 note1x768 note2x583 note3x398 note4x213 note5x28 note6x856 note7x671 note8x486 note9x301 note10x116 note11x944 note12x759 note13x574 note14x389 note15x204 note16x19 note17x847 note18x662 note19x477 note20x292 note21x107 note22x935 note23x750 note24x565 note25x380 note26x195 note27x10 note28x838 note29x653 note30x468 note31x283 note32x98 note33x926 note34x741 note35x556 note36x371 note37x186 note38x1 note39x829 note40x644 note41x459 note42x274 note43x89 note44x917 note45x732 note46x547 note47x362 note48x177 note49x1005 note50x820 note51x635 note52x450 note53x265 note54x80 note55x908 note56x723 note57x538 note58x353 note59x168 note60x996 note61x811 note62x626 note63x441 note64x256 note65x71 note66x899 note67x714 note68x529 note69x344 note70x159 note71x987 note72x802 note73x617 note74x432 note75x247"}, {"role": "user", "content": "What is the first note?"}], "max_tokens": 48, "temperature": 0.0, "draft": false, "chat_template_kwargs": {"enable_thinking": false}}, "status": 200, "response": {"id": "chatcmpl-3cc07e88fc66005ffb52965dd69f1bd5", "object": "chat.completion", "created": 1793474500, "model": "flashnext", "choices": [{"index": 0, "message": {"role": "assistant", "content": "The first note is **note0x0**."}, "finish_reason": "stop"}], "usage": {"prompt_tokens": 10219, "completion_tokens": 11, "total_tokens": 10230, "prompt_tokens_details": {"cached_tokens": 10176}, "completion_tokens_details": {"reasoning_tokens": 0}}, "exact_mode": "exact", "tensorfold": {"enable_thinking": false, "reasoning_effort": "none", "engine": "lanes", "tokens_per_second": 36.13988187029093, "seconds": 0.27670262, "prefill_seconds": 0.267597819, "prefill_widths": [], "prefill_raised": [], "time_to_first_token": 0.268215425, "sampling": "greedy", "drafts": false, "token_sha": "eea964a89e62", "token_sha256": "eea964a89e62f6e2059b2da5a676da894801486bd2b3f05aad65bbf32aacef96", "min_rows": 1}, "speculative": {"rounds": 10, "drafted": 0, "accepted": 0, "acceptance_rate": 0.0, "tokens_per_round": 1.1}}, "seconds": 0.5461170673370361} +{"url": "http://127.0.0.1:30461/v1/chat/completions", "request": {"model": "flashnext", "messages": [{"role": "system", "content": "You are a careful assistant. 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note2x386 note3x201 note4x16 note5x844 note6x659 note7x474 note8x289 note9x104 note10x932 note11x747 note12x562 note13x377 note14x192 note15x7 note16x835 note17x650 note18x465 note19x280 note20x95 note21x923 note22x738 note23x553 note24x368 note25x183 note26x1011 note27x826 note28x641 note29x456 note30x271 note31x86 note32x914 note33x729 note34x544 note35x359 note36x174 note37x1002 note38x817 note39x632 note40x447 note41x262 note42x77 note43x905 note44x720 note45x535 note46x350 note47x165 note48x993 note49x808 note50x623 note51x438 note52x253 note53x68 note54x896 note55x711 note56x526 note57x341 note58x156 note59x984 note60x799 note61x614 note62x429 note63x244 note64x59 note65x887 note66x702 note67x517 note68x332 note69x147 note70x975 note71x790 note72x605 note73x420 note74x235 note75x50 note76x878 note77x693 note78x508 note79x323 note80x138 note81x966 note82x781 note83x596 note84x411 note85x226 note86x41 note87x869 note88x684 note0x499 note1x314 note2x129 note3x957 note4x772 note5x587 note6x402 note7x217 note8x32 note9x860 note10x675 note11x490 note12x305 note13x120 note14x948 note15x763 note16x578 note17x393 note18x208 note19x23 note20x851 note21x666 note22x481 note23x296 note24x111 note25x939 note26x754 note27x569 note28x384 note29x199 note30x14 note31x842 note32x657 note33x472 note34x287 note35x102 note36x930 note37x745 note38x560 note39x375 note40x190 note41x5 note42x833 note43x648 note44x463 note45x278 note46x93 note47x921 note48x736 note49x551 note50x366 note51x181 note52x1009 note53x824 note54x639 note55x454 note56x269 note57x84 note58x912 note59x727 note60x542 note61x357 note62x172 note63x1000 note64x815 note65x630 note66x445 note67x260 note68x75 note69x903 note70x718 note71x533 note72x348 note73x163 note74x991 note75x806 note76x621 note77x436 note78x251 note79x66 note80x894 note81x709 note82x524 note83x339 note84x154 note85x982 note86x797 note87x612 note88x427 note0x242 note1x57 note2x885 note3x700 note4x515 note5x330 note6x145 note7x973 note8x788 note9x603 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note13x619 note14x434 note15x249 note16x64 note17x892 note18x707 note19x522 note20x337 note21x152 note22x980 note23x795 note24x610 note25x425 note26x240 note27x55 note28x883 note29x698 note30x513 note31x328 note32x143 note33x971 note34x786 note35x601 note36x416 note37x231 note38x46 note39x874 note40x689 note41x504 note42x319 note43x134 note44x962 note45x777 note46x592 note47x407 note48x222 note49x37 note50x865 note51x680 note52x495 note53x310 note54x125 note55x953 note56x768 note57x583 note58x398 note59x213 note60x28 note61x856 note62x671 note63x486 note64x301 note65x116 note66x944 note67x759 note68x574 note69x389 note70x204 note71x19 note72x847 note73x662 note74x477 note75x292 note76x107 note77x935 note78x750 note79x565 note80x380 note81x195 note82x10 note83x838 note84x653 note85x468 note86x283 note87x98 note88x926 note0x741 note1x556 note2x371 note3x186 note4x1 note5x829 note6x644 note7x459 note8x274 note9x89 note10x917 note11x732 note12x547 note13x362 note14x177 note15x1005 note16x820 note17x635 note18x450 note19x265 note20x80 note21x908 note22x723 note23x538 note24x353 note25x168 note26x996 note27x811 note28x626 note29x441 note30x256 note31x71 note32x899 note33x714 note34x529 note35x344 note36x159 note37x987 note38x802 note39x617 note40x432 note41x247 note42x62 note43x890 note44x705 note45x520 note46x335 note47x150 note48x978 note49x793 note50x608 note51x423 note52x238 note53x53 note54x881 note55x696 note56x511 note57x326 note58x141 note59x969 note60x784 note61x599 note62x414 note63x229 note64x44 note65x872 note66x687 note67x502 note68x317 note69x132 note70x960 note71x775 note72x590 note73x405 note74x220 note75x35 note76x863 note77x678 note78x493 note79x308 note80x123 note81x951 note82x766 note83x581 note84x396 note85x211 note86x26 note87x854 note88x669 note0x484 note1x299 note2x114 note3x942 note4x757 note5x572 note6x387 note7x202 note8x17 note9x845 note10x660 note11x475 note12x290 note13x105 note14x933 note15x748 note16x563 note17x378 note18x193 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note25x410 note26x225 note27x40 note28x868 note29x683 note30x498 note31x313 note32x128 note33x956 note34x771 note35x586 note36x401 note37x216 note38x31 note39x859 note40x674 note41x489 note42x304 note43x119 note44x947 note45x762 note46x577 note47x392 note48x207 note49x22 note50x850 note51x665 note52x480 note53x295 note54x110 note55x938 note56x753 note57x568 note58x383 note59x198 note60x13 note61x841 note62x656 note63x471 note64x286 note65x101 note66x929 note67x744 note68x559 note69x374 note70x189 note71x4 note72x832 note73x647 note74x462 note75x277 note76x92 note77x920 note78x735 note79x550 note80x365 note81x180 note82x1008 note83x823 note84x638 note85x453 note86x268 note87x83 note88x911 note0x726 note1x541 note2x356 note3x171 note4x999 note5x814 note6x629 note7x444 note8x259 note9x74 note10x902 note11x717 note12x532 note13x347 note14x162 note15x990 note16x805 note17x620 note18x435 note19x250 note20x65 note21x893 note22x708 note23x523 note24x338 note25x153 note26x981 note27x796 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note35x828 note36x643 note37x458 note38x273 note39x88 note40x916 note41x731 note42x546 note43x361 note44x176 note45x1004 note46x819 note47x634 note48x449 note49x264 note50x79 note51x907 note52x722 note53x537 note54x352 note55x167 note56x995 note57x810 note58x625 note59x440 note60x255 note61x70 note62x898 note63x713 note64x528 note65x343 note66x158 note67x986 note68x801 note69x616 note70x431 note71x246 note72x61 note73x889 note74x704 note75x519 note76x334 note77x149 note78x977 note79x792 note80x607 note81x422 note82x237 note83x52 note84x880 note85x695 note86x510 note87x325 note88x140 note0x968 note1x783 note2x598 note3x413 note4x228 note5x43 note6x871 note7x686 note8x501 note9x316 note10x131 note11x959 note12x774 note13x589 note14x404 note15x219 note16x34 note17x862 note18x677 note19x492 note20x307 note21x122 note22x950 note23x765 note24x580 note25x395 note26x210 note27x25 note28x853 note29x668 note30x483 note31x298 note32x113 note33x941 note34x756 note35x571 note36x386 note37x201 note38x16 note39x844 note40x659 note41x474 note42x289 note43x104 note44x932 note45x747 note46x562 note47x377 note48x192 note49x7 note50x835 note51x650 note52x465 note53x280 note54x95 note55x923 note56x738 note57x553 note58x368 note59x183 note60x1011 note61x826 note62x641 note63x456 note64x271 note65x86 note66x914 note67x729 note68x544 note69x359 note70x174 note71x1002 note72x817 note73x632 note74x447 note75x262 note76x77 note77x905 note78x720 note79x535 note80x350 note81x165 note82x993 note83x808 note84x623 note85x438 note86x253 note87x68 note88x896 note0x711 note1x526 note2x341 note3x156 note4x984 note5x799 note6x614 note7x429 note8x244 note9x59 note10x887 note11x702 note12x517 note13x332 note14x147 note15x975 note16x790 note17x605 note18x420 note19x235 note20x50 note21x878 note22x693 note23x508 note24x323 note25x138 note26x966 note27x781 note28x596 note29x411 note30x226 note31x41 note32x869 note33x684 note34x499 note35x314 note36x129 note37x957 note38x772 note39x587 note40x402 note41x217 note42x32 note43x860 note44x675 note45x490 note46x305 note47x120 note48x948 note49x763 note50x578 note51x393 note52x208 note53x23 note54x851 note55x666 note56x481 note57x296 note58x111 note59x939 note60x754 note61x569 note62x384 note63x199 note64x14 note65x842 note66x657 note67x472 note68x287 note69x102 note70x930 note71x745 note72x560 note73x375 note74x190 note75x5 note76x833 note77x648 note78x463 note79x278 note80x93 note81x921 note82x736 note83x551 note84x366 note85x181 note86x1009 note87x824 note88x639 note0x454 note1x269 note2x84 note3x912 note4x727 note5x542 note6x357 note7x172 note8x1000 note9x815 note10x630 note11x445 note12x260 note13x75 note14x903 note15x718 note16x533 note17x348 note18x163 note19x991 note20x806 note21x621 note22x436 note23x251 note24x66 note25x894 note26x709 note27x524 note28x339 note29x154 note30x982 note31x797 note32x612 note33x427 note34x242 note35x57 note36x885 note37x700 note38x515 note39x330 note40x145 note41x973 note42x788 note43x603 note44x418 note45x233 note46x48 note47x876 note48x691 note49x506 note50x321 note51x136 note52x964 note53x779 note54x594 note55x409 note56x224 note57x39 note58x867 note59x682 note60x497 note61x312 note62x127 note63x955 note64x770 note65x585 note66x400 note67x215 note68x30 note69x858 note70x673 note71x488 note72x303 note73x118 note74x946 note75x761 note76x576 note77x391 note78x206 note79x21 note80x849 note81x664 note82x479 note83x294 note84x109 note85x937 note86x752 note87x567 note88x382 note0x197 note1x12 note2x840 note3x655 note4x470 note5x285 note6x100 note7x928 note8x743 note9x558 note10x373 note11x188 note12x3 note13x831 note14x646 note15x461 note16x276 note17x91 note18x919 note19x734 note20x549 note21x364 note22x179 note23x1007 note24x822 note25x637 note26x452 note27x267 note28x82 note29x910 note30x725 note31x540 note32x355 note33x170 note34x998 note35x813 note36x628 note37x443 note38x258 note39x73 note40x901 note41x716 note42x531 note43x346 note44x161 note45x989 note46x804 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note50x820 note51x635 note52x450 note53x265 note54x80 note55x908 note56x723 note57x538 note58x353 note59x168 note60x996 note61x811 note62x626 note63x441 note64x256 note65x71 note66x899 note67x714 note68x529 note69x344 note70x159 note71x987 note72x802 note73x617 note74x432 note75x247"}, {"role": "user", "content": "What is the first note?"}, {"role": "assistant", "content": "The first note is **note0x0**."}, {"role": "user", "content": "And the second one?"}], "max_tokens": 48, "temperature": 0.0, "draft": false, "chat_template_kwargs": {"enable_thinking": false}}, "status": 200, "response": {"id": "chatcmpl-f0b6a4b4521a150733d8cdeb52285b86", "object": "chat.completion", "created": 1793474501, "model": "flashnext", "choices": [{"index": 0, "message": {"role": "assistant", "content": "The second note is **note1x828**."}, "finish_reason": "stop"}], "usage": {"prompt_tokens": 10248, "completion_tokens": 13, "total_tokens": 10261, "prompt_tokens_details": {"cached_tokens": 10240}, "completion_tokens_details": {"reasoning_tokens": 0}}, "exact_mode": "exact", "tensorfold": {"enable_thinking": false, "reasoning_effort": "none", "engine": "lanes", "tokens_per_second": 36.20597393923564, "seconds": 0.331437017, "prefill_seconds": 0.088513216, "prefill_widths": [], "prefill_raised": [], "time_to_first_token": 0.089732056, "sampling": "greedy", "drafts": false, "token_sha": "7e4bf5aba972", "token_sha256": "7e4bf5aba9727191d8505e971356abb0485616846741651f36545f4775ef04fc", "min_rows": 1}, "speculative": {"rounds": 12, "drafted": 0, "accepted": 0, "acceptance_rate": 0.0, "tokens_per_round": 1.0833333333333333}}, "seconds": 0.42244386672973633} +{"url": "http://127.0.0.1:30461/v1/chat/completions", "request": {"model": "flashnext", "messages": [{"role": "system", "content": "You are a careful assistant. Reference notes: note0x0 note1x828 note2x643 note3x458 note4x273 note5x88 note6x916 note7x731 note8x546 note9x361 note10x176 note11x1004 note12x819 note13x634 note14x449 note15x264 note16x79 note17x907 note18x722 note19x537 note20x352 note21x167 note22x995 note23x810 note24x625 note25x440 note26x255 note27x70 note28x898 note29x713 note30x528 note31x343 note32x158 note33x986 note34x801 note35x616 note36x431 note37x246 note38x61 note39x889 note40x704 note41x519 note42x334 note43x149 note44x977 note45x792 note46x607 note47x422 note48x237 note49x52 note50x880 note51x695 note52x510 note53x325 note54x140 note55x968 note56x783 note57x598 note58x413 note59x228 note60x43 note61x871 note62x686 note63x501 note64x316 note65x131 note66x959 note67x774 note68x589 note69x404 note70x219 note71x34 note72x862 note73x677 note74x492 note75x307 note76x122 note77x950 note78x765 note79x580 note80x395 note81x210 note82x25 note83x853 note84x668 note85x483 note86x298 note87x113 note88x941 note0x756 note1x571 note2x386 note3x201 note4x16 note5x844 note6x659 note7x474 note8x289 note9x104 note10x932 note11x747 note12x562 note13x377 note14x192 note15x7 note16x835 note17x650 note18x465 note19x280 note20x95 note21x923 note22x738 note23x553 note24x368 note25x183 note26x1011 note27x826 note28x641 note29x456 note30x271 note31x86 note32x914 note33x729 note34x544 note35x359 note36x174 note37x1002 note38x817 note39x632 note40x447 note41x262 note42x77 note43x905 note44x720 note45x535 note46x350 note47x165 note48x993 note49x808 note50x623 note51x438 note52x253 note53x68 note54x896 note55x711 note56x526 note57x341 note58x156 note59x984 note60x799 note61x614 note62x429 note63x244 note64x59 note65x887 note66x702 note67x517 note68x332 note69x147 note70x975 note71x790 note72x605 note73x420 note74x235 note75x50 note76x878 note77x693 note78x508 note79x323 note80x138 note81x966 note82x781 note83x596 note84x411 note85x226 note86x41 note87x869 note88x684 note0x499 note1x314 note2x129 note3x957 note4x772 note5x587 note6x402 note7x217 note8x32 note9x860 note10x675 note11x490 note12x305 note13x120 note14x948 note15x763 note16x578 note17x393 note18x208 note19x23 note20x851 note21x666 note22x481 note23x296 note24x111 note25x939 note26x754 note27x569 note28x384 note29x199 note30x14 note31x842 note32x657 note33x472 note34x287 note35x102 note36x930 note37x745 note38x560 note39x375 note40x190 note41x5 note42x833 note43x648 note44x463 note45x278 note46x93 note47x921 note48x736 note49x551 note50x366 note51x181 note52x1009 note53x824 note54x639 note55x454 note56x269 note57x84 note58x912 note59x727 note60x542 note61x357 note62x172 note63x1000 note64x815 note65x630 note66x445 note67x260 note68x75 note69x903 note70x718 note71x533 note72x348 note73x163 note74x991 note75x806 note76x621 note77x436 note78x251 note79x66 note80x894 note81x709 note82x524 note83x339 note84x154 note85x982 note86x797 note87x612 note88x427 note0x242 note1x57 note2x885 note3x700 note4x515 note5x330 note6x145 note7x973 note8x788 note9x603 note10x418 note11x233 note12x48 note13x876 note14x691 note15x506 note16x321 note17x136 note18x964 note19x779 note20x594 note21x409 note22x224 note23x39 note24x867 note25x682 note26x497 note27x312 note28x127 note29x955 note30x770 note31x585 note32x400 note33x215 note34x30 note35x858 note36x673 note37x488 note38x303 note39x118 note40x946 note41x761 note42x576 note43x391 note44x206 note45x21 note46x849 note47x664 note48x479 note49x294 note50x109 note51x937 note52x752 note53x567 note54x382 note55x197 note56x12 note57x840 note58x655 note59x470 note60x285 note61x100 note62x928 note63x743 note64x558 note65x373 note66x188 note67x3 note68x831 note69x646 note70x461 note71x276 note72x91 note73x919 note74x734 note75x549 note76x364 note77x179 note78x1007 note79x822 note80x637 note81x452 note82x267 note83x82 note84x910 note85x725 note86x540 note87x355 note88x170 note0x998 note1x813 note2x628 note3x443 note4x258 note5x73 note6x901 note7x716 note8x531 note9x346 note10x161 note11x989 note12x804 note13x619 note14x434 note15x249 note16x64 note17x892 note18x707 note19x522 note20x337 note21x152 note22x980 note23x795 note24x610 note25x425 note26x240 note27x55 note28x883 note29x698 note30x513 note31x328 note32x143 note33x971 note34x786 note35x601 note36x416 note37x231 note38x46 note39x874 note40x689 note41x504 note42x319 note43x134 note44x962 note45x777 note46x592 note47x407 note48x222 note49x37 note50x865 note51x680 note52x495 note53x310 note54x125 note55x953 note56x768 note57x583 note58x398 note59x213 note60x28 note61x856 note62x671 note63x486 note64x301 note65x116 note66x944 note67x759 note68x574 note69x389 note70x204 note71x19 note72x847 note73x662 note74x477 note75x292 note76x107 note77x935 note78x750 note79x565 note80x380 note81x195 note82x10 note83x838 note84x653 note85x468 note86x283 note87x98 note88x926 note0x741 note1x556 note2x371 note3x186 note4x1 note5x829 note6x644 note7x459 note8x274 note9x89 note10x917 note11x732 note12x547 note13x362 note14x177 note15x1005 note16x820 note17x635 note18x450 note19x265 note20x80 note21x908 note22x723 note23x538 note24x353 note25x168 note26x996 note27x811 note28x626 note29x441 note30x256 note31x71 note32x899 note33x714 note34x529 note35x344 note36x159 note37x987 note38x802 note39x617 note40x432 note41x247 note42x62 note43x890 note44x705 note45x520 note46x335 note47x150 note48x978 note49x793 note50x608 note51x423 note52x238 note53x53 note54x881 note55x696 note56x511 note57x326 note58x141 note59x969 note60x784 note61x599 note62x414 note63x229 note64x44 note65x872 note66x687 note67x502 note68x317 note69x132 note70x960 note71x775 note72x590 note73x405 note74x220 note75x35 note76x863 note77x678 note78x493 note79x308 note80x123 note81x951 note82x766 note83x581 note84x396 note85x211 note86x26 note87x854 note88x669 note0x484 note1x299 note2x114 note3x942 note4x757 note5x572 note6x387 note7x202 note8x17 note9x845 note10x660 note11x475 note12x290 note13x105 note14x933 note15x748 note16x563 note17x378 note18x193 note19x8 note20x836 note21x651 note22x466 note23x281 note24x96 note25x924 note26x739 note27x554 note28x369 note29x184 note30x1012 note31x827 note32x642 note33x457 note34x272 note35x87 note36x915 note37x730 note38x545 note39x360 note40x175 note41x1003 note42x818 note43x633 note44x448 note45x263 note46x78 note47x906 note48x721 note49x536 note50x351 note51x166 note52x994 note53x809 note54x624 note55x439 note56x254 note57x69 note58x897 note59x712 note60x527 note61x342 note62x157 note63x985 note64x800 note65x615 note66x430 note67x245 note68x60 note69x888 note70x703 note71x518 note72x333 note73x148 note74x976 note75x791 note76x606 note77x421 note78x236 note79x51 note80x879 note81x694 note82x509 note83x324 note84x139 note85x967 note86x782 note87x597 note88x412 note0x227 note1x42 note2x870 note3x685 note4x500 note5x315 note6x130 note7x958 note8x773 note9x588 note10x403 note11x218 note12x33 note13x861 note14x676 note15x491 note16x306 note17x121 note18x949 note19x764 note20x579 note21x394 note22x209 note23x24 note24x852 note25x667 note26x482 note27x297 note28x112 note29x940 note30x755 note31x570 note32x385 note33x200 note34x15 note35x843 note36x658 note37x473 note38x288 note39x103 note40x931 note41x746 note42x561 note43x376 note44x191 note45x6 note46x834 note47x649 note48x464 note49x279 note50x94 note51x922 note52x737 note53x552 note54x367 note55x182 note56x1010 note57x825 note58x640 note59x455 note60x270 note61x85 note62x913 note63x728 note64x543 note65x358 note66x173 note67x1001 note68x816 note69x631 note70x446 note71x261 note72x76 note73x904 note74x719 note75x534 note76x349 note77x164 note78x992 note79x807 note80x622 note81x437 note82x252 note83x67 note84x895 note85x710 note86x525 note87x340 note88x155 note0x983 note1x798 note2x613 note3x428 note4x243 note5x58 note6x886 note7x701 note8x516 note9x331 note10x146 note11x974 note12x789 note13x604 note14x419 note15x234 note16x49 note17x877 note18x692 note19x507 note20x322 note21x137 note22x965 note23x780 note24x595 note25x410 note26x225 note27x40 note28x868 note29x683 note30x498 note31x313 note32x128 note33x956 note34x771 note35x586 note36x401 note37x216 note38x31 note39x859 note40x674 note41x489 note42x304 note43x119 note44x947 note45x762 note46x577 note47x392 note48x207 note49x22 note50x850 note51x665 note52x480 note53x295 note54x110 note55x938 note56x753 note57x568 note58x383 note59x198 note60x13 note61x841 note62x656 note63x471 note64x286 note65x101 note66x929 note67x744 note68x559 note69x374 note70x189 note71x4 note72x832 note73x647 note74x462 note75x277 note76x92 note77x920 note78x735 note79x550 note80x365 note81x180 note82x1008 note83x823 note84x638 note85x453 note86x268 note87x83 note88x911 note0x726 note1x541 note2x356 note3x171 note4x999 note5x814 note6x629 note7x444 note8x259 note9x74 note10x902 note11x717 note12x532 note13x347 note14x162 note15x990 note16x805 note17x620 note18x435 note19x250 note20x65 note21x893 note22x708 note23x523 note24x338 note25x153 note26x981 note27x796 note28x611 note29x426 note30x241 note31x56 note32x884 note33x699 note34x514 note35x329 note36x144 note37x972 note38x787 note39x602 note40x417 note41x232 note42x47 note43x875 note44x690 note45x505 note46x320 note47x135 note48x963 note49x778 note50x593 note51x408 note52x223 note53x38 note54x866 note55x681 note56x496 note57x311 note58x126 note59x954 note60x769 note61x584 note62x399 note63x214 note64x29 note65x857 note66x672 note67x487 note68x302 note69x117 note70x945 note71x760 note72x575 note73x390 note74x205 note75x20 note76x848 note77x663 note78x478 note79x293 note80x108 note81x936 note82x751 note83x566 note84x381 note85x196 note86x11 note87x839 note88x654 note0x469 note1x284 note2x99 note3x927 note4x742 note5x557 note6x372 note7x187 note8x2 note9x830 note10x645 note11x460 note12x275 note13x90 note14x918 note15x733 note16x548 note17x363 note18x178 note19x1006 note20x821 note21x636 note22x451 note23x266 note24x81 note25x909 note26x724 note27x539 note28x354 note29x169 note30x997 note31x812 note32x627 note33x442 note34x257 note35x72 note36x900 note37x715 note38x530 note39x345 note40x160 note41x988 note42x803 note43x618 note44x433 note45x248 note46x63 note47x891 note48x706 note49x521 note50x336 note51x151 note52x979 note53x794 note54x609 note55x424 note56x239 note57x54 note58x882 note59x697 note60x512 note61x327 note62x142 note63x970 note64x785 note65x600 note66x415 note67x230 note68x45 note69x873 note70x688 note71x503 note72x318 note73x133 note74x961 note75x776 note76x591 note77x406 note78x221 note79x36 note80x864 note81x679 note82x494 note83x309 note84x124 note85x952 note86x767 note87x582 note88x397 note0x212 note1x27 note2x855 note3x670 note4x485 note5x300 note6x115 note7x943 note8x758 note9x573 note10x388 note11x203 note12x18 note13x846 note14x661 note15x476 note16x291 note17x106 note18x934 note19x749 note20x564 note21x379 note22x194 note23x9 note24x837 note25x652 note26x467 note27x282 note28x97 note29x925 note30x740 note31x555 note32x370 note33x185 note34x0 note35x828 note36x643 note37x458 note38x273 note39x88 note40x916 note41x731 note42x546 note43x361 note44x176 note45x1004 note46x819 note47x634 note48x449 note49x264 note50x79 note51x907 note52x722 note53x537 note54x352 note55x167 note56x995 note57x810 note58x625 note59x440 note60x255 note61x70 note62x898 note63x713 note64x528 note65x343 note66x158 note67x986 note68x801 note69x616 note70x431 note71x246 note72x61 note73x889 note74x704 note75x519 note76x334 note77x149 note78x977 note79x792 note80x607 note81x422 note82x237 note83x52 note84x880 note85x695 note86x510 note87x325 note88x140 note0x968 note1x783 note2x598 note3x413 note4x228 note5x43 note6x871 note7x686 note8x501 note9x316 note10x131 note11x959 note12x774 note13x589 note14x404 note15x219 note16x34 note17x862 note18x677 note19x492 note20x307 note21x122 note22x950 note23x765 note24x580 note25x395 note26x210 note27x25 note28x853 note29x668 note30x483 note31x298 note32x113 note33x941 note34x756 note35x571 note36x386 note37x201 note38x16 note39x844 note40x659 note41x474 note42x289 note43x104 note44x932 note45x747 note46x562 note47x377 note48x192 note49x7 note50x835 note51x650 note52x465 note53x280 note54x95 note55x923 note56x738 note57x553 note58x368 note59x183 note60x1011 note61x826 note62x641 note63x456 note64x271 note65x86 note66x914 note67x729 note68x544 note69x359 note70x174 note71x1002 note72x817 note73x632 note74x447 note75x262 note76x77 note77x905 note78x720 note79x535 note80x350 note81x165 note82x993 note83x808 note84x623 note85x438 note86x253 note87x68 note88x896 note0x711 note1x526 note2x341 note3x156 note4x984 note5x799 note6x614 note7x429 note8x244 note9x59 note10x887 note11x702 note12x517 note13x332 note14x147 note15x975 note16x790 note17x605 note18x420 note19x235 note20x50 note21x878 note22x693 note23x508 note24x323 note25x138 note26x966 note27x781 note28x596 note29x411 note30x226 note31x41 note32x869 note33x684 note34x499 note35x314 note36x129 note37x957 note38x772 note39x587 note40x402 note41x217 note42x32 note43x860 note44x675 note45x490 note46x305 note47x120 note48x948 note49x763 note50x578 note51x393 note52x208 note53x23 note54x851 note55x666 note56x481 note57x296 note58x111 note59x939 note60x754 note61x569 note62x384 note63x199 note64x14 note65x842 note66x657 note67x472 note68x287 note69x102 note70x930 note71x745 note72x560 note73x375 note74x190 note75x5 note76x833 note77x648 note78x463 note79x278 note80x93 note81x921 note82x736 note83x551 note84x366 note85x181 note86x1009 note87x824 note88x639 note0x454 note1x269 note2x84 note3x912 note4x727 note5x542 note6x357 note7x172 note8x1000 note9x815 note10x630 note11x445 note12x260 note13x75 note14x903 note15x718 note16x533 note17x348 note18x163 note19x991 note20x806 note21x621 note22x436 note23x251 note24x66 note25x894 note26x709 note27x524 note28x339 note29x154 note30x982 note31x797 note32x612 note33x427 note34x242 note35x57 note36x885 note37x700 note38x515 note39x330 note40x145 note41x973 note42x788 note43x603 note44x418 note45x233 note46x48 note47x876 note48x691 note49x506 note50x321 note51x136 note52x964 note53x779 note54x594 note55x409 note56x224 note57x39 note58x867 note59x682 note60x497 note61x312 note62x127 note63x955 note64x770 note65x585 note66x400 note67x215 note68x30 note69x858 note70x673 note71x488 note72x303 note73x118 note74x946 note75x761 note76x576 note77x391 note78x206 note79x21 note80x849 note81x664 note82x479 note83x294 note84x109 note85x937 note86x752 note87x567 note88x382 note0x197 note1x12 note2x840 note3x655 note4x470 note5x285 note6x100 note7x928 note8x743 note9x558 note10x373 note11x188 note12x3 note13x831 note14x646 note15x461 note16x276 note17x91 note18x919 note19x734 note20x549 note21x364 note22x179 note23x1007 note24x822 note25x637 note26x452 note27x267 note28x82 note29x910 note30x725 note31x540 note32x355 note33x170 note34x998 note35x813 note36x628 note37x443 note38x258 note39x73 note40x901 note41x716 note42x531 note43x346 note44x161 note45x989 note46x804 note47x619 note48x434 note49x249 note50x64 note51x892 note52x707 note53x522 note54x337 note55x152 note56x980 note57x795 note58x610 note59x425 note60x240 note61x55 note62x883 note63x698 note64x513 note65x328 note66x143 note67x971 note68x786 note69x601 note70x416 note71x231 note72x46 note73x874 note74x689 note75x504 note76x319 note77x134 note78x962 note79x777 note80x592 note81x407 note82x222 note83x37 note84x865 note85x680 note86x495 note87x310 note88x125 note0x953 note1x768 note2x583 note3x398 note4x213 note5x28 note6x856 note7x671 note8x486 note9x301 note10x116 note11x944 note12x759 note13x574 note14x389 note15x204 note16x19 note17x847 note18x662 note19x477 note20x292 note21x107 note22x935 note23x750 note24x565 note25x380 note26x195 note27x10 note28x838 note29x653 note30x468 note31x283 note32x98 note33x926 note34x741 note35x556 note36x371 note37x186 note38x1 note39x829 note40x644 note41x459 note42x274 note43x89 note44x917 note45x732 note46x547 note47x362 note48x177 note49x1005 note50x820 note51x635 note52x450 note53x265 note54x80 note55x908 note56x723 note57x538 note58x353 note59x168 note60x996 note61x811 note62x626 note63x441 note64x256 note65x71 note66x899 note67x714 note68x529 note69x344 note70x159 note71x987 note72x802 note73x617 note74x432 note75x247"}, {"role": "user", "content": "What is the first note?"}, {"role": "assistant", "content": "The first note is **note0x0**."}, {"role": "user", "content": "And the second one?"}, {"role": "assistant", "content": "The second note is **note1x828**."}, {"role": "user", "content": "Is note5x5 listed?"}], "max_tokens": 48, "temperature": 0.0, "draft": false, "chat_template_kwargs": {"enable_thinking": false}}, "status": 200, "response": {"id": "chatcmpl-4563ef9a7050e36f683a03cd054ee54f", "object": "chat.completion", "created": 1793474501, "model": "flashnext", "choices": [{"index": 0, "message": {"role": "assistant", "content": "No, **note5x5** is not listed in the provided reference notes.\n\nThe list contains notes with hex suffixes (e.g., `note5x88`, `note5x587`, `note5"}, "finish_reason": "length"}], "usage": {"prompt_tokens": 10281, "completion_tokens": 48, "total_tokens": 10329, "prompt_tokens_details": {"cached_tokens": 10240}, "completion_tokens_details": {"reasoning_tokens": 0}}, "exact_mode": "exact", "tensorfold": {"enable_thinking": false, "reasoning_effort": "none", "engine": "lanes", "tokens_per_second": 36.14720396608968, "seconds": 1.30023888, "prefill_seconds": 0.25137599, "prefill_widths": [], "prefill_raised": [], "time_to_first_token": 0.252441685, "sampling": "greedy", "drafts": false, "token_sha": "e7287d6bf366", "token_sha256": "e7287d6bf36620acbd71b1537e7b5ea9b239198191676c8c2261aad653c64a81", "min_rows": 1}, "speculative": {"rounds": 47, "drafted": 0, "accepted": 0, "acceptance_rate": 0.0, "tokens_per_round": 1.0212765957446808}}, "seconds": 1.5535354614257812} +{"url": "http://127.0.0.1:30461/v1/chat/completions", "request": {"model": "flashnext", "messages": [{"role": "system", "content": "You are a careful assistant. Reference notes: note0x0 note1x828 note2x643 note3x458 note4x273 note5x88 note6x916 note7x731 note8x546 note9x361 note10x176 note11x1004 note12x819 note13x634 note14x449 note15x264 note16x79 note17x907 note18x722 note19x537 note20x352 note21x167 note22x995 note23x810 note24x625 note25x440 note26x255 note27x70 note28x898 note29x713 note30x528 note31x343 note32x158 note33x986 note34x801 note35x616 note36x431 note37x246 note38x61 note39x889 note40x704 note41x519 note42x334 note43x149 note44x977 note45x792 note46x607 note47x422 note48x237 note49x52 note50x880 note51x695 note52x510 note53x325 note54x140 note55x968 note56x783 note57x598 note58x413 note59x228 note60x43 note61x871 note62x686 note63x501 note64x316 note65x131 note66x959 note67x774 note68x589 note69x404 note70x219 note71x34 note72x862 note73x677 note74x492 note75x307 note76x122 note77x950 note78x765 note79x580 note80x395 note81x210 note82x25 note83x853 note84x668 note85x483 note86x298 note87x113 note88x941 note0x756 note1x571 note2x386 note3x201 note4x16 note5x844 note6x659 note7x474 note8x289 note9x104 note10x932 note11x747 note12x562 note13x377 note14x192 note15x7 note16x835 note17x650 note18x465 note19x280 note20x95 note21x923 note22x738 note23x553 note24x368 note25x183 note26x1011 note27x826 note28x641 note29x456 note30x271 note31x86 note32x914 note33x729 note34x544 note35x359 note36x174 note37x1002 note38x817 note39x632 note40x447 note41x262 note42x77 note43x905 note44x720 note45x535 note46x350 note47x165 note48x993 note49x808 note50x623 note51x438 note52x253 note53x68 note54x896 note55x711 note56x526 note57x341 note58x156 note59x984 note60x799 note61x614 note62x429 note63x244 note64x59 note65x887 note66x702 note67x517 note68x332 note69x147 note70x975 note71x790 note72x605 note73x420 note74x235 note75x50 note76x878 note77x693 note78x508 note79x323 note80x138 note81x966 note82x781 note83x596 note84x411 note85x226 note86x41 note87x869 note88x684 note0x499 note1x314 note2x129 note3x957 note4x772 note5x587 note6x402 note7x217 note8x32 note9x860 note10x675 note11x490 note12x305 note13x120 note14x948 note15x763 note16x578 note17x393 note18x208 note19x23 note20x851 note21x666 note22x481 note23x296 note24x111 note25x939 note26x754 note27x569 note28x384 note29x199 note30x14 note31x842 note32x657 note33x472 note34x287 note35x102 note36x930 note37x745 note38x560 note39x375 note40x190 note41x5 note42x833 note43x648 note44x463 note45x278 note46x93 note47x921 note48x736 note49x551 note50x366 note51x181 note52x1009 note53x824 note54x639 note55x454 note56x269 note57x84 note58x912 note59x727 note60x542 note61x357 note62x172 note63x1000 note64x815 note65x630 note66x445 note67x260 note68x75 note69x903 note70x718 note71x533 note72x348 note73x163 note74x991 note75x806 note76x621 note77x436 note78x251 note79x66 note80x894 note81x709 note82x524 note83x339 note84x154 note85x982 note86x797 note87x612 note88x427 note0x242 note1x57 note2x885 note3x700 note4x515 note5x330 note6x145 note7x973 note8x788 note9x603 note10x418 note11x233 note12x48 note13x876 note14x691 note15x506 note16x321 note17x136 note18x964 note19x779 note20x594 note21x409 note22x224 note23x39 note24x867 note25x682 note26x497 note27x312 note28x127 note29x955 note30x770 note31x585 note32x400 note33x215 note34x30 note35x858 note36x673 note37x488 note38x303 note39x118 note40x946 note41x761 note42x576 note43x391 note44x206 note45x21 note46x849 note47x664 note48x479 note49x294 note50x109 note51x937 note52x752 note53x567 note54x382 note55x197 note56x12 note57x840 note58x655 note59x470 note60x285 note61x100 note62x928 note63x743 note64x558 note65x373 note66x188 note67x3 note68x831 note69x646 note70x461 note71x276 note72x91 note73x919 note74x734 note75x549 note76x364 note77x179 note78x1007 note79x822 note80x637 note81x452 note82x267 note83x82 note84x910 note85x725 note86x540 note87x355 note88x170 note0x998 note1x813 note2x628 note3x443 note4x258 note5x73 note6x901 note7x716 note8x531 note9x346 note10x161 note11x989 note12x804 note13x619 note14x434 note15x249 note16x64 note17x892 note18x707 note19x522 note20x337 note21x152 note22x980 note23x795 note24x610 note25x425 note26x240 note27x55 note28x883 note29x698 note30x513 note31x328 note32x143 note33x971 note34x786 note35x601 note36x416 note37x231 note38x46 note39x874 note40x689 note41x504 note42x319 note43x134 note44x962 note45x777 note46x592 note47x407 note48x222 note49x37 note50x865 note51x680 note52x495 note53x310 note54x125 note55x953 note56x768 note57x583 note58x398 note59x213 note60x28 note61x856 note62x671 note63x486 note64x301 note65x116 note66x944 note67x759 note68x574 note69x389 note70x204 note71x19 note72x847 note73x662 note74x477 note75x292 note76x107 note77x935 note78x750 note79x565 note80x380 note81x195 note82x10 note83x838 note84x653 note85x468 note86x283 note87x98 note88x926 note0x741 note1x556 note2x371 note3x186 note4x1 note5x829 note6x644 note7x459 note8x274 note9x89 note10x917 note11x732 note12x547 note13x362 note14x177 note15x1005 note16x820 note17x635 note18x450 note19x265 note20x80 note21x908 note22x723 note23x538 note24x353 note25x168 note26x996 note27x811 note28x626 note29x441 note30x256 note31x71 note32x899 note33x714 note34x529 note35x344 note36x159 note37x987 note38x802 note39x617 note40x432 note41x247 note42x62 note43x890 note44x705 note45x520 note46x335 note47x150 note48x978 note49x793 note50x608 note51x423 note52x238 note53x53 note54x881 note55x696 note56x511 note57x326 note58x141 note59x969 note60x784 note61x599 note62x414 note63x229 note64x44 note65x872 note66x687 note67x502 note68x317 note69x132 note70x960 note71x775 note72x590 note73x405 note74x220 note75x35 note76x863 note77x678 note78x493 note79x308 note80x123 note81x951 note82x766 note83x581 note84x396 note85x211 note86x26 note87x854 note88x669 note0x484 note1x299 note2x114 note3x942 note4x757 note5x572 note6x387 note7x202 note8x17 note9x845 note10x660 note11x475 note12x290 note13x105 note14x933 note15x748 note16x563 note17x378 note18x193 note19x8 note20x836 note21x651 note22x466 note23x281 note24x96 note25x924 note26x739 note27x554 note28x369 note29x184 note30x1012 note31x827 note32x642 note33x457 note34x272 note35x87 note36x915 note37x730 note38x545 note39x360 note40x175 note41x1003 note42x818 note43x633 note44x448 note45x263 note46x78 note47x906 note48x721 note49x536 note50x351 note51x166 note52x994 note53x809 note54x624 note55x439 note56x254 note57x69 note58x897 note59x712 note60x527 note61x342 note62x157 note63x985 note64x800 note65x615 note66x430 note67x245 note68x60 note69x888 note70x703 note71x518 note72x333 note73x148 note74x976 note75x791 note76x606 note77x421 note78x236 note79x51 note80x879 note81x694 note82x509 note83x324 note84x139 note85x967 note86x782 note87x597 note88x412 note0x227 note1x42 note2x870 note3x685 note4x500 note5x315 note6x130 note7x958 note8x773 note9x588 note10x403 note11x218 note12x33 note13x861 note14x676 note15x491 note16x306 note17x121 note18x949 note19x764 note20x579 note21x394 note22x209 note23x24 note24x852 note25x667 note26x482 note27x297 note28x112 note29x940 note30x755 note31x570 note32x385 note33x200 note34x15 note35x843 note36x658 note37x473 note38x288 note39x103 note40x931 note41x746 note42x561 note43x376 note44x191 note45x6 note46x834 note47x649 note48x464 note49x279 note50x94 note51x922 note52x737 note53x552 note54x367 note55x182 note56x1010 note57x825 note58x640 note59x455 note60x270 note61x85 note62x913 note63x728 note64x543 note65x358 note66x173 note67x1001 note68x816 note69x631 note70x446 note71x261 note72x76 note73x904 note74x719 note75x534 note76x349 note77x164 note78x992 note79x807 note80x622 note81x437 note82x252 note83x67 note84x895 note85x710 note86x525 note87x340 note88x155 note0x983 note1x798 note2x613 note3x428 note4x243 note5x58 note6x886 note7x701 note8x516 note9x331 note10x146 note11x974 note12x789 note13x604 note14x419 note15x234 note16x49 note17x877 note18x692 note19x507 note20x322 note21x137 note22x965 note23x780 note24x595 note25x410 note26x225 note27x40 note28x868 note29x683 note30x498 note31x313 note32x128 note33x956 note34x771 note35x586 note36x401 note37x216 note38x31 note39x859 note40x674 note41x489 note42x304 note43x119 note44x947 note45x762 note46x577 note47x392 note48x207 note49x22 note50x850 note51x665 note52x480 note53x295 note54x110 note55x938 note56x753 note57x568 note58x383 note59x198 note60x13 note61x841 note62x656 note63x471 note64x286 note65x101 note66x929 note67x744 note68x559 note69x374 note70x189 note71x4 note72x832 note73x647 note74x462 note75x277 note76x92 note77x920 note78x735 note79x550 note80x365 note81x180 note82x1008 note83x823 note84x638 note85x453 note86x268 note87x83 note88x911 note0x726 note1x541 note2x356 note3x171 note4x999 note5x814 note6x629 note7x444 note8x259 note9x74 note10x902 note11x717 note12x532 note13x347 note14x162 note15x990 note16x805 note17x620 note18x435 note19x250 note20x65 note21x893 note22x708 note23x523 note24x338 note25x153 note26x981 note27x796 note28x611 note29x426 note30x241 note31x56 note32x884 note33x699 note34x514 note35x329 note36x144 note37x972 note38x787 note39x602 note40x417 note41x232 note42x47 note43x875 note44x690 note45x505 note46x320 note47x135 note48x963 note49x778 note50x593 note51x408 note52x223 note53x38 note54x866 note55x681 note56x496 note57x311 note58x126 note59x954 note60x769 note61x584 note62x399 note63x214 note64x29 note65x857 note66x672 note67x487 note68x302 note69x117 note70x945 note71x760 note72x575 note73x390 note74x205 note75x20 note76x848 note77x663 note78x478 note79x293 note80x108 note81x936 note82x751 note83x566 note84x381 note85x196 note86x11 note87x839 note88x654 note0x469 note1x284 note2x99 note3x927 note4x742 note5x557 note6x372 note7x187 note8x2 note9x830 note10x645 note11x460 note12x275 note13x90 note14x918 note15x733 note16x548 note17x363 note18x178 note19x1006 note20x821 note21x636 note22x451 note23x266 note24x81 note25x909 note26x724 note27x539 note28x354 note29x169 note30x997 note31x812 note32x627 note33x442 note34x257 note35x72 note36x900 note37x715 note38x530 note39x345 note40x160 note41x988 note42x803 note43x618 note44x433 note45x248 note46x63 note47x891 note48x706 note49x521 note50x336 note51x151 note52x979 note53x794 note54x609 note55x424 note56x239 note57x54 note58x882 note59x697 note60x512 note61x327 note62x142 note63x970 note64x785 note65x600 note66x415 note67x230 note68x45 note69x873 note70x688 note71x503 note72x318 note73x133 note74x961 note75x776 note76x591 note77x406 note78x221 note79x36 note80x864 note81x679 note82x494 note83x309 note84x124 note85x952 note86x767 note87x582 note88x397 note0x212 note1x27 note2x855 note3x670 note4x485 note5x300 note6x115 note7x943 note8x758 note9x573 note10x388 note11x203 note12x18 note13x846 note14x661 note15x476 note16x291 note17x106 note18x934 note19x749 note20x564 note21x379 note22x194 note23x9 note24x837 note25x652 note26x467 note27x282 note28x97 note29x925 note30x740 note31x555 note32x370 note33x185 note34x0 note35x828 note36x643 note37x458 note38x273 note39x88 note40x916 note41x731 note42x546 note43x361 note44x176 note45x1004 note46x819 note47x634 note48x449 note49x264 note50x79 note51x907 note52x722 note53x537 note54x352 note55x167 note56x995 note57x810 note58x625 note59x440 note60x255 note61x70 note62x898 note63x713 note64x528 note65x343 note66x158 note67x986 note68x801 note69x616 note70x431 note71x246 note72x61 note73x889 note74x704 note75x519 note76x334 note77x149 note78x977 note79x792 note80x607 note81x422 note82x237 note83x52 note84x880 note85x695 note86x510 note87x325 note88x140 note0x968 note1x783 note2x598 note3x413 note4x228 note5x43 note6x871 note7x686 note8x501 note9x316 note10x131 note11x959 note12x774 note13x589 note14x404 note15x219 note16x34 note17x862 note18x677 note19x492 note20x307 note21x122 note22x950 note23x765 note24x580 note25x395 note26x210 note27x25 note28x853 note29x668 note30x483 note31x298 note32x113 note33x941 note34x756 note35x571 note36x386 note37x201 note38x16 note39x844 note40x659 note41x474 note42x289 note43x104 note44x932 note45x747 note46x562 note47x377 note48x192 note49x7 note50x835 note51x650 note52x465 note53x280 note54x95 note55x923 note56x738 note57x553 note58x368 note59x183 note60x1011 note61x826 note62x641 note63x456 note64x271 note65x86 note66x914 note67x729 note68x544 note69x359 note70x174 note71x1002 note72x817 note73x632 note74x447 note75x262 note76x77 note77x905 note78x720 note79x535 note80x350 note81x165 note82x993 note83x808 note84x623 note85x438 note86x253 note87x68 note88x896 note0x711 note1x526 note2x341 note3x156 note4x984 note5x799 note6x614 note7x429 note8x244 note9x59 note10x887 note11x702 note12x517 note13x332 note14x147 note15x975 note16x790 note17x605 note18x420 note19x235 note20x50 note21x878 note22x693 note23x508 note24x323 note25x138 note26x966 note27x781 note28x596 note29x411 note30x226 note31x41 note32x869 note33x684 note34x499 note35x314 note36x129 note37x957 note38x772 note39x587 note40x402 note41x217 note42x32 note43x860 note44x675 note45x490 note46x305 note47x120 note48x948 note49x763 note50x578 note51x393 note52x208 note53x23 note54x851 note55x666 note56x481 note57x296 note58x111 note59x939 note60x754 note61x569 note62x384 note63x199 note64x14 note65x842 note66x657 note67x472 note68x287 note69x102 note70x930 note71x745 note72x560 note73x375 note74x190 note75x5 note76x833 note77x648 note78x463 note79x278 note80x93 note81x921 note82x736 note83x551 note84x366 note85x181 note86x1009 note87x824 note88x639 note0x454 note1x269 note2x84 note3x912 note4x727 note5x542 note6x357 note7x172 note8x1000 note9x815 note10x630 note11x445 note12x260 note13x75 note14x903 note15x718 note16x533 note17x348 note18x163 note19x991 note20x806 note21x621 note22x436 note23x251 note24x66 note25x894 note26x709 note27x524 note28x339 note29x154 note30x982 note31x797 note32x612 note33x427 note34x242 note35x57 note36x885 note37x700 note38x515 note39x330 note40x145 note41x973 note42x788 note43x603 note44x418 note45x233 note46x48 note47x876 note48x691 note49x506 note50x321 note51x136 note52x964 note53x779 note54x594 note55x409 note56x224 note57x39 note58x867 note59x682 note60x497 note61x312 note62x127 note63x955 note64x770 note65x585 note66x400 note67x215 note68x30 note69x858 note70x673 note71x488 note72x303 note73x118 note74x946 note75x761 note76x576 note77x391 note78x206 note79x21 note80x849 note81x664 note82x479 note83x294 note84x109 note85x937 note86x752 note87x567 note88x382 note0x197 note1x12 note2x840 note3x655 note4x470 note5x285 note6x100 note7x928 note8x743 note9x558 note10x373 note11x188 note12x3 note13x831 note14x646 note15x461 note16x276 note17x91 note18x919 note19x734 note20x549 note21x364 note22x179 note23x1007 note24x822 note25x637 note26x452 note27x267 note28x82 note29x910 note30x725 note31x540 note32x355 note33x170 note34x998 note35x813 note36x628 note37x443 note38x258 note39x73 note40x901 note41x716 note42x531 note43x346 note44x161 note45x989 note46x804 note47x619 note48x434 note49x249 note50x64 note51x892 note52x707 note53x522 note54x337 note55x152 note56x980 note57x795 note58x610 note59x425 note60x240 note61x55 note62x883 note63x698 note64x513 note65x328 note66x143 note67x971 note68x786 note69x601 note70x416 note71x231 note72x46 note73x874 note74x689 note75x504 note76x319 note77x134 note78x962 note79x777 note80x592 note81x407 note82x222 note83x37 note84x865 note85x680 note86x495 note87x310 note88x125 note0x953 note1x768 note2x583 note3x398 note4x213 note5x28 note6x856 note7x671 note8x486 note9x301 note10x116 note11x944 note12x759 note13x574 note14x389 note15x204 note16x19 note17x847 note18x662 note19x477 note20x292 note21x107 note22x935 note23x750 note24x565 note25x380 note26x195 note27x10 note28x838 note29x653 note30x468 note31x283 note32x98 note33x926 note34x741 note35x556 note36x371 note37x186 note38x1 note39x829 note40x644 note41x459 note42x274 note43x89 note44x917 note45x732 note46x547 note47x362 note48x177 note49x1005 note50x820 note51x635 note52x450 note53x265 note54x80 note55x908 note56x723 note57x538 note58x353 note59x168 note60x996 note61x811 note62x626 note63x441 note64x256 note65x71 note66x899 note67x714 note68x529 note69x344 note70x159 note71x987 note72x802 note73x617 note74x432 note75x247"}, {"role": "user", "content": "What is the first note?"}, {"role": "assistant", "content": "The first note is **note0x0**."}, {"role": "user", "content": "And the second one?"}, {"role": "assistant", "content": "The second note is **note1x828**."}, {"role": "user", "content": "Is note5x5 listed?"}], "max_tokens": 48, "temperature": 0.0, "draft": false, "chat_template_kwargs": {"enable_thinking": false}}, "status": 200, "response": {"id": "chatcmpl-fb34c820df81faf877d0861cb3206e2e", "object": "chat.completion", "created": 1793474503, "model": "flashnext", "choices": [{"index": 0, "message": {"role": "assistant", "content": "No, **note5x5** is not listed in the provided reference notes.\n\nThe list contains notes with hex suffixes (e.g., `note5x88`, `note5x587`, `note5"}, "finish_reason": "length"}], "usage": {"prompt_tokens": 10281, "completion_tokens": 48, "total_tokens": 10329, "prompt_tokens_details": {"cached_tokens": 10240}, "completion_tokens_details": {"reasoning_tokens": 0}}, "exact_mode": "exact", "tensorfold": {"enable_thinking": false, "reasoning_effort": "none", "engine": "lanes", "tokens_per_second": 36.02171937387127, "seconds": 1.304768368, "prefill_seconds": 0.252569615, "prefill_widths": [], "prefill_raised": [], "time_to_first_token": 0.253809345, "sampling": "greedy", "drafts": false, "token_sha": "e7287d6bf366", "token_sha256": "e7287d6bf36620acbd71b1537e7b5ea9b239198191676c8c2261aad653c64a81", "min_rows": 1}, "speculative": {"rounds": 47, "drafted": 0, "accepted": 0, "acceptance_rate": 0.0, "tokens_per_round": 1.0212765957446808}}, "seconds": 1.5594532489776611} +{"url": "http://127.0.0.1:30461/v1/chat/completions", "request": {"model": "flashnext", "messages": [{"role": "system", "content": "You are a careful assistant. Reference notes: note0x0 note1x828 note2x643 note3x458 note4x273 note5x88 note6x916 note7x731 note8x546 note9x361 note10x176 note11x1004 note12x819 note13x634 note14x449 note15x264 note16x79 note17x907 note18x722 note19x537 note20x352 note21x167 note22x995 note23x810 note24x625 note25x440 note26x255 note27x70 note28x898 note29x713 note30x528 note31x343 note32x158 note33x986 note34x801 note35x616 note36x431 note37x246 note38x61 note39x889 note40x704 note41x519 note42x334 note43x149 note44x977 note45x792 note46x607 note47x422 note48x237 note49x52 note50x880 note51x695 note52x510 note53x325 note54x140 note55x968 note56x783 note57x598 note58x413 note59x228 note60x43 note61x871 note62x686 note63x501 note64x316 note65x131 note66x959 note67x774 note68x589 note69x404 note70x219 note71x34 note72x862 note73x677 note74x492 note75x307 note76x122 note77x950 note78x765 note79x580 note80x395 note81x210 note82x25 note83x853 note84x668 note85x483 note86x298 note87x113 note88x941 note0x756 note1x571 note2x386 note3x201 note4x16 note5x844 note6x659 note7x474 note8x289 note9x104 note10x932 note11x747 note12x562 note13x377 note14x192 note15x7 note16x835 note17x650 note18x465 note19x280 note20x95 note21x923 note22x738 note23x553 note24x368 note25x183 note26x1011 note27x826 note28x641 note29x456 note30x271 note31x86 note32x914 note33x729 note34x544 note35x359 note36x174 note37x1002 note38x817 note39x632 note40x447 note41x262 note42x77 note43x905 note44x720 note45x535 note46x350 note47x165 note48x993 note49x808 note50x623 note51x438 note52x253 note53x68 note54x896 note55x711 note56x526 note57x341 note58x156 note59x984 note60x799 note61x614 note62x429 note63x244 note64x59 note65x887 note66x702 note67x517 note68x332 note69x147 note70x975 note71x790 note72x605 note73x420 note74x235 note75x50 note76x878 note77x693 note78x508 note79x323 note80x138 note81x966 note82x781 note83x596 note84x411 note85x226 note86x41 note87x869 note88x684 note0x499 note1x314 note2x129 note3x957 note4x772 note5x587 note6x402 note7x217 note8x32 note9x860 note10x675 note11x490 note12x305 note13x120 note14x948 note15x763 note16x578 note17x393 note18x208 note19x23 note20x851 note21x666 note22x481 note23x296 note24x111 note25x939 note26x754 note27x569 note28x384 note29x199 note30x14 note31x842 note32x657 note33x472 note34x287 note35x102 note36x930 note37x745 note38x560 note39x375 note40x190 note41x5 note42x833 note43x648 note44x463 note45x278 note46x93 note47x921 note48x736 note49x551 note50x366 note51x181 note52x1009 note53x824 note54x639 note55x454 note56x269 note57x84 note58x912 note59x727 note60x542 note61x357 note62x172 note63x1000 note64x815 note65x630 note66x445 note67x260 note68x75 note69x903 note70x718 note71x533 note72x348 note73x163 note74x991 note75x806 note76x621 note77x436 note78x251 note79x66 note80x894 note81x709 note82x524 note83x339 note84x154 note85x982 note86x797 note87x612 note88x427 note0x242 note1x57 note2x885 note3x700 note4x515 note5x330 note6x145 note7x973 note8x788 note9x603 note10x418 note11x233 note12x48 note13x876 note14x691 note15x506 note16x321 note17x136 note18x964 note19x779 note20x594 note21x409 note22x224 note23x39 note24x867 note25x682 note26x497 note27x312 note28x127 note29x955 note30x770 note31x585 note32x400 note33x215 note34x30 note35x858 note36x673 note37x488 note38x303 note39x118 note40x946 note41x761 note42x576 note43x391 note44x206 note45x21 note46x849 note47x664 note48x479 note49x294 note50x109 note51x937 note52x752 note53x567 note54x382 note55x197 note56x12 note57x840 note58x655 note59x470 note60x285 note61x100 note62x928 note63x743 note64x558 note65x373 note66x188 note67x3 note68x831 note69x646 note70x461 note71x276 note72x91 note73x919 note74x734 note75x549 note76x364 note77x179 note78x1007 note79x822 note80x637 note81x452 note82x267 note83x82 note84x910 note85x725 note86x540 note87x355 note88x170 note0x998 note1x813 note2x628 note3x443 note4x258 note5x73 note6x901 note7x716 note8x531 note9x346 note10x161 note11x989 note12x804 note13x619 note14x434 note15x249 note16x64 note17x892 note18x707 note19x522 note20x337 note21x152 note22x980 note23x795 note24x610 note25x425 note26x240 note27x55 note28x883 note29x698 note30x513 note31x328 note32x143 note33x971 note34x786 note35x601 note36x416 note37x231 note38x46 note39x874 note40x689 note41x504 note42x319 note43x134 note44x962 note45x777 note46x592 note47x407 note48x222 note49x37 note50x865 note51x680 note52x495 note53x310 note54x125 note55x953 note56x768 note57x583 note58x398 note59x213 note60x28 note61x856 note62x671 note63x486 note64x301 note65x116 note66x944 note67x759 note68x574 note69x389 note70x204 note71x19 note72x847 note73x662 note74x477 note75x292 note76x107 note77x935 note78x750 note79x565 note80x380 note81x195 note82x10 note83x838 note84x653 note85x468 note86x283 note87x98 note88x926 note0x741 note1x556 note2x371 note3x186 note4x1 note5x829 note6x644 note7x459 note8x274 note9x89 note10x917 note11x732 note12x547 note13x362 note14x177 note15x1005 note16x820 note17x635 note18x450 note19x265 note20x80 note21x908 note22x723 note23x538 note24x353 note25x168 note26x996 note27x811 note28x626 note29x441 note30x256 note31x71 note32x899 note33x714 note34x529 note35x344 note36x159 note37x987 note38x802 note39x617 note40x432 note41x247 note42x62 note43x890 note44x705 note45x520 note46x335 note47x150 note48x978 note49x793 note50x608 note51x423 note52x238 note53x53 note54x881 note55x696 note56x511 note57x326 note58x141 note59x969 note60x784 note61x599 note62x414 note63x229 note64x44 note65x872 note66x687 note67x502 note68x317 note69x132 note70x960 note71x775 note72x590 note73x405 note74x220 note75x35 note76x863 note77x678 note78x493 note79x308 note80x123 note81x951 note82x766 note83x581 note84x396 note85x211 note86x26 note87x854 note88x669 note0x484 note1x299 note2x114 note3x942 note4x757 note5x572 note6x387 note7x202 note8x17 note9x845 note10x660 note11x475 note12x290 note13x105 note14x933 note15x748 note16x563 note17x378 note18x193 note19x8 note20x836 note21x651 note22x466 note23x281 note24x96 note25x924 note26x739 note27x554 note28x369 note29x184 note30x1012 note31x827 note32x642 note33x457 note34x272 note35x87 note36x915 note37x730 note38x545 note39x360 note40x175 note41x1003 note42x818 note43x633 note44x448 note45x263 note46x78 note47x906 note48x721 note49x536 note50x351 note51x166 note52x994 note53x809 note54x624 note55x439 note56x254 note57x69 note58x897 note59x712 note60x527 note61x342 note62x157 note63x985 note64x800 note65x615 note66x430 note67x245 note68x60 note69x888 note70x703 note71x518 note72x333 note73x148 note74x976 note75x791 note76x606 note77x421 note78x236 note79x51 note80x879 note81x694 note82x509 note83x324 note84x139 note85x967 note86x782 note87x597 note88x412 note0x227 note1x42 note2x870 note3x685 note4x500 note5x315 note6x130 note7x958 note8x773 note9x588 note10x403 note11x218 note12x33 note13x861 note14x676 note15x491 note16x306 note17x121 note18x949 note19x764 note20x579 note21x394 note22x209 note23x24 note24x852 note25x667 note26x482 note27x297 note28x112 note29x940 note30x755 note31x570 note32x385 note33x200 note34x15 note35x843 note36x658 note37x473 note38x288 note39x103 note40x931 note41x746 note42x561 note43x376 note44x191 note45x6 note46x834 note47x649 note48x464 note49x279 note50x94 note51x922 note52x737 note53x552 note54x367 note55x182 note56x1010 note57x825 note58x640 note59x455 note60x270 note61x85 note62x913 note63x728 note64x543 note65x358 note66x173 note67x1001 note68x816 note69x631 note70x446 note71x261 note72x76 note73x904 note74x719 note75x534 note76x349 note77x164 note78x992 note79x807 note80x622 note81x437 note82x252 note83x67 note84x895 note85x710 note86x525 note87x340 note88x155 note0x983 note1x798 note2x613 note3x428 note4x243 note5x58 note6x886 note7x701 note8x516 note9x331 note10x146 note11x974 note12x789 note13x604 note14x419 note15x234 note16x49 note17x877 note18x692 note19x507 note20x322 note21x137 note22x965 note23x780 note24x595 note25x410 note26x225 note27x40 note28x868 note29x683 note30x498 note31x313 note32x128 note33x956 note34x771 note35x586 note36x401 note37x216 note38x31 note39x859 note40x674 note41x489 note42x304 note43x119 note44x947 note45x762 note46x577 note47x392 note48x207 note49x22 note50x850 note51x665 note52x480 note53x295 note54x110 note55x938 note56x753 note57x568 note58x383 note59x198 note60x13 note61x841 note62x656 note63x471 note64x286 note65x101 note66x929 note67x744 note68x559 note69x374 note70x189 note71x4 note72x832 note73x647 note74x462 note75x277 note76x92 note77x920 note78x735 note79x550 note80x365 note81x180 note82x1008 note83x823 note84x638 note85x453 note86x268 note87x83 note88x911 note0x726 note1x541 note2x356 note3x171 note4x999 note5x814 note6x629 note7x444 note8x259 note9x74 note10x902 note11x717 note12x532 note13x347 note14x162 note15x990 note16x805 note17x620 note18x435 note19x250 note20x65 note21x893 note22x708 note23x523 note24x338 note25x153 note26x981 note27x796 note28x611 note29x426 note30x241 note31x56 note32x884 note33x699 note34x514 note35x329 note36x144 note37x972 note38x787 note39x602 note40x417 note41x232 note42x47 note43x875 note44x690 note45x505 note46x320 note47x135 note48x963 note49x778 note50x593 note51x408 note52x223 note53x38 note54x866 note55x681 note56x496 note57x311 note58x126 note59x954 note60x769 note61x584 note62x399 note63x214 note64x29 note65x857 note66x672 note67x487 note68x302 note69x117 note70x945 note71x760 note72x575 note73x390 note74x205 note75x20 note76x848 note77x663 note78x478 note79x293 note80x108 note81x936 note82x751 note83x566 note84x381 note85x196 note86x11 note87x839 note88x654 note0x469 note1x284 note2x99 note3x927 note4x742 note5x557 note6x372 note7x187 note8x2 note9x830 note10x645 note11x460 note12x275 note13x90 note14x918 note15x733 note16x548 note17x363 note18x178 note19x1006 note20x821 note21x636 note22x451 note23x266 note24x81 note25x909 note26x724 note27x539 note28x354 note29x169 note30x997 note31x812 note32x627 note33x442 note34x257 note35x72 note36x900 note37x715 note38x530 note39x345 note40x160 note41x988 note42x803 note43x618 note44x433 note45x248 note46x63 note47x891 note48x706 note49x521 note50x336 note51x151 note52x979 note53x794 note54x609 note55x424 note56x239 note57x54 note58x882 note59x697 note60x512 note61x327 note62x142 note63x970 note64x785 note65x600 note66x415 note67x230 note68x45 note69x873 note70x688 note71x503 note72x318 note73x133 note74x961 note75x776 note76x591 note77x406 note78x221 note79x36 note80x864 note81x679 note82x494 note83x309 note84x124 note85x952 note86x767 note87x582 note88x397 note0x212 note1x27 note2x855 note3x670 note4x485 note5x300 note6x115 note7x943 note8x758 note9x573 note10x388 note11x203 note12x18 note13x846 note14x661 note15x476 note16x291 note17x106 note18x934 note19x749 note20x564 note21x379 note22x194 note23x9 note24x837 note25x652 note26x467 note27x282 note28x97 note29x925 note30x740 note31x555 note32x370 note33x185 note34x0 note35x828 note36x643 note37x458 note38x273 note39x88 note40x916 note41x731 note42x546 note43x361 note44x176 note45x1004 note46x819 note47x634 note48x449 note49x264 note50x79 note51x907 note52x722 note53x537 note54x352 note55x167 note56x995 note57x810 note58x625 note59x440 note60x255 note61x70 note62x898 note63x713 note64x528 note65x343 note66x158 note67x986 note68x801 note69x616 note70x431 note71x246 note72x61 note73x889 note74x704 note75x519 note76x334 note77x149 note78x977 note79x792 note80x607 note81x422 note82x237 note83x52 note84x880 note85x695 note86x510 note87x325 note88x140 note0x968 note1x783 note2x598 note3x413 note4x228 note5x43 note6x871 note7x686 note8x501 note9x316 note10x131 note11x959 note12x774 note13x589 note14x404 note15x219 note16x34 note17x862 note18x677 note19x492 note20x307 note21x122 note22x950 note23x765 note24x580 note25x395 note26x210 note27x25 note28x853 note29x668 note30x483 note31x298 note32x113 note33x941 note34x756 note35x571 note36x386 note37x201 note38x16 note39x844 note40x659 note41x474 note42x289 note43x104 note44x932 note45x747 note46x562 note47x377 note48x192 note49x7 note50x835 note51x650 note52x465 note53x280 note54x95 note55x923 note56x738 note57x553 note58x368 note59x183 note60x1011 note61x826 note62x641 note63x456 note64x271 note65x86 note66x914 note67x729 note68x544 note69x359 note70x174 note71x1002 note72x817 note73x632 note74x447 note75x262 note76x77 note77x905 note78x720 note79x535 note80x350 note81x165 note82x993 note83x808 note84x623 note85x438 note86x253 note87x68 note88x896 note0x711 note1x526 note2x341 note3x156 note4x984 note5x799 note6x614 note7x429 note8x244 note9x59 note10x887 note11x702 note12x517 note13x332 note14x147 note15x975 note16x790 note17x605 note18x420 note19x235 note20x50 note21x878 note22x693 note23x508 note24x323 note25x138 note26x966 note27x781 note28x596 note29x411 note30x226 note31x41 note32x869 note33x684 note34x499 note35x314 note36x129 note37x957 note38x772 note39x587 note40x402 note41x217 note42x32 note43x860 note44x675 note45x490 note46x305 note47x120 note48x948 note49x763 note50x578 note51x393 note52x208 note53x23 note54x851 note55x666 note56x481 note57x296 note58x111 note59x939 note60x754 note61x569 note62x384 note63x199 note64x14 note65x842 note66x657 note67x472 note68x287 note69x102 note70x930 note71x745 note72x560 note73x375 note74x190 note75x5 note76x833 note77x648 note78x463 note79x278 note80x93 note81x921 note82x736 note83x551 note84x366 note85x181 note86x1009 note87x824 note88x639 note0x454 note1x269 note2x84 note3x912 note4x727 note5x542 note6x357 note7x172 note8x1000 note9x815 note10x630 note11x445 note12x260 note13x75 note14x903 note15x718 note16x533 note17x348 note18x163 note19x991 note20x806 note21x621 note22x436 note23x251 note24x66 note25x894 note26x709 note27x524 note28x339 note29x154 note30x982 note31x797 note32x612 note33x427 note34x242 note35x57 note36x885 note37x700 note38x515 note39x330 note40x145 note41x973 note42x788 note43x603 note44x418 note45x233 note46x48 note47x876 note48x691 note49x506 note50x321 note51x136 note52x964 note53x779 note54x594 note55x409 note56x224 note57x39 note58x867 note59x682 note60x497 note61x312 note62x127 note63x955 note64x770 note65x585 note66x400 note67x215 note68x30 note69x858 note70x673 note71x488 note72x303 note73x118 note74x946 note75x761 note76x576 note77x391 note78x206 note79x21 note80x849 note81x664 note82x479 note83x294 note84x109 note85x937 note86x752 note87x567 note88x382 note0x197 note1x12 note2x840 note3x655 note4x470 note5x285 note6x100 note7x928 note8x743 note9x558 note10x373 note11x188 note12x3 note13x831 note14x646 note15x461 note16x276 note17x91 note18x919 note19x734 note20x549 note21x364 note22x179 note23x1007 note24x822 note25x637 note26x452 note27x267 note28x82 note29x910 note30x725 note31x540 note32x355 note33x170 note34x998 note35x813 note36x628 note37x443 note38x258 note39x73 note40x901 note41x716 note42x531 note43x346 note44x161 note45x989 note46x804 note47x619 note48x434 note49x249 note50x64 note51x892 note52x707 note53x522 note54x337 note55x152 note56x980 note57x795 note58x610 note59x425 note60x240 note61x55 note62x883 note63x698 note64x513 note65x328 note66x143 note67x971 note68x786 note69x601 note70x416 note71x231 note72x46 note73x874 note74x689 note75x504 note76x319 note77x134 note78x962 note79x777 note80x592 note81x407 note82x222 note83x37 note84x865 note85x680 note86x495 note87x310 note88x125 note0x953 note1x768 note2x583 note3x398 note4x213 note5x28 note6x856 note7x671 note8x486 note9x301 note10x116 note11x944 note12x759 note13x574 note14x389 note15x204 note16x19 note17x847 note18x662 note19x477 note20x292 note21x107 note22x935 note23x750 note24x565 note25x380 note26x195 note27x10 note28x838 note29x653 note30x468 note31x283 note32x98 note33x926 note34x741 note35x556 note36x371 note37x186 note38x1 note39x829 note40x644 note41x459 note42x274 note43x89 note44x917 note45x732 note46x547 note47x362 note48x177 note49x1005 note50x820 note51x635 note52x450 note53x265 note54x80 note55x908 note56x723 note57x538 note58x353 note59x168 note60x996 note61x811 note62x626 note63x441 note64x256 note65x71 note66x899 note67x714 note68x529 note69x344 note70x159 note71x987 note72x802 note73x617 note74x432 note75x247"}, {"role": "user", "content": "What is the first note?"}, {"role": "assistant", "content": "The first note is **note0x0**."}, {"role": "user", "content": "And the second one?"}, {"role": "assistant", "content": "The second note is **note1x828**."}, {"role": "user", "content": "Is note7x7 listed?"}], "max_tokens": 48, "temperature": 0.0, "draft": false, "chat_template_kwargs": {"enable_thinking": false}}, "status": 200, "response": {"id": "chatcmpl-02ff6e3728ae2e1812338a55881e2a77", "object": "chat.completion", "created": 1793474504, "model": "flashnext", "choices": [{"index": 0, "message": {"role": "assistant", "content": "No, **note7x7** is not listed in the provided reference notes.\n\nThe notes follow a pattern where the second part (after the 'x') is a hexadecimal number (e.g., `note1x828"}, "finish_reason": "length"}], "usage": {"prompt_tokens": 10281, "completion_tokens": 48, "total_tokens": 10329, "prompt_tokens_details": {"cached_tokens": 10240}, "completion_tokens_details": {"reasoning_tokens": 0}}, "exact_mode": "exact", "tensorfold": {"enable_thinking": false, "reasoning_effort": "none", "engine": "lanes", "tokens_per_second": 36.151047951500715, "seconds": 1.300100624, "prefill_seconds": 0.251938754, "prefill_widths": [], "prefill_raised": [], "time_to_first_token": 0.253230472, "sampling": "greedy", "drafts": false, "token_sha": "55e1d46d0689", "token_sha256": "55e1d46d06891dff37e5a39f83ae22514ba7952a98a301c70166bbb637c3f3b6", "min_rows": 1}, "speculative": {"rounds": 47, "drafted": 0, "accepted": 0, "acceptance_rate": 0.0, "tokens_per_round": 1.0212765957446808}}, "seconds": 1.5544788837432861} +{"url": "http://127.0.0.1:30461/v1/chat/completions", "request": {"model": "flashnext", "messages": [{"role": "system", "content": "You are a careful assistant. Reference notes: note0x0 note1x828 note2x643 note3x458 note4x273 note5x88 note6x916 note7x731 note8x546 note9x361 note10x176 note11x1004 note12x819 note13x634 note14x449 note15x264 note16x79 note17x907 note18x722 note19x537 note20x352 note21x167 note22x995 note23x810 note24x625 note25x440 note26x255 note27x70 note28x898 note29x713 note30x528 note31x343 note32x158 note33x986 note34x801 note35x616 note36x431 note37x246 note38x61 note39x889 note40x704 note41x519 note42x334 note43x149 note44x977 note45x792 note46x607 note47x422 note48x237 note49x52 note50x880 note51x695 note52x510 note53x325 note54x140 note55x968 note56x783 note57x598 note58x413 note59x228 note60x43 note61x871 note62x686 note63x501 note64x316 note65x131 note66x959 note67x774 note68x589 note69x404 note70x219 note71x34 note72x862 note73x677 note74x492 note75x307 note76x122 note77x950 note78x765 note79x580 note80x395 note81x210 note82x25 note83x853 note84x668 note85x483 note86x298 note87x113 note88x941 note0x756 note1x571 note2x386 note3x201 note4x16 note5x844 note6x659 note7x474 note8x289 note9x104 note10x932 note11x747 note12x562 note13x377 note14x192 note15x7 note16x835 note17x650 note18x465 note19x280 note20x95 note21x923 note22x738 note23x553 note24x368 note25x183 note26x1011 note27x826 note28x641 note29x456 note30x271 note31x86 note32x914 note33x729 note34x544 note35x359 note36x174 note37x1002 note38x817 note39x632 note40x447 note41x262 note42x77 note43x905 note44x720 note45x535 note46x350 note47x165 note48x993 note49x808 note50x623 note51x438 note52x253 note53x68 note54x896 note55x711 note56x526 note57x341 note58x156 note59x984 note60x799 note61x614 note62x429 note63x244 note64x59 note65x887 note66x702 note67x517 note68x332 note69x147 note70x975 note71x790 note72x605 note73x420 note74x235 note75x50 note76x878 note77x693 note78x508 note79x323 note80x138 note81x966 note82x781 note83x596 note84x411 note85x226 note86x41 note87x869 note88x684 note0x499 note1x314 note2x129 note3x957 note4x772 note5x587 note6x402 note7x217 note8x32 note9x860 note10x675 note11x490 note12x305 note13x120 note14x948 note15x763 note16x578 note17x393 note18x208 note19x23 note20x851 note21x666 note22x481 note23x296 note24x111 note25x939 note26x754 note27x569 note28x384 note29x199 note30x14 note31x842 note32x657 note33x472 note34x287 note35x102 note36x930 note37x745 note38x560 note39x375 note40x190 note41x5 note42x833 note43x648 note44x463 note45x278 note46x93 note47x921 note48x736 note49x551 note50x366 note51x181 note52x1009 note53x824 note54x639 note55x454 note56x269 note57x84 note58x912 note59x727 note60x542 note61x357 note62x172 note63x1000 note64x815 note65x630 note66x445 note67x260 note68x75 note69x903 note70x718 note71x533 note72x348 note73x163 note74x991 note75x806 note76x621 note77x436 note78x251 note79x66 note80x894 note81x709 note82x524 note83x339 note84x154 note85x982 note86x797 note87x612 note88x427 note0x242 note1x57 note2x885 note3x700 note4x515 note5x330 note6x145 note7x973 note8x788 note9x603 note10x418 note11x233 note12x48 note13x876 note14x691 note15x506 note16x321 note17x136 note18x964 note19x779 note20x594 note21x409 note22x224 note23x39 note24x867 note25x682 note26x497 note27x312 note28x127 note29x955 note30x770 note31x585 note32x400 note33x215 note34x30 note35x858 note36x673 note37x488 note38x303 note39x118 note40x946 note41x761 note42x576 note43x391 note44x206 note45x21 note46x849 note47x664 note48x479 note49x294 note50x109 note51x937 note52x752 note53x567 note54x382 note55x197 note56x12 note57x840 note58x655 note59x470 note60x285 note61x100 note62x928 note63x743 note64x558 note65x373 note66x188 note67x3 note68x831 note69x646 note70x461 note71x276 note72x91 note73x919 note74x734 note75x549 note76x364 note77x179 note78x1007 note79x822 note80x637 note81x452 note82x267 note83x82 note84x910 note85x725 note86x540 note87x355 note88x170 note0x998 note1x813 note2x628 note3x443 note4x258 note5x73 note6x901 note7x716 note8x531 note9x346 note10x161 note11x989 note12x804 note13x619 note14x434 note15x249 note16x64 note17x892 note18x707 note19x522 note20x337 note21x152 note22x980 note23x795 note24x610 note25x425 note26x240 note27x55 note28x883 note29x698 note30x513 note31x328 note32x143 note33x971 note34x786 note35x601 note36x416 note37x231 note38x46 note39x874 note40x689 note41x504 note42x319 note43x134 note44x962 note45x777 note46x592 note47x407 note48x222 note49x37 note50x865 note51x680 note52x495 note53x310 note54x125 note55x953 note56x768 note57x583 note58x398 note59x213 note60x28 note61x856 note62x671 note63x486 note64x301 note65x116 note66x944 note67x759 note68x574 note69x389 note70x204 note71x19 note72x847 note73x662 note74x477 note75x292 note76x107 note77x935 note78x750 note79x565 note80x380 note81x195 note82x10 note83x838 note84x653 note85x468 note86x283 note87x98 note88x926 note0x741 note1x556 note2x371 note3x186 note4x1 note5x829 note6x644 note7x459 note8x274 note9x89 note10x917 note11x732 note12x547 note13x362 note14x177 note15x1005 note16x820 note17x635 note18x450 note19x265 note20x80 note21x908 note22x723 note23x538 note24x353 note25x168 note26x996 note27x811 note28x626 note29x441 note30x256 note31x71 note32x899 note33x714 note34x529 note35x344 note36x159 note37x987 note38x802 note39x617 note40x432 note41x247 note42x62 note43x890 note44x705 note45x520 note46x335 note47x150 note48x978 note49x793 note50x608 note51x423 note52x238 note53x53 note54x881 note55x696 note56x511 note57x326 note58x141 note59x969 note60x784 note61x599 note62x414 note63x229 note64x44 note65x872 note66x687 note67x502 note68x317 note69x132 note70x960 note71x775 note72x590 note73x405 note74x220 note75x35 note76x863 note77x678 note78x493 note79x308 note80x123 note81x951 note82x766 note83x581 note84x396 note85x211 note86x26 note87x854 note88x669 note0x484 note1x299 note2x114 note3x942 note4x757 note5x572 note6x387 note7x202 note8x17 note9x845 note10x660 note11x475 note12x290 note13x105 note14x933 note15x748 note16x563 note17x378 note18x193 note19x8 note20x836 note21x651 note22x466 note23x281 note24x96 note25x924 note26x739 note27x554 note28x369 note29x184 note30x1012 note31x827 note32x642 note33x457 note34x272 note35x87 note36x915 note37x730 note38x545 note39x360 note40x175 note41x1003 note42x818 note43x633 note44x448 note45x263 note46x78 note47x906 note48x721 note49x536 note50x351 note51x166 note52x994 note53x809 note54x624 note55x439 note56x254 note57x69 note58x897 note59x712 note60x527 note61x342 note62x157 note63x985 note64x800 note65x615 note66x430 note67x245 note68x60 note69x888 note70x703 note71x518 note72x333 note73x148 note74x976 note75x791 note76x606 note77x421 note78x236 note79x51 note80x879 note81x694 note82x509 note83x324 note84x139 note85x967 note86x782 note87x597 note88x412 note0x227 note1x42 note2x870 note3x685 note4x500 note5x315 note6x130 note7x958 note8x773 note9x588 note10x403 note11x218 note12x33 note13x861 note14x676 note15x491 note16x306 note17x121 note18x949 note19x764 note20x579 note21x394 note22x209 note23x24 note24x852 note25x667 note26x482 note27x297 note28x112 note29x940 note30x755 note31x570 note32x385 note33x200 note34x15 note35x843 note36x658 note37x473 note38x288 note39x103 note40x931 note41x746 note42x561 note43x376 note44x191 note45x6 note46x834 note47x649 note48x464 note49x279 note50x94 note51x922 note52x737 note53x552 note54x367 note55x182 note56x1010 note57x825 note58x640 note59x455 note60x270 note61x85 note62x913 note63x728 note64x543 note65x358 note66x173 note67x1001 note68x816 note69x631 note70x446 note71x261 note72x76 note73x904 note74x719 note75x534 note76x349 note77x164 note78x992 note79x807 note80x622 note81x437 note82x252 note83x67 note84x895 note85x710 note86x525 note87x340 note88x155 note0x983 note1x798 note2x613 note3x428 note4x243 note5x58 note6x886 note7x701 note8x516 note9x331 note10x146 note11x974 note12x789 note13x604 note14x419 note15x234 note16x49 note17x877 note18x692 note19x507 note20x322 note21x137 note22x965 note23x780 note24x595 note25x410 note26x225 note27x40 note28x868 note29x683 note30x498 note31x313 note32x128 note33x956 note34x771 note35x586 note36x401 note37x216 note38x31 note39x859 note40x674 note41x489 note42x304 note43x119 note44x947 note45x762 note46x577 note47x392 note48x207 note49x22 note50x850 note51x665 note52x480 note53x295 note54x110 note55x938 note56x753 note57x568 note58x383 note59x198 note60x13 note61x841 note62x656 note63x471 note64x286 note65x101 note66x929 note67x744 note68x559 note69x374 note70x189 note71x4 note72x832 note73x647 note74x462 note75x277 note76x92 note77x920 note78x735 note79x550 note80x365 note81x180 note82x1008 note83x823 note84x638 note85x453 note86x268 note87x83 note88x911 note0x726 note1x541 note2x356 note3x171 note4x999 note5x814 note6x629 note7x444 note8x259 note9x74 note10x902 note11x717 note12x532 note13x347 note14x162 note15x990 note16x805 note17x620 note18x435 note19x250 note20x65 note21x893 note22x708 note23x523 note24x338 note25x153 note26x981 note27x796 note28x611 note29x426 note30x241 note31x56 note32x884 note33x699 note34x514 note35x329 note36x144 note37x972 note38x787 note39x602 note40x417 note41x232 note42x47 note43x875 note44x690 note45x505 note46x320 note47x135 note48x963 note49x778 note50x593 note51x408 note52x223 note53x38 note54x866 note55x681 note56x496 note57x311 note58x126 note59x954 note60x769 note61x584 note62x399 note63x214 note64x29 note65x857 note66x672 note67x487 note68x302 note69x117 note70x945 note71x760 note72x575 note73x390 note74x205 note75x20 note76x848 note77x663 note78x478 note79x293 note80x108 note81x936 note82x751 note83x566 note84x381 note85x196 note86x11 note87x839 note88x654 note0x469 note1x284 note2x99 note3x927 note4x742 note5x557 note6x372 note7x187 note8x2 note9x830 note10x645 note11x460 note12x275 note13x90 note14x918 note15x733 note16x548 note17x363 note18x178 note19x1006 note20x821 note21x636 note22x451 note23x266 note24x81 note25x909 note26x724 note27x539 note28x354 note29x169 note30x997 note31x812 note32x627 note33x442 note34x257 note35x72 note36x900 note37x715 note38x530 note39x345 note40x160 note41x988 note42x803 note43x618 note44x433 note45x248 note46x63 note47x891 note48x706 note49x521 note50x336 note51x151 note52x979 note53x794 note54x609 note55x424 note56x239 note57x54 note58x882 note59x697 note60x512 note61x327 note62x142 note63x970 note64x785 note65x600 note66x415 note67x230 note68x45 note69x873 note70x688 note71x503 note72x318 note73x133 note74x961 note75x776 note76x591 note77x406 note78x221 note79x36 note80x864 note81x679 note82x494 note83x309 note84x124 note85x952 note86x767 note87x582 note88x397 note0x212 note1x27 note2x855 note3x670 note4x485 note5x300 note6x115 note7x943 note8x758 note9x573 note10x388 note11x203 note12x18 note13x846 note14x661 note15x476 note16x291 note17x106 note18x934 note19x749 note20x564 note21x379 note22x194 note23x9 note24x837 note25x652 note26x467 note27x282 note28x97 note29x925 note30x740 note31x555 note32x370 note33x185 note34x0 note35x828 note36x643 note37x458 note38x273 note39x88 note40x916 note41x731 note42x546 note43x361 note44x176 note45x1004 note46x819 note47x634 note48x449 note49x264 note50x79 note51x907 note52x722 note53x537 note54x352 note55x167 note56x995 note57x810 note58x625 note59x440 note60x255 note61x70 note62x898 note63x713 note64x528 note65x343 note66x158 note67x986 note68x801 note69x616 note70x431 note71x246 note72x61 note73x889 note74x704 note75x519 note76x334 note77x149 note78x977 note79x792 note80x607 note81x422 note82x237 note83x52 note84x880 note85x695 note86x510 note87x325 note88x140 note0x968 note1x783 note2x598 note3x413 note4x228 note5x43 note6x871 note7x686 note8x501 note9x316 note10x131 note11x959 note12x774 note13x589 note14x404 note15x219 note16x34 note17x862 note18x677 note19x492 note20x307 note21x122 note22x950 note23x765 note24x580 note25x395 note26x210 note27x25 note28x853 note29x668 note30x483 note31x298 note32x113 note33x941 note34x756 note35x571 note36x386 note37x201 note38x16 note39x844 note40x659 note41x474 note42x289 note43x104 note44x932 note45x747 note46x562 note47x377 note48x192 note49x7 note50x835 note51x650 note52x465 note53x280 note54x95 note55x923 note56x738 note57x553 note58x368 note59x183 note60x1011 note61x826 note62x641 note63x456 note64x271 note65x86 note66x914 note67x729 note68x544 note69x359 note70x174 note71x1002 note72x817 note73x632 note74x447 note75x262 note76x77 note77x905 note78x720 note79x535 note80x350 note81x165 note82x993 note83x808 note84x623 note85x438 note86x253 note87x68 note88x896 note0x711 note1x526 note2x341 note3x156 note4x984 note5x799 note6x614 note7x429 note8x244 note9x59 note10x887 note11x702 note12x517 note13x332 note14x147 note15x975 note16x790 note17x605 note18x420 note19x235 note20x50 note21x878 note22x693 note23x508 note24x323 note25x138 note26x966 note27x781 note28x596 note29x411 note30x226 note31x41 note32x869 note33x684 note34x499 note35x314 note36x129 note37x957 note38x772 note39x587 note40x402 note41x217 note42x32 note43x860 note44x675 note45x490 note46x305 note47x120 note48x948 note49x763 note50x578 note51x393 note52x208 note53x23 note54x851 note55x666 note56x481 note57x296 note58x111 note59x939 note60x754 note61x569 note62x384 note63x199 note64x14 note65x842 note66x657 note67x472 note68x287 note69x102 note70x930 note71x745 note72x560 note73x375 note74x190 note75x5 note76x833 note77x648 note78x463 note79x278 note80x93 note81x921 note82x736 note83x551 note84x366 note85x181 note86x1009 note87x824 note88x639 note0x454 note1x269 note2x84 note3x912 note4x727 note5x542 note6x357 note7x172 note8x1000 note9x815 note10x630 note11x445 note12x260 note13x75 note14x903 note15x718 note16x533 note17x348 note18x163 note19x991 note20x806 note21x621 note22x436 note23x251 note24x66 note25x894 note26x709 note27x524 note28x339 note29x154 note30x982 note31x797 note32x612 note33x427 note34x242 note35x57 note36x885 note37x700 note38x515 note39x330 note40x145 note41x973 note42x788 note43x603 note44x418 note45x233 note46x48 note47x876 note48x691 note49x506 note50x321 note51x136 note52x964 note53x779 note54x594 note55x409 note56x224 note57x39 note58x867 note59x682 note60x497 note61x312 note62x127 note63x955 note64x770 note65x585 note66x400 note67x215 note68x30 note69x858 note70x673 note71x488 note72x303 note73x118 note74x946 note75x761 note76x576 note77x391 note78x206 note79x21 note80x849 note81x664 note82x479 note83x294 note84x109 note85x937 note86x752 note87x567 note88x382 note0x197 note1x12 note2x840 note3x655 note4x470 note5x285 note6x100 note7x928 note8x743 note9x558 note10x373 note11x188 note12x3 note13x831 note14x646 note15x461 note16x276 note17x91 note18x919 note19x734 note20x549 note21x364 note22x179 note23x1007 note24x822 note25x637 note26x452 note27x267 note28x82 note29x910 note30x725 note31x540 note32x355 note33x170 note34x998 note35x813 note36x628 note37x443 note38x258 note39x73 note40x901 note41x716 note42x531 note43x346 note44x161 note45x989 note46x804 note47x619 note48x434 note49x249 note50x64 note51x892 note52x707 note53x522 note54x337 note55x152 note56x980 note57x795 note58x610 note59x425 note60x240 note61x55 note62x883 note63x698 note64x513 note65x328 note66x143 note67x971 note68x786 note69x601 note70x416 note71x231 note72x46 note73x874 note74x689 note75x504 note76x319 note77x134 note78x962 note79x777 note80x592 note81x407 note82x222 note83x37 note84x865 note85x680 note86x495 note87x310 note88x125 note0x953 note1x768 note2x583 note3x398 note4x213 note5x28 note6x856 note7x671 note8x486 note9x301 note10x116 note11x944 note12x759 note13x574 note14x389 note15x204 note16x19 note17x847 note18x662 note19x477 note20x292 note21x107 note22x935 note23x750 note24x565 note25x380 note26x195 note27x10 note28x838 note29x653 note30x468 note31x283 note32x98 note33x926 note34x741 note35x556 note36x371 note37x186 note38x1 note39x829 note40x644 note41x459 note42x274 note43x89 note44x917 note45x732 note46x547 note47x362 note48x177 note49x1005 note50x820 note51x635 note52x450 note53x265 note54x80 note55x908 note56x723 note57x538 note58x353 note59x168 note60x996 note61x811 note62x626 note63x441 note64x256 note65x71 note66x899 note67x714 note68x529 note69x344 note70x159 note71x987 note72x802 note73x617 note74x432 note75x247"}, {"role": "user", "content": "What is the first note?"}, {"role": "assistant", "content": "The first note is **note0x0**."}, {"role": "user", "content": "And the second one?"}, {"role": "assistant", "content": "The second note is **note1x828**."}, {"role": "user", "content": "Name the last note."}], "max_tokens": 48, "temperature": 0.0, "draft": false, "chat_template_kwargs": {"enable_thinking": false}}, "status": 200, "response": {"id": "chatcmpl-6d2581f620d44ea7b4290d6eaee192eb", "object": "chat.completion", "created": 1793474506, "model": "flashnext", "choices": [{"index": 0, "message": {"role": "assistant", "content": "The last note is **note75x247**."}, "finish_reason": "stop"}], "usage": {"prompt_tokens": 10279, "completion_tokens": 14, "total_tokens": 10293, "prompt_tokens_details": {"cached_tokens": 10240}, "completion_tokens_details": {"reasoning_tokens": 0}}, "exact_mode": "exact", "tensorfold": {"enable_thinking": false, "reasoning_effort": "none", "engine": "lanes", "tokens_per_second": 36.255511576814335, "seconds": 0.358566172, "prefill_seconds": 0.243356573, "prefill_widths": [], "prefill_raised": [], "time_to_first_token": 0.24461064, "sampling": "greedy", "drafts": false, "token_sha": "9537be85f86c", "token_sha256": "9537be85f86c467fa028c7e7cd58d5b693a814bcc9988a99dec273e8e81523c1", "min_rows": 1}, "speculative": {"rounds": 13, "drafted": 0, "accepted": 0, "acceptance_rate": 0.0, "tokens_per_round": 1.0769230769230769}}, "seconds": 0.6041960716247559} +{"url": "http://127.0.0.1:30461/v1/chat/completions", "request": {"model": "flashnext", "messages": [{"role": "system", "content": "You are a careful assistant. Reference notes: note0x0 note1x828 note2x643 note3x458 note4x273 note5x88 note6x916 note7x731 note8x546 note9x361 note10x176 note11x1004 note12x819 note13x634 note14x449 note15x264 note16x79 note17x907 note18x722 note19x537 note20x352 note21x167 note22x995 note23x810 note24x625 note25x440 note26x255 note27x70 note28x898 note29x713 note30x528 note31x343 note32x158 note33x986 note34x801 note35x616 note36x431 note37x246 note38x61 note39x889 note40x704 note41x519 note42x334 note43x149 note44x977 note45x792 note46x607 note47x422 note48x237 note49x52 note50x880 note51x695 note52x510 note53x325 note54x140 note55x968 note56x783 note57x598 note58x413 note59x228 note60x43 note61x871 note62x686 note63x501 note64x316 note65x131 note66x959 note67x774 note68x589 note69x404 note70x219 note71x34 note72x862 note73x677 note74x492 note75x307 note76x122 note77x950 note78x765 note79x580 note80x395 note81x210 note82x25 note83x853 note84x668 note85x483 note86x298 note87x113 note88x941 note0x756 note1x571 note2x386 note3x201 note4x16 note5x844 note6x659 note7x474 note8x289 note9x104 note10x932 note11x747 note12x562 note13x377 note14x192 note15x7 note16x835 note17x650 note18x465 note19x280 note20x95 note21x923 note22x738 note23x553 note24x368 note25x183 note26x1011 note27x826 note28x641 note29x456 note30x271 note31x86 note32x914 note33x729 note34x544 note35x359 note36x174 note37x1002 note38x817 note39x632 note40x447 note41x262 note42x77 note43x905 note44x720 note45x535 note46x350 note47x165 note48x993 note49x808 note50x623 note51x438 note52x253 note53x68 note54x896 note55x711 note56x526 note57x341 note58x156 note59x984 note60x799 note61x614 note62x429 note63x244 note64x59 note65x887 note66x702 note67x517 note68x332 note69x147 note70x975 note71x790 note72x605 note73x420 note74x235 note75x50 note76x878 note77x693 note78x508 note79x323 note80x138 note81x966 note82x781 note83x596 note84x411 note85x226 note86x41 note87x869 note88x684 note0x499 note1x314 note2x129 note3x957 note4x772 note5x587 note6x402 note7x217 note8x32 note9x860 note10x675 note11x490 note12x305 note13x120 note14x948 note15x763 note16x578 note17x393 note18x208 note19x23 note20x851 note21x666 note22x481 note23x296 note24x111 note25x939 note26x754 note27x569 note28x384 note29x199 note30x14 note31x842 note32x657 note33x472 note34x287 note35x102 note36x930 note37x745 note38x560 note39x375 note40x190 note41x5 note42x833 note43x648 note44x463 note45x278 note46x93 note47x921 note48x736 note49x551 note50x366 note51x181 note52x1009 note53x824 note54x639 note55x454 note56x269 note57x84 note58x912 note59x727 note60x542 note61x357 note62x172 note63x1000 note64x815 note65x630 note66x445 note67x260 note68x75 note69x903 note70x718 note71x533 note72x348 note73x163 note74x991 note75x806 note76x621 note77x436 note78x251 note79x66 note80x894 note81x709 note82x524 note83x339 note84x154 note85x982 note86x797 note87x612 note88x427 note0x242 note1x57 note2x885 note3x700 note4x515 note5x330 note6x145 note7x973 note8x788 note9x603 note10x418 note11x233 note12x48 note13x876 note14x691 note15x506 note16x321 note17x136 note18x964 note19x779 note20x594 note21x409 note22x224 note23x39 note24x867 note25x682 note26x497 note27x312 note28x127 note29x955 note30x770 note31x585 note32x400 note33x215 note34x30 note35x858 note36x673 note37x488 note38x303 note39x118 note40x946 note41x761 note42x576 note43x391 note44x206 note45x21 note46x849 note47x664 note48x479 note49x294 note50x109 note51x937 note52x752 note53x567 note54x382 note55x197 note56x12 note57x840 note58x655 note59x470 note60x285 note61x100 note62x928 note63x743 note64x558 note65x373 note66x188 note67x3 note68x831 note69x646 note70x461 note71x276 note72x91 note73x919 note74x734 note75x549 note76x364 note77x179 note78x1007 note79x822 note80x637 note81x452 note82x267 note83x82 note84x910 note85x725 note86x540 note87x355 note88x170 note0x998 note1x813 note2x628 note3x443 note4x258 note5x73 note6x901 note7x716 note8x531 note9x346 note10x161 note11x989 note12x804 note13x619 note14x434 note15x249 note16x64 note17x892 note18x707 note19x522 note20x337 note21x152 note22x980 note23x795 note24x610 note25x425 note26x240 note27x55 note28x883 note29x698 note30x513 note31x328 note32x143 note33x971 note34x786 note35x601 note36x416 note37x231 note38x46 note39x874 note40x689 note41x504 note42x319 note43x134 note44x962 note45x777 note46x592 note47x407 note48x222 note49x37 note50x865 note51x680 note52x495 note53x310 note54x125 note55x953 note56x768 note57x583 note58x398 note59x213 note60x28 note61x856 note62x671 note63x486 note64x301 note65x116 note66x944 note67x759 note68x574 note69x389 note70x204 note71x19 note72x847 note73x662 note74x477 note75x292 note76x107 note77x935 note78x750 note79x565 note80x380 note81x195 note82x10 note83x838 note84x653 note85x468 note86x283 note87x98 note88x926 note0x741 note1x556 note2x371 note3x186 note4x1 note5x829 note6x644 note7x459 note8x274 note9x89 note10x917 note11x732 note12x547 note13x362 note14x177 note15x1005 note16x820 note17x635 note18x450 note19x265 note20x80 note21x908 note22x723 note23x538 note24x353 note25x168 note26x996 note27x811 note28x626 note29x441 note30x256 note31x71 note32x899 note33x714 note34x529 note35x344 note36x159 note37x987 note38x802 note39x617 note40x432 note41x247 note42x62 note43x890 note44x705 note45x520 note46x335 note47x150 note48x978 note49x793 note50x608 note51x423 note52x238 note53x53 note54x881 note55x696 note56x511 note57x326 note58x141 note59x969 note60x784 note61x599 note62x414 note63x229 note64x44 note65x872 note66x687 note67x502 note68x317 note69x132 note70x960 note71x775 note72x590 note73x405 note74x220 note75x35 note76x863 note77x678 note78x493 note79x308 note80x123 note81x951 note82x766 note83x581 note84x396 note85x211 note86x26 note87x854 note88x669 note0x484 note1x299 note2x114 note3x942 note4x757 note5x572 note6x387 note7x202 note8x17 note9x845 note10x660 note11x475 note12x290 note13x105 note14x933 note15x748 note16x563 note17x378 note18x193 note19x8 note20x836 note21x651 note22x466 note23x281 note24x96 note25x924 note26x739 note27x554 note28x369 note29x184 note30x1012 note31x827 note32x642 note33x457 note34x272 note35x87 note36x915 note37x730 note38x545 note39x360 note40x175 note41x1003 note42x818 note43x633 note44x448 note45x263 note46x78 note47x906 note48x721 note49x536 note50x351 note51x166 note52x994 note53x809 note54x624 note55x439 note56x254 note57x69 note58x897 note59x712 note60x527 note61x342 note62x157 note63x985 note64x800 note65x615 note66x430 note67x245 note68x60 note69x888 note70x703 note71x518 note72x333 note73x148 note74x976 note75x791 note76x606 note77x421 note78x236 note79x51 note80x879 note81x694 note82x509 note83x324 note84x139 note85x967 note86x782 note87x597 note88x412 note0x227 note1x42 note2x870 note3x685 note4x500 note5x315 note6x130 note7x958 note8x773 note9x588 note10x403 note11x218 note12x33 note13x861 note14x676 note15x491 note16x306 note17x121 note18x949 note19x764 note20x579 note21x394 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note41x217 note42x32 note43x860 note44x675 note45x490 note46x305 note47x120 note48x948 note49x763 note50x578 note51x393 note52x208 note53x23 note54x851 note55x666 note56x481 note57x296 note58x111 note59x939 note60x754 note61x569 note62x384 note63x199 note64x14 note65x842 note66x657 note67x472 note68x287 note69x102 note70x930 note71x745 note72x560 note73x375 note74x190 note75x5 note76x833 note77x648 note78x463 note79x278 note80x93 note81x921 note82x736 note83x551 note84x366 note85x181 note86x1009 note87x824 note88x639 note0x454 note1x269 note2x84 note3x912 note4x727 note5x542 note6x357 note7x172 note8x1000 note9x815 note10x630 note11x445 note12x260 note13x75 note14x903 note15x718 note16x533 note17x348 note18x163 note19x991 note20x806 note21x621 note22x436 note23x251 note24x66 note25x894 note26x709 note27x524 note28x339 note29x154 note30x982 note31x797 note32x612 note33x427 note34x242 note35x57 note36x885 note37x700 note38x515 note39x330 note40x145 note41x973 note42x788 note43x603 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note50x820 note51x635 note52x450 note53x265 note54x80 note55x908 note56x723 note57x538 note58x353 note59x168 note60x996 note61x811 note62x626 note63x441 note64x256 note65x71 note66x899 note67x714 note68x529 note69x344 note70x159 note71x987 note72x802 note73x617 note74x432 note75x247"}, {"role": "user", "content": "What is the third note?"}], "max_tokens": 48, "temperature": 0.0, "draft": false, "chat_template_kwargs": {"enable_thinking": false}}, "status": 200, "response": {"id": "chatcmpl-22b57270a767818627693d733a05cce1", "object": "chat.completion", "created": 1793474507, "model": "flashnext", "choices": [{"index": 0, "message": {"role": "assistant", "content": "The third note is **note2x643**."}, "finish_reason": "stop"}], "usage": {"prompt_tokens": 10219, "completion_tokens": 13, "total_tokens": 10232, "prompt_tokens_details": {"cached_tokens": 10176}, "completion_tokens_details": {"reasoning_tokens": 0}}, "exact_mode": "exact", "tensorfold": {"enable_thinking": false, "reasoning_effort": "none", "engine": "lanes", "tokens_per_second": 36.10733729257508, "seconds": 0.332342424, "prefill_seconds": 0.267012416, "prefill_widths": [], "prefill_raised": [], "time_to_first_token": 0.268422184, "sampling": "greedy", "drafts": false, "token_sha": "86effbb58f5b", "token_sha256": "86effbb58f5b1a059c85bb7445693561cdba823838fe7776eaafd0a10e14cf56", "min_rows": 1}, "speculative": {"rounds": 12, "drafted": 0, "accepted": 0, "acceptance_rate": 0.0, "tokens_per_round": 1.0833333333333333}}, "seconds": 0.6016504764556885} +{"url": "http://127.0.0.1:30461/v1/chat/completions", "request": {"model": "flashnext", "messages": [{"role": "system", "content": "You are a careful assistant. 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note6x402 note7x217 note8x32 note9x860 note10x675 note11x490 note12x305 note13x120 note14x948 note15x763 note16x578 note17x393 note18x208 note19x23 note20x851 note21x666 note22x481 note23x296 note24x111 note25x939 note26x754 note27x569 note28x384 note29x199 note30x14 note31x842 note32x657 note33x472 note34x287 note35x102 note36x930 note37x745 note38x560 note39x375 note40x190 note41x5 note42x833 note43x648 note44x463 note45x278 note46x93 note47x921 note48x736 note49x551 note50x366 note51x181 note52x1009 note53x824 note54x639 note55x454 note56x269 note57x84 note58x912 note59x727 note60x542 note61x357 note62x172 note63x1000 note64x815 note65x630 note66x445 note67x260 note68x75 note69x903 note70x718 note71x533 note72x348 note73x163 note74x991 note75x806 note76x621 note77x436 note78x251 note79x66 note80x894 note81x709 note82x524 note83x339 note84x154 note85x982 note86x797 note87x612 note88x427 note0x242 note1x57 note2x885 note3x700 note4x515 note5x330 note6x145 note7x973 note8x788 note9x603 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"completion_tokens_details": {"reasoning_tokens": 0}}, "exact_mode": "exact", "tensorfold": {"enable_thinking": false, "reasoning_effort": "none", "engine": "lanes", "tokens_per_second": 36.14701812810009, "seconds": 0.331977591, "prefill_seconds": 0.088448355, "prefill_widths": [], "prefill_raised": [], "time_to_first_token": 0.089578911, "sampling": "greedy", "drafts": false, "token_sha": "7e4bf5aba972", "token_sha256": "7e4bf5aba9727191d8505e971356abb0485616846741651f36545f4775ef04fc", "min_rows": 1}, "speculative": {"rounds": 12, "drafted": 0, "accepted": 0, "acceptance_rate": 0.0, "tokens_per_round": 1.0833333333333333}}, "seconds": 0.4225313663482666} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/exactness/exact-serve-cancel.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/exactness/exact-serve-cancel.jsonl new file mode 100644 index 0000000000..aad6430f39 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/exactness/exact-serve-cancel.jsonl @@ -0,0 +1,9 @@ +{"url": "http://127.0.0.1:30461/v1/chat/completions", "request": {"model": "flashnext", "messages": [{"role": "user", "content": "Count from one to ten in words."}], "max_tokens": 32, "temperature": 0.0, "stream": false, "chat_template_kwargs": {"enable_thinking": false}}, "status": 200, "response": {"id": "chatcmpl-e5fae045346a1650165ad5e86d1102e3", "object": "chat.completion", "created": 1793474470, "model": "flashnext", "choices": [{"index": 0, "message": {"role": "assistant", "content": "Here are the numbers from one to ten in words:\n\n1. One\n2. Two\n3. Three\n4. Four\n5. Five\n"}, "finish_reason": "length"}], "usage": {"prompt_tokens": 20, "completion_tokens": 32, "total_tokens": 52, "prompt_tokens_details": {"cached_tokens": 0}, "completion_tokens_details": {"reasoning_tokens": 0}}, "exact_mode": "exact", "tensorfold": {"enable_thinking": false, "reasoning_effort": "none", "engine": "lanes", "tokens_per_second": 75.73902025288521, "seconds": 0.409300251, "prefill_seconds": 0.126150351, "prefill_widths": [], "prefill_raised": [], "time_to_first_token": 0.127235132, "sampling": "greedy", "drafts": true, "token_sha": "3f3630855924", "token_sha256": "3f3630855924a925f073d1526957b4aca9410805f10806d3a67f7f931e4ef406", "min_rows": 2}, "speculative": {"rounds": 7, "drafted": 32, "accepted": 24, "acceptance_rate": 0.75, "tokens_per_round": 4.571428571428571}}, "seconds": 0.5382308959960938} +{"url": "http://127.0.0.1:30461/v1/chat/completions", "request": {"model": "flashnext", "messages": [{"role": "user", "content": "Count from one to ten in words."}], "max_tokens": 32, "temperature": 0.0, "stream": false, "chat_template_kwargs": {"enable_thinking": false}}, "status": 200, "response": {"id": "chatcmpl-9fa1e6ef78294cc2240b24c0da964db6", "object": "chat.completion", "created": 1793474471, "model": "flashnext", "choices": [{"index": 0, "message": {"role": "assistant", "content": "Here are the numbers from one to ten in words:\n\n1. One\n2. Two\n3. Three\n4. Four\n5. Five\n"}, "finish_reason": "length"}], "usage": {"prompt_tokens": 20, "completion_tokens": 32, "total_tokens": 52, "prompt_tokens_details": {"cached_tokens": 0}, "completion_tokens_details": {"reasoning_tokens": 0}}, "exact_mode": "exact", "tensorfold": {"enable_thinking": false, "reasoning_effort": "none", "engine": "lanes", "tokens_per_second": 63.59106837105718, "seconds": 0.487489844, "prefill_seconds": 0.12381976, "prefill_widths": [], "prefill_raised": [], "time_to_first_token": 0.124245166, "sampling": "greedy", "drafts": true, "token_sha": "3f3630855924", "token_sha256": "3f3630855924a925f073d1526957b4aca9410805f10806d3a67f7f931e4ef406", "min_rows": 2}, "speculative": {"rounds": 7, "drafted": 32, "accepted": 24, "acceptance_rate": 0.75, "tokens_per_round": 4.571428571428571}}, "seconds": 0.6281914710998535} +{"url": "http://127.0.0.1:30461/v1/chat/completions", "request": {"model": "flashnext", "messages": [{"role": "user", "content": "Count from one to ten in words."}], "max_tokens": 32, "temperature": 0.0, "stream": false, "chat_template_kwargs": {"enable_thinking": false}}, "status": 200, "response": {"id": "chatcmpl-36e1e3dd7c40a7ef45843544aae03e0b", "object": "chat.completion", "created": 1793474471, "model": "flashnext", "choices": [{"index": 0, "message": {"role": "assistant", "content": "Here are the numbers from one to ten in words:\n\n1. One\n2. Two\n3. Three\n4. Four\n5. Five\n"}, "finish_reason": "length"}], "usage": {"prompt_tokens": 20, "completion_tokens": 32, "total_tokens": 52, "prompt_tokens_details": {"cached_tokens": 0}, "completion_tokens_details": {"reasoning_tokens": 0}}, "exact_mode": "exact", "tensorfold": {"enable_thinking": false, "reasoning_effort": "none", "engine": "lanes", "tokens_per_second": 75.81466501554391, "seconds": 0.408891868, "prefill_seconds": 0.123749188, "prefill_widths": [], "prefill_raised": [], "time_to_first_token": 0.124363909, "sampling": "greedy", "drafts": true, "token_sha": "3f3630855924", "token_sha256": "3f3630855924a925f073d1526957b4aca9410805f10806d3a67f7f931e4ef406", "min_rows": 2}, "speculative": {"rounds": 7, "drafted": 32, "accepted": 24, "acceptance_rate": 0.75, "tokens_per_round": 4.571428571428571}}, "seconds": 0.5494725704193115} +{"url": "http://127.0.0.1:30461/v1/chat/completions", "request": {"model": "flashnext", "messages": [{"role": "user", "content": "cancel0-1793474472407485424 item0x0 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1793474432, "model": "flashnext", "choices": [{"index": 0, "message": {"role": "assistant", "content": "2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37"}, "finish_reason": "stop"}], "usage": {"prompt_tokens": 23, "completion_tokens": 43, "total_tokens": 66, "prompt_tokens_details": {"cached_tokens": 0}, "completion_tokens_details": {"reasoning_tokens": 0}}, "exact_mode": "exact", "tensorfold": {"enable_thinking": false, "reasoning_effort": "none", "engine": "lanes", "tokens_per_second": 15.099629843755295, "seconds": 2.781525139, "prefill_seconds": 0.130969046, "prefill_widths": [], "prefill_raised": [], "time_to_first_token": 0.132004865, "sampling": "greedy", "drafts": false, "token_sha": "005a2bec0a1b", "token_sha256": "005a2bec0a1b958c27359d9f240f6a903fc0ce8789cb26affcf74052737c2320", "min_rows": 1}, "speculative": {"rounds": 42, "drafted": 0, "accepted": 0, "acceptance_rate": 0.0, "tokens_per_round": 1.0238095238095237}}, "seconds": 2.9146389961242676} +{"url": "http://127.0.0.1:30461/v1/chat/completions", "request": {"model": "flashnext", "messages": [{"role": "user", "content": "Explain in two sentences why the sky is blue."}], "max_tokens": 64, "temperature": 0.0, "seed": 7, "draft": false, "chat_template_kwargs": {"enable_thinking": false}}, "status": 200, "response": {"id": "chatcmpl-72053ca80032f6a3267a59e6d284a447", "object": "chat.completion", "created": 1793474432, "model": "flashnext", "choices": [{"index": 0, "message": {"role": "assistant", "content": "Sunlight enters Earth's atmosphere and scatters in all directions, with shorter blue wavelengths scattering more strongly than other colors due to Rayleigh scattering. This scattered blue light is what our eyes perceive when we look up at the sky."}, "finish_reason": "stop"}], "usage": {"prompt_tokens": 23, "completion_tokens": 47, "total_tokens": 70, "prompt_tokens_details": {"cached_tokens": 0}, "completion_tokens_details": {"reasoning_tokens": 0}}, "exact_mode": "exact", "tensorfold": {"enable_thinking": false, "reasoning_effort": "none", "engine": "lanes", "tokens_per_second": 16.89608824809849, "seconds": 2.722523659, "prefill_seconds": 0.254746954, "prefill_widths": [], "prefill_raised": [], "time_to_first_token": 0.386524262, "sampling": "greedy", "drafts": false, "token_sha": "c8e6705737f3", "token_sha256": "c8e6705737f351a3a09e1a5793ea7ce5677322b7ddd926a1d7057a14a3a05642", "min_rows": 1}, "speculative": {"rounds": 46, "drafted": 0, "accepted": 0, "acceptance_rate": 0.0, "tokens_per_round": 1.0217391304347827}}, "seconds": 3.1099965572357178} +{"url": "http://127.0.0.1:30461/v1/chat/completions", "request": {"model": "flashnext", "messages": 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value, with the labels cycling through `item0` to `item96` across eight distinct groups."}, "finish_reason": "stop"}], "usage": {"prompt_tokens": 3413, "completion_tokens": 60, "total_tokens": 3473, "prompt_tokens_details": {"cached_tokens": 3392}, "completion_tokens_details": {"reasoning_tokens": 0}}, "exact_mode": "exact", "tensorfold": {"enable_thinking": false, "reasoning_effort": "none", "engine": "lanes", "tokens_per_second": 18.268095084690568, "seconds": 3.229674453, "prefill_seconds": 0.156974876, "prefill_widths": [], "prefill_raised": [], "time_to_first_token": 0.17954779, "sampling": "greedy", "drafts": false, "token_sha": "7f4c8846ddc9", "token_sha256": "7f4c8846ddc9db07f73a77e777d19104dcc11230ef31ffcbdbd681e88dd204b5", "min_rows": 1}, "speculative": {"rounds": 59, "drafted": 0, "accepted": 0, "acceptance_rate": 0.0, "tokens_per_round": 1.0169491525423728}}, "seconds": 3.4105031490325928} +{"url": "http://127.0.0.1:30461/v1/chat/completions", "request": {"model": "flashnext", "messages": [{"role": "user", "content": "Write a short poem about the sea."}], "max_tokens": 64, "temperature": 0.0, "seed": 7, "draft": false, "chat_template_kwargs": {"enable_thinking": false}}, "status": 200, "response": {"id": "chatcmpl-4e1bf50ab1da0f3d0ee5a4d250198726", "object": "chat.completion", "created": 1793474432, "model": "flashnext", "choices": [{"index": 0, "message": {"role": "assistant", "content": "Beneath the moon\u2019s pale, silver gaze,\nThe ocean hums its ancient ways.\nA rhythm kept in salt and spray,\nThat washes sorrow far away.\n\nThe waves rise high, then break and fall,\nAnswering nature\u2019s tidal call.\nA mirror for the sky\u2019s deep"}, "finish_reason": "length"}], "usage": {"prompt_tokens": 20, "completion_tokens": 64, "total_tokens": 84, "prompt_tokens_details": {"cached_tokens": 0}, "completion_tokens_details": {"reasoning_tokens": 0}}, "exact_mode": "exact", "tensorfold": {"enable_thinking": false, "reasoning_effort": "none", 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{"role": "assistant", "content": "Salt and spray upon the breeze,\nWhispered secrets, ancient seas.\nBlue beneath the moon\u2019s pale eye,\nWhere the hidden currents lie.\n\nWaves that break on shores of stone,\nClaim the land, then leave it alone.\nIn your depth, the stars reflect,\nA mirror"}, "finish_reason": "length"}], "usage": {"prompt_tokens": 20, "completion_tokens": 64, "total_tokens": 84, "prompt_tokens_details": {"cached_tokens": 0}, "completion_tokens_details": {"reasoning_tokens": 0}}, "exact_mode": "exact", "tensorfold": {"enable_thinking": false, "reasoning_effort": "none", "engine": "lanes", "tokens_per_second": 37.79348900574237, "seconds": 1.666953797, "prefill_seconds": 0.12153987, "prefill_widths": [], "prefill_raised": [], "time_to_first_token": 0.122242714, "sampling": "exact", "drafts": false, "token_sha": "c0e21e789784", "token_sha256": "c0e21e789784d9ea2d45a012477c7c75a48bf3610e978a6961254670b0302613", "min_rows": 1}, "speculative": {"rounds": 63, "drafted": 0, "accepted": 0, "acceptance_rate": 0.0, "tokens_per_round": 1.0158730158730158}}, "seconds": 1.8922898769378662} +{"url": "http://127.0.0.1:30461/v1/chat/completions", "request": {"model": "flashnext", "messages": [{"role": "user", "content": "List the first twelve prime numbers, separated by commas."}], "max_tokens": 64, "temperature": 0.8, "seed": 7, "draft": false, "chat_template_kwargs": {"enable_thinking": false}}, "status": 200, "response": {"id": "chatcmpl-8e8549b441b8ac9eca79fb25448b60d3", "object": "chat.completion", "created": 1793474438, "model": "flashnext", "choices": [{"index": 0, "message": {"role": "assistant", "content": "2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37"}, "finish_reason": "stop"}], "usage": {"prompt_tokens": 23, "completion_tokens": 43, "total_tokens": 66, "prompt_tokens_details": {"cached_tokens": 0}, "completion_tokens_details": {"reasoning_tokens": 0}}, "exact_mode": "exact", "tensorfold": {"enable_thinking": false, "reasoning_effort": "none", "engine": "lanes", "tokens_per_second": 39.10976275879164, "seconds": 1.073900659, "prefill_seconds": 0.133940909, "prefill_widths": [], "prefill_raised": [], "time_to_first_token": 0.134790839, "sampling": "exact", "drafts": false, "token_sha": "005a2bec0a1b", "token_sha256": "005a2bec0a1b958c27359d9f240f6a903fc0ce8789cb26affcf74052737c2320", "min_rows": 1}, "speculative": {"rounds": 42, "drafted": 0, "accepted": 0, "acceptance_rate": 0.0, "tokens_per_round": 1.0238095238095237}}, "seconds": 1.2484421730041504} +{"url": "http://127.0.0.1:30461/v1/chat/completions", "request": {"model": "flashnext", "messages": [{"role": "user", "content": "Explain in two sentences why the sky is blue."}], "max_tokens": 64, "temperature": 0.8, "seed": 7, "draft": false, "chat_template_kwargs": {"enable_thinking": false}}, "status": 200, "response": {"id": "chatcmpl-92abb72c4179fe5e8937a16a473a33a7", "object": "chat.completion", "created": 1793474439, "model": "flashnext", "choices": [{"index": 0, "message": {"role": "assistant", "content": "Sunlight enters Earth's atmosphere and scatters in all directions, with shorter blue wavelengths being scattered more strongly than other colors due to Rayleigh scattering. This scattered blue light is what our eyes perceive when we look up at the sky."}, "finish_reason": "stop"}], "usage": {"prompt_tokens": 23, "completion_tokens": 48, "total_tokens": 71, "prompt_tokens_details": {"cached_tokens": 0}, "completion_tokens_details": {"reasoning_tokens": 0}}, "exact_mode": "exact", "tensorfold": {"enable_thinking": false, "reasoning_effort": "none", "engine": "lanes", "tokens_per_second": 37.967143921905446, "seconds": 1.237912446, "prefill_seconds": 0.134339825, "prefill_widths": [], "prefill_raised": [], "time_to_first_token": 0.134964524, "sampling": "exact", "drafts": false, "token_sha": "aa3696ad4413", "token_sha256": "aa3696ad4413c4e602188fcf1e4977b40c6ca900446263b9fe4df6bc77d91842", "min_rows": 1}, "speculative": {"rounds": 47, "drafted": 0, "accepted": 0, "acceptance_rate": 0.0, "tokens_per_round": 1.0212765957446808}}, "seconds": 1.3751955032348633} +{"url": "http://127.0.0.1:30461/v1/chat/completions", "request": {"model": "flashnext", "messages": [{"role": "user", "content": "Count from one to thirty in words."}], "max_tokens": 64, "temperature": 0.8, "seed": 7, "draft": false, "chat_template_kwargs": {"enable_thinking": false}}, "status": 200, "response": {"id": "chatcmpl-53a9670948ec267d0994e3ad91f647ec", "object": "chat.completion", "created": 1793474441, "model": "flashnext", "choices": [{"index": 0, "message": {"role": "assistant", "content": "Here is the count from one to thirty in words:\n\n1. One\n2. Two\n3. Three\n4. Four\n5. Five\n6. Six\n7. Seven\n8. Eight\n9. Nine\n10. Ten\n11. Eleven\n12. Twelve\n1"}, "finish_reason": "length"}], "usage": {"prompt_tokens": 20, "completion_tokens": 64, "total_tokens": 84, "prompt_tokens_details": {"cached_tokens": 0}, "completion_tokens_details": {"reasoning_tokens": 0}}, "exact_mode": "exact", "tensorfold": {"enable_thinking": false, "reasoning_effort": "none", "engine": "lanes", "tokens_per_second": 37.03299591205044, "seconds": 1.701185617, "prefill_seconds": 0.121254086, "prefill_widths": [], "prefill_raised": [], "time_to_first_token": 0.121707113, "sampling": "exact", "drafts": false, "token_sha": "424bb4882c66", "token_sha256": "424bb4882c669373613489d541c3568ff7827f0376f9f49cef26ee9d0e483562", "min_rows": 1}, "speculative": {"rounds": 63, "drafted": 0, "accepted": 0, "acceptance_rate": 0.0, "tokens_per_round": 1.0158730158730158}}, "seconds": 1.8237574100494385} +{"url": "http://127.0.0.1:30461/v1/chat/completions", "request": {"model": "flashnext", "messages": [{"role": "user", "content": "Write a short poem about the sea."}], "max_tokens": 64, "temperature": 0.8, "seed": 7, "draft": true, "chat_template_kwargs": {"enable_thinking": false}}, "status": 200, "response": {"id": "chatcmpl-bd8949ca895ada9b81a1721ce51670fc", "object": "chat.completion", "created": 1793474443, "model": "flashnext", "choices": [{"index": 0, "message": {"role": "assistant", "content": "Salt and spray upon the breeze,\nWhispered secrets, ancient seas.\nBlue beneath the moon\u2019s pale eye,\nWhere the hidden currents lie.\n\nWaves that break on shores of stone,\nClaim the land, then leave it alone.\nIn your depth, the stars reflect,\nA mirror"}, "finish_reason": "length"}], "usage": {"prompt_tokens": 20, "completion_tokens": 64, "total_tokens": 84, "prompt_tokens_details": {"cached_tokens": 0}, "completion_tokens_details": {"reasoning_tokens": 0}}, "exact_mode": "exact", "tensorfold": {"enable_thinking": false, "reasoning_effort": "none", "engine": "lanes", "tokens_per_second": 45.03024247166627, "seconds": 1.399059755, "prefill_seconds": 0.124590429, "prefill_widths": [], "prefill_raised": [], "time_to_first_token": 0.125821113, "sampling": "exact", "drafts": true, "token_sha": "c0e21e789784", "token_sha256": "c0e21e789784d9ea2d45a012477c7c75a48bf3610e978a6961254670b0302613", "min_rows": 2}, "speculative": {"rounds": 35, "drafted": 54, "accepted": 28, "acceptance_rate": 0.5185185185185185, "tokens_per_round": 1.8285714285714285}}, "seconds": 1.5455970764160156} +{"url": "http://127.0.0.1:30461/v1/chat/completions", "request": {"model": "flashnext", "messages": [{"role": "user", "content": "List the first twelve prime numbers, separated by commas."}], "max_tokens": 64, "temperature": 0.8, "seed": 7, "draft": true, "chat_template_kwargs": {"enable_thinking": false}}, "status": 200, "response": {"id": "chatcmpl-e3c1af88800659ffb80d222ff55da6ab", "object": "chat.completion", "created": 1793474444, "model": "flashnext", "choices": [{"index": 0, "message": {"role": "assistant", "content": "2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37"}, "finish_reason": "stop"}], "usage": {"prompt_tokens": 23, "completion_tokens": 43, "total_tokens": 66, "prompt_tokens_details": {"cached_tokens": 0}, "completion_tokens_details": {"reasoning_tokens": 0}}, "exact_mode": "exact", "tensorfold": {"enable_thinking": false, "reasoning_effort": "none", "engine": "lanes", "tokens_per_second": 95.26860625141161, "seconds": 0.440858764, "prefill_seconds": 0.142963003, "prefill_widths": [], "prefill_raised": [], "time_to_first_token": 0.244499298, "sampling": "exact", "drafts": true, "token_sha": "005a2bec0a1b", "token_sha256": "005a2bec0a1b958c27359d9f240f6a903fc0ce8789cb26affcf74052737c2320", "min_rows": 7}, "speculative": {"rounds": 6, "drafted": 41, "accepted": 40, "acceptance_rate": 0.975609756097561, "tokens_per_round": 7.166666666666667}}, "seconds": 0.7559010982513428} +{"url": "http://127.0.0.1:30461/v1/chat/completions", "request": {"model": "flashnext", "messages": [{"role": "user", "content": "Explain in two sentences why the sky is blue."}], "max_tokens": 64, "temperature": 0.8, "seed": 7, "draft": true, "chat_template_kwargs": {"enable_thinking": false}}, "status": 200, "response": {"id": "chatcmpl-16d25d9c3f15b7c6ee36f0cf20fd7f34", "object": "chat.completion", "created": 1793474445, "model": "flashnext", "choices": [{"index": 0, "message": {"role": "assistant", "content": "Sunlight enters Earth's atmosphere and scatters in all directions, with shorter blue wavelengths being scattered more strongly than other colors due to Rayleigh scattering. This scattered blue light is what our eyes perceive when we look up at the sky."}, "finish_reason": "stop"}], "usage": {"prompt_tokens": 23, "completion_tokens": 48, "total_tokens": 71, "prompt_tokens_details": {"cached_tokens": 0}, "completion_tokens_details": {"reasoning_tokens": 0}}, "exact_mode": "exact", "tensorfold": {"enable_thinking": false, "reasoning_effort": "none", "engine": "lanes", "tokens_per_second": 57.49630823544775, "seconds": 0.817443788, "prefill_seconds": 0.138720604, "prefill_widths": [], "prefill_raised": [], "time_to_first_token": 0.139243212, "sampling": "exact", "drafts": true, "token_sha": "aa3696ad4413", "token_sha256": "aa3696ad4413c4e602188fcf1e4977b40c6ca900446263b9fe4df6bc77d91842", "min_rows": 2}, "speculative": {"rounds": 16, "drafted": 39, "accepted": 35, "acceptance_rate": 0.8974358974358975, "tokens_per_round": 3.0}}, "seconds": 0.9576196670532227} +{"url": "http://127.0.0.1:30461/v1/chat/completions", "request": {"model": "flashnext", "messages": [{"role": "user", "content": "Count from one to thirty in words."}], "max_tokens": 64, "temperature": 0.8, "seed": 7, "draft": true, "chat_template_kwargs": {"enable_thinking": false}}, "status": 200, "response": {"id": "chatcmpl-c2b97e76e5def98d9e3a5e4396cb1691", "object": "chat.completion", "created": 1793474446, "model": "flashnext", "choices": [{"index": 0, "message": {"role": "assistant", "content": "Here is the count from one to thirty in words:\n\n1. One\n2. Two\n3. Three\n4. Four\n5. Five\n6. Six\n7. Seven\n8. Eight\n9. Nine\n10. Ten\n11. Eleven\n12. Twelve\n1"}, "finish_reason": "length"}], "usage": {"prompt_tokens": 20, "completion_tokens": 64, "total_tokens": 84, "prompt_tokens_details": {"cached_tokens": 0}, "completion_tokens_details": {"reasoning_tokens": 0}}, "exact_mode": "exact", "tensorfold": {"enable_thinking": false, "reasoning_effort": "none", "engine": "lanes", "tokens_per_second": 75.53214119923805, "seconds": 0.834082008, "prefill_seconds": 0.123520348, "prefill_widths": [], "prefill_raised": [], "time_to_first_token": 0.124389373, "sampling": "exact", "drafts": true, "token_sha": "424bb4882c66", "token_sha256": "424bb4882c669373613489d541c3568ff7827f0376f9f49cef26ee9d0e483562", "min_rows": 2}, "speculative": {"rounds": 12, "drafted": 55, "accepted": 51, "acceptance_rate": 0.9272727272727272, "tokens_per_round": 5.333333333333333}}, "seconds": 0.9595789909362793} +{"url": "http://127.0.0.1:30461/v1/chat/completions", "request": {"model": "flashnext", "messages": [{"role": "user", "content": "List the first twelve prime numbers, separated by commas."}], "max_tokens": 64, "temperature": 0.8, "seed": 7, "draft": true, "chat_template_kwargs": {"enable_thinking": false}}, "status": 200, "response": {"id": "chatcmpl-53235e57a1fd6dedb3f81abf97e8435f", "object": "chat.completion", "created": 1793474447, "model": "flashnext", "choices": [{"index": 0, "message": {"role": "assistant", "content": "2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37"}, "finish_reason": "stop"}], "usage": {"prompt_tokens": 23, "completion_tokens": 43, "total_tokens": 66, "prompt_tokens_details": {"cached_tokens": 0}, "completion_tokens_details": {"reasoning_tokens": 0}}, "exact_mode": "exact", "tensorfold": {"enable_thinking": false, "reasoning_effort": "none", "engine": "lanes", "tokens_per_second": 36.76289480133358, "seconds": 1.142456279, "prefill_seconds": 0.412254541, "prefill_widths": [], "prefill_raised": [], "time_to_first_token": 0.536807862, "sampling": "exact", "drafts": true, "token_sha": "005a2bec0a1b", "token_sha256": "005a2bec0a1b958c27359d9f240f6a903fc0ce8789cb26affcf74052737c2320", "min_rows": 7}, "speculative": {"rounds": 6, "drafted": 41, "accepted": 40, "acceptance_rate": 0.975609756097561, "tokens_per_round": 7.166666666666667}}, "seconds": 1.6803574562072754} +{"url": "http://127.0.0.1:30461/v1/chat/completions", "request": {"model": "flashnext", "messages": [{"role": "user", "content": "Count from one to thirty in words."}], "max_tokens": 64, "temperature": 0.8, "seed": 7, "draft": true, "chat_template_kwargs": {"enable_thinking": false}}, "status": 200, "response": {"id": "chatcmpl-7007450f3872816224cfc2dee6ac558b", "object": "chat.completion", "created": 1793474447, "model": "flashnext", "choices": [{"index": 0, "message": {"role": "assistant", "content": "Here is the count from one to thirty in words:\n\n1. 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[{"role": "user", "content": "Explain in two sentences why the sky is blue."}], "max_tokens": 64, "temperature": 0.8, "seed": 7, "draft": false, "chat_template_kwargs": {"enable_thinking": false}}, "status": 200, "response": {"id": "chatcmpl-5eb9108ac0407c2ff382ac9bec4ef552", "object": "chat.completion", "created": 1793474463, "model": "flashnext", "choices": [{"index": 0, "message": {"role": "assistant", "content": "Sunlight enters Earth's atmosphere and scatters in all directions, with shorter blue wavelengths being scattered more strongly than other colors due to Rayleigh scattering. This scattered blue light is what our eyes perceive when we look up at the sky."}, "finish_reason": "stop"}], "usage": {"prompt_tokens": 23, "completion_tokens": 48, "total_tokens": 71, "prompt_tokens_details": {"cached_tokens": 0}, "completion_tokens_details": {"reasoning_tokens": 0}}, "exact_mode": "exact", "tensorfold": {"enable_thinking": false, "reasoning_effort": "none", "engine": "lanes", "tokens_per_second": 14.913475917203305, "seconds": 3.151512113, "prefill_seconds": 0.136227671, "prefill_widths": [], "prefill_raised": [], "time_to_first_token": 0.258034502, "sampling": "exact", "drafts": false, "token_sha": "aa3696ad4413", "token_sha256": "aa3696ad4413c4e602188fcf1e4977b40c6ca900446263b9fe4df6bc77d91842", "min_rows": 1}, "speculative": {"rounds": 47, "drafted": 0, "accepted": 0, "acceptance_rate": 0.0, "tokens_per_round": 1.0212765957446808}}, "seconds": 3.4102888107299805} +{"url": "http://127.0.0.1:30461/v1/chat/completions", "request": {"model": "flashnext", "messages": [{"role": "user", "content": "Write a short poem about the sea."}], "max_tokens": 64, "temperature": 0.8, "seed": 7, "draft": false, "chat_template_kwargs": {"enable_thinking": false}}, "status": 200, "response": {"id": "chatcmpl-9d3c945d7003ac9c82eccd4043f0b6b8", "object": "chat.completion", "created": 1793474463, "model": "flashnext", "choices": [{"index": 0, "message": {"role": "assistant", "content": "Salt and spray upon the breeze,\nWhispered secrets, ancient seas.\nBlue beneath the moon\u2019s pale eye,\nWhere the hidden currents lie.\n\nWaves that break on shores of stone,\nClaim the land, then leave it alone.\nIn your depth, the stars reflect,\nA mirror"}, "finish_reason": "length"}], "usage": {"prompt_tokens": 20, "completion_tokens": 64, "total_tokens": 84, "prompt_tokens_details": {"cached_tokens": 0}, "completion_tokens_details": {"reasoning_tokens": 0}}, "exact_mode": "exact", "tensorfold": {"enable_thinking": false, "reasoning_effort": "none", "engine": "lanes", 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"content": "Beneath the moon\u2019s pale, silver gaze,\nThe ocean hums its ancient ways.\nA rhythm kept in salt and spray,\nThat washes sorrow far away.\n\nThe waves rise high, then break and fall,\nAnswering nature\u2019s tidal call.\nA mirror for the sky\u2019s deep"}, "finish_reason": "length"}], "usage": {"prompt_tokens": 20, "completion_tokens": 64, "total_tokens": 84, "prompt_tokens_details": {"cached_tokens": 0}, "completion_tokens_details": {"reasoning_tokens": 0}}, "exact_mode": "exact", "tensorfold": {"enable_thinking": false, "reasoning_effort": "none", "engine": "lanes", "tokens_per_second": 45.5085997550392, "seconds": 1.384353734, "prefill_seconds": 0.127258967, "prefill_widths": [], "prefill_raised": [], "time_to_first_token": 0.127916226, "sampling": "greedy", "drafts": true, "token_sha": "bf3402132772", "token_sha256": "bf340213277244a9a02c4602c2abe994ecbb17d6a385aa6d5bb7f88a501f2545", "min_rows": 2}, "speculative": {"rounds": 33, "drafted": 61, "accepted": 31, "acceptance_rate": 0.5081967213114754, "tokens_per_round": 1.9393939393939394}}, "seconds": 1.6176269054412842} +{"url": "http://127.0.0.1:30461/v1/chat/completions", "request": {"model": "flashnext", "messages": [{"role": "user", "content": "Write a short poem about the sea."}, {"role": "assistant", "content": "Beneath the moon\u2019s pale, silver gaze,\nThe ocean hums its ancient ways.\nA rhythm kept in salt and spray,\nThat washes sorrow far away.\n\nThe waves rise high, then break and fall,\nAnswering nature\u2019s tidal call.\nA mirror for the sky\u2019s deep"}, {"role": "user", "content": "Now say it shorter."}], "max_tokens": 64, "temperature": 0.0, "seed": 7, "draft": false, "chat_template_kwargs": {"enable_thinking": false}}, "status": 200, "response": {"id": "chatcmpl-e322e6bfc51a9e6c43b7e31230ead256", "object": "chat.completion", "created": 1793474469, "model": "flashnext", "choices": [{"index": 0, "message": {"role": "assistant", "content": "Salt and spray,\nWash sorrow away."}, "finish_reason": "stop"}], "usage": {"prompt_tokens": 103, "completion_tokens": 11, "total_tokens": 114, "prompt_tokens_details": {"cached_tokens": 0}, "completion_tokens_details": {"reasoning_tokens": 0}}, "exact_mode": "exact", "tensorfold": {"enable_thinking": false, "reasoning_effort": "none", "engine": "lanes", "tokens_per_second": 39.34749622064348, "seconds": 0.254145777, "prefill_seconds": 0.406021674, "prefill_widths": [], "prefill_raised": [], "time_to_first_token": 0.407088461, "sampling": "greedy", "drafts": false, "token_sha": "3a793d464e98", "token_sha256": "3a793d464e9820a04665343d5adfcf3bb49b47d37a77f49fea5eafbe51dfe6c9", "min_rows": 1}, "speculative": {"rounds": 10, "drafted": 0, "accepted": 0, "acceptance_rate": 0.0, "tokens_per_round": 1.1}}, "seconds": 0.6774873733520508} +{"url": "http://127.0.0.1:30461/v1/chat/completions", "request": {"model": "flashnext", "messages": [{"role": "user", "content": "Write a short poem about the sea."}, {"role": "assistant", "content": "Beneath the moon\u2019s pale, silver gaze,\nThe ocean hums its ancient ways.\nA rhythm kept in salt and spray,\nThat washes sorrow far away.\n\nThe waves rise high, then break and fall,\nAnswering nature\u2019s tidal call.\nA mirror for the sky\u2019s deep"}, {"role": "user", "content": "Now say it shorter."}], "max_tokens": 64, "temperature": 0.0, "seed": 7, "draft": true, "chat_template_kwargs": {"enable_thinking": false}}, "status": 200, "response": {"id": "chatcmpl-7b4667fcbe7b02ec020a7c5eada2bb5e", "object": "chat.completion", "created": 1793474470, "model": "flashnext", "choices": [{"index": 0, "message": {"role": "assistant", "content": "Salt and spray,\nWash sorrow away."}, "finish_reason": "stop"}], "usage": {"prompt_tokens": 103, "completion_tokens": 11, "total_tokens": 114, "prompt_tokens_details": {"cached_tokens": 0}, "completion_tokens_details": {"reasoning_tokens": 0}}, "exact_mode": "exact", "tensorfold": {"enable_thinking": false, "reasoning_effort": "none", "engine": "lanes", "tokens_per_second": 33.47332368239391, "seconds": 0.298745356, "prefill_seconds": 0.26360508, "prefill_widths": [], "prefill_raised": [], "time_to_first_token": 0.264389147, "sampling": "greedy", "drafts": true, "token_sha": "3a793d464e98", "token_sha256": "3a793d464e9820a04665343d5adfcf3bb49b47d37a77f49fea5eafbe51dfe6c9", "min_rows": 2}, "speculative": {"rounds": 6, "drafted": 13, "accepted": 8, "acceptance_rate": 0.6153846153846154, "tokens_per_round": 1.8333333333333333}}, "seconds": 0.5770764350891113} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/exactness/seam-corpus.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/exactness/seam-corpus.json new file mode 100644 index 0000000000..a6fa959843 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/exactness/seam-corpus.json @@ -0,0 +1,31 @@ +{ + "python": "3.13.5", + "chars": 39999, + "files_used": [ + { + "file": "__future__.py", + "sha256": "981d4c398849f9ebcab72300d9c1fe288fd6d7f28957b3b3fa3a493a5836d95c" + }, + { + "file": "__hello__.py", + "sha256": "a8ce70b199497950f0f06def93115a6814daf1f961934457f59046909901487f" + }, + { + "file": "_aix_support.py", + "sha256": "0982f187c62fbfc1e8d368c8eb4104b56df71009a6b2823565a699e7b4cd945c" + }, + { + "file": "_android_support.py", + "sha256": "2010868fba48f4c92a317e807e34e3a0bd6d383a68f95a07152ad91ed6651636" + }, + { + "file": "_apple_support.py", + "sha256": "3bde7533b66dafa0c755c92bf09b30932a723ca58905a3fac670d53e3149f47b" + }, + { + "file": "_collections_abc.py", + "sha256": "2cfe340c4cf54077f054cd366a2c7a515e9ee8da7d8b3fa071251f280034756d" + } + ], + "text_sha256": "5bbfb9160196d715cf78402a789adf7478eb485477fa4b5390c1707804f620f3" +} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/logs/generate-exact-chunk2048.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/logs/generate-exact-chunk2048.log new file mode 100644 index 0000000000..64a573f7a5 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/logs/generate-exact-chunk2048.log @@ -0,0 +1,1293 @@ +loaded in 20.4 s, 78.15 GiB on the device +prompt 10368 tokens in 19.716 s (525.9 tok/s); 63 tokens in 1.778 s (35.44 tok/s) +logits hash c8f6888043c972e0 +ids { 27775, 383, 279, 1970, 3766, 11, 1532, 369, 449, 6157, 321, 11782, 314, 279, 12654, 5129, 6522, 13067, 5064, 303, 279, 41643, 13, 271, 13962, 220, 16, 13, 1510, 548, 20409, 18162, 3181, 63, 198, 332, 71516, 64700, 1061, 4536, 7189, 328, 734, 1422, 3309, 51047, 3992, 4203, 1149, 1049, 5954, 13015, 310, 7056, 3725, 12654, 4275, 303, 1428, 10478, 1608, 1510, 1445, 1259 } +--- +<|im_start|>user +# file: __future__.py +"""Record of phased-in incompatible language changes. + +Each line is of the form: + + FeatureName = "_Feature(" OptionalRelease "," MandatoryRelease "," + CompilerFlag ")" + +where, normally, OptionalRelease < MandatoryRelease, and both are 5-tuples +of the same form as sys.version_info: + + (PY_MAJOR_VERSION, # the 2 in 2.1.0a3; an int + PY_MINOR_VERSION, # the 1; an int + PY_MICRO_VERSION, # the 0; an int + PY_RELEASE_LEVEL, # "alpha", "beta", "candidate" or "final"; string + PY_RELEASE_SERIAL # the 3; an int + ) + +OptionalRelease records the first release in which + + from __future__ import FeatureName + +was accepted. + +In the case of MandatoryReleases that have not yet occurred, +MandatoryRelease predicts the release in which the feature will become part +of the language. + +Else MandatoryRelease records when the feature became part of the language; +in releases at or after that, modules no longer need + + from __future__ import FeatureName + +to use the feature in question, but may continue to use such imports. + +MandatoryRelease may also be None, meaning that a planned feature got +dropped or that the release version is undetermined. + +Instances of class _Feature have two corresponding methods, +.getOptionalRelease() and .getMandatoryRelease(). + +CompilerFlag is the (bitfield) flag that should be passed in the fourth +argument to the builtin function compile() to enable the feature in +dynamically compiled code. This flag is stored in the .compiler_flag +attribute on _Future instances. These values must match the appropriate +#defines of CO_xxx flags in Include/cpython/compile.h. + +No feature line is ever to be deleted from this file. +""" + +all_feature_names = [ + "nested_scopes", + "generators", + "division", + "absolute_import", + "with_statement", + "print_function", + "unicode_literals", + "barry_as_FLUFL", + "generator_stop", + "annotations", +] + +__all__ = ["all_feature_names"] + all_feature_names + +# The CO_xxx symbols are defined here under the same names defined in +# code.h and used by compile.h, so that an editor search will find them here. +# However, they're not exported in __all__, because they don't really belong to +# this module. +CO_NESTED = 0x0010 # nested_scopes +CO_GENERATOR_ALLOWED = 0 # generators (obsolete, was 0x1000) +CO_FUTURE_DIVISION = 0x20000 # division +CO_FUTURE_ABSOLUTE_IMPORT = 0x40000 # perform absolute imports by default +CO_FUTURE_WITH_STATEMENT = 0x80000 # with statement +CO_FUTURE_PRINT_FUNCTION = 0x100000 # print function +CO_FUTURE_UNICODE_LITERALS = 0x200000 # unicode string literals +CO_FUTURE_BARRY_AS_BDFL = 0x400000 +CO_FUTURE_GENERATOR_STOP = 0x800000 # StopIteration becomes RuntimeError in generators +CO_FUTURE_ANNOTATIONS = 0x1000000 # annotations become strings at runtime + + +class _Feature: + + def __init__(self, optionalRelease, mandatoryRelease, compiler_flag): + self.optional = optionalRelease + self.mandatory = mandatoryRelease + self.compiler_flag = compiler_flag + + def getOptionalRelease(self): + """Return first release in which this feature was recognized. + + This is a 5-tuple, of the same form as sys.version_info. + """ + return self.optional + + def getMandatoryRelease(self): + """Return release in which this feature will become mandatory. + + This is a 5-tuple, of the same form as sys.version_info, or, if + the feature was dropped, or the release date is undetermined, is None. + """ + return self.mandatory + + def __repr__(self): + return "_Feature" + repr((self.optional, + self.mandatory, + self.compiler_flag)) + + +nested_scopes = _Feature((2, 1, 0, "beta", 1), + (2, 2, 0, "alpha", 0), + CO_NESTED) + +generators = _Feature((2, 2, 0, "alpha", 1), + (2, 3, 0, "final", 0), + CO_GENERATOR_ALLOWED) + +division = _Feature((2, 2, 0, "alpha", 2), + (3, 0, 0, "alpha", 0), + CO_FUTURE_DIVISION) + +absolute_import = _Feature((2, 5, 0, "alpha", 1), + (3, 0, 0, "alpha", 0), + CO_FUTURE_ABSOLUTE_IMPORT) + +with_statement = _Feature((2, 5, 0, "alpha", 1), + (2, 6, 0, "alpha", 0), + CO_FUTURE_WITH_STATEMENT) + +print_function = _Feature((2, 6, 0, "alpha", 2), + (3, 0, 0, "alpha", 0), + CO_FUTURE_PRINT_FUNCTION) + +unicode_literals = _Feature((2, 6, 0, "alpha", 2), + (3, 0, 0, "alpha", 0), + CO_FUTURE_UNICODE_LITERALS) + +barry_as_FLUFL = _Feature((3, 1, 0, "alpha", 2), + (4, 0, 0, "alpha", 0), + CO_FUTURE_BARRY_AS_BDFL) + +generator_stop = _Feature((3, 5, 0, "beta", 1), + (3, 7, 0, "alpha", 0), + CO_FUTURE_GENERATOR_STOP) + +annotations = _Feature((3, 7, 0, "beta", 1), + None, + CO_FUTURE_ANNOTATIONS) + +# file: __hello__.py +initialized = True + +class TestFrozenUtf8_1: + """\u00b6""" + +class TestFrozenUtf8_2: + """\u03c0""" + +class TestFrozenUtf8_4: + """\U0001f600""" + +def main(): + print("Hello world!") + +if __name__ == '__main__': + main() + +# file: _aix_support.py +"""Shared AIX support functions.""" + +import sys +import sysconfig + + +# Taken from _osx_support _read_output function +def _read_cmd_output(commandstring, capture_stderr=False): + """Output from successful command execution or None""" + # Similar to os.popen(commandstring, "r").read(), + # but without actually using os.popen because that + # function is not usable during python bootstrap. + import os + import contextlib + fp = open("/tmp/_aix_support.%s"%( + os.getpid(),), "w+b") + + with contextlib.closing(fp) as fp: + if capture_stderr: + cmd = "%s >'%s' 2>&1" % (commandstring, fp.name) + else: + cmd = "%s 2>/dev/null >'%s'" % (commandstring, fp.name) + return fp.read() if not os.system(cmd) else None + + +def _aix_tag(vrtl, bd): + # type: (List[int], int) -> str + # Infer the ABI bitwidth from maxsize (assuming 64 bit as the default) + _sz = 32 if sys.maxsize == (2**31-1) else 64 + _bd = bd if bd != 0 else 9988 + # vrtl[version, release, technology_level] + return "aix-{:1x}{:1d}{:02d}-{:04d}-{}".format(vrtl[0], vrtl[1], vrtl[2], _bd, _sz) + + +# extract version, release and technology level from a VRMF string +def _aix_vrtl(vrmf): + # type: (str) -> List[int] + v, r, tl = vrmf.split(".")[:3] + return [int(v[-1]), int(r), int(tl)] + + +def _aix_bos_rte(): + # type: () -> Tuple[str, int] + """ + Return a Tuple[str, int] e.g., ['7.1.4.34', 1806] + The fileset bos.rte represents the current AIX run-time level. It's VRMF and + builddate reflect the current ABI levels of the runtime environment. + If no builddate is found give a value that will satisfy pep425 related queries + """ + # All AIX systems to have lslpp installed in this location + # subprocess may not be available during python bootstrap + try: + import subprocess + out = subprocess.check_output(["/usr/bin/lslpp", "-Lqc", "bos.rte"]) + except ImportError: + out = _read_cmd_output("/usr/bin/lslpp -Lqc bos.rte") + out = out.decode("utf-8") + out = out.strip().split(":") # type: ignore + _bd = int(out[-1]) if out[-1] != '' else 9988 + return (str(out[2]), _bd) + + +def aix_platform(): + # type: () -> str + """ + AIX filesets are identified by four decimal values: V.R.M.F. + V (version) and R (release) can be retrieved using ``uname`` + Since 2007, starting with AIX 5.3 TL7, the M value has been + included with the fileset bos.rte and represents the Technology + Level (TL) of AIX. The F (Fix) value also increases, but is not + relevant for comparing releases and binary compatibility. + For binary compatibility the so-called builddate is needed. + Again, the builddate of an AIX release is associated with bos.rte. + AIX ABI compatibility is described as guaranteed at: https://www.ibm.com/\ + support/knowledgecenter/en/ssw_aix_72/install/binary_compatability.html + + For pep425 purposes the AIX platform tag becomes: + "aix-{:1x}{:1d}{:02d}-{:04d}-{}".format(v, r, tl, builddate, bitsize) + e.g., "aix-6107-1415-32" for AIX 6.1 TL7 bd 1415, 32-bit + and, "aix-6107-1415-64" for AIX 6.1 TL7 bd 1415, 64-bit + """ + vrmf, bd = _aix_bos_rte() + return _aix_tag(_aix_vrtl(vrmf), bd) + + +# extract vrtl from the BUILD_GNU_TYPE as an int +def _aix_bgt(): + # type: () -> List[int] + gnu_type = sysconfig.get_config_var("BUILD_GNU_TYPE") + if not gnu_type: + raise ValueError("BUILD_GNU_TYPE is not defined") + return _aix_vrtl(vrmf=gnu_type) + + +def aix_buildtag(): + # type: () -> str + """ + Return the platform_tag of the system Python was built on. + """ + # AIX_BUILDDATE is defined by configure with: + # lslpp -Lcq bos.rte | awk -F: '{ print $NF }' + build_date = sysconfig.get_config_var("AIX_BUILDDATE") + try: + build_date = int(build_date) + except (ValueError, TypeError): + raise ValueError(f"AIX_BUILDDATE is not defined or invalid: " + f"{build_date!r}") + return _aix_tag(_aix_bgt(), build_date) + +# file: _android_support.py +import io +import sys +from threading import RLock +from time import sleep, time + +# The maximum length of a log message in bytes, including the level marker and +# tag, is defined as LOGGER_ENTRY_MAX_PAYLOAD at +# https://cs.android.com/android/platform/superproject/+/android-14.0.0_r1:system/logging/liblog/include/log/log.h;l=71. +# Messages longer than this will be truncated by logcat. This limit has already +# been reduced at least once in the history of Android (from 4076 to 4068 between +# API level 23 and 26), so leave some headroom. +MAX_BYTES_PER_WRITE = 4000 + +# UTF-8 uses a maximum of 4 bytes per character, so limiting text writes to this +# size ensures that we can always avoid exceeding MAX_BYTES_PER_WRITE. +# However, if the actual number of bytes per character is smaller than that, +# then we may still join multiple consecutive text writes into binary +# writes containing a larger number of characters. +MAX_CHARS_PER_WRITE = MAX_BYTES_PER_WRITE // 4 + + +# When embedded in an app on current versions of Android, there's no easy way to +# monitor the C-level stdout and stderr. The testbed comes with a .c file to +# redirect them to the system log using a pipe, but that wouldn't be convenient +# or appropriate for all apps. So we redirect at the Python level instead. +def init_streams(android_log_write, stdout_prio, stderr_prio): + if sys.executable: + return # Not embedded in an app. + + global logcat + logcat = Logcat(android_log_write) + + sys.stdout = TextLogStream( + stdout_prio, "python.stdout", sys.stdout.fileno()) + sys.stderr = TextLogStream( + stderr_prio, "python.stderr", sys.stderr.fileno()) + + +class TextLogStream(io.TextIOWrapper): + def __init__(self, prio, tag, fileno=None, **kwargs): + # The default is surrogateescape for stdout and backslashreplace for + # stderr, but in the context of an Android log, readability is more + # important than reversibility. + kwargs.setdefault("encoding", "UTF-8") + kwargs.setdefault("errors", "backslashreplace") + + super().__init__(BinaryLogStream(prio, tag, fileno), **kwargs) + self._lock = RLock() + self._pending_bytes = [] + self._pending_bytes_count = 0 + + def __repr__(self): + return f"" + + def write(self, s): + if not isinstance(s, str): + raise TypeError( + f"write() argument must be str, not {type(s).__name__}") + + # In case `s` is a str subclass that writes itself to stdout or stderr + # when we call its methods, convert it to an actual str. + s = str.__str__(s) + + # We want to emit one log message per line wherever possible, so split + # the string into lines first. Note that "".splitlines() == [], so + # nothing will be logged for an empty string. + with self._lock: + for line in s.splitlines(keepends=True): + while line: + chunk = line[:MAX_CHARS_PER_WRITE] + line = line[MAX_CHARS_PER_WRITE:] + self._write_chunk(chunk) + + return len(s) + + # The size and behavior of TextIOWrapper's buffer is not part of its public + # API, so we handle buffering ourselves to avoid truncation. + def _write_chunk(self, s): + b = s.encode(self.encoding, self.errors) + if self._pending_bytes_count + len(b) > MAX_BYTES_PER_WRITE: + self.flush() + + self._pending_bytes.append(b) + self._pending_bytes_count += len(b) + if ( + self.write_through + or b.endswith(b"\n") + or self._pending_bytes_count > MAX_BYTES_PER_WRITE + ): + self.flush() + + def flush(self): + with self._lock: + self.buffer.write(b"".join(self._pending_bytes)) + self._pending_bytes.clear() + self._pending_bytes_count = 0 + + # Since this is a line-based logging system, line buffering cannot be turned + # off, i.e. a newline always causes a flush. + @property + def line_buffering(self): + return True + + +class BinaryLogStream(io.RawIOBase): + def __init__(self, prio, tag, fileno=None): + self.prio = prio + self.tag = tag + self._fileno = fileno + + def __repr__(self): + return f"" + + def writable(self): + return True + + def write(self, b): + if type(b) is not bytes: + try: + b = bytes(memoryview(b)) + except TypeError: + raise TypeError( + f"write() argument must be bytes-like, not {type(b).__name__}" + ) from None + + # Writing an empty string to the stream should have no effect. + if b: + logcat.write(self.prio, self.tag, b) + return len(b) + + # This is needed by the test suite --timeout option, which uses faulthandler. + def fileno(self): + if self._fileno is None: + raise io.UnsupportedOperation("fileno") + return self._fileno + + +# When a large volume of data is written to logcat at once, e.g. when a test +# module fails in --verbose3 mode, there's a risk of overflowing logcat's own +# buffer and losing messages. We avoid this by imposing a rate limit using the +# token bucket algorithm, based on a conservative estimate of how fast `adb +# logcat` can consume data. +MAX_BYTES_PER_SECOND = 1024 * 1024 + +# The logcat buffer size of a device can be determined by running `logcat -g`. +# We set the token bucket size to half of the buffer size of our current minimum +# API level, because other things on the system will be producing messages as +# well. +BUCKET_SIZE = 128 * 1024 + +# https://cs.android.com/android/platform/superproject/+/android-14.0.0_r1:system/logging/liblog/include/log/log_read.h;l=39 +PER_MESSAGE_OVERHEAD = 28 + + +class Logcat: + def __init__(self, android_log_write): + self.android_log_write = android_log_write + self._lock = RLock() + self._bucket_level = 0 + self._prev_write_time = time() + + def write(self, prio, tag, message): + # Encode null bytes using "modified UTF-8" to avoid them truncating the + # message. + message = message.replace(b"\x00", b"\xc0\x80") + + with self._lock: + now = time() + self._bucket_level += ( + (now - self._prev_write_time) * MAX_BYTES_PER_SECOND) + + # If the bucket level is still below zero, the clock must have gone + # backwards, so reset it to zero and continue. + self._bucket_level = max(0, min(self._bucket_level, BUCKET_SIZE)) + self._prev_write_time = now + + self._bucket_level -= PER_MESSAGE_OVERHEAD + len(tag) + len(message) + if self._bucket_level < 0: + sleep(-self._bucket_level / MAX_BYTES_PER_SECOND) + + self.android_log_write(prio, tag, message) + +# file: _apple_support.py +import io +import sys + + +def init_streams(log_write, stdout_level, stderr_level): + # Redirect stdout and stderr to the Apple system log. This method is + # invoked by init_apple_streams() (initconfig.c) if config->use_system_logger + # is enabled. + sys.stdout = SystemLog(log_write, stdout_level, errors=sys.stderr.errors) + sys.stderr = SystemLog(log_write, stderr_level, errors=sys.stderr.errors) + + +class SystemLog(io.TextIOWrapper): + def __init__(self, log_write, level, **kwargs): + kwargs.setdefault("encoding", "UTF-8") + kwargs.setdefault("line_buffering", True) + super().__init__(LogStream(log_write, level), **kwargs) + + def __repr__(self): + return f"" + + def write(self, s): + if not isinstance(s, str): + raise TypeError( + f"write() argument must be str, not {type(s).__name__}") + + # In case `s` is a str subclass that writes itself to stdout or stderr + # when we call its methods, convert it to an actual str. + s = str.__str__(s) + + # We want to emit one log message per line, so split + # the string before sending it to the superclass. + for line in s.splitlines(keepends=True): + super().write(line) + + return len(s) + + +class LogStream(io.RawIOBase): + def __init__(self, log_write, level): + self.log_write = log_write + self.level = level + + def __repr__(self): + return f"" + + def writable(self): + return True + + def write(self, b): + if type(b) is not bytes: + try: + b = bytes(memoryview(b)) + except TypeError: + raise TypeError( + f"write() argument must be bytes-like, not {type(b).__name__}" + ) from None + + # Writing an empty string to the stream should have no effect. + if b: + # Encode null bytes using "modified UTF-8" to avoid truncating the + # message. This should not affect the return value, as the caller + # may be expecting it to match the length of the input. + self.log_write(self.level, b.replace(b"\x00", b"\xc0\x80")) + + return len(b) + +# file: _collections_abc.py +# Copyright 2007 Google, Inc. All Rights Reserved. +# Licensed to PSF under a Contributor Agreement. + +"""Abstract Base Classes (ABCs) for collections, according to PEP 3119. + +Unit tests are in test_collections. +""" + +############ Maintenance notes ######################################### +# +# ABCs are different from other standard library modules in that they +# specify compliance tests. In general, once an ABC has been published, +# new methods (either abstract or concrete) cannot be added. +# +# Though classes that inherit from an ABC would automatically receive a +# new mixin method, registered classes would become non-compliant and +# violate the contract promised by ``isinstance(someobj, SomeABC)``. +# +# Though irritating, the correct procedure for adding new abstract or +# mixin methods is to create a new ABC as a subclass of the previous +# ABC. For example, union(), intersection(), and difference() cannot +# be added to Set but could go into a new ABC that extends Set. +# +# Because they are so hard to change, new ABCs should have their APIs +# carefully thought through prior to publication. +# +# Since ABCMeta only checks for the presence of methods, it is possible +# to alter the signature of a method by adding optional arguments +# or changing parameters names. This is still a bit dubious but at +# least it won't cause isinstance() to return an incorrect result. +# +# +####################################################################### + +from abc import ABCMeta, abstractmethod +import sys + +GenericAlias = type(list[int]) +EllipsisType = type(...) +def _f(): pass +FunctionType = type(_f) +del _f + +__all__ = ["Awaitable", "Coroutine", + "AsyncIterable", "AsyncIterator", "AsyncGenerator", + "Hashable", "Iterable", "Iterator", "Generator", "Reversible", + "Sized", "Container", "Callable", "Collection", + "Set", "MutableSet", + "Mapping", "MutableMapping", + "MappingView", "KeysView", "ItemsView", "ValuesView", + "Sequence", "MutableSequence", + "ByteString", "Buffer", + ] + +# This module has been renamed from collections.abc to _collections_abc to +# speed up interpreter startup. Some of the types such as MutableMapping are +# required early but collections module imports a lot of other modules. +# See issue #19218 +__name__ = "collections.abc" + +# Private list of types that we want to register with the various ABCs +# so that they will pass tests like: +# it = iter(somebytearray) +# assert isinstance(it, Iterable) +# Note: in other implementations, these types might not be distinct +# and they may have their own implementation specific types that +# are not included on this list. +bytes_iterator = type(iter(b'')) +bytearray_iterator = type(iter(bytearray())) +#callable_iterator = ??? +dict_keyiterator = type(iter({}.keys())) +dict_valueiterator = type(iter({}.values())) +dict_itemiterator = type(iter({}.items())) +list_iterator = type(iter([])) +list_reverseiterator = type(iter(reversed([]))) +range_iterator = type(iter(range(0))) +longrange_iterator = type(iter(range(1 << 1000))) +set_iterator = type(iter(set())) +str_iterator = type(iter("")) +tuple_iterator = type(iter(())) +zip_iterator = type(iter(zip())) +## views ## +dict_keys = type({}.keys()) +dict_values = type({}.values()) +dict_items = type({}.items()) +## misc ## +mappingproxy = type(type.__dict__) +def _get_framelocalsproxy(): + return type(sys._getframe().f_locals) +framelocalsproxy = _get_framelocalsproxy() +del _get_framelocalsproxy +generator = type((lambda: (yield))()) +## coroutine ## +async def _coro(): pass +_coro = _coro() +coroutine = type(_coro) +_coro.close() # Prevent ResourceWarning +del _coro +## asynchronous generator ## +async def _ag(): yield +_ag = _ag() +async_generator = type(_ag) +del _ag + + +### ONE-TRICK PONIES ### + +def _check_methods(C, *methods): + mro = C.__mro__ + for method in methods: + for B in mro: + if method in B.__dict__: + if B.__dict__[method] is None: + return NotImplemented + break + else: + return NotImplemented + return True + +class Hashable(metaclass=ABCMeta): + + __slots__ = () + + @abstractmethod + def __hash__(self): + return 0 + + @classmethod + def __subclasshook__(cls, C): + if cls is Hashable: + return _check_methods(C, "__hash__") + return NotImplemented + + +class Awaitable(metaclass=ABCMeta): + + __slots__ = () + + @abstractmethod + def __await__(self): + yield + + @classmethod + def __subclasshook__(cls, C): + if cls is Awaitable: + return _check_methods(C, "__await__") + return NotImplemented + + __class_getitem__ = classmethod(GenericAlias) + + +class Coroutine(Awaitable): + + __slots__ = () + + @abstractmethod + def send(self, value): + """Send a value into the coroutine. + Return next yielded value or raise StopIteration. + """ + raise StopIteration + + @abstractmethod + def throw(self, typ, val=None, tb=None): + """Raise an exception in the coroutine. + Return next yielded value or raise StopIteration. + """ + if val is None: + if tb is None: + raise typ + val = typ() + if tb is not None: + val = val.with_traceback(tb) + raise val + + def close(self): + """Raise GeneratorExit inside coroutine. + """ + try: + self.throw(GeneratorExit) + except (GeneratorExit, StopIteration): + pass + else: + raise RuntimeError("coroutine ignored GeneratorExit") + + @classmethod + def __subclasshook__(cls, C): + if cls is Coroutine: + return _check_methods(C, '__await__', 'send', 'throw', 'close') + return NotImplemented + + +Coroutine.register(coroutine) + + +class AsyncIterable(metaclass=ABCMeta): + + __slots__ = () + + @abstractmethod + def __aiter__(self): + return AsyncIterator() + + @classmethod + def __subclasshook__(cls, C): + if cls is AsyncIterable: + return _check_methods(C, "__aiter__") + return NotImplemented + + __class_getitem__ = classmethod(GenericAlias) + + +class AsyncIterator(AsyncIterable): + + __slots__ = () + + @abstractmethod + async def __anext__(self): + """Return the next item or raise StopAsyncIteration when exhausted.""" + raise StopAsyncIteration + + def __aiter__(self): + return self + + @classmethod + def __subclasshook__(cls, C): + if cls is AsyncIterator: + return _check_methods(C, "__anext__", "__aiter__") + return NotImplemented + + +class AsyncGenerator(AsyncIterator): + + __slots__ = () + + async def __anext__(self): + """Return the next item from the asynchronous generator. + When exhausted, raise StopAsyncIteration. + """ + return await self.asend(None) + + @abstractmethod + async def asend(self, value): + """Send a value into the asynchronous generator. + Return next yielded value or raise StopAsyncIteration. + """ + raise StopAsyncIteration + + @abstractmethod + async def athrow(self, typ, val=None, tb=None): + """Raise an exception in the asynchronous generator. + Return next yielded value or raise StopAsyncIteration. + """ + if val is None: + if tb is None: + raise typ + val = typ() + if tb is not None: + val = val.with_traceback(tb) + raise val + + async def aclose(self): + """Raise GeneratorExit inside coroutine. + """ + try: + await self.athrow(GeneratorExit) + except (GeneratorExit, StopAsyncIteration): + pass + else: + raise RuntimeError("asynchronous generator ignored GeneratorExit") + + @classmethod + def __subclasshook__(cls, C): + if cls is AsyncGenerator: + return _check_methods(C, '__aiter__', '__anext__', + 'asend', 'athrow', 'aclose') + return NotImplemented + + +AsyncGenerator.register(async_generator) + + +class Iterable(metaclass=ABCMeta): + + __slots__ = () + + @abstractmethod + def __iter__(self): + while False: + yield None + + @classmethod + def __subclasshook__(cls, C): + if cls is Iterable: + return _check_methods(C, "__iter__") + return NotImplemented + + __class_getitem__ = classmethod(GenericAlias) + + +class Iterator(Iterable): + + __slots__ = () + + @abstractmethod + def __next__(self): + 'Return the next item from the iterator. When exhausted, raise StopIteration' + raise StopIteration + + def __iter__(self): + return self + + @classmethod + def __subclasshook__(cls, C): + if cls is Iterator: + return _check_methods(C, '__iter__', '__next__') + return NotImplemented + + +Iterator.register(bytes_iterator) +Iterator.register(bytearray_iterator) +#Iterator.register(callable_iterator) +Iterator.register(dict_keyiterator) +Iterator.register(dict_valueiterator) +Iterator.register(dict_itemiterator) +Iterator.register(list_iterator) +Iterator.register(list_reverseiterator) +Iterator.register(range_iterator) +Iterator.register(longrange_iterator) +Iterator.register(set_iterator) +Iterator.register(str_iterator) +Iterator.register(tuple_iterator) +Iterator.register(zip_iterator) + + +class Reversible(Iterable): + + __slots__ = () + + @abstractmethod + def __reversed__(self): + while False: + yield None + + @classmethod + def __subclasshook__(cls, C): + if cls is Reversible: + return _check_methods(C, "__reversed__", "__iter__") + return NotImplemented + + +class Generator(Iterator): + + __slots__ = () + + def __next__(self): + """Return the next item from the generator. + When exhausted, raise StopIteration. + """ + return self.send(None) + + @abstractmethod + def send(self, value): + """Send a value into the generator. + Return next yielded value or raise StopIteration. + """ + raise StopIteration + + @abstractmethod + def throw(self, typ, val=None, tb=None): + """Raise an exception in the generator. + Return next yielded value or raise StopIteration. + """ + if val is None: + if tb is None: + raise typ + val = typ() + if tb is not None: + val = val.with_traceback(tb) + raise val + + def close(self): + """Raise GeneratorExit inside generator. + """ + try: + self.throw(GeneratorExit) + except (GeneratorExit, StopIteration): + pass + else: + raise RuntimeError("generator ignored GeneratorExit") + + @classmethod + def __subclasshook__(cls, C): + if cls is Generator: + return _check_methods(C, '__iter__', '__next__', + 'send', 'throw', 'close') + return NotImplemented + + +Generator.register(generator) + + +class Sized(metaclass=ABCMeta): + + __slots__ = () + + @abstractmethod + def __len__(self): + return 0 + + @classmethod + def __subclasshook__(cls, C): + if cls is Sized: + return _check_methods(C, "__len__") + return NotImplemented + + +class Container(metaclass=ABCMeta): + + __slots__ = () + + @abstractmethod + def __contains__(self, x): + return False + + @classmethod + def __subclasshook__(cls, C): + if cls is Container: + return _check_methods(C, "__contains__") + return NotImplemented + + __class_getitem__ = classmethod(GenericAlias) + + +class Collection(Sized, Iterable, Container): + + __slots__ = () + + @classmethod + def __subclasshook__(cls, C): + if cls is Collection: + return _check_methods(C, "__len__", "__iter__", "__contains__") + return NotImplemented + + +class Buffer(metaclass=ABCMeta): + + __slots__ = () + + @abstractmethod + def __buffer__(self, flags: int, /) -> memoryview: + raise NotImplementedError + + @classmethod + def __subclasshook__(cls, C): + if cls is Buffer: + return _check_methods(C, "__buffer__") + return NotImplemented + + +class _CallableGenericAlias(GenericAlias): + """ Represent `Callable[argtypes, resulttype]`. + + This sets ``__args__`` to a tuple containing the flattened ``argtypes`` + followed by ``resulttype``. + + Example: ``Callable[[int, str], float]`` sets ``__args__`` to + ``(int, str, float)``. + """ + + __slots__ = () + + def __new__(cls, origin, args): + if not (isinstance(args, tuple) and len(args) == 2): + raise TypeError( + "Callable must be used as Callable[[arg, ...], result].") + t_args, t_result = args + if isinstance(t_args, (tuple, list)): + args = (*t_args, t_result) + elif not _is_param_expr(t_args): + raise TypeError(f"Expected a list of types, an ellipsis, " + f"ParamSpec, or Concatenate. Got {t_args}") + return super().__new__(cls, origin, args) + + def __repr__(self): + if len(self.__args__) == 2 and _is_param_expr(self.__args__[0]): + return super().__repr__() + return (f'collections.abc.Callable' + f'[[{", ".join([_type_repr(a) for a in self.__args__[:-1]])}], ' + f'{_type_repr(self.__args__[-1])}]') + + def __reduce__(self): + args = self.__args__ + if not (len(args) == 2 and _is_param_expr(args[0])): + args = list(args[:-1]), args[-1] + return _CallableGenericAlias, (Callable, args) + + def __getitem__(self, item): + # Called during TypeVar substitution, returns the custom subclass + # rather than the default types.GenericAlias object. Most of the + # code is copied from typing's _GenericAlias and the builtin + # types.GenericAlias. + if not isinstance(item, tuple): + item = (item,) + + new_args = super().__getitem__(item).__args__ + + # args[0] occurs due to things like Z[[int, str, bool]] from PEP 612 + if not isinstance(new_args[0], (tuple, list)): + t_result = new_args[-1] + t_args = new_args[:-1] + new_args = (t_args, t_result) + return _CallableGenericAlias(Callable, tuple(new_args)) + +def _is_param_expr(obj): + """Checks if obj matches either a list of types, ``...``, ``ParamSpec`` or + ``_ConcatenateGenericAlias`` from typing.py + """ + if obj is Ellipsis: + return True + if isinstance(obj, list): + return True + obj = type(obj) + names = ('ParamSpec', '_ConcatenateGenericAlias') + return obj.__module__ == 'typing' and any(obj.__name__ == name for name in names) + +def _type_repr(obj): + """Return the repr() of an object, special-casing types (internal helper). + + Copied from :mod:`typing` since collections.abc + shouldn't depend on that module. + (Keep this roughly in sync with the typing version.) + """ + if isinstance(obj, type): + if obj.__module__ == 'builtins': + return obj.__qualname__ + return f'{obj.__module__}.{obj.__qualname__}' + if obj is Ellipsis: + return '...' + if isinstance(obj, FunctionType): + return obj.__name__ + return repr(obj) + + +class Callable(metaclass=ABCMeta): + + __slots__ = () + + @abstractmethod + def __call__(self, *args, **kwds): + return False + + @classmethod + def __subclasshook__(cls, C): + if cls is Callable: + return _check_methods(C, "__call__") + return NotImplemented + + __class_getitem__ = classmethod(_CallableGenericAlias) + + +### SETS ### + + +class Set(Collection): + """A set is a finite, iterable container. + + This class provides concrete generic implementations of all + methods except for __contains__, __iter__ and __len__. + + To override the comparisons (presumably for speed, as the + semantics are fixed), redefine __le__ and __ge__, + then the other operations will automatically follow suit. + """ + + __slots__ = () + + def __le__(self, other): + if not isinstance(other, Set): + return NotImplemented + if len(self) > len(other): + return False + for elem in self: + if elem not in other: + return False + return True + + def __lt__(self, other): + if not isinstance(other, Set): + return NotImplemented + return len(self) < len(other) and self.__le__(other) + + def __gt__(self, other): + if not isinstance(other, Set): + return NotImplemented + return len(self) > len(other) and self.__ge__(other) + + def __ge__(self, other): + if not isinstance(other, Set): + return NotImplemented + if len(self) < len(other): + return False + for elem in other: + if elem not in self: + return False + return True + + def __eq__(self, other): + if not isinstance(other, Set): + return NotImplemented + return len(self) == len(other) and self.__le__(other) + + @classmethod + def _from_iterable(cls, it): + '''Construct an instance of the class from any iterable input. + + Must override this method if the class constructor signature + does not accept an iterable for an input. + ''' + return cls(it) + + def __and__(self, other): + if not isinstance(other, Iterable): + return NotImplemented + return self._from_iterable(value for value in other if value in self) + + __rand__ = __and__ + + def isdisjoint(self, other): + 'Return True if two sets have a null intersection.' + for value in other: + if value in self: + return False + return True + + def __or__(self, other): + if not isinstance(other, Iterable): + return NotImplemented + chain = (e for s in (self, other) for e in s) + return self._from_iterable(chain) + + __ror__ = __or__ + + def __sub__(self, other): + if not isinstance(other, Set): + if not isinstance(other, Iterable): + return NotImplemented + other = self._from_iterable(other) + return self._from_iterable(value for value in self + if value not in other) + + def __rsub__(self, other): + if not isinstance(other, Set): + if not isinstance(other, Iterable): + return NotImplemented + other = self._from_iterable(other) + return self._from_iterable(value for value in other + if value not in self) + + def __xor__(self, other): + if not isinstance(other, Set): + if not isinstance(other, Iterable): + return NotImplemented + other = self._from_iterable(other) + return (self - other) | (other - self) + + __rxor__ = __xor__ + + def _hash(self): + """Compute the hash value of a set. + + Note that we don't define __hash__: not all sets are hashable. + But if you define a hashable set type, its __hash__ should + call this function. + + This must be compatible __eq__. + + All sets ought to compare equal if they contain the same + elements, regardless of how they are implemented, and + regardless of the order of the elements; so there's not much + freedom for __eq__ or __hash__. We match the algorithm used + by the built-in frozenset type. + """ + MAX = sys.maxsize + MASK = 2 * MAX + 1 + n = len(self) + h = 1927868237 * (n + 1) + h &= MASK + for x in self: + hx = hash(x) + h ^= (hx ^ (hx << 16) ^ 89869747) * 3644798167 + h &= MASK + h ^= (h >> 11) ^ (h >> 25) + h = h * 69069 + 907133923 + h &= MASK + if h > MAX: + h -= MASK + 1 + if h == -1: + h = 590923713 + return h + + +Set.register(frozenset) + + +class MutableSet(Set): + """A mutable set is a finite, iterable container. + + This class provides concrete generic implementations of all + methods except for __contains__, __iter__, __len__, + add(), and discard(). + + To override the comparisons (presumably for speed, as the + semantics are fixed), all you have to do is redefine __le__ and + then the other operations will automatically follow suit. + """ + + __slots__ = () + + @abstractmethod + def add(self, value): + """Add an element.""" + raise NotImplementedError + + @abstractmethod + def discard(self, value): + """Remove an element. Do not raise an exception if absent.""" + raise NotImplementedError + + def remove(self, value): + """Remove an element. If not a member, raise a KeyError.""" + if value not in self: + raise KeyError(value) + self.discard(value) + + def pop(self): + """Return the popped value. Raise KeyError if empty.""" + it = iter(self) + try: + value = next(it) + except StopIteration: + raise KeyError from None + self.discard(value) + return value + + def clear(self): + """This is slow<|im_end|> +<|im_start|>assistant + + + + +Based on the code provided, here is an analysis and summary of the Python standard library modules included in the snippet. + +### 1. `__future__.py` +**Purpose:** This module records "phased-in incompatible language changes." It allows developers to enable future Python features in current versions using `from __ +--- +info: graphs: 1 captured (9 ms each), 61 of 63 rounds replayed diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/logs/generate-exact-chunk20480.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/logs/generate-exact-chunk20480.log new file mode 100644 index 0000000000..37707efad7 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/logs/generate-exact-chunk20480.log @@ -0,0 +1,1293 @@ +loaded in 23.5 s, 104.93 GiB on the device +prompt 10368 tokens in 18.316 s (566.1 tok/s); 63 tokens in 1.777 s (35.45 tok/s) +logits hash c8f6888043c972e0 +ids { 27775, 383, 279, 1970, 3766, 11, 1532, 369, 449, 6157, 321, 11782, 314, 279, 12654, 5129, 6522, 13067, 5064, 303, 279, 41643, 13, 271, 13962, 220, 16, 13, 1510, 548, 20409, 18162, 3181, 63, 198, 332, 71516, 64700, 1061, 4536, 7189, 328, 734, 1422, 3309, 51047, 3992, 4203, 1149, 1049, 5954, 13015, 310, 7056, 3725, 12654, 4275, 303, 1428, 10478, 1608, 1510, 1445, 1259 } +--- +<|im_start|>user +# file: __future__.py +"""Record of phased-in incompatible language changes. + +Each line is of the form: + + FeatureName = "_Feature(" OptionalRelease "," MandatoryRelease "," + CompilerFlag ")" + +where, normally, OptionalRelease < MandatoryRelease, and both are 5-tuples +of the same form as sys.version_info: + + (PY_MAJOR_VERSION, # the 2 in 2.1.0a3; an int + PY_MINOR_VERSION, # the 1; an int + PY_MICRO_VERSION, # the 0; an int + PY_RELEASE_LEVEL, # "alpha", "beta", "candidate" or "final"; string + PY_RELEASE_SERIAL # the 3; an int + ) + +OptionalRelease records the first release in which + + from __future__ import FeatureName + +was accepted. + +In the case of MandatoryReleases that have not yet occurred, +MandatoryRelease predicts the release in which the feature will become part +of the language. + +Else MandatoryRelease records when the feature became part of the language; +in releases at or after that, modules no longer need + + from __future__ import FeatureName + +to use the feature in question, but may continue to use such imports. + +MandatoryRelease may also be None, meaning that a planned feature got +dropped or that the release version is undetermined. + +Instances of class _Feature have two corresponding methods, +.getOptionalRelease() and .getMandatoryRelease(). + +CompilerFlag is the (bitfield) flag that should be passed in the fourth +argument to the builtin function compile() to enable the feature in +dynamically compiled code. This flag is stored in the .compiler_flag +attribute on _Future instances. These values must match the appropriate +#defines of CO_xxx flags in Include/cpython/compile.h. + +No feature line is ever to be deleted from this file. +""" + +all_feature_names = [ + "nested_scopes", + "generators", + "division", + "absolute_import", + "with_statement", + "print_function", + "unicode_literals", + "barry_as_FLUFL", + "generator_stop", + "annotations", +] + +__all__ = ["all_feature_names"] + all_feature_names + +# The CO_xxx symbols are defined here under the same names defined in +# code.h and used by compile.h, so that an editor search will find them here. +# However, they're not exported in __all__, because they don't really belong to +# this module. +CO_NESTED = 0x0010 # nested_scopes +CO_GENERATOR_ALLOWED = 0 # generators (obsolete, was 0x1000) +CO_FUTURE_DIVISION = 0x20000 # division +CO_FUTURE_ABSOLUTE_IMPORT = 0x40000 # perform absolute imports by default +CO_FUTURE_WITH_STATEMENT = 0x80000 # with statement +CO_FUTURE_PRINT_FUNCTION = 0x100000 # print function +CO_FUTURE_UNICODE_LITERALS = 0x200000 # unicode string literals +CO_FUTURE_BARRY_AS_BDFL = 0x400000 +CO_FUTURE_GENERATOR_STOP = 0x800000 # StopIteration becomes RuntimeError in generators +CO_FUTURE_ANNOTATIONS = 0x1000000 # annotations become strings at runtime + + +class _Feature: + + def __init__(self, optionalRelease, mandatoryRelease, compiler_flag): + self.optional = optionalRelease + self.mandatory = mandatoryRelease + self.compiler_flag = compiler_flag + + def getOptionalRelease(self): + """Return first release in which this feature was recognized. + + This is a 5-tuple, of the same form as sys.version_info. + """ + return self.optional + + def getMandatoryRelease(self): + """Return release in which this feature will become mandatory. + + This is a 5-tuple, of the same form as sys.version_info, or, if + the feature was dropped, or the release date is undetermined, is None. + """ + return self.mandatory + + def __repr__(self): + return "_Feature" + repr((self.optional, + self.mandatory, + self.compiler_flag)) + + +nested_scopes = _Feature((2, 1, 0, "beta", 1), + (2, 2, 0, "alpha", 0), + CO_NESTED) + +generators = _Feature((2, 2, 0, "alpha", 1), + (2, 3, 0, "final", 0), + CO_GENERATOR_ALLOWED) + +division = _Feature((2, 2, 0, "alpha", 2), + (3, 0, 0, "alpha", 0), + CO_FUTURE_DIVISION) + +absolute_import = _Feature((2, 5, 0, "alpha", 1), + (3, 0, 0, "alpha", 0), + CO_FUTURE_ABSOLUTE_IMPORT) + +with_statement = _Feature((2, 5, 0, "alpha", 1), + (2, 6, 0, "alpha", 0), + CO_FUTURE_WITH_STATEMENT) + +print_function = _Feature((2, 6, 0, "alpha", 2), + (3, 0, 0, "alpha", 0), + CO_FUTURE_PRINT_FUNCTION) + +unicode_literals = _Feature((2, 6, 0, "alpha", 2), + (3, 0, 0, "alpha", 0), + CO_FUTURE_UNICODE_LITERALS) + +barry_as_FLUFL = _Feature((3, 1, 0, "alpha", 2), + (4, 0, 0, "alpha", 0), + CO_FUTURE_BARRY_AS_BDFL) + +generator_stop = _Feature((3, 5, 0, "beta", 1), + (3, 7, 0, "alpha", 0), + CO_FUTURE_GENERATOR_STOP) + +annotations = _Feature((3, 7, 0, "beta", 1), + None, + CO_FUTURE_ANNOTATIONS) + +# file: __hello__.py +initialized = True + +class TestFrozenUtf8_1: + """\u00b6""" + +class TestFrozenUtf8_2: + """\u03c0""" + +class TestFrozenUtf8_4: + """\U0001f600""" + +def main(): + print("Hello world!") + +if __name__ == '__main__': + main() + +# file: _aix_support.py +"""Shared AIX support functions.""" + +import sys +import sysconfig + + +# Taken from _osx_support _read_output function +def _read_cmd_output(commandstring, capture_stderr=False): + """Output from successful command execution or None""" + # Similar to os.popen(commandstring, "r").read(), + # but without actually using os.popen because that + # function is not usable during python bootstrap. + import os + import contextlib + fp = open("/tmp/_aix_support.%s"%( + os.getpid(),), "w+b") + + with contextlib.closing(fp) as fp: + if capture_stderr: + cmd = "%s >'%s' 2>&1" % (commandstring, fp.name) + else: + cmd = "%s 2>/dev/null >'%s'" % (commandstring, fp.name) + return fp.read() if not os.system(cmd) else None + + +def _aix_tag(vrtl, bd): + # type: (List[int], int) -> str + # Infer the ABI bitwidth from maxsize (assuming 64 bit as the default) + _sz = 32 if sys.maxsize == (2**31-1) else 64 + _bd = bd if bd != 0 else 9988 + # vrtl[version, release, technology_level] + return "aix-{:1x}{:1d}{:02d}-{:04d}-{}".format(vrtl[0], vrtl[1], vrtl[2], _bd, _sz) + + +# extract version, release and technology level from a VRMF string +def _aix_vrtl(vrmf): + # type: (str) -> List[int] + v, r, tl = vrmf.split(".")[:3] + return [int(v[-1]), int(r), int(tl)] + + +def _aix_bos_rte(): + # type: () -> Tuple[str, int] + """ + Return a Tuple[str, int] e.g., ['7.1.4.34', 1806] + The fileset bos.rte represents the current AIX run-time level. It's VRMF and + builddate reflect the current ABI levels of the runtime environment. + If no builddate is found give a value that will satisfy pep425 related queries + """ + # All AIX systems to have lslpp installed in this location + # subprocess may not be available during python bootstrap + try: + import subprocess + out = subprocess.check_output(["/usr/bin/lslpp", "-Lqc", "bos.rte"]) + except ImportError: + out = _read_cmd_output("/usr/bin/lslpp -Lqc bos.rte") + out = out.decode("utf-8") + out = out.strip().split(":") # type: ignore + _bd = int(out[-1]) if out[-1] != '' else 9988 + return (str(out[2]), _bd) + + +def aix_platform(): + # type: () -> str + """ + AIX filesets are identified by four decimal values: V.R.M.F. + V (version) and R (release) can be retrieved using ``uname`` + Since 2007, starting with AIX 5.3 TL7, the M value has been + included with the fileset bos.rte and represents the Technology + Level (TL) of AIX. The F (Fix) value also increases, but is not + relevant for comparing releases and binary compatibility. + For binary compatibility the so-called builddate is needed. + Again, the builddate of an AIX release is associated with bos.rte. + AIX ABI compatibility is described as guaranteed at: https://www.ibm.com/\ + support/knowledgecenter/en/ssw_aix_72/install/binary_compatability.html + + For pep425 purposes the AIX platform tag becomes: + "aix-{:1x}{:1d}{:02d}-{:04d}-{}".format(v, r, tl, builddate, bitsize) + e.g., "aix-6107-1415-32" for AIX 6.1 TL7 bd 1415, 32-bit + and, "aix-6107-1415-64" for AIX 6.1 TL7 bd 1415, 64-bit + """ + vrmf, bd = _aix_bos_rte() + return _aix_tag(_aix_vrtl(vrmf), bd) + + +# extract vrtl from the BUILD_GNU_TYPE as an int +def _aix_bgt(): + # type: () -> List[int] + gnu_type = sysconfig.get_config_var("BUILD_GNU_TYPE") + if not gnu_type: + raise ValueError("BUILD_GNU_TYPE is not defined") + return _aix_vrtl(vrmf=gnu_type) + + +def aix_buildtag(): + # type: () -> str + """ + Return the platform_tag of the system Python was built on. + """ + # AIX_BUILDDATE is defined by configure with: + # lslpp -Lcq bos.rte | awk -F: '{ print $NF }' + build_date = sysconfig.get_config_var("AIX_BUILDDATE") + try: + build_date = int(build_date) + except (ValueError, TypeError): + raise ValueError(f"AIX_BUILDDATE is not defined or invalid: " + f"{build_date!r}") + return _aix_tag(_aix_bgt(), build_date) + +# file: _android_support.py +import io +import sys +from threading import RLock +from time import sleep, time + +# The maximum length of a log message in bytes, including the level marker and +# tag, is defined as LOGGER_ENTRY_MAX_PAYLOAD at +# https://cs.android.com/android/platform/superproject/+/android-14.0.0_r1:system/logging/liblog/include/log/log.h;l=71. +# Messages longer than this will be truncated by logcat. This limit has already +# been reduced at least once in the history of Android (from 4076 to 4068 between +# API level 23 and 26), so leave some headroom. +MAX_BYTES_PER_WRITE = 4000 + +# UTF-8 uses a maximum of 4 bytes per character, so limiting text writes to this +# size ensures that we can always avoid exceeding MAX_BYTES_PER_WRITE. +# However, if the actual number of bytes per character is smaller than that, +# then we may still join multiple consecutive text writes into binary +# writes containing a larger number of characters. +MAX_CHARS_PER_WRITE = MAX_BYTES_PER_WRITE // 4 + + +# When embedded in an app on current versions of Android, there's no easy way to +# monitor the C-level stdout and stderr. The testbed comes with a .c file to +# redirect them to the system log using a pipe, but that wouldn't be convenient +# or appropriate for all apps. So we redirect at the Python level instead. +def init_streams(android_log_write, stdout_prio, stderr_prio): + if sys.executable: + return # Not embedded in an app. + + global logcat + logcat = Logcat(android_log_write) + + sys.stdout = TextLogStream( + stdout_prio, "python.stdout", sys.stdout.fileno()) + sys.stderr = TextLogStream( + stderr_prio, "python.stderr", sys.stderr.fileno()) + + +class TextLogStream(io.TextIOWrapper): + def __init__(self, prio, tag, fileno=None, **kwargs): + # The default is surrogateescape for stdout and backslashreplace for + # stderr, but in the context of an Android log, readability is more + # important than reversibility. + kwargs.setdefault("encoding", "UTF-8") + kwargs.setdefault("errors", "backslashreplace") + + super().__init__(BinaryLogStream(prio, tag, fileno), **kwargs) + self._lock = RLock() + self._pending_bytes = [] + self._pending_bytes_count = 0 + + def __repr__(self): + return f"" + + def write(self, s): + if not isinstance(s, str): + raise TypeError( + f"write() argument must be str, not {type(s).__name__}") + + # In case `s` is a str subclass that writes itself to stdout or stderr + # when we call its methods, convert it to an actual str. + s = str.__str__(s) + + # We want to emit one log message per line wherever possible, so split + # the string into lines first. Note that "".splitlines() == [], so + # nothing will be logged for an empty string. + with self._lock: + for line in s.splitlines(keepends=True): + while line: + chunk = line[:MAX_CHARS_PER_WRITE] + line = line[MAX_CHARS_PER_WRITE:] + self._write_chunk(chunk) + + return len(s) + + # The size and behavior of TextIOWrapper's buffer is not part of its public + # API, so we handle buffering ourselves to avoid truncation. + def _write_chunk(self, s): + b = s.encode(self.encoding, self.errors) + if self._pending_bytes_count + len(b) > MAX_BYTES_PER_WRITE: + self.flush() + + self._pending_bytes.append(b) + self._pending_bytes_count += len(b) + if ( + self.write_through + or b.endswith(b"\n") + or self._pending_bytes_count > MAX_BYTES_PER_WRITE + ): + self.flush() + + def flush(self): + with self._lock: + self.buffer.write(b"".join(self._pending_bytes)) + self._pending_bytes.clear() + self._pending_bytes_count = 0 + + # Since this is a line-based logging system, line buffering cannot be turned + # off, i.e. a newline always causes a flush. + @property + def line_buffering(self): + return True + + +class BinaryLogStream(io.RawIOBase): + def __init__(self, prio, tag, fileno=None): + self.prio = prio + self.tag = tag + self._fileno = fileno + + def __repr__(self): + return f"" + + def writable(self): + return True + + def write(self, b): + if type(b) is not bytes: + try: + b = bytes(memoryview(b)) + except TypeError: + raise TypeError( + f"write() argument must be bytes-like, not {type(b).__name__}" + ) from None + + # Writing an empty string to the stream should have no effect. + if b: + logcat.write(self.prio, self.tag, b) + return len(b) + + # This is needed by the test suite --timeout option, which uses faulthandler. + def fileno(self): + if self._fileno is None: + raise io.UnsupportedOperation("fileno") + return self._fileno + + +# When a large volume of data is written to logcat at once, e.g. when a test +# module fails in --verbose3 mode, there's a risk of overflowing logcat's own +# buffer and losing messages. We avoid this by imposing a rate limit using the +# token bucket algorithm, based on a conservative estimate of how fast `adb +# logcat` can consume data. +MAX_BYTES_PER_SECOND = 1024 * 1024 + +# The logcat buffer size of a device can be determined by running `logcat -g`. +# We set the token bucket size to half of the buffer size of our current minimum +# API level, because other things on the system will be producing messages as +# well. +BUCKET_SIZE = 128 * 1024 + +# https://cs.android.com/android/platform/superproject/+/android-14.0.0_r1:system/logging/liblog/include/log/log_read.h;l=39 +PER_MESSAGE_OVERHEAD = 28 + + +class Logcat: + def __init__(self, android_log_write): + self.android_log_write = android_log_write + self._lock = RLock() + self._bucket_level = 0 + self._prev_write_time = time() + + def write(self, prio, tag, message): + # Encode null bytes using "modified UTF-8" to avoid them truncating the + # message. + message = message.replace(b"\x00", b"\xc0\x80") + + with self._lock: + now = time() + self._bucket_level += ( + (now - self._prev_write_time) * MAX_BYTES_PER_SECOND) + + # If the bucket level is still below zero, the clock must have gone + # backwards, so reset it to zero and continue. + self._bucket_level = max(0, min(self._bucket_level, BUCKET_SIZE)) + self._prev_write_time = now + + self._bucket_level -= PER_MESSAGE_OVERHEAD + len(tag) + len(message) + if self._bucket_level < 0: + sleep(-self._bucket_level / MAX_BYTES_PER_SECOND) + + self.android_log_write(prio, tag, message) + +# file: _apple_support.py +import io +import sys + + +def init_streams(log_write, stdout_level, stderr_level): + # Redirect stdout and stderr to the Apple system log. This method is + # invoked by init_apple_streams() (initconfig.c) if config->use_system_logger + # is enabled. + sys.stdout = SystemLog(log_write, stdout_level, errors=sys.stderr.errors) + sys.stderr = SystemLog(log_write, stderr_level, errors=sys.stderr.errors) + + +class SystemLog(io.TextIOWrapper): + def __init__(self, log_write, level, **kwargs): + kwargs.setdefault("encoding", "UTF-8") + kwargs.setdefault("line_buffering", True) + super().__init__(LogStream(log_write, level), **kwargs) + + def __repr__(self): + return f"" + + def write(self, s): + if not isinstance(s, str): + raise TypeError( + f"write() argument must be str, not {type(s).__name__}") + + # In case `s` is a str subclass that writes itself to stdout or stderr + # when we call its methods, convert it to an actual str. + s = str.__str__(s) + + # We want to emit one log message per line, so split + # the string before sending it to the superclass. + for line in s.splitlines(keepends=True): + super().write(line) + + return len(s) + + +class LogStream(io.RawIOBase): + def __init__(self, log_write, level): + self.log_write = log_write + self.level = level + + def __repr__(self): + return f"" + + def writable(self): + return True + + def write(self, b): + if type(b) is not bytes: + try: + b = bytes(memoryview(b)) + except TypeError: + raise TypeError( + f"write() argument must be bytes-like, not {type(b).__name__}" + ) from None + + # Writing an empty string to the stream should have no effect. + if b: + # Encode null bytes using "modified UTF-8" to avoid truncating the + # message. This should not affect the return value, as the caller + # may be expecting it to match the length of the input. + self.log_write(self.level, b.replace(b"\x00", b"\xc0\x80")) + + return len(b) + +# file: _collections_abc.py +# Copyright 2007 Google, Inc. All Rights Reserved. +# Licensed to PSF under a Contributor Agreement. + +"""Abstract Base Classes (ABCs) for collections, according to PEP 3119. + +Unit tests are in test_collections. +""" + +############ Maintenance notes ######################################### +# +# ABCs are different from other standard library modules in that they +# specify compliance tests. In general, once an ABC has been published, +# new methods (either abstract or concrete) cannot be added. +# +# Though classes that inherit from an ABC would automatically receive a +# new mixin method, registered classes would become non-compliant and +# violate the contract promised by ``isinstance(someobj, SomeABC)``. +# +# Though irritating, the correct procedure for adding new abstract or +# mixin methods is to create a new ABC as a subclass of the previous +# ABC. For example, union(), intersection(), and difference() cannot +# be added to Set but could go into a new ABC that extends Set. +# +# Because they are so hard to change, new ABCs should have their APIs +# carefully thought through prior to publication. +# +# Since ABCMeta only checks for the presence of methods, it is possible +# to alter the signature of a method by adding optional arguments +# or changing parameters names. This is still a bit dubious but at +# least it won't cause isinstance() to return an incorrect result. +# +# +####################################################################### + +from abc import ABCMeta, abstractmethod +import sys + +GenericAlias = type(list[int]) +EllipsisType = type(...) +def _f(): pass +FunctionType = type(_f) +del _f + +__all__ = ["Awaitable", "Coroutine", + "AsyncIterable", "AsyncIterator", "AsyncGenerator", + "Hashable", "Iterable", "Iterator", "Generator", "Reversible", + "Sized", "Container", "Callable", "Collection", + "Set", "MutableSet", + "Mapping", "MutableMapping", + "MappingView", "KeysView", "ItemsView", "ValuesView", + "Sequence", "MutableSequence", + "ByteString", "Buffer", + ] + +# This module has been renamed from collections.abc to _collections_abc to +# speed up interpreter startup. Some of the types such as MutableMapping are +# required early but collections module imports a lot of other modules. +# See issue #19218 +__name__ = "collections.abc" + +# Private list of types that we want to register with the various ABCs +# so that they will pass tests like: +# it = iter(somebytearray) +# assert isinstance(it, Iterable) +# Note: in other implementations, these types might not be distinct +# and they may have their own implementation specific types that +# are not included on this list. +bytes_iterator = type(iter(b'')) +bytearray_iterator = type(iter(bytearray())) +#callable_iterator = ??? +dict_keyiterator = type(iter({}.keys())) +dict_valueiterator = type(iter({}.values())) +dict_itemiterator = type(iter({}.items())) +list_iterator = type(iter([])) +list_reverseiterator = type(iter(reversed([]))) +range_iterator = type(iter(range(0))) +longrange_iterator = type(iter(range(1 << 1000))) +set_iterator = type(iter(set())) +str_iterator = type(iter("")) +tuple_iterator = type(iter(())) +zip_iterator = type(iter(zip())) +## views ## +dict_keys = type({}.keys()) +dict_values = type({}.values()) +dict_items = type({}.items()) +## misc ## +mappingproxy = type(type.__dict__) +def _get_framelocalsproxy(): + return type(sys._getframe().f_locals) +framelocalsproxy = _get_framelocalsproxy() +del _get_framelocalsproxy +generator = type((lambda: (yield))()) +## coroutine ## +async def _coro(): pass +_coro = _coro() +coroutine = type(_coro) +_coro.close() # Prevent ResourceWarning +del _coro +## asynchronous generator ## +async def _ag(): yield +_ag = _ag() +async_generator = type(_ag) +del _ag + + +### ONE-TRICK PONIES ### + +def _check_methods(C, *methods): + mro = C.__mro__ + for method in methods: + for B in mro: + if method in B.__dict__: + if B.__dict__[method] is None: + return NotImplemented + break + else: + return NotImplemented + return True + +class Hashable(metaclass=ABCMeta): + + __slots__ = () + + @abstractmethod + def __hash__(self): + return 0 + + @classmethod + def __subclasshook__(cls, C): + if cls is Hashable: + return _check_methods(C, "__hash__") + return NotImplemented + + +class Awaitable(metaclass=ABCMeta): + + __slots__ = () + + @abstractmethod + def __await__(self): + yield + + @classmethod + def __subclasshook__(cls, C): + if cls is Awaitable: + return _check_methods(C, "__await__") + return NotImplemented + + __class_getitem__ = classmethod(GenericAlias) + + +class Coroutine(Awaitable): + + __slots__ = () + + @abstractmethod + def send(self, value): + """Send a value into the coroutine. + Return next yielded value or raise StopIteration. + """ + raise StopIteration + + @abstractmethod + def throw(self, typ, val=None, tb=None): + """Raise an exception in the coroutine. + Return next yielded value or raise StopIteration. + """ + if val is None: + if tb is None: + raise typ + val = typ() + if tb is not None: + val = val.with_traceback(tb) + raise val + + def close(self): + """Raise GeneratorExit inside coroutine. + """ + try: + self.throw(GeneratorExit) + except (GeneratorExit, StopIteration): + pass + else: + raise RuntimeError("coroutine ignored GeneratorExit") + + @classmethod + def __subclasshook__(cls, C): + if cls is Coroutine: + return _check_methods(C, '__await__', 'send', 'throw', 'close') + return NotImplemented + + +Coroutine.register(coroutine) + + +class AsyncIterable(metaclass=ABCMeta): + + __slots__ = () + + @abstractmethod + def __aiter__(self): + return AsyncIterator() + + @classmethod + def __subclasshook__(cls, C): + if cls is AsyncIterable: + return _check_methods(C, "__aiter__") + return NotImplemented + + __class_getitem__ = classmethod(GenericAlias) + + +class AsyncIterator(AsyncIterable): + + __slots__ = () + + @abstractmethod + async def __anext__(self): + """Return the next item or raise StopAsyncIteration when exhausted.""" + raise StopAsyncIteration + + def __aiter__(self): + return self + + @classmethod + def __subclasshook__(cls, C): + if cls is AsyncIterator: + return _check_methods(C, "__anext__", "__aiter__") + return NotImplemented + + +class AsyncGenerator(AsyncIterator): + + __slots__ = () + + async def __anext__(self): + """Return the next item from the asynchronous generator. + When exhausted, raise StopAsyncIteration. + """ + return await self.asend(None) + + @abstractmethod + async def asend(self, value): + """Send a value into the asynchronous generator. + Return next yielded value or raise StopAsyncIteration. + """ + raise StopAsyncIteration + + @abstractmethod + async def athrow(self, typ, val=None, tb=None): + """Raise an exception in the asynchronous generator. + Return next yielded value or raise StopAsyncIteration. + """ + if val is None: + if tb is None: + raise typ + val = typ() + if tb is not None: + val = val.with_traceback(tb) + raise val + + async def aclose(self): + """Raise GeneratorExit inside coroutine. + """ + try: + await self.athrow(GeneratorExit) + except (GeneratorExit, StopAsyncIteration): + pass + else: + raise RuntimeError("asynchronous generator ignored GeneratorExit") + + @classmethod + def __subclasshook__(cls, C): + if cls is AsyncGenerator: + return _check_methods(C, '__aiter__', '__anext__', + 'asend', 'athrow', 'aclose') + return NotImplemented + + +AsyncGenerator.register(async_generator) + + +class Iterable(metaclass=ABCMeta): + + __slots__ = () + + @abstractmethod + def __iter__(self): + while False: + yield None + + @classmethod + def __subclasshook__(cls, C): + if cls is Iterable: + return _check_methods(C, "__iter__") + return NotImplemented + + __class_getitem__ = classmethod(GenericAlias) + + +class Iterator(Iterable): + + __slots__ = () + + @abstractmethod + def __next__(self): + 'Return the next item from the iterator. When exhausted, raise StopIteration' + raise StopIteration + + def __iter__(self): + return self + + @classmethod + def __subclasshook__(cls, C): + if cls is Iterator: + return _check_methods(C, '__iter__', '__next__') + return NotImplemented + + +Iterator.register(bytes_iterator) +Iterator.register(bytearray_iterator) +#Iterator.register(callable_iterator) +Iterator.register(dict_keyiterator) +Iterator.register(dict_valueiterator) +Iterator.register(dict_itemiterator) +Iterator.register(list_iterator) +Iterator.register(list_reverseiterator) +Iterator.register(range_iterator) +Iterator.register(longrange_iterator) +Iterator.register(set_iterator) +Iterator.register(str_iterator) +Iterator.register(tuple_iterator) +Iterator.register(zip_iterator) + + +class Reversible(Iterable): + + __slots__ = () + + @abstractmethod + def __reversed__(self): + while False: + yield None + + @classmethod + def __subclasshook__(cls, C): + if cls is Reversible: + return _check_methods(C, "__reversed__", "__iter__") + return NotImplemented + + +class Generator(Iterator): + + __slots__ = () + + def __next__(self): + """Return the next item from the generator. + When exhausted, raise StopIteration. + """ + return self.send(None) + + @abstractmethod + def send(self, value): + """Send a value into the generator. + Return next yielded value or raise StopIteration. + """ + raise StopIteration + + @abstractmethod + def throw(self, typ, val=None, tb=None): + """Raise an exception in the generator. + Return next yielded value or raise StopIteration. + """ + if val is None: + if tb is None: + raise typ + val = typ() + if tb is not None: + val = val.with_traceback(tb) + raise val + + def close(self): + """Raise GeneratorExit inside generator. + """ + try: + self.throw(GeneratorExit) + except (GeneratorExit, StopIteration): + pass + else: + raise RuntimeError("generator ignored GeneratorExit") + + @classmethod + def __subclasshook__(cls, C): + if cls is Generator: + return _check_methods(C, '__iter__', '__next__', + 'send', 'throw', 'close') + return NotImplemented + + +Generator.register(generator) + + +class Sized(metaclass=ABCMeta): + + __slots__ = () + + @abstractmethod + def __len__(self): + return 0 + + @classmethod + def __subclasshook__(cls, C): + if cls is Sized: + return _check_methods(C, "__len__") + return NotImplemented + + +class Container(metaclass=ABCMeta): + + __slots__ = () + + @abstractmethod + def __contains__(self, x): + return False + + @classmethod + def __subclasshook__(cls, C): + if cls is Container: + return _check_methods(C, "__contains__") + return NotImplemented + + __class_getitem__ = classmethod(GenericAlias) + + +class Collection(Sized, Iterable, Container): + + __slots__ = () + + @classmethod + def __subclasshook__(cls, C): + if cls is Collection: + return _check_methods(C, "__len__", "__iter__", "__contains__") + return NotImplemented + + +class Buffer(metaclass=ABCMeta): + + __slots__ = () + + @abstractmethod + def __buffer__(self, flags: int, /) -> memoryview: + raise NotImplementedError + + @classmethod + def __subclasshook__(cls, C): + if cls is Buffer: + return _check_methods(C, "__buffer__") + return NotImplemented + + +class _CallableGenericAlias(GenericAlias): + """ Represent `Callable[argtypes, resulttype]`. + + This sets ``__args__`` to a tuple containing the flattened ``argtypes`` + followed by ``resulttype``. + + Example: ``Callable[[int, str], float]`` sets ``__args__`` to + ``(int, str, float)``. + """ + + __slots__ = () + + def __new__(cls, origin, args): + if not (isinstance(args, tuple) and len(args) == 2): + raise TypeError( + "Callable must be used as Callable[[arg, ...], result].") + t_args, t_result = args + if isinstance(t_args, (tuple, list)): + args = (*t_args, t_result) + elif not _is_param_expr(t_args): + raise TypeError(f"Expected a list of types, an ellipsis, " + f"ParamSpec, or Concatenate. Got {t_args}") + return super().__new__(cls, origin, args) + + def __repr__(self): + if len(self.__args__) == 2 and _is_param_expr(self.__args__[0]): + return super().__repr__() + return (f'collections.abc.Callable' + f'[[{", ".join([_type_repr(a) for a in self.__args__[:-1]])}], ' + f'{_type_repr(self.__args__[-1])}]') + + def __reduce__(self): + args = self.__args__ + if not (len(args) == 2 and _is_param_expr(args[0])): + args = list(args[:-1]), args[-1] + return _CallableGenericAlias, (Callable, args) + + def __getitem__(self, item): + # Called during TypeVar substitution, returns the custom subclass + # rather than the default types.GenericAlias object. Most of the + # code is copied from typing's _GenericAlias and the builtin + # types.GenericAlias. + if not isinstance(item, tuple): + item = (item,) + + new_args = super().__getitem__(item).__args__ + + # args[0] occurs due to things like Z[[int, str, bool]] from PEP 612 + if not isinstance(new_args[0], (tuple, list)): + t_result = new_args[-1] + t_args = new_args[:-1] + new_args = (t_args, t_result) + return _CallableGenericAlias(Callable, tuple(new_args)) + +def _is_param_expr(obj): + """Checks if obj matches either a list of types, ``...``, ``ParamSpec`` or + ``_ConcatenateGenericAlias`` from typing.py + """ + if obj is Ellipsis: + return True + if isinstance(obj, list): + return True + obj = type(obj) + names = ('ParamSpec', '_ConcatenateGenericAlias') + return obj.__module__ == 'typing' and any(obj.__name__ == name for name in names) + +def _type_repr(obj): + """Return the repr() of an object, special-casing types (internal helper). + + Copied from :mod:`typing` since collections.abc + shouldn't depend on that module. + (Keep this roughly in sync with the typing version.) + """ + if isinstance(obj, type): + if obj.__module__ == 'builtins': + return obj.__qualname__ + return f'{obj.__module__}.{obj.__qualname__}' + if obj is Ellipsis: + return '...' + if isinstance(obj, FunctionType): + return obj.__name__ + return repr(obj) + + +class Callable(metaclass=ABCMeta): + + __slots__ = () + + @abstractmethod + def __call__(self, *args, **kwds): + return False + + @classmethod + def __subclasshook__(cls, C): + if cls is Callable: + return _check_methods(C, "__call__") + return NotImplemented + + __class_getitem__ = classmethod(_CallableGenericAlias) + + +### SETS ### + + +class Set(Collection): + """A set is a finite, iterable container. + + This class provides concrete generic implementations of all + methods except for __contains__, __iter__ and __len__. + + To override the comparisons (presumably for speed, as the + semantics are fixed), redefine __le__ and __ge__, + then the other operations will automatically follow suit. + """ + + __slots__ = () + + def __le__(self, other): + if not isinstance(other, Set): + return NotImplemented + if len(self) > len(other): + return False + for elem in self: + if elem not in other: + return False + return True + + def __lt__(self, other): + if not isinstance(other, Set): + return NotImplemented + return len(self) < len(other) and self.__le__(other) + + def __gt__(self, other): + if not isinstance(other, Set): + return NotImplemented + return len(self) > len(other) and self.__ge__(other) + + def __ge__(self, other): + if not isinstance(other, Set): + return NotImplemented + if len(self) < len(other): + return False + for elem in other: + if elem not in self: + return False + return True + + def __eq__(self, other): + if not isinstance(other, Set): + return NotImplemented + return len(self) == len(other) and self.__le__(other) + + @classmethod + def _from_iterable(cls, it): + '''Construct an instance of the class from any iterable input. + + Must override this method if the class constructor signature + does not accept an iterable for an input. + ''' + return cls(it) + + def __and__(self, other): + if not isinstance(other, Iterable): + return NotImplemented + return self._from_iterable(value for value in other if value in self) + + __rand__ = __and__ + + def isdisjoint(self, other): + 'Return True if two sets have a null intersection.' + for value in other: + if value in self: + return False + return True + + def __or__(self, other): + if not isinstance(other, Iterable): + return NotImplemented + chain = (e for s in (self, other) for e in s) + return self._from_iterable(chain) + + __ror__ = __or__ + + def __sub__(self, other): + if not isinstance(other, Set): + if not isinstance(other, Iterable): + return NotImplemented + other = self._from_iterable(other) + return self._from_iterable(value for value in self + if value not in other) + + def __rsub__(self, other): + if not isinstance(other, Set): + if not isinstance(other, Iterable): + return NotImplemented + other = self._from_iterable(other) + return self._from_iterable(value for value in other + if value not in self) + + def __xor__(self, other): + if not isinstance(other, Set): + if not isinstance(other, Iterable): + return NotImplemented + other = self._from_iterable(other) + return (self - other) | (other - self) + + __rxor__ = __xor__ + + def _hash(self): + """Compute the hash value of a set. + + Note that we don't define __hash__: not all sets are hashable. + But if you define a hashable set type, its __hash__ should + call this function. + + This must be compatible __eq__. + + All sets ought to compare equal if they contain the same + elements, regardless of how they are implemented, and + regardless of the order of the elements; so there's not much + freedom for __eq__ or __hash__. We match the algorithm used + by the built-in frozenset type. + """ + MAX = sys.maxsize + MASK = 2 * MAX + 1 + n = len(self) + h = 1927868237 * (n + 1) + h &= MASK + for x in self: + hx = hash(x) + h ^= (hx ^ (hx << 16) ^ 89869747) * 3644798167 + h &= MASK + h ^= (h >> 11) ^ (h >> 25) + h = h * 69069 + 907133923 + h &= MASK + if h > MAX: + h -= MASK + 1 + if h == -1: + h = 590923713 + return h + + +Set.register(frozenset) + + +class MutableSet(Set): + """A mutable set is a finite, iterable container. + + This class provides concrete generic implementations of all + methods except for __contains__, __iter__, __len__, + add(), and discard(). + + To override the comparisons (presumably for speed, as the + semantics are fixed), all you have to do is redefine __le__ and + then the other operations will automatically follow suit. + """ + + __slots__ = () + + @abstractmethod + def add(self, value): + """Add an element.""" + raise NotImplementedError + + @abstractmethod + def discard(self, value): + """Remove an element. Do not raise an exception if absent.""" + raise NotImplementedError + + def remove(self, value): + """Remove an element. If not a member, raise a KeyError.""" + if value not in self: + raise KeyError(value) + self.discard(value) + + def pop(self): + """Return the popped value. Raise KeyError if empty.""" + it = iter(self) + try: + value = next(it) + except StopIteration: + raise KeyError from None + self.discard(value) + return value + + def clear(self): + """This is slow<|im_end|> +<|im_start|>assistant + + + + +Based on the code provided, here is an analysis and summary of the Python standard library modules included in the snippet. + +### 1. `__future__.py` +**Purpose:** This module records "phased-in incompatible language changes." It allows developers to enable future Python features in current versions using `from __ +--- +info: graphs: 1 captured (9 ms each), 61 of 63 rounds replayed diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/logs/generate-exact-chunk512.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/logs/generate-exact-chunk512.log new file mode 100644 index 0000000000..f95b076167 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/logs/generate-exact-chunk512.log @@ -0,0 +1,1293 @@ +loaded in 20.9 s, 75.92 GiB on the device +prompt 10368 tokens in 22.995 s (450.9 tok/s); 63 tokens in 1.778 s (35.43 tok/s) +logits hash c8f6888043c972e0 +ids { 27775, 383, 279, 1970, 3766, 11, 1532, 369, 449, 6157, 321, 11782, 314, 279, 12654, 5129, 6522, 13067, 5064, 303, 279, 41643, 13, 271, 13962, 220, 16, 13, 1510, 548, 20409, 18162, 3181, 63, 198, 332, 71516, 64700, 1061, 4536, 7189, 328, 734, 1422, 3309, 51047, 3992, 4203, 1149, 1049, 5954, 13015, 310, 7056, 3725, 12654, 4275, 303, 1428, 10478, 1608, 1510, 1445, 1259 } +--- +<|im_start|>user +# file: __future__.py +"""Record of phased-in incompatible language changes. + +Each line is of the form: + + FeatureName = "_Feature(" OptionalRelease "," MandatoryRelease "," + CompilerFlag ")" + +where, normally, OptionalRelease < MandatoryRelease, and both are 5-tuples +of the same form as sys.version_info: + + (PY_MAJOR_VERSION, # the 2 in 2.1.0a3; an int + PY_MINOR_VERSION, # the 1; an int + PY_MICRO_VERSION, # the 0; an int + PY_RELEASE_LEVEL, # "alpha", "beta", "candidate" or "final"; string + PY_RELEASE_SERIAL # the 3; an int + ) + +OptionalRelease records the first release in which + + from __future__ import FeatureName + +was accepted. + +In the case of MandatoryReleases that have not yet occurred, +MandatoryRelease predicts the release in which the feature will become part +of the language. + +Else MandatoryRelease records when the feature became part of the language; +in releases at or after that, modules no longer need + + from __future__ import FeatureName + +to use the feature in question, but may continue to use such imports. + +MandatoryRelease may also be None, meaning that a planned feature got +dropped or that the release version is undetermined. + +Instances of class _Feature have two corresponding methods, +.getOptionalRelease() and .getMandatoryRelease(). + +CompilerFlag is the (bitfield) flag that should be passed in the fourth +argument to the builtin function compile() to enable the feature in +dynamically compiled code. This flag is stored in the .compiler_flag +attribute on _Future instances. These values must match the appropriate +#defines of CO_xxx flags in Include/cpython/compile.h. + +No feature line is ever to be deleted from this file. +""" + +all_feature_names = [ + "nested_scopes", + "generators", + "division", + "absolute_import", + "with_statement", + "print_function", + "unicode_literals", + "barry_as_FLUFL", + "generator_stop", + "annotations", +] + +__all__ = ["all_feature_names"] + all_feature_names + +# The CO_xxx symbols are defined here under the same names defined in +# code.h and used by compile.h, so that an editor search will find them here. +# However, they're not exported in __all__, because they don't really belong to +# this module. +CO_NESTED = 0x0010 # nested_scopes +CO_GENERATOR_ALLOWED = 0 # generators (obsolete, was 0x1000) +CO_FUTURE_DIVISION = 0x20000 # division +CO_FUTURE_ABSOLUTE_IMPORT = 0x40000 # perform absolute imports by default +CO_FUTURE_WITH_STATEMENT = 0x80000 # with statement +CO_FUTURE_PRINT_FUNCTION = 0x100000 # print function +CO_FUTURE_UNICODE_LITERALS = 0x200000 # unicode string literals +CO_FUTURE_BARRY_AS_BDFL = 0x400000 +CO_FUTURE_GENERATOR_STOP = 0x800000 # StopIteration becomes RuntimeError in generators +CO_FUTURE_ANNOTATIONS = 0x1000000 # annotations become strings at runtime + + +class _Feature: + + def __init__(self, optionalRelease, mandatoryRelease, compiler_flag): + self.optional = optionalRelease + self.mandatory = mandatoryRelease + self.compiler_flag = compiler_flag + + def getOptionalRelease(self): + """Return first release in which this feature was recognized. + + This is a 5-tuple, of the same form as sys.version_info. + """ + return self.optional + + def getMandatoryRelease(self): + """Return release in which this feature will become mandatory. + + This is a 5-tuple, of the same form as sys.version_info, or, if + the feature was dropped, or the release date is undetermined, is None. + """ + return self.mandatory + + def __repr__(self): + return "_Feature" + repr((self.optional, + self.mandatory, + self.compiler_flag)) + + +nested_scopes = _Feature((2, 1, 0, "beta", 1), + (2, 2, 0, "alpha", 0), + CO_NESTED) + +generators = _Feature((2, 2, 0, "alpha", 1), + (2, 3, 0, "final", 0), + CO_GENERATOR_ALLOWED) + +division = _Feature((2, 2, 0, "alpha", 2), + (3, 0, 0, "alpha", 0), + CO_FUTURE_DIVISION) + +absolute_import = _Feature((2, 5, 0, "alpha", 1), + (3, 0, 0, "alpha", 0), + CO_FUTURE_ABSOLUTE_IMPORT) + +with_statement = _Feature((2, 5, 0, "alpha", 1), + (2, 6, 0, "alpha", 0), + CO_FUTURE_WITH_STATEMENT) + +print_function = _Feature((2, 6, 0, "alpha", 2), + (3, 0, 0, "alpha", 0), + CO_FUTURE_PRINT_FUNCTION) + +unicode_literals = _Feature((2, 6, 0, "alpha", 2), + (3, 0, 0, "alpha", 0), + CO_FUTURE_UNICODE_LITERALS) + +barry_as_FLUFL = _Feature((3, 1, 0, "alpha", 2), + (4, 0, 0, "alpha", 0), + CO_FUTURE_BARRY_AS_BDFL) + +generator_stop = _Feature((3, 5, 0, "beta", 1), + (3, 7, 0, "alpha", 0), + CO_FUTURE_GENERATOR_STOP) + +annotations = _Feature((3, 7, 0, "beta", 1), + None, + CO_FUTURE_ANNOTATIONS) + +# file: __hello__.py +initialized = True + +class TestFrozenUtf8_1: + """\u00b6""" + +class TestFrozenUtf8_2: + """\u03c0""" + +class TestFrozenUtf8_4: + """\U0001f600""" + +def main(): + print("Hello world!") + +if __name__ == '__main__': + main() + +# file: _aix_support.py +"""Shared AIX support functions.""" + +import sys +import sysconfig + + +# Taken from _osx_support _read_output function +def _read_cmd_output(commandstring, capture_stderr=False): + """Output from successful command execution or None""" + # Similar to os.popen(commandstring, "r").read(), + # but without actually using os.popen because that + # function is not usable during python bootstrap. + import os + import contextlib + fp = open("/tmp/_aix_support.%s"%( + os.getpid(),), "w+b") + + with contextlib.closing(fp) as fp: + if capture_stderr: + cmd = "%s >'%s' 2>&1" % (commandstring, fp.name) + else: + cmd = "%s 2>/dev/null >'%s'" % (commandstring, fp.name) + return fp.read() if not os.system(cmd) else None + + +def _aix_tag(vrtl, bd): + # type: (List[int], int) -> str + # Infer the ABI bitwidth from maxsize (assuming 64 bit as the default) + _sz = 32 if sys.maxsize == (2**31-1) else 64 + _bd = bd if bd != 0 else 9988 + # vrtl[version, release, technology_level] + return "aix-{:1x}{:1d}{:02d}-{:04d}-{}".format(vrtl[0], vrtl[1], vrtl[2], _bd, _sz) + + +# extract version, release and technology level from a VRMF string +def _aix_vrtl(vrmf): + # type: (str) -> List[int] + v, r, tl = vrmf.split(".")[:3] + return [int(v[-1]), int(r), int(tl)] + + +def _aix_bos_rte(): + # type: () -> Tuple[str, int] + """ + Return a Tuple[str, int] e.g., ['7.1.4.34', 1806] + The fileset bos.rte represents the current AIX run-time level. It's VRMF and + builddate reflect the current ABI levels of the runtime environment. + If no builddate is found give a value that will satisfy pep425 related queries + """ + # All AIX systems to have lslpp installed in this location + # subprocess may not be available during python bootstrap + try: + import subprocess + out = subprocess.check_output(["/usr/bin/lslpp", "-Lqc", "bos.rte"]) + except ImportError: + out = _read_cmd_output("/usr/bin/lslpp -Lqc bos.rte") + out = out.decode("utf-8") + out = out.strip().split(":") # type: ignore + _bd = int(out[-1]) if out[-1] != '' else 9988 + return (str(out[2]), _bd) + + +def aix_platform(): + # type: () -> str + """ + AIX filesets are identified by four decimal values: V.R.M.F. + V (version) and R (release) can be retrieved using ``uname`` + Since 2007, starting with AIX 5.3 TL7, the M value has been + included with the fileset bos.rte and represents the Technology + Level (TL) of AIX. The F (Fix) value also increases, but is not + relevant for comparing releases and binary compatibility. + For binary compatibility the so-called builddate is needed. + Again, the builddate of an AIX release is associated with bos.rte. + AIX ABI compatibility is described as guaranteed at: https://www.ibm.com/\ + support/knowledgecenter/en/ssw_aix_72/install/binary_compatability.html + + For pep425 purposes the AIX platform tag becomes: + "aix-{:1x}{:1d}{:02d}-{:04d}-{}".format(v, r, tl, builddate, bitsize) + e.g., "aix-6107-1415-32" for AIX 6.1 TL7 bd 1415, 32-bit + and, "aix-6107-1415-64" for AIX 6.1 TL7 bd 1415, 64-bit + """ + vrmf, bd = _aix_bos_rte() + return _aix_tag(_aix_vrtl(vrmf), bd) + + +# extract vrtl from the BUILD_GNU_TYPE as an int +def _aix_bgt(): + # type: () -> List[int] + gnu_type = sysconfig.get_config_var("BUILD_GNU_TYPE") + if not gnu_type: + raise ValueError("BUILD_GNU_TYPE is not defined") + return _aix_vrtl(vrmf=gnu_type) + + +def aix_buildtag(): + # type: () -> str + """ + Return the platform_tag of the system Python was built on. + """ + # AIX_BUILDDATE is defined by configure with: + # lslpp -Lcq bos.rte | awk -F: '{ print $NF }' + build_date = sysconfig.get_config_var("AIX_BUILDDATE") + try: + build_date = int(build_date) + except (ValueError, TypeError): + raise ValueError(f"AIX_BUILDDATE is not defined or invalid: " + f"{build_date!r}") + return _aix_tag(_aix_bgt(), build_date) + +# file: _android_support.py +import io +import sys +from threading import RLock +from time import sleep, time + +# The maximum length of a log message in bytes, including the level marker and +# tag, is defined as LOGGER_ENTRY_MAX_PAYLOAD at +# https://cs.android.com/android/platform/superproject/+/android-14.0.0_r1:system/logging/liblog/include/log/log.h;l=71. +# Messages longer than this will be truncated by logcat. This limit has already +# been reduced at least once in the history of Android (from 4076 to 4068 between +# API level 23 and 26), so leave some headroom. +MAX_BYTES_PER_WRITE = 4000 + +# UTF-8 uses a maximum of 4 bytes per character, so limiting text writes to this +# size ensures that we can always avoid exceeding MAX_BYTES_PER_WRITE. +# However, if the actual number of bytes per character is smaller than that, +# then we may still join multiple consecutive text writes into binary +# writes containing a larger number of characters. +MAX_CHARS_PER_WRITE = MAX_BYTES_PER_WRITE // 4 + + +# When embedded in an app on current versions of Android, there's no easy way to +# monitor the C-level stdout and stderr. The testbed comes with a .c file to +# redirect them to the system log using a pipe, but that wouldn't be convenient +# or appropriate for all apps. So we redirect at the Python level instead. +def init_streams(android_log_write, stdout_prio, stderr_prio): + if sys.executable: + return # Not embedded in an app. + + global logcat + logcat = Logcat(android_log_write) + + sys.stdout = TextLogStream( + stdout_prio, "python.stdout", sys.stdout.fileno()) + sys.stderr = TextLogStream( + stderr_prio, "python.stderr", sys.stderr.fileno()) + + +class TextLogStream(io.TextIOWrapper): + def __init__(self, prio, tag, fileno=None, **kwargs): + # The default is surrogateescape for stdout and backslashreplace for + # stderr, but in the context of an Android log, readability is more + # important than reversibility. + kwargs.setdefault("encoding", "UTF-8") + kwargs.setdefault("errors", "backslashreplace") + + super().__init__(BinaryLogStream(prio, tag, fileno), **kwargs) + self._lock = RLock() + self._pending_bytes = [] + self._pending_bytes_count = 0 + + def __repr__(self): + return f"" + + def write(self, s): + if not isinstance(s, str): + raise TypeError( + f"write() argument must be str, not {type(s).__name__}") + + # In case `s` is a str subclass that writes itself to stdout or stderr + # when we call its methods, convert it to an actual str. + s = str.__str__(s) + + # We want to emit one log message per line wherever possible, so split + # the string into lines first. Note that "".splitlines() == [], so + # nothing will be logged for an empty string. + with self._lock: + for line in s.splitlines(keepends=True): + while line: + chunk = line[:MAX_CHARS_PER_WRITE] + line = line[MAX_CHARS_PER_WRITE:] + self._write_chunk(chunk) + + return len(s) + + # The size and behavior of TextIOWrapper's buffer is not part of its public + # API, so we handle buffering ourselves to avoid truncation. + def _write_chunk(self, s): + b = s.encode(self.encoding, self.errors) + if self._pending_bytes_count + len(b) > MAX_BYTES_PER_WRITE: + self.flush() + + self._pending_bytes.append(b) + self._pending_bytes_count += len(b) + if ( + self.write_through + or b.endswith(b"\n") + or self._pending_bytes_count > MAX_BYTES_PER_WRITE + ): + self.flush() + + def flush(self): + with self._lock: + self.buffer.write(b"".join(self._pending_bytes)) + self._pending_bytes.clear() + self._pending_bytes_count = 0 + + # Since this is a line-based logging system, line buffering cannot be turned + # off, i.e. a newline always causes a flush. + @property + def line_buffering(self): + return True + + +class BinaryLogStream(io.RawIOBase): + def __init__(self, prio, tag, fileno=None): + self.prio = prio + self.tag = tag + self._fileno = fileno + + def __repr__(self): + return f"" + + def writable(self): + return True + + def write(self, b): + if type(b) is not bytes: + try: + b = bytes(memoryview(b)) + except TypeError: + raise TypeError( + f"write() argument must be bytes-like, not {type(b).__name__}" + ) from None + + # Writing an empty string to the stream should have no effect. + if b: + logcat.write(self.prio, self.tag, b) + return len(b) + + # This is needed by the test suite --timeout option, which uses faulthandler. + def fileno(self): + if self._fileno is None: + raise io.UnsupportedOperation("fileno") + return self._fileno + + +# When a large volume of data is written to logcat at once, e.g. when a test +# module fails in --verbose3 mode, there's a risk of overflowing logcat's own +# buffer and losing messages. We avoid this by imposing a rate limit using the +# token bucket algorithm, based on a conservative estimate of how fast `adb +# logcat` can consume data. +MAX_BYTES_PER_SECOND = 1024 * 1024 + +# The logcat buffer size of a device can be determined by running `logcat -g`. +# We set the token bucket size to half of the buffer size of our current minimum +# API level, because other things on the system will be producing messages as +# well. +BUCKET_SIZE = 128 * 1024 + +# https://cs.android.com/android/platform/superproject/+/android-14.0.0_r1:system/logging/liblog/include/log/log_read.h;l=39 +PER_MESSAGE_OVERHEAD = 28 + + +class Logcat: + def __init__(self, android_log_write): + self.android_log_write = android_log_write + self._lock = RLock() + self._bucket_level = 0 + self._prev_write_time = time() + + def write(self, prio, tag, message): + # Encode null bytes using "modified UTF-8" to avoid them truncating the + # message. + message = message.replace(b"\x00", b"\xc0\x80") + + with self._lock: + now = time() + self._bucket_level += ( + (now - self._prev_write_time) * MAX_BYTES_PER_SECOND) + + # If the bucket level is still below zero, the clock must have gone + # backwards, so reset it to zero and continue. + self._bucket_level = max(0, min(self._bucket_level, BUCKET_SIZE)) + self._prev_write_time = now + + self._bucket_level -= PER_MESSAGE_OVERHEAD + len(tag) + len(message) + if self._bucket_level < 0: + sleep(-self._bucket_level / MAX_BYTES_PER_SECOND) + + self.android_log_write(prio, tag, message) + +# file: _apple_support.py +import io +import sys + + +def init_streams(log_write, stdout_level, stderr_level): + # Redirect stdout and stderr to the Apple system log. This method is + # invoked by init_apple_streams() (initconfig.c) if config->use_system_logger + # is enabled. + sys.stdout = SystemLog(log_write, stdout_level, errors=sys.stderr.errors) + sys.stderr = SystemLog(log_write, stderr_level, errors=sys.stderr.errors) + + +class SystemLog(io.TextIOWrapper): + def __init__(self, log_write, level, **kwargs): + kwargs.setdefault("encoding", "UTF-8") + kwargs.setdefault("line_buffering", True) + super().__init__(LogStream(log_write, level), **kwargs) + + def __repr__(self): + return f"" + + def write(self, s): + if not isinstance(s, str): + raise TypeError( + f"write() argument must be str, not {type(s).__name__}") + + # In case `s` is a str subclass that writes itself to stdout or stderr + # when we call its methods, convert it to an actual str. + s = str.__str__(s) + + # We want to emit one log message per line, so split + # the string before sending it to the superclass. + for line in s.splitlines(keepends=True): + super().write(line) + + return len(s) + + +class LogStream(io.RawIOBase): + def __init__(self, log_write, level): + self.log_write = log_write + self.level = level + + def __repr__(self): + return f"" + + def writable(self): + return True + + def write(self, b): + if type(b) is not bytes: + try: + b = bytes(memoryview(b)) + except TypeError: + raise TypeError( + f"write() argument must be bytes-like, not {type(b).__name__}" + ) from None + + # Writing an empty string to the stream should have no effect. + if b: + # Encode null bytes using "modified UTF-8" to avoid truncating the + # message. This should not affect the return value, as the caller + # may be expecting it to match the length of the input. + self.log_write(self.level, b.replace(b"\x00", b"\xc0\x80")) + + return len(b) + +# file: _collections_abc.py +# Copyright 2007 Google, Inc. All Rights Reserved. +# Licensed to PSF under a Contributor Agreement. + +"""Abstract Base Classes (ABCs) for collections, according to PEP 3119. + +Unit tests are in test_collections. +""" + +############ Maintenance notes ######################################### +# +# ABCs are different from other standard library modules in that they +# specify compliance tests. In general, once an ABC has been published, +# new methods (either abstract or concrete) cannot be added. +# +# Though classes that inherit from an ABC would automatically receive a +# new mixin method, registered classes would become non-compliant and +# violate the contract promised by ``isinstance(someobj, SomeABC)``. +# +# Though irritating, the correct procedure for adding new abstract or +# mixin methods is to create a new ABC as a subclass of the previous +# ABC. For example, union(), intersection(), and difference() cannot +# be added to Set but could go into a new ABC that extends Set. +# +# Because they are so hard to change, new ABCs should have their APIs +# carefully thought through prior to publication. +# +# Since ABCMeta only checks for the presence of methods, it is possible +# to alter the signature of a method by adding optional arguments +# or changing parameters names. This is still a bit dubious but at +# least it won't cause isinstance() to return an incorrect result. +# +# +####################################################################### + +from abc import ABCMeta, abstractmethod +import sys + +GenericAlias = type(list[int]) +EllipsisType = type(...) +def _f(): pass +FunctionType = type(_f) +del _f + +__all__ = ["Awaitable", "Coroutine", + "AsyncIterable", "AsyncIterator", "AsyncGenerator", + "Hashable", "Iterable", "Iterator", "Generator", "Reversible", + "Sized", "Container", "Callable", "Collection", + "Set", "MutableSet", + "Mapping", "MutableMapping", + "MappingView", "KeysView", "ItemsView", "ValuesView", + "Sequence", "MutableSequence", + "ByteString", "Buffer", + ] + +# This module has been renamed from collections.abc to _collections_abc to +# speed up interpreter startup. Some of the types such as MutableMapping are +# required early but collections module imports a lot of other modules. +# See issue #19218 +__name__ = "collections.abc" + +# Private list of types that we want to register with the various ABCs +# so that they will pass tests like: +# it = iter(somebytearray) +# assert isinstance(it, Iterable) +# Note: in other implementations, these types might not be distinct +# and they may have their own implementation specific types that +# are not included on this list. +bytes_iterator = type(iter(b'')) +bytearray_iterator = type(iter(bytearray())) +#callable_iterator = ??? +dict_keyiterator = type(iter({}.keys())) +dict_valueiterator = type(iter({}.values())) +dict_itemiterator = type(iter({}.items())) +list_iterator = type(iter([])) +list_reverseiterator = type(iter(reversed([]))) +range_iterator = type(iter(range(0))) +longrange_iterator = type(iter(range(1 << 1000))) +set_iterator = type(iter(set())) +str_iterator = type(iter("")) +tuple_iterator = type(iter(())) +zip_iterator = type(iter(zip())) +## views ## +dict_keys = type({}.keys()) +dict_values = type({}.values()) +dict_items = type({}.items()) +## misc ## +mappingproxy = type(type.__dict__) +def _get_framelocalsproxy(): + return type(sys._getframe().f_locals) +framelocalsproxy = _get_framelocalsproxy() +del _get_framelocalsproxy +generator = type((lambda: (yield))()) +## coroutine ## +async def _coro(): pass +_coro = _coro() +coroutine = type(_coro) +_coro.close() # Prevent ResourceWarning +del _coro +## asynchronous generator ## +async def _ag(): yield +_ag = _ag() +async_generator = type(_ag) +del _ag + + +### ONE-TRICK PONIES ### + +def _check_methods(C, *methods): + mro = C.__mro__ + for method in methods: + for B in mro: + if method in B.__dict__: + if B.__dict__[method] is None: + return NotImplemented + break + else: + return NotImplemented + return True + +class Hashable(metaclass=ABCMeta): + + __slots__ = () + + @abstractmethod + def __hash__(self): + return 0 + + @classmethod + def __subclasshook__(cls, C): + if cls is Hashable: + return _check_methods(C, "__hash__") + return NotImplemented + + +class Awaitable(metaclass=ABCMeta): + + __slots__ = () + + @abstractmethod + def __await__(self): + yield + + @classmethod + def __subclasshook__(cls, C): + if cls is Awaitable: + return _check_methods(C, "__await__") + return NotImplemented + + __class_getitem__ = classmethod(GenericAlias) + + +class Coroutine(Awaitable): + + __slots__ = () + + @abstractmethod + def send(self, value): + """Send a value into the coroutine. + Return next yielded value or raise StopIteration. + """ + raise StopIteration + + @abstractmethod + def throw(self, typ, val=None, tb=None): + """Raise an exception in the coroutine. + Return next yielded value or raise StopIteration. + """ + if val is None: + if tb is None: + raise typ + val = typ() + if tb is not None: + val = val.with_traceback(tb) + raise val + + def close(self): + """Raise GeneratorExit inside coroutine. + """ + try: + self.throw(GeneratorExit) + except (GeneratorExit, StopIteration): + pass + else: + raise RuntimeError("coroutine ignored GeneratorExit") + + @classmethod + def __subclasshook__(cls, C): + if cls is Coroutine: + return _check_methods(C, '__await__', 'send', 'throw', 'close') + return NotImplemented + + +Coroutine.register(coroutine) + + +class AsyncIterable(metaclass=ABCMeta): + + __slots__ = () + + @abstractmethod + def __aiter__(self): + return AsyncIterator() + + @classmethod + def __subclasshook__(cls, C): + if cls is AsyncIterable: + return _check_methods(C, "__aiter__") + return NotImplemented + + __class_getitem__ = classmethod(GenericAlias) + + +class AsyncIterator(AsyncIterable): + + __slots__ = () + + @abstractmethod + async def __anext__(self): + """Return the next item or raise StopAsyncIteration when exhausted.""" + raise StopAsyncIteration + + def __aiter__(self): + return self + + @classmethod + def __subclasshook__(cls, C): + if cls is AsyncIterator: + return _check_methods(C, "__anext__", "__aiter__") + return NotImplemented + + +class AsyncGenerator(AsyncIterator): + + __slots__ = () + + async def __anext__(self): + """Return the next item from the asynchronous generator. + When exhausted, raise StopAsyncIteration. + """ + return await self.asend(None) + + @abstractmethod + async def asend(self, value): + """Send a value into the asynchronous generator. + Return next yielded value or raise StopAsyncIteration. + """ + raise StopAsyncIteration + + @abstractmethod + async def athrow(self, typ, val=None, tb=None): + """Raise an exception in the asynchronous generator. + Return next yielded value or raise StopAsyncIteration. + """ + if val is None: + if tb is None: + raise typ + val = typ() + if tb is not None: + val = val.with_traceback(tb) + raise val + + async def aclose(self): + """Raise GeneratorExit inside coroutine. + """ + try: + await self.athrow(GeneratorExit) + except (GeneratorExit, StopAsyncIteration): + pass + else: + raise RuntimeError("asynchronous generator ignored GeneratorExit") + + @classmethod + def __subclasshook__(cls, C): + if cls is AsyncGenerator: + return _check_methods(C, '__aiter__', '__anext__', + 'asend', 'athrow', 'aclose') + return NotImplemented + + +AsyncGenerator.register(async_generator) + + +class Iterable(metaclass=ABCMeta): + + __slots__ = () + + @abstractmethod + def __iter__(self): + while False: + yield None + + @classmethod + def __subclasshook__(cls, C): + if cls is Iterable: + return _check_methods(C, "__iter__") + return NotImplemented + + __class_getitem__ = classmethod(GenericAlias) + + +class Iterator(Iterable): + + __slots__ = () + + @abstractmethod + def __next__(self): + 'Return the next item from the iterator. When exhausted, raise StopIteration' + raise StopIteration + + def __iter__(self): + return self + + @classmethod + def __subclasshook__(cls, C): + if cls is Iterator: + return _check_methods(C, '__iter__', '__next__') + return NotImplemented + + +Iterator.register(bytes_iterator) +Iterator.register(bytearray_iterator) +#Iterator.register(callable_iterator) +Iterator.register(dict_keyiterator) +Iterator.register(dict_valueiterator) +Iterator.register(dict_itemiterator) +Iterator.register(list_iterator) +Iterator.register(list_reverseiterator) +Iterator.register(range_iterator) +Iterator.register(longrange_iterator) +Iterator.register(set_iterator) +Iterator.register(str_iterator) +Iterator.register(tuple_iterator) +Iterator.register(zip_iterator) + + +class Reversible(Iterable): + + __slots__ = () + + @abstractmethod + def __reversed__(self): + while False: + yield None + + @classmethod + def __subclasshook__(cls, C): + if cls is Reversible: + return _check_methods(C, "__reversed__", "__iter__") + return NotImplemented + + +class Generator(Iterator): + + __slots__ = () + + def __next__(self): + """Return the next item from the generator. + When exhausted, raise StopIteration. + """ + return self.send(None) + + @abstractmethod + def send(self, value): + """Send a value into the generator. + Return next yielded value or raise StopIteration. + """ + raise StopIteration + + @abstractmethod + def throw(self, typ, val=None, tb=None): + """Raise an exception in the generator. + Return next yielded value or raise StopIteration. + """ + if val is None: + if tb is None: + raise typ + val = typ() + if tb is not None: + val = val.with_traceback(tb) + raise val + + def close(self): + """Raise GeneratorExit inside generator. + """ + try: + self.throw(GeneratorExit) + except (GeneratorExit, StopIteration): + pass + else: + raise RuntimeError("generator ignored GeneratorExit") + + @classmethod + def __subclasshook__(cls, C): + if cls is Generator: + return _check_methods(C, '__iter__', '__next__', + 'send', 'throw', 'close') + return NotImplemented + + +Generator.register(generator) + + +class Sized(metaclass=ABCMeta): + + __slots__ = () + + @abstractmethod + def __len__(self): + return 0 + + @classmethod + def __subclasshook__(cls, C): + if cls is Sized: + return _check_methods(C, "__len__") + return NotImplemented + + +class Container(metaclass=ABCMeta): + + __slots__ = () + + @abstractmethod + def __contains__(self, x): + return False + + @classmethod + def __subclasshook__(cls, C): + if cls is Container: + return _check_methods(C, "__contains__") + return NotImplemented + + __class_getitem__ = classmethod(GenericAlias) + + +class Collection(Sized, Iterable, Container): + + __slots__ = () + + @classmethod + def __subclasshook__(cls, C): + if cls is Collection: + return _check_methods(C, "__len__", "__iter__", "__contains__") + return NotImplemented + + +class Buffer(metaclass=ABCMeta): + + __slots__ = () + + @abstractmethod + def __buffer__(self, flags: int, /) -> memoryview: + raise NotImplementedError + + @classmethod + def __subclasshook__(cls, C): + if cls is Buffer: + return _check_methods(C, "__buffer__") + return NotImplemented + + +class _CallableGenericAlias(GenericAlias): + """ Represent `Callable[argtypes, resulttype]`. + + This sets ``__args__`` to a tuple containing the flattened ``argtypes`` + followed by ``resulttype``. + + Example: ``Callable[[int, str], float]`` sets ``__args__`` to + ``(int, str, float)``. + """ + + __slots__ = () + + def __new__(cls, origin, args): + if not (isinstance(args, tuple) and len(args) == 2): + raise TypeError( + "Callable must be used as Callable[[arg, ...], result].") + t_args, t_result = args + if isinstance(t_args, (tuple, list)): + args = (*t_args, t_result) + elif not _is_param_expr(t_args): + raise TypeError(f"Expected a list of types, an ellipsis, " + f"ParamSpec, or Concatenate. Got {t_args}") + return super().__new__(cls, origin, args) + + def __repr__(self): + if len(self.__args__) == 2 and _is_param_expr(self.__args__[0]): + return super().__repr__() + return (f'collections.abc.Callable' + f'[[{", ".join([_type_repr(a) for a in self.__args__[:-1]])}], ' + f'{_type_repr(self.__args__[-1])}]') + + def __reduce__(self): + args = self.__args__ + if not (len(args) == 2 and _is_param_expr(args[0])): + args = list(args[:-1]), args[-1] + return _CallableGenericAlias, (Callable, args) + + def __getitem__(self, item): + # Called during TypeVar substitution, returns the custom subclass + # rather than the default types.GenericAlias object. Most of the + # code is copied from typing's _GenericAlias and the builtin + # types.GenericAlias. + if not isinstance(item, tuple): + item = (item,) + + new_args = super().__getitem__(item).__args__ + + # args[0] occurs due to things like Z[[int, str, bool]] from PEP 612 + if not isinstance(new_args[0], (tuple, list)): + t_result = new_args[-1] + t_args = new_args[:-1] + new_args = (t_args, t_result) + return _CallableGenericAlias(Callable, tuple(new_args)) + +def _is_param_expr(obj): + """Checks if obj matches either a list of types, ``...``, ``ParamSpec`` or + ``_ConcatenateGenericAlias`` from typing.py + """ + if obj is Ellipsis: + return True + if isinstance(obj, list): + return True + obj = type(obj) + names = ('ParamSpec', '_ConcatenateGenericAlias') + return obj.__module__ == 'typing' and any(obj.__name__ == name for name in names) + +def _type_repr(obj): + """Return the repr() of an object, special-casing types (internal helper). + + Copied from :mod:`typing` since collections.abc + shouldn't depend on that module. + (Keep this roughly in sync with the typing version.) + """ + if isinstance(obj, type): + if obj.__module__ == 'builtins': + return obj.__qualname__ + return f'{obj.__module__}.{obj.__qualname__}' + if obj is Ellipsis: + return '...' + if isinstance(obj, FunctionType): + return obj.__name__ + return repr(obj) + + +class Callable(metaclass=ABCMeta): + + __slots__ = () + + @abstractmethod + def __call__(self, *args, **kwds): + return False + + @classmethod + def __subclasshook__(cls, C): + if cls is Callable: + return _check_methods(C, "__call__") + return NotImplemented + + __class_getitem__ = classmethod(_CallableGenericAlias) + + +### SETS ### + + +class Set(Collection): + """A set is a finite, iterable container. + + This class provides concrete generic implementations of all + methods except for __contains__, __iter__ and __len__. + + To override the comparisons (presumably for speed, as the + semantics are fixed), redefine __le__ and __ge__, + then the other operations will automatically follow suit. + """ + + __slots__ = () + + def __le__(self, other): + if not isinstance(other, Set): + return NotImplemented + if len(self) > len(other): + return False + for elem in self: + if elem not in other: + return False + return True + + def __lt__(self, other): + if not isinstance(other, Set): + return NotImplemented + return len(self) < len(other) and self.__le__(other) + + def __gt__(self, other): + if not isinstance(other, Set): + return NotImplemented + return len(self) > len(other) and self.__ge__(other) + + def __ge__(self, other): + if not isinstance(other, Set): + return NotImplemented + if len(self) < len(other): + return False + for elem in other: + if elem not in self: + return False + return True + + def __eq__(self, other): + if not isinstance(other, Set): + return NotImplemented + return len(self) == len(other) and self.__le__(other) + + @classmethod + def _from_iterable(cls, it): + '''Construct an instance of the class from any iterable input. + + Must override this method if the class constructor signature + does not accept an iterable for an input. + ''' + return cls(it) + + def __and__(self, other): + if not isinstance(other, Iterable): + return NotImplemented + return self._from_iterable(value for value in other if value in self) + + __rand__ = __and__ + + def isdisjoint(self, other): + 'Return True if two sets have a null intersection.' + for value in other: + if value in self: + return False + return True + + def __or__(self, other): + if not isinstance(other, Iterable): + return NotImplemented + chain = (e for s in (self, other) for e in s) + return self._from_iterable(chain) + + __ror__ = __or__ + + def __sub__(self, other): + if not isinstance(other, Set): + if not isinstance(other, Iterable): + return NotImplemented + other = self._from_iterable(other) + return self._from_iterable(value for value in self + if value not in other) + + def __rsub__(self, other): + if not isinstance(other, Set): + if not isinstance(other, Iterable): + return NotImplemented + other = self._from_iterable(other) + return self._from_iterable(value for value in other + if value not in self) + + def __xor__(self, other): + if not isinstance(other, Set): + if not isinstance(other, Iterable): + return NotImplemented + other = self._from_iterable(other) + return (self - other) | (other - self) + + __rxor__ = __xor__ + + def _hash(self): + """Compute the hash value of a set. + + Note that we don't define __hash__: not all sets are hashable. + But if you define a hashable set type, its __hash__ should + call this function. + + This must be compatible __eq__. + + All sets ought to compare equal if they contain the same + elements, regardless of how they are implemented, and + regardless of the order of the elements; so there's not much + freedom for __eq__ or __hash__. We match the algorithm used + by the built-in frozenset type. + """ + MAX = sys.maxsize + MASK = 2 * MAX + 1 + n = len(self) + h = 1927868237 * (n + 1) + h &= MASK + for x in self: + hx = hash(x) + h ^= (hx ^ (hx << 16) ^ 89869747) * 3644798167 + h &= MASK + h ^= (h >> 11) ^ (h >> 25) + h = h * 69069 + 907133923 + h &= MASK + if h > MAX: + h -= MASK + 1 + if h == -1: + h = 590923713 + return h + + +Set.register(frozenset) + + +class MutableSet(Set): + """A mutable set is a finite, iterable container. + + This class provides concrete generic implementations of all + methods except for __contains__, __iter__, __len__, + add(), and discard(). + + To override the comparisons (presumably for speed, as the + semantics are fixed), all you have to do is redefine __le__ and + then the other operations will automatically follow suit. + """ + + __slots__ = () + + @abstractmethod + def add(self, value): + """Add an element.""" + raise NotImplementedError + + @abstractmethod + def discard(self, value): + """Remove an element. Do not raise an exception if absent.""" + raise NotImplementedError + + def remove(self, value): + """Remove an element. If not a member, raise a KeyError.""" + if value not in self: + raise KeyError(value) + self.discard(value) + + def pop(self): + """Return the popped value. Raise KeyError if empty.""" + it = iter(self) + try: + value = next(it) + except StopIteration: + raise KeyError from None + self.discard(value) + return value + + def clear(self): + """This is slow<|im_end|> +<|im_start|>assistant + + + + +Based on the code provided, here is an analysis and summary of the Python standard library modules included in the snippet. + +### 1. `__future__.py` +**Purpose:** This module records "phased-in incompatible language changes." It allows developers to enable future Python features in current versions using `from __ +--- +info: graphs: 1 captured (9 ms each), 61 of 63 rounds replayed diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/logs/generate-exact-chunk8192.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/logs/generate-exact-chunk8192.log new file mode 100644 index 0000000000..199d7410ab --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/logs/generate-exact-chunk8192.log @@ -0,0 +1,1293 @@ +loaded in 20.5 s, 87.08 GiB on the device +prompt 10368 tokens in 18.556 s (558.7 tok/s); 63 tokens in 1.775 s (35.50 tok/s) +logits hash c8f6888043c972e0 +ids { 27775, 383, 279, 1970, 3766, 11, 1532, 369, 449, 6157, 321, 11782, 314, 279, 12654, 5129, 6522, 13067, 5064, 303, 279, 41643, 13, 271, 13962, 220, 16, 13, 1510, 548, 20409, 18162, 3181, 63, 198, 332, 71516, 64700, 1061, 4536, 7189, 328, 734, 1422, 3309, 51047, 3992, 4203, 1149, 1049, 5954, 13015, 310, 7056, 3725, 12654, 4275, 303, 1428, 10478, 1608, 1510, 1445, 1259 } +--- +<|im_start|>user +# file: __future__.py +"""Record of phased-in incompatible language changes. + +Each line is of the form: + + FeatureName = "_Feature(" OptionalRelease "," MandatoryRelease "," + CompilerFlag ")" + +where, normally, OptionalRelease < MandatoryRelease, and both are 5-tuples +of the same form as sys.version_info: + + (PY_MAJOR_VERSION, # the 2 in 2.1.0a3; an int + PY_MINOR_VERSION, # the 1; an int + PY_MICRO_VERSION, # the 0; an int + PY_RELEASE_LEVEL, # "alpha", "beta", "candidate" or "final"; string + PY_RELEASE_SERIAL # the 3; an int + ) + +OptionalRelease records the first release in which + + from __future__ import FeatureName + +was accepted. + +In the case of MandatoryReleases that have not yet occurred, +MandatoryRelease predicts the release in which the feature will become part +of the language. + +Else MandatoryRelease records when the feature became part of the language; +in releases at or after that, modules no longer need + + from __future__ import FeatureName + +to use the feature in question, but may continue to use such imports. + +MandatoryRelease may also be None, meaning that a planned feature got +dropped or that the release version is undetermined. + +Instances of class _Feature have two corresponding methods, +.getOptionalRelease() and .getMandatoryRelease(). + +CompilerFlag is the (bitfield) flag that should be passed in the fourth +argument to the builtin function compile() to enable the feature in +dynamically compiled code. This flag is stored in the .compiler_flag +attribute on _Future instances. These values must match the appropriate +#defines of CO_xxx flags in Include/cpython/compile.h. + +No feature line is ever to be deleted from this file. +""" + +all_feature_names = [ + "nested_scopes", + "generators", + "division", + "absolute_import", + "with_statement", + "print_function", + "unicode_literals", + "barry_as_FLUFL", + "generator_stop", + "annotations", +] + +__all__ = ["all_feature_names"] + all_feature_names + +# The CO_xxx symbols are defined here under the same names defined in +# code.h and used by compile.h, so that an editor search will find them here. +# However, they're not exported in __all__, because they don't really belong to +# this module. +CO_NESTED = 0x0010 # nested_scopes +CO_GENERATOR_ALLOWED = 0 # generators (obsolete, was 0x1000) +CO_FUTURE_DIVISION = 0x20000 # division +CO_FUTURE_ABSOLUTE_IMPORT = 0x40000 # perform absolute imports by default +CO_FUTURE_WITH_STATEMENT = 0x80000 # with statement +CO_FUTURE_PRINT_FUNCTION = 0x100000 # print function +CO_FUTURE_UNICODE_LITERALS = 0x200000 # unicode string literals +CO_FUTURE_BARRY_AS_BDFL = 0x400000 +CO_FUTURE_GENERATOR_STOP = 0x800000 # StopIteration becomes RuntimeError in generators +CO_FUTURE_ANNOTATIONS = 0x1000000 # annotations become strings at runtime + + +class _Feature: + + def __init__(self, optionalRelease, mandatoryRelease, compiler_flag): + self.optional = optionalRelease + self.mandatory = mandatoryRelease + self.compiler_flag = compiler_flag + + def getOptionalRelease(self): + """Return first release in which this feature was recognized. + + This is a 5-tuple, of the same form as sys.version_info. + """ + return self.optional + + def getMandatoryRelease(self): + """Return release in which this feature will become mandatory. + + This is a 5-tuple, of the same form as sys.version_info, or, if + the feature was dropped, or the release date is undetermined, is None. + """ + return self.mandatory + + def __repr__(self): + return "_Feature" + repr((self.optional, + self.mandatory, + self.compiler_flag)) + + +nested_scopes = _Feature((2, 1, 0, "beta", 1), + (2, 2, 0, "alpha", 0), + CO_NESTED) + +generators = _Feature((2, 2, 0, "alpha", 1), + (2, 3, 0, "final", 0), + CO_GENERATOR_ALLOWED) + +division = _Feature((2, 2, 0, "alpha", 2), + (3, 0, 0, "alpha", 0), + CO_FUTURE_DIVISION) + +absolute_import = _Feature((2, 5, 0, "alpha", 1), + (3, 0, 0, "alpha", 0), + CO_FUTURE_ABSOLUTE_IMPORT) + +with_statement = _Feature((2, 5, 0, "alpha", 1), + (2, 6, 0, "alpha", 0), + CO_FUTURE_WITH_STATEMENT) + +print_function = _Feature((2, 6, 0, "alpha", 2), + (3, 0, 0, "alpha", 0), + CO_FUTURE_PRINT_FUNCTION) + +unicode_literals = _Feature((2, 6, 0, "alpha", 2), + (3, 0, 0, "alpha", 0), + CO_FUTURE_UNICODE_LITERALS) + +barry_as_FLUFL = _Feature((3, 1, 0, "alpha", 2), + (4, 0, 0, "alpha", 0), + CO_FUTURE_BARRY_AS_BDFL) + +generator_stop = _Feature((3, 5, 0, "beta", 1), + (3, 7, 0, "alpha", 0), + CO_FUTURE_GENERATOR_STOP) + +annotations = _Feature((3, 7, 0, "beta", 1), + None, + CO_FUTURE_ANNOTATIONS) + +# file: __hello__.py +initialized = True + +class TestFrozenUtf8_1: + """\u00b6""" + +class TestFrozenUtf8_2: + """\u03c0""" + +class TestFrozenUtf8_4: + """\U0001f600""" + +def main(): + print("Hello world!") + +if __name__ == '__main__': + main() + +# file: _aix_support.py +"""Shared AIX support functions.""" + +import sys +import sysconfig + + +# Taken from _osx_support _read_output function +def _read_cmd_output(commandstring, capture_stderr=False): + """Output from successful command execution or None""" + # Similar to os.popen(commandstring, "r").read(), + # but without actually using os.popen because that + # function is not usable during python bootstrap. + import os + import contextlib + fp = open("/tmp/_aix_support.%s"%( + os.getpid(),), "w+b") + + with contextlib.closing(fp) as fp: + if capture_stderr: + cmd = "%s >'%s' 2>&1" % (commandstring, fp.name) + else: + cmd = "%s 2>/dev/null >'%s'" % (commandstring, fp.name) + return fp.read() if not os.system(cmd) else None + + +def _aix_tag(vrtl, bd): + # type: (List[int], int) -> str + # Infer the ABI bitwidth from maxsize (assuming 64 bit as the default) + _sz = 32 if sys.maxsize == (2**31-1) else 64 + _bd = bd if bd != 0 else 9988 + # vrtl[version, release, technology_level] + return "aix-{:1x}{:1d}{:02d}-{:04d}-{}".format(vrtl[0], vrtl[1], vrtl[2], _bd, _sz) + + +# extract version, release and technology level from a VRMF string +def _aix_vrtl(vrmf): + # type: (str) -> List[int] + v, r, tl = vrmf.split(".")[:3] + return [int(v[-1]), int(r), int(tl)] + + +def _aix_bos_rte(): + # type: () -> Tuple[str, int] + """ + Return a Tuple[str, int] e.g., ['7.1.4.34', 1806] + The fileset bos.rte represents the current AIX run-time level. It's VRMF and + builddate reflect the current ABI levels of the runtime environment. + If no builddate is found give a value that will satisfy pep425 related queries + """ + # All AIX systems to have lslpp installed in this location + # subprocess may not be available during python bootstrap + try: + import subprocess + out = subprocess.check_output(["/usr/bin/lslpp", "-Lqc", "bos.rte"]) + except ImportError: + out = _read_cmd_output("/usr/bin/lslpp -Lqc bos.rte") + out = out.decode("utf-8") + out = out.strip().split(":") # type: ignore + _bd = int(out[-1]) if out[-1] != '' else 9988 + return (str(out[2]), _bd) + + +def aix_platform(): + # type: () -> str + """ + AIX filesets are identified by four decimal values: V.R.M.F. + V (version) and R (release) can be retrieved using ``uname`` + Since 2007, starting with AIX 5.3 TL7, the M value has been + included with the fileset bos.rte and represents the Technology + Level (TL) of AIX. The F (Fix) value also increases, but is not + relevant for comparing releases and binary compatibility. + For binary compatibility the so-called builddate is needed. + Again, the builddate of an AIX release is associated with bos.rte. + AIX ABI compatibility is described as guaranteed at: https://www.ibm.com/\ + support/knowledgecenter/en/ssw_aix_72/install/binary_compatability.html + + For pep425 purposes the AIX platform tag becomes: + "aix-{:1x}{:1d}{:02d}-{:04d}-{}".format(v, r, tl, builddate, bitsize) + e.g., "aix-6107-1415-32" for AIX 6.1 TL7 bd 1415, 32-bit + and, "aix-6107-1415-64" for AIX 6.1 TL7 bd 1415, 64-bit + """ + vrmf, bd = _aix_bos_rte() + return _aix_tag(_aix_vrtl(vrmf), bd) + + +# extract vrtl from the BUILD_GNU_TYPE as an int +def _aix_bgt(): + # type: () -> List[int] + gnu_type = sysconfig.get_config_var("BUILD_GNU_TYPE") + if not gnu_type: + raise ValueError("BUILD_GNU_TYPE is not defined") + return _aix_vrtl(vrmf=gnu_type) + + +def aix_buildtag(): + # type: () -> str + """ + Return the platform_tag of the system Python was built on. + """ + # AIX_BUILDDATE is defined by configure with: + # lslpp -Lcq bos.rte | awk -F: '{ print $NF }' + build_date = sysconfig.get_config_var("AIX_BUILDDATE") + try: + build_date = int(build_date) + except (ValueError, TypeError): + raise ValueError(f"AIX_BUILDDATE is not defined or invalid: " + f"{build_date!r}") + return _aix_tag(_aix_bgt(), build_date) + +# file: _android_support.py +import io +import sys +from threading import RLock +from time import sleep, time + +# The maximum length of a log message in bytes, including the level marker and +# tag, is defined as LOGGER_ENTRY_MAX_PAYLOAD at +# https://cs.android.com/android/platform/superproject/+/android-14.0.0_r1:system/logging/liblog/include/log/log.h;l=71. +# Messages longer than this will be truncated by logcat. This limit has already +# been reduced at least once in the history of Android (from 4076 to 4068 between +# API level 23 and 26), so leave some headroom. +MAX_BYTES_PER_WRITE = 4000 + +# UTF-8 uses a maximum of 4 bytes per character, so limiting text writes to this +# size ensures that we can always avoid exceeding MAX_BYTES_PER_WRITE. +# However, if the actual number of bytes per character is smaller than that, +# then we may still join multiple consecutive text writes into binary +# writes containing a larger number of characters. +MAX_CHARS_PER_WRITE = MAX_BYTES_PER_WRITE // 4 + + +# When embedded in an app on current versions of Android, there's no easy way to +# monitor the C-level stdout and stderr. The testbed comes with a .c file to +# redirect them to the system log using a pipe, but that wouldn't be convenient +# or appropriate for all apps. So we redirect at the Python level instead. +def init_streams(android_log_write, stdout_prio, stderr_prio): + if sys.executable: + return # Not embedded in an app. + + global logcat + logcat = Logcat(android_log_write) + + sys.stdout = TextLogStream( + stdout_prio, "python.stdout", sys.stdout.fileno()) + sys.stderr = TextLogStream( + stderr_prio, "python.stderr", sys.stderr.fileno()) + + +class TextLogStream(io.TextIOWrapper): + def __init__(self, prio, tag, fileno=None, **kwargs): + # The default is surrogateescape for stdout and backslashreplace for + # stderr, but in the context of an Android log, readability is more + # important than reversibility. + kwargs.setdefault("encoding", "UTF-8") + kwargs.setdefault("errors", "backslashreplace") + + super().__init__(BinaryLogStream(prio, tag, fileno), **kwargs) + self._lock = RLock() + self._pending_bytes = [] + self._pending_bytes_count = 0 + + def __repr__(self): + return f"" + + def write(self, s): + if not isinstance(s, str): + raise TypeError( + f"write() argument must be str, not {type(s).__name__}") + + # In case `s` is a str subclass that writes itself to stdout or stderr + # when we call its methods, convert it to an actual str. + s = str.__str__(s) + + # We want to emit one log message per line wherever possible, so split + # the string into lines first. Note that "".splitlines() == [], so + # nothing will be logged for an empty string. + with self._lock: + for line in s.splitlines(keepends=True): + while line: + chunk = line[:MAX_CHARS_PER_WRITE] + line = line[MAX_CHARS_PER_WRITE:] + self._write_chunk(chunk) + + return len(s) + + # The size and behavior of TextIOWrapper's buffer is not part of its public + # API, so we handle buffering ourselves to avoid truncation. + def _write_chunk(self, s): + b = s.encode(self.encoding, self.errors) + if self._pending_bytes_count + len(b) > MAX_BYTES_PER_WRITE: + self.flush() + + self._pending_bytes.append(b) + self._pending_bytes_count += len(b) + if ( + self.write_through + or b.endswith(b"\n") + or self._pending_bytes_count > MAX_BYTES_PER_WRITE + ): + self.flush() + + def flush(self): + with self._lock: + self.buffer.write(b"".join(self._pending_bytes)) + self._pending_bytes.clear() + self._pending_bytes_count = 0 + + # Since this is a line-based logging system, line buffering cannot be turned + # off, i.e. a newline always causes a flush. + @property + def line_buffering(self): + return True + + +class BinaryLogStream(io.RawIOBase): + def __init__(self, prio, tag, fileno=None): + self.prio = prio + self.tag = tag + self._fileno = fileno + + def __repr__(self): + return f"" + + def writable(self): + return True + + def write(self, b): + if type(b) is not bytes: + try: + b = bytes(memoryview(b)) + except TypeError: + raise TypeError( + f"write() argument must be bytes-like, not {type(b).__name__}" + ) from None + + # Writing an empty string to the stream should have no effect. + if b: + logcat.write(self.prio, self.tag, b) + return len(b) + + # This is needed by the test suite --timeout option, which uses faulthandler. + def fileno(self): + if self._fileno is None: + raise io.UnsupportedOperation("fileno") + return self._fileno + + +# When a large volume of data is written to logcat at once, e.g. when a test +# module fails in --verbose3 mode, there's a risk of overflowing logcat's own +# buffer and losing messages. We avoid this by imposing a rate limit using the +# token bucket algorithm, based on a conservative estimate of how fast `adb +# logcat` can consume data. +MAX_BYTES_PER_SECOND = 1024 * 1024 + +# The logcat buffer size of a device can be determined by running `logcat -g`. +# We set the token bucket size to half of the buffer size of our current minimum +# API level, because other things on the system will be producing messages as +# well. +BUCKET_SIZE = 128 * 1024 + +# https://cs.android.com/android/platform/superproject/+/android-14.0.0_r1:system/logging/liblog/include/log/log_read.h;l=39 +PER_MESSAGE_OVERHEAD = 28 + + +class Logcat: + def __init__(self, android_log_write): + self.android_log_write = android_log_write + self._lock = RLock() + self._bucket_level = 0 + self._prev_write_time = time() + + def write(self, prio, tag, message): + # Encode null bytes using "modified UTF-8" to avoid them truncating the + # message. + message = message.replace(b"\x00", b"\xc0\x80") + + with self._lock: + now = time() + self._bucket_level += ( + (now - self._prev_write_time) * MAX_BYTES_PER_SECOND) + + # If the bucket level is still below zero, the clock must have gone + # backwards, so reset it to zero and continue. + self._bucket_level = max(0, min(self._bucket_level, BUCKET_SIZE)) + self._prev_write_time = now + + self._bucket_level -= PER_MESSAGE_OVERHEAD + len(tag) + len(message) + if self._bucket_level < 0: + sleep(-self._bucket_level / MAX_BYTES_PER_SECOND) + + self.android_log_write(prio, tag, message) + +# file: _apple_support.py +import io +import sys + + +def init_streams(log_write, stdout_level, stderr_level): + # Redirect stdout and stderr to the Apple system log. This method is + # invoked by init_apple_streams() (initconfig.c) if config->use_system_logger + # is enabled. + sys.stdout = SystemLog(log_write, stdout_level, errors=sys.stderr.errors) + sys.stderr = SystemLog(log_write, stderr_level, errors=sys.stderr.errors) + + +class SystemLog(io.TextIOWrapper): + def __init__(self, log_write, level, **kwargs): + kwargs.setdefault("encoding", "UTF-8") + kwargs.setdefault("line_buffering", True) + super().__init__(LogStream(log_write, level), **kwargs) + + def __repr__(self): + return f"" + + def write(self, s): + if not isinstance(s, str): + raise TypeError( + f"write() argument must be str, not {type(s).__name__}") + + # In case `s` is a str subclass that writes itself to stdout or stderr + # when we call its methods, convert it to an actual str. + s = str.__str__(s) + + # We want to emit one log message per line, so split + # the string before sending it to the superclass. + for line in s.splitlines(keepends=True): + super().write(line) + + return len(s) + + +class LogStream(io.RawIOBase): + def __init__(self, log_write, level): + self.log_write = log_write + self.level = level + + def __repr__(self): + return f"" + + def writable(self): + return True + + def write(self, b): + if type(b) is not bytes: + try: + b = bytes(memoryview(b)) + except TypeError: + raise TypeError( + f"write() argument must be bytes-like, not {type(b).__name__}" + ) from None + + # Writing an empty string to the stream should have no effect. + if b: + # Encode null bytes using "modified UTF-8" to avoid truncating the + # message. This should not affect the return value, as the caller + # may be expecting it to match the length of the input. + self.log_write(self.level, b.replace(b"\x00", b"\xc0\x80")) + + return len(b) + +# file: _collections_abc.py +# Copyright 2007 Google, Inc. All Rights Reserved. +# Licensed to PSF under a Contributor Agreement. + +"""Abstract Base Classes (ABCs) for collections, according to PEP 3119. + +Unit tests are in test_collections. +""" + +############ Maintenance notes ######################################### +# +# ABCs are different from other standard library modules in that they +# specify compliance tests. In general, once an ABC has been published, +# new methods (either abstract or concrete) cannot be added. +# +# Though classes that inherit from an ABC would automatically receive a +# new mixin method, registered classes would become non-compliant and +# violate the contract promised by ``isinstance(someobj, SomeABC)``. +# +# Though irritating, the correct procedure for adding new abstract or +# mixin methods is to create a new ABC as a subclass of the previous +# ABC. For example, union(), intersection(), and difference() cannot +# be added to Set but could go into a new ABC that extends Set. +# +# Because they are so hard to change, new ABCs should have their APIs +# carefully thought through prior to publication. +# +# Since ABCMeta only checks for the presence of methods, it is possible +# to alter the signature of a method by adding optional arguments +# or changing parameters names. This is still a bit dubious but at +# least it won't cause isinstance() to return an incorrect result. +# +# +####################################################################### + +from abc import ABCMeta, abstractmethod +import sys + +GenericAlias = type(list[int]) +EllipsisType = type(...) +def _f(): pass +FunctionType = type(_f) +del _f + +__all__ = ["Awaitable", "Coroutine", + "AsyncIterable", "AsyncIterator", "AsyncGenerator", + "Hashable", "Iterable", "Iterator", "Generator", "Reversible", + "Sized", "Container", "Callable", "Collection", + "Set", "MutableSet", + "Mapping", "MutableMapping", + "MappingView", "KeysView", "ItemsView", "ValuesView", + "Sequence", "MutableSequence", + "ByteString", "Buffer", + ] + +# This module has been renamed from collections.abc to _collections_abc to +# speed up interpreter startup. Some of the types such as MutableMapping are +# required early but collections module imports a lot of other modules. +# See issue #19218 +__name__ = "collections.abc" + +# Private list of types that we want to register with the various ABCs +# so that they will pass tests like: +# it = iter(somebytearray) +# assert isinstance(it, Iterable) +# Note: in other implementations, these types might not be distinct +# and they may have their own implementation specific types that +# are not included on this list. +bytes_iterator = type(iter(b'')) +bytearray_iterator = type(iter(bytearray())) +#callable_iterator = ??? +dict_keyiterator = type(iter({}.keys())) +dict_valueiterator = type(iter({}.values())) +dict_itemiterator = type(iter({}.items())) +list_iterator = type(iter([])) +list_reverseiterator = type(iter(reversed([]))) +range_iterator = type(iter(range(0))) +longrange_iterator = type(iter(range(1 << 1000))) +set_iterator = type(iter(set())) +str_iterator = type(iter("")) +tuple_iterator = type(iter(())) +zip_iterator = type(iter(zip())) +## views ## +dict_keys = type({}.keys()) +dict_values = type({}.values()) +dict_items = type({}.items()) +## misc ## +mappingproxy = type(type.__dict__) +def _get_framelocalsproxy(): + return type(sys._getframe().f_locals) +framelocalsproxy = _get_framelocalsproxy() +del _get_framelocalsproxy +generator = type((lambda: (yield))()) +## coroutine ## +async def _coro(): pass +_coro = _coro() +coroutine = type(_coro) +_coro.close() # Prevent ResourceWarning +del _coro +## asynchronous generator ## +async def _ag(): yield +_ag = _ag() +async_generator = type(_ag) +del _ag + + +### ONE-TRICK PONIES ### + +def _check_methods(C, *methods): + mro = C.__mro__ + for method in methods: + for B in mro: + if method in B.__dict__: + if B.__dict__[method] is None: + return NotImplemented + break + else: + return NotImplemented + return True + +class Hashable(metaclass=ABCMeta): + + __slots__ = () + + @abstractmethod + def __hash__(self): + return 0 + + @classmethod + def __subclasshook__(cls, C): + if cls is Hashable: + return _check_methods(C, "__hash__") + return NotImplemented + + +class Awaitable(metaclass=ABCMeta): + + __slots__ = () + + @abstractmethod + def __await__(self): + yield + + @classmethod + def __subclasshook__(cls, C): + if cls is Awaitable: + return _check_methods(C, "__await__") + return NotImplemented + + __class_getitem__ = classmethod(GenericAlias) + + +class Coroutine(Awaitable): + + __slots__ = () + + @abstractmethod + def send(self, value): + """Send a value into the coroutine. + Return next yielded value or raise StopIteration. + """ + raise StopIteration + + @abstractmethod + def throw(self, typ, val=None, tb=None): + """Raise an exception in the coroutine. + Return next yielded value or raise StopIteration. + """ + if val is None: + if tb is None: + raise typ + val = typ() + if tb is not None: + val = val.with_traceback(tb) + raise val + + def close(self): + """Raise GeneratorExit inside coroutine. + """ + try: + self.throw(GeneratorExit) + except (GeneratorExit, StopIteration): + pass + else: + raise RuntimeError("coroutine ignored GeneratorExit") + + @classmethod + def __subclasshook__(cls, C): + if cls is Coroutine: + return _check_methods(C, '__await__', 'send', 'throw', 'close') + return NotImplemented + + +Coroutine.register(coroutine) + + +class AsyncIterable(metaclass=ABCMeta): + + __slots__ = () + + @abstractmethod + def __aiter__(self): + return AsyncIterator() + + @classmethod + def __subclasshook__(cls, C): + if cls is AsyncIterable: + return _check_methods(C, "__aiter__") + return NotImplemented + + __class_getitem__ = classmethod(GenericAlias) + + +class AsyncIterator(AsyncIterable): + + __slots__ = () + + @abstractmethod + async def __anext__(self): + """Return the next item or raise StopAsyncIteration when exhausted.""" + raise StopAsyncIteration + + def __aiter__(self): + return self + + @classmethod + def __subclasshook__(cls, C): + if cls is AsyncIterator: + return _check_methods(C, "__anext__", "__aiter__") + return NotImplemented + + +class AsyncGenerator(AsyncIterator): + + __slots__ = () + + async def __anext__(self): + """Return the next item from the asynchronous generator. + When exhausted, raise StopAsyncIteration. + """ + return await self.asend(None) + + @abstractmethod + async def asend(self, value): + """Send a value into the asynchronous generator. + Return next yielded value or raise StopAsyncIteration. + """ + raise StopAsyncIteration + + @abstractmethod + async def athrow(self, typ, val=None, tb=None): + """Raise an exception in the asynchronous generator. + Return next yielded value or raise StopAsyncIteration. + """ + if val is None: + if tb is None: + raise typ + val = typ() + if tb is not None: + val = val.with_traceback(tb) + raise val + + async def aclose(self): + """Raise GeneratorExit inside coroutine. + """ + try: + await self.athrow(GeneratorExit) + except (GeneratorExit, StopAsyncIteration): + pass + else: + raise RuntimeError("asynchronous generator ignored GeneratorExit") + + @classmethod + def __subclasshook__(cls, C): + if cls is AsyncGenerator: + return _check_methods(C, '__aiter__', '__anext__', + 'asend', 'athrow', 'aclose') + return NotImplemented + + +AsyncGenerator.register(async_generator) + + +class Iterable(metaclass=ABCMeta): + + __slots__ = () + + @abstractmethod + def __iter__(self): + while False: + yield None + + @classmethod + def __subclasshook__(cls, C): + if cls is Iterable: + return _check_methods(C, "__iter__") + return NotImplemented + + __class_getitem__ = classmethod(GenericAlias) + + +class Iterator(Iterable): + + __slots__ = () + + @abstractmethod + def __next__(self): + 'Return the next item from the iterator. When exhausted, raise StopIteration' + raise StopIteration + + def __iter__(self): + return self + + @classmethod + def __subclasshook__(cls, C): + if cls is Iterator: + return _check_methods(C, '__iter__', '__next__') + return NotImplemented + + +Iterator.register(bytes_iterator) +Iterator.register(bytearray_iterator) +#Iterator.register(callable_iterator) +Iterator.register(dict_keyiterator) +Iterator.register(dict_valueiterator) +Iterator.register(dict_itemiterator) +Iterator.register(list_iterator) +Iterator.register(list_reverseiterator) +Iterator.register(range_iterator) +Iterator.register(longrange_iterator) +Iterator.register(set_iterator) +Iterator.register(str_iterator) +Iterator.register(tuple_iterator) +Iterator.register(zip_iterator) + + +class Reversible(Iterable): + + __slots__ = () + + @abstractmethod + def __reversed__(self): + while False: + yield None + + @classmethod + def __subclasshook__(cls, C): + if cls is Reversible: + return _check_methods(C, "__reversed__", "__iter__") + return NotImplemented + + +class Generator(Iterator): + + __slots__ = () + + def __next__(self): + """Return the next item from the generator. + When exhausted, raise StopIteration. + """ + return self.send(None) + + @abstractmethod + def send(self, value): + """Send a value into the generator. + Return next yielded value or raise StopIteration. + """ + raise StopIteration + + @abstractmethod + def throw(self, typ, val=None, tb=None): + """Raise an exception in the generator. + Return next yielded value or raise StopIteration. + """ + if val is None: + if tb is None: + raise typ + val = typ() + if tb is not None: + val = val.with_traceback(tb) + raise val + + def close(self): + """Raise GeneratorExit inside generator. + """ + try: + self.throw(GeneratorExit) + except (GeneratorExit, StopIteration): + pass + else: + raise RuntimeError("generator ignored GeneratorExit") + + @classmethod + def __subclasshook__(cls, C): + if cls is Generator: + return _check_methods(C, '__iter__', '__next__', + 'send', 'throw', 'close') + return NotImplemented + + +Generator.register(generator) + + +class Sized(metaclass=ABCMeta): + + __slots__ = () + + @abstractmethod + def __len__(self): + return 0 + + @classmethod + def __subclasshook__(cls, C): + if cls is Sized: + return _check_methods(C, "__len__") + return NotImplemented + + +class Container(metaclass=ABCMeta): + + __slots__ = () + + @abstractmethod + def __contains__(self, x): + return False + + @classmethod + def __subclasshook__(cls, C): + if cls is Container: + return _check_methods(C, "__contains__") + return NotImplemented + + __class_getitem__ = classmethod(GenericAlias) + + +class Collection(Sized, Iterable, Container): + + __slots__ = () + + @classmethod + def __subclasshook__(cls, C): + if cls is Collection: + return _check_methods(C, "__len__", "__iter__", "__contains__") + return NotImplemented + + +class Buffer(metaclass=ABCMeta): + + __slots__ = () + + @abstractmethod + def __buffer__(self, flags: int, /) -> memoryview: + raise NotImplementedError + + @classmethod + def __subclasshook__(cls, C): + if cls is Buffer: + return _check_methods(C, "__buffer__") + return NotImplemented + + +class _CallableGenericAlias(GenericAlias): + """ Represent `Callable[argtypes, resulttype]`. + + This sets ``__args__`` to a tuple containing the flattened ``argtypes`` + followed by ``resulttype``. + + Example: ``Callable[[int, str], float]`` sets ``__args__`` to + ``(int, str, float)``. + """ + + __slots__ = () + + def __new__(cls, origin, args): + if not (isinstance(args, tuple) and len(args) == 2): + raise TypeError( + "Callable must be used as Callable[[arg, ...], result].") + t_args, t_result = args + if isinstance(t_args, (tuple, list)): + args = (*t_args, t_result) + elif not _is_param_expr(t_args): + raise TypeError(f"Expected a list of types, an ellipsis, " + f"ParamSpec, or Concatenate. Got {t_args}") + return super().__new__(cls, origin, args) + + def __repr__(self): + if len(self.__args__) == 2 and _is_param_expr(self.__args__[0]): + return super().__repr__() + return (f'collections.abc.Callable' + f'[[{", ".join([_type_repr(a) for a in self.__args__[:-1]])}], ' + f'{_type_repr(self.__args__[-1])}]') + + def __reduce__(self): + args = self.__args__ + if not (len(args) == 2 and _is_param_expr(args[0])): + args = list(args[:-1]), args[-1] + return _CallableGenericAlias, (Callable, args) + + def __getitem__(self, item): + # Called during TypeVar substitution, returns the custom subclass + # rather than the default types.GenericAlias object. Most of the + # code is copied from typing's _GenericAlias and the builtin + # types.GenericAlias. + if not isinstance(item, tuple): + item = (item,) + + new_args = super().__getitem__(item).__args__ + + # args[0] occurs due to things like Z[[int, str, bool]] from PEP 612 + if not isinstance(new_args[0], (tuple, list)): + t_result = new_args[-1] + t_args = new_args[:-1] + new_args = (t_args, t_result) + return _CallableGenericAlias(Callable, tuple(new_args)) + +def _is_param_expr(obj): + """Checks if obj matches either a list of types, ``...``, ``ParamSpec`` or + ``_ConcatenateGenericAlias`` from typing.py + """ + if obj is Ellipsis: + return True + if isinstance(obj, list): + return True + obj = type(obj) + names = ('ParamSpec', '_ConcatenateGenericAlias') + return obj.__module__ == 'typing' and any(obj.__name__ == name for name in names) + +def _type_repr(obj): + """Return the repr() of an object, special-casing types (internal helper). + + Copied from :mod:`typing` since collections.abc + shouldn't depend on that module. + (Keep this roughly in sync with the typing version.) + """ + if isinstance(obj, type): + if obj.__module__ == 'builtins': + return obj.__qualname__ + return f'{obj.__module__}.{obj.__qualname__}' + if obj is Ellipsis: + return '...' + if isinstance(obj, FunctionType): + return obj.__name__ + return repr(obj) + + +class Callable(metaclass=ABCMeta): + + __slots__ = () + + @abstractmethod + def __call__(self, *args, **kwds): + return False + + @classmethod + def __subclasshook__(cls, C): + if cls is Callable: + return _check_methods(C, "__call__") + return NotImplemented + + __class_getitem__ = classmethod(_CallableGenericAlias) + + +### SETS ### + + +class Set(Collection): + """A set is a finite, iterable container. + + This class provides concrete generic implementations of all + methods except for __contains__, __iter__ and __len__. + + To override the comparisons (presumably for speed, as the + semantics are fixed), redefine __le__ and __ge__, + then the other operations will automatically follow suit. + """ + + __slots__ = () + + def __le__(self, other): + if not isinstance(other, Set): + return NotImplemented + if len(self) > len(other): + return False + for elem in self: + if elem not in other: + return False + return True + + def __lt__(self, other): + if not isinstance(other, Set): + return NotImplemented + return len(self) < len(other) and self.__le__(other) + + def __gt__(self, other): + if not isinstance(other, Set): + return NotImplemented + return len(self) > len(other) and self.__ge__(other) + + def __ge__(self, other): + if not isinstance(other, Set): + return NotImplemented + if len(self) < len(other): + return False + for elem in other: + if elem not in self: + return False + return True + + def __eq__(self, other): + if not isinstance(other, Set): + return NotImplemented + return len(self) == len(other) and self.__le__(other) + + @classmethod + def _from_iterable(cls, it): + '''Construct an instance of the class from any iterable input. + + Must override this method if the class constructor signature + does not accept an iterable for an input. + ''' + return cls(it) + + def __and__(self, other): + if not isinstance(other, Iterable): + return NotImplemented + return self._from_iterable(value for value in other if value in self) + + __rand__ = __and__ + + def isdisjoint(self, other): + 'Return True if two sets have a null intersection.' + for value in other: + if value in self: + return False + return True + + def __or__(self, other): + if not isinstance(other, Iterable): + return NotImplemented + chain = (e for s in (self, other) for e in s) + return self._from_iterable(chain) + + __ror__ = __or__ + + def __sub__(self, other): + if not isinstance(other, Set): + if not isinstance(other, Iterable): + return NotImplemented + other = self._from_iterable(other) + return self._from_iterable(value for value in self + if value not in other) + + def __rsub__(self, other): + if not isinstance(other, Set): + if not isinstance(other, Iterable): + return NotImplemented + other = self._from_iterable(other) + return self._from_iterable(value for value in other + if value not in self) + + def __xor__(self, other): + if not isinstance(other, Set): + if not isinstance(other, Iterable): + return NotImplemented + other = self._from_iterable(other) + return (self - other) | (other - self) + + __rxor__ = __xor__ + + def _hash(self): + """Compute the hash value of a set. + + Note that we don't define __hash__: not all sets are hashable. + But if you define a hashable set type, its __hash__ should + call this function. + + This must be compatible __eq__. + + All sets ought to compare equal if they contain the same + elements, regardless of how they are implemented, and + regardless of the order of the elements; so there's not much + freedom for __eq__ or __hash__. We match the algorithm used + by the built-in frozenset type. + """ + MAX = sys.maxsize + MASK = 2 * MAX + 1 + n = len(self) + h = 1927868237 * (n + 1) + h &= MASK + for x in self: + hx = hash(x) + h ^= (hx ^ (hx << 16) ^ 89869747) * 3644798167 + h &= MASK + h ^= (h >> 11) ^ (h >> 25) + h = h * 69069 + 907133923 + h &= MASK + if h > MAX: + h -= MASK + 1 + if h == -1: + h = 590923713 + return h + + +Set.register(frozenset) + + +class MutableSet(Set): + """A mutable set is a finite, iterable container. + + This class provides concrete generic implementations of all + methods except for __contains__, __iter__, __len__, + add(), and discard(). + + To override the comparisons (presumably for speed, as the + semantics are fixed), all you have to do is redefine __le__ and + then the other operations will automatically follow suit. + """ + + __slots__ = () + + @abstractmethod + def add(self, value): + """Add an element.""" + raise NotImplementedError + + @abstractmethod + def discard(self, value): + """Remove an element. Do not raise an exception if absent.""" + raise NotImplementedError + + def remove(self, value): + """Remove an element. If not a member, raise a KeyError.""" + if value not in self: + raise KeyError(value) + self.discard(value) + + def pop(self): + """Return the popped value. Raise KeyError if empty.""" + it = iter(self) + try: + value = next(it) + except StopIteration: + raise KeyError from None + self.discard(value) + return value + + def clear(self): + """This is slow<|im_end|> +<|im_start|>assistant + + + + +Based on the code provided, here is an analysis and summary of the Python standard library modules included in the snippet. + +### 1. `__future__.py` +**Purpose:** This module records "phased-in incompatible language changes." It allows developers to enable future Python features in current versions using `from __ +--- +info: graphs: 1 captured (4 ms each), 61 of 63 rounds replayed diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/logs/rewind-exact-nocache.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/logs/rewind-exact-nocache.log new file mode 100644 index 0000000000..e69de29bb2 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/logs/rewind-exact.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/logs/rewind-exact.log new file mode 100644 index 0000000000..a758f3b329 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/logs/rewind-exact.log @@ -0,0 +1,17 @@ +PASS rewind turn 1, drafts on: 0 prompt tokens from kept states +PASS rewind turn 2, drafts on: 10176 prompt tokens from kept states +PASS rewind turn 3, drafts on: 10240 prompt tokens from kept states +PASS rewind regenerate turn 3, drafts on: 10240 prompt tokens from kept states +PASS rewind edit turn 3, drafts on: 10240 prompt tokens from kept states +PASS rewind delete turn 3, then turn 4, drafts on: 10240 prompt tokens from kept states +PASS rewind edit turn 1, drafts on: 10176 prompt tokens from kept states +PASS rewind turn 2 again, drafts on: 10240 prompt tokens from kept states +PASS rewind turn 1, drafts off: 10176 prompt tokens from kept states +PASS rewind turn 2, drafts off: 10240 prompt tokens from kept states +PASS rewind turn 3, drafts off: 10240 prompt tokens from kept states +PASS rewind regenerate turn 3, drafts off: 10240 prompt tokens from kept states +PASS rewind edit turn 3, drafts off: 10240 prompt tokens from kept states +PASS rewind delete turn 3, then turn 4, drafts off: 10240 prompt tokens from kept states +PASS rewind edit turn 1, drafts off: 10176 prompt tokens from kept states +PASS rewind turn 2 again, drafts off: 10240 prompt tokens from kept states +rewind PASS: 0 differing replies diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/logs/serve-cancel-exact.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/logs/serve-cancel-exact.log new file mode 100644 index 0000000000..77962f8a9b --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/logs/serve-cancel-exact.log @@ -0,0 +1,4 @@ +ok cancel 0: the next short request took 0.62 s (alone 0.55 s) +ok cancel 1: the next short request took 0.62 s (alone 0.55 s) +ok cancel 2: the next short request took 0.60 s (alone 0.55 s) +failed 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/logs/serve-check-exact.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/logs/serve-check-exact.log new file mode 100644 index 0000000000..a0dc95eeb3 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/logs/serve-check-exact.log @@ -0,0 +1,16 @@ +ok greedy: drafted == serial +ok greedy: solo == together +ok greedy: serial together == serial solo +ok greedy: the same twice +ok greedy: decoders unchanged by a long prompt +ok greedy: long prompt among decoders == alone +ok greedy: serial long prompt among decoders == alone +ok t0.8: drafted == serial +ok t0.8: solo == together +ok t0.8: serial together == serial solo +ok t0.8: the same twice +ok t0.8: decoders unchanged by a long prompt +ok t0.8: long prompt among decoders == alone +ok t0.8: serial long prompt among decoders == alone +ok resumed == fresh (cached {'cached_tokens': 0}) +failed 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/logs/server-ex-exact-nocache.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/logs/server-ex-exact-nocache.log new file mode 100644 index 0000000000..adc7d6acb3 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/logs/server-ex-exact-nocache.log @@ -0,0 +1,45 @@ +[tensorfold] HIP rank 0 of 1: policy matrix=auto,attention=auto,kernels=auto,graphs=auto,prefill_step=4096,fill_rows=512,mtp_depth=gated; mtp drafts 7 under 0.9, 8 snapshots +info: lane costs ms by window rows 1:25.28 2:29.66 3:34.70 4:38.25 5:43.17 6:46.61 7:49.87 8:53.51; head step 1.287 +[tensorfold] open-file limit raised: soft 1024 -> 524288 +warning: libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 82.15 GiB on the device, 4 streams of 32832 positions, 1.09 GiB each; prompts in 4096-row chunks +[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: MTP + copies; context: 32768; loaded in 37.5s) +[tensorfold] 127.0.0.1 "GET /health HTTP/1.1" 200 - +[tensorfold] done chatcmpl-d1f77e04500462564374bacd28fc4eb1 prompt=10219 cached=0 thinking=False effort=none tokens=11 sha=eea964a89e62 finish=stop rounds=3 accepted=11/12 ttft=18.558 decode=0.188 elapsed=18.746 queued=0.000 tok/s=53.1 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-bcb27e22d5fc24ea74991246e68e5500 prompt=10248 cached=0 thinking=False effort=none tokens=13 sha=7e4bf5aba972 finish=stop rounds=3 accepted=9/16 ttft=18.608 decode=0.219 elapsed=18.827 queued=0.000 tok/s=54.7 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-38e6d8e8b792a1843ba44640d6d7d6c8 prompt=10281 cached=0 thinking=False effort=none tokens=48 sha=e7287d6bf366 finish=length rounds=17 accepted=31/40 ttft=18.697 decode=0.981 elapsed=19.677 queued=0.000 tok/s=47.9 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-14510cd468aa8f1fe4d89689b97ecc5e prompt=10281 cached=0 thinking=False effort=none tokens=48 sha=e7287d6bf366 finish=length rounds=17 accepted=31/40 ttft=18.714 decode=1.011 elapsed=19.725 queued=0.000 tok/s=46.5 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-6ba85ee47971a938ce56431d7338e6eb prompt=10281 cached=0 thinking=False effort=none tokens=48 sha=55e1d46d0689 finish=length rounds=21 accepted=27/41 ttft=18.753 decode=1.097 elapsed=19.850 queued=0.000 tok/s=42.8 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-f83e24455a034904467619e2aa2fa844 prompt=10279 cached=0 thinking=False effort=none tokens=14 sha=9537be85f86c finish=stop rounds=4 accepted=12/20 ttft=18.745 decode=0.371 elapsed=19.115 queued=0.000 tok/s=35.1 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-808211de9a40ae8b3f1a720cd0e2c670 prompt=10219 cached=0 thinking=False effort=none tokens=13 sha=86effbb58f5b finish=stop rounds=5 accepted=11/13 ttft=18.655 decode=0.262 elapsed=18.917 queued=0.000 tok/s=45.8 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-fd6899ec32eae079ec10362c3a655592 prompt=10248 cached=0 thinking=False effort=none tokens=13 sha=7e4bf5aba972 finish=stop rounds=3 accepted=9/16 ttft=18.772 decode=0.318 elapsed=19.089 queued=0.000 tok/s=37.8 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-5ca345f5c50f029d444969545441b1d3 prompt=10219 cached=0 thinking=False effort=none tokens=11 sha=eea964a89e62 finish=stop rounds=10 accepted=0/0 ttft=18.554 decode=0.276 elapsed=18.831 queued=0.000 tok/s=36.2 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-f84d708b00f6047db996fbbff37e91a8 prompt=10248 cached=0 thinking=False effort=none tokens=13 sha=7e4bf5aba972 finish=stop rounds=12 accepted=0/0 ttft=18.647 decode=0.332 elapsed=18.980 queued=0.000 tok/s=36.1 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-20fed9a2eebe185e54afb09e3e15ad32 prompt=10281 cached=0 thinking=False effort=none tokens=48 sha=e7287d6bf366 finish=length rounds=47 accepted=0/0 ttft=18.708 decode=1.353 elapsed=20.061 queued=0.000 tok/s=34.7 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-408c8b4ef358471d9cd738c294098094 prompt=10281 cached=0 thinking=False effort=none tokens=48 sha=e7287d6bf366 finish=length rounds=47 accepted=0/0 ttft=18.727 decode=1.306 elapsed=20.032 queued=0.000 tok/s=36.0 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-67eb654abfc3a94aa1375adb9b2a6eeb prompt=10281 cached=0 thinking=False effort=none tokens=48 sha=55e1d46d0689 finish=length rounds=47 accepted=0/0 ttft=18.801 decode=1.303 elapsed=20.104 queued=0.000 tok/s=36.1 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-fd77dd60307c0984e43ab25a012bbbca prompt=10279 cached=0 thinking=False effort=none tokens=14 sha=9537be85f86c finish=stop rounds=13 accepted=0/0 ttft=18.756 decode=0.360 elapsed=19.115 queued=0.000 tok/s=36.2 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-72e349dea9964107b9568d2d023c4165 prompt=10219 cached=0 thinking=False effort=none tokens=13 sha=86effbb58f5b finish=stop rounds=12 accepted=0/0 ttft=18.808 decode=0.333 elapsed=19.141 queued=0.000 tok/s=36.0 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-8f9f4dda5d2ec4ad89541adbb00447d3 prompt=10248 cached=0 thinking=False effort=none tokens=13 sha=7e4bf5aba972 finish=stop rounds=12 accepted=0/0 ttft=18.672 decode=0.352 elapsed=19.024 queued=0.000 tok/s=34.1 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /memory HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /metrics HTTP/1.1" 200 - +[tensorfold] shutting down (SIGTERM): draining: new requests get 503; 0 request(s) in progress may finish within 20.0 s +[tensorfold] shutting down: drained +info: graphs: 8 captured (18 ms each), 337 of 353 rounds replayed +[tensorfold] shutting down: stopped diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/logs/server-ex-exact.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/logs/server-ex-exact.log new file mode 100644 index 0000000000..dd6a3cacea --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/logs/server-ex-exact.log @@ -0,0 +1,266 @@ +[tensorfold] HIP rank 0 of 1: policy matrix=auto,attention=auto,kernels=auto,graphs=auto,prefill_step=4096,fill_rows=512,mtp_depth=gated; mtp drafts 7 under 0.9, 8 snapshots +info: lane costs ms by window rows 1:25.65 2:29.58 3:34.72 4:38.11 5:44.69 6:46.45 7:49.67 8:55.62; head step 1.289 +[tensorfold] open-file limit raised: soft 1024 -> 524288 +warning: libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 82.15 GiB on the device, 4 streams of 32832 positions, 1.09 GiB each; prompts in 4096-row chunks +[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: MTP + copies; context: 32768; loaded in 29.6s) +[tensorfold] 127.0.0.1 "GET /health HTTP/1.1" 200 - +info: prompt cache: 20 tokens, resumed at 0, kept 0; 0 states, 0 MiB and 0 MiB spare of 1024 MiB (hits 0, misses 1, evicted 0, refused 0, failed 0) +[tensorfold] done chatcmpl-e8968625994720e652bdc43ffab782a9 prompt=20 cached=0 thinking=False effort=none tokens=64 sha=bf3402132772 finish=length rounds=63 accepted=0/0 ttft=0.127 decode=1.604 elapsed=1.731 queued=0.000 tok/s=39.3 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 23 tokens, resumed at 0, kept 0; 0 states, 0 MiB and 0 MiB spare of 1024 MiB (hits 0, misses 2, evicted 0, refused 0, failed 0) +[tensorfold] done chatcmpl-4e4e43fd9297edf9c89ec94ff9f143a7 prompt=23 cached=0 thinking=False effort=none tokens=43 sha=005a2bec0a1b finish=stop rounds=42 accepted=0/0 ttft=0.132 decode=1.071 elapsed=1.203 queued=0.000 tok/s=39.2 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 23 tokens, resumed at 0, kept 0; 0 states, 0 MiB and 0 MiB spare of 1024 MiB (hits 0, misses 3, evicted 0, refused 0, failed 0) +[tensorfold] done chatcmpl-284d83bb5192d8e7ec6438649be475d0 prompt=23 cached=0 thinking=False effort=none tokens=47 sha=c8e6705737f3 finish=stop rounds=46 accepted=0/0 ttft=0.135 decode=1.175 elapsed=1.310 queued=0.000 tok/s=39.1 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 20 tokens, resumed at 0, kept 0; 0 states, 0 MiB and 0 MiB spare of 1024 MiB (hits 0, misses 4, evicted 0, refused 0, failed 0) +[tensorfold] done chatcmpl-037524185342d176df7c339df095bb83 prompt=20 cached=0 thinking=False effort=none tokens=64 sha=424bb4882c66 finish=length rounds=63 accepted=0/0 ttft=0.123 decode=1.605 elapsed=1.728 queued=0.000 tok/s=39.3 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 20 tokens, resumed at 0, kept 0; 0 states, 0 MiB and 0 MiB spare of 1024 MiB (hits 0, misses 5, evicted 0, refused 0, failed 0) +[tensorfold] done chatcmpl-5e3c6bac5a6c1316441353d1515b5130 prompt=20 cached=0 thinking=False effort=none tokens=64 sha=bf3402132772 finish=length rounds=33 accepted=31/61 ttft=0.129 decode=1.351 elapsed=1.480 queued=0.000 tok/s=46.6 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 23 tokens, resumed at 0, kept 0; 0 states, 0 MiB and 0 MiB spare of 1024 MiB (hits 0, misses 6, evicted 0, refused 0, failed 0) +[tensorfold] done chatcmpl-cb8d44b1c977cf5439c12396788f4723 prompt=23 cached=0 thinking=False effort=none tokens=43 sha=005a2bec0a1b finish=stop rounds=6 accepted=40/41 ttft=0.143 decode=0.433 elapsed=0.576 queued=0.000 tok/s=97.0 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 23 tokens, resumed at 0, kept 0; 0 states, 0 MiB and 0 MiB spare of 1024 MiB (hits 0, misses 7, evicted 0, refused 0, failed 0) +[tensorfold] done chatcmpl-44ef8c22e5fd83ed158f1226e68c0226 prompt=23 cached=0 thinking=False effort=none tokens=47 sha=c8e6705737f3 finish=stop rounds=16 accepted=34/44 ttft=0.137 decode=0.773 elapsed=0.910 queued=0.000 tok/s=59.5 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 20 tokens, resumed at 0, kept 0; 0 states, 0 MiB and 0 MiB spare of 1024 MiB (hits 0, misses 8, evicted 0, refused 0, failed 0) +[tensorfold] done chatcmpl-beedccda29b6cdc4410cd1c23b09c979 prompt=20 cached=0 thinking=False effort=none tokens=64 sha=424bb4882c66 finish=length rounds=12 accepted=51/55 ttft=0.124 decode=0.698 elapsed=0.821 queued=0.000 tok/s=90.3 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 20 tokens, resumed at 0, kept 0; 0 states, 0 MiB and 0 MiB spare of 1024 MiB (hits 0, misses 9, evicted 0, refused 0, failed 0) +info: prompt cache: 20 tokens, resumed at 0, kept 0; 0 states, 0 MiB and 0 MiB spare of 1024 MiB (hits 0, misses 10, evicted 0, refused 0, failed 0) +info: prompt cache: 23 tokens, resumed at 0, kept 0; 0 states, 0 MiB and 0 MiB spare of 1024 MiB (hits 0, misses 11, evicted 0, refused 0, failed 0) +info: prompt cache: 23 tokens, resumed at 0, kept 0; 0 states, 0 MiB and 0 MiB spare of 1024 MiB (hits 0, misses 12, evicted 0, refused 0, failed 0) +[tensorfold] done chatcmpl-4fc02a0c32bdb2ab1dd5ff1e4800acb9 prompt=23 cached=0 thinking=False effort=none tokens=43 sha=005a2bec0a1b finish=stop rounds=6 accepted=40/41 ttft=0.510 decode=1.188 elapsed=1.698 queued=0.128 tok/s=35.3 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-bf968ac64d46575ca1d615a804d7d0db prompt=20 cached=0 thinking=False effort=none tokens=64 sha=424bb4882c66 finish=length rounds=12 accepted=51/55 ttft=0.334 decode=2.131 elapsed=2.465 queued=0.128 tok/s=29.6 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-097164da29e16d1c7c6f3a8a04f31bda prompt=23 cached=0 thinking=False effort=none tokens=47 sha=c8e6705737f3 finish=stop rounds=16 accepted=34/44 ttft=0.672 decode=2.088 elapsed=2.760 queued=0.128 tok/s=22.0 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-9c69fec950d26ee5fce8fffb29eb3879 prompt=20 cached=0 thinking=False effort=none tokens=64 sha=bf3402132772 finish=length rounds=33 accepted=31/61 ttft=0.129 decode=3.295 elapsed=3.424 queued=0.000 tok/s=19.1 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 20 tokens, resumed at 0, kept 0; 0 states, 0 MiB and 0 MiB spare of 1024 MiB (hits 0, misses 13, evicted 0, refused 0, failed 0) +info: prompt cache: 20 tokens, resumed at 0, kept 0; 0 states, 0 MiB and 0 MiB spare of 1024 MiB (hits 0, misses 14, evicted 0, refused 0, failed 0) +info: prompt cache: 23 tokens, resumed at 0, kept 0; 0 states, 0 MiB and 0 MiB spare of 1024 MiB (hits 0, misses 15, evicted 0, refused 0, failed 0) +info: prompt cache: 23 tokens, resumed at 0, kept 0; 0 states, 0 MiB and 0 MiB spare of 1024 MiB (hits 0, misses 16, evicted 0, refused 0, failed 0) +[tensorfold] done chatcmpl-0c029a3430692b1b5591e5f4a7db3fcf prompt=23 cached=0 thinking=False effort=none tokens=43 sha=005a2bec0a1b finish=stop rounds=42 accepted=0/0 ttft=0.521 decode=2.328 elapsed=2.849 queued=0.123 tok/s=18.0 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-22b4396946172f811d5dab51b4097e64 prompt=23 cached=0 thinking=False effort=none tokens=47 sha=c8e6705737f3 finish=stop rounds=46 accepted=0/0 ttft=0.390 decode=2.647 elapsed=3.037 queued=0.123 tok/s=17.4 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-698f328fb3b18126de8d4d6a5b80feb9 prompt=20 cached=0 thinking=False effort=none tokens=64 sha=bf3402132772 finish=length rounds=63 accepted=0/0 ttft=0.124 decode=3.521 elapsed=3.645 queued=0.000 tok/s=17.9 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-92ef95939a216e5e6a014837c93ebfca prompt=20 cached=0 thinking=False effort=none tokens=64 sha=424bb4882c66 finish=length rounds=63 accepted=0/0 ttft=0.257 decode=3.388 elapsed=3.645 queued=0.123 tok/s=18.6 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 20 tokens, resumed at 0, kept 0; 0 states, 0 MiB and 0 MiB spare of 1024 MiB (hits 0, misses 17, evicted 0, refused 0, failed 0) +[tensorfold] done chatcmpl-a36fcecfe60da70f8d7b77153adf89fd prompt=20 cached=0 thinking=False effort=none tokens=64 sha=bf3402132772 finish=length rounds=33 accepted=31/61 ttft=0.127 decode=1.364 elapsed=1.491 queued=0.000 tok/s=46.2 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 23 tokens, resumed at 0, kept 0; 0 states, 0 MiB and 0 MiB spare of 1024 MiB (hits 0, misses 18, evicted 0, refused 0, failed 0) +[tensorfold] done chatcmpl-418a6deec48a91af4d03097829ee9e9e prompt=23 cached=0 thinking=False effort=none tokens=43 sha=005a2bec0a1b finish=stop rounds=6 accepted=40/41 ttft=0.143 decode=0.434 elapsed=0.576 queued=0.000 tok/s=96.8 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 23 tokens, resumed at 0, kept 0; 0 states, 0 MiB and 0 MiB spare of 1024 MiB (hits 0, misses 19, evicted 0, refused 0, failed 0) +[tensorfold] done chatcmpl-6782ee1e5e308d90b30b549e3b35b429 prompt=23 cached=0 thinking=False effort=none tokens=47 sha=c8e6705737f3 finish=stop rounds=16 accepted=34/44 ttft=0.138 decode=0.764 elapsed=0.902 queued=0.000 tok/s=60.2 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 20 tokens, resumed at 0, kept 0; 0 states, 0 MiB and 0 MiB spare of 1024 MiB (hits 0, misses 20, evicted 0, refused 0, failed 0) +[tensorfold] done chatcmpl-09c95bcfc91a9a2e8a60acf95effb613 prompt=20 cached=0 thinking=False effort=none tokens=64 sha=424bb4882c66 finish=length rounds=12 accepted=51/55 ttft=0.125 decode=0.700 elapsed=0.825 queued=0.000 tok/s=90.0 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 20 tokens, resumed at 0, kept 0; 0 states, 0 MiB and 0 MiB spare of 1024 MiB (hits 0, misses 21, evicted 0, refused 0, failed 0) +info: prompt cache: 23 tokens, resumed at 0, kept 0; 0 states, 0 MiB and 0 MiB spare of 1024 MiB (hits 0, misses 22, evicted 0, refused 0, failed 0) +info: prompt cache: 23 tokens, resumed at 0, kept 0; 0 states, 0 MiB and 0 MiB spare of 1024 MiB (hits 0, misses 23, evicted 0, refused 0, failed 0) +[tensorfold] done chatcmpl-450fc5a969743fcf74f8c7de4b00e055 prompt=23 cached=0 thinking=False effort=none tokens=43 sha=005a2bec0a1b finish=stop rounds=6 accepted=40/41 ttft=0.273 decode=5.216 elapsed=5.489 queued=0.129 tok/s=8.1 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 3413 tokens, resumed at 0, kept 1; 1 states, 212 MiB and 0 MiB spare of 1024 MiB (hits 0, misses 24, evicted 0, refused 0, failed 0) +[tensorfold] done chatcmpl-174d5cef2c7182f06622a3adf12b72bc prompt=23 cached=0 thinking=False effort=none tokens=47 sha=c8e6705737f3 finish=stop rounds=16 accepted=34/44 ttft=0.411 decode=8.060 elapsed=8.471 queued=0.129 tok/s=5.7 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-3f164105383de577d845f4debb372c8c prompt=20 cached=0 thinking=False effort=none tokens=64 sha=bf3402132772 finish=length rounds=33 accepted=31/61 ttft=0.130 decode=9.609 elapsed=9.738 queued=0.000 tok/s=6.6 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-e2b2f780b5ced821c0e63e23fec334f9 prompt=3413 cached=0 thinking=False effort=none tokens=60 sha=7f4c8846ddc9 finish=stop rounds=28 accepted=31/46 ttft=7.159 decode=2.287 elapsed=9.446 queued=0.111 tok/s=25.8 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 3413 tokens, resumed at 3392, kept 0; 1 states, 212 MiB and 0 MiB spare of 1024 MiB (hits 1, misses 24, evicted 0, refused 0, failed 0) +[tensorfold] done chatcmpl-d242ce4d031de294ee7db5794642df10 prompt=3413 cached=3392 thinking=False effort=none tokens=60 sha=7f4c8846ddc9 finish=stop rounds=28 accepted=31/46 ttft=0.181 decode=1.321 elapsed=1.502 queued=0.000 tok/s=44.7 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 23 tokens, resumed at 0, kept 0; 1 states, 212 MiB and 0 MiB spare of 1024 MiB (hits 1, misses 25, evicted 0, refused 0, failed 0) +info: prompt cache: 20 tokens, resumed at 0, kept 0; 1 states, 212 MiB and 0 MiB spare of 1024 MiB (hits 1, misses 26, evicted 0, refused 0, failed 0) +info: prompt cache: 23 tokens, resumed at 0, kept 0; 1 states, 212 MiB and 0 MiB spare of 1024 MiB (hits 1, misses 27, evicted 0, refused 0, failed 0) +info: prompt cache: 3413 tokens, resumed at 3392, kept 0; 1 states, 212 MiB and 0 MiB spare of 1024 MiB (hits 2, misses 27, evicted 0, refused 0, failed 0) +[tensorfold] done chatcmpl-652faf99c50bc4ed5acef70decd4f0a0 prompt=23 cached=0 thinking=False effort=none tokens=43 sha=005a2bec0a1b finish=stop rounds=42 accepted=0/0 ttft=0.132 decode=2.782 elapsed=2.914 queued=0.000 tok/s=15.1 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-72053ca80032f6a3267a59e6d284a447 prompt=23 cached=0 thinking=False effort=none tokens=47 sha=c8e6705737f3 finish=stop rounds=46 accepted=0/0 ttft=0.387 decode=2.723 elapsed=3.109 queued=0.131 tok/s=16.9 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-2ab375748eb73584dacd697c708cd40b prompt=3413 cached=3392 thinking=False effort=none tokens=60 sha=7f4c8846ddc9 finish=stop rounds=59 accepted=0/0 ttft=0.180 decode=3.229 elapsed=3.409 queued=0.021 tok/s=18.3 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-4e1bf50ab1da0f3d0ee5a4d250198726 prompt=20 cached=0 thinking=False effort=none tokens=64 sha=bf3402132772 finish=length rounds=63 accepted=0/0 ttft=0.253 decode=3.682 elapsed=3.935 queued=0.131 tok/s=17.1 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 20 tokens, resumed at 0, kept 0; 1 states, 212 MiB and 0 MiB spare of 1024 MiB (hits 2, misses 28, evicted 0, refused 0, failed 0) +[tensorfold] done chatcmpl-c983e9c7bca00f05cf8322f3aba9763b prompt=20 cached=0 thinking=False effort=none tokens=64 sha=c0e21e789784 finish=length rounds=63 accepted=0/0 ttft=0.122 decode=1.667 elapsed=1.789 queued=0.000 tok/s=37.8 seed=7 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 23 tokens, resumed at 0, kept 0; 1 states, 212 MiB and 0 MiB spare of 1024 MiB (hits 2, misses 29, evicted 0, refused 0, failed 0) +[tensorfold] done chatcmpl-8e8549b441b8ac9eca79fb25448b60d3 prompt=23 cached=0 thinking=False effort=none tokens=43 sha=005a2bec0a1b finish=stop rounds=42 accepted=0/0 ttft=0.135 decode=1.074 elapsed=1.208 queued=0.000 tok/s=39.1 seed=7 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 23 tokens, resumed at 0, kept 0; 1 states, 212 MiB and 0 MiB spare of 1024 MiB (hits 2, misses 30, evicted 0, refused 0, failed 0) +[tensorfold] done chatcmpl-92abb72c4179fe5e8937a16a473a33a7 prompt=23 cached=0 thinking=False effort=none tokens=48 sha=aa3696ad4413 finish=stop rounds=47 accepted=0/0 ttft=0.135 decode=1.238 elapsed=1.373 queued=0.000 tok/s=38.0 seed=7 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 20 tokens, resumed at 0, kept 0; 1 states, 212 MiB and 0 MiB spare of 1024 MiB (hits 2, misses 31, evicted 0, refused 0, failed 0) +[tensorfold] done chatcmpl-53a9670948ec267d0994e3ad91f647ec prompt=20 cached=0 thinking=False effort=none tokens=64 sha=424bb4882c66 finish=length rounds=63 accepted=0/0 ttft=0.122 decode=1.701 elapsed=1.823 queued=0.000 tok/s=37.0 seed=7 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 20 tokens, resumed at 0, kept 0; 1 states, 212 MiB and 0 MiB spare of 1024 MiB (hits 2, misses 32, evicted 0, refused 0, failed 0) +[tensorfold] done chatcmpl-bd8949ca895ada9b81a1721ce51670fc prompt=20 cached=0 thinking=False effort=none tokens=64 sha=c0e21e789784 finish=length rounds=35 accepted=28/54 ttft=0.126 decode=1.398 elapsed=1.524 queued=0.000 tok/s=45.1 seed=7 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 23 tokens, resumed at 0, kept 0; 1 states, 212 MiB and 0 MiB spare of 1024 MiB (hits 2, misses 33, evicted 0, refused 0, failed 0) +[tensorfold] done chatcmpl-e3c1af88800659ffb80d222ff55da6ab prompt=23 cached=0 thinking=False effort=none tokens=43 sha=005a2bec0a1b finish=stop rounds=6 accepted=40/41 ttft=0.244 decode=0.440 elapsed=0.685 queued=0.000 tok/s=95.4 seed=7 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 23 tokens, resumed at 0, kept 0; 1 states, 212 MiB and 0 MiB spare of 1024 MiB (hits 2, misses 34, evicted 0, refused 0, failed 0) +[tensorfold] done chatcmpl-16d25d9c3f15b7c6ee36f0cf20fd7f34 prompt=23 cached=0 thinking=False effort=none tokens=48 sha=aa3696ad4413 finish=stop rounds=16 accepted=35/39 ttft=0.139 decode=0.817 elapsed=0.957 queued=0.000 tok/s=57.5 seed=7 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 20 tokens, resumed at 0, kept 0; 1 states, 212 MiB and 0 MiB spare of 1024 MiB (hits 2, misses 35, evicted 0, refused 0, failed 0) +[tensorfold] done chatcmpl-c2b97e76e5def98d9e3a5e4396cb1691 prompt=20 cached=0 thinking=False effort=none tokens=64 sha=424bb4882c66 finish=length rounds=12 accepted=51/55 ttft=0.124 decode=0.834 elapsed=0.958 queued=0.000 tok/s=75.6 seed=7 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 20 tokens, resumed at 0, kept 0; 1 states, 212 MiB and 0 MiB spare of 1024 MiB (hits 2, misses 36, evicted 0, refused 0, failed 0) +info: prompt cache: 20 tokens, resumed at 0, kept 0; 1 states, 212 MiB and 0 MiB spare of 1024 MiB (hits 2, misses 37, evicted 0, refused 0, failed 0) +info: prompt cache: 23 tokens, resumed at 0, kept 0; 1 states, 212 MiB and 0 MiB spare of 1024 MiB (hits 2, misses 38, evicted 0, refused 0, failed 0) +info: prompt cache: 23 tokens, resumed at 0, kept 0; 1 states, 212 MiB and 0 MiB spare of 1024 MiB (hits 2, misses 39, evicted 0, refused 0, failed 0) +[tensorfold] done chatcmpl-53235e57a1fd6dedb3f81abf97e8435f prompt=23 cached=0 thinking=False effort=none tokens=43 sha=005a2bec0a1b finish=stop rounds=6 accepted=40/41 ttft=0.537 decode=1.142 elapsed=1.679 queued=0.123 tok/s=36.8 seed=7 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-7007450f3872816224cfc2dee6ac558b prompt=20 cached=0 thinking=False effort=none tokens=64 sha=424bb4882c66 finish=length rounds=12 accepted=51/55 ttft=0.252 decode=2.202 elapsed=2.454 queued=0.123 tok/s=28.6 seed=7 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-b1a0443cf229009df13df4d400d332ad prompt=23 cached=0 thinking=False effort=none tokens=48 sha=aa3696ad4413 finish=stop rounds=16 accepted=35/39 ttft=0.392 decode=2.349 elapsed=2.741 queued=0.123 tok/s=20.0 seed=7 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-e2c74ed9d352a295f837a10bdcfb882d prompt=20 cached=0 thinking=False effort=none tokens=64 sha=c0e21e789784 finish=length rounds=35 accepted=28/54 ttft=0.125 decode=3.374 elapsed=3.499 queued=0.000 tok/s=18.7 seed=7 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 20 tokens, resumed at 0, kept 0; 1 states, 212 MiB and 0 MiB spare of 1024 MiB (hits 2, misses 40, evicted 0, refused 0, failed 0) +info: prompt cache: 20 tokens, resumed at 0, kept 0; 1 states, 212 MiB and 0 MiB spare of 1024 MiB (hits 2, misses 41, evicted 0, refused 0, failed 0) +info: prompt cache: 23 tokens, resumed at 0, kept 0; 1 states, 212 MiB and 0 MiB spare of 1024 MiB (hits 2, misses 42, evicted 0, refused 0, failed 0) +info: prompt cache: 23 tokens, resumed at 0, kept 0; 1 states, 212 MiB and 0 MiB spare of 1024 MiB (hits 2, misses 43, evicted 0, refused 0, failed 0) +[tensorfold] done chatcmpl-c686d8ed7f442b3d7453c7f371ff736e prompt=23 cached=0 thinking=False effort=none tokens=43 sha=005a2bec0a1b finish=stop rounds=42 accepted=0/0 ttft=0.518 decode=2.524 elapsed=3.042 queued=0.123 tok/s=16.6 seed=7 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-4f8333ab7e7e842e65d53c2e4325b727 prompt=23 cached=0 thinking=False effort=none tokens=48 sha=aa3696ad4413 finish=stop rounds=47 accepted=0/0 ttft=0.383 decode=2.887 elapsed=3.270 queued=0.123 tok/s=16.3 seed=7 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-ff21a56bf7b5bcfbdea5d1b38e10ea04 prompt=20 cached=0 thinking=False effort=none tokens=64 sha=c0e21e789784 finish=length rounds=63 accepted=0/0 ttft=0.124 decode=3.831 elapsed=3.955 queued=0.000 tok/s=16.4 seed=7 +[tensorfold] done chatcmpl-bdb63ea93b800bb231947b90ab2037ff prompt=20 cached=0 thinking=False effort=none tokens=64 sha=424bb4882c66 finish=length rounds=63 accepted=0/0 ttft=0.247 decode=3.708 elapsed=3.955 queued=0.123 tok/s=17.0 seed=7 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 20 tokens, resumed at 0, kept 0; 1 states, 212 MiB and 0 MiB spare of 1024 MiB (hits 2, misses 44, evicted 0, refused 0, failed 0) +[tensorfold] done chatcmpl-e2cf2781cc9bc3160383f90fc75d6675 prompt=20 cached=0 thinking=False effort=none tokens=64 sha=c0e21e789784 finish=length rounds=35 accepted=28/54 ttft=0.124 decode=1.412 elapsed=1.536 queued=0.000 tok/s=44.6 seed=7 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 23 tokens, resumed at 0, kept 0; 1 states, 212 MiB and 0 MiB spare of 1024 MiB (hits 2, misses 45, evicted 0, refused 0, failed 0) +[tensorfold] done chatcmpl-9b33328a0f1aaa6cd36f4f8b3efc3fac prompt=23 cached=0 thinking=False effort=none tokens=43 sha=005a2bec0a1b finish=stop rounds=6 accepted=40/41 ttft=0.142 decode=0.578 elapsed=0.721 queued=0.000 tok/s=72.6 seed=7 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 23 tokens, resumed at 0, kept 0; 1 states, 212 MiB and 0 MiB spare of 1024 MiB (hits 2, misses 46, evicted 0, refused 0, failed 0) +[tensorfold] done chatcmpl-144f8198141b158493eaacc0731a91d5 prompt=23 cached=0 thinking=False effort=none tokens=48 sha=aa3696ad4413 finish=stop rounds=16 accepted=35/39 ttft=0.138 decode=0.702 elapsed=0.839 queued=0.000 tok/s=67.0 seed=7 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 20 tokens, resumed at 0, kept 0; 1 states, 212 MiB and 0 MiB spare of 1024 MiB (hits 2, misses 47, evicted 0, refused 0, failed 0) +[tensorfold] done chatcmpl-cd7f40b948b040a3d96e0599d76a0d60 prompt=20 cached=0 thinking=False effort=none tokens=64 sha=424bb4882c66 finish=length rounds=12 accepted=51/55 ttft=0.126 decode=0.810 elapsed=0.936 queued=0.000 tok/s=77.8 seed=7 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 20 tokens, resumed at 0, kept 0; 1 states, 212 MiB and 0 MiB spare of 1024 MiB (hits 2, misses 48, evicted 0, refused 0, failed 0) +info: prompt cache: 23 tokens, resumed at 0, kept 0; 1 states, 212 MiB and 0 MiB spare of 1024 MiB (hits 2, misses 49, evicted 0, refused 0, failed 0) +info: prompt cache: 23 tokens, resumed at 0, kept 0; 1 states, 212 MiB and 0 MiB spare of 1024 MiB (hits 2, misses 50, evicted 0, refused 0, failed 0) +info: prompt cache: 3413 tokens, resumed at 3392, kept 0; 1 states, 212 MiB and 0 MiB spare of 1024 MiB (hits 3, misses 50, evicted 0, refused 0, failed 0) +[tensorfold] done chatcmpl-414842eb3e67c604e38283db1e12e6b3 prompt=23 cached=0 thinking=False effort=none tokens=43 sha=005a2bec0a1b finish=stop rounds=6 accepted=40/41 ttft=0.485 decode=1.305 elapsed=1.790 queued=0.124 tok/s=32.2 seed=7 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-8467c5266e126b3a7fc2aee418ff7d6a prompt=23 cached=0 thinking=False effort=none tokens=48 sha=aa3696ad4413 finish=stop rounds=16 accepted=35/39 ttft=0.265 decode=2.423 elapsed=2.688 queued=0.124 tok/s=19.4 seed=7 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-e73a4a330bd75b1167a9ef1a2127bfca prompt=3413 cached=3392 thinking=False effort=none tokens=45 sha=24e159362742 finish=stop rounds=23 accepted=23/36 ttft=0.301 decode=2.522 elapsed=2.822 queued=0.126 tok/s=17.4 seed=7 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-2844567fc374da9305964d6cd8a7baf9 prompt=20 cached=0 thinking=False effort=none tokens=64 sha=c0e21e789784 finish=length rounds=35 accepted=28/54 ttft=0.127 decode=3.630 elapsed=3.756 queued=0.000 tok/s=17.4 seed=7 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 3413 tokens, resumed at 3392, kept 0; 1 states, 212 MiB and 0 MiB spare of 1024 MiB (hits 4, misses 50, evicted 0, refused 0, failed 0) +[tensorfold] done chatcmpl-2e957c41b1f40a970ad09248d5a9fc79 prompt=3413 cached=3392 thinking=False effort=none tokens=45 sha=24e159362742 finish=stop rounds=23 accepted=23/36 ttft=0.159 decode=1.050 elapsed=1.209 queued=0.000 tok/s=41.9 seed=7 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 20 tokens, resumed at 0, kept 0; 1 states, 212 MiB and 0 MiB spare of 1024 MiB (hits 4, misses 51, evicted 0, refused 0, failed 0) +info: prompt cache: 23 tokens, resumed at 0, kept 0; 1 states, 212 MiB and 0 MiB spare of 1024 MiB (hits 4, misses 52, evicted 0, refused 0, failed 0) +info: prompt cache: 23 tokens, resumed at 0, kept 0; 1 states, 212 MiB and 0 MiB spare of 1024 MiB (hits 4, misses 53, evicted 0, refused 0, failed 0) +info: prompt cache: 3413 tokens, resumed at 3392, kept 0; 1 states, 212 MiB and 0 MiB spare of 1024 MiB (hits 5, misses 53, evicted 0, refused 0, failed 0) +[tensorfold] done chatcmpl-2ead825ec6afcf7776f82eb18a52239d prompt=23 cached=0 thinking=False effort=none tokens=43 sha=005a2bec0a1b finish=stop rounds=42 accepted=0/0 ttft=0.393 decode=2.784 elapsed=3.177 queued=0.121 tok/s=15.1 seed=7 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-80ef309fd83a75d78f81f53cf9d34ce9 prompt=3413 cached=3392 thinking=False effort=none tokens=45 sha=24e159362742 finish=stop rounds=44 accepted=0/0 ttft=0.178 decode=2.690 elapsed=2.867 queued=0.023 tok/s=16.4 seed=7 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-5eb9108ac0407c2ff382ac9bec4ef552 prompt=23 cached=0 thinking=False effort=none tokens=48 sha=aa3696ad4413 finish=stop rounds=47 accepted=0/0 ttft=0.258 decode=3.152 elapsed=3.410 queued=0.121 tok/s=14.9 seed=7 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-9d3c945d7003ac9c82eccd4043f0b6b8 prompt=20 cached=0 thinking=False effort=none tokens=64 sha=c0e21e789784 finish=length rounds=63 accepted=0/0 ttft=0.122 decode=3.695 elapsed=3.817 queued=0.000 tok/s=17.1 seed=7 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 20 tokens, resumed at 0, kept 0; 1 states, 212 MiB and 0 MiB spare of 1024 MiB (hits 5, misses 54, evicted 0, refused 0, failed 0) +[tensorfold] done chatcmpl-92739116caaf382726c83d88652b6421 prompt=20 cached=0 thinking=False effort=none tokens=64 sha=bf3402132772 finish=length rounds=33 accepted=31/61 ttft=0.128 decode=1.384 elapsed=1.512 queued=0.000 tok/s=45.5 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 103 tokens, resumed at 0, kept 1; 2 states, 326 MiB and 0 MiB spare of 1024 MiB (hits 5, misses 55, evicted 0, refused 0, failed 0) +[tensorfold] done chatcmpl-e322e6bfc51a9e6c43b7e31230ead256 prompt=103 cached=0 thinking=False effort=none tokens=11 sha=3a793d464e98 finish=stop rounds=10 accepted=0/0 ttft=0.407 decode=0.254 elapsed=0.661 queued=0.000 tok/s=39.4 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +warning: prompt cache: restore of the kept 64-token state failed for a 103-token prompt (backend refused the restore, RestoreRefused); prefilling from the start +info: prompt cache: 103 tokens, resumed at 0, kept 0; 1 states, 212 MiB and 0 MiB spare of 1024 MiB (hits 5, misses 55, evicted 0, refused 0, failed 1) +[tensorfold] done chatcmpl-7b4667fcbe7b02ec020a7c5eada2bb5e prompt=103 cached=0 thinking=False effort=none tokens=11 sha=3a793d464e98 finish=stop rounds=6 accepted=8/13 ttft=0.264 decode=0.299 elapsed=0.563 queued=0.000 tok/s=33.5 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 20 tokens, resumed at 0, kept 0; 1 states, 212 MiB and 0 MiB spare of 1024 MiB (hits 5, misses 56, evicted 0, refused 0, failed 1) +[tensorfold] done chatcmpl-e5fae045346a1650165ad5e86d1102e3 prompt=20 cached=0 thinking=False effort=none tokens=32 sha=3f3630855924 finish=length rounds=7 accepted=24/32 ttft=0.127 decode=0.409 elapsed=0.536 queued=0.000 tok/s=75.8 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 20 tokens, resumed at 0, kept 0; 1 states, 212 MiB and 0 MiB spare of 1024 MiB (hits 5, misses 57, evicted 0, refused 0, failed 1) +[tensorfold] done chatcmpl-9fa1e6ef78294cc2240b24c0da964db6 prompt=20 cached=0 thinking=False effort=none tokens=32 sha=3f3630855924 finish=length rounds=7 accepted=24/32 ttft=0.124 decode=0.488 elapsed=0.612 queued=0.000 tok/s=63.6 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 20 tokens, resumed at 0, kept 0; 1 states, 212 MiB and 0 MiB spare of 1024 MiB (hits 5, misses 58, evicted 0, refused 0, failed 1) +[tensorfold] done chatcmpl-36e1e3dd7c40a7ef45843544aae03e0b prompt=20 cached=0 thinking=False effort=none tokens=32 sha=3f3630855924 finish=length rounds=7 accepted=24/32 ttft=0.124 decode=0.409 elapsed=0.533 queued=0.000 tok/s=75.8 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 403 - +info: prompt cache: 20 tokens, resumed at 0, kept 0; 1 states, 212 MiB and 0 MiB spare of 1024 MiB (hits 5, misses 59, evicted 0, refused 0, failed 1) +[tensorfold] done chatcmpl-fb3cc8d0e62234ce7468925d383b6c8f prompt=20 cached=0 thinking=False effort=none tokens=32 sha=3f3630855924 finish=length rounds=7 accepted=24/32 ttft=0.128 decode=0.493 elapsed=0.620 queued=0.000 tok/s=62.9 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 403 - +info: prompt cache: 20 tokens, resumed at 0, kept 0; 1 states, 212 MiB and 0 MiB spare of 1024 MiB (hits 5, misses 60, evicted 0, refused 0, failed 1) +[tensorfold] done chatcmpl-7e1fdef485c9919b6d3c459f4bf50d6a prompt=20 cached=0 thinking=False effort=none tokens=32 sha=3f3630855924 finish=length rounds=7 accepted=24/32 ttft=0.127 decode=0.487 elapsed=0.614 queued=0.000 tok/s=63.7 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 403 - +info: prompt cache: 20 tokens, resumed at 0, kept 0; 1 states, 212 MiB and 0 MiB spare of 1024 MiB (hits 5, misses 61, evicted 0, refused 0, failed 1) +[tensorfold] done chatcmpl-46d574bce600eb7c2d30473be2c2d3f5 prompt=20 cached=0 thinking=False effort=none tokens=32 sha=3f3630855924 finish=length rounds=7 accepted=24/32 ttft=0.126 decode=0.470 elapsed=0.596 queued=0.000 tok/s=65.9 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 10219 tokens, resumed at 0, kept 3; 2 states, 807 MiB and 0 MiB spare of 1024 MiB (hits 5, misses 62, evicted 2, refused 0, failed 1) +[tensorfold] done chatcmpl-0aba9c2d85e653b4dbc91a6d0a41f078 prompt=10219 cached=0 thinking=False effort=none tokens=11 sha=eea964a89e62 finish=stop rounds=3 accepted=11/12 ttft=19.008 decode=0.256 elapsed=19.265 queued=0.000 tok/s=39.0 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 10248 tokens, resumed at 10176, kept 1; 2 states, 824 MiB and 0 MiB spare of 1024 MiB (hits 6, misses 62, evicted 3, refused 0, failed 1) +[tensorfold] done chatcmpl-2f0c0ab18b174f36f4248a1f71b61682 prompt=10248 cached=10176 thinking=False effort=none tokens=13 sha=7e4bf5aba972 finish=stop rounds=4 accepted=10/21 ttft=0.442 decode=0.289 elapsed=0.731 queued=0.000 tok/s=41.5 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 10281 tokens, resumed at 10240, kept 0; 2 states, 824 MiB and 0 MiB spare of 1024 MiB (hits 7, misses 62, evicted 3, refused 0, failed 1) +[tensorfold] done chatcmpl-fa75006f715fb7ae6d4c6ceecf61e462 prompt=10281 cached=10240 thinking=False effort=none tokens=48 sha=e7287d6bf366 finish=length rounds=17 accepted=31/40 ttft=0.258 decode=0.852 elapsed=1.110 queued=0.000 tok/s=55.1 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 10281 tokens, resumed at 10240, kept 0; 2 states, 824 MiB and 0 MiB spare of 1024 MiB (hits 8, misses 62, evicted 3, refused 0, failed 1) +[tensorfold] done chatcmpl-877f0e40877a72d37d30bab565dc7805 prompt=10281 cached=10240 thinking=False effort=none tokens=48 sha=e7287d6bf366 finish=length rounds=17 accepted=31/40 ttft=0.257 decode=0.900 elapsed=1.157 queued=0.000 tok/s=52.2 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 10281 tokens, resumed at 10240, kept 0; 2 states, 824 MiB and 0 MiB spare of 1024 MiB (hits 9, misses 62, evicted 3, refused 0, failed 1) +[tensorfold] done chatcmpl-97ce141868346f553bb93c1abfea9db8 prompt=10281 cached=10240 thinking=False effort=none tokens=48 sha=55e1d46d0689 finish=length rounds=21 accepted=27/41 ttft=0.257 decode=0.969 elapsed=1.226 queued=0.000 tok/s=48.5 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 10279 tokens, resumed at 10240, kept 0; 2 states, 824 MiB and 0 MiB spare of 1024 MiB (hits 10, misses 62, evicted 3, refused 0, failed 1) +[tensorfold] done chatcmpl-406f89a58b638dd08cb1e4da4edb314b prompt=10279 cached=10240 thinking=False effort=none tokens=14 sha=9537be85f86c finish=stop rounds=4 accepted=12/20 ttft=0.254 decode=0.289 elapsed=0.544 queued=0.000 tok/s=44.9 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 10219 tokens, resumed at 10176, kept 0; 2 states, 824 MiB and 0 MiB spare of 1024 MiB (hits 11, misses 62, evicted 3, refused 0, failed 1) +[tensorfold] done chatcmpl-e58a6fda3aa48f02164327a092709d60 prompt=10219 cached=10176 thinking=False effort=none tokens=13 sha=86effbb58f5b finish=stop rounds=5 accepted=11/13 ttft=0.277 decode=0.265 elapsed=0.542 queued=0.000 tok/s=45.2 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 10248 tokens, resumed at 10240, kept 0; 2 states, 824 MiB and 0 MiB spare of 1024 MiB (hits 12, misses 62, evicted 3, refused 0, failed 1) +[tensorfold] done chatcmpl-bf81efa19a2fd894ea36d9da9dd23cb0 prompt=10248 cached=10240 thinking=False effort=none tokens=13 sha=7e4bf5aba972 finish=stop rounds=4 accepted=10/21 ttft=0.099 decode=0.289 elapsed=0.387 queued=0.000 tok/s=41.6 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 10219 tokens, resumed at 10176, kept 0; 2 states, 824 MiB and 0 MiB spare of 1024 MiB (hits 13, misses 62, evicted 3, refused 0, failed 1) +[tensorfold] done chatcmpl-3cc07e88fc66005ffb52965dd69f1bd5 prompt=10219 cached=10176 thinking=False effort=none tokens=11 sha=eea964a89e62 finish=stop rounds=10 accepted=0/0 ttft=0.268 decode=0.277 elapsed=0.545 queued=0.000 tok/s=36.1 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 10248 tokens, resumed at 10240, kept 0; 2 states, 824 MiB and 0 MiB spare of 1024 MiB (hits 14, misses 62, evicted 3, refused 0, failed 1) +[tensorfold] done chatcmpl-f0b6a4b4521a150733d8cdeb52285b86 prompt=10248 cached=10240 thinking=False effort=none tokens=13 sha=7e4bf5aba972 finish=stop rounds=12 accepted=0/0 ttft=0.090 decode=0.331 elapsed=0.421 queued=0.000 tok/s=36.2 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 10281 tokens, resumed at 10240, kept 0; 2 states, 824 MiB and 0 MiB spare of 1024 MiB (hits 15, misses 62, evicted 3, refused 0, failed 1) +[tensorfold] done chatcmpl-4563ef9a7050e36f683a03cd054ee54f prompt=10281 cached=10240 thinking=False effort=none tokens=48 sha=e7287d6bf366 finish=length rounds=47 accepted=0/0 ttft=0.252 decode=1.300 elapsed=1.553 queued=0.000 tok/s=36.1 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 10281 tokens, resumed at 10240, kept 0; 2 states, 824 MiB and 0 MiB spare of 1024 MiB (hits 16, misses 62, evicted 3, refused 0, failed 1) +[tensorfold] done chatcmpl-fb34c820df81faf877d0861cb3206e2e prompt=10281 cached=10240 thinking=False effort=none tokens=48 sha=e7287d6bf366 finish=length rounds=47 accepted=0/0 ttft=0.254 decode=1.304 elapsed=1.558 queued=0.000 tok/s=36.0 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 10281 tokens, resumed at 10240, kept 0; 2 states, 824 MiB and 0 MiB spare of 1024 MiB (hits 17, misses 62, evicted 3, refused 0, failed 1) +[tensorfold] done chatcmpl-02ff6e3728ae2e1812338a55881e2a77 prompt=10281 cached=10240 thinking=False effort=none tokens=48 sha=55e1d46d0689 finish=length rounds=47 accepted=0/0 ttft=0.253 decode=1.300 elapsed=1.553 queued=0.000 tok/s=36.2 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 10279 tokens, resumed at 10240, kept 0; 2 states, 824 MiB and 0 MiB spare of 1024 MiB (hits 18, misses 62, evicted 3, refused 0, failed 1) +[tensorfold] done chatcmpl-6d2581f620d44ea7b4290d6eaee192eb prompt=10279 cached=10240 thinking=False effort=none tokens=14 sha=9537be85f86c finish=stop rounds=13 accepted=0/0 ttft=0.245 decode=0.358 elapsed=0.603 queued=0.000 tok/s=36.3 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 10219 tokens, resumed at 10176, kept 0; 2 states, 824 MiB and 0 MiB spare of 1024 MiB (hits 19, misses 62, evicted 3, refused 0, failed 1) +[tensorfold] done chatcmpl-22b57270a767818627693d733a05cce1 prompt=10219 cached=10176 thinking=False effort=none tokens=13 sha=86effbb58f5b finish=stop rounds=12 accepted=0/0 ttft=0.268 decode=0.332 elapsed=0.601 queued=0.000 tok/s=36.1 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +info: prompt cache: 10248 tokens, resumed at 10240, kept 0; 2 states, 824 MiB and 0 MiB spare of 1024 MiB (hits 20, misses 62, evicted 3, refused 0, failed 1) +[tensorfold] done chatcmpl-80f34639a7c2e1873d792cb51838fd3d prompt=10248 cached=10240 thinking=False effort=none tokens=13 sha=7e4bf5aba972 finish=stop rounds=12 accepted=0/0 ttft=0.090 decode=0.332 elapsed=0.422 queued=0.000 tok/s=36.1 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /memory HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /metrics HTTP/1.1" 200 - +[tensorfold] shutting down (SIGTERM): draining: new requests get 503; 0 request(s) in progress may finish within 20.0 s +[tensorfold] shutting down: drained +info: graphs: 42 captured (9 ms each), 1483 of 1589 rounds replayed +[tensorfold] shutting down: stopped diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/memory/ex-exact-memory-endpoint.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/memory/ex-exact-memory-endpoint.json new file mode 100644 index 0000000000..c6aa396fd4 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/memory/ex-exact-memory-endpoint.json @@ -0,0 +1 @@ +{"schema_version": 1, "context_window": 32768, "context_fitted": false, "device": {"active_bytes": 91494358724, "cache_bytes": 0, "peak_bytes": 91519535572, "peak_scope": "since_start_or_health_reset"}} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/memory/ex-exact-metrics.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/memory/ex-exact-metrics.txt new file mode 100644 index 0000000000..08e577bdb0 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/memory/ex-exact-metrics.txt @@ -0,0 +1,220 @@ +# HELP tensorfold:requests_running Requests in prefill or decode. +# TYPE tensorfold:requests_running gauge +tensorfold:requests_running 0 +# HELP tensorfold:requests_waiting Requests queued or held until a lane is free. +# TYPE tensorfold:requests_waiting gauge +tensorfold:requests_waiting 0 +# HELP tensorfold:generation_tokens_running Generated tokens held by live streams. +# TYPE tensorfold:generation_tokens_running gauge +tensorfold:generation_tokens_running 0 +# HELP tensorfold:prompt_tokens_total Prompt tokens of finished requests. +# TYPE tensorfold:prompt_tokens_total counter +tensorfold:prompt_tokens_total 186060 +# HELP tensorfold:generation_tokens_total Generated tokens of finished requests. +# TYPE tensorfold:generation_tokens_total counter +tensorfold:generation_tokens_total 3812 +# HELP tensorfold:kv_cache_usage_ratio Tokens in a stream cache divided by that stream's context window. +# TYPE tensorfold:kv_cache_usage_ratio gauge +tensorfold:kv_cache_usage_ratio{pool="0"} 0 +# HELP tensorfold:mtp_drafted_total Draft tokens verified on finished requests. +# TYPE tensorfold:mtp_drafted_total counter +tensorfold:mtp_drafted_total 2088 +# HELP tensorfold:mtp_accepted_total Draft tokens kept on finished requests. +# TYPE tensorfold:mtp_accepted_total counter +tensorfold:mtp_accepted_total 1572 +# HELP tensorfold:request_latency_seconds Seconds from arrival to the reply leaving. +# TYPE tensorfold:request_latency_seconds histogram +tensorfold:request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:request_latency_seconds_bucket{le="0.5"} 3 +tensorfold:request_latency_seconds_bucket{le="1"} 29 +tensorfold:request_latency_seconds_bucket{le="2.5"} 55 +tensorfold:request_latency_seconds_bucket{le="5"} 78 +tensorfold:request_latency_seconds_bucket{le="10"} 82 +tensorfold:request_latency_seconds_bucket{le="30"} 83 +tensorfold:request_latency_seconds_bucket{le="60"} 83 +tensorfold:request_latency_seconds_bucket{le="120"} 83 +tensorfold:request_latency_seconds_bucket{le="300"} 83 +tensorfold:request_latency_seconds_bucket{le="+Inf"} 83 +tensorfold:request_latency_seconds_sum 188.038988 +tensorfold:request_latency_seconds_count 83 +# HELP tensorfold:time_to_first_token_seconds Seconds from arrival to the first generated token. +# TYPE tensorfold:time_to_first_token_seconds histogram +tensorfold:time_to_first_token_seconds_bucket{le="0.01"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.05"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.1"} 3 +tensorfold:time_to_first_token_seconds_bucket{le="0.25"} 48 +tensorfold:time_to_first_token_seconds_bucket{le="0.5"} 76 +tensorfold:time_to_first_token_seconds_bucket{le="1"} 81 +tensorfold:time_to_first_token_seconds_bucket{le="2.5"} 81 +tensorfold:time_to_first_token_seconds_bucket{le="5"} 81 +tensorfold:time_to_first_token_seconds_bucket{le="10"} 82 +tensorfold:time_to_first_token_seconds_bucket{le="30"} 83 +tensorfold:time_to_first_token_seconds_bucket{le="60"} 83 +tensorfold:time_to_first_token_seconds_bucket{le="120"} 83 +tensorfold:time_to_first_token_seconds_bucket{le="300"} 83 +tensorfold:time_to_first_token_seconds_bucket{le="+Inf"} 83 +tensorfold:time_to_first_token_seconds_sum 44.293355 +tensorfold:time_to_first_token_seconds_count 83 +# HELP tensorfold:request_decode_seconds Seconds a finished request spent decoding. Its sum over generation_tokens_total is the decode rate. +# TYPE tensorfold:request_decode_seconds histogram +tensorfold:request_decode_seconds_bucket{le="0.01"} 0 +tensorfold:request_decode_seconds_bucket{le="0.05"} 0 +tensorfold:request_decode_seconds_bucket{le="0.1"} 0 +tensorfold:request_decode_seconds_bucket{le="0.25"} 0 +tensorfold:request_decode_seconds_bucket{le="0.5"} 21 +tensorfold:request_decode_seconds_bucket{le="1"} 33 +tensorfold:request_decode_seconds_bucket{le="2.5"} 61 +tensorfold:request_decode_seconds_bucket{le="5"} 80 +tensorfold:request_decode_seconds_bucket{le="10"} 83 +tensorfold:request_decode_seconds_bucket{le="30"} 83 +tensorfold:request_decode_seconds_bucket{le="60"} 83 +tensorfold:request_decode_seconds_bucket{le="120"} 83 +tensorfold:request_decode_seconds_bucket{le="300"} 83 +tensorfold:request_decode_seconds_bucket{le="+Inf"} 83 +tensorfold:request_decode_seconds_sum 143.745634 +tensorfold:request_decode_seconds_count 83 +# HELP tensorfold:request_time_per_output_token_seconds Seconds from the first generated token to the last, divided by the tokens less one. +# TYPE tensorfold:request_time_per_output_token_seconds histogram +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.005"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.01"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.015"} 11 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.02"} 20 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.025"} 32 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.03"} 53 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.04"} 57 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.05"} 59 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.075"} 80 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.1"} 80 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.15"} 81 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.2"} 83 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.3"} 83 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.5"} 83 +tensorfold:request_time_per_output_token_seconds_bucket{le="1"} 83 +tensorfold:request_time_per_output_token_seconds_bucket{le="+Inf"} 83 +tensorfold:request_time_per_output_token_seconds_sum 3.032835 +tensorfold:request_time_per_output_token_seconds_count 83 +# HELP tensorfold:decode_rounds_total Decode rounds used by finished requests. +# TYPE tensorfold:decode_rounds_total counter +tensorfold:decode_rounds_total 2252 +# HELP tensorfold:request_prefill_seconds Seconds a finished request's prompt pass took. +# TYPE tensorfold:request_prefill_seconds histogram +tensorfold:request_prefill_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.1"} 3 +tensorfold:request_prefill_seconds_bucket{le="0.25"} 56 +tensorfold:request_prefill_seconds_bucket{le="0.5"} 80 +tensorfold:request_prefill_seconds_bucket{le="1"} 81 +tensorfold:request_prefill_seconds_bucket{le="2.5"} 81 +tensorfold:request_prefill_seconds_bucket{le="5"} 81 +tensorfold:request_prefill_seconds_bucket{le="10"} 82 +tensorfold:request_prefill_seconds_bucket{le="30"} 83 +tensorfold:request_prefill_seconds_bucket{le="60"} 83 +tensorfold:request_prefill_seconds_bucket{le="120"} 83 +tensorfold:request_prefill_seconds_bucket{le="300"} 83 +tensorfold:request_prefill_seconds_bucket{le="+Inf"} 83 +tensorfold:request_prefill_seconds_sum 41.301937 +tensorfold:request_prefill_seconds_count 83 +# HELP tensorfold:process_resident_bytes Current resident set (VmRSS); device memory is not in it, so it is not a physical footprint (Linux). +# TYPE tensorfold:process_resident_bytes gauge +tensorfold:process_resident_bytes 100230422528 +# HELP tensorfold:process_resident_anon_bytes Current resident anonymous memory (RssAnon): heap, stacks and private maps (Linux). +# TYPE tensorfold:process_resident_anon_bytes gauge +tensorfold:process_resident_anon_bytes 33316683776 +# HELP tensorfold:process_resident_file_bytes Current resident file-backed memory (RssFile): the binary, libraries and mapped files (Linux). +# TYPE tensorfold:process_resident_file_bytes gauge +tensorfold:process_resident_file_bytes 66771087360 +# HELP tensorfold:process_resident_shmem_bytes Current resident shared memory (RssShmem): System V shared memory, tmpfs maps and shared anonymous maps (Linux). +# TYPE tensorfold:process_resident_shmem_bytes gauge +tensorfold:process_resident_shmem_bytes 142651392 +# HELP tensorfold:process_resident_peak_bytes Kernel lifetime peak resident set (VmHWM); never reset by health (Linux). +# TYPE tensorfold:process_resident_peak_bytes gauge +tensorfold:process_resident_peak_bytes 109884239872 +# HELP tensorfold:device_memory_bytes Device memory the engine holds now: weights, caches and live streams; only where the backend counts it (CUDA). +# TYPE tensorfold:device_memory_bytes gauge +tensorfold:device_memory_bytes 91494358724 +# HELP tensorfold:device_memory_peak_bytes The most device memory the engine has held since start or the last /health?reset_peak=1. +# TYPE tensorfold:device_memory_peak_bytes gauge +tensorfold:device_memory_peak_bytes 91519535572 +# HELP tensorfold:pinned_memory_bytes Pinned host memory the engine holds now: staging buffers and windows; only where the backend counts it (CUDA). +# TYPE tensorfold:pinned_memory_bytes gauge +tensorfold:pinned_memory_bytes 0 +# HELP tensorfold:num_requests_running Requests in prefill or decode. A mirror of tensorfold:requests_running. +# TYPE tensorfold:num_requests_running gauge +tensorfold:num_requests_running 0 +# HELP tensorfold:num_requests_waiting Requests queued or held until a lane is free. A mirror of tensorfold:requests_waiting. +# TYPE tensorfold:num_requests_waiting gauge +tensorfold:num_requests_waiting 0 +# HELP tensorfold:kv_cache_usage_perc A stream's cache occupancy under vLLM's name; same streams and ratios as tensorfold:kv_cache_usage_ratio. +# TYPE tensorfold:kv_cache_usage_perc gauge +tensorfold:kv_cache_usage_perc{stream="0"} 0 +# HELP tensorfold:spec_decode_num_draft_tokens_total Draft tokens verified on finished requests, this server's single draft counter. +# TYPE tensorfold:spec_decode_num_draft_tokens_total counter +tensorfold:spec_decode_num_draft_tokens_total 2088 +# HELP tensorfold:spec_decode_num_accepted_tokens_total Draft tokens kept on finished requests. +# TYPE tensorfold:spec_decode_num_accepted_tokens_total counter +tensorfold:spec_decode_num_accepted_tokens_total 1572 +# HELP tensorfold:e2e_request_latency_seconds Seconds from arrival to the reply leaving, under vLLM's name. +# TYPE tensorfold:e2e_request_latency_seconds histogram +tensorfold:e2e_request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.5"} 3 +tensorfold:e2e_request_latency_seconds_bucket{le="1"} 29 +tensorfold:e2e_request_latency_seconds_bucket{le="2.5"} 55 +tensorfold:e2e_request_latency_seconds_bucket{le="5"} 78 +tensorfold:e2e_request_latency_seconds_bucket{le="10"} 82 +tensorfold:e2e_request_latency_seconds_bucket{le="30"} 83 +tensorfold:e2e_request_latency_seconds_bucket{le="60"} 83 +tensorfold:e2e_request_latency_seconds_bucket{le="120"} 83 +tensorfold:e2e_request_latency_seconds_bucket{le="300"} 83 +tensorfold:e2e_request_latency_seconds_bucket{le="+Inf"} 83 +tensorfold:e2e_request_latency_seconds_sum 188.038988 +tensorfold:e2e_request_latency_seconds_count 83 +# HELP tensorfold:request_decode_time_seconds Seconds a finished request spent decoding, under vLLM's name. +# TYPE tensorfold:request_decode_time_seconds histogram +tensorfold:request_decode_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.5"} 21 +tensorfold:request_decode_time_seconds_bucket{le="1"} 33 +tensorfold:request_decode_time_seconds_bucket{le="2.5"} 61 +tensorfold:request_decode_time_seconds_bucket{le="5"} 80 +tensorfold:request_decode_time_seconds_bucket{le="10"} 83 +tensorfold:request_decode_time_seconds_bucket{le="30"} 83 +tensorfold:request_decode_time_seconds_bucket{le="60"} 83 +tensorfold:request_decode_time_seconds_bucket{le="120"} 83 +tensorfold:request_decode_time_seconds_bucket{le="300"} 83 +tensorfold:request_decode_time_seconds_bucket{le="+Inf"} 83 +tensorfold:request_decode_time_seconds_sum 143.745634 +tensorfold:request_decode_time_seconds_count 83 +# HELP tensorfold:request_prefill_time_seconds Seconds a finished request's prompt pass took, under vLLM's name. +# TYPE tensorfold:request_prefill_time_seconds histogram +tensorfold:request_prefill_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.1"} 3 +tensorfold:request_prefill_time_seconds_bucket{le="0.25"} 56 +tensorfold:request_prefill_time_seconds_bucket{le="0.5"} 80 +tensorfold:request_prefill_time_seconds_bucket{le="1"} 81 +tensorfold:request_prefill_time_seconds_bucket{le="2.5"} 81 +tensorfold:request_prefill_time_seconds_bucket{le="5"} 81 +tensorfold:request_prefill_time_seconds_bucket{le="10"} 82 +tensorfold:request_prefill_time_seconds_bucket{le="30"} 83 +tensorfold:request_prefill_time_seconds_bucket{le="60"} 83 +tensorfold:request_prefill_time_seconds_bucket{le="120"} 83 +tensorfold:request_prefill_time_seconds_bucket{le="300"} 83 +tensorfold:request_prefill_time_seconds_bucket{le="+Inf"} 83 +tensorfold:request_prefill_time_seconds_sum 41.301937 +tensorfold:request_prefill_time_seconds_count 83 +# HELP tensorfold:client_disconnections_total Requests a client left before the reply left the server. +# TYPE tensorfold:client_disconnections_total counter +tensorfold:client_disconnections_total 0 +# HELP tensorfold:preemptions_total Requests that had to give a lane up to a later one. +# TYPE tensorfold:preemptions_total counter +tensorfold:preemptions_total 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/memory/ex-exact-nocache-memory-endpoint.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/memory/ex-exact-nocache-memory-endpoint.json new file mode 100644 index 0000000000..15eb89329e --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/memory/ex-exact-nocache-memory-endpoint.json @@ -0,0 +1 @@ +{"schema_version": 1, "context_window": 32768, "context_fitted": false, "device": {"active_bytes": 88206068372, "cache_bytes": 0, "peak_bytes": 88231245220, "peak_scope": "since_start_or_health_reset"}} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/memory/ex-exact-nocache-metrics.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/memory/ex-exact-nocache-metrics.txt new file mode 100644 index 0000000000..1d343015b5 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/memory/ex-exact-nocache-metrics.txt @@ -0,0 +1,220 @@ +# HELP tensorfold:requests_running Requests in prefill or decode. +# TYPE tensorfold:requests_running gauge +tensorfold:requests_running 0 +# HELP tensorfold:requests_waiting Requests queued or held until a lane is free. +# TYPE tensorfold:requests_waiting gauge +tensorfold:requests_waiting 0 +# HELP tensorfold:generation_tokens_running Generated tokens held by live streams. +# TYPE tensorfold:generation_tokens_running gauge +tensorfold:generation_tokens_running 0 +# HELP tensorfold:prompt_tokens_total Prompt tokens of finished requests. +# TYPE tensorfold:prompt_tokens_total counter +tensorfold:prompt_tokens_total 164112 +# HELP tensorfold:generation_tokens_total Generated tokens of finished requests. +# TYPE tensorfold:generation_tokens_total counter +tensorfold:generation_tokens_total 416 +# HELP tensorfold:kv_cache_usage_ratio Tokens in a stream cache divided by that stream's context window. +# TYPE tensorfold:kv_cache_usage_ratio gauge +tensorfold:kv_cache_usage_ratio{pool="0"} 0 +# HELP tensorfold:mtp_drafted_total Draft tokens verified on finished requests. +# TYPE tensorfold:mtp_drafted_total counter +tensorfold:mtp_drafted_total 198 +# HELP tensorfold:mtp_accepted_total Draft tokens kept on finished requests. +# TYPE tensorfold:mtp_accepted_total counter +tensorfold:mtp_accepted_total 141 +# HELP tensorfold:request_latency_seconds Seconds from arrival to the reply leaving. +# TYPE tensorfold:request_latency_seconds histogram +tensorfold:request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:request_latency_seconds_bucket{le="1"} 0 +tensorfold:request_latency_seconds_bucket{le="2.5"} 0 +tensorfold:request_latency_seconds_bucket{le="5"} 0 +tensorfold:request_latency_seconds_bucket{le="10"} 0 +tensorfold:request_latency_seconds_bucket{le="30"} 16 +tensorfold:request_latency_seconds_bucket{le="60"} 16 +tensorfold:request_latency_seconds_bucket{le="120"} 16 +tensorfold:request_latency_seconds_bucket{le="300"} 16 +tensorfold:request_latency_seconds_bucket{le="+Inf"} 16 +tensorfold:request_latency_seconds_sum 309.236554 +tensorfold:request_latency_seconds_count 16 +# HELP tensorfold:time_to_first_token_seconds Seconds from arrival to the first generated token. +# TYPE tensorfold:time_to_first_token_seconds histogram +tensorfold:time_to_first_token_seconds_bucket{le="0.01"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.05"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.25"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.5"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="2.5"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="5"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="10"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="30"} 16 +tensorfold:time_to_first_token_seconds_bucket{le="60"} 16 +tensorfold:time_to_first_token_seconds_bucket{le="120"} 16 +tensorfold:time_to_first_token_seconds_bucket{le="300"} 16 +tensorfold:time_to_first_token_seconds_bucket{le="+Inf"} 16 +tensorfold:time_to_first_token_seconds_sum 299.173177 +tensorfold:time_to_first_token_seconds_count 16 +# HELP tensorfold:request_decode_seconds Seconds a finished request spent decoding. Its sum over generation_tokens_total is the decode rate. +# TYPE tensorfold:request_decode_seconds histogram +tensorfold:request_decode_seconds_bucket{le="0.01"} 0 +tensorfold:request_decode_seconds_bucket{le="0.05"} 0 +tensorfold:request_decode_seconds_bucket{le="0.1"} 0 +tensorfold:request_decode_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_seconds_bucket{le="0.5"} 10 +tensorfold:request_decode_seconds_bucket{le="1"} 11 +tensorfold:request_decode_seconds_bucket{le="2.5"} 16 +tensorfold:request_decode_seconds_bucket{le="5"} 16 +tensorfold:request_decode_seconds_bucket{le="10"} 16 +tensorfold:request_decode_seconds_bucket{le="30"} 16 +tensorfold:request_decode_seconds_bucket{le="60"} 16 +tensorfold:request_decode_seconds_bucket{le="120"} 16 +tensorfold:request_decode_seconds_bucket{le="300"} 16 +tensorfold:request_decode_seconds_bucket{le="+Inf"} 16 +tensorfold:request_decode_seconds_sum 10.063377 +tensorfold:request_decode_seconds_count 16 +# HELP tensorfold:request_time_per_output_token_seconds Seconds from the first generated token to the last, divided by the tokens less one. +# TYPE tensorfold:request_time_per_output_token_seconds histogram +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.005"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.01"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.015"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.02"} 2 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.025"} 6 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.03"} 16 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.04"} 16 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.05"} 16 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.075"} 16 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.1"} 16 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.15"} 16 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.2"} 16 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.3"} 16 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.5"} 16 +tensorfold:request_time_per_output_token_seconds_bucket{le="1"} 16 +tensorfold:request_time_per_output_token_seconds_bucket{le="+Inf"} 16 +tensorfold:request_time_per_output_token_seconds_sum 0.404046 +tensorfold:request_time_per_output_token_seconds_count 16 +# HELP tensorfold:decode_rounds_total Decode rounds used by finished requests. +# TYPE tensorfold:decode_rounds_total counter +tensorfold:decode_rounds_total 273 +# HELP tensorfold:request_prefill_seconds Seconds a finished request's prompt pass took. +# TYPE tensorfold:request_prefill_seconds histogram +tensorfold:request_prefill_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.5"} 0 +tensorfold:request_prefill_seconds_bucket{le="1"} 0 +tensorfold:request_prefill_seconds_bucket{le="2.5"} 0 +tensorfold:request_prefill_seconds_bucket{le="5"} 0 +tensorfold:request_prefill_seconds_bucket{le="10"} 0 +tensorfold:request_prefill_seconds_bucket{le="30"} 16 +tensorfold:request_prefill_seconds_bucket{le="60"} 16 +tensorfold:request_prefill_seconds_bucket{le="120"} 16 +tensorfold:request_prefill_seconds_bucket{le="300"} 16 +tensorfold:request_prefill_seconds_bucket{le="+Inf"} 16 +tensorfold:request_prefill_seconds_sum 298.924635 +tensorfold:request_prefill_seconds_count 16 +# HELP tensorfold:process_resident_bytes Current resident set (VmRSS); device memory is not in it, so it is not a physical footprint (Linux). +# TYPE tensorfold:process_resident_bytes gauge +tensorfold:process_resident_bytes 105000038400 +# HELP tensorfold:process_resident_anon_bytes Current resident anonymous memory (RssAnon): heap, stacks and private maps (Linux). +# TYPE tensorfold:process_resident_anon_bytes gauge +tensorfold:process_resident_anon_bytes 32371531776 +# HELP tensorfold:process_resident_file_bytes Current resident file-backed memory (RssFile): the binary, libraries and mapped files (Linux). +# TYPE tensorfold:process_resident_file_bytes gauge +tensorfold:process_resident_file_bytes 72494243840 +# HELP tensorfold:process_resident_shmem_bytes Current resident shared memory (RssShmem): System V shared memory, tmpfs maps and shared anonymous maps (Linux). +# TYPE tensorfold:process_resident_shmem_bytes gauge +tensorfold:process_resident_shmem_bytes 134262784 +# HELP tensorfold:process_resident_peak_bytes Kernel lifetime peak resident set (VmHWM); never reset by health (Linux). +# TYPE tensorfold:process_resident_peak_bytes gauge +tensorfold:process_resident_peak_bytes 112510197760 +# HELP tensorfold:device_memory_bytes Device memory the engine holds now: weights, caches and live streams; only where the backend counts it (CUDA). +# TYPE tensorfold:device_memory_bytes gauge +tensorfold:device_memory_bytes 88206068372 +# HELP tensorfold:device_memory_peak_bytes The most device memory the engine has held since start or the last /health?reset_peak=1. +# TYPE tensorfold:device_memory_peak_bytes gauge +tensorfold:device_memory_peak_bytes 88231245220 +# HELP tensorfold:pinned_memory_bytes Pinned host memory the engine holds now: staging buffers and windows; only where the backend counts it (CUDA). +# TYPE tensorfold:pinned_memory_bytes gauge +tensorfold:pinned_memory_bytes 0 +# HELP tensorfold:num_requests_running Requests in prefill or decode. A mirror of tensorfold:requests_running. +# TYPE tensorfold:num_requests_running gauge +tensorfold:num_requests_running 0 +# HELP tensorfold:num_requests_waiting Requests queued or held until a lane is free. A mirror of tensorfold:requests_waiting. +# TYPE tensorfold:num_requests_waiting gauge +tensorfold:num_requests_waiting 0 +# HELP tensorfold:kv_cache_usage_perc A stream's cache occupancy under vLLM's name; same streams and ratios as tensorfold:kv_cache_usage_ratio. +# TYPE tensorfold:kv_cache_usage_perc gauge +tensorfold:kv_cache_usage_perc{stream="0"} 0 +# HELP tensorfold:spec_decode_num_draft_tokens_total Draft tokens verified on finished requests, this server's single draft counter. +# TYPE tensorfold:spec_decode_num_draft_tokens_total counter +tensorfold:spec_decode_num_draft_tokens_total 198 +# HELP tensorfold:spec_decode_num_accepted_tokens_total Draft tokens kept on finished requests. +# TYPE tensorfold:spec_decode_num_accepted_tokens_total counter +tensorfold:spec_decode_num_accepted_tokens_total 141 +# HELP tensorfold:e2e_request_latency_seconds Seconds from arrival to the reply leaving, under vLLM's name. +# TYPE tensorfold:e2e_request_latency_seconds histogram +tensorfold:e2e_request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="2.5"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="5"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="10"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="30"} 16 +tensorfold:e2e_request_latency_seconds_bucket{le="60"} 16 +tensorfold:e2e_request_latency_seconds_bucket{le="120"} 16 +tensorfold:e2e_request_latency_seconds_bucket{le="300"} 16 +tensorfold:e2e_request_latency_seconds_bucket{le="+Inf"} 16 +tensorfold:e2e_request_latency_seconds_sum 309.236554 +tensorfold:e2e_request_latency_seconds_count 16 +# HELP tensorfold:request_decode_time_seconds Seconds a finished request spent decoding, under vLLM's name. +# TYPE tensorfold:request_decode_time_seconds histogram +tensorfold:request_decode_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.5"} 10 +tensorfold:request_decode_time_seconds_bucket{le="1"} 11 +tensorfold:request_decode_time_seconds_bucket{le="2.5"} 16 +tensorfold:request_decode_time_seconds_bucket{le="5"} 16 +tensorfold:request_decode_time_seconds_bucket{le="10"} 16 +tensorfold:request_decode_time_seconds_bucket{le="30"} 16 +tensorfold:request_decode_time_seconds_bucket{le="60"} 16 +tensorfold:request_decode_time_seconds_bucket{le="120"} 16 +tensorfold:request_decode_time_seconds_bucket{le="300"} 16 +tensorfold:request_decode_time_seconds_bucket{le="+Inf"} 16 +tensorfold:request_decode_time_seconds_sum 10.063377 +tensorfold:request_decode_time_seconds_count 16 +# HELP tensorfold:request_prefill_time_seconds Seconds a finished request's prompt pass took, under vLLM's name. +# TYPE tensorfold:request_prefill_time_seconds histogram +tensorfold:request_prefill_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.5"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="2.5"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="5"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="10"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="30"} 16 +tensorfold:request_prefill_time_seconds_bucket{le="60"} 16 +tensorfold:request_prefill_time_seconds_bucket{le="120"} 16 +tensorfold:request_prefill_time_seconds_bucket{le="300"} 16 +tensorfold:request_prefill_time_seconds_bucket{le="+Inf"} 16 +tensorfold:request_prefill_time_seconds_sum 298.924635 +tensorfold:request_prefill_time_seconds_count 16 +# HELP tensorfold:client_disconnections_total Requests a client left before the reply left the server. +# TYPE tensorfold:client_disconnections_total counter +tensorfold:client_disconnections_total 0 +# HELP tensorfold:preemptions_total Requests that had to give a lane up to a later one. +# TYPE tensorfold:preemptions_total counter +tensorfold:preemptions_total 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/memory/ex-exact-nocache-samples.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/memory/ex-exact-nocache-samples.jsonl new file mode 100644 index 0000000000..490df38a1f --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/memory/ex-exact-nocache-samples.jsonl @@ -0,0 +1,286 @@ +{"t_s": 0.0, "VmRSS_bytes": 86642688, "VmHWM_bytes": 86642688, "Pss_bytes": 84950016, "vram_used_bytes": 187682816, "vram_total_bytes": 4294967296, "gtt_used_bytes": 31657984, "gtt_total_bytes": 193273528320} +{"t_s": 1.01, "VmRSS_bytes": 5457612800, "VmHWM_bytes": 5457612800, "Pss_bytes": 5455175680, "vram_used_bytes": 188604416, "vram_total_bytes": 4294967296, "gtt_used_bytes": 3557093376, "gtt_total_bytes": 193273528320} +{"t_s": 2.03, "VmRSS_bytes": 10234478592, "VmHWM_bytes": 10234478592, "Pss_bytes": 10233745408, "vram_used_bytes": 188764160, "vram_total_bytes": 4294967296, "gtt_used_bytes": 8445554688, "gtt_total_bytes": 193273528320} +{"t_s": 3.06, "VmRSS_bytes": 15043993600, "VmHWM_bytes": 15043993600, "Pss_bytes": 15065935872, "vram_used_bytes": 189038592, "vram_total_bytes": 4294967296, "gtt_used_bytes": 11773734912, "gtt_total_bytes": 193273528320} +{"t_s": 4.1, "VmRSS_bytes": 19616722944, "VmHWM_bytes": 19616722944, "Pss_bytes": 19618480128, "vram_used_bytes": 189345792, "vram_total_bytes": 4294967296, "gtt_used_bytes": 16699944960, "gtt_total_bytes": 193273528320} +{"t_s": 5.14, "VmRSS_bytes": 24310304768, "VmHWM_bytes": 24310304768, "Pss_bytes": 24315469824, "vram_used_bytes": 189657088, "vram_total_bytes": 4294967296, "gtt_used_bytes": 21626155008, "gtt_total_bytes": 193273528320} +{"t_s": 6.21, "VmRSS_bytes": 29105786880, "VmHWM_bytes": 29105786880, "Pss_bytes": 29107281920, "vram_used_bytes": 190001152, "vram_total_bytes": 4294967296, "gtt_used_bytes": 26554462208, "gtt_total_bytes": 193273528320} +{"t_s": 7.28, "VmRSS_bytes": 33906360320, "VmHWM_bytes": 33906360320, "Pss_bytes": 33929351168, "vram_used_bytes": 190300160, "vram_total_bytes": 4294967296, "gtt_used_bytes": 31480672256, "gtt_total_bytes": 193273528320} +{"t_s": 8.36, "VmRSS_bytes": 38903447552, "VmHWM_bytes": 38903447552, "Pss_bytes": 38901010432, "vram_used_bytes": 190615552, "vram_total_bytes": 4294967296, "gtt_used_bytes": 36413173760, "gtt_total_bytes": 193273528320} +{"t_s": 9.45, "VmRSS_bytes": 43774623744, "VmHWM_bytes": 43774623744, "Pss_bytes": 43793158144, "vram_used_bytes": 190922752, "vram_total_bytes": 4294967296, "gtt_used_bytes": 41339383808, "gtt_total_bytes": 193273528320} +{"t_s": 10.55, "VmRSS_bytes": 48797749248, "VmHWM_bytes": 48797749248, "Pss_bytes": 48809467904, "vram_used_bytes": 191209472, "vram_total_bytes": 4294967296, "gtt_used_bytes": 46273982464, "gtt_total_bytes": 193273528320} +{"t_s": 11.66, "VmRSS_bytes": 53586608128, "VmHWM_bytes": 53586608128, "Pss_bytes": 53585158144, "vram_used_bytes": 191533056, "vram_total_bytes": 4294967296, "gtt_used_bytes": 51200192512, "gtt_total_bytes": 193273528320} +{"t_s": 12.78, "VmRSS_bytes": 58504564736, "VmHWM_bytes": 58504564736, "Pss_bytes": 58510516224, "vram_used_bytes": 191823872, "vram_total_bytes": 4294967296, "gtt_used_bytes": 56132694016, "gtt_total_bytes": 193273528320} +{"t_s": 13.91, "VmRSS_bytes": 63384797184, "VmHWM_bytes": 63384797184, "Pss_bytes": 63384719360, "vram_used_bytes": 192163840, "vram_total_bytes": 4294967296, 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b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/provenance.json @@ -0,0 +1,22 @@ +{ + "binaries_sha256": { + "new": "02bb6abe0d4d8768fafab0cecdc7c879409b12966eb768d98bb94746d0551ef6", + "base": "933ee938de6f9798e53d3a8629723f39cdb6863d7a261dcd0d742624a7a672b7", + "flashnext_hip_test": "cc7c2312ce9d59a2b38a23c62ff9e8c029c559ae64ebd47b66cbfcd2d704c565" + }, + "source_commits": { + "kit_source": "37aed1a0384625d4ff35c23e7df2b502d2a8b7f6" + }, + "upstream_scripts_sha256": { + "tools/bench_openai.py": "d5af4fbb756cdfb573546c0e0017652a4bb8f509d1251af683be7a3cbdd426f6", + "tools/bench_concurrent.py": "0e72e26769f082459329fc068c25f6f72a9155e422962ea54cb5d1226227752d", + "tools/bench_cache.py": "711cb8abbbbcd1c34ad628ab1cb89161984ecd18c8fb092d10b16b100d33fc3c", + "tools/bench_timing.py": "158f636ef0b3bed460ce19ef4872b6d8607ff7a8590562d06bae8bd55e6f44ed", + "tools/bench_evidence.py": "54c28474f0804dbd120e3fb5859be0d1667ef21ca502880d0bed098ec9bb42ff", + "tools/bench_metrics.py": "26f4c3ecbb03df4f12e24d18840fea989d9ef8c63117ca11eb944ef670458a27", + "tools/memory_receipts.py": "9e3681e5223320c4d6b72b9a58f3d0c3e35c48086a0779ef6f5a467c6427909c", + "zig/tests/qwen35/serve_check.py": "f4b21cec2b2899d1fd4d284658a4ae054fc1d6e21991538bd91b1207d2896388", + "zig/tests/qwen35/serve_cancel.py": "5ce3dd948df1e2089ba8f3a27fe69e2642a3546aa2a734f5aed06afc473cdf58", + "zig/tests/flashnext_hip/rewind.py": "64889ccb90b555c74cd284762c955872b938e66eb3e25412ad87e143a9299487" + } +} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/publication.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/publication.json new file mode 100644 index 0000000000..1931466bdd --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/publication.json @@ -0,0 +1,104 @@ +{ + "replacements_per_file": { + "run.log": { + "replacements": 0 + }, + "environment.json": { + "replacements": 0 + }, + "provenance.json": { + "replacements": 0 + }, + "checkpoint.json": { + "replacements": 0 + }, + "steps.tsv": { + "replacements": 0 + }, + "summary.json": { + "replacements": 0 + }, + "summary.md": { + "replacements": 0 + }, + "runs/ex-exact-nocache.json": { + "replacements": 0 + }, + "runs/ex-exact.json": { + "replacements": 0 + }, + "exactness/exact-rewind-nocache.jsonl": { + "replacements": 0 + }, + "exactness/exact-rewind-nocache.json": { + "replacements": 0 + }, + "exactness/exact-serve-check.jsonl": { + "replacements": 0 + }, + "exactness/exact-serve-cancel.jsonl": { + "replacements": 0 + }, + "exactness/exact-rewind.jsonl": { + "replacements": 0 + }, + "exactness/exact-rewind.json": { + "replacements": 0 + }, + "exactness/seam-corpus.json": { + "replacements": 0 + }, + "record_http.py": { + "replacements": 0 + }, + "logs/generate-exact-chunk2048.log": { + "replacements": 0 + }, + "logs/generate-exact-chunk20480.log": { + "replacements": 0 + }, + "logs/generate-exact-chunk512.log": { + "replacements": 0 + }, + "logs/generate-exact-chunk8192.log": { + "replacements": 0 + }, + "logs/rewind-exact-nocache.log": { + "replacements": 0 + }, + "logs/rewind-exact.log": { + "replacements": 0 + }, + "logs/serve-cancel-exact.log": { + "replacements": 0 + }, + "logs/serve-check-exact.log": { + "replacements": 0 + }, + "logs/server-ex-exact-nocache.log": { + "replacements": 0 + }, + "memory/ex-exact-nocache-samples.jsonl": { + "replacements": 0 + }, + "memory/ex-exact-nocache-memory-endpoint.json": { + "replacements": 0 + }, + "memory/ex-exact-nocache-metrics.txt": { + "replacements": 0 + }, + "logs/server-ex-exact.log": { + "replacements": 0 + }, + "memory/ex-exact-samples.jsonl": { + "replacements": 0 + }, + "memory/ex-exact-memory-endpoint.json": { + "replacements": 0 + }, + "memory/ex-exact-metrics.txt": { + "replacements": 0 + } + }, + "rule": "machine-local paths, host and user names replaced by placeholders; request and reply values, token ids and hashes unchanged" +} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/record_http.py b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/record_http.py new file mode 100644 index 0000000000..5e27df1daf --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/record_http.py @@ -0,0 +1,125 @@ +"""Run an unmodified upstream HTTP check and keep every exchange; usage: record_http.py SCRIPT OUT.jsonl ARGS... + +Like docs/receipts/gfx1151-qwen-833bbfcb/record-served.py (same record keys), and it also sees http.client calls and a +raw-socket request dropped before any reply (serve_cancel.py), which urlopen alone would miss. Requests and replies +reach the script unchanged. +""" +import http.client +import io +import json +import pathlib +import runpy +import socket +import sys +import threading +import time +import urllib.error +import urllib.request + +script, receipt = pathlib.Path(sys.argv[1]).resolve(), pathlib.Path(sys.argv[2]).resolve() +args = sys.argv[3:] +lock = threading.Lock() +nested = threading.local() # urlopen runs on http.client: one exchange, one record + + +def body_of(data): + try: + return json.loads(data) if data else None + except (TypeError, ValueError): + return None + + +def reply_of(raw): + try: + return json.loads(raw) + except ValueError: + return raw.decode(errors="replace") + + +def write(url, request, status, response, started, **extra): + row = {"url": url, "request": request, "status": status, "response": response, + "seconds": time.time() - started, **extra} + with lock, receipt.open("a") as f: + f.write(json.dumps(row) + "\n") + + +real_urlopen = urllib.request.urlopen + + +def urlopen(req, *a, **kw): + url = req.full_url if isinstance(req, urllib.request.Request) else str(req) + request = body_of(req.data) if isinstance(req, urllib.request.Request) else None + started = time.time() + nested.on = True + try: + r = real_urlopen(req, *a, **kw) + raw, status, headers = r.read(), r.status, r.headers + r.close() + except urllib.error.HTTPError as e: + raw = e.read() + write(url, request, e.code, reply_of(raw), started) + raise urllib.error.HTTPError(url, e.code, e.reason, e.headers, io.BytesIO(raw)) + finally: + nested.on = False + write(url, request, status, reply_of(raw), started) + out = io.BytesIO(raw) + out.status, out.headers = status, headers + return out + + +real_request, real_getresponse = http.client.HTTPConnection.request, http.client.HTTPConnection.getresponse + + +def request(self, method, url, body=None, headers={}, **kw): + self._recorded = (url, body_of(body), time.time()) + return real_request(self, method, url, body, headers, **kw) + + +def getresponse(self): + r = real_getresponse(self) + if getattr(nested, "on", False): + return r + url, sent, started = self._recorded + raw = r.read() + write(f"http://{self.host}:{self.port}{url}", sent, r.status, reply_of(raw), started) + r.read = lambda amt=None: raw + return r + + +class Dropped: + """A socket: the request it sent is recorded when the script closes it without ever reading a reply.""" + + def __init__(self, sock, address): + self.sock, self.address, self.sent, self.started, self.read = sock, address, b"", time.time(), False + + def sendall(self, data, *a): + self.sent += data + return self.sock.sendall(data, *a) + + def makefile(self, *a, **kw): + self.read = True + return self.sock.makefile(*a, **kw) + + def recv(self, *a): + self.read = True + return self.sock.recv(*a) + + def close(self): + if self.sent and not self.read: + head, _, body = self.sent.partition(b"\r\n\r\n") + path = head.split(b" ")[1].decode() + write(f"http://{self.address[0]}:{self.address[1]}{path}", body_of(body), None, None, self.started, + note="client closed the socket without reading a reply") + self.sent = b"" + return self.sock.close() + + def __getattr__(self, name): + return getattr(self.sock, name) + + +real_connect = socket.create_connection +urllib.request.urlopen = urlopen +http.client.HTTPConnection.request, http.client.HTTPConnection.getresponse = request, getresponse +socket.create_connection = lambda address, *a, **kw: Dropped(real_connect(address, *a, **kw), address) +sys.argv = [str(script), *args] +runpy.run_path(str(script), run_name="__main__") diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/run.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/run.log new file mode 100644 index 0000000000..ea391a6c1f --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/run.log @@ -0,0 +1,43 @@ +pgrep: pattern that searches for process name longer than 15 characters will result in zero matches +Try `pgrep -f' option to match against the complete command line. +pgrep: pattern that searches for process name longer than 15 characters will result in zero matches +Try `pgrep -f' option to match against the complete command line. +pgrep: pattern that searches for process name longer than 15 characters will result in zero matches +Try `pgrep -f' option to match against the complete command line. +pgrep: pattern that searches for process name longer than 15 characters will result in zero matches +Try `pgrep -f' option to match against the complete command line. +pgrep: pattern that searches for process name longer than 15 characters will result in zero matches +Try `pgrep -f' option to match against the complete command line. +== 2026-10-31T19:13:41Z server ex-exact-nocache: context 32768, parallel 4, prompt cache 0 GiB +== 2026-10-31T19:14:19Z step rewind-exact-nocache +== 2026-10-31T19:19:28Z step rewind-exact-nocache rc=0 +== 2026-10-31T19:19:30Z server ex-exact: context 32768, parallel 4, prompt cache 1 GiB +== 2026-10-31T19:20:00Z step serve-check-exact +== 2026-10-31T19:21:10Z step serve-check-exact rc=0 +== 2026-10-31T19:21:10Z step serve-cancel-exact +== 2026-10-31T19:21:15Z step serve-cancel-exact rc=0 +== 2026-10-31T19:21:15Z step rewind-exact +== 2026-10-31T19:21:48Z step rewind-exact rc=0 +== 2026-10-31T19:21:49Z step generate-exact-chunk512 +== 2026-10-31T19:22:36Z step generate-exact-chunk512 rc=0 +== 2026-10-31T19:22:36Z step generate-exact-chunk2048 +== 2026-10-31T19:23:19Z step generate-exact-chunk2048 rc=0 +== 2026-10-31T19:23:19Z step generate-exact-chunk8192 +== 2026-10-31T19:24:00Z step generate-exact-chunk8192 rc=0 +== 2026-10-31T19:24:00Z step generate-exact-chunk20480 +== 2026-10-31T19:24:45Z step generate-exact-chunk20480 rc=0 +## Exactness +| numerics | serve_check | accepted/drafted (served) | token-hash audit | serve_cancel | rewind (cache on vs off) | one chunk hash | +|---|---|---|---|---|---|---| +| exact | 15 ok, 0 fail | 1285/1688 | 11 groups, 0 differ | 3 ok, 0 fail | 0 differ (rc 0), up to 10240 cached tokens | yes | + +## Prompt-chunk seams (`generate --chat --max 64 --hash`) +| numerics | --chunk | prompt tokens | logits hash | rc | +|---|---|---|---|---| +| exact | 512 | 10368 | c8f6888043c972e0 | 0 | +| exact | 2048 | 10368 | c8f6888043c972e0 | 0 | +| exact | 8192 | 10368 | c8f6888043c972e0 | 0 | +| exact | 20480 | 10368 | c8f6888043c972e0 | 0 | + +Seams exercised (prompt longer than 8,192 and shorter than the largest chunk): exact True. +== 2026-10-31T19:24:45Z exactness done; next: finalize.sh diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/runs/ex-exact-nocache.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/runs/ex-exact-nocache.json new file mode 100644 index 0000000000..fb963bc8b4 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/runs/ex-exact-nocache.json @@ -0,0 +1,48 @@ +{ + "tag": "ex-exact-nocache", + "context": 32768, + "parallel": 4, + "prompt_cache_gib": 0, + "flags": "", + "ready_s": 38, + "status": "ready", + "server_exit": 0, + "ram_class_gib": 192, + "mem_total_gib": 184.58, + "load": { + "serving_line": "[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: MTP + copies; context: 32768; loaded in 37.5s)", + "loaded_s": 37.5, + "startup_lines": [ + "[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 82.15 GiB on the device, 4 streams of 32832 positions, 1.09 GiB each; prompts in 4096-row chunks" + ], + "tail": [] + }, + "sample_interval_s": 1.0, + "samples": 287, + "process": { + "rss_peak_sampled_bytes": 111522340864, + "rss_lifetime_peak_bytes": 112510197760, + "scope": "VmRSS/VmHWM of the one server process; device memory is not in it" + }, + "device": { + "scope": "amdgpu sysfs, whole card; baseline taken idle before the server started", + "gtt_baseline_bytes": 31657984, + "gtt_peak_bytes": 89199894528, + "gtt_peak_over_baseline_bytes": 89168236544, + "gtt_total_bytes": 193273528320, + "vram_baseline_bytes": 187670528, + "vram_peak_bytes": 200482816, + "vram_peak_over_baseline_bytes": 12812288, + "vram_total_bytes": 4294967296 + }, + "server_memory_endpoint": { + "active_bytes": 88206068372, + "cache_bytes": 0, + "peak_bytes": 88231245220, + "peak_scope": "since_start_or_health_reset" + }, + "server_resident_peak_bytes": 112510197760.0, + "drafted_total": 198.0, + "accepted_total": 141.0, + "spec_hit_rate": 0.7121212121212122 +} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/runs/ex-exact.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/runs/ex-exact.json new file mode 100644 index 0000000000..dc3134a7d3 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/runs/ex-exact.json @@ -0,0 +1,48 @@ +{ + "tag": "ex-exact", + "context": 32768, + "parallel": 4, + "prompt_cache_gib": 1, + "flags": "", + "ready_s": 30, + "status": "ready", + "server_exit": 0, + "ram_class_gib": 192, + "mem_total_gib": 184.58, + "load": { + "serving_line": "[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: MTP + copies; context: 32768; loaded in 29.6s)", + "loaded_s": 29.6, + "startup_lines": [ + "[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 82.15 GiB on the device, 4 streams of 32832 positions, 1.09 GiB each; prompts in 4096-row chunks" + ], + "tail": [] + }, + "sample_interval_s": 1.0, + "samples": 116, + "process": { + "rss_peak_sampled_bytes": 109333901312, + "rss_lifetime_peak_bytes": 109884239872, + "scope": "VmRSS/VmHWM of the one server process; device memory is not in it" + }, + "device": { + "scope": "amdgpu sysfs, whole card; baseline taken idle before the server started", + "gtt_baseline_bytes": 31657984, + "gtt_peak_bytes": 92512325632, + "gtt_peak_over_baseline_bytes": 92480667648, + "gtt_total_bytes": 193273528320, + "vram_baseline_bytes": 187670528, + "vram_peak_bytes": 205484032, + "vram_peak_over_baseline_bytes": 17813504, + "vram_total_bytes": 4294967296 + }, + "server_memory_endpoint": { + "active_bytes": 91494358724, + "cache_bytes": 0, + "peak_bytes": 91519535572, + "peak_scope": "since_start_or_health_reset" + }, + "server_resident_peak_bytes": 109884239872.0, + "drafted_total": 2088.0, + "accepted_total": 1572.0, + "spec_hit_rate": 0.7528735632183908 +} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/steps.tsv b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/steps.tsv new file mode 100644 index 0000000000..5460299928 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/steps.tsv @@ -0,0 +1,8 @@ +rewind-exact-nocache 0 309 ex-exact-nocache +serve-check-exact 0 70 ex-exact +serve-cancel-exact 0 5 ex-exact +rewind-exact 0 33 ex-exact +generate-exact-chunk512 0 47 - +generate-exact-chunk2048 0 43 - +generate-exact-chunk8192 0 41 - +generate-exact-chunk20480 0 45 - diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/summary.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/summary.json new file mode 100644 index 0000000000..d9c7987da2 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/summary.json @@ -0,0 +1,51 @@ +{ + "exact": { + "serve_check": { + "ok": 15, + "fail": 0, + "rc": 0, + "groups": 11, + "groups_with_different_hashes": 0, + "drafted": 1688, + "accepted": 1285 + }, + "serve_cancel": { + "ok": 3, + "fail": 0, + "rc": 0 + }, + "rewind": { + "differing": 0, + "rc": 0, + "max_cached_tokens": 10240 + }, + "chunks": { + "2048": { + "rc": 0, + "prompt_tokens": "10368", + "hash": "c8f6888043c972e0", + "ids": null + }, + "20480": { + "rc": 0, + "prompt_tokens": "10368", + "hash": "c8f6888043c972e0", + "ids": null + }, + "512": { + "rc": 0, + "prompt_tokens": "10368", + "hash": "c8f6888043c972e0", + "ids": null + }, + "8192": { + "rc": 0, + "prompt_tokens": "10368", + "hash": "c8f6888043c972e0", + "ids": null + } + }, + "one_hash": true, + "seams_exercised": true + } +} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/summary.md b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/summary.md new file mode 100644 index 0000000000..42db634cbb --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/exactness/summary.md @@ -0,0 +1,14 @@ +## Exactness +| numerics | serve_check | accepted/drafted (served) | token-hash audit | serve_cancel | rewind (cache on vs off) | one chunk hash | +|---|---|---|---|---|---|---| +| exact | 15 ok, 0 fail | 1285/1688 | 11 groups, 0 differ | 3 ok, 0 fail | 0 differ (rc 0), up to 10240 cached tokens | yes | + +## Prompt-chunk seams (`generate --chat --max 64 --hash`) +| numerics | --chunk | prompt tokens | logits hash | rc | +|---|---|---|---|---| +| exact | 512 | 10368 | c8f6888043c972e0 | 0 | +| exact | 2048 | 10368 | c8f6888043c972e0 | 0 | +| exact | 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file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/environment.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/environment.json new file mode 100644 index 0000000000..23b3ef40d1 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/environment.json @@ -0,0 +1,7 @@ +{ + "gpu_arch": "gfx1151", + "rocm": "7.15.26333-0000000", + "python": "3.13.5", + "mem_total_kib": 193548104, + "native_window_tokens": 262144 +} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/hash-base.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/hash-base.log new file mode 100644 index 0000000000..dc0595c6f3 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/hash-base.log @@ -0,0 +1,23 @@ +loaded in 7.5 s, 75.82 GiB on the device +prompt 24 tokens in 0.920 s (26.1 tok/s); 63 tokens in 2.195 s (28.70 tok/s) +logits hash 243ecea88fe50d9f +ids { 71093, 12305, 198, 727, 73111, 1393, 25, 514, 8, 1411, 514, 25, 198, 262, 4071, 198, 262, 3301, 279, 307, 7324, 76938, 1324, 13, 198, 1031, 262, 561, 76938, 8240, 8211, 440, 426, 7, 15, 8, 283, 220, 15, 11, 426, 7, 16, 8, 283, 220, 16, 11, 321, 1754, 16905, 198, 262, 1324, 369, 279, 2542, 314, 279, 1330, 36497, 5981, 13, 198 } +--- +<|im_start|>user +Write a Python function that returns the n-th Fibonacci number.<|im_end|> +<|im_start|>assistant + + + + +```python +def fibonacci(n: int) -> int: + """ + Return the n-th Fibonacci number. + + The Fibonacci sequence starts with F(0) = 0, F(1) = 1, and each subsequent + number is the sum of the two preceding ones. + +--- +info: graphs: 1 captured (3 ms each), 61 of 63 rounds replayed +rc=0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/hash-new.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/hash-new.log new file mode 100644 index 0000000000..c76f855613 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/hash-new.log @@ -0,0 +1,23 @@ +loaded in 28.7 s, 75.92 GiB on the device +prompt 24 tokens in 0.144 s (166.4 tok/s); 63 tokens in 1.634 s (38.55 tok/s) +logits hash 243ecea88fe50d9f +ids { 71093, 12305, 198, 727, 73111, 1393, 25, 514, 8, 1411, 514, 25, 198, 262, 4071, 198, 262, 3301, 279, 307, 7324, 76938, 1324, 13, 198, 1031, 262, 561, 76938, 8240, 8211, 440, 426, 7, 15, 8, 283, 220, 15, 11, 426, 7, 16, 8, 283, 220, 16, 11, 321, 1754, 16905, 198, 262, 1324, 369, 279, 2542, 314, 279, 1330, 36497, 5981, 13, 198 } +--- +<|im_start|>user +Write a Python function that returns the n-th Fibonacci number.<|im_end|> +<|im_start|>assistant + + + + +```python +def fibonacci(n: int) -> int: + """ + Return the n-th Fibonacci number. + + The Fibonacci sequence starts with F(0) = 0, F(1) = 1, and each subsequent + number is the sum of the two preceding ones. + +--- +info: graphs: 1 captured (8 ms each), 61 of 63 rounds replayed +rc=0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/cold-base-131072-r1.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/cold-base-131072-r1.log new file mode 100644 index 0000000000..a559d5421e --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/cold-base-131072-r1.log @@ -0,0 +1 @@ +{"expected_prompt_tokens": 131072, "prompt_tokens": 131072, "cached_tokens": 0, "ttft_s": 507.8125120110053, "prefill_tps": 258.1110092796599} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/cold-base-131072-r2.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/cold-base-131072-r2.log new file mode 100644 index 0000000000..ec19161195 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/cold-base-131072-r2.log @@ -0,0 +1 @@ +{"expected_prompt_tokens": 131072, "prompt_tokens": 131072, "cached_tokens": 0, "ttft_s": 508.40254470999935, "prefill_tps": 257.81145543786664} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/cold-base-2048-r1.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/cold-base-2048-r1.log new file mode 100644 index 0000000000..fa5dbd84f4 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/cold-base-2048-r1.log @@ -0,0 +1 @@ +{"expected_prompt_tokens": 2048, "prompt_tokens": 2048, "cached_tokens": 0, "ttft_s": 7.06196431198623, "prefill_tps": 290.0042976037052} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/cold-base-2048-r2.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/cold-base-2048-r2.log new file mode 100644 index 0000000000..e9d4ac940b --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/cold-base-2048-r2.log @@ -0,0 +1 @@ +{"expected_prompt_tokens": 2048, "prompt_tokens": 2048, "cached_tokens": 0, "ttft_s": 6.909189859987237, "prefill_tps": 296.41680739741366} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/cold-base-261888-r1.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/cold-base-261888-r1.log new file mode 100644 index 0000000000..bf07379e0a --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/cold-base-261888-r1.log @@ -0,0 +1 @@ +{"expected_prompt_tokens": 261888, "prompt_tokens": 261888, "cached_tokens": 0, "ttft_s": 1068.3615734420018, "prefill_tps": 245.13049374872253} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/cold-base-261888-r2.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/cold-base-261888-r2.log new file mode 100644 index 0000000000..e7c87f9ec3 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/cold-base-261888-r2.log @@ -0,0 +1 @@ +{"expected_prompt_tokens": 261888, "prompt_tokens": 261888, "cached_tokens": 0, "ttft_s": 1071.3024943700002, "prefill_tps": 244.45756579145112} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/cold-base-32768-r1.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/cold-base-32768-r1.log new file mode 100644 index 0000000000..115902ce8b --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/cold-base-32768-r1.log @@ -0,0 +1 @@ +{"expected_prompt_tokens": 32768, "prompt_tokens": 32768, "cached_tokens": 0, "ttft_s": 125.98323771200376, "prefill_tps": 260.09809396157345} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/cold-base-32768-r2.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/cold-base-32768-r2.log new file mode 100644 index 0000000000..48a1ed6f15 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/cold-base-32768-r2.log @@ -0,0 +1 @@ +{"expected_prompt_tokens": 32768, "prompt_tokens": 32768, "cached_tokens": 0, "ttft_s": 125.7340703390073, "prefill_tps": 260.61353069736873} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/cold-base-65536-r1.log 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b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/openai-base-r1.log @@ -0,0 +1,2 @@ +{"label": "base-r1", "prompt": "fibonacci-raw", "temperature": 0.0, "decode_tps_median": 50.94231226334963, "decode_tps_all": [50.94, 50.55, 51.82], "ttft_s_median": 0.1237561879970599, "prefill_tps_median": 113.126, "itl_mean_ms_median": 19.63, "itl_p50_ms_median": 0.0, "itl_p95_ms_median": 60.457, "round_gap_p50_ms_median": 51.767, "round_gap_p95_ms_median": 61.898, "tokens_per_chunk_median": 2.753} +{"label": "base-r1", "prompt": "gpu-chat-no-think", "temperature": 0.0, "decode_tps_median": 46.230151172948915, "decode_tps_all": [47.64, 46.23, 45.68], "ttft_s_median": 0.23948523399303667, "prefill_tps_median": 129.444, "itl_mean_ms_median": 21.631, "itl_p50_ms_median": 0.0, "itl_p95_ms_median": 59.392, "round_gap_p50_ms_median": 50.651, "round_gap_p95_ms_median": 61.651, "tokens_per_chunk_median": 2.37} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/openai-base-r2.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/openai-base-r2.log new file mode 100644 index 0000000000..73d06ba838 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/openai-base-r2.log @@ -0,0 +1,2 @@ +{"label": "base-r2", "prompt": "fibonacci-raw", "temperature": 0.0, "decode_tps_median": 50.65589029239793, "decode_tps_all": [50.66, 49.37, 51.01], "ttft_s_median": 0.12365881900768727, "prefill_tps_median": 113.215, "itl_mean_ms_median": 19.741, "itl_p50_ms_median": 0.0, "itl_p95_ms_median": 60.643, "round_gap_p50_ms_median": 51.903, "round_gap_p95_ms_median": 61.958, "tokens_per_chunk_median": 2.753} +{"label": "base-r2", "prompt": "gpu-chat-no-think", "temperature": 0.0, "decode_tps_median": 44.70131133081844, "decode_tps_all": [44.7, 43.34, 44.8], "ttft_s_median": 0.2396756490052212, "prefill_tps_median": 129.341, "itl_mean_ms_median": 22.371, "itl_p50_ms_median": 0.0, "itl_p95_ms_median": 59.394, "round_gap_p50_ms_median": 50.412, "round_gap_p95_ms_median": 61.547, "tokens_per_chunk_median": 2.37} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/openai-new-r1.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/openai-new-r1.log new file mode 100644 index 0000000000..091053df7d --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/openai-new-r1.log @@ -0,0 +1,2 @@ +{"label": "new-r1", "prompt": "fibonacci-raw", "temperature": 0.0, "decode_tps_median": 69.15345703661757, "decode_tps_all": [69.77, 68.12, 69.15], "ttft_s_median": 0.09834573298576288, "prefill_tps_median": 142.355, "itl_mean_ms_median": 14.461, "itl_p50_ms_median": 0.0, "itl_p95_ms_median": 70.896, "round_gap_p50_ms_median": 45.971, "round_gap_p95_ms_median": 112.928, "tokens_per_chunk_median": 3.71} +{"label": "new-r1", "prompt": "gpu-chat-no-think", "temperature": 0.0, "decode_tps_median": 55.4400335994644, "decode_tps_all": [56.07, 55.44, 55.2], "ttft_s_median": 0.1711614170053508, "prefill_tps_median": 181.116, "itl_mean_ms_median": 18.038, "itl_p50_ms_median": 0.0, "itl_p95_ms_median": 58.012, "round_gap_p50_ms_median": 38.606, "round_gap_p95_ms_median": 118.704, "tokens_per_chunk_median": 2.462} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/openai-new-r2.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/openai-new-r2.log new file mode 100644 index 0000000000..033696f3de --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/openai-new-r2.log @@ -0,0 +1,2 @@ +{"label": "new-r2", "prompt": "fibonacci-raw", "temperature": 0.0, "decode_tps_median": 68.92013159633264, "decode_tps_all": [68.92, 68.84, 69.03], "ttft_s_median": 0.09981447600875981, "prefill_tps_median": 140.26, "itl_mean_ms_median": 14.51, "itl_p50_ms_median": 0.0, "itl_p95_ms_median": 73.213, "round_gap_p50_ms_median": 44.973, "round_gap_p95_ms_median": 93.904, "tokens_per_chunk_median": 3.71} +{"label": "new-r2", "prompt": "gpu-chat-no-think", "temperature": 0.0, "decode_tps_median": 56.392749687389006, "decode_tps_all": [56.15, 57.61, 56.39], "ttft_s_median": 0.16568006199668162, "prefill_tps_median": 187.108, "itl_mean_ms_median": 17.733, "itl_p50_ms_median": 0.0, "itl_p95_ms_median": 54.016, "round_gap_p50_ms_median": 38.419, "round_gap_p95_ms_median": 71.808, "tokens_per_chunk_median": 2.462} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-base-131072-r1.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-base-131072-r1.log new file mode 100644 index 0000000000..c13f7da667 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-base-131072-r1.log @@ -0,0 +1,15 @@ +[tensorfold] HIP rank 0 of 1: policy matrix=auto,attention=auto,kernels=auto,graphs=auto,prefill_step=1024,fill_rows=512; mtp drafts 3 under 0.3, 8 snapshots +[tensorfold] open-file limit raised: soft 1024 -> 524288 +warning: libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 76.58 GiB on the device, 1 stream of 139328 positions, 4.54 GiB each; prompts in 1024-row chunks +[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: MTP + copies; context: 139264; loaded in 12.8s) +[tensorfold] 127.0.0.1 "GET /health HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-82d2b80d44a97fef91fb0d8387fae337 prompt=256 cached=0 thinking=False effort=none tokens=1 sha=3635a91e3da8 finish=length rounds=0 accepted=0/0 ttft=2.092 decode=0.000 elapsed=2.092 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-bbf297c4125afefcf8779cac290b6f9a prompt=131072 cached=0 thinking=False effort=none tokens=1 sha=397ed1e27591 finish=length rounds=0 accepted=0/0 ttft=507.808 decode=0.000 elapsed=507.808 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "GET /memory HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /metrics HTTP/1.1" 200 - +[tensorfold] shutting down (SIGTERM): draining: new requests get 503; 0 request(s) in progress may finish within 20.0 s +[tensorfold] shutting down: drained +[tensorfold] shutting down: stopped diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-base-131072-r2.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-base-131072-r2.log new file mode 100644 index 0000000000..eb43c82768 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-base-131072-r2.log @@ -0,0 +1,15 @@ +[tensorfold] HIP rank 0 of 1: policy matrix=auto,attention=auto,kernels=auto,graphs=auto,prefill_step=1024,fill_rows=512; mtp drafts 3 under 0.3, 8 snapshots +[tensorfold] open-file limit raised: soft 1024 -> 524288 +warning: libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 76.58 GiB on the device, 1 stream of 139328 positions, 4.54 GiB each; prompts in 1024-row chunks +[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: MTP + copies; context: 139264; loaded in 13.2s) +[tensorfold] 127.0.0.1 "GET /health HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-67ff196b409b0691c05bf73c8c74c3da prompt=256 cached=0 thinking=False effort=none tokens=1 sha=3635a91e3da8 finish=length rounds=0 accepted=0/0 ttft=2.092 decode=0.000 elapsed=2.092 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-b224d2701faa9975f0119717cd0c5f4d prompt=131072 cached=0 thinking=False effort=none tokens=1 sha=397ed1e27591 finish=length rounds=0 accepted=0/0 ttft=508.397 decode=0.000 elapsed=508.397 queued=0.001 tok/s=0.0 +[tensorfold] 127.0.0.1 "GET /memory HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /metrics HTTP/1.1" 200 - +[tensorfold] shutting down (SIGTERM): draining: new requests get 503; 0 request(s) in progress may finish within 20.0 s +[tensorfold] shutting down: drained +[tensorfold] shutting down: stopped diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-base-2048-r1.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-base-2048-r1.log new file mode 100644 index 0000000000..07a9341830 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-base-2048-r1.log @@ -0,0 +1,15 @@ +[tensorfold] HIP rank 0 of 1: policy matrix=auto,attention=auto,kernels=auto,graphs=auto,prefill_step=1024,fill_rows=512; mtp drafts 3 under 0.3, 8 snapshots +[tensorfold] open-file limit raised: soft 1024 -> 524288 +warning: libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 76.58 GiB on the device, 1 stream of 10304 positions, 0.84 GiB each; prompts in 1024-row chunks +[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: MTP + copies; context: 10240; loaded in 11.7s) +[tensorfold] 127.0.0.1 "GET /health HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-c36e5c5145170cb9867b7765d4bbf756 prompt=256 cached=0 thinking=False effort=none tokens=1 sha=3635a91e3da8 finish=length rounds=0 accepted=0/0 ttft=1.950 decode=0.000 elapsed=1.950 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-7fe00d96051c48cb81dc3b6f39e85005 prompt=2048 cached=0 thinking=False effort=none tokens=1 sha=82a93b152b27 finish=length rounds=0 accepted=0/0 ttft=7.061 decode=0.000 elapsed=7.061 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "GET /memory HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /metrics HTTP/1.1" 200 - +[tensorfold] shutting down (SIGTERM): draining: new requests get 503; 0 request(s) in progress may finish within 20.0 s +[tensorfold] shutting down: drained +[tensorfold] shutting down: stopped diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-base-2048-r2.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-base-2048-r2.log new file mode 100644 index 0000000000..1bd1ab1b99 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-base-2048-r2.log @@ -0,0 +1,15 @@ +[tensorfold] HIP rank 0 of 1: policy matrix=auto,attention=auto,kernels=auto,graphs=auto,prefill_step=1024,fill_rows=512; mtp drafts 3 under 0.3, 8 snapshots +[tensorfold] open-file limit raised: soft 1024 -> 524288 +warning: libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 76.58 GiB on the device, 1 stream of 10304 positions, 0.84 GiB each; prompts in 1024-row chunks +[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: MTP + copies; context: 10240; loaded in 12.0s) +[tensorfold] 127.0.0.1 "GET /health HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-6d5a2b3f3166fa969fb1d3e45eb78bb3 prompt=256 cached=0 thinking=False effort=none tokens=1 sha=3635a91e3da8 finish=length rounds=0 accepted=0/0 ttft=1.891 decode=0.000 elapsed=1.891 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-0ad9050ad5d5b39b6515c892cf194f07 prompt=2048 cached=0 thinking=False effort=none tokens=1 sha=82a93b152b27 finish=length rounds=0 accepted=0/0 ttft=6.909 decode=0.000 elapsed=6.909 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "GET /memory HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /metrics HTTP/1.1" 200 - +[tensorfold] shutting down (SIGTERM): draining: new requests get 503; 0 request(s) in progress may finish within 20.0 s +[tensorfold] shutting down: drained +[tensorfold] shutting down: stopped diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-base-261888-r1.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-base-261888-r1.log new file mode 100644 index 0000000000..e98447727a --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-base-261888-r1.log @@ -0,0 +1,15 @@ +[tensorfold] HIP rank 0 of 1: policy matrix=auto,attention=auto,kernels=auto,graphs=auto,prefill_step=1024,fill_rows=512; mtp drafts 3 under 0.3, 8 snapshots +[tensorfold] open-file limit raised: soft 1024 -> 524288 +warning: libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 76.58 GiB on the device, 1 stream of 262208 positions, 8.07 GiB each; prompts in 1024-row chunks +[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: MTP + copies; context: 262144; loaded in 12.2s) +[tensorfold] 127.0.0.1 "GET /health HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-5b433ea67a5ff868af555a8700448f21 prompt=256 cached=0 thinking=False effort=none tokens=1 sha=3635a91e3da8 finish=length rounds=0 accepted=0/0 ttft=2.302 decode=0.000 elapsed=2.303 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-b558bf72f7c1495952f56a55e47a6f17 prompt=261888 cached=0 thinking=False effort=none tokens=1 sha=52beab51fc39 finish=length rounds=0 accepted=0/0 ttft=1068.353 decode=0.000 elapsed=1068.353 queued=0.001 tok/s=0.0 +[tensorfold] 127.0.0.1 "GET /memory HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /metrics HTTP/1.1" 200 - +[tensorfold] shutting down (SIGTERM): draining: new requests get 503; 0 request(s) in progress may finish within 20.0 s +[tensorfold] shutting down: drained +[tensorfold] shutting down: stopped diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-base-261888-r2.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-base-261888-r2.log new file mode 100644 index 0000000000..d2774734d2 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-base-261888-r2.log @@ -0,0 +1,15 @@ +[tensorfold] HIP rank 0 of 1: policy matrix=auto,attention=auto,kernels=auto,graphs=auto,prefill_step=1024,fill_rows=512; mtp drafts 3 under 0.3, 8 snapshots +[tensorfold] open-file limit raised: soft 1024 -> 524288 +warning: libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 76.58 GiB on the device, 1 stream of 262208 positions, 8.07 GiB each; prompts in 1024-row chunks +[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: MTP + copies; context: 262144; loaded in 13.0s) +[tensorfold] 127.0.0.1 "GET /health HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-89205b474bc20bfd145d3cc575a72b07 prompt=256 cached=0 thinking=False effort=none tokens=1 sha=3635a91e3da8 finish=length rounds=0 accepted=0/0 ttft=2.183 decode=0.000 elapsed=2.183 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-5895dcb797312b02917458352d048c40 prompt=261888 cached=0 thinking=False effort=none tokens=1 sha=52beab51fc39 finish=length rounds=0 accepted=0/0 ttft=1071.293 decode=0.000 elapsed=1071.293 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "GET /memory HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /metrics HTTP/1.1" 200 - +[tensorfold] shutting down (SIGTERM): draining: new requests get 503; 0 request(s) in progress may finish within 20.0 s +[tensorfold] shutting down: drained +[tensorfold] shutting down: stopped diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-base-32768-r1.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-base-32768-r1.log new file mode 100644 index 0000000000..04bf5ee91b --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-base-32768-r1.log @@ -0,0 +1,15 @@ +[tensorfold] HIP rank 0 of 1: policy matrix=auto,attention=auto,kernels=auto,graphs=auto,prefill_step=1024,fill_rows=512; mtp drafts 3 under 0.3, 8 snapshots +[tensorfold] open-file limit raised: soft 1024 -> 524288 +warning: libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 76.58 GiB on the device, 1 stream of 41024 positions, 1.73 GiB each; prompts in 1024-row chunks +[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: MTP + copies; context: 40960; loaded in 13.0s) +[tensorfold] 127.0.0.1 "GET /health HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-315bf3578ea5046b869f9efac40ab837 prompt=256 cached=0 thinking=False effort=none tokens=1 sha=3635a91e3da8 finish=length rounds=0 accepted=0/0 ttft=2.026 decode=0.000 elapsed=2.027 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-dcafd42730ebdd0a43c684afb6750862 prompt=32768 cached=0 thinking=False effort=none tokens=1 sha=7104741a92e7 finish=length rounds=0 accepted=0/0 ttft=125.939 decode=0.000 elapsed=125.939 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "GET /memory HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /metrics HTTP/1.1" 200 - +[tensorfold] shutting down (SIGTERM): draining: new requests get 503; 0 request(s) in progress may finish within 20.0 s +[tensorfold] shutting down: drained +[tensorfold] shutting down: stopped diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-base-32768-r2.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-base-32768-r2.log new file mode 100644 index 0000000000..dfb9456745 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-base-32768-r2.log @@ -0,0 +1,15 @@ +[tensorfold] HIP rank 0 of 1: policy matrix=auto,attention=auto,kernels=auto,graphs=auto,prefill_step=1024,fill_rows=512; mtp drafts 3 under 0.3, 8 snapshots +[tensorfold] open-file limit raised: soft 1024 -> 524288 +warning: libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 76.58 GiB on the device, 1 stream of 41024 positions, 1.73 GiB each; prompts in 1024-row chunks +[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: MTP + copies; context: 40960; loaded in 12.5s) +[tensorfold] 127.0.0.1 "GET /health HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-f4986d33934af57a609fe40f53cd4772 prompt=256 cached=0 thinking=False effort=none tokens=1 sha=3635a91e3da8 finish=length rounds=0 accepted=0/0 ttft=1.956 decode=0.000 elapsed=1.956 queued=0.001 tok/s=0.0 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-6e63f58fb39feb46767ea54b818a4f49 prompt=32768 cached=0 thinking=False effort=none tokens=1 sha=7104741a92e7 finish=length rounds=0 accepted=0/0 ttft=125.732 decode=0.000 elapsed=125.732 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "GET /memory HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /metrics HTTP/1.1" 200 - +[tensorfold] shutting down (SIGTERM): draining: new requests get 503; 0 request(s) in progress may finish within 20.0 s +[tensorfold] shutting down: drained +[tensorfold] shutting down: stopped diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-base-65536-r1.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-base-65536-r1.log new file mode 100644 index 0000000000..b62e9028af --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-base-65536-r1.log @@ -0,0 +1,15 @@ +[tensorfold] HIP rank 0 of 1: policy matrix=auto,attention=auto,kernels=auto,graphs=auto,prefill_step=1024,fill_rows=512; mtp drafts 3 under 0.3, 8 snapshots +[tensorfold] open-file limit raised: soft 1024 -> 524288 +warning: libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 76.58 GiB on the device, 1 stream of 73792 positions, 2.66 GiB each; prompts in 1024-row chunks +[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: MTP + copies; context: 73728; loaded in 12.2s) +[tensorfold] 127.0.0.1 "GET /health HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-770119f77ffac7ff804a31500c1c946d prompt=256 cached=0 thinking=False effort=none tokens=1 sha=3635a91e3da8 finish=length rounds=0 accepted=0/0 ttft=2.119 decode=0.000 elapsed=2.119 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-8646331847412af4a1cc33897a5e755f prompt=65536 cached=0 thinking=False effort=none tokens=1 sha=7d7e080fddd8 finish=length rounds=0 accepted=0/0 ttft=252.718 decode=0.000 elapsed=252.718 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "GET /memory HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /metrics HTTP/1.1" 200 - +[tensorfold] shutting down (SIGTERM): draining: new requests get 503; 0 request(s) in progress may finish within 20.0 s +[tensorfold] shutting down: drained +[tensorfold] shutting down: stopped diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-base-65536-r2.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-base-65536-r2.log new file mode 100644 index 0000000000..e6c0c816ef --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-base-65536-r2.log @@ -0,0 +1,15 @@ +[tensorfold] HIP rank 0 of 1: policy matrix=auto,attention=auto,kernels=auto,graphs=auto,prefill_step=1024,fill_rows=512; mtp drafts 3 under 0.3, 8 snapshots +[tensorfold] open-file limit raised: soft 1024 -> 524288 +warning: libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 76.58 GiB on the device, 1 stream of 73792 positions, 2.66 GiB each; prompts in 1024-row chunks +[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: MTP + copies; context: 73728; loaded in 12.5s) +[tensorfold] 127.0.0.1 "GET /health HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-4978618dea3e302c92ea37e5d0e14931 prompt=256 cached=0 thinking=False effort=none tokens=1 sha=3635a91e3da8 finish=length rounds=0 accepted=0/0 ttft=1.990 decode=0.000 elapsed=1.990 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-53872f60d9dbe60ec8755609ba7eaac3 prompt=65536 cached=0 thinking=False effort=none tokens=1 sha=7d7e080fddd8 finish=length rounds=0 accepted=0/0 ttft=252.725 decode=0.000 elapsed=252.725 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "GET /memory HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /metrics HTTP/1.1" 200 - +[tensorfold] shutting down (SIGTERM): draining: new requests get 503; 0 request(s) in progress may finish within 20.0 s +[tensorfold] shutting down: drained +[tensorfold] shutting down: stopped diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-base-8192-r1.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-base-8192-r1.log new file mode 100644 index 0000000000..9f329175b7 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-base-8192-r1.log @@ -0,0 +1,15 @@ +[tensorfold] HIP rank 0 of 1: policy matrix=auto,attention=auto,kernels=auto,graphs=auto,prefill_step=1024,fill_rows=512; mtp drafts 3 under 0.3, 8 snapshots +[tensorfold] open-file limit raised: soft 1024 -> 524288 +warning: libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 76.58 GiB on the device, 1 stream of 16448 positions, 1.02 GiB each; prompts in 1024-row chunks +[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: MTP + copies; context: 16384; loaded in 12.3s) +[tensorfold] 127.0.0.1 "GET /health HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-e8d2d4a957f249aac890192bc15ef155 prompt=256 cached=0 thinking=False effort=none tokens=1 sha=3635a91e3da8 finish=length rounds=0 accepted=0/0 ttft=2.018 decode=0.000 elapsed=2.018 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-bf8e81c4d3338c2aec3c763f83ce566f prompt=8192 cached=0 thinking=False effort=none tokens=1 sha=731e88ce52c6 finish=length rounds=0 accepted=0/0 ttft=31.351 decode=0.000 elapsed=31.351 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "GET /memory HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /metrics HTTP/1.1" 200 - +[tensorfold] shutting down (SIGTERM): draining: new requests get 503; 0 request(s) in progress may finish within 20.0 s +[tensorfold] shutting down: drained +[tensorfold] shutting down: stopped diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-base-8192-r2.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-base-8192-r2.log new file mode 100644 index 0000000000..894e750665 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-base-8192-r2.log @@ -0,0 +1,15 @@ +[tensorfold] HIP rank 0 of 1: policy matrix=auto,attention=auto,kernels=auto,graphs=auto,prefill_step=1024,fill_rows=512; mtp drafts 3 under 0.3, 8 snapshots +[tensorfold] open-file limit raised: soft 1024 -> 524288 +warning: libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 76.58 GiB on the device, 1 stream of 16448 positions, 1.02 GiB each; prompts in 1024-row chunks +[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: MTP + copies; context: 16384; loaded in 12.4s) +[tensorfold] 127.0.0.1 "GET /health HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-167b27754b6b69c2017b3f61e10dfb44 prompt=256 cached=0 thinking=False effort=none tokens=1 sha=3635a91e3da8 finish=length rounds=0 accepted=0/0 ttft=2.009 decode=0.000 elapsed=2.009 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-97bc8690e5d6ca21459e52f6a99090c0 prompt=8192 cached=0 thinking=False effort=none tokens=1 sha=731e88ce52c6 finish=length rounds=0 accepted=0/0 ttft=31.305 decode=0.000 elapsed=31.306 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "GET /memory HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /metrics HTTP/1.1" 200 - +[tensorfold] shutting down (SIGTERM): draining: new requests get 503; 0 request(s) in progress may finish within 20.0 s +[tensorfold] shutting down: drained +[tensorfold] shutting down: stopped diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-new-131072-r1.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-new-131072-r1.log new file mode 100644 index 0000000000..7d3ac42fb5 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-new-131072-r1.log @@ -0,0 +1,17 @@ +[tensorfold] HIP rank 0 of 1: policy matrix=auto,attention=auto,kernels=auto,graphs=auto,prefill_step=4096,fill_rows=512,mtp_depth=gated; mtp drafts 7 under 0.9, 8 snapshots +info: lane costs ms by window rows 1:25.35 2:29.72 3:34.83 4:38.54 5:43.50 6:46.83 7:50.22 8:53.78; head step 1.306 +[tensorfold] open-file limit raised: soft 1024 -> 524288 +warning: libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 84.97 GiB on the device, 1 stream of 139328 positions, 4.15 GiB each; prompts in 4096-row chunks +[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: MTP + copies; context: 139264; loaded in 27.6s) +[tensorfold] 127.0.0.1 "GET /health HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-ded46e7c6e539cc360c38e6ee1e0db6b prompt=256 cached=0 thinking=False effort=none tokens=1 sha=3635a91e3da8 finish=length rounds=0 accepted=0/0 ttft=0.438 decode=0.000 elapsed=0.438 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-04082722078baeccd56a76a2b5e4abbf prompt=131072 cached=0 thinking=False effort=none tokens=1 sha=397ed1e27591 finish=length rounds=0 accepted=0/0 ttft=277.872 decode=0.000 elapsed=277.872 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "GET /memory HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /metrics HTTP/1.1" 200 - +[tensorfold] shutting down (SIGTERM): draining: new requests get 503; 0 request(s) in progress may finish within 20.0 s +[tensorfold] shutting down: drained +info: graphs: 8 captured (16 ms each), 64 of 80 rounds replayed +[tensorfold] shutting down: stopped diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-new-131072-r2.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-new-131072-r2.log new file mode 100644 index 0000000000..744da9d29b --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-new-131072-r2.log @@ -0,0 +1,17 @@ +[tensorfold] HIP rank 0 of 1: policy matrix=auto,attention=auto,kernels=auto,graphs=auto,prefill_step=4096,fill_rows=512,mtp_depth=gated; mtp drafts 7 under 0.9, 8 snapshots +info: lane costs ms by window rows 1:25.34 2:29.76 3:35.03 4:39.05 5:43.45 6:46.91 7:50.02 8:53.80; head step 1.325 +[tensorfold] open-file limit raised: soft 1024 -> 524288 +warning: libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 84.97 GiB on the device, 1 stream of 139328 positions, 4.15 GiB each; prompts in 4096-row chunks +[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: MTP + copies; context: 139264; loaded in 28.8s) +[tensorfold] 127.0.0.1 "GET /health HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-b6f10f7812bd6d67db9326aad4d13d79 prompt=256 cached=0 thinking=False effort=none tokens=1 sha=3635a91e3da8 finish=length rounds=0 accepted=0/0 ttft=0.453 decode=0.000 elapsed=0.453 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-55b5eeeaadd691cdd85ad85ecd8b66b8 prompt=131072 cached=0 thinking=False effort=none tokens=1 sha=397ed1e27591 finish=length rounds=0 accepted=0/0 ttft=277.984 decode=0.000 elapsed=277.985 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "GET /memory HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /metrics HTTP/1.1" 200 - +[tensorfold] shutting down (SIGTERM): draining: new requests get 503; 0 request(s) in progress may finish within 20.0 s +[tensorfold] shutting down: drained +info: graphs: 8 captured (29 ms each), 64 of 80 rounds replayed +[tensorfold] shutting down: stopped diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-new-2048-r1.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-new-2048-r1.log new file mode 100644 index 0000000000..2cd8930a21 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-new-2048-r1.log @@ -0,0 +1,17 @@ +[tensorfold] HIP rank 0 of 1: policy matrix=auto,attention=auto,kernels=auto,graphs=auto,prefill_step=4096,fill_rows=512,mtp_depth=gated; mtp drafts 7 under 0.9, 8 snapshots +info: lane costs ms by window rows 1:25.26 2:29.60 3:34.69 4:38.20 5:43.21 6:46.90 7:49.95 8:53.49; head step 1.287 +[tensorfold] open-file limit raised: soft 1024 -> 524288 +warning: libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 81.55 GiB on the device, 1 stream of 10304 positions, 0.45 GiB each; prompts in 4096-row chunks +[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: MTP + copies; context: 10240; loaded in 26.0s) +[tensorfold] 127.0.0.1 "GET /health HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-925286a7d88a0c756772a4c176f3d411 prompt=256 cached=0 thinking=False effort=none tokens=1 sha=3635a91e3da8 finish=length rounds=0 accepted=0/0 ttft=0.440 decode=0.003 elapsed=0.443 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-e9ff60b7c1ddb67ac4494a60b2c7d525 prompt=2048 cached=0 thinking=False effort=none tokens=1 sha=82a93b152b27 finish=length rounds=0 accepted=0/0 ttft=3.005 decode=0.000 elapsed=3.005 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "GET /memory HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /metrics HTTP/1.1" 200 - +[tensorfold] shutting down (SIGTERM): draining: new requests get 503; 0 request(s) in progress may finish within 20.0 s +[tensorfold] shutting down: drained +info: graphs: 8 captured (26 ms each), 64 of 80 rounds replayed +[tensorfold] shutting down: stopped diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-new-2048-r2.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-new-2048-r2.log new file mode 100644 index 0000000000..69968ceb1d --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-new-2048-r2.log @@ -0,0 +1,17 @@ +[tensorfold] HIP rank 0 of 1: policy matrix=auto,attention=auto,kernels=auto,graphs=auto,prefill_step=4096,fill_rows=512,mtp_depth=gated; mtp drafts 7 under 0.9, 8 snapshots +info: lane costs ms by window rows 1:25.24 2:29.59 3:34.71 4:38.32 5:43.21 6:46.64 7:49.89 8:53.57; head step 1.292 +[tensorfold] open-file limit raised: soft 1024 -> 524288 +warning: libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 81.55 GiB on the device, 1 stream of 10304 positions, 0.45 GiB each; prompts in 4096-row chunks +[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: MTP + copies; context: 10240; loaded in 25.1s) +[tensorfold] 127.0.0.1 "GET /health HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-22eb11560e0ac4368fea5d8702dbcd36 prompt=256 cached=0 thinking=False effort=none tokens=1 sha=3635a91e3da8 finish=length rounds=0 accepted=0/0 ttft=0.440 decode=0.000 elapsed=0.440 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-45fe881b1a1d6c9a595804d8c9aecfd8 prompt=2048 cached=0 thinking=False effort=none tokens=1 sha=82a93b152b27 finish=length rounds=0 accepted=0/0 ttft=3.031 decode=0.000 elapsed=3.031 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "GET /memory HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /metrics HTTP/1.1" 200 - +[tensorfold] shutting down (SIGTERM): draining: new requests get 503; 0 request(s) in progress may finish within 20.0 s +[tensorfold] shutting down: drained +info: graphs: 8 captured (17 ms each), 64 of 80 rounds replayed +[tensorfold] shutting down: stopped diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-new-261888-r1.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-new-261888-r1.log new file mode 100644 index 0000000000..be67384702 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-new-261888-r1.log @@ -0,0 +1,17 @@ +[tensorfold] HIP rank 0 of 1: policy matrix=auto,attention=auto,kernels=auto,graphs=auto,prefill_step=4096,fill_rows=512,mtp_depth=gated; mtp drafts 7 under 0.9, 8 snapshots +info: lane costs ms by window rows 1:25.88 2:29.81 3:34.92 4:38.40 5:44.04 6:46.97 7:50.14 8:54.32; head step 1.286 +[tensorfold] open-file limit raised: soft 1024 -> 524288 +warning: libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 88.22 GiB on the device, 1 stream of 262208 positions, 7.67 GiB each; prompts in 4096-row chunks +[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: MTP + copies; context: 262144; loaded in 38.2s) +[tensorfold] 127.0.0.1 "GET /health HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-171f1165c0f1b396c3ba6e8fc3bb5d66 prompt=256 cached=0 thinking=False effort=none tokens=1 sha=3635a91e3da8 finish=length rounds=0 accepted=0/0 ttft=0.453 decode=0.000 elapsed=0.453 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-cf1e1176f5b58524743aff9771f48e61 prompt=261888 cached=0 thinking=False effort=none tokens=1 sha=52beab51fc39 finish=length rounds=0 accepted=0/0 ttft=598.532 decode=0.001 elapsed=598.532 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "GET /memory HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /metrics HTTP/1.1" 200 - +[tensorfold] shutting down (SIGTERM): draining: new requests get 503; 0 request(s) in progress may finish within 20.0 s +[tensorfold] shutting down: drained +info: graphs: 8 captured (3 ms each), 64 of 80 rounds replayed +[tensorfold] shutting down: stopped diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-new-261888-r2.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-new-261888-r2.log new file mode 100644 index 0000000000..ce9bc02df6 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-new-261888-r2.log @@ -0,0 +1,17 @@ +[tensorfold] HIP rank 0 of 1: policy matrix=auto,attention=auto,kernels=auto,graphs=auto,prefill_step=4096,fill_rows=512,mtp_depth=gated; mtp drafts 7 under 0.9, 8 snapshots +info: lane costs ms by window rows 1:25.43 2:29.88 3:34.95 4:38.41 5:43.63 6:47.80 7:50.27 8:54.02; head step 1.288 +[tensorfold] open-file limit raised: soft 1024 -> 524288 +warning: libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 88.22 GiB on the device, 1 stream of 262208 positions, 7.67 GiB each; prompts in 4096-row chunks +[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: MTP + copies; context: 262144; loaded in 27.8s) +[tensorfold] 127.0.0.1 "GET /health HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-c55a6dbb202c124f90c6a81200432ca6 prompt=256 cached=0 thinking=False effort=none tokens=1 sha=3635a91e3da8 finish=length rounds=0 accepted=0/0 ttft=0.454 decode=0.000 elapsed=0.454 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-1171aacd6d170f423ed197e31734965f prompt=261888 cached=0 thinking=False effort=none tokens=1 sha=52beab51fc39 finish=length rounds=0 accepted=0/0 ttft=599.139 decode=0.000 elapsed=599.139 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "GET /memory HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /metrics HTTP/1.1" 200 - +[tensorfold] shutting down (SIGTERM): draining: new requests get 503; 0 request(s) in progress may finish within 20.0 s +[tensorfold] shutting down: drained +info: graphs: 8 captured (23 ms each), 64 of 80 rounds replayed +[tensorfold] shutting down: stopped diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-new-32768-r1.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-new-32768-r1.log new file mode 100644 index 0000000000..b2d9827412 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-new-32768-r1.log @@ -0,0 +1,17 @@ +[tensorfold] HIP rank 0 of 1: policy matrix=auto,attention=auto,kernels=auto,graphs=auto,prefill_step=4096,fill_rows=512,mtp_depth=gated; mtp drafts 7 under 0.9, 8 snapshots +info: lane costs ms by window rows 1:25.51 2:29.82 3:34.90 4:38.90 5:50.33 6:46.78 7:50.12 8:53.71; head step 1.291 +[tensorfold] open-file limit raised: soft 1024 -> 524288 +warning: libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 82.37 GiB on the device, 1 stream of 41024 positions, 1.33 GiB each; prompts in 4096-row chunks +[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: MTP + copies; context: 40960; loaded in 27.0s) +[tensorfold] 127.0.0.1 "GET /health HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-7bb559c41d27ce60451ec8a580bb8ac3 prompt=256 cached=0 thinking=False effort=none tokens=1 sha=3635a91e3da8 finish=length rounds=0 accepted=0/0 ttft=0.444 decode=0.000 elapsed=0.444 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-fcc44c29ca2e3ec174c7055493c4cf91 prompt=32768 cached=0 thinking=False effort=none tokens=1 sha=7104741a92e7 finish=length rounds=0 accepted=0/0 ttft=63.924 decode=0.000 elapsed=63.924 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "GET /memory HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /metrics HTTP/1.1" 200 - +[tensorfold] shutting down (SIGTERM): draining: new requests get 503; 0 request(s) in progress may finish within 20.0 s +[tensorfold] shutting down: drained +info: graphs: 8 captured (7 ms each), 64 of 80 rounds replayed +[tensorfold] shutting down: stopped diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-new-32768-r2.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-new-32768-r2.log new file mode 100644 index 0000000000..05332cf089 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-new-32768-r2.log @@ -0,0 +1,17 @@ +[tensorfold] HIP rank 0 of 1: policy matrix=auto,attention=auto,kernels=auto,graphs=auto,prefill_step=4096,fill_rows=512,mtp_depth=gated; mtp drafts 7 under 0.9, 8 snapshots +info: lane costs ms by window rows 1:29.50 2:30.13 3:37.78 4:38.12 5:43.32 6:46.96 7:49.80 8:53.56; head step 1.285 +[tensorfold] open-file limit raised: soft 1024 -> 524288 +warning: libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 82.37 GiB on the device, 1 stream of 41024 positions, 1.33 GiB each; prompts in 4096-row chunks +[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: MTP + copies; context: 40960; loaded in 28.1s) +[tensorfold] 127.0.0.1 "GET /health HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-ac4efb130fc2cfb715d357f3d6c654a2 prompt=256 cached=0 thinking=False effort=none tokens=1 sha=3635a91e3da8 finish=length rounds=0 accepted=0/0 ttft=0.428 decode=0.000 elapsed=0.428 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-6860246ebcb699a8482938aa1cca0599 prompt=32768 cached=0 thinking=False effort=none tokens=1 sha=7104741a92e7 finish=length rounds=0 accepted=0/0 ttft=63.692 decode=0.000 elapsed=63.692 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "GET /memory HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /metrics HTTP/1.1" 200 - +[tensorfold] shutting down (SIGTERM): draining: new requests get 503; 0 request(s) in progress may finish within 20.0 s +[tensorfold] shutting down: drained +info: graphs: 8 captured (3 ms each), 64 of 80 rounds replayed +[tensorfold] shutting down: stopped diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-new-65536-r1.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-new-65536-r1.log new file mode 100644 index 0000000000..9ff90a81a2 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-new-65536-r1.log @@ -0,0 +1,17 @@ +[tensorfold] HIP rank 0 of 1: policy matrix=auto,attention=auto,kernels=auto,graphs=auto,prefill_step=4096,fill_rows=512,mtp_depth=gated; mtp drafts 7 under 0.9, 8 snapshots +info: lane costs ms by window rows 1:25.70 2:29.64 3:34.78 4:38.20 5:43.65 6:46.86 7:50.16 8:53.86; head step 1.287 +[tensorfold] open-file limit raised: soft 1024 -> 524288 +warning: libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 83.23 GiB on the device, 1 stream of 73792 positions, 2.27 GiB each; prompts in 4096-row chunks +[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: MTP + copies; context: 73728; loaded in 38.6s) +[tensorfold] 127.0.0.1 "GET /health HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-1fb34244986b947731bee3be3fb3535c prompt=256 cached=0 thinking=False effort=none tokens=1 sha=3635a91e3da8 finish=length rounds=0 accepted=0/0 ttft=0.432 decode=0.000 elapsed=0.432 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-23be0ddcc8ca2198bbcde2ec4e698eb2 prompt=65536 cached=0 thinking=False effort=none tokens=1 sha=7d7e080fddd8 finish=length rounds=0 accepted=0/0 ttft=131.819 decode=0.000 elapsed=131.819 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "GET /memory HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /metrics HTTP/1.1" 200 - +[tensorfold] shutting down (SIGTERM): draining: new requests get 503; 0 request(s) in progress may finish within 20.0 s +[tensorfold] shutting down: drained +info: graphs: 8 captured (10 ms each), 64 of 80 rounds replayed +[tensorfold] shutting down: stopped diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-new-65536-r2.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-new-65536-r2.log new file mode 100644 index 0000000000..7b23f79efe --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-new-65536-r2.log @@ -0,0 +1,17 @@ +[tensorfold] HIP rank 0 of 1: policy matrix=auto,attention=auto,kernels=auto,graphs=auto,prefill_step=4096,fill_rows=512,mtp_depth=gated; mtp drafts 7 under 0.9, 8 snapshots +info: lane costs ms by window rows 1:25.28 2:32.14 3:34.84 4:46.16 5:43.33 6:46.69 7:49.81 8:53.59; head step 1.293 +[tensorfold] open-file limit raised: soft 1024 -> 524288 +warning: libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 83.23 GiB on the device, 1 stream of 73792 positions, 2.27 GiB each; prompts in 4096-row chunks +[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: MTP + copies; context: 73728; loaded in 26.8s) +[tensorfold] 127.0.0.1 "GET /health HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-979149cbcd05ba7c693ed2b607068ad2 prompt=256 cached=0 thinking=False effort=none tokens=1 sha=3635a91e3da8 finish=length rounds=0 accepted=0/0 ttft=0.430 decode=0.000 elapsed=0.430 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-aa65061f784dbda69b072c1884cc6ee8 prompt=65536 cached=0 thinking=False effort=none tokens=1 sha=7d7e080fddd8 finish=length rounds=0 accepted=0/0 ttft=132.084 decode=0.000 elapsed=132.084 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "GET /memory HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /metrics HTTP/1.1" 200 - +[tensorfold] shutting down (SIGTERM): draining: new requests get 503; 0 request(s) in progress may finish within 20.0 s +[tensorfold] shutting down: drained +info: graphs: 8 captured (37 ms each), 64 of 80 rounds replayed +[tensorfold] shutting down: stopped diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-new-8192-r1.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-new-8192-r1.log new file mode 100644 index 0000000000..becb54e489 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-new-8192-r1.log @@ -0,0 +1,17 @@ +[tensorfold] HIP rank 0 of 1: policy matrix=auto,attention=auto,kernels=auto,graphs=auto,prefill_step=4096,fill_rows=512,mtp_depth=gated; mtp drafts 7 under 0.9, 8 snapshots +info: lane costs ms by window rows 1:25.65 2:29.62 3:34.76 4:38.09 5:43.60 6:46.68 7:49.82 8:53.70; head step 1.290 +[tensorfold] open-file limit raised: soft 1024 -> 524288 +warning: libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 81.71 GiB on the device, 1 stream of 16448 positions, 0.62 GiB each; prompts in 4096-row chunks +[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: MTP + copies; context: 16384; loaded in 24.5s) +[tensorfold] 127.0.0.1 "GET /health HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-98d8738741e4c7bbb60e0e08cef08763 prompt=256 cached=0 thinking=False effort=none tokens=1 sha=3635a91e3da8 finish=length rounds=0 accepted=0/0 ttft=0.439 decode=0.000 elapsed=0.439 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-4f1a1dbee306cf4a7a852d8ade908bbc prompt=8192 cached=0 thinking=False effort=none tokens=1 sha=731e88ce52c6 finish=length rounds=0 accepted=0/0 ttft=14.544 decode=0.103 elapsed=14.647 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "GET /memory HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /metrics HTTP/1.1" 200 - +[tensorfold] shutting down (SIGTERM): draining: new requests get 503; 0 request(s) in progress may finish within 20.0 s +[tensorfold] shutting down: drained +info: graphs: 8 captured (8 ms each), 64 of 80 rounds replayed +[tensorfold] shutting down: stopped diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-new-8192-r2.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-new-8192-r2.log new file mode 100644 index 0000000000..321ed91681 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-cold-new-8192-r2.log @@ -0,0 +1,17 @@ +[tensorfold] HIP rank 0 of 1: policy matrix=auto,attention=auto,kernels=auto,graphs=auto,prefill_step=4096,fill_rows=512,mtp_depth=gated; mtp drafts 7 under 0.9, 8 snapshots +info: lane costs ms by window rows 1:25.40 2:29.88 3:34.79 4:38.32 5:43.28 6:46.77 7:49.97 8:53.73; head step 1.290 +[tensorfold] open-file limit raised: soft 1024 -> 524288 +warning: libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 81.71 GiB on the device, 1 stream of 16448 positions, 0.62 GiB each; prompts in 4096-row chunks +[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: MTP + copies; context: 16384; loaded in 26.6s) +[tensorfold] 127.0.0.1 "GET /health HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-2f387d0b8c90a493e0668b7f1cccc435 prompt=256 cached=0 thinking=False effort=none tokens=1 sha=3635a91e3da8 finish=length rounds=0 accepted=0/0 ttft=0.439 decode=0.000 elapsed=0.439 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-5d40f957a39959ee096d1ea193a015ad prompt=8192 cached=0 thinking=False effort=none tokens=1 sha=731e88ce52c6 finish=length rounds=0 accepted=0/0 ttft=14.701 decode=0.000 elapsed=14.701 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "GET /memory HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /metrics HTTP/1.1" 200 - +[tensorfold] shutting down (SIGTERM): draining: new requests get 503; 0 request(s) in progress may finish within 20.0 s +[tensorfold] shutting down: drained +info: graphs: 8 captured (20 ms each), 64 of 80 rounds replayed +[tensorfold] shutting down: stopped diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-d16k-drafts-base-r1.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-d16k-drafts-base-r1.log new file mode 100644 index 0000000000..3f3c6e7d1b --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-d16k-drafts-base-r1.log @@ -0,0 +1,26 @@ +[tensorfold] HIP rank 0 of 1: policy matrix=auto,attention=auto,kernels=auto,graphs=auto,prefill_step=1024,fill_rows=512; mtp drafts 3 under 0.3, 8 snapshots +[tensorfold] open-file limit raised: soft 1024 -> 524288 +warning: libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 76.58 GiB on the device, 1 stream of 19520 positions, 1.11 GiB each; prompts in 1024-row chunks +[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: MTP + copies; context: 19456; loaded in 12.1s) +[tensorfold] 127.0.0.1 "GET /health HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-24cc6cac871d8f35b5bfd9c4d0d5f9f6 prompt=16384 cached=0 thinking=False effort=none tokens=16 sha=a955cb2f9f8d finish=length rounds=5 accepted=10/10 ttft=64.286 decode=0.336 elapsed=64.622 queued=0.000 tok/s=44.6 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-af92be126daf71d806c4628421e92fbb prompt=16384 cached=0 thinking=False effort=none tokens=256 sha=09172b34c45a finish=length rounds=121 accepted=134/186 ttft=46.427 decode=7.344 elapsed=53.771 queued=0.000 tok/s=34.7 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-cffba4bf14f47c4bcfdb1fed03e3b300 prompt=16384 cached=0 thinking=False effort=none tokens=256 sha=09172b34c45a finish=length rounds=121 accepted=134/186 ttft=46.458 decode=6.275 elapsed=52.733 queued=0.000 tok/s=40.6 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-a6a74125fef81029c822ad1bcc28afe9 prompt=16384 cached=0 thinking=False effort=none tokens=256 sha=09172b34c45a finish=length rounds=121 accepted=134/186 ttft=46.540 decode=6.210 elapsed=52.750 queued=0.000 tok/s=41.1 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-5ccf7ee32256e136fa1f496d426a1e3c prompt=16384 cached=0 thinking=False effort=none tokens=1024 sha=35725e749acd finish=length rounds=523 accepted=500/747 ttft=46.423 decode=28.882 elapsed=75.305 queued=0.000 tok/s=35.4 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-24f148dbcb7359117a091ab7cbbc13de prompt=16384 cached=0 thinking=False effort=none tokens=1024 sha=35725e749acd finish=length rounds=523 accepted=500/747 ttft=46.505 decode=26.627 elapsed=73.131 queued=0.000 tok/s=38.4 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-7e5a1e13c66ea6e0d63bf422ff3c485a prompt=16384 cached=0 thinking=False effort=none tokens=1024 sha=35725e749acd finish=length rounds=523 accepted=500/747 ttft=46.529 decode=26.714 elapsed=73.243 queued=0.000 tok/s=38.3 +[tensorfold] 127.0.0.1 "GET /memory HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /metrics HTTP/1.1" 200 - +[tensorfold] shutting down (SIGTERM): draining: new requests get 503; 0 request(s) in progress may finish within 20.0 s +[tensorfold] shutting down: drained +info: graphs: 3 captured (3 ms each), 1931 of 1937 rounds replayed +[tensorfold] shutting down: stopped diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-d16k-drafts-base-r2.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-d16k-drafts-base-r2.log new file mode 100644 index 0000000000..9a7147cb8d --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-d16k-drafts-base-r2.log @@ -0,0 +1,26 @@ +[tensorfold] HIP rank 0 of 1: policy matrix=auto,attention=auto,kernels=auto,graphs=auto,prefill_step=1024,fill_rows=512; mtp drafts 3 under 0.3, 8 snapshots +[tensorfold] open-file limit raised: soft 1024 -> 524288 +warning: libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 76.58 GiB on the device, 1 stream of 19520 positions, 1.11 GiB each; prompts in 1024-row chunks +[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: MTP + copies; context: 19456; loaded in 12.5s) +[tensorfold] 127.0.0.1 "GET /health HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-6e9db47e0c5dac9483ef928ba5d72580 prompt=16384 cached=0 thinking=False effort=none tokens=16 sha=a955cb2f9f8d finish=length rounds=5 accepted=10/10 ttft=64.993 decode=0.329 elapsed=65.321 queued=0.000 tok/s=45.6 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-4a0930d08a52638ab86e3b39d6dbe2c8 prompt=16384 cached=0 thinking=False effort=none tokens=256 sha=09172b34c45a finish=length rounds=121 accepted=134/186 ttft=46.374 decode=7.316 elapsed=53.690 queued=0.000 tok/s=34.9 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-f6a5261b126f6df1db5969cb5a62e3a2 prompt=16384 cached=0 thinking=False effort=none tokens=256 sha=09172b34c45a finish=length rounds=121 accepted=134/186 ttft=46.574 decode=6.217 elapsed=52.791 queued=0.000 tok/s=41.0 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-60578714782d391969aec20274516628 prompt=16384 cached=0 thinking=False effort=none tokens=256 sha=09172b34c45a finish=length rounds=121 accepted=134/186 ttft=46.489 decode=6.389 elapsed=52.878 queued=0.000 tok/s=39.9 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-a889c0c1b7098414445d6e0a6bda9024 prompt=16384 cached=0 thinking=False effort=none tokens=1024 sha=35725e749acd finish=length rounds=523 accepted=500/747 ttft=46.555 decode=29.749 elapsed=76.305 queued=0.000 tok/s=34.4 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-bfafad01c44ed49f312b10f500ab9d18 prompt=16384 cached=0 thinking=False effort=none tokens=1024 sha=35725e749acd finish=length rounds=523 accepted=500/747 ttft=46.644 decode=26.387 elapsed=73.032 queued=0.000 tok/s=38.8 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-23c5af6b97f158fcbbc0de28abbefe40 prompt=16384 cached=0 thinking=False effort=none tokens=1024 sha=35725e749acd finish=length rounds=523 accepted=500/747 ttft=46.567 decode=26.825 elapsed=73.392 queued=0.000 tok/s=38.1 +[tensorfold] 127.0.0.1 "GET /memory HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /metrics HTTP/1.1" 200 - +[tensorfold] shutting down (SIGTERM): draining: new requests get 503; 0 request(s) in progress may finish within 20.0 s +[tensorfold] shutting down: drained +info: graphs: 3 captured (3 ms each), 1931 of 1937 rounds replayed +[tensorfold] shutting down: stopped diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-d16k-drafts-new-r1.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-d16k-drafts-new-r1.log new file mode 100644 index 0000000000..52cca14f79 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-d16k-drafts-new-r1.log @@ -0,0 +1,27 @@ +[tensorfold] HIP rank 0 of 1: policy matrix=auto,attention=auto,kernels=auto,graphs=auto,prefill_step=4096,fill_rows=512,mtp_depth=gated; mtp drafts 7 under 0.9, 8 snapshots +info: lane costs ms by window rows 1:31.16 2:29.67 3:34.69 4:38.30 5:43.30 6:47.22 7:50.50 8:53.54; head step 1.294 +[tensorfold] open-file limit raised: soft 1024 -> 524288 +warning: libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 81.80 GiB on the device, 1 stream of 19520 positions, 0.71 GiB each; prompts in 4096-row chunks +[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: MTP + copies; context: 19456; loaded in 25.8s) +[tensorfold] 127.0.0.1 "GET /health HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-2f46c28f50c23cf3023f214b028bf8d6 prompt=16384 cached=0 thinking=False effort=none tokens=16 sha=a955cb2f9f8d finish=length rounds=2 accepted=13/13 ttft=30.783 decode=0.394 elapsed=31.177 queued=0.000 tok/s=38.0 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-d3046f4721ccabbcb2ad939e6111f20b prompt=16384 cached=0 thinking=False effort=none tokens=256 sha=09172b34c45a finish=length rounds=89 accepted=167/262 ttft=30.913 decode=4.895 elapsed=35.808 queued=0.000 tok/s=52.1 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-e888380a3b7fdba7817cf24b71405b8b prompt=16384 cached=0 thinking=False effort=none tokens=256 sha=09172b34c45a finish=length rounds=89 accepted=167/262 ttft=30.873 decode=4.914 elapsed=35.788 queued=0.000 tok/s=51.9 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-eaca51829eed4c4fda3c348ca497a0fd prompt=16384 cached=0 thinking=False effort=none tokens=256 sha=09172b34c45a finish=length rounds=89 accepted=167/262 ttft=30.911 decode=4.838 elapsed=35.748 queued=0.000 tok/s=52.7 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-ff7ff5ea24aaa7f1393e42cb8f283fef prompt=16384 cached=0 thinking=False effort=none tokens=1024 sha=35725e749acd finish=length rounds=401 accepted=622/1018 ttft=31.107 decode=20.693 elapsed=51.800 queued=0.000 tok/s=49.4 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-82961a568d2d19e6d274f97cf4c84e92 prompt=16384 cached=0 thinking=False effort=none tokens=1024 sha=35725e749acd finish=length rounds=401 accepted=622/1018 ttft=30.934 decode=20.685 elapsed=51.619 queued=0.000 tok/s=49.5 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-af5050b3b7b0d46cb5845cacc6a43581 prompt=16384 cached=0 thinking=False effort=none tokens=1024 sha=35725e749acd finish=length rounds=401 accepted=622/1018 ttft=30.935 decode=20.863 elapsed=51.798 queued=0.000 tok/s=49.0 +[tensorfold] 127.0.0.1 "GET /memory HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /metrics HTTP/1.1" 200 - +[tensorfold] shutting down (SIGTERM): draining: new requests get 503; 0 request(s) in progress may finish within 20.0 s +[tensorfold] shutting down: drained +info: graphs: 8 captured (14 ms each), 1536 of 1552 rounds replayed +[tensorfold] shutting down: stopped diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-d16k-drafts-new-r2.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-d16k-drafts-new-r2.log new file mode 100644 index 0000000000..6c4e11ec5b --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-d16k-drafts-new-r2.log @@ -0,0 +1,27 @@ +[tensorfold] HIP rank 0 of 1: policy matrix=auto,attention=auto,kernels=auto,graphs=auto,prefill_step=4096,fill_rows=512,mtp_depth=gated; mtp drafts 7 under 0.9, 8 snapshots +info: lane costs ms by window rows 1:25.25 2:29.60 3:34.83 4:38.06 5:43.24 6:46.64 7:49.79 8:53.53; head step 1.304 +[tensorfold] open-file limit raised: soft 1024 -> 524288 +warning: libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 81.80 GiB on the device, 1 stream of 19520 positions, 0.71 GiB each; prompts in 4096-row chunks +[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: MTP + copies; context: 19456; loaded in 27.1s) +[tensorfold] 127.0.0.1 "GET /health HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-48386794b75b98ce1ef47013aee9c262 prompt=16384 cached=0 thinking=False effort=none tokens=16 sha=a955cb2f9f8d finish=length rounds=2 accepted=13/13 ttft=30.754 decode=0.252 elapsed=31.006 queued=0.000 tok/s=59.5 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-53cb86f3e3794a92caed86442ba86b26 prompt=16384 cached=0 thinking=False effort=none tokens=256 sha=09172b34c45a finish=length rounds=89 accepted=167/262 ttft=30.742 decode=4.920 elapsed=35.663 queued=0.000 tok/s=51.8 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-2a16228e952e659ef075326a5aa657a4 prompt=16384 cached=0 thinking=False effort=none tokens=256 sha=09172b34c45a finish=length rounds=89 accepted=167/262 ttft=30.851 decode=5.028 elapsed=35.879 queued=0.000 tok/s=50.7 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-85091c3e877c74fc93829ffff3f9a26f prompt=16384 cached=0 thinking=False effort=none tokens=256 sha=09172b34c45a finish=length rounds=89 accepted=167/262 ttft=30.891 decode=5.085 elapsed=35.976 queued=0.000 tok/s=50.2 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-80f53b4d371aeef9756ccbf6c6c54612 prompt=16384 cached=0 thinking=False effort=none tokens=1024 sha=35725e749acd finish=length rounds=401 accepted=622/1018 ttft=30.929 decode=21.262 elapsed=52.191 queued=0.000 tok/s=48.1 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-9e594625c72cf059422a2f679e7bc2c7 prompt=16384 cached=0 thinking=False effort=none tokens=1024 sha=35725e749acd finish=length rounds=401 accepted=622/1018 ttft=30.923 decode=21.300 elapsed=52.222 queued=0.000 tok/s=48.0 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-c3aec4068ab9bd598e4d6c69ed408962 prompt=16384 cached=0 thinking=False effort=none tokens=1024 sha=35725e749acd finish=length rounds=401 accepted=622/1018 ttft=30.983 decode=20.930 elapsed=51.912 queued=0.000 tok/s=48.9 +[tensorfold] 127.0.0.1 "GET /memory HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /metrics HTTP/1.1" 200 - +[tensorfold] shutting down (SIGTERM): draining: new requests get 503; 0 request(s) in progress may finish within 20.0 s +[tensorfold] shutting down: drained +info: graphs: 8 captured (44 ms each), 1536 of 1552 rounds replayed +[tensorfold] shutting down: stopped diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-d16k-serial-base-r1.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-d16k-serial-base-r1.log new file mode 100644 index 0000000000..9f4ce0e8bf --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-d16k-serial-base-r1.log @@ -0,0 +1,26 @@ +[tensorfold] HIP rank 0 of 1: policy matrix=auto,attention=auto,kernels=auto,graphs=auto,prefill_step=1024,fill_rows=512; mtp drafts 3 under 0.3, 8 snapshots +[tensorfold] open-file limit raised: soft 1024 -> 524288 +warning: libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 76.58 GiB on the device, 1 stream of 19520 positions, 1.11 GiB each; prompts in 1024-row chunks +[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: off; context: 19456; loaded in 11.5s) +[tensorfold] 127.0.0.1 "GET /health HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-7307e693b31f4f771de0aa364f94ae4d prompt=16384 cached=0 thinking=False effort=none tokens=16 sha=a955cb2f9f8d finish=length rounds=15 accepted=0/0 ttft=64.586 decode=0.621 elapsed=65.207 queued=0.000 tok/s=24.2 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-0d36a052afc434993b91182356bbfef1 prompt=16384 cached=0 thinking=False effort=none tokens=256 sha=09172b34c45a finish=length rounds=255 accepted=0/0 ttft=46.316 decode=9.395 elapsed=55.711 queued=0.000 tok/s=27.1 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-01d50f4419946ad5102b8ae44ba773d5 prompt=16384 cached=0 thinking=False effort=none tokens=256 sha=09172b34c45a finish=length rounds=255 accepted=0/0 ttft=46.385 decode=8.387 elapsed=54.771 queued=0.000 tok/s=30.4 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-7782f8547e0da44aed67528f33a755a6 prompt=16384 cached=0 thinking=False effort=none tokens=256 sha=09172b34c45a finish=length rounds=255 accepted=0/0 ttft=46.310 decode=8.572 elapsed=54.882 queued=0.000 tok/s=29.7 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-79bf77ccb2cd55de487e6d3382644b02 prompt=16384 cached=0 thinking=False effort=none tokens=1024 sha=35725e749acd finish=length rounds=1023 accepted=0/0 ttft=46.533 decode=36.761 elapsed=83.294 queued=0.000 tok/s=27.8 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-ff6a93afc9511add03fa2049effba561 prompt=16384 cached=0 thinking=False effort=none tokens=1024 sha=35725e749acd finish=length rounds=1023 accepted=0/0 ttft=46.423 decode=33.914 elapsed=80.338 queued=0.000 tok/s=30.2 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-59593f7b41b0e61262a2a163fbdedb76 prompt=16384 cached=0 thinking=False effort=none tokens=1024 sha=35725e749acd finish=length rounds=1023 accepted=0/0 ttft=46.456 decode=33.773 elapsed=80.228 queued=0.000 tok/s=30.3 +[tensorfold] 127.0.0.1 "GET /memory HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /metrics HTTP/1.1" 200 - +[tensorfold] shutting down (SIGTERM): draining: new requests get 503; 0 request(s) in progress may finish within 20.0 s +[tensorfold] shutting down: drained +info: graphs: 1 captured (2 ms each), 3847 of 3849 rounds replayed +[tensorfold] shutting down: stopped diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-d16k-serial-base-r2.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-d16k-serial-base-r2.log new file mode 100644 index 0000000000..63bed2b748 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-d16k-serial-base-r2.log @@ -0,0 +1,26 @@ +[tensorfold] HIP rank 0 of 1: policy matrix=auto,attention=auto,kernels=auto,graphs=auto,prefill_step=1024,fill_rows=512; mtp drafts 3 under 0.3, 8 snapshots +[tensorfold] open-file limit raised: soft 1024 -> 524288 +warning: libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 76.58 GiB on the device, 1 stream of 19520 positions, 1.11 GiB each; prompts in 1024-row chunks +[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: off; context: 19456; loaded in 12.3s) +[tensorfold] 127.0.0.1 "GET /health HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-b945fd387ddabea65dcfff7e4c66d634 prompt=16384 cached=0 thinking=False effort=none tokens=16 sha=a955cb2f9f8d finish=length rounds=15 accepted=0/0 ttft=64.569 decode=0.759 elapsed=65.328 queued=0.000 tok/s=19.8 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-49fb59d008778ad8928a02b8225c2289 prompt=16384 cached=0 thinking=False effort=none tokens=256 sha=09172b34c45a finish=length rounds=255 accepted=0/0 ttft=46.472 decode=9.649 elapsed=56.121 queued=0.000 tok/s=26.4 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-ffff277af6df49a9d05a430a7cce9eed prompt=16384 cached=0 thinking=False effort=none tokens=256 sha=09172b34c45a finish=length rounds=255 accepted=0/0 ttft=46.367 decode=8.670 elapsed=55.037 queued=0.000 tok/s=29.4 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-22fca07234b1eabf1e7875a5695cb91f prompt=16384 cached=0 thinking=False effort=none tokens=256 sha=09172b34c45a finish=length rounds=255 accepted=0/0 ttft=46.689 decode=8.650 elapsed=55.339 queued=0.000 tok/s=29.5 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-039cbde124279ab61062edac1092cec7 prompt=16384 cached=0 thinking=False effort=none tokens=1024 sha=35725e749acd finish=length rounds=1023 accepted=0/0 ttft=46.684 decode=37.975 elapsed=84.659 queued=0.000 tok/s=26.9 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-a034d4fe13dd0eee2bef448a81d70f35 prompt=16384 cached=0 thinking=False effort=none tokens=1024 sha=35725e749acd finish=length rounds=1023 accepted=0/0 ttft=46.601 decode=34.112 elapsed=80.713 queued=0.000 tok/s=30.0 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-82d2dac2567135b02d7b58231a3f46d0 prompt=16384 cached=0 thinking=False effort=none tokens=1024 sha=35725e749acd finish=length rounds=1023 accepted=0/0 ttft=46.564 decode=34.111 elapsed=80.675 queued=0.000 tok/s=30.0 +[tensorfold] 127.0.0.1 "GET /memory HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /metrics HTTP/1.1" 200 - +[tensorfold] shutting down (SIGTERM): draining: new requests get 503; 0 request(s) in progress may finish within 20.0 s +[tensorfold] shutting down: drained +info: graphs: 1 captured (2 ms each), 3847 of 3849 rounds replayed +[tensorfold] shutting down: stopped diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-d16k-serial-new-r1.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-d16k-serial-new-r1.log new file mode 100644 index 0000000000..a265159c1c --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-d16k-serial-new-r1.log @@ -0,0 +1,27 @@ +[tensorfold] HIP rank 0 of 1: policy matrix=auto,attention=auto,kernels=auto,graphs=auto,prefill_step=4096,fill_rows=512,mtp_depth=gated; mtp drafts 7 under 0.9, 8 snapshots +info: lane costs ms by window rows 1:25.25 2:29.58 3:34.70 4:38.07 5:43.29 6:46.97 7:49.86 8:53.57; head step 1.285 +[tensorfold] open-file limit raised: soft 1024 -> 524288 +warning: libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 81.80 GiB on the device, 1 stream of 19520 positions, 0.71 GiB each; prompts in 4096-row chunks +[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: off; context: 19456; loaded in 38.2s) +[tensorfold] 127.0.0.1 "GET /health HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-5611138456c1d8a6b7bd870af3026bb2 prompt=16384 cached=0 thinking=False effort=none tokens=16 sha=a955cb2f9f8d finish=length rounds=15 accepted=0/0 ttft=30.452 decode=0.414 elapsed=30.867 queued=0.000 tok/s=36.2 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-1bef209ed50a5079f7ff85a3770d945a prompt=16384 cached=0 thinking=False effort=none tokens=256 sha=09172b34c45a finish=length rounds=255 accepted=0/0 ttft=30.648 decode=7.145 elapsed=37.793 queued=0.000 tok/s=35.7 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-16d7c33c189e5a634b16f931301ec80f prompt=16384 cached=0 thinking=False effort=none tokens=256 sha=09172b34c45a finish=length rounds=255 accepted=0/0 ttft=30.558 decode=7.167 elapsed=37.725 queued=0.000 tok/s=35.6 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-370558350964bf4fb19cff46a559dd13 prompt=16384 cached=0 thinking=False effort=none tokens=256 sha=09172b34c45a finish=length rounds=255 accepted=0/0 ttft=30.589 decode=7.177 elapsed=37.767 queued=0.000 tok/s=35.5 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-86e0d33aeede7798dfd5726f57da198c prompt=16384 cached=0 thinking=False effort=none tokens=1024 sha=35725e749acd finish=length rounds=1023 accepted=0/0 ttft=30.601 decode=28.612 elapsed=59.213 queued=0.000 tok/s=35.8 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-4a103e1957c30f933368105395ff4e2c prompt=16384 cached=0 thinking=False effort=none tokens=1024 sha=35725e749acd finish=length rounds=1023 accepted=0/0 ttft=30.714 decode=28.459 elapsed=59.173 queued=0.000 tok/s=35.9 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-ab3ec74cf1ee8a4808f87352a02d90ba prompt=16384 cached=0 thinking=False effort=none tokens=1024 sha=35725e749acd finish=length rounds=1023 accepted=0/0 ttft=30.698 decode=28.691 elapsed=59.389 queued=0.000 tok/s=35.7 +[tensorfold] 127.0.0.1 "GET /memory HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /metrics HTTP/1.1" 200 - +[tensorfold] shutting down (SIGTERM): draining: new requests get 503; 0 request(s) in progress may finish within 20.0 s +[tensorfold] shutting down: drained +info: graphs: 8 captured (28 ms each), 3913 of 3929 rounds replayed +[tensorfold] shutting down: stopped diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-d16k-serial-new-r2.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-d16k-serial-new-r2.log new file mode 100644 index 0000000000..49371a38f1 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-d16k-serial-new-r2.log @@ -0,0 +1,27 @@ +[tensorfold] HIP rank 0 of 1: policy matrix=auto,attention=auto,kernels=auto,graphs=auto,prefill_step=4096,fill_rows=512,mtp_depth=gated; mtp drafts 7 under 0.9, 8 snapshots +info: lane costs ms by window rows 1:25.26 2:29.59 3:34.83 4:38.09 5:43.24 6:46.62 7:52.71 8:53.60; head step 1.316 +[tensorfold] open-file limit raised: soft 1024 -> 524288 +warning: libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 81.80 GiB on the device, 1 stream of 19520 positions, 0.71 GiB each; prompts in 4096-row chunks +[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: off; context: 19456; loaded in 26.7s) +[tensorfold] 127.0.0.1 "GET /health HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-4aae9ee698440b24056010b2cb154c31 prompt=16384 cached=0 thinking=False effort=none tokens=16 sha=a955cb2f9f8d finish=length rounds=15 accepted=0/0 ttft=30.596 decode=0.415 elapsed=31.011 queued=0.000 tok/s=36.1 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-b20507213dd24b1c5739b957e5425a54 prompt=16384 cached=0 thinking=False effort=none tokens=256 sha=09172b34c45a finish=length rounds=255 accepted=0/0 ttft=30.707 decode=7.187 elapsed=37.894 queued=0.000 tok/s=35.5 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-b2302e4ed3f394d8c1636b785d85270f prompt=16384 cached=0 thinking=False effort=none tokens=256 sha=09172b34c45a finish=length rounds=255 accepted=0/0 ttft=30.778 decode=7.351 elapsed=38.128 queued=0.000 tok/s=34.7 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-6ec0d8c085f55c3f69259c35792b6d45 prompt=16384 cached=0 thinking=False effort=none tokens=256 sha=09172b34c45a finish=length rounds=255 accepted=0/0 ttft=30.706 decode=7.110 elapsed=37.817 queued=0.000 tok/s=35.9 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-f708b83886b58687dde5d4cd4c47407e prompt=16384 cached=0 thinking=False effort=none tokens=1024 sha=35725e749acd finish=length rounds=1023 accepted=0/0 ttft=30.821 decode=28.836 elapsed=59.657 queued=0.000 tok/s=35.5 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-db0a6fa867b82fadcfd961c70d7026c6 prompt=16384 cached=0 thinking=False effort=none tokens=1024 sha=35725e749acd finish=length rounds=1023 accepted=0/0 ttft=30.798 decode=28.598 elapsed=59.396 queued=0.000 tok/s=35.8 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-d7aa51249326cc295d9462fbd4ef68e3 prompt=16384 cached=0 thinking=False effort=none tokens=1024 sha=35725e749acd finish=length rounds=1023 accepted=0/0 ttft=30.776 decode=28.677 elapsed=59.453 queued=0.000 tok/s=35.7 +[tensorfold] 127.0.0.1 "GET /memory HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /metrics HTTP/1.1" 200 - +[tensorfold] shutting down (SIGTERM): draining: new requests get 503; 0 request(s) in progress may finish within 20.0 s +[tensorfold] shutting down: drained +info: graphs: 8 captured (48 ms each), 3913 of 3929 rounds replayed +[tensorfold] shutting down: stopped diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-decode-base-r1.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-decode-base-r1.log new file mode 100644 index 0000000000..2b74b68e0b --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-decode-base-r1.log @@ -0,0 +1,100 @@ +[tensorfold] HIP rank 0 of 1: policy matrix=auto,attention=auto,kernels=auto,graphs=auto,prefill_step=1024,fill_rows=512; mtp drafts 3 under 0.3, 8 snapshots +[tensorfold] open-file limit raised: soft 1024 -> 524288 +warning: libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 76.58 GiB on the device, 4 streams of 16448 positions, 1.02 GiB each; prompts in 1024-row chunks +[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: MTP + copies; context: 16384; loaded in 12.8s) +[tensorfold] 127.0.0.1 "GET /health HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-4a7fc74d94da10898e3fc9ac3634593f prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=92 accepted=163/197 ttft=0.816 decode=6.130 elapsed=6.947 queued=0.000 tok/s=41.6 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-d6c59bec5f92f878d146cb62882c93c5 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=92 accepted=163/197 ttft=0.123 decode=5.006 elapsed=5.129 queued=0.000 tok/s=50.9 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-d1cf3595b837ad2abebf52e709b9cfc7 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=92 accepted=163/197 ttft=0.123 decode=5.045 elapsed=5.168 queued=0.000 tok/s=50.5 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-31e5ea90940d2548da8bfc3359069aa9 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=92 accepted=163/197 ttft=0.123 decode=4.921 elapsed=5.044 queued=0.000 tok/s=51.8 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-ff218b12c04bf52fa19516681876fbb5 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=107 accepted=149/213 ttft=0.347 decode=6.660 elapsed=7.008 queued=0.000 tok/s=38.3 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-c1d5379d005d1fbdb0822979d47237c0 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=107 accepted=149/213 ttft=0.238 decode=5.352 elapsed=5.591 queued=0.000 tok/s=47.6 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-7955c88f4388f225243fac8b30e4d6b0 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=107 accepted=149/213 ttft=0.239 decode=5.624 elapsed=5.863 queued=0.000 tok/s=45.3 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-a878aea6d690f03914d884e20b487df5 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=107 accepted=149/213 ttft=0.238 decode=5.583 elapsed=5.821 queued=0.000 tok/s=45.7 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-60c39f15cc6daf332c31b61b83c94de6 prompt=14 cached=0 thinking=False effort=none tokens=16 sha=f4b7395f11a0 finish=length rounds=9 accepted=6/10 ttft=0.123 decode=0.531 elapsed=0.653 queued=0.000 tok/s=28.3 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-46af64c307f1d522fa9c0ef9661c90e5 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=92 accepted=163/197 ttft=0.123 decode=4.727 elapsed=4.850 queued=0.000 tok/s=53.9 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-b067c6ca9a6ff4f67e4578c806706e18 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=255 accepted=0/0 ttft=0.120 decode=8.010 elapsed=8.131 queued=0.000 tok/s=31.8 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-bb5d5dc2826778a1dd13e07293793244 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=92 accepted=163/197 ttft=0.122 decode=4.931 elapsed=5.053 queued=0.000 tok/s=51.7 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-95a68ae4865fd46c0b99de821428859a prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=92 accepted=163/197 ttft=0.122 decode=4.920 elapsed=5.042 queued=0.000 tok/s=51.8 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-d7f1390b1a7bbdfad3404d18d6ee7846 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=92 accepted=163/197 ttft=0.123 decode=5.065 elapsed=5.188 queued=0.000 tok/s=50.3 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-6111d39a8085d48d308165b7c9778cc7 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=77 accepted=178/230 ttft=0.123 decode=11.746 elapsed=11.869 queued=0.000 tok/s=21.7 +[tensorfold] done cmpl-66c3f9530ad190e9057a6bf41da46f07 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=77 accepted=178/230 ttft=0.258 decode=11.611 elapsed=11.869 queued=0.122 tok/s=22.0 +[tensorfold] done cmpl-dbf96240e9ab735bed48151cd9f85220 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=77 accepted=178/230 ttft=0.393 decode=11.475 elapsed=11.869 queued=0.122 tok/s=22.2 +[tensorfold] done cmpl-4dae87ff08d6332de28d62d11d34ccde prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=77 accepted=178/230 ttft=0.529 decode=11.340 elapsed=11.869 queued=0.122 tok/s=22.5 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-e3d20517c2990f643cdd799f7c1a1ff8 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=77 accepted=178/230 ttft=0.123 decode=11.384 elapsed=11.507 queued=0.000 tok/s=22.4 +[tensorfold] done cmpl-035deccfaed370cdd2b2bc629d34d79a prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=77 accepted=178/230 ttft=0.245 decode=11.264 elapsed=11.508 queued=0.122 tok/s=22.6 +[tensorfold] done cmpl-a510ad9c8adf83af50b3469382f77b2c prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=77 accepted=178/230 ttft=0.488 decode=11.020 elapsed=11.509 queued=0.122 tok/s=23.1 +[tensorfold] done cmpl-37dc96cb61dba99704f9c2d2afd2f2ae prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=77 accepted=178/230 ttft=0.367 decode=11.143 elapsed=11.510 queued=0.122 tok/s=22.9 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-c23f18eb72d5eb8e20c650e571ea2cf3 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=77 accepted=178/230 ttft=0.125 decode=11.290 elapsed=11.415 queued=0.000 tok/s=22.6 +[tensorfold] done cmpl-db24bb0c7976ace814d3ebdac7b771ed prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=77 accepted=178/230 ttft=0.246 decode=11.168 elapsed=11.415 queued=0.124 tok/s=22.8 +[tensorfold] done cmpl-1c24906f3df8765f70810067fca81570 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=77 accepted=178/230 ttft=0.368 decode=11.047 elapsed=11.415 queued=0.124 tok/s=23.1 +[tensorfold] done cmpl-e1e10006f54f0ae0e89191e273a50163 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=77 accepted=178/230 ttft=0.490 decode=10.925 elapsed=11.415 queued=0.124 tok/s=23.3 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-450381c5041c801f20d9db24c0cefecc prompt=31 cached=0 thinking=False effort=none tokens=16 sha=a9100b9c265b finish=length rounds=8 accepted=7/10 ttft=0.240 decode=0.419 elapsed=0.659 queued=0.000 tok/s=35.8 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-3c598102fc1a176a1d2f40422ea2f19b prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=107 accepted=149/213 ttft=0.239 decode=5.703 elapsed=5.942 queued=0.000 tok/s=44.7 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-cdebb04985b7d0c790b42423a656a927 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=255 accepted=0/0 ttft=0.237 decode=7.795 elapsed=8.032 queued=0.000 tok/s=32.7 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-de55ee7fb2deb9fa0f9d0140bb42b441 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=107 accepted=149/213 ttft=0.240 decode=5.808 elapsed=6.048 queued=0.000 tok/s=43.9 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-6671f8db62c60b9e0757d9f927a5c015 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=107 accepted=149/213 ttft=0.238 decode=5.594 elapsed=5.832 queued=0.000 tok/s=45.6 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-5729cef967392fb3855652a2de67f904 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=107 accepted=149/213 ttft=0.238 decode=5.767 elapsed=6.005 queued=0.000 tok/s=44.2 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-2f20c50dce51f45e94e5a5ee735a11e1 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=94 accepted=162/269 ttft=0.239 decode=14.524 elapsed=14.763 queued=0.000 tok/s=17.6 +[tensorfold] done chatcmpl-57a41ee65fcec044ea85ff7e587b8d90 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=94 accepted=162/269 ttft=0.476 decode=14.287 elapsed=14.763 queued=0.238 tok/s=17.8 +[tensorfold] done chatcmpl-fb925e12c285700dfdd1cf6a856b3793 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=94 accepted=162/269 ttft=0.714 decode=14.049 elapsed=14.763 queued=0.237 tok/s=18.2 +[tensorfold] done chatcmpl-4951c87f261b1d0c13a55a25cdaf1367 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=94 accepted=162/269 ttft=0.952 decode=13.811 elapsed=14.763 queued=0.237 tok/s=18.5 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-480cd990680f3cd010263d2ce65cda0a prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=94 accepted=162/269 ttft=0.239 decode=13.695 elapsed=13.933 queued=0.000 tok/s=18.6 +[tensorfold] done chatcmpl-d1b34ac8eb043757dd735bc4d796234c prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=94 accepted=162/269 ttft=0.477 decode=13.457 elapsed=13.933 queued=0.237 tok/s=18.9 +[tensorfold] done chatcmpl-84416caad8b852d5ec1f389a638f0548 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=94 accepted=162/269 ttft=0.718 decode=13.215 elapsed=13.933 queued=0.237 tok/s=19.3 +[tensorfold] done chatcmpl-ac0bd133237a2e2a44d36ea93951fde0 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=94 accepted=162/269 ttft=0.977 decode=12.956 elapsed=13.933 queued=0.237 tok/s=19.7 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-f638a121482c8a7efc2891a962060ec1 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=94 accepted=162/269 ttft=0.239 decode=13.644 elapsed=13.883 queued=0.000 tok/s=18.7 +[tensorfold] done chatcmpl-ad820a1aab8baa15d0c00ab6c4e353d7 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=94 accepted=162/269 ttft=0.476 decode=13.407 elapsed=13.883 queued=0.238 tok/s=19.0 +[tensorfold] done chatcmpl-aee9e6afcced465bb9a440bb4806c108 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=94 accepted=162/269 ttft=0.714 decode=13.170 elapsed=13.883 queued=0.238 tok/s=19.4 +[tensorfold] done chatcmpl-b4de79d67b9947b260832aea91381409 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=94 accepted=162/269 ttft=0.952 decode=12.932 elapsed=13.884 queued=0.237 tok/s=19.7 +[tensorfold] 127.0.0.1 "GET /memory HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /metrics HTTP/1.1" 200 - +[tensorfold] shutting down (SIGTERM): draining: new requests get 503; 0 request(s) in progress may finish within 20.0 s +[tensorfold] shutting down: drained +info: graphs: 7 captured (38 ms each), 2618 of 2632 rounds replayed +[tensorfold] shutting down: stopped diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-decode-base-r2.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-decode-base-r2.log new file mode 100644 index 0000000000..50520d1139 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-decode-base-r2.log @@ -0,0 +1,100 @@ +[tensorfold] HIP rank 0 of 1: policy matrix=auto,attention=auto,kernels=auto,graphs=auto,prefill_step=1024,fill_rows=512; mtp drafts 3 under 0.3, 8 snapshots +[tensorfold] open-file limit raised: soft 1024 -> 524288 +warning: libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 76.58 GiB on the device, 4 streams of 16448 positions, 1.02 GiB each; prompts in 1024-row chunks +[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: MTP + copies; context: 16384; loaded in 16.5s) +[tensorfold] 127.0.0.1 "GET /health HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-66310db19c0cc204610b5b726fc85454 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=92 accepted=163/197 ttft=0.786 decode=5.873 elapsed=6.658 queued=0.000 tok/s=43.4 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-f2857da8bb3a3e324e5e8bc028b08b67 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=92 accepted=163/197 ttft=0.123 decode=5.034 elapsed=5.157 queued=0.000 tok/s=50.7 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-02791d5a0a1c19e69ea0a5e131b309d9 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=92 accepted=163/197 ttft=0.123 decode=5.165 elapsed=5.288 queued=0.000 tok/s=49.4 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-7015c94f13cc027feae35522125a4466 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=92 accepted=163/197 ttft=0.123 decode=4.999 elapsed=5.122 queued=0.000 tok/s=51.0 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-a8c70846f45f70d0ec3c0b8955ed2170 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=107 accepted=149/213 ttft=0.384 decode=7.139 elapsed=7.523 queued=0.000 tok/s=35.7 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-31500bab6dfbf7dca470c2bcb1dc5dc2 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=107 accepted=149/213 ttft=0.240 decode=5.705 elapsed=5.945 queued=0.000 tok/s=44.7 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-8aa06f237b481927b1d9a55d14ba9332 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=107 accepted=149/213 ttft=0.238 decode=5.884 elapsed=6.122 queued=0.000 tok/s=43.3 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-e7802015e9f2224f2a52f968d37230c4 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=107 accepted=149/213 ttft=0.238 decode=5.692 elapsed=5.930 queued=0.000 tok/s=44.8 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-f34e731a7f4a14bef0ce25bab983a347 prompt=14 cached=0 thinking=False effort=none tokens=16 sha=f4b7395f11a0 finish=length rounds=9 accepted=6/10 ttft=0.123 decode=0.556 elapsed=0.679 queued=0.000 tok/s=27.0 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-8ac79a98792d53dc6ddbf1fc9826c0e0 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=92 accepted=163/197 ttft=0.123 decode=4.765 elapsed=4.888 queued=0.000 tok/s=53.5 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-6de68284ae18e8a6eb213621522c7613 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=255 accepted=0/0 ttft=0.120 decode=8.031 elapsed=8.151 queued=0.000 tok/s=31.8 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-0cdc611f4f5130c8f0c998ead46e08e2 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=92 accepted=163/197 ttft=0.122 decode=5.013 elapsed=5.136 queued=0.000 tok/s=50.9 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-fa07dc15df03ed5bffb8927992dbf334 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=92 accepted=163/197 ttft=0.122 decode=5.036 elapsed=5.159 queued=0.000 tok/s=50.6 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-3b0820a3b43d75671b5221038a0085e4 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=92 accepted=163/197 ttft=0.123 decode=5.060 elapsed=5.183 queued=0.000 tok/s=50.4 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-4bef750b7035786b841d88246cfec068 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=77 accepted=178/230 ttft=0.258 decode=11.546 elapsed=11.804 queued=0.122 tok/s=22.1 +[tensorfold] done cmpl-bd28361b113d203ef3e585d54a24e20e prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=77 accepted=178/230 ttft=0.123 decode=11.683 elapsed=11.806 queued=0.000 tok/s=21.8 +[tensorfold] done cmpl-80b7a425e77257c8a06121853c484619 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=77 accepted=178/230 ttft=0.393 decode=11.413 elapsed=11.806 queued=0.122 tok/s=22.3 +[tensorfold] done cmpl-2d3651193878f69b041dcd3cd82ad974 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=77 accepted=178/230 ttft=0.529 decode=11.278 elapsed=11.806 queued=0.122 tok/s=22.6 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-0f840fe2de54e8f862ef64ad91b426d9 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=77 accepted=178/230 ttft=0.124 decode=11.373 elapsed=11.497 queued=0.000 tok/s=22.4 +[tensorfold] done cmpl-b93e6464e92c40d00ea1a640124acfc8 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=77 accepted=178/230 ttft=0.246 decode=11.251 elapsed=11.497 queued=0.124 tok/s=22.7 +[tensorfold] done cmpl-4a3aa917095847deaaffd2f0fe887eca prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=77 accepted=178/230 ttft=0.368 decode=11.129 elapsed=11.497 queued=0.123 tok/s=22.9 +[tensorfold] done cmpl-bc2233c93306b952bc2db78b1aaf8ca2 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=77 accepted=178/230 ttft=0.490 decode=11.007 elapsed=11.497 queued=0.123 tok/s=23.2 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-acd320560f31461938cb5920e9abe2d4 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=77 accepted=178/230 ttft=0.124 decode=11.170 elapsed=11.294 queued=0.000 tok/s=22.8 +[tensorfold] done cmpl-4a6ceab963fc341168ecc75958cb54fe prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=77 accepted=178/230 ttft=0.277 decode=11.016 elapsed=11.294 queued=0.000 tok/s=23.1 +[tensorfold] done cmpl-2a5fc0d7686eac55d7d1ba28b161c3db prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=77 accepted=178/230 ttft=0.400 decode=10.893 elapsed=11.294 queued=0.000 tok/s=23.4 +[tensorfold] done cmpl-fb2362baae87fd21f0723c1e62302114 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=77 accepted=178/230 ttft=0.539 decode=10.754 elapsed=11.293 queued=0.123 tok/s=23.7 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-9d779a2cba3cff57d118c218dd615d4d prompt=31 cached=0 thinking=False effort=none tokens=16 sha=a9100b9c265b finish=length rounds=8 accepted=7/10 ttft=0.238 decode=0.337 elapsed=0.575 queued=0.000 tok/s=44.6 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-98896d975d954595de2e18cae85aac31 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=107 accepted=149/213 ttft=0.239 decode=5.700 elapsed=5.939 queued=0.000 tok/s=44.7 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-68184765f21f3296669c3e3dcbf130b8 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=255 accepted=0/0 ttft=0.238 decode=7.994 elapsed=8.232 queued=0.000 tok/s=31.9 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-6d02e01be4f0b0600f59d934aed82a18 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=107 accepted=149/213 ttft=0.240 decode=5.588 elapsed=5.828 queued=0.000 tok/s=45.6 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-45545137dc639a18082a5f7d978ae59c prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=107 accepted=149/213 ttft=0.238 decode=5.540 elapsed=5.778 queued=0.000 tok/s=46.0 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-9fe345b5730e8a7e9cbb9e67e9a27cc9 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=107 accepted=149/213 ttft=0.239 decode=5.808 elapsed=6.046 queued=0.000 tok/s=43.9 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-fe156b583fc990ca20b55aa3bc0947de prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=94 accepted=162/269 ttft=0.239 decode=14.205 elapsed=14.444 queued=0.000 tok/s=18.0 +[tensorfold] done chatcmpl-507e64f7cb106d95416ffc4075067aab prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=94 accepted=162/269 ttft=0.479 decode=13.967 elapsed=14.446 queued=0.000 tok/s=18.3 +[tensorfold] done chatcmpl-097759347bc6af7e6cf713b252135e95 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=94 accepted=162/269 ttft=0.718 decode=13.728 elapsed=14.446 queued=0.238 tok/s=18.6 +[tensorfold] done chatcmpl-24e257044db9a8347c84ca09fe5f1095 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=94 accepted=162/269 ttft=0.960 decode=13.487 elapsed=14.446 queued=0.238 tok/s=18.9 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-ed795c4879d08287fb8df2a0b91a2860 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=94 accepted=162/269 ttft=0.240 decode=14.287 elapsed=14.527 queued=0.000 tok/s=17.8 +[tensorfold] done chatcmpl-5bf0ec680d36cb8b5848357473279a44 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=94 accepted=162/269 ttft=0.478 decode=14.049 elapsed=14.527 queued=0.239 tok/s=18.2 +[tensorfold] done chatcmpl-f28c19cfbdb2c2dae5fb40ddf787d433 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=94 accepted=162/269 ttft=0.952 decode=13.576 elapsed=14.529 queued=0.239 tok/s=18.8 +[tensorfold] done chatcmpl-798b25d26d97e3de014f415b8c7f33f4 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=94 accepted=162/269 ttft=0.715 decode=13.815 elapsed=14.530 queued=0.239 tok/s=18.5 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-9b6c52af7aa5760741f5d4fff4c7603b prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=94 accepted=162/269 ttft=0.240 decode=14.282 elapsed=14.522 queued=0.000 tok/s=17.9 +[tensorfold] done chatcmpl-65df927efdf46f8fd92ee9796c5a3a1e prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=94 accepted=162/269 ttft=0.480 decode=14.044 elapsed=14.524 queued=0.239 tok/s=18.2 +[tensorfold] done chatcmpl-5178ea09e6328f554251588a7082983a prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=94 accepted=162/269 ttft=0.718 decode=13.806 elapsed=14.524 queued=0.239 tok/s=18.5 +[tensorfold] done chatcmpl-324b4723c90a99e5f799832704169aca prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=94 accepted=162/269 ttft=0.956 decode=13.568 elapsed=14.524 queued=0.239 tok/s=18.8 +[tensorfold] 127.0.0.1 "GET /memory HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /metrics HTTP/1.1" 200 - +[tensorfold] shutting down (SIGTERM): draining: new requests get 503; 0 request(s) in progress may finish within 20.0 s +[tensorfold] shutting down: drained +info: graphs: 7 captured (3 ms each), 2618 of 2632 rounds replayed +[tensorfold] shutting down: stopped diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-decode-new-r1.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-decode-new-r1.log new file mode 100644 index 0000000000..24ec33d2a8 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-decode-new-r1.log @@ -0,0 +1,101 @@ +[tensorfold] HIP rank 0 of 1: policy matrix=auto,attention=auto,kernels=auto,graphs=auto,prefill_step=4096,fill_rows=512,mtp_depth=gated; mtp drafts 7 under 0.9, 8 snapshots +info: lane costs ms by window rows 1:25.32 2:29.61 3:38.57 4:38.20 5:43.19 6:46.63 7:49.93 8:53.53; head step 1.286 +[tensorfold] open-file limit raised: soft 1024 -> 524288 +warning: libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 81.71 GiB on the device, 4 streams of 16448 positions, 0.62 GiB each; prompts in 4096-row chunks +[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: MTP + copies; context: 16384; loaded in 29.8s) +[tensorfold] 127.0.0.1 "GET /health HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-cbdd79ba0d18fc51df0113646f6e98b3 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=68 accepted=187/232 ttft=0.099 decode=3.625 elapsed=3.724 queued=0.000 tok/s=70.3 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-acd5dfa3e05a95b3138c54cc41371618 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=68 accepted=187/232 ttft=0.097 decode=3.655 elapsed=3.752 queued=0.000 tok/s=69.8 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-6ec2e5f3681607d4ffaa01926cd24fc6 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=68 accepted=187/232 ttft=0.097 decode=3.744 elapsed=3.841 queued=0.000 tok/s=68.1 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-84dafab102a0ef8da13f1761369e55a5 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=68 accepted=187/232 ttft=0.101 decode=3.688 elapsed=3.789 queued=0.000 tok/s=69.2 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-80666829b43ae4f1aa6aef524eac48a7 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=103 accepted=152/213 ttft=0.210 decode=4.903 elapsed=5.113 queued=0.000 tok/s=52.0 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-61d0ba5be9d0d61da998f00782c46227 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=103 accepted=152/213 ttft=0.169 decode=4.548 elapsed=4.716 queued=0.000 tok/s=56.1 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-38c4a4b6a187f2823ed858e882d1a7d9 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=103 accepted=152/213 ttft=0.171 decode=4.600 elapsed=4.770 queued=0.000 tok/s=55.4 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-54416cbc96f66ea48e8792386e13dc0b prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=103 accepted=152/213 ttft=0.172 decode=4.620 elapsed=4.792 queued=0.000 tok/s=55.2 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-6e708ad4444ea43854fd347ac33a60e0 prompt=14 cached=0 thinking=False effort=none tokens=16 sha=f4b7395f11a0 finish=length rounds=8 accepted=8/10 ttft=0.119 decode=0.282 elapsed=0.401 queued=0.000 tok/s=53.2 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-0105763828bea015156b71b972a409d5 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=68 accepted=187/232 ttft=0.099 decode=3.871 elapsed=3.970 queued=0.000 tok/s=65.9 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-6753740db270787ca4c14a33f4c4002b prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=255 accepted=0/0 ttft=0.099 decode=6.680 elapsed=6.779 queued=0.000 tok/s=38.2 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-2b8f795a28d86db756534e74d7dd5c15 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=68 accepted=187/232 ttft=0.097 decode=3.747 elapsed=3.844 queued=0.000 tok/s=68.0 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-3d549201d0ba9d7718010241d3e7678c prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=68 accepted=187/232 ttft=0.097 decode=3.974 elapsed=4.071 queued=0.000 tok/s=64.2 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-a3d706f4a24f889f4918419cc8f39c86 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=68 accepted=187/232 ttft=0.099 decode=3.554 elapsed=3.652 queued=0.000 tok/s=71.8 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-23ae7bd3142ad07765d585e8738315c2 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=68 accepted=187/232 ttft=0.099 decode=9.070 elapsed=9.169 queued=0.000 tok/s=28.1 +[tensorfold] done cmpl-571ef80b6db5040ca57e0041731954bd prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=68 accepted=187/232 ttft=0.242 decode=8.927 elapsed=9.169 queued=0.098 tok/s=28.6 +[tensorfold] done cmpl-aab2f74b248e78e6767c9850e7981978 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=68 accepted=187/232 ttft=0.357 decode=8.812 elapsed=9.169 queued=0.098 tok/s=28.9 +[tensorfold] done cmpl-f32a1e85372a931ffa57f75819f789f1 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=68 accepted=187/232 ttft=0.797 decode=8.372 elapsed=9.169 queued=0.098 tok/s=30.5 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-6d56e4e81a76c7f83f88a2be3db8aaf0 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=68 accepted=187/232 ttft=0.097 decode=8.451 elapsed=8.548 queued=0.000 tok/s=30.2 +[tensorfold] done cmpl-ae9f91a383fec012cf36eccdd78058c4 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=68 accepted=187/232 ttft=0.193 decode=8.355 elapsed=8.549 queued=0.000 tok/s=30.5 +[tensorfold] done cmpl-ef31eaf7f7fd414409f024c5606fe985 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=68 accepted=187/232 ttft=0.290 decode=8.259 elapsed=8.549 queued=0.096 tok/s=30.9 +[tensorfold] done cmpl-bca7916d992cdec68e0d4a75429282d8 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=68 accepted=187/232 ttft=0.387 decode=8.162 elapsed=8.549 queued=0.096 tok/s=31.2 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-e421cd8ca661e59d4b48f2afbee5d2a6 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=68 accepted=187/232 ttft=0.097 decode=8.666 elapsed=8.763 queued=0.000 tok/s=29.4 +[tensorfold] done cmpl-f4bb0146b75c4fd5736cf08fec0fa673 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=68 accepted=187/232 ttft=0.291 decode=8.472 elapsed=8.763 queued=0.096 tok/s=30.1 +[tensorfold] done cmpl-a093dd3897f6aacc2e1f3ee89cc82a71 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=68 accepted=187/232 ttft=0.194 decode=8.569 elapsed=8.763 queued=0.000 tok/s=29.8 +[tensorfold] done cmpl-149cf4d71d6cc93bd369767c5983306a prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=68 accepted=187/232 ttft=0.387 decode=8.376 elapsed=8.763 queued=0.096 tok/s=30.4 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-80b3f0b8b3e3c02c746b16c2047704e6 prompt=31 cached=0 thinking=False effort=none tokens=16 sha=a9100b9c265b finish=length rounds=5 accepted=10/13 ttft=0.164 decode=0.230 elapsed=0.394 queued=0.000 tok/s=65.3 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-546c369ec25897fe0d936d5d5738668f prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=103 accepted=152/213 ttft=0.164 decode=4.739 elapsed=4.904 queued=0.000 tok/s=53.8 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-ada1ccecf0a6fea88a6713b3e0dc71af prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=255 accepted=0/0 ttft=0.165 decode=6.603 elapsed=6.768 queued=0.000 tok/s=38.6 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-35eab678a8d7b0a99b82012fe82f3dfe prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=103 accepted=152/213 ttft=0.164 decode=4.692 elapsed=4.856 queued=0.000 tok/s=54.3 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-77acdacac8ce2871967005d8ffa0b16f prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=103 accepted=152/213 ttft=0.166 decode=4.479 elapsed=4.645 queued=0.000 tok/s=56.9 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-769fd080e7b6ea14fc25e601d34bbf88 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=103 accepted=152/213 ttft=0.167 decode=4.535 elapsed=4.701 queued=0.000 tok/s=56.2 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-ce54d517820792842700d66119f8e453 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=103 accepted=152/213 ttft=0.165 decode=10.204 elapsed=10.369 queued=0.000 tok/s=25.0 +[tensorfold] done chatcmpl-33c4137aa8a34c508ab925ca4ad5037d prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=103 accepted=152/213 ttft=0.329 decode=10.041 elapsed=10.369 queued=0.000 tok/s=25.4 +[tensorfold] done chatcmpl-a14dd3b146684d1ca9695ff70ed44b2f prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=103 accepted=152/213 ttft=0.493 decode=9.877 elapsed=10.370 queued=0.000 tok/s=25.8 +[tensorfold] done chatcmpl-4ae8bfb4f1aaa5d06cc278210bd42c14 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=103 accepted=152/213 ttft=0.658 decode=9.712 elapsed=10.370 queued=0.000 tok/s=26.3 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-c7f85aaaf6cc92eb1df6d54ec5b95ea3 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=103 accepted=152/213 ttft=0.166 decode=10.171 elapsed=10.337 queued=0.000 tok/s=25.1 +[tensorfold] done chatcmpl-82d83f844fb6fae417c6462935e00f01 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=103 accepted=152/213 ttft=0.624 decode=9.774 elapsed=10.397 queued=0.165 tok/s=26.1 +[tensorfold] done chatcmpl-4d658f27999991fad358f004461078fa prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=103 accepted=152/213 ttft=0.332 decode=10.080 elapsed=10.412 queued=0.165 tok/s=25.3 +[tensorfold] done chatcmpl-f6f069d7c3efb83b8bb40ad0d0bed530 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=103 accepted=152/213 ttft=0.788 decode=9.626 elapsed=10.414 queued=0.165 tok/s=26.5 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-ff01c2b7fbd4052a358201d674f5c085 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=103 accepted=152/213 ttft=0.167 decode=9.613 elapsed=9.780 queued=0.000 tok/s=26.5 +[tensorfold] done chatcmpl-6f480e5f103450a8c92724a5713bc1d9 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=103 accepted=152/213 ttft=0.333 decode=9.448 elapsed=9.780 queued=0.166 tok/s=27.0 +[tensorfold] done chatcmpl-ab38eca2b58bbdaca0a5ee018c249795 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=103 accepted=152/213 ttft=0.499 decode=9.281 elapsed=9.780 queued=0.166 tok/s=27.5 +[tensorfold] done chatcmpl-52fc0e46deb717902a15393b2b8bec0e prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=103 accepted=152/213 ttft=0.666 decode=9.115 elapsed=9.780 queued=0.166 tok/s=28.0 +[tensorfold] 127.0.0.1 "GET /memory HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /metrics HTTP/1.1" 200 - +[tensorfold] shutting down (SIGTERM): draining: new requests get 503; 0 request(s) in progress may finish within 20.0 s +[tensorfold] shutting down: drained +info: graphs: 15 captured (25 ms each), 2454 of 2484 rounds replayed +[tensorfold] shutting down: stopped diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-decode-new-r2.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-decode-new-r2.log new file mode 100644 index 0000000000..d6d63dd2fc --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-decode-new-r2.log @@ -0,0 +1,101 @@ +[tensorfold] HIP rank 0 of 1: policy matrix=auto,attention=auto,kernels=auto,graphs=auto,prefill_step=4096,fill_rows=512,mtp_depth=gated; mtp drafts 7 under 0.9, 8 snapshots +info: lane costs ms by window rows 1:25.27 2:29.67 3:35.06 4:38.14 5:43.22 6:46.66 7:49.76 8:53.58; head step 1.302 +[tensorfold] open-file limit raised: soft 1024 -> 524288 +warning: libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 81.71 GiB on the device, 4 streams of 16448 positions, 0.62 GiB each; prompts in 4096-row chunks +[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: MTP + copies; context: 16384; loaded in 26.1s) +[tensorfold] 127.0.0.1 "GET /health HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-8d5b49dc59cf6406efa2340a5e17d3d7 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=68 accepted=187/232 ttft=0.258 decode=3.876 elapsed=4.134 queued=0.000 tok/s=65.8 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-d00ba1a2356162b07a94ae77365f5f83 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=68 accepted=187/232 ttft=0.099 decode=3.881 elapsed=3.980 queued=0.000 tok/s=65.7 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-0595663614408ba35625d7cba5d2d24f prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=68 accepted=187/232 ttft=0.099 decode=3.886 elapsed=3.985 queued=0.000 tok/s=65.6 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-375cb080d9bef15e14fc0a27d1391b3b prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=68 accepted=187/232 ttft=0.099 decode=3.875 elapsed=3.975 queued=0.000 tok/s=65.8 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-2b08356fba519d37fcd84320c61b72c8 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=103 accepted=152/213 ttft=0.170 decode=4.424 elapsed=4.594 queued=0.000 tok/s=57.6 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-2c57048dd46ddfc93498cce35b6a533a prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=103 accepted=152/213 ttft=0.164 decode=4.719 elapsed=4.884 queued=0.000 tok/s=54.0 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-d4ad0d6f25bdbea22478c2b6ff86c480 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=103 accepted=152/213 ttft=0.167 decode=4.427 elapsed=4.594 queued=0.000 tok/s=57.6 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-1704f8ee8234283d140d1efa9585513f prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=103 accepted=152/213 ttft=0.164 decode=4.702 elapsed=4.867 queued=0.000 tok/s=54.2 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-c396b86e7656eb21e5aa52a24b19ac37 prompt=14 cached=0 thinking=False effort=none tokens=16 sha=f4b7395f11a0 finish=length rounds=8 accepted=8/10 ttft=0.099 decode=0.280 elapsed=0.379 queued=0.000 tok/s=53.5 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-19350ff8f1a3031a05bf3bb02558cddf prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=68 accepted=187/232 ttft=0.097 decode=3.706 elapsed=3.803 queued=0.000 tok/s=68.8 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-c5ec862b8457f00275e1bf31021d4f1d prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=255 accepted=0/0 ttft=0.095 decode=6.735 elapsed=6.830 queued=0.000 tok/s=37.9 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-3def8c1e2c0eaf45422ccf0d4c2b2f41 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=68 accepted=187/232 ttft=0.098 decode=3.764 elapsed=3.861 queued=0.000 tok/s=67.8 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-0698ab678b559919a4caf07e0f6e8cfc prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=68 accepted=187/232 ttft=0.099 decode=3.888 elapsed=3.987 queued=0.000 tok/s=65.6 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-67141a963d647b923bff661f5f7f80ec prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=68 accepted=187/232 ttft=0.099 decode=3.881 elapsed=3.981 queued=0.000 tok/s=65.7 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-178c7c32da477d46e85d91a0a9b87fb5 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=68 accepted=187/232 ttft=0.100 decode=8.769 elapsed=8.869 queued=0.000 tok/s=29.1 +[tensorfold] done cmpl-0af76fe6908b68c781f6decc8d2b0c2b prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=68 accepted=187/232 ttft=0.228 decode=8.641 elapsed=8.869 queued=0.099 tok/s=29.5 +[tensorfold] done cmpl-da7bb5ce0565058145fc899fc3912a1f prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=68 accepted=187/232 ttft=0.337 decode=8.531 elapsed=8.869 queued=0.099 tok/s=29.9 +[tensorfold] done cmpl-cefac1e917b7504c3030bacb0e85f747 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=68 accepted=187/232 ttft=0.455 decode=8.414 elapsed=8.869 queued=0.099 tok/s=30.3 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-c032a0f056b78afaf30b092c630c098a prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=68 accepted=187/232 ttft=0.100 decode=8.707 elapsed=8.807 queued=0.000 tok/s=29.3 +[tensorfold] done cmpl-92ea9adaa7159ac4294d162ec924ff0b prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=68 accepted=187/232 ttft=0.332 decode=8.474 elapsed=8.807 queued=0.099 tok/s=30.1 +[tensorfold] done cmpl-0703b815c39b800ea9baa8fdc9105d73 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=68 accepted=187/232 ttft=0.429 decode=8.378 elapsed=8.807 queued=0.099 tok/s=30.4 +[tensorfold] done cmpl-a47f8e4bb488c75ab27c5db998d301ed prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=68 accepted=187/232 ttft=0.526 decode=8.281 elapsed=8.807 queued=0.098 tok/s=30.8 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-1d3f8a7f2baf4cfe02a5b6dc67984356 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=68 accepted=187/232 ttft=0.097 decode=8.681 elapsed=8.778 queued=0.000 tok/s=29.4 +[tensorfold] done cmpl-dc13477ef146835ab6012f14f60f918b prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=68 accepted=187/232 ttft=0.193 decode=8.603 elapsed=8.796 queued=0.000 tok/s=29.6 +[tensorfold] done cmpl-15ea2ce2af51522b2c9831043d9f2a89 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=68 accepted=187/232 ttft=0.290 decode=8.506 elapsed=8.796 queued=0.000 tok/s=30.0 +[tensorfold] done cmpl-7d6c5ead83f1ad99baacf6f723538ee3 prompt=14 cached=0 thinking=False effort=none tokens=256 sha=beb57dfacf5e finish=length rounds=68 accepted=187/232 ttft=0.387 decode=8.410 elapsed=8.796 queued=0.096 tok/s=30.3 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-72e8003095186d0205ac51b59ac5ebda prompt=31 cached=0 thinking=False effort=none tokens=16 sha=a9100b9c265b finish=length rounds=5 accepted=10/13 ttft=0.164 decode=0.230 elapsed=0.394 queued=0.000 tok/s=65.2 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-618afe0c698205e4b0fc06d4a3cdbe60 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=103 accepted=152/213 ttft=0.166 decode=4.759 elapsed=4.925 queued=0.000 tok/s=53.6 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-4d67f3239d2822c530517a25daaf36ea prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=255 accepted=0/0 ttft=0.164 decode=6.701 elapsed=6.865 queued=0.000 tok/s=38.1 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-22798e41aaf01bece67eb759858fbfe6 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=103 accepted=152/213 ttft=0.166 decode=4.382 elapsed=4.548 queued=0.000 tok/s=58.2 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-f3b5ce353d5dc797bb9e8708b7fa0f8b prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=103 accepted=152/213 ttft=0.165 decode=4.740 elapsed=4.905 queued=0.000 tok/s=53.8 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-5dc904938d3a9487f6290076c9acb825 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=103 accepted=152/213 ttft=0.166 decode=4.355 elapsed=4.521 queued=0.000 tok/s=58.6 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-3f41067ac41ae16d6fe0e63609ba5ffd prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=103 accepted=152/213 ttft=0.333 decode=9.533 elapsed=9.866 queued=0.166 tok/s=26.7 +[tensorfold] done chatcmpl-4bd089e5a4a54aacf708b8f28ba1b8a0 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=103 accepted=152/213 ttft=0.167 decode=9.699 elapsed=9.866 queued=0.000 tok/s=26.3 +[tensorfold] done chatcmpl-82887ccb796adad93dab7bb68838db99 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=103 accepted=152/213 ttft=0.498 decode=9.368 elapsed=9.866 queued=0.166 tok/s=27.2 +[tensorfold] done chatcmpl-b38474473d842920c9ec2ce8740d2c26 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=103 accepted=152/213 ttft=0.665 decode=9.201 elapsed=9.866 queued=0.166 tok/s=27.7 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-92c43210e9685568a14859cf73595b33 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=103 accepted=152/213 ttft=0.168 decode=10.429 elapsed=10.596 queued=0.000 tok/s=24.5 +[tensorfold] done chatcmpl-f35db05172dd246e3d3666de3ac5a1c3 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=103 accepted=152/213 ttft=0.334 decode=10.262 elapsed=10.596 queued=0.167 tok/s=24.8 +[tensorfold] done chatcmpl-917c4977794262f2f422ce550bd96b68 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=103 accepted=152/213 ttft=0.528 decode=10.113 elapsed=10.642 queued=0.167 tok/s=25.2 +[tensorfold] done chatcmpl-deb4ba73995efb161599a4d260b8aec3 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=103 accepted=152/213 ttft=0.697 decode=10.136 elapsed=10.833 queued=0.166 tok/s=25.2 +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/chat/completions HTTP/1.1" 200 - +[tensorfold] done chatcmpl-44d0c522c2fb9d5fec77e71fb2c6debd prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=103 accepted=152/213 ttft=0.168 decode=10.372 elapsed=10.539 queued=0.000 tok/s=24.6 +[tensorfold] done chatcmpl-c551c8eb5c0b4d45552864631278628b prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=103 accepted=152/213 ttft=0.333 decode=10.206 elapsed=10.539 queued=0.167 tok/s=25.0 +[tensorfold] done chatcmpl-fac9e4c26a8111ab413f4a3bc0e4f532 prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=103 accepted=152/213 ttft=0.499 decode=10.040 elapsed=10.539 queued=0.166 tok/s=25.4 +[tensorfold] done chatcmpl-4d4ce4060b77e2863f65c510147a4dab prompt=31 cached=0 thinking=False effort=none tokens=256 sha=e5fa3204ab36 finish=length rounds=103 accepted=152/213 ttft=0.664 decode=9.876 elapsed=10.540 queued=0.166 tok/s=25.8 +[tensorfold] 127.0.0.1 "GET /memory HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /metrics HTTP/1.1" 200 - +[tensorfold] shutting down (SIGTERM): draining: new requests get 503; 0 request(s) in progress may finish within 20.0 s +[tensorfold] shutting down: drained +info: graphs: 15 captured (20 ms each), 2454 of 2484 rounds replayed +[tensorfold] shutting down: stopped diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-mem-base-r1.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-mem-base-r1.log new file mode 100644 index 0000000000..e733568f14 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-mem-base-r1.log @@ -0,0 +1,15 @@ +[tensorfold] HIP rank 0 of 1: policy matrix=auto,attention=auto,kernels=auto,graphs=auto,prefill_step=1024,fill_rows=512; mtp drafts 3 under 0.3, 8 snapshots +[tensorfold] open-file limit raised: soft 1024 -> 524288 +warning: libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 76.58 GiB on the device, 1 stream of 20544 positions, 1.14 GiB each; prompts in 1024-row chunks +[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: MTP + copies; context: 20480; loaded in 10.4s) +[tensorfold] 127.0.0.1 "GET /health HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-48f36b171e7cf79d885ebbc0b5a4953d prompt=256 cached=0 thinking=False effort=none tokens=1 sha=3635a91e3da8 finish=length rounds=0 accepted=0/0 ttft=0.702 decode=0.000 elapsed=0.703 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-da35ea42ec7a3f6fc2435e3c52de567a prompt=16384 cached=0 thinking=False effort=none tokens=1 sha=239d455de119 finish=length rounds=0 accepted=0/0 ttft=46.469 decode=0.000 elapsed=46.469 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "GET /memory HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /metrics HTTP/1.1" 200 - +[tensorfold] shutting down (SIGTERM): draining: new requests get 503; 0 request(s) in progress may finish within 20.0 s +[tensorfold] shutting down: drained +[tensorfold] shutting down: stopped diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-mem-base-r2.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-mem-base-r2.log new file mode 100644 index 0000000000..7731a61a37 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-mem-base-r2.log @@ -0,0 +1,15 @@ +[tensorfold] HIP rank 0 of 1: policy matrix=auto,attention=auto,kernels=auto,graphs=auto,prefill_step=1024,fill_rows=512; mtp drafts 3 under 0.3, 8 snapshots +[tensorfold] open-file limit raised: soft 1024 -> 524288 +warning: libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 76.58 GiB on the device, 1 stream of 20544 positions, 1.14 GiB each; prompts in 1024-row chunks +[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: MTP + copies; context: 20480; loaded in 10.4s) +[tensorfold] 127.0.0.1 "GET /health HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-7257e01589272fd41f5e79af634a6d9b prompt=256 cached=0 thinking=False effort=none tokens=1 sha=3635a91e3da8 finish=length rounds=0 accepted=0/0 ttft=0.706 decode=0.000 elapsed=0.706 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-2049dbc6a54e65764e51a4b5f6dd94e9 prompt=16384 cached=0 thinking=False effort=none tokens=1 sha=239d455de119 finish=length rounds=0 accepted=0/0 ttft=46.461 decode=0.000 elapsed=46.461 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "GET /memory HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /metrics HTTP/1.1" 200 - +[tensorfold] shutting down (SIGTERM): draining: new requests get 503; 0 request(s) in progress may finish within 20.0 s +[tensorfold] shutting down: drained +[tensorfold] shutting down: stopped diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-mem-new-default-r1.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-mem-new-default-r1.log new file mode 100644 index 0000000000..d522bbce1f --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-mem-new-default-r1.log @@ -0,0 +1,17 @@ +[tensorfold] HIP rank 0 of 1: policy matrix=auto,attention=auto,kernels=auto,graphs=auto,prefill_step=4096,fill_rows=512,mtp_depth=gated; mtp drafts 7 under 0.9, 8 snapshots +info: lane costs ms by window rows 1:25.28 2:29.56 3:34.67 4:38.19 5:43.15 6:46.56 7:49.88 8:53.41; head step 1.303 +[tensorfold] open-file limit raised: soft 1024 -> 524288 +warning: libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 81.82 GiB on the device, 1 stream of 20544 positions, 0.74 GiB each; prompts in 4096-row chunks +[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: MTP + copies; context: 20480; loaded in 37.7s) +[tensorfold] 127.0.0.1 "GET /health HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-4876792493aa20ac626341ab35c0971a prompt=256 cached=0 thinking=False effort=none tokens=1 sha=3635a91e3da8 finish=length rounds=0 accepted=0/0 ttft=0.436 decode=0.000 elapsed=0.436 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-31f3f109ef17ca26f87db0a6559f2735 prompt=16384 cached=0 thinking=False effort=none tokens=1 sha=239d455de119 finish=length rounds=0 accepted=0/0 ttft=30.733 decode=0.000 elapsed=30.733 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "GET /memory HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /metrics HTTP/1.1" 200 - +[tensorfold] shutting down (SIGTERM): draining: new requests get 503; 0 request(s) in progress may finish within 20.0 s +[tensorfold] shutting down: drained +info: graphs: 8 captured (15 ms each), 64 of 80 rounds replayed +[tensorfold] shutting down: stopped diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-mem-new-default-r2.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-mem-new-default-r2.log new file mode 100644 index 0000000000..7bbccf03d2 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-mem-new-default-r2.log @@ -0,0 +1,17 @@ +[tensorfold] HIP rank 0 of 1: policy matrix=auto,attention=auto,kernels=auto,graphs=auto,prefill_step=4096,fill_rows=512,mtp_depth=gated; mtp drafts 7 under 0.9, 8 snapshots +info: lane costs ms by window rows 1:25.27 2:29.61 3:34.69 4:38.26 5:43.18 6:46.69 7:49.90 8:53.43; head step 1.293 +[tensorfold] open-file limit raised: soft 1024 -> 524288 +warning: libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 81.82 GiB on the device, 1 stream of 20544 positions, 0.74 GiB each; prompts in 4096-row chunks +[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: MTP + copies; context: 20480; loaded in 28.3s) +[tensorfold] 127.0.0.1 "GET /health HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-e0de752e5d6d3c384122ded02b853f75 prompt=256 cached=0 thinking=False effort=none tokens=1 sha=3635a91e3da8 finish=length rounds=0 accepted=0/0 ttft=0.443 decode=0.000 elapsed=0.443 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-f984764f5c9601384235f47f273713a0 prompt=16384 cached=0 thinking=False effort=none tokens=1 sha=239d455de119 finish=length rounds=0 accepted=0/0 ttft=30.822 decode=0.000 elapsed=30.822 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "GET /memory HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /metrics HTTP/1.1" 200 - +[tensorfold] shutting down (SIGTERM): draining: new requests get 503; 0 request(s) in progress may finish within 20.0 s +[tensorfold] shutting down: drained +info: graphs: 8 captured (14 ms each), 64 of 80 rounds replayed +[tensorfold] shutting down: stopped diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-mem-new-mapped-cold-r1.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-mem-new-mapped-cold-r1.log new file mode 100644 index 0000000000..f90973b1b3 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-mem-new-mapped-cold-r1.log @@ -0,0 +1,17 @@ +[tensorfold] HIP rank 0 of 1: policy matrix=auto,attention=auto,kernels=auto,graphs=auto,prefill_step=4096,fill_rows=512,rows=mapped,mtp_depth=gated; mtp drafts 7 under 0.9, 8 snapshots +info: lane costs ms by window rows 1:25.25 2:29.57 3:34.65 4:38.35 5:43.22 6:46.57 7:49.99 8:53.49; head step 1.289 +[tensorfold] open-file limit raised: soft 1024 -> 524288 +warning: libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 81.82 GiB on the device, 1 stream of 20544 positions, 0.74 GiB each; prompts in 4096-row chunks +[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: MTP + copies; context: 20480; loaded in 18.3s) +[tensorfold] 127.0.0.1 "GET /health HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-a01dfb69693a5697e5409239af0221e7 prompt=256 cached=0 thinking=False effort=none tokens=1 sha=3635a91e3da8 finish=length rounds=0 accepted=0/0 ttft=1.656 decode=0.000 elapsed=1.657 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-26053f98e4635a49715d511f3cd4e148 prompt=16384 cached=0 thinking=False effort=none tokens=1 sha=239d455de119 finish=length rounds=0 accepted=0/0 ttft=46.296 decode=0.000 elapsed=46.296 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "GET /memory HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /metrics HTTP/1.1" 200 - +[tensorfold] shutting down (SIGTERM): draining: new requests get 503; 0 request(s) in progress may finish within 20.0 s +[tensorfold] shutting down: drained +info: graphs: 8 captured (6 ms each), 64 of 80 rounds replayed +[tensorfold] shutting down: stopped diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-mem-new-mapped-cold-r2.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-mem-new-mapped-cold-r2.log new file mode 100644 index 0000000000..65f32f65f6 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-mem-new-mapped-cold-r2.log @@ -0,0 +1,17 @@ +[tensorfold] HIP rank 0 of 1: policy matrix=auto,attention=auto,kernels=auto,graphs=auto,prefill_step=4096,fill_rows=512,rows=mapped,mtp_depth=gated; mtp drafts 7 under 0.9, 8 snapshots +info: lane costs ms by window rows 1:25.27 2:29.64 3:35.11 4:38.10 5:43.23 6:46.64 7:49.78 8:53.54; head step 1.289 +[tensorfold] open-file limit raised: soft 1024 -> 524288 +warning: libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 81.82 GiB on the device, 1 stream of 20544 positions, 0.74 GiB each; prompts in 4096-row chunks +[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: MTP + copies; context: 20480; loaded in 18.7s) +[tensorfold] 127.0.0.1 "GET /health HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-1fa8b03a82ac471a0a64aac2ca5d5ecb prompt=256 cached=0 thinking=False effort=none tokens=1 sha=3635a91e3da8 finish=length rounds=0 accepted=0/0 ttft=1.611 decode=0.000 elapsed=1.612 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-d5ad2c1ebfa9efaca8b58c83860d89ff prompt=16384 cached=0 thinking=False effort=none tokens=1 sha=239d455de119 finish=length rounds=0 accepted=0/0 ttft=46.202 decode=0.000 elapsed=46.202 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "GET /memory HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /metrics HTTP/1.1" 200 - +[tensorfold] shutting down (SIGTERM): draining: new requests get 503; 0 request(s) in progress may finish within 20.0 s +[tensorfold] shutting down: drained +info: graphs: 8 captured (20 ms each), 64 of 80 rounds replayed +[tensorfold] shutting down: stopped diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-mem-new-mapped-warm-r1.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-mem-new-mapped-warm-r1.log new file mode 100644 index 0000000000..b55d6d6962 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-mem-new-mapped-warm-r1.log @@ -0,0 +1,17 @@ +[tensorfold] HIP rank 0 of 1: policy matrix=auto,attention=auto,kernels=auto,graphs=auto,prefill_step=4096,fill_rows=512,rows=mapped,mtp_depth=gated; mtp drafts 7 under 0.9, 8 snapshots +info: lane costs ms by window rows 1:25.26 2:29.56 3:34.64 4:38.54 5:43.26 6:46.64 7:50.06 8:53.45; head step 1.298 +[tensorfold] open-file limit raised: soft 1024 -> 524288 +warning: libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 81.82 GiB on the device, 1 stream of 20544 positions, 0.74 GiB each; prompts in 4096-row chunks +[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: MTP + copies; context: 20480; loaded in 13.8s) +[tensorfold] 127.0.0.1 "GET /health HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-6c2317639a5436ba834369eb71f09e20 prompt=256 cached=0 thinking=False effort=none tokens=1 sha=3635a91e3da8 finish=length rounds=0 accepted=0/0 ttft=0.451 decode=0.000 elapsed=0.451 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-990081086def1a5e8051c989a684cd92 prompt=16384 cached=0 thinking=False effort=none tokens=1 sha=239d455de119 finish=length rounds=0 accepted=0/0 ttft=30.922 decode=0.000 elapsed=30.922 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "GET /memory HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /metrics HTTP/1.1" 200 - +[tensorfold] shutting down (SIGTERM): draining: new requests get 503; 0 request(s) in progress may finish within 20.0 s +[tensorfold] shutting down: drained +info: graphs: 8 captured (12 ms each), 64 of 80 rounds replayed +[tensorfold] shutting down: stopped diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-mem-new-mapped-warm-r2.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-mem-new-mapped-warm-r2.log new file mode 100644 index 0000000000..61b94db8a8 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-mem-new-mapped-warm-r2.log @@ -0,0 +1,17 @@ +[tensorfold] HIP rank 0 of 1: policy matrix=auto,attention=auto,kernels=auto,graphs=auto,prefill_step=4096,fill_rows=512,rows=mapped,mtp_depth=gated; mtp drafts 7 under 0.9, 8 snapshots +info: lane costs ms by window rows 1:25.24 2:29.62 3:34.83 4:38.05 5:43.17 6:46.62 7:49.71 8:53.55; head step 1.297 +[tensorfold] open-file limit raised: soft 1024 -> 524288 +warning: libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 81.82 GiB on the device, 1 stream of 20544 positions, 0.74 GiB each; prompts in 4096-row chunks +[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: MTP + copies; context: 20480; loaded in 14.1s) +[tensorfold] 127.0.0.1 "GET /health HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-d1866585a6dbaaa586347ff92f512490 prompt=256 cached=0 thinking=False effort=none tokens=1 sha=3635a91e3da8 finish=length rounds=0 accepted=0/0 ttft=0.440 decode=0.000 elapsed=0.440 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-9e4778c63dd7248b7ecbc7180be58688 prompt=16384 cached=0 thinking=False effort=none tokens=1 sha=239d455de119 finish=length rounds=0 accepted=0/0 ttft=30.938 decode=0.000 elapsed=30.938 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "GET /memory HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /metrics HTTP/1.1" 200 - +[tensorfold] shutting down (SIGTERM): draining: new requests get 503; 0 request(s) in progress may finish within 20.0 s +[tensorfold] shutting down: drained +info: graphs: 8 captured (32 ms each), 64 of 80 rounds replayed +[tensorfold] shutting down: stopped diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-mem-new-step1024-mapped-r1.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-mem-new-step1024-mapped-r1.log new file mode 100644 index 0000000000..cd54fd57a7 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-mem-new-step1024-mapped-r1.log @@ -0,0 +1,17 @@ +[tensorfold] HIP rank 0 of 1: policy matrix=auto,attention=auto,kernels=auto,graphs=auto,prefill_step=1024,fill_rows=512,rows=mapped,mtp_depth=gated; mtp drafts 7 under 0.9, 8 snapshots +info: lane costs ms by window rows 1:25.29 2:29.55 3:34.64 4:38.42 5:43.26 6:46.68 7:50.08 8:53.52; head step 1.285 +[tensorfold] open-file limit raised: soft 1024 -> 524288 +warning: libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 77.36 GiB on the device, 1 stream of 20544 positions, 0.74 GiB each; prompts in 1024-row chunks +[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: MTP + copies; context: 20480; loaded in 13.8s) +[tensorfold] 127.0.0.1 "GET /health HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-977a2dedbc724d77c395fff4fb665842 prompt=256 cached=0 thinking=False effort=none tokens=1 sha=3635a91e3da8 finish=length rounds=0 accepted=0/0 ttft=0.439 decode=0.000 elapsed=0.439 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-8c771ee8b431446b937d242df4473689 prompt=16384 cached=0 thinking=False effort=none tokens=1 sha=239d455de119 finish=length rounds=0 accepted=0/0 ttft=34.124 decode=0.000 elapsed=34.124 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "GET /memory HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /metrics HTTP/1.1" 200 - +[tensorfold] shutting down (SIGTERM): draining: new requests get 503; 0 request(s) in progress may finish within 20.0 s +[tensorfold] shutting down: drained +info: graphs: 8 captured (13 ms each), 64 of 80 rounds replayed +[tensorfold] shutting down: stopped diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-mem-new-step1024-mapped-r2.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-mem-new-step1024-mapped-r2.log new file mode 100644 index 0000000000..127e019605 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-mem-new-step1024-mapped-r2.log @@ -0,0 +1,17 @@ +[tensorfold] HIP rank 0 of 1: policy matrix=auto,attention=auto,kernels=auto,graphs=auto,prefill_step=1024,fill_rows=512,rows=mapped,mtp_depth=gated; mtp drafts 7 under 0.9, 8 snapshots +info: lane costs ms by window rows 1:25.26 2:29.59 3:34.67 4:38.45 5:43.19 6:46.62 7:50.04 8:53.50; head step 1.287 +[tensorfold] open-file limit raised: soft 1024 -> 524288 +warning: libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 77.36 GiB on the device, 1 stream of 20544 positions, 0.74 GiB each; prompts in 1024-row chunks +[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: MTP + copies; context: 20480; loaded in 13.8s) +[tensorfold] 127.0.0.1 "GET /health HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-f4d77503890bc90b160d584a31892740 prompt=256 cached=0 thinking=False effort=none tokens=1 sha=3635a91e3da8 finish=length rounds=0 accepted=0/0 ttft=0.443 decode=0.000 elapsed=0.443 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-e155ec84bb5e620ce39429f5e12ba30f prompt=16384 cached=0 thinking=False effort=none tokens=1 sha=239d455de119 finish=length rounds=0 accepted=0/0 ttft=34.122 decode=0.000 elapsed=34.123 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "GET /memory HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /metrics HTTP/1.1" 200 - +[tensorfold] shutting down (SIGTERM): draining: new requests get 503; 0 request(s) in progress may finish within 20.0 s +[tensorfold] shutting down: drained +info: graphs: 8 captured (12 ms each), 64 of 80 rounds replayed +[tensorfold] shutting down: stopped diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-mem-new-step1024-r1.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-mem-new-step1024-r1.log new file mode 100644 index 0000000000..ef8bb27603 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-mem-new-step1024-r1.log @@ -0,0 +1,17 @@ +[tensorfold] HIP rank 0 of 1: policy matrix=auto,attention=auto,kernels=auto,graphs=auto,prefill_step=1024,fill_rows=512,mtp_depth=gated; mtp drafts 7 under 0.9, 8 snapshots +info: lane costs ms by window rows 1:25.37 2:29.66 3:34.72 4:38.11 5:43.50 6:46.56 7:49.72 8:53.78; head step 1.295 +[tensorfold] open-file limit raised: soft 1024 -> 524288 +warning: libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 77.36 GiB on the device, 1 stream of 20544 positions, 0.74 GiB each; prompts in 1024-row chunks +[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: MTP + copies; context: 20480; loaded in 29.6s) +[tensorfold] 127.0.0.1 "GET /health HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-9065ac039622df64393a266dfe28ad2d prompt=256 cached=0 thinking=False effort=none tokens=1 sha=3635a91e3da8 finish=length rounds=0 accepted=0/0 ttft=0.428 decode=0.000 elapsed=0.428 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-4c08101f367c44e6f8cfe52ef72d5bc7 prompt=16384 cached=0 thinking=False effort=none tokens=1 sha=239d455de119 finish=length rounds=0 accepted=0/0 ttft=33.899 decode=0.000 elapsed=33.899 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "GET /memory HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /metrics HTTP/1.1" 200 - +[tensorfold] shutting down (SIGTERM): draining: new requests get 503; 0 request(s) in progress may finish within 20.0 s +[tensorfold] shutting down: drained +info: graphs: 8 captured (22 ms each), 64 of 80 rounds replayed +[tensorfold] shutting down: stopped diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-mem-new-step1024-r2.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-mem-new-step1024-r2.log new file mode 100644 index 0000000000..1781caf704 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-mem-new-step1024-r2.log @@ -0,0 +1,17 @@ +[tensorfold] HIP rank 0 of 1: policy matrix=auto,attention=auto,kernels=auto,graphs=auto,prefill_step=1024,fill_rows=512,mtp_depth=gated; mtp drafts 7 under 0.9, 8 snapshots +info: lane costs ms by window rows 1:25.29 2:29.60 3:52.40 4:38.53 5:43.21 6:46.60 7:49.98 8:53.48; head step 1.290 +[tensorfold] open-file limit raised: soft 1024 -> 524288 +warning: libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 77.36 GiB on the device, 1 stream of 20544 positions, 0.74 GiB each; prompts in 1024-row chunks +[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: MTP + copies; context: 20480; loaded in 31.7s) +[tensorfold] 127.0.0.1 "GET /health HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-fbe2c176490a5bafb488a93ad56d250c prompt=256 cached=0 thinking=False effort=none tokens=1 sha=3635a91e3da8 finish=length rounds=0 accepted=0/0 ttft=0.443 decode=0.000 elapsed=0.443 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-144830af40c148afcd552598d084f57e prompt=16384 cached=0 thinking=False effort=none tokens=1 sha=239d455de119 finish=length rounds=0 accepted=0/0 ttft=33.835 decode=0.000 elapsed=33.835 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "GET /memory HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /metrics HTTP/1.1" 200 - +[tensorfold] shutting down (SIGTERM): draining: new requests get 503; 0 request(s) in progress may finish within 20.0 s +[tensorfold] shutting down: drained +info: graphs: 8 captured (14 ms each), 64 of 80 rounds replayed +[tensorfold] shutting down: stopped diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-mem-new-step20480-r1.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-mem-new-step20480-r1.log new file mode 100644 index 0000000000..30a256de80 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-mem-new-step20480-r1.log @@ -0,0 +1,17 @@ +[tensorfold] HIP rank 0 of 1: policy matrix=auto,attention=auto,kernels=auto,graphs=auto,prefill_step=20480,fill_rows=512,mtp_depth=gated; mtp drafts 7 under 0.9, 8 snapshots +info: lane costs ms by window rows 1:27.59 2:29.67 3:34.70 4:38.04 5:43.23 6:46.85 7:49.76 8:53.48; head step 1.282 +[tensorfold] open-file limit raised: soft 1024 -> 524288 +warning: libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 105.63 GiB on the device, 1 stream of 20544 positions, 0.74 GiB each; prompts in 20480-row chunks +[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: MTP + copies; context: 20480; loaded in 31.4s) +[tensorfold] 127.0.0.1 "GET /health HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-dce5acb8f5fd149e43222de96736b423 prompt=256 cached=0 thinking=False effort=none tokens=1 sha=3635a91e3da8 finish=length rounds=0 accepted=0/0 ttft=0.425 decode=0.000 elapsed=0.425 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-eab143821ba5b6a1d252f8f836f7ac71 prompt=16384 cached=0 thinking=False effort=none tokens=1 sha=239d455de119 finish=length rounds=0 accepted=0/0 ttft=29.692 decode=0.001 elapsed=29.692 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "GET /memory HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /metrics HTTP/1.1" 200 - +[tensorfold] shutting down (SIGTERM): draining: new requests get 503; 0 request(s) in progress may finish within 20.0 s +[tensorfold] shutting down: drained +info: graphs: 8 captured (18 ms each), 64 of 80 rounds replayed +[tensorfold] shutting down: stopped diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-mem-new-step20480-r2.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-mem-new-step20480-r2.log new file mode 100644 index 0000000000..7596a36b57 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/server-mem-new-step20480-r2.log @@ -0,0 +1,17 @@ +[tensorfold] HIP rank 0 of 1: policy matrix=auto,attention=auto,kernels=auto,graphs=auto,prefill_step=20480,fill_rows=512,mtp_depth=gated; mtp drafts 7 under 0.9, 8 snapshots +info: lane costs ms by window rows 1:25.26 2:30.04 3:34.68 4:38.11 5:43.28 6:46.76 7:49.80 8:53.48; head step 1.287 +[tensorfold] open-file limit raised: soft 1024 -> 524288 +warning: libtfgrammar.so is required for structured output and required tool calls (HTTP 400 when missing); restore the matching release archive's lib/ directory or run zig build grammar -Dxgrammar=DIR; prepare DIR with git clone --branch v0.2.8 --recurse-submodules https://github.com/mlc-ai/xgrammar +[tensorfold] HIP gfx1151 device 0, rank 0 of 1: Flash Next, 105.63 GiB on the device, 1 stream of 20544 positions, 0.74 GiB each; prompts in 20480-row chunks +[tensorfold] serving flashnext at http://127.0.0.1:30461/v1 (sampling: temperature 1.0, top_k 20, top_p 0.95; drafts: MTP + copies; context: 20480; loaded in 34.1s) +[tensorfold] 127.0.0.1 "GET /health HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-653e5b7c36af6c9adbc7937ce17cde4d prompt=256 cached=0 thinking=False effort=none tokens=1 sha=3635a91e3da8 finish=length rounds=0 accepted=0/0 ttft=0.425 decode=0.000 elapsed=0.426 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "POST /v1/completions HTTP/1.1" 200 - +[tensorfold] done cmpl-2689050e0bab0d1b5ae0f50561b72525 prompt=16384 cached=0 thinking=False effort=none tokens=1 sha=239d455de119 finish=length rounds=0 accepted=0/0 ttft=29.838 decode=0.000 elapsed=29.838 queued=0.000 tok/s=0.0 +[tensorfold] 127.0.0.1 "GET /memory HTTP/1.1" 200 - +[tensorfold] 127.0.0.1 "GET /metrics HTTP/1.1" 200 - +[tensorfold] shutting down (SIGTERM): draining: new requests get 503; 0 request(s) in progress may finish within 20.0 s +[tensorfold] shutting down: drained +info: graphs: 8 captured (3 ms each), 64 of 80 rounds replayed +[tensorfold] shutting down: stopped diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/session-01.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/session-01.log new file mode 100644 index 0000000000..57245a4666 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/session-01.log @@ -0,0 +1,80 @@ +pgrep: pattern that searches for process name longer than 15 characters will result in zero matches +Try `pgrep -f' option to match against the complete command line. +pgrep: pattern that searches for process name longer than 15 characters will result in zero matches +Try `pgrep -f' option to match against the complete command line. +pgrep: pattern that searches for process name longer than 15 characters will result in zero matches +Try `pgrep -f' option to match against the complete command line. +pgrep: pattern that searches for process name longer than 15 characters will result in zero matches +Try `pgrep -f' option to match against the complete command line. +pgrep: pattern that searches for process name longer than 15 characters will result in zero matches +Try `pgrep -f' option to match against the complete command line. +== 2026-10-31T09:34:07Z server cold-new-2048-r1: context 10240, parallel 1, prompt cache 0 GiB +== 2026-10-31T09:34:33Z step cold-new-2048-r1 +== 2026-10-31T09:34:37Z step cold-new-2048-r1 rc=0 +== 2026-10-31T09:34:39Z server cold-base-2048-r1: context 10240, parallel 1, prompt cache 0 GiB +== 2026-10-31T09:34:51Z step cold-base-2048-r1 +== 2026-10-31T09:35:00Z step cold-base-2048-r1 rc=0 +== 2026-10-31T09:35:02Z server cold-new-2048-r2: context 10240, parallel 1, prompt cache 0 GiB +== 2026-10-31T09:35:28Z step cold-new-2048-r2 +== 2026-10-31T09:35:32Z step cold-new-2048-r2 rc=0 +== 2026-10-31T09:35:34Z server cold-base-2048-r2: context 10240, parallel 1, prompt cache 0 GiB +== 2026-10-31T09:35:46Z step cold-base-2048-r2 +== 2026-10-31T09:35:55Z step cold-base-2048-r2 rc=0 +== 2026-10-31T09:35:56Z server cold-new-8192-r1: context 16384, parallel 1, prompt cache 0 GiB +== 2026-10-31T09:36:21Z step cold-new-8192-r1 +== 2026-10-31T09:36:37Z step cold-new-8192-r1 rc=0 +== 2026-10-31T09:36:38Z server cold-base-8192-r1: context 16384, parallel 1, prompt cache 0 GiB +== 2026-10-31T09:36:51Z step cold-base-8192-r1 +== 2026-10-31T09:37:25Z step cold-base-8192-r1 rc=0 +== 2026-10-31T09:37:26Z server cold-new-8192-r2: context 16384, parallel 1, prompt cache 0 GiB +== 2026-10-31T09:37:53Z step cold-new-8192-r2 +== 2026-10-31T09:38:09Z step cold-new-8192-r2 rc=0 +== 2026-10-31T09:38:11Z server cold-base-8192-r2: context 16384, parallel 1, prompt cache 0 GiB +== 2026-10-31T09:38:24Z step cold-base-8192-r2 +== 2026-10-31T09:38:58Z step cold-base-8192-r2 rc=0 +== 2026-10-31T09:39:00Z server cold-new-32768-r1: context 40960, parallel 1, prompt cache 0 GiB +== 2026-10-31T09:39:27Z step cold-new-32768-r1 +== 2026-10-31T09:40:32Z step cold-new-32768-r1 rc=0 +== 2026-10-31T09:40:34Z server cold-base-32768-r1: context 40960, parallel 1, prompt cache 0 GiB +== 2026-10-31T09:40:47Z step cold-base-32768-r1 +== 2026-10-31T09:42:56Z step cold-base-32768-r1 rc=0 +== 2026-10-31T09:42:58Z server cold-new-32768-r2: context 40960, parallel 1, prompt cache 0 GiB +== 2026-10-31T09:43:28Z step cold-new-32768-r2 +== 2026-10-31T09:44:32Z step cold-new-32768-r2 rc=0 +== 2026-10-31T09:44:34Z server cold-base-32768-r2: context 40960, parallel 1, prompt cache 0 GiB +== 2026-10-31T09:44:47Z step cold-base-32768-r2 +== 2026-10-31T09:46:55Z step cold-base-32768-r2 rc=0 +## Cold prefill (max_tokens 1, prompt cache off, fresh server per run) +| arm | prompt tokens | context | prefill tok/s (median) | per round | TTFT (s) | wall (s) | cached tokens | GTT+VRAM peak over idle (GiB) | RSS peak (GiB) | server | +|---|---|---|---|---|---|---|---|---|---|---| +| new | 2,048 | 10240 | 673.7 | 681.4, 666.0 | 3.040 | 3.041 | 0 | 82.45 | 102.9 | ready | +| base | 2,048 | 10240 | 293.2 | 290.0, 296.4 | 6.986 | 6.996 | 0 | 78.21 | 76.81 | ready | +| new | 8,192 | 16384 | 558.2 | 559.2, 557.2 | 14.68 | 14.68 | 0 | 82.62 | 105.0 | ready | +| base | 8,192 | 16384 | 261.3 | 261.3, 261.3 | 31.35 | 31.35 | 0 | 78.39 | 77.56 | ready | +| new | 32,768 | 40960 | 513.5 | 512.6, 514.5 | 63.81 | 63.81 | 0 | 83.33 | 105.0 | ready | +| base | 32,768 | 40960 | 260.4 | 260.1, 260.6 | 125.9 | 125.9 | 0 | 79.09 | 79.81 | ready | + +new / base, prefill tok/s +| prompt tokens | new | base | ratio | +|---|---|---|---| +| 2,048 | 673.7 | 293.2 | 2.298 | +| 8,192 | 558.2 | 261.3 | 2.136 | +| 32,768 | 513.5 | 260.4 | 1.972 | + +## Decode, one stream (bench_openai.py, 256 tokens, greedy, drafts on) +| arm | prompt | decode tok/s (median) | per round | TTFT (s) | wall (s, derived) | spec-decode hit rate | GTT+VRAM peak (GiB) | RSS peak (GiB) | +|---|---|---|---|---|---|---|---|---| + +## Prefill, serial decode and Default MTP decode (one public-code prompt, greedy, cache off, drafts as stated) +| arm | decode | output tokens | decode tok/s (median) | every rep | TTFT (s) | wall (s) | spec-decode hit rate | GTT+VRAM peak over idle (GiB) | RSS peak (GiB) | cached tokens | +|---|---|---|---|---|---|---|---|---|---|---| + +| arm | prefill tok/s (cold, 16K) | MTP token hash == serial's | +|---|---|---| +| new | - | | +| base | - | | + +## Concurrent (bench_concurrent.py --levels 1,4 --alone --serial) +| arm | prompt | streams | aggregate tok/s | per-stream tok/s | concurrent==alone (eq/ne/failed) | alone==draft:false (eq/ne/failed) | failed requests | +|---|---|---|---|---|---|---|---| +== 2026-10-31T09:46:58Z perf done; next: finalize.sh diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/session-02.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/session-02.log new file mode 100644 index 0000000000..9e80b144d0 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/session-02.log @@ -0,0 +1,74 @@ +pgrep: pattern that searches for process name longer than 15 characters will result in zero matches +Try `pgrep -f' option to match against the complete command line. +pgrep: pattern that searches for process name longer than 15 characters will result in zero matches +Try `pgrep -f' option to match against the complete command line. +pgrep: pattern that searches for process name longer than 15 characters will result in zero matches +Try `pgrep -f' option to match against the complete command line. +pgrep: pattern that searches for process name longer than 15 characters will result in zero matches +Try `pgrep -f' option to match against the complete command line. +pgrep: pattern that searches for process name longer than 15 characters will result in zero matches +Try `pgrep -f' option to match against the complete command line. +== 2026-10-31T10:03:40Z server cold-new-65536-r1: context 73728, parallel 1, prompt cache 0 GiB +== 2026-10-31T10:04:19Z step cold-new-65536-r1 +== 2026-10-31T10:06:31Z step cold-new-65536-r1 rc=0 +== 2026-10-31T10:06:33Z server cold-base-65536-r1: context 73728, parallel 1, prompt cache 0 GiB +== 2026-10-31T10:06:47Z step cold-base-65536-r1 +== 2026-10-31T10:11:01Z step cold-base-65536-r1 rc=0 +== 2026-10-31T10:11:04Z server cold-new-65536-r2: context 73728, parallel 1, prompt cache 0 GiB +== 2026-10-31T10:11:31Z step cold-new-65536-r2 +== 2026-10-31T10:13:44Z step cold-new-65536-r2 rc=0 +== 2026-10-31T10:13:46Z server cold-base-65536-r2: context 73728, parallel 1, prompt cache 0 GiB +== 2026-10-31T10:13:59Z step cold-base-65536-r2 +== 2026-10-31T10:18:14Z step cold-base-65536-r2 rc=0 +== 2026-10-31T10:18:16Z server cold-new-131072-r1: context 139264, parallel 1, prompt cache 0 GiB +== 2026-10-31T10:18:45Z step cold-new-131072-r1 +== 2026-10-31T10:23:23Z step cold-new-131072-r1 rc=0 +== 2026-10-31T10:23:25Z server cold-base-131072-r1: context 139264, parallel 1, prompt cache 0 GiB +== 2026-10-31T10:23:39Z step cold-base-131072-r1 +== 2026-10-31T10:32:08Z step cold-base-131072-r1 rc=0 +== 2026-10-31T10:32:11Z server cold-new-131072-r2: context 139264, parallel 1, prompt cache 0 GiB +== 2026-10-31T10:32:40Z step cold-new-131072-r2 +== 2026-10-31T10:37:19Z step cold-new-131072-r2 rc=0 +== 2026-10-31T10:37:21Z server cold-base-131072-r2: context 139264, parallel 1, prompt cache 0 GiB +== 2026-10-31T10:37:35Z step cold-base-131072-r2 +== 2026-10-31T10:46:06Z step cold-base-131072-r2 rc=0 +## Cold prefill (max_tokens 1, prompt cache off, fresh server per run) +| arm | prompt tokens | context | prefill tok/s (median) | per round | TTFT (s) | wall (s) | cached tokens | GTT+VRAM peak over idle (GiB) | RSS peak (GiB) | server | +|---|---|---|---|---|---|---|---|---|---|---| +| new | 2,048 | 10240 | 673.7 | 681.4, 666.0 | 3.040 | 3.041 | 0 | 82.45 | 102.9 | ready | +| base | 2,048 | 10240 | 293.2 | 290.0, 296.4 | 6.986 | 6.996 | 0 | 78.21 | 76.81 | ready | +| new | 8,192 | 16384 | 558.2 | 559.2, 557.2 | 14.68 | 14.68 | 0 | 82.62 | 105.0 | ready | +| base | 8,192 | 16384 | 261.3 | 261.3, 261.3 | 31.35 | 31.35 | 0 | 78.39 | 77.56 | ready | +| new | 32,768 | 40960 | 513.5 | 512.6, 514.5 | 63.81 | 63.81 | 0 | 83.33 | 105.0 | ready | +| base | 32,768 | 40960 | 260.4 | 260.1, 260.6 | 125.9 | 125.9 | 0 | 79.09 | 79.81 | ready | +| new | 65,536 | 73728 | 496.7 | 497.2, 496.2 | 132.0 | 132.0 | 0 | 84.27 | 104.3 | ready | +| base | 65,536 | 73728 | 259.3 | 259.3, 259.3 | 252.7 | 252.7 | 0 | 80.03 | 81.64 | ready | +| new | 131,072 | 139264 | 471.6 | 471.7, 471.5 | 277.9 | 277.9 | 0 | 86.14 | 103.8 | ready | +| base | 131,072 | 139264 | 258.0 | 258.1, 257.8 | 508.1 | 508.1 | 0 | 81.91 | 83.66 | ready | + +new / base, prefill tok/s +| prompt tokens | new | base | ratio | +|---|---|---|---| +| 2,048 | 673.7 | 293.2 | 2.298 | +| 8,192 | 558.2 | 261.3 | 2.136 | +| 32,768 | 513.5 | 260.4 | 1.972 | +| 65,536 | 496.7 | 259.3 | 1.915 | +| 131,072 | 471.6 | 258.0 | 1.828 | + +## Decode, one stream (bench_openai.py, 256 tokens, greedy, drafts on) +| arm | prompt | decode tok/s (median) | per round | TTFT (s) | wall (s, derived) | spec-decode hit rate | GTT+VRAM peak (GiB) | RSS peak (GiB) | +|---|---|---|---|---|---|---|---|---| + +## Prefill, serial decode and Default MTP decode (one public-code prompt, greedy, cache off, drafts as stated) +| arm | decode | output tokens | decode tok/s (median) | every rep | TTFT (s) | wall (s) | spec-decode hit rate | GTT+VRAM peak over idle (GiB) | RSS peak (GiB) | cached tokens | +|---|---|---|---|---|---|---|---|---|---|---| + +| arm | prefill tok/s (cold, 16K) | MTP token hash == serial's | +|---|---|---| +| new | - | | +| base | - | | + +## Concurrent (bench_concurrent.py --levels 1,4 --alone --serial) +| arm | prompt | streams | aggregate tok/s | per-stream tok/s | concurrent==alone (eq/ne/failed) | alone==draft:false (eq/ne/failed) | failed requests | +|---|---|---|---|---|---|---|---| +== 2026-10-31T10:46:09Z perf done; next: finalize.sh diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/session-03.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/session-03.log new file mode 100644 index 0000000000..ce3e77bb5e --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/session-03.log @@ -0,0 +1,65 @@ +pgrep: pattern that searches for process name longer than 15 characters will result in zero matches +Try `pgrep -f' option to match against the complete command line. +pgrep: pattern that searches for process name longer than 15 characters will result in zero matches +Try `pgrep -f' option to match against the complete command line. +pgrep: pattern that searches for process name longer than 15 characters will result in zero matches +Try `pgrep -f' option to match against the complete command line. +pgrep: pattern that searches for process name longer than 15 characters will result in zero matches +Try `pgrep -f' option to match against the complete command line. +pgrep: pattern that searches for process name longer than 15 characters will result in zero matches +Try `pgrep -f' option to match against the complete command line. +== 2026-10-31T12:47:29Z server cold-new-261888-r1: context 262144, parallel 1, prompt cache 0 GiB +== 2026-10-31T12:48:08Z step cold-new-261888-r1 +== 2026-10-31T12:58:08Z step cold-new-261888-r1 rc=0 +== 2026-10-31T12:58:10Z server cold-base-261888-r1: context 262144, parallel 1, prompt cache 0 GiB +== 2026-10-31T12:58:23Z step cold-base-261888-r1 +== 2026-10-31T13:16:14Z step cold-base-261888-r1 rc=0 +== 2026-10-31T13:16:17Z server cold-new-261888-r2: context 262144, parallel 1, prompt cache 0 GiB +== 2026-10-31T13:16:45Z step cold-new-261888-r2 +== 2026-10-31T13:26:44Z step cold-new-261888-r2 rc=0 +== 2026-10-31T13:26:47Z server cold-base-261888-r2: context 262144, parallel 1, prompt cache 0 GiB +== 2026-10-31T13:27:00Z step cold-base-261888-r2 +== 2026-10-31T13:44:54Z step cold-base-261888-r2 rc=0 +## Cold prefill (max_tokens 1, prompt cache off, fresh server per run) +| arm | prompt tokens | context | prefill tok/s (median) | per round | TTFT (s) | wall (s) | cached tokens | GTT+VRAM peak over idle (GiB) | RSS peak (GiB) | server | +|---|---|---|---|---|---|---|---|---|---|---| +| new | 2,048 | 10240 | 673.7 | 681.4, 666.0 | 3.040 | 3.041 | 0 | 82.45 | 102.9 | ready | +| base | 2,048 | 10240 | 293.2 | 290.0, 296.4 | 6.986 | 6.996 | 0 | 78.21 | 76.81 | ready | +| new | 8,192 | 16384 | 558.2 | 559.2, 557.2 | 14.68 | 14.68 | 0 | 82.62 | 105.0 | ready | +| base | 8,192 | 16384 | 261.3 | 261.3, 261.3 | 31.35 | 31.35 | 0 | 78.39 | 77.56 | ready | +| new | 32,768 | 40960 | 513.5 | 512.6, 514.5 | 63.81 | 63.81 | 0 | 83.33 | 105.0 | ready | +| base | 32,768 | 40960 | 260.4 | 260.1, 260.6 | 125.9 | 125.9 | 0 | 79.09 | 79.81 | ready | +| new | 65,536 | 73728 | 496.7 | 497.2, 496.2 | 132.0 | 132.0 | 0 | 84.27 | 104.3 | ready | +| base | 65,536 | 73728 | 259.3 | 259.3, 259.3 | 252.7 | 252.7 | 0 | 80.03 | 81.64 | ready | +| new | 131,072 | 139264 | 471.6 | 471.7, 471.5 | 277.9 | 277.9 | 0 | 86.14 | 103.8 | ready | +| base | 131,072 | 139264 | 258.0 | 258.1, 257.8 | 508.1 | 508.1 | 0 | 81.91 | 83.66 | ready | +| new | 261,888 | 262144 | 437.3 | 437.5, 437.1 | 598.8 | 598.8 | 0 | 89.68 | 103.9 | ready | +| base | 261,888 | 262144 | 244.8 | 245.1, 244.5 | 1,070 | 1,070 | 0 | 85.45 | 86.69 | ready | + +new / base, prefill tok/s +| prompt tokens | new | base | ratio | +|---|---|---|---| +| 2,048 | 673.7 | 293.2 | 2.298 | +| 8,192 | 558.2 | 261.3 | 2.136 | +| 32,768 | 513.5 | 260.4 | 1.972 | +| 65,536 | 496.7 | 259.3 | 1.915 | +| 131,072 | 471.6 | 258.0 | 1.828 | +| 261,888 | 437.3 | 244.8 | 1.786 | + +## Decode, one stream (bench_openai.py, 256 tokens, greedy, drafts on) +| arm | prompt | decode tok/s (median) | per round | TTFT (s) | wall (s, derived) | spec-decode hit rate | GTT+VRAM peak (GiB) | RSS peak (GiB) | +|---|---|---|---|---|---|---|---|---| + +## Prefill, serial decode and Default MTP decode (one public-code prompt, greedy, cache off, drafts as stated) +| arm | decode | output tokens | decode tok/s (median) | every rep | TTFT (s) | wall (s) | spec-decode hit rate | GTT+VRAM peak over idle (GiB) | RSS peak (GiB) | cached tokens | +|---|---|---|---|---|---|---|---|---|---|---| + +| arm | prefill tok/s (cold, 16K) | MTP token hash == serial's | +|---|---|---| +| new | - | | +| base | - | | + +## Concurrent (bench_concurrent.py --levels 1,4 --alone --serial) +| arm | prompt | streams | aggregate tok/s | per-stream tok/s | concurrent==alone (eq/ne/failed) | alone==draft:false (eq/ne/failed) | failed requests | +|---|---|---|---|---|---|---|---| +== 2026-10-31T13:44:56Z perf done; next: finalize.sh diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/session-04.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/session-04.log new file mode 100644 index 0000000000..5066139e6b --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/session-04.log @@ -0,0 +1,85 @@ +pgrep: pattern that searches for process name longer than 15 characters will result in zero matches +Try `pgrep -f' option to match against the complete command line. +pgrep: pattern that searches for process name longer than 15 characters will result in zero matches +Try `pgrep -f' option to match against the complete command line. +pgrep: pattern that searches for process name longer than 15 characters will result in zero matches +Try `pgrep -f' option to match against the complete command line. +pgrep: pattern that searches for process name longer than 15 characters will result in zero matches +Try `pgrep -f' option to match against the complete command line. +pgrep: pattern that searches for process name longer than 15 characters will result in zero matches +Try `pgrep -f' option to match against the complete command line. +== 2026-10-31T13:53:58Z server decode-new-r1: context 16384, parallel 4, prompt cache 0 GiB +== 2026-10-31T13:54:28Z step openai-new-r1 +== 2026-10-31T13:55:03Z step openai-new-r1 rc=0 +== 2026-10-31T13:55:03Z step concurrent-new-r1 +== 2026-10-31T13:56:49Z step concurrent-new-r1 rc=0 +== 2026-10-31T13:56:52Z server decode-base-r1: context 16384, parallel 4, prompt cache 0 GiB +== 2026-10-31T13:57:05Z step openai-base-r1 +== 2026-10-31T13:57:52Z step openai-base-r1 rc=0 +== 2026-10-31T13:57:52Z step concurrent-base-r1 +== 2026-10-31T14:00:11Z step concurrent-base-r1 rc=0 +== 2026-10-31T14:00:12Z server decode-new-r2: context 16384, parallel 4, prompt cache 0 GiB +== 2026-10-31T14:00:39Z step openai-new-r2 +== 2026-10-31T14:01:15Z step openai-new-r2 rc=0 +== 2026-10-31T14:01:15Z step concurrent-new-r2 +== 2026-10-31T14:03:01Z step concurrent-new-r2 rc=0 +== 2026-10-31T14:03:04Z server decode-base-r2: context 16384, parallel 4, prompt cache 0 GiB +== 2026-10-31T14:03:21Z step openai-base-r2 +== 2026-10-31T14:04:09Z step openai-base-r2 rc=0 +== 2026-10-31T14:04:09Z step concurrent-base-r2 +== 2026-10-31T14:06:29Z step concurrent-base-r2 rc=0 +## Cold prefill (max_tokens 1, prompt cache off, fresh server per run) +| arm | prompt tokens | context | prefill tok/s (median) | per round | TTFT (s) | wall (s) | cached tokens | GTT+VRAM peak over idle (GiB) | RSS peak (GiB) | server | +|---|---|---|---|---|---|---|---|---|---|---| +| new | 2,048 | 10240 | 673.7 | 681.4, 666.0 | 3.040 | 3.041 | 0 | 82.45 | 102.9 | ready | +| base | 2,048 | 10240 | 293.2 | 290.0, 296.4 | 6.986 | 6.996 | 0 | 78.21 | 76.81 | ready | +| new | 8,192 | 16384 | 558.2 | 559.2, 557.2 | 14.68 | 14.68 | 0 | 82.62 | 105.0 | ready | +| base | 8,192 | 16384 | 261.3 | 261.3, 261.3 | 31.35 | 31.35 | 0 | 78.39 | 77.56 | ready | +| new | 32,768 | 40960 | 513.5 | 512.6, 514.5 | 63.81 | 63.81 | 0 | 83.33 | 105.0 | ready | +| base | 32,768 | 40960 | 260.4 | 260.1, 260.6 | 125.9 | 125.9 | 0 | 79.09 | 79.81 | ready | +| new | 65,536 | 73728 | 496.7 | 497.2, 496.2 | 132.0 | 132.0 | 0 | 84.27 | 104.3 | ready | +| base | 65,536 | 73728 | 259.3 | 259.3, 259.3 | 252.7 | 252.7 | 0 | 80.03 | 81.64 | ready | +| new | 131,072 | 139264 | 471.6 | 471.7, 471.5 | 277.9 | 277.9 | 0 | 86.14 | 103.8 | ready | +| base | 131,072 | 139264 | 258.0 | 258.1, 257.8 | 508.1 | 508.1 | 0 | 81.91 | 83.66 | ready | +| new | 261,888 | 262144 | 437.3 | 437.5, 437.1 | 598.8 | 598.8 | 0 | 89.68 | 103.9 | ready | +| base | 261,888 | 262144 | 244.8 | 245.1, 244.5 | 1,070 | 1,070 | 0 | 85.45 | 86.69 | ready | + +new / base, prefill tok/s +| prompt tokens | new | base | ratio | +|---|---|---|---| +| 2,048 | 673.7 | 293.2 | 2.298 | +| 8,192 | 558.2 | 261.3 | 2.136 | +| 32,768 | 513.5 | 260.4 | 1.972 | +| 65,536 | 496.7 | 259.3 | 1.915 | +| 131,072 | 471.6 | 258.0 | 1.828 | +| 261,888 | 437.3 | 244.8 | 1.786 | + +## Decode, one stream (bench_openai.py, 256 tokens, greedy, drafts on) +| arm | prompt | decode tok/s (median) | per round | TTFT (s) | wall (s, derived) | spec-decode hit rate | GTT+VRAM peak (GiB) | RSS peak (GiB) | +|---|---|---|---|---|---|---|---|---| +| new | fibonacci-raw | 69.04 | 69.15, 68.92 | 0.09908 | 3.793 | 76.2 % | 84.38 | 104.7 | +| new | gpu-chat-no-think | 55.92 | 55.44, 56.39 | 0.1684 | 4.729 | 76.2 % | 84.38 | 104.7 | +| base | fibonacci-raw | 50.80 | 50.94, 50.66 | 0.1237 | 5.143 | 70.9 % | 81.33 | 76.80 | +| base | gpu-chat-no-think | 45.47 | 46.23, 44.70 | 0.2396 | 5.848 | 70.9 % | 81.33 | 76.80 | + +## Prefill, serial decode and Default MTP decode (one public-code prompt, greedy, cache off, drafts as stated) +| arm | decode | output tokens | decode tok/s (median) | every rep | TTFT (s) | wall (s) | spec-decode hit rate | GTT+VRAM peak over idle (GiB) | RSS peak (GiB) | cached tokens | +|---|---|---|---|---|---|---|---|---|---|---| + +| arm | prefill tok/s (cold, 16K) | MTP token hash == serial's | +|---|---|---| +| new | - | | +| base | - | | + +## Concurrent (bench_concurrent.py --levels 1,4 --alone --serial) +| arm | prompt | streams | aggregate tok/s | per-stream tok/s | concurrent==alone (eq/ne/failed) | alone==draft:false (eq/ne/failed) | failed requests | +|---|---|---|---|---|---|---|---| +| new | chat | 1 | 57.20 | 57.20 | 6/0/0 | 2/0/0 | 0 | +| new | chat | 4 | 99.75 | 25.85 | 24/0/0 | 2/0/0 | 0 | +| new | code | 1 | 68.45 | 68.45 | 6/0/0 | 2/0/0 | 0 | +| new | code | 4 | 117.4 | 30.00 | 24/0/0 | 2/0/0 | 0 | +| base | chat | 1 | 45.30 | 45.30 | 6/0/0 | 2/0/0 | 0 | +| base | chat | 4 | 72.95 | 18.65 | 24/0/0 | 2/0/0 | 0 | +| base | code | 1 | 51.15 | 51.15 | 6/0/0 | 2/0/0 | 0 | +| base | code | 4 | 89.65 | 22.70 | 24/0/0 | 2/0/0 | 0 | +== 2026-10-31T14:06:30Z perf done; next: finalize.sh diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/session-05.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/session-05.log new file mode 100644 index 0000000000..56ee8028ae --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/session-05.log @@ -0,0 +1,97 @@ +pgrep: pattern that searches for process name longer than 15 characters will result in zero matches +Try `pgrep -f' option to match against the complete command line. +pgrep: pattern that searches for process name longer than 15 characters will result in zero matches +Try `pgrep -f' option to match against the complete command line. +pgrep: pattern that searches for process name longer than 15 characters will result in zero matches +Try `pgrep -f' option to match against the complete command line. +pgrep: pattern that searches for process name longer than 15 characters will result in zero matches +Try `pgrep -f' option to match against the complete command line. +pgrep: pattern that searches for process name longer than 15 characters will result in zero matches +Try `pgrep -f' option to match against the complete command line. +== 2026-10-31T14:23:14Z server d16k-serial-new-r1: context 19456, parallel 1, prompt cache 0 GiB --no-drafts +== 2026-10-31T14:23:53Z step d16k-serial-new-r1 +== 2026-10-31T14:29:16Z step d16k-serial-new-r1 rc=0 +== 2026-10-31T14:29:18Z server d16k-serial-base-r1: context 19456, parallel 1, prompt cache 0 GiB --no-drafts +== 2026-10-31T14:29:30Z step d16k-serial-base-r1 +== 2026-10-31T14:37:25Z step d16k-serial-base-r1 rc=0 +== 2026-10-31T14:37:26Z server d16k-drafts-new-r1: context 19456, parallel 1, prompt cache 0 GiB +== 2026-10-31T14:37:52Z step d16k-drafts-new-r1 +== 2026-10-31T14:42:46Z step d16k-drafts-new-r1 rc=0 +== 2026-10-31T14:42:49Z server d16k-drafts-base-r1: context 19456, parallel 1, prompt cache 0 GiB +== 2026-10-31T14:43:02Z step d16k-drafts-base-r1 +== 2026-10-31T14:50:28Z step d16k-drafts-base-r1 rc=0 +== 2026-10-31T14:50:29Z server d16k-serial-new-r2: context 19456, parallel 1, prompt cache 0 GiB --no-drafts +== 2026-10-31T14:50:56Z step d16k-serial-new-r2 +== 2026-10-31T14:56:20Z step d16k-serial-new-r2 rc=0 +== 2026-10-31T14:56:22Z server d16k-serial-base-r2: context 19456, parallel 1, prompt cache 0 GiB --no-drafts +== 2026-10-31T14:56:35Z step d16k-serial-base-r2 +== 2026-10-31T15:04:33Z step d16k-serial-base-r2 rc=0 +== 2026-10-31T15:04:36Z server d16k-drafts-new-r2: context 19456, parallel 1, prompt cache 0 GiB +== 2026-10-31T15:05:04Z step d16k-drafts-new-r2 +== 2026-10-31T15:09:59Z step d16k-drafts-new-r2 rc=0 +== 2026-10-31T15:10:00Z server d16k-drafts-base-r2: context 19456, parallel 1, prompt cache 0 GiB +== 2026-10-31T15:10:13Z step d16k-drafts-base-r2 +== 2026-10-31T15:17:41Z step d16k-drafts-base-r2 rc=0 +## Cold prefill (max_tokens 1, prompt cache off, fresh server per run) +| arm | prompt tokens | context | prefill tok/s (median) | per round | TTFT (s) | wall (s) | cached tokens | GTT+VRAM peak over idle (GiB) | RSS peak (GiB) | server | +|---|---|---|---|---|---|---|---|---|---|---| +| new | 2,048 | 10240 | 673.7 | 681.4, 666.0 | 3.040 | 3.041 | 0 | 82.45 | 102.9 | ready | +| base | 2,048 | 10240 | 293.2 | 290.0, 296.4 | 6.986 | 6.996 | 0 | 78.21 | 76.81 | ready | +| new | 8,192 | 16384 | 558.2 | 559.2, 557.2 | 14.68 | 14.68 | 0 | 82.62 | 105.0 | ready | +| base | 8,192 | 16384 | 261.3 | 261.3, 261.3 | 31.35 | 31.35 | 0 | 78.39 | 77.56 | ready | +| new | 32,768 | 40960 | 513.5 | 512.6, 514.5 | 63.81 | 63.81 | 0 | 83.33 | 105.0 | ready | +| base | 32,768 | 40960 | 260.4 | 260.1, 260.6 | 125.9 | 125.9 | 0 | 79.09 | 79.81 | ready | +| new | 65,536 | 73728 | 496.7 | 497.2, 496.2 | 132.0 | 132.0 | 0 | 84.27 | 104.3 | ready | +| base | 65,536 | 73728 | 259.3 | 259.3, 259.3 | 252.7 | 252.7 | 0 | 80.03 | 81.64 | ready | +| new | 131,072 | 139264 | 471.6 | 471.7, 471.5 | 277.9 | 277.9 | 0 | 86.14 | 103.8 | ready | +| base | 131,072 | 139264 | 258.0 | 258.1, 257.8 | 508.1 | 508.1 | 0 | 81.91 | 83.66 | ready | +| new | 261,888 | 262144 | 437.3 | 437.5, 437.1 | 598.8 | 598.8 | 0 | 89.68 | 103.9 | ready | +| base | 261,888 | 262144 | 244.8 | 245.1, 244.5 | 1,070 | 1,070 | 0 | 85.45 | 86.69 | ready | + +new / base, prefill tok/s +| prompt tokens | new | base | ratio | +|---|---|---|---| +| 2,048 | 673.7 | 293.2 | 2.298 | +| 8,192 | 558.2 | 261.3 | 2.136 | +| 32,768 | 513.5 | 260.4 | 1.972 | +| 65,536 | 496.7 | 259.3 | 1.915 | +| 131,072 | 471.6 | 258.0 | 1.828 | +| 261,888 | 437.3 | 244.8 | 1.786 | + +## Decode, one stream (bench_openai.py, 256 tokens, greedy, drafts on) +| arm | prompt | decode tok/s (median) | per round | TTFT (s) | wall (s, derived) | spec-decode hit rate | GTT+VRAM peak (GiB) | RSS peak (GiB) | +|---|---|---|---|---|---|---|---|---| +| new | fibonacci-raw | 69.04 | 69.15, 68.92 | 0.09908 | 3.793 | 76.2 % | 84.38 | 104.7 | +| new | gpu-chat-no-think | 55.92 | 55.44, 56.39 | 0.1684 | 4.729 | 76.2 % | 84.38 | 104.7 | +| base | fibonacci-raw | 50.80 | 50.94, 50.66 | 0.1237 | 5.143 | 70.9 % | 81.33 | 76.80 | +| base | gpu-chat-no-think | 45.47 | 46.23, 44.70 | 0.2396 | 5.848 | 70.9 % | 81.33 | 76.80 | + +## Prefill, serial decode and Default MTP decode (one public-code prompt, greedy, cache off, drafts as stated) +| arm | decode | output tokens | decode tok/s (median) | every rep | TTFT (s) | wall (s) | spec-decode hit rate | GTT+VRAM peak over idle (GiB) | RSS peak (GiB) | cached tokens | +|---|---|---|---|---|---|---|---|---|---|---| +| base | Default MTP | 256 | 40.27 | 34.91, 40.64, 41.07, 34.86, 41.02, 39.91 | 46.48 | 52.84 | 68.1 % | 78.48 | 78.67 | 0 | +| base | Default MTP | 1024 | 38.26 | 35.44, 38.42, 38.33, 34.39, 38.77, 38.19 | 46.54 | 73.32 | 68.1 % | 78.48 | 78.67 | 0 | +| new | Default MTP | 256 | 51.86 | 52.11, 51.89, 52.71, 51.83, 51.75, 50.15 | 30.91 | 35.86 | 61.8 % | 82.72 | 103.8 | 0 | +| new | Default MTP | 1024 | 49.05 | 49.44, 49.46, 49.22, 48.11, 48.03, 48.88 | 30.94 | 51.86 | 61.8 % | 82.72 | 103.8 | 0 | +| base | serial (--no-drafts) | 256 | 29.64 | 27.14, 30.41, 29.92, 26.43, 29.41, 29.86 | 46.38 | 55.19 | - | 78.48 | 78.63 | 0 | +| base | serial (--no-drafts) | 1024 | 29.99 | 27.83, 30.16, 30.29, 26.94, 29.99, 29.99 | 46.55 | 80.70 | - | 78.48 | 78.63 | 0 | +| new | serial (--no-drafts) | 256 | 35.55 | 35.72, 35.58, 35.53, 35.48, 35.45, 35.86 | 30.71 | 37.86 | - | 82.68 | 104.9 | 0 | +| new | serial (--no-drafts) | 1024 | 35.71 | 35.75, 35.95, 35.66, 35.48, 35.77, 35.67 | 30.75 | 59.39 | - | 82.68 | 104.9 | 0 | + +| arm | prefill tok/s (cold, 16K) | serial decode tok/s (256) | serial decode tok/s (1024) | Default MTP decode tok/s (256) | Default MTP decode tok/s (1024) | MTP token hash == serial's | +|---|---|---|---|---|---|---| +| new | 533.5 | 35.55 | 35.71 | 51.86 | 49.05 | yes/yes | +| base | 353.3 | 29.64 | 29.99 | 40.27 | 38.26 | yes/yes | + +## Concurrent (bench_concurrent.py --levels 1,4 --alone --serial) +| arm | prompt | streams | aggregate tok/s | per-stream tok/s | concurrent==alone (eq/ne/failed) | alone==draft:false (eq/ne/failed) | failed requests | +|---|---|---|---|---|---|---|---| +| new | chat | 1 | 57.20 | 57.20 | 6/0/0 | 2/0/0 | 0 | +| new | chat | 4 | 99.75 | 25.85 | 24/0/0 | 2/0/0 | 0 | +| new | code | 1 | 68.45 | 68.45 | 6/0/0 | 2/0/0 | 0 | +| new | code | 4 | 117.4 | 30.00 | 24/0/0 | 2/0/0 | 0 | +| base | chat | 1 | 45.30 | 45.30 | 6/0/0 | 2/0/0 | 0 | +| base | chat | 4 | 72.95 | 18.65 | 24/0/0 | 2/0/0 | 0 | +| base | code | 1 | 51.15 | 51.15 | 6/0/0 | 2/0/0 | 0 | +| base | code | 4 | 89.65 | 22.70 | 24/0/0 | 2/0/0 | 0 | +== 2026-10-31T15:17:42Z perf done; next: finalize.sh diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/session-06.log b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/session-06.log new file mode 100644 index 0000000000..c064f7302e --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/logs/session-06.log @@ -0,0 +1,66 @@ +pgrep: pattern that searches for process name longer than 15 characters will result in zero matches +Try `pgrep -f' option to match against the complete command line. +pgrep: pattern that searches for process name longer than 15 characters will result in zero matches +Try `pgrep -f' option to match against the complete command line. +pgrep: pattern that searches for process name longer than 15 characters will result in zero matches +Try `pgrep -f' option to match against the complete command line. +pgrep: pattern that searches for process name longer than 15 characters will result in zero matches +Try `pgrep -f' option to match against the complete command line. +pgrep: pattern that searches for process name longer than 15 characters will result in zero matches +Try `pgrep -f' option to match against the complete command line. +== 2026-10-31T17:40:29Z server mem-new-default-r1: context 20480, parallel 1, prompt cache 0 GiB +== 2026-10-31T17:41:07Z step mem-new-default-r1 +== 2026-10-31T17:41:38Z step mem-new-default-r1 rc=0 +== 2026-10-31T17:41:40Z server mem-new-step1024-r1: context 20480, parallel 1, prompt cache 0 GiB --policy prefill_step=1024 +== 2026-10-31T17:42:10Z step mem-new-step1024-r1 +== 2026-10-31T17:42:45Z step mem-new-step1024-r1 rc=0 +== 2026-10-31T17:42:47Z server mem-new-step20480-r1: context 20480, parallel 1, prompt cache 0 GiB --policy prefill_step=20480 +== 2026-10-31T17:43:19Z step mem-new-step20480-r1 +== 2026-10-31T17:43:49Z step mem-new-step20480-r1 rc=0 +== 2026-10-31T17:43:51Z server mem-new-mapped-cold-r1: context 20480, parallel 1, prompt cache 0 GiB --policy rows=mapped +== 2026-10-31T17:44:10Z step mem-new-mapped-cold-r1 +== 2026-10-31T17:44:58Z step mem-new-mapped-cold-r1 rc=0 +== 2026-10-31T17:45:01Z server mem-new-mapped-warm-r1: context 20480, parallel 1, prompt cache 0 GiB --policy rows=mapped +== 2026-10-31T17:45:15Z step mem-new-mapped-warm-r1 +== 2026-10-31T17:45:46Z step mem-new-mapped-warm-r1 rc=0 +== 2026-10-31T17:45:48Z server mem-new-step1024-mapped-r1: context 20480, parallel 1, prompt cache 0 GiB --policy prefill_step=1024,rows=mapped +== 2026-10-31T17:46:02Z step mem-new-step1024-mapped-r1 +== 2026-10-31T17:46:37Z step mem-new-step1024-mapped-r1 rc=0 +== 2026-10-31T17:46:38Z server mem-base-r1: context 20480, parallel 1, prompt cache 0 GiB +== 2026-10-31T17:46:49Z step mem-base-r1 +== 2026-10-31T17:47:36Z step mem-base-r1 rc=0 +== 2026-10-31T17:47:39Z server mem-new-default-r2: context 20480, parallel 1, prompt cache 0 GiB +== 2026-10-31T17:48:08Z step mem-new-default-r2 +== 2026-10-31T17:48:39Z step mem-new-default-r2 rc=0 +== 2026-10-31T17:48:42Z server mem-new-step1024-r2: context 20480, parallel 1, prompt cache 0 GiB --policy prefill_step=1024 +== 2026-10-31T17:49:14Z step mem-new-step1024-r2 +== 2026-10-31T17:49:48Z step mem-new-step1024-r2 rc=0 +== 2026-10-31T17:49:51Z server mem-new-step20480-r2: context 20480, parallel 1, prompt cache 0 GiB --policy prefill_step=20480 +== 2026-10-31T17:50:25Z step mem-new-step20480-r2 +== 2026-10-31T17:50:55Z step mem-new-step20480-r2 rc=0 +== 2026-10-31T17:50:57Z server mem-new-mapped-cold-r2: context 20480, parallel 1, prompt cache 0 GiB --policy rows=mapped +== 2026-10-31T17:51:17Z step mem-new-mapped-cold-r2 +== 2026-10-31T17:52:04Z step mem-new-mapped-cold-r2 rc=0 +== 2026-10-31T17:52:07Z server mem-new-mapped-warm-r2: context 20480, parallel 1, prompt cache 0 GiB --policy rows=mapped +== 2026-10-31T17:52:22Z step mem-new-mapped-warm-r2 +== 2026-10-31T17:52:54Z step mem-new-mapped-warm-r2 rc=0 +== 2026-10-31T17:52:55Z server mem-new-step1024-mapped-r2: context 20480, parallel 1, prompt cache 0 GiB --policy prefill_step=1024,rows=mapped +== 2026-10-31T17:53:09Z step mem-new-step1024-mapped-r2 +== 2026-10-31T17:53:44Z step mem-new-step1024-mapped-r2 rc=0 +== 2026-10-31T17:53:45Z server mem-base-r2: context 20480, parallel 1, prompt cache 0 GiB +== 2026-10-31T17:53:56Z step mem-base-r2 +== 2026-10-31T17:54:43Z step mem-base-r2 rc=0 +mem-base-r1 | 76.58 GiB on the device, 1 stream of 20544 positions, 1.14 GiB each; prompts in 1024-row chunks | 84292440064 84332322816 | ttft 46.471027742984006 +mem-base-r2 | 76.58 GiB on the device, 1 stream of 20544 positions, 1.14 GiB each; prompts in 1024-row chunks | 84292440064 84356018176 | ttft 46.46257960499497 +mem-new-default-r1 | 81.82 GiB on the device, 1 stream of 20544 positions, 0.74 GiB each; prompts in 4096-row chunks | 88832692224 112119701504 | ttft 30.735502470983192 +mem-new-default-r2 | 81.82 GiB on the device, 1 stream of 20544 positions, 0.74 GiB each; prompts in 4096-row chunks | 88832692224 112311951360 | ttft 30.823120265005855 +mem-new-mapped-cold-r1 | 81.82 GiB on the device, 1 stream of 20544 positions, 0.74 GiB each; prompts in 4096-row chunks | 88832692224 84365791232 | ttft 46.297117879992584 +mem-new-mapped-cold-r2 | 81.82 GiB on the device, 1 stream of 20544 positions, 0.74 GiB each; prompts in 4096-row chunks | 88832692224 84386779136 | ttft 46.203377994999755 +mem-new-mapped-warm-r1 | 81.82 GiB on the device, 1 stream of 20544 positions, 0.74 GiB each; prompts in 4096-row chunks | 88832692224 84412772352 | ttft 30.92277264900622 +mem-new-mapped-warm-r2 | 81.82 GiB on the device, 1 stream of 20544 positions, 0.74 GiB each; prompts in 4096-row chunks | 88832692224 84432424960 | ttft 30.93969676399138 +mem-new-step1024-mapped-r1 | 77.36 GiB on the device, 1 stream of 20544 positions, 0.74 GiB each; prompts in 1024-row chunks | 84038602752 84413345792 | ttft 34.125737205991754 +mem-new-step1024-mapped-r2 | 77.36 GiB on the device, 1 stream of 20544 positions, 0.74 GiB each; prompts in 1024-row chunks | 84038602752 84431228928 | ttft 34.12385592798819 +mem-new-step1024-r1 | 77.36 GiB on the device, 1 stream of 20544 positions, 0.74 GiB each; prompts in 1024-row chunks | 84038602752 110197727232 | ttft 33.89995566298603 +mem-new-step1024-r2 | 77.36 GiB on the device, 1 stream of 20544 positions, 0.74 GiB each; prompts in 1024-row chunks | 84038602752 111990099968 | ttft 33.83586324600037 +mem-new-step20480-r1 | 105.63 GiB on the device, 1 stream of 20544 positions, 0.74 GiB each; prompts in 20480-row chunks | 114392780800 112203182080 | ttft 29.693808502983302 +mem-new-step20480-r2 | 105.63 GiB on the device, 1 stream of 20544 positions, 0.74 GiB each; prompts in 20480-row chunks | 114392780800 112598904832 | ttft 29.839465764991473 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory-ab/mem-base-r1.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory-ab/mem-base-r1.json new file mode 100644 index 0000000000..df96b3f30a --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory-ab/mem-base-r1.json @@ -0,0 +1,19 @@ +{ + "expected_prompt_tokens": 16384, + "prompt_tokens_match": true, + "request_sha256": "c077a8ae348c4bbd060be8dab4a5a6b8d24e0285c0b92d406b83c112be538c5d", + "request_matches_file": true, + "prompt_tokens": 16384, + "cached_tokens": 0, + "tokens": 1, + "cache_state": "cold", + "complete": true, + "error": null, + "ttft_s": 46.471027742984006, + "prefill_tps": 352.5637541440771, + "elapsed_s": 46.47119862298132, + "token_sha": "239d455de119", + "token_sha256": "239d455de119eea379ea247e8b8dcc86f7088cac40ad26df3dda79f9cdfee42c", + "output_sha256": "bfbba6a59afa0e6fe98879f7f1c6ae73ed2bc2104e4c0aeb99d4e28864a1a28d", + "chunk_gaps_ms": null +} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory-ab/mem-base-r2.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory-ab/mem-base-r2.json new file mode 100644 index 0000000000..d72d3e37bb --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory-ab/mem-base-r2.json @@ -0,0 +1,19 @@ +{ + "expected_prompt_tokens": 16384, + "prompt_tokens_match": true, + "request_sha256": "c077a8ae348c4bbd060be8dab4a5a6b8d24e0285c0b92d406b83c112be538c5d", + "request_matches_file": true, + "prompt_tokens": 16384, + "cached_tokens": 0, + "tokens": 1, + "cache_state": "cold", + "complete": true, + "error": null, + "ttft_s": 46.46257960499497, + "prefill_tps": 352.6278596515686, + "elapsed_s": 46.46293523098575, + "token_sha": "239d455de119", + "token_sha256": "239d455de119eea379ea247e8b8dcc86f7088cac40ad26df3dda79f9cdfee42c", + "output_sha256": "bfbba6a59afa0e6fe98879f7f1c6ae73ed2bc2104e4c0aeb99d4e28864a1a28d", + "chunk_gaps_ms": null +} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory-ab/mem-new-default-r1.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory-ab/mem-new-default-r1.json new file mode 100644 index 0000000000..34d8fbdf0c --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory-ab/mem-new-default-r1.json @@ -0,0 +1,19 @@ +{ + "expected_prompt_tokens": 16384, + "prompt_tokens_match": true, + "request_sha256": "c077a8ae348c4bbd060be8dab4a5a6b8d24e0285c0b92d406b83c112be538c5d", + "request_matches_file": true, + "prompt_tokens": 16384, + "cached_tokens": 0, + "tokens": 1, + "cache_state": "cold", + "complete": true, + "error": null, + "ttft_s": 30.735502470983192, + "prefill_tps": 533.064328961852, + "elapsed_s": 30.735611274983967, + "token_sha": "239d455de119", + "token_sha256": "239d455de119eea379ea247e8b8dcc86f7088cac40ad26df3dda79f9cdfee42c", + "output_sha256": "bfbba6a59afa0e6fe98879f7f1c6ae73ed2bc2104e4c0aeb99d4e28864a1a28d", + "chunk_gaps_ms": null +} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory-ab/mem-new-default-r2.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory-ab/mem-new-default-r2.json new file mode 100644 index 0000000000..508a22ded4 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory-ab/mem-new-default-r2.json @@ -0,0 +1,19 @@ +{ + "expected_prompt_tokens": 16384, + "prompt_tokens_match": true, + "request_sha256": "c077a8ae348c4bbd060be8dab4a5a6b8d24e0285c0b92d406b83c112be538c5d", + "request_matches_file": true, + "prompt_tokens": 16384, + "cached_tokens": 0, + "tokens": 1, + "cache_state": "cold", + "complete": true, + "error": null, + "ttft_s": 30.823120265005855, + "prefill_tps": 531.5490404325192, + "elapsed_s": 30.823257883021142, + "token_sha": "239d455de119", + "token_sha256": "239d455de119eea379ea247e8b8dcc86f7088cac40ad26df3dda79f9cdfee42c", + "output_sha256": "bfbba6a59afa0e6fe98879f7f1c6ae73ed2bc2104e4c0aeb99d4e28864a1a28d", + "chunk_gaps_ms": null +} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory-ab/mem-new-mapped-cold-r1.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory-ab/mem-new-mapped-cold-r1.json new file mode 100644 index 0000000000..5c9764acdc --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory-ab/mem-new-mapped-cold-r1.json @@ -0,0 +1,19 @@ +{ + "expected_prompt_tokens": 16384, + "prompt_tokens_match": true, + "request_sha256": "c077a8ae348c4bbd060be8dab4a5a6b8d24e0285c0b92d406b83c112be538c5d", + "request_matches_file": true, + "prompt_tokens": 16384, + "cached_tokens": 0, + "tokens": 1, + "cache_state": "cold", + "complete": true, + "error": null, + "ttft_s": 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"complete": true, + "error": null, + "ttft_s": 46.203377994999755, + "prefill_tps": 354.6061069771374, + "elapsed_s": 46.20349165800144, + "token_sha": "239d455de119", + "token_sha256": "239d455de119eea379ea247e8b8dcc86f7088cac40ad26df3dda79f9cdfee42c", + "output_sha256": "bfbba6a59afa0e6fe98879f7f1c6ae73ed2bc2104e4c0aeb99d4e28864a1a28d", + "chunk_gaps_ms": null +} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory-ab/mem-new-mapped-warm-r1.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory-ab/mem-new-mapped-warm-r1.json new file mode 100644 index 0000000000..7708085ce6 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory-ab/mem-new-mapped-warm-r1.json @@ -0,0 +1,19 @@ +{ + "expected_prompt_tokens": 16384, + "prompt_tokens_match": true, + "request_sha256": "c077a8ae348c4bbd060be8dab4a5a6b8d24e0285c0b92d406b83c112be538c5d", + "request_matches_file": true, + "prompt_tokens": 16384, + "cached_tokens": 0, + 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b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory-ab/mem-new-step1024-r2.json @@ -0,0 +1,19 @@ +{ + "expected_prompt_tokens": 16384, + "prompt_tokens_match": true, + "request_sha256": "c077a8ae348c4bbd060be8dab4a5a6b8d24e0285c0b92d406b83c112be538c5d", + "request_matches_file": true, + "prompt_tokens": 16384, + "cached_tokens": 0, + "tokens": 1, + "cache_state": "cold", + "complete": true, + "error": null, + "ttft_s": 33.83586324600037, + "prefill_tps": 484.2199497285384, + "elapsed_s": 33.835985956015065, + "token_sha": "239d455de119", + "token_sha256": "239d455de119eea379ea247e8b8dcc86f7088cac40ad26df3dda79f9cdfee42c", + "output_sha256": "bfbba6a59afa0e6fe98879f7f1c6ae73ed2bc2104e4c0aeb99d4e28864a1a28d", + "chunk_gaps_ms": null +} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory-ab/mem-new-step20480-r1.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory-ab/mem-new-step20480-r1.json new file mode 100644 index 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b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory-ab/mem-new-step20480-r2.json new file mode 100644 index 0000000000..f68f532a08 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory-ab/mem-new-step20480-r2.json @@ -0,0 +1,19 @@ +{ + "expected_prompt_tokens": 16384, + "prompt_tokens_match": true, + "request_sha256": "c077a8ae348c4bbd060be8dab4a5a6b8d24e0285c0b92d406b83c112be538c5d", + "request_matches_file": true, + "prompt_tokens": 16384, + "cached_tokens": 0, + "tokens": 1, + "cache_state": "cold", + "complete": true, + "error": null, + "ttft_s": 29.839465764991473, + "prefill_tps": 549.0714923999137, + "elapsed_s": 29.839604995999252, + "token_sha": "239d455de119", + "token_sha256": "239d455de119eea379ea247e8b8dcc86f7088cac40ad26df3dda79f9cdfee42c", + "output_sha256": "bfbba6a59afa0e6fe98879f7f1c6ae73ed2bc2104e4c0aeb99d4e28864a1a28d", + "chunk_gaps_ms": null +} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory-ab/summary.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory-ab/summary.txt new file mode 100644 index 0000000000..53a614f583 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory-ab/summary.txt @@ -0,0 +1,14 @@ +mem-base-r1 | 76.58 GiB on the device, 1 stream of 20544 positions, 1.14 GiB each; prompts in 1024-row chunks | 84292440064 84332322816 | ttft 46.471027742984006 +mem-base-r2 | 76.58 GiB on the device, 1 stream of 20544 positions, 1.14 GiB each; prompts in 1024-row chunks | 84292440064 84356018176 | ttft 46.46257960499497 +mem-new-default-r1 | 81.82 GiB on the device, 1 stream of 20544 positions, 0.74 GiB each; prompts in 4096-row chunks | 88832692224 112119701504 | ttft 30.735502470983192 +mem-new-default-r2 | 81.82 GiB on the device, 1 stream of 20544 positions, 0.74 GiB each; prompts in 4096-row chunks | 88832692224 112311951360 | ttft 30.823120265005855 +mem-new-mapped-cold-r1 | 81.82 GiB on the device, 1 stream of 20544 positions, 0.74 GiB each; prompts in 4096-row chunks | 88832692224 84365791232 | ttft 46.297117879992584 +mem-new-mapped-cold-r2 | 81.82 GiB on the device, 1 stream of 20544 positions, 0.74 GiB each; prompts in 4096-row chunks | 88832692224 84386779136 | ttft 46.203377994999755 +mem-new-mapped-warm-r1 | 81.82 GiB on the device, 1 stream of 20544 positions, 0.74 GiB each; prompts in 4096-row chunks | 88832692224 84412772352 | ttft 30.92277264900622 +mem-new-mapped-warm-r2 | 81.82 GiB on the device, 1 stream of 20544 positions, 0.74 GiB each; prompts in 4096-row chunks | 88832692224 84432424960 | ttft 30.93969676399138 +mem-new-step1024-mapped-r1 | 77.36 GiB on the device, 1 stream of 20544 positions, 0.74 GiB each; prompts in 1024-row chunks | 84038602752 84413345792 | ttft 34.125737205991754 +mem-new-step1024-mapped-r2 | 77.36 GiB on the device, 1 stream of 20544 positions, 0.74 GiB each; prompts in 1024-row chunks | 84038602752 84431228928 | ttft 34.12385592798819 +mem-new-step1024-r1 | 77.36 GiB on the device, 1 stream of 20544 positions, 0.74 GiB each; prompts in 1024-row chunks | 84038602752 110197727232 | ttft 33.89995566298603 +mem-new-step1024-r2 | 77.36 GiB on the device, 1 stream of 20544 positions, 0.74 GiB each; prompts in 1024-row chunks | 84038602752 111990099968 | ttft 33.83586324600037 +mem-new-step20480-r1 | 105.63 GiB on the device, 1 stream of 20544 positions, 0.74 GiB each; prompts in 20480-row chunks | 114392780800 112203182080 | ttft 29.693808502983302 +mem-new-step20480-r2 | 105.63 GiB on the device, 1 stream of 20544 positions, 0.74 GiB each; prompts in 20480-row chunks | 114392780800 112598904832 | ttft 29.839465764991473 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-131072-r1-memory-endpoint.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-131072-r1-memory-endpoint.json new file mode 100644 index 0000000000..a8d3d2a2d7 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-131072-r1-memory-endpoint.json @@ -0,0 +1 @@ +{"schema_version": 1, "context_window": 139264, "context_fitted": false, "device": {"active_bytes": 86777744832, "cache_bytes": 0, "peak_bytes": 87088670148, "peak_scope": "since_start_or_health_reset"}} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-131072-r1-metrics.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-131072-r1-metrics.txt new file mode 100644 index 0000000000..e9fb332856 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-131072-r1-metrics.txt @@ -0,0 +1,220 @@ +# HELP tensorfold:requests_running Requests in prefill or decode. +# TYPE tensorfold:requests_running gauge +tensorfold:requests_running 0 +# HELP tensorfold:requests_waiting Requests queued or held until a lane is free. +# TYPE tensorfold:requests_waiting gauge +tensorfold:requests_waiting 0 +# HELP tensorfold:generation_tokens_running Generated tokens held by live streams. +# TYPE tensorfold:generation_tokens_running gauge +tensorfold:generation_tokens_running 0 +# HELP tensorfold:prompt_tokens_total Prompt tokens of finished requests. +# TYPE tensorfold:prompt_tokens_total counter +tensorfold:prompt_tokens_total 131328 +# HELP tensorfold:generation_tokens_total Generated tokens of finished requests. +# TYPE tensorfold:generation_tokens_total counter +tensorfold:generation_tokens_total 2 +# HELP tensorfold:kv_cache_usage_ratio Tokens in a stream cache divided by that stream's context window. +# TYPE tensorfold:kv_cache_usage_ratio gauge +tensorfold:kv_cache_usage_ratio{pool="0"} 0 +# HELP tensorfold:mtp_drafted_total Draft tokens verified on finished requests. +# TYPE tensorfold:mtp_drafted_total counter +tensorfold:mtp_drafted_total 0 +# HELP tensorfold:mtp_accepted_total Draft tokens kept on finished requests. +# TYPE tensorfold:mtp_accepted_total counter +tensorfold:mtp_accepted_total 0 +# HELP tensorfold:request_latency_seconds Seconds from arrival to the reply leaving. +# TYPE tensorfold:request_latency_seconds histogram +tensorfold:request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:request_latency_seconds_bucket{le="1"} 0 +tensorfold:request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:request_latency_seconds_bucket{le="5"} 1 +tensorfold:request_latency_seconds_bucket{le="10"} 1 +tensorfold:request_latency_seconds_bucket{le="30"} 1 +tensorfold:request_latency_seconds_bucket{le="60"} 1 +tensorfold:request_latency_seconds_bucket{le="120"} 1 +tensorfold:request_latency_seconds_bucket{le="300"} 1 +tensorfold:request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:request_latency_seconds_sum 509.899909 +tensorfold:request_latency_seconds_count 2 +# HELP tensorfold:time_to_first_token_seconds Seconds from arrival to the first generated token. +# TYPE tensorfold:time_to_first_token_seconds histogram +tensorfold:time_to_first_token_seconds_bucket{le="0.01"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.05"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.25"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.5"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="2.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="10"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="30"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="60"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="120"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="300"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="+Inf"} 2 +tensorfold:time_to_first_token_seconds_sum 509.899556 +tensorfold:time_to_first_token_seconds_count 2 +# HELP tensorfold:request_decode_seconds Seconds a finished request spent decoding. Its sum over generation_tokens_total is the decode rate. +# TYPE tensorfold:request_decode_seconds histogram +tensorfold:request_decode_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_seconds_bucket{le="1"} 2 +tensorfold:request_decode_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_seconds_bucket{le="5"} 2 +tensorfold:request_decode_seconds_bucket{le="10"} 2 +tensorfold:request_decode_seconds_bucket{le="30"} 2 +tensorfold:request_decode_seconds_bucket{le="60"} 2 +tensorfold:request_decode_seconds_bucket{le="120"} 2 +tensorfold:request_decode_seconds_bucket{le="300"} 2 +tensorfold:request_decode_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_seconds_sum 0.000353 +tensorfold:request_decode_seconds_count 2 +# HELP tensorfold:request_time_per_output_token_seconds Seconds from the first generated token to the last, divided by the tokens less one. +# TYPE tensorfold:request_time_per_output_token_seconds histogram +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.005"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.01"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.015"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.02"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.03"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.04"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.05"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.15"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.2"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.3"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.5"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="+Inf"} 0 +tensorfold:request_time_per_output_token_seconds_sum 0 +tensorfold:request_time_per_output_token_seconds_count 0 +# HELP tensorfold:decode_rounds_total Decode rounds used by finished requests. +# TYPE tensorfold:decode_rounds_total counter +tensorfold:decode_rounds_total 0 +# HELP tensorfold:request_prefill_seconds Seconds a finished request's prompt pass took. +# TYPE tensorfold:request_prefill_seconds histogram +tensorfold:request_prefill_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.5"} 0 +tensorfold:request_prefill_seconds_bucket{le="1"} 0 +tensorfold:request_prefill_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_seconds_bucket{le="60"} 1 +tensorfold:request_prefill_seconds_bucket{le="120"} 1 +tensorfold:request_prefill_seconds_bucket{le="300"} 1 +tensorfold:request_prefill_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_seconds_sum 509.89811 +tensorfold:request_prefill_seconds_count 2 +# HELP tensorfold:process_resident_bytes Current resident set (VmRSS); device memory is not in it, so it is not a physical footprint (Linux). +# TYPE tensorfold:process_resident_bytes gauge +tensorfold:process_resident_bytes 89820459008 +# HELP tensorfold:process_resident_anon_bytes Current resident anonymous memory (RssAnon): heap, stacks and private maps (Linux). +# TYPE tensorfold:process_resident_anon_bytes gauge +tensorfold:process_resident_anon_bytes 305340416 +# HELP tensorfold:process_resident_file_bytes Current resident file-backed memory (RssFile): the binary, libraries and mapped files (Linux). +# TYPE tensorfold:process_resident_file_bytes gauge +tensorfold:process_resident_file_bytes 89403215872 +# HELP tensorfold:process_resident_shmem_bytes Current resident shared memory (RssShmem): System V shared memory, tmpfs maps and shared anonymous maps (Linux). +# TYPE tensorfold:process_resident_shmem_bytes gauge +tensorfold:process_resident_shmem_bytes 111902720 +# HELP tensorfold:process_resident_peak_bytes Kernel lifetime peak resident set (VmHWM); never reset by health (Linux). +# TYPE tensorfold:process_resident_peak_bytes gauge +tensorfold:process_resident_peak_bytes 89828397056 +# HELP tensorfold:device_memory_bytes Device memory the engine holds now: weights, caches and live streams; only where the backend counts it (CUDA). +# TYPE tensorfold:device_memory_bytes gauge +tensorfold:device_memory_bytes 86777744832 +# HELP tensorfold:device_memory_peak_bytes The most device memory the engine has held since start or the last /health?reset_peak=1. +# TYPE tensorfold:device_memory_peak_bytes gauge +tensorfold:device_memory_peak_bytes 87088670148 +# HELP tensorfold:pinned_memory_bytes Pinned host memory the engine holds now: staging buffers and windows; only where the backend counts it (CUDA). +# TYPE tensorfold:pinned_memory_bytes gauge +tensorfold:pinned_memory_bytes 0 +# HELP tensorfold:num_requests_running Requests in prefill or decode. A mirror of tensorfold:requests_running. +# TYPE tensorfold:num_requests_running gauge +tensorfold:num_requests_running 0 +# HELP tensorfold:num_requests_waiting Requests queued or held until a lane is free. A mirror of tensorfold:requests_waiting. +# TYPE tensorfold:num_requests_waiting gauge +tensorfold:num_requests_waiting 0 +# HELP tensorfold:kv_cache_usage_perc A stream's cache occupancy under vLLM's name; same streams and ratios as tensorfold:kv_cache_usage_ratio. +# TYPE tensorfold:kv_cache_usage_perc gauge +tensorfold:kv_cache_usage_perc{stream="0"} 0 +# HELP tensorfold:spec_decode_num_draft_tokens_total Draft tokens verified on finished requests, this server's single draft counter. +# TYPE tensorfold:spec_decode_num_draft_tokens_total counter +tensorfold:spec_decode_num_draft_tokens_total 0 +# HELP tensorfold:spec_decode_num_accepted_tokens_total Draft tokens kept on finished requests. +# TYPE tensorfold:spec_decode_num_accepted_tokens_total counter +tensorfold:spec_decode_num_accepted_tokens_total 0 +# HELP tensorfold:e2e_request_latency_seconds Seconds from arrival to the reply leaving, under vLLM's name. +# TYPE tensorfold:e2e_request_latency_seconds histogram +tensorfold:e2e_request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="10"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="30"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="60"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="120"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="300"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:e2e_request_latency_seconds_sum 509.899909 +tensorfold:e2e_request_latency_seconds_count 2 +# HELP tensorfold:request_decode_time_seconds Seconds a finished request spent decoding, under vLLM's name. +# TYPE tensorfold:request_decode_time_seconds histogram +tensorfold:request_decode_time_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="10"} 2 +tensorfold:request_decode_time_seconds_bucket{le="30"} 2 +tensorfold:request_decode_time_seconds_bucket{le="60"} 2 +tensorfold:request_decode_time_seconds_bucket{le="120"} 2 +tensorfold:request_decode_time_seconds_bucket{le="300"} 2 +tensorfold:request_decode_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_time_seconds_sum 0.000353 +tensorfold:request_decode_time_seconds_count 2 +# HELP tensorfold:request_prefill_time_seconds Seconds a finished request's prompt pass took, under vLLM's name. +# TYPE tensorfold:request_prefill_time_seconds histogram +tensorfold:request_prefill_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.5"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="60"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="120"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="300"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_time_seconds_sum 509.89811 +tensorfold:request_prefill_time_seconds_count 2 +# HELP tensorfold:client_disconnections_total Requests a client left before the reply left the server. +# TYPE tensorfold:client_disconnections_total counter +tensorfold:client_disconnections_total 0 +# HELP tensorfold:preemptions_total Requests that had to give a lane up to a later one. +# TYPE tensorfold:preemptions_total counter +tensorfold:preemptions_total 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-131072-r1-samples.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-131072-r1-samples.jsonl new file mode 100644 index 0000000000..ab978da0d7 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-131072-r1-samples.jsonl @@ -0,0 +1,391 @@ +{"t_s": 0.0, "VmRSS_bytes": 43970560, "VmHWM_bytes": 43970560, "Pss_bytes": 44131328, "vram_used_bytes": 187670528, "vram_total_bytes": 4294967296, "gtt_used_bytes": 31657984, "gtt_total_bytes": 193273528320} +{"t_s": 1.04, "VmRSS_bytes": 8611803136, "VmHWM_bytes": 8611803136, "Pss_bytes": 8609412096, "vram_used_bytes": 188768256, "vram_total_bytes": 4294967296, "gtt_used_bytes": 6821748736, "gtt_total_bytes": 193273528320} +{"t_s": 2.11, "VmRSS_bytes": 15726743552, "VmHWM_bytes": 15726743552, "Pss_bytes": 15841518592, "vram_used_bytes": 189202432, "vram_total_bytes": 4294967296, "gtt_used_bytes": 13375348736, "gtt_total_bytes": 193273528320} +{"t_s": 3.2, "VmRSS_bytes": 20770455552, "VmHWM_bytes": 20770455552, "Pss_bytes": 20827177984, "vram_used_bytes": 189554688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 18288975872, "gtt_total_bytes": 193273528320} +{"t_s": 4.3, "VmRSS_bytes": 26312941568, "VmHWM_bytes": 26312941568, "Pss_bytes": 26333881344, "vram_used_bytes": 189898752, "vram_total_bytes": 4294967296, "gtt_used_bytes": 23215185920, "gtt_total_bytes": 193273528320} +{"t_s": 5.41, "VmRSS_bytes": 34109755392, "VmHWM_bytes": 34109755392, "Pss_bytes": 34143278080, "vram_used_bytes": 190443520, "vram_total_bytes": 4294967296, "gtt_used_bytes": 31404564480, "gtt_total_bytes": 193273528320} +{"t_s": 6.55, "VmRSS_bytes": 41893617664, "VmHWM_bytes": 41893617664, "Pss_bytes": 41903875072, "vram_used_bytes": 190996480, "vram_total_bytes": 4294967296, "gtt_used_bytes": 39598137344, "gtt_total_bytes": 193273528320} +{"t_s": 7.71, "VmRSS_bytes": 50224041984, "VmHWM_bytes": 50224041984, "Pss_bytes": 50228597760, "vram_used_bytes": 191520768, "vram_total_bytes": 4294967296, "gtt_used_bytes": 47793807360, "gtt_total_bytes": 193273528320} +{"t_s": 8.91, "VmRSS_bytes": 57274773504, "VmHWM_bytes": 57274773504, "Pss_bytes": 57272380416, "vram_used_bytes": 192081920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 55981088768, "gtt_total_bytes": 193273528320} +{"t_s": 10.12, "VmRSS_bytes": 66327293952, "VmHWM_bytes": 66327293952, "Pss_bytes": 66335566848, "vram_used_bytes": 192634880, "vram_total_bytes": 4294967296, "gtt_used_bytes": 64176758784, "gtt_total_bytes": 193273528320} +{"t_s": 11.36, "VmRSS_bytes": 74547355648, "VmHWM_bytes": 74547355648, "Pss_bytes": 74553892864, "vram_used_bytes": 193220608, "vram_total_bytes": 4294967296, "gtt_used_bytes": 72370331648, "gtt_total_bytes": 193273528320} +{"t_s": 12.61, "VmRSS_bytes": 80810328064, "VmHWM_bytes": 82468560896, "Pss_bytes": 80808013824, "vram_used_bytes": 194768896, "vram_total_bytes": 4294967296, "gtt_used_bytes": 86001819648, "gtt_total_bytes": 193273528320} +{"t_s": 13.85, "VmRSS_bytes": 80847609856, "VmHWM_bytes": 82468560896, "Pss_bytes": 80861713408, "vram_used_bytes": 194719744, "vram_total_bytes": 4294967296, "gtt_used_bytes": 87660666880, "gtt_total_bytes": 193273528320} +{"t_s": 15.13, "VmRSS_bytes": 81026351104, "VmHWM_bytes": 82468560896, "Pss_bytes": 81023955968, "vram_used_bytes": 194719744, "vram_total_bytes": 4294967296, "gtt_used_bytes": 87660666880, "gtt_total_bytes": 193273528320} +{"t_s": 16.39, "VmRSS_bytes": 81343660032, "VmHWM_bytes": 82468560896, "Pss_bytes": 81414497280, "vram_used_bytes": 194678784, "vram_total_bytes": 4294967296, "gtt_used_bytes": 87973142528, "gtt_total_bytes": 193273528320} +{"t_s": 17.68, "VmRSS_bytes": 81423544320, "VmHWM_bytes": 82468560896, "Pss_bytes": 81421149184, "vram_used_bytes": 194678784, "vram_total_bytes": 4294967296, "gtt_used_bytes": 87973142528, "gtt_total_bytes": 193273528320} +{"t_s": 18.95, "VmRSS_bytes": 81534726144, "VmHWM_bytes": 82468560896, "Pss_bytes": 81608258560, "vram_used_bytes": 194678784, "vram_total_bytes": 4294967296, "gtt_used_bytes": 87973142528, "gtt_total_bytes": 193273528320} +{"t_s": 20.25, "VmRSS_bytes": 81814347776, "VmHWM_bytes": 82468560896, "Pss_bytes": 81811952640, "vram_used_bytes": 194678784, "vram_total_bytes": 4294967296, "gtt_used_bytes": 87973142528, "gtt_total_bytes": 193273528320} +{"t_s": 21.53, "VmRSS_bytes": 81814347776, "VmHWM_bytes": 82468560896, "Pss_bytes": 81811952640, "vram_used_bytes": 194678784, "vram_total_bytes": 4294967296, "gtt_used_bytes": 87973142528, "gtt_total_bytes": 193273528320} +{"t_s": 22.8, "VmRSS_bytes": 81934348288, "VmHWM_bytes": 82468560896, "Pss_bytes": 81997190144, "vram_used_bytes": 194678784, "vram_total_bytes": 4294967296, "gtt_used_bytes": 87973142528, "gtt_total_bytes": 193273528320} +{"t_s": 24.09, "VmRSS_bytes": 82211696640, "VmHWM_bytes": 82468560896, "Pss_bytes": 82209301504, "vram_used_bytes": 194678784, "vram_total_bytes": 4294967296, "gtt_used_bytes": 87973142528, "gtt_total_bytes": 193273528320} +{"t_s": 25.39, "VmRSS_bytes": 82211696640, "VmHWM_bytes": 82468560896, "Pss_bytes": 82209301504, "vram_used_bytes": 194678784, "vram_total_bytes": 4294967296, "gtt_used_bytes": 87973142528, "gtt_total_bytes": 193273528320} +{"t_s": 26.65, "VmRSS_bytes": 82211696640, "VmHWM_bytes": 82468560896, "Pss_bytes": 82248913920, "vram_used_bytes": 194678784, "vram_total_bytes": 4294967296, "gtt_used_bytes": 87973142528, "gtt_total_bytes": 193273528320} +{"t_s": 27.93, "VmRSS_bytes": 82509987840, "VmHWM_bytes": 82509987840, "Pss_bytes": 82555901952, "vram_used_bytes": 194678784, "vram_total_bytes": 4294967296, "gtt_used_bytes": 87973142528, "gtt_total_bytes": 193273528320} +{"t_s": 29.22, "VmRSS_bytes": 82558283776, "VmHWM_bytes": 82558283776, "Pss_bytes": 82555889664, "vram_used_bytes": 194678784, "vram_total_bytes": 4294967296, "gtt_used_bytes": 87973142528, "gtt_total_bytes": 193273528320} +{"t_s": 30.51, "VmRSS_bytes": 82558283776, "VmHWM_bytes": 82558283776, "Pss_bytes": 82555889664, "vram_used_bytes": 194678784, "vram_total_bytes": 4294967296, "gtt_used_bytes": 87973142528, "gtt_total_bytes": 193273528320} +{"t_s": 31.8, "VmRSS_bytes": 82732015616, "VmHWM_bytes": 82732015616, "Pss_bytes": 82752911360, "vram_used_bytes": 194678784, "vram_total_bytes": 4294967296, "gtt_used_bytes": 87973142528, "gtt_total_bytes": 193273528320} +{"t_s": 33.11, "VmRSS_bytes": 82755239936, "VmHWM_bytes": 82755239936, "Pss_bytes": 82752845824, "vram_used_bytes": 194678784, "vram_total_bytes": 4294967296, "gtt_used_bytes": 87973142528, "gtt_total_bytes": 193273528320} +{"t_s": 34.4, "VmRSS_bytes": 82755239936, "VmHWM_bytes": 82755239936, "Pss_bytes": 82752845824, "vram_used_bytes": 194678784, "vram_total_bytes": 4294967296, "gtt_used_bytes": 87973142528, "gtt_total_bytes": 193273528320} +{"t_s": 35.68, "VmRSS_bytes": 82910928896, "VmHWM_bytes": 82910928896, "Pss_bytes": 82957551616, "vram_used_bytes": 194678784, "vram_total_bytes": 4294967296, "gtt_used_bytes": 87973142528, "gtt_total_bytes": 193273528320} +{"t_s": 36.98, "VmRSS_bytes": 83073626112, "VmHWM_bytes": 83073626112, "Pss_bytes": 83071232000, "vram_used_bytes": 194678784, "vram_total_bytes": 4294967296, "gtt_used_bytes": 87973142528, "gtt_total_bytes": 193273528320} +{"t_s": 38.3, "VmRSS_bytes": 83073626112, "VmHWM_bytes": 83073626112, "Pss_bytes": 83071232000, "vram_used_bytes": 194678784, 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"vram_total_bytes": 4294967296, "gtt_used_bytes": 87973142528, "gtt_total_bytes": 193273528320} +{"t_s": 500.77, "VmRSS_bytes": 89676554240, "VmHWM_bytes": 89676554240, "Pss_bytes": 89674159104, "vram_used_bytes": 194678784, "vram_total_bytes": 4294967296, "gtt_used_bytes": 87973142528, "gtt_total_bytes": 193273528320} +{"t_s": 502.15, "VmRSS_bytes": 89676554240, "VmHWM_bytes": 89676554240, "Pss_bytes": 89674159104, "vram_used_bytes": 194678784, "vram_total_bytes": 4294967296, "gtt_used_bytes": 87973142528, "gtt_total_bytes": 193273528320} +{"t_s": 503.55, "VmRSS_bytes": 89712156672, "VmHWM_bytes": 89712156672, "Pss_bytes": 89709761536, "vram_used_bytes": 194678784, "vram_total_bytes": 4294967296, "gtt_used_bytes": 87973142528, "gtt_total_bytes": 193273528320} +{"t_s": 504.94, "VmRSS_bytes": 89712156672, "VmHWM_bytes": 89712156672, "Pss_bytes": 89709761536, "vram_used_bytes": 194678784, "vram_total_bytes": 4294967296, "gtt_used_bytes": 87973142528, "gtt_total_bytes": 193273528320} +{"t_s": 506.33, "VmRSS_bytes": 89712156672, "VmHWM_bytes": 89712156672, "Pss_bytes": 89709761536, "vram_used_bytes": 194678784, "vram_total_bytes": 4294967296, "gtt_used_bytes": 87973142528, "gtt_total_bytes": 193273528320} +{"t_s": 507.72, "VmRSS_bytes": 89731874816, "VmHWM_bytes": 89731874816, "Pss_bytes": 89729479680, "vram_used_bytes": 194678784, "vram_total_bytes": 4294967296, "gtt_used_bytes": 87973142528, "gtt_total_bytes": 193273528320} +{"t_s": 509.12, "VmRSS_bytes": 89731874816, "VmHWM_bytes": 89731874816, "Pss_bytes": 89729478656, "vram_used_bytes": 194678784, "vram_total_bytes": 4294967296, "gtt_used_bytes": 87973142528, "gtt_total_bytes": 193273528320} +{"t_s": 510.49, "VmRSS_bytes": 89731874816, "VmHWM_bytes": 89731874816, "Pss_bytes": 89729549312, "vram_used_bytes": 194678784, "vram_total_bytes": 4294967296, "gtt_used_bytes": 87973142528, "gtt_total_bytes": 193273528320} +{"t_s": 511.88, "VmRSS_bytes": 89771036672, "VmHWM_bytes": 89771036672, "Pss_bytes": 89768641536, "vram_used_bytes": 194678784, "vram_total_bytes": 4294967296, "gtt_used_bytes": 87973142528, "gtt_total_bytes": 193273528320} +{"t_s": 513.28, "VmRSS_bytes": 89771036672, "VmHWM_bytes": 89771036672, "Pss_bytes": 89768641536, "vram_used_bytes": 194678784, "vram_total_bytes": 4294967296, "gtt_used_bytes": 87973142528, "gtt_total_bytes": 193273528320} +{"t_s": 514.65, "VmRSS_bytes": 89771036672, "VmHWM_bytes": 89771036672, "Pss_bytes": 89768711168, "vram_used_bytes": 194678784, "vram_total_bytes": 4294967296, "gtt_used_bytes": 87973142528, "gtt_total_bytes": 193273528320} +{"t_s": 516.04, "VmRSS_bytes": 89804742656, "VmHWM_bytes": 89804742656, "Pss_bytes": 89802347520, "vram_used_bytes": 194678784, "vram_total_bytes": 4294967296, "gtt_used_bytes": 87973142528, "gtt_total_bytes": 193273528320} +{"t_s": 517.43, "VmRSS_bytes": 89804742656, "VmHWM_bytes": 89804742656, "Pss_bytes": 89802347520, "vram_used_bytes": 194678784, "vram_total_bytes": 4294967296, "gtt_used_bytes": 87973142528, "gtt_total_bytes": 193273528320} +{"t_s": 518.8, "VmRSS_bytes": 89804742656, "VmHWM_bytes": 89804742656, "Pss_bytes": 89802417152, "vram_used_bytes": 194678784, "vram_total_bytes": 4294967296, "gtt_used_bytes": 87973142528, "gtt_total_bytes": 193273528320} +{"t_s": 520.2, "VmRSS_bytes": 89831333888, "VmHWM_bytes": 89831333888, "Pss_bytes": 89828937728, "vram_used_bytes": 194678784, "vram_total_bytes": 4294967296, "gtt_used_bytes": 87973142528, "gtt_total_bytes": 193273528320} +{"t_s": 521.6, "VmRSS_bytes": 89831333888, "VmHWM_bytes": 89831333888, "Pss_bytes": 89828938752, "vram_used_bytes": 194678784, "vram_total_bytes": 4294967296, "gtt_used_bytes": 87973142528, "gtt_total_bytes": 193273528320} +{"t_s": 522.98, "VmRSS_bytes": 89831333888, "VmHWM_bytes": 89831333888, "Pss_bytes": 89828937728, "vram_used_bytes": 194678784, "vram_total_bytes": 4294967296, "gtt_used_bytes": 87660666880, "gtt_total_bytes": 193273528320} +{"t_s": 524.27, "VmRSS_bytes": 82692734976, "VmHWM_bytes": 89828397056, "Pss_bytes": 81945792512, "vram_used_bytes": 194531328, "vram_total_bytes": 4294967296, "gtt_used_bytes": 198942720, "gtt_total_bytes": 193273528320} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-131072-r2-memory-endpoint.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-131072-r2-memory-endpoint.json new file mode 100644 index 0000000000..a8d3d2a2d7 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-131072-r2-memory-endpoint.json @@ -0,0 +1 @@ +{"schema_version": 1, "context_window": 139264, "context_fitted": false, "device": {"active_bytes": 86777744832, "cache_bytes": 0, "peak_bytes": 87088670148, "peak_scope": "since_start_or_health_reset"}} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-131072-r2-metrics.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-131072-r2-metrics.txt new file mode 100644 index 0000000000..b6934d5dc2 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-131072-r2-metrics.txt @@ -0,0 +1,220 @@ +# HELP tensorfold:requests_running Requests in prefill or decode. +# TYPE tensorfold:requests_running gauge +tensorfold:requests_running 0 +# HELP tensorfold:requests_waiting Requests queued or held until a lane is free. +# TYPE tensorfold:requests_waiting gauge +tensorfold:requests_waiting 0 +# HELP tensorfold:generation_tokens_running Generated tokens held by live streams. +# TYPE tensorfold:generation_tokens_running gauge +tensorfold:generation_tokens_running 0 +# HELP tensorfold:prompt_tokens_total Prompt tokens of finished requests. +# TYPE tensorfold:prompt_tokens_total counter +tensorfold:prompt_tokens_total 131328 +# HELP tensorfold:generation_tokens_total Generated tokens of finished requests. +# TYPE tensorfold:generation_tokens_total counter +tensorfold:generation_tokens_total 2 +# HELP tensorfold:kv_cache_usage_ratio Tokens in a stream cache divided by that stream's context window. +# TYPE tensorfold:kv_cache_usage_ratio gauge +tensorfold:kv_cache_usage_ratio{pool="0"} 0 +# HELP tensorfold:mtp_drafted_total Draft tokens verified on finished requests. +# TYPE tensorfold:mtp_drafted_total counter +tensorfold:mtp_drafted_total 0 +# HELP tensorfold:mtp_accepted_total Draft tokens kept on finished requests. +# TYPE tensorfold:mtp_accepted_total counter +tensorfold:mtp_accepted_total 0 +# HELP tensorfold:request_latency_seconds Seconds from arrival to the reply leaving. +# TYPE tensorfold:request_latency_seconds histogram +tensorfold:request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:request_latency_seconds_bucket{le="1"} 0 +tensorfold:request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:request_latency_seconds_bucket{le="5"} 1 +tensorfold:request_latency_seconds_bucket{le="10"} 1 +tensorfold:request_latency_seconds_bucket{le="30"} 1 +tensorfold:request_latency_seconds_bucket{le="60"} 1 +tensorfold:request_latency_seconds_bucket{le="120"} 1 +tensorfold:request_latency_seconds_bucket{le="300"} 1 +tensorfold:request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:request_latency_seconds_sum 510.489786 +tensorfold:request_latency_seconds_count 2 +# HELP tensorfold:time_to_first_token_seconds Seconds from arrival to the first generated token. +# TYPE tensorfold:time_to_first_token_seconds histogram +tensorfold:time_to_first_token_seconds_bucket{le="0.01"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.05"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.25"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.5"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="2.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="10"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="30"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="60"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="120"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="300"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="+Inf"} 2 +tensorfold:time_to_first_token_seconds_sum 510.489504 +tensorfold:time_to_first_token_seconds_count 2 +# HELP tensorfold:request_decode_seconds Seconds a finished request spent decoding. Its sum over generation_tokens_total is the decode rate. +# TYPE tensorfold:request_decode_seconds histogram +tensorfold:request_decode_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_seconds_bucket{le="1"} 2 +tensorfold:request_decode_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_seconds_bucket{le="5"} 2 +tensorfold:request_decode_seconds_bucket{le="10"} 2 +tensorfold:request_decode_seconds_bucket{le="30"} 2 +tensorfold:request_decode_seconds_bucket{le="60"} 2 +tensorfold:request_decode_seconds_bucket{le="120"} 2 +tensorfold:request_decode_seconds_bucket{le="300"} 2 +tensorfold:request_decode_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_seconds_sum 0.000282 +tensorfold:request_decode_seconds_count 2 +# HELP tensorfold:request_time_per_output_token_seconds Seconds from the first generated token to the last, divided by the tokens less one. +# TYPE tensorfold:request_time_per_output_token_seconds histogram +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.005"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.01"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.015"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.02"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.03"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.04"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.05"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.15"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.2"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.3"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.5"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="+Inf"} 0 +tensorfold:request_time_per_output_token_seconds_sum 0 +tensorfold:request_time_per_output_token_seconds_count 0 +# HELP tensorfold:decode_rounds_total Decode rounds used by finished requests. +# TYPE tensorfold:decode_rounds_total counter +tensorfold:decode_rounds_total 0 +# HELP tensorfold:request_prefill_seconds Seconds a finished request's prompt pass took. +# TYPE tensorfold:request_prefill_seconds histogram +tensorfold:request_prefill_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.5"} 0 +tensorfold:request_prefill_seconds_bucket{le="1"} 0 +tensorfold:request_prefill_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_seconds_bucket{le="60"} 1 +tensorfold:request_prefill_seconds_bucket{le="120"} 1 +tensorfold:request_prefill_seconds_bucket{le="300"} 1 +tensorfold:request_prefill_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_seconds_sum 510.487455 +tensorfold:request_prefill_seconds_count 2 +# HELP tensorfold:process_resident_bytes Current resident set (VmRSS); device memory is not in it, so it is not a physical footprint (Linux). +# TYPE tensorfold:process_resident_bytes gauge +tensorfold:process_resident_bytes 89818791936 +# HELP tensorfold:process_resident_anon_bytes Current resident anonymous memory (RssAnon): heap, stacks and private maps (Linux). +# TYPE tensorfold:process_resident_anon_bytes gauge +tensorfold:process_resident_anon_bytes 305545216 +# HELP tensorfold:process_resident_file_bytes Current resident file-backed memory (RssFile): the binary, libraries and mapped files (Linux). +# TYPE tensorfold:process_resident_file_bytes gauge +tensorfold:process_resident_file_bytes 89401344000 +# HELP tensorfold:process_resident_shmem_bytes Current resident shared memory (RssShmem): System V shared memory, tmpfs maps and shared anonymous maps (Linux). +# TYPE tensorfold:process_resident_shmem_bytes gauge +tensorfold:process_resident_shmem_bytes 111902720 +# HELP tensorfold:process_resident_peak_bytes Kernel lifetime peak resident set (VmHWM); never reset by health (Linux). +# TYPE tensorfold:process_resident_peak_bytes gauge +tensorfold:process_resident_peak_bytes 89827643392 +# HELP tensorfold:device_memory_bytes Device memory the engine holds now: weights, caches and live streams; only where the backend counts it (CUDA). +# TYPE tensorfold:device_memory_bytes gauge +tensorfold:device_memory_bytes 86777744832 +# HELP tensorfold:device_memory_peak_bytes The most device memory the engine has held since start or the last /health?reset_peak=1. +# TYPE tensorfold:device_memory_peak_bytes gauge +tensorfold:device_memory_peak_bytes 87088670148 +# HELP tensorfold:pinned_memory_bytes Pinned host memory the engine holds now: staging buffers and windows; only where the backend counts it (CUDA). +# TYPE tensorfold:pinned_memory_bytes gauge +tensorfold:pinned_memory_bytes 0 +# HELP tensorfold:num_requests_running Requests in prefill or decode. A mirror of tensorfold:requests_running. +# TYPE tensorfold:num_requests_running gauge +tensorfold:num_requests_running 0 +# HELP tensorfold:num_requests_waiting Requests queued or held until a lane is free. A mirror of tensorfold:requests_waiting. +# TYPE tensorfold:num_requests_waiting gauge +tensorfold:num_requests_waiting 0 +# HELP tensorfold:kv_cache_usage_perc A stream's cache occupancy under vLLM's name; same streams and ratios as tensorfold:kv_cache_usage_ratio. +# TYPE tensorfold:kv_cache_usage_perc gauge +tensorfold:kv_cache_usage_perc{stream="0"} 0 +# HELP tensorfold:spec_decode_num_draft_tokens_total Draft tokens verified on finished requests, this server's single draft counter. +# TYPE tensorfold:spec_decode_num_draft_tokens_total counter +tensorfold:spec_decode_num_draft_tokens_total 0 +# HELP tensorfold:spec_decode_num_accepted_tokens_total Draft tokens kept on finished requests. +# TYPE tensorfold:spec_decode_num_accepted_tokens_total counter +tensorfold:spec_decode_num_accepted_tokens_total 0 +# HELP tensorfold:e2e_request_latency_seconds Seconds from arrival to the reply leaving, under vLLM's name. +# TYPE tensorfold:e2e_request_latency_seconds histogram +tensorfold:e2e_request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="10"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="30"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="60"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="120"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="300"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:e2e_request_latency_seconds_sum 510.489786 +tensorfold:e2e_request_latency_seconds_count 2 +# HELP tensorfold:request_decode_time_seconds Seconds a finished request spent decoding, under vLLM's name. +# TYPE tensorfold:request_decode_time_seconds histogram +tensorfold:request_decode_time_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="10"} 2 +tensorfold:request_decode_time_seconds_bucket{le="30"} 2 +tensorfold:request_decode_time_seconds_bucket{le="60"} 2 +tensorfold:request_decode_time_seconds_bucket{le="120"} 2 +tensorfold:request_decode_time_seconds_bucket{le="300"} 2 +tensorfold:request_decode_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_time_seconds_sum 0.000282 +tensorfold:request_decode_time_seconds_count 2 +# HELP tensorfold:request_prefill_time_seconds Seconds a finished request's prompt pass took, under vLLM's name. +# TYPE tensorfold:request_prefill_time_seconds histogram +tensorfold:request_prefill_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.5"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="60"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="120"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="300"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_time_seconds_sum 510.487455 +tensorfold:request_prefill_time_seconds_count 2 +# HELP tensorfold:client_disconnections_total Requests a client left before the reply left the server. +# TYPE tensorfold:client_disconnections_total counter +tensorfold:client_disconnections_total 0 +# HELP tensorfold:preemptions_total Requests that had to give a lane up to a later one. +# TYPE tensorfold:preemptions_total counter +tensorfold:preemptions_total 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-131072-r2-samples.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-131072-r2-samples.jsonl new file mode 100644 index 0000000000..7961187964 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-131072-r2-samples.jsonl @@ -0,0 +1,383 @@ +{"t_s": 0.0, "VmRSS_bytes": 36061184, "VmHWM_bytes": 36061184, "Pss_bytes": 35905536, 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"vram_total_bytes": 4294967296, "gtt_used_bytes": 87660666880, "gtt_total_bytes": 193273528320} +{"t_s": 526.06, "VmRSS_bytes": 82625953792, "VmHWM_bytes": 89827643392, "Pss_bytes": 81944166400, "vram_used_bytes": 194592768, "vram_total_bytes": 4294967296, "gtt_used_bytes": 198942720, "gtt_total_bytes": 193273528320} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-2048-r1-memory-endpoint.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-2048-r1-memory-endpoint.json new file mode 100644 index 0000000000..1babacb168 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-2048-r1-memory-endpoint.json @@ -0,0 +1 @@ +{"schema_version": 1, "context_window": 10240, "context_fitted": false, "device": {"active_bytes": 83111398848, "cache_bytes": 0, "peak_bytes": 83116795332, "peak_scope": "since_start_or_health_reset"}} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-2048-r1-metrics.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-2048-r1-metrics.txt new file mode 100644 index 0000000000..987149267b --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-2048-r1-metrics.txt @@ -0,0 +1,220 @@ +# HELP tensorfold:requests_running Requests in prefill or decode. +# TYPE tensorfold:requests_running gauge +tensorfold:requests_running 0 +# HELP tensorfold:requests_waiting Requests queued or held until a lane is free. +# TYPE tensorfold:requests_waiting gauge +tensorfold:requests_waiting 0 +# HELP tensorfold:generation_tokens_running Generated tokens held by live streams. +# TYPE tensorfold:generation_tokens_running gauge +tensorfold:generation_tokens_running 0 +# HELP tensorfold:prompt_tokens_total Prompt tokens of finished requests. +# TYPE tensorfold:prompt_tokens_total counter +tensorfold:prompt_tokens_total 2304 +# HELP tensorfold:generation_tokens_total Generated tokens of finished requests. +# TYPE tensorfold:generation_tokens_total counter +tensorfold:generation_tokens_total 2 +# HELP tensorfold:kv_cache_usage_ratio Tokens in a stream cache divided by that stream's context window. +# TYPE tensorfold:kv_cache_usage_ratio gauge +tensorfold:kv_cache_usage_ratio{pool="0"} 0 +# HELP tensorfold:mtp_drafted_total Draft tokens verified on finished requests. +# TYPE tensorfold:mtp_drafted_total counter +tensorfold:mtp_drafted_total 0 +# HELP tensorfold:mtp_accepted_total Draft tokens kept on finished requests. +# TYPE tensorfold:mtp_accepted_total counter +tensorfold:mtp_accepted_total 0 +# HELP tensorfold:request_latency_seconds Seconds from arrival to the reply leaving. +# TYPE tensorfold:request_latency_seconds histogram +tensorfold:request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:request_latency_seconds_bucket{le="1"} 0 +tensorfold:request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:request_latency_seconds_bucket{le="5"} 1 +tensorfold:request_latency_seconds_bucket{le="10"} 2 +tensorfold:request_latency_seconds_bucket{le="30"} 2 +tensorfold:request_latency_seconds_bucket{le="60"} 2 +tensorfold:request_latency_seconds_bucket{le="120"} 2 +tensorfold:request_latency_seconds_bucket{le="300"} 2 +tensorfold:request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:request_latency_seconds_sum 9.011446 +tensorfold:request_latency_seconds_count 2 +# HELP tensorfold:time_to_first_token_seconds Seconds from arrival to the first generated token. +# TYPE tensorfold:time_to_first_token_seconds histogram +tensorfold:time_to_first_token_seconds_bucket{le="0.01"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.05"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.25"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.5"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="2.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="10"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="30"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="60"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="120"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="300"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="+Inf"} 2 +tensorfold:time_to_first_token_seconds_sum 9.011156 +tensorfold:time_to_first_token_seconds_count 2 +# HELP tensorfold:request_decode_seconds Seconds a finished request spent decoding. Its sum over generation_tokens_total is the decode rate. +# TYPE tensorfold:request_decode_seconds histogram +tensorfold:request_decode_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_seconds_bucket{le="1"} 2 +tensorfold:request_decode_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_seconds_bucket{le="5"} 2 +tensorfold:request_decode_seconds_bucket{le="10"} 2 +tensorfold:request_decode_seconds_bucket{le="30"} 2 +tensorfold:request_decode_seconds_bucket{le="60"} 2 +tensorfold:request_decode_seconds_bucket{le="120"} 2 +tensorfold:request_decode_seconds_bucket{le="300"} 2 +tensorfold:request_decode_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_seconds_sum 0.000291 +tensorfold:request_decode_seconds_count 2 +# HELP tensorfold:request_time_per_output_token_seconds Seconds from the first generated token to the last, divided by the tokens less one. +# TYPE tensorfold:request_time_per_output_token_seconds histogram +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.005"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.01"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.015"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.02"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.03"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.04"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.05"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.15"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.2"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.3"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.5"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="+Inf"} 0 +tensorfold:request_time_per_output_token_seconds_sum 0 +tensorfold:request_time_per_output_token_seconds_count 0 +# HELP tensorfold:decode_rounds_total Decode rounds used by finished requests. +# TYPE tensorfold:decode_rounds_total counter +tensorfold:decode_rounds_total 0 +# HELP tensorfold:request_prefill_seconds Seconds a finished request's prompt pass took. +# TYPE tensorfold:request_prefill_seconds histogram +tensorfold:request_prefill_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.5"} 0 +tensorfold:request_prefill_seconds_bucket{le="1"} 0 +tensorfold:request_prefill_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_seconds_bucket{le="10"} 2 +tensorfold:request_prefill_seconds_bucket{le="30"} 2 +tensorfold:request_prefill_seconds_bucket{le="60"} 2 +tensorfold:request_prefill_seconds_bucket{le="120"} 2 +tensorfold:request_prefill_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_seconds_sum 9.01005 +tensorfold:request_prefill_seconds_count 2 +# HELP tensorfold:process_resident_bytes Current resident set (VmRSS); device memory is not in it, so it is not a physical footprint (Linux). +# TYPE tensorfold:process_resident_bytes gauge +tensorfold:process_resident_bytes 81804464128 +# HELP tensorfold:process_resident_anon_bytes Current resident anonymous memory (RssAnon): heap, stacks and private maps (Linux). +# TYPE tensorfold:process_resident_anon_bytes gauge +tensorfold:process_resident_anon_bytes 304812032 +# HELP tensorfold:process_resident_file_bytes Current resident file-backed memory (RssFile): the binary, libraries and mapped files (Linux). +# TYPE tensorfold:process_resident_file_bytes gauge +tensorfold:process_resident_file_bytes 81387749376 +# HELP tensorfold:process_resident_shmem_bytes Current resident shared memory (RssShmem): System V shared memory, tmpfs maps and shared anonymous maps (Linux). +# TYPE tensorfold:process_resident_shmem_bytes gauge +tensorfold:process_resident_shmem_bytes 111902720 +# HELP tensorfold:process_resident_peak_bytes Kernel lifetime peak resident set (VmHWM); never reset by health (Linux). +# TYPE tensorfold:process_resident_peak_bytes gauge +tensorfold:process_resident_peak_bytes 82468945920 +# HELP tensorfold:device_memory_bytes Device memory the engine holds now: weights, caches and live streams; only where the backend counts it (CUDA). +# TYPE tensorfold:device_memory_bytes gauge +tensorfold:device_memory_bytes 83111398848 +# HELP tensorfold:device_memory_peak_bytes The most device memory the engine has held since start or the last /health?reset_peak=1. +# TYPE tensorfold:device_memory_peak_bytes gauge +tensorfold:device_memory_peak_bytes 83116795332 +# HELP tensorfold:pinned_memory_bytes Pinned host memory the engine holds now: staging buffers and windows; only where the backend counts it (CUDA). +# TYPE tensorfold:pinned_memory_bytes gauge +tensorfold:pinned_memory_bytes 0 +# HELP tensorfold:num_requests_running Requests in prefill or decode. A mirror of tensorfold:requests_running. +# TYPE tensorfold:num_requests_running gauge +tensorfold:num_requests_running 0 +# HELP tensorfold:num_requests_waiting Requests queued or held until a lane is free. A mirror of tensorfold:requests_waiting. +# TYPE tensorfold:num_requests_waiting gauge +tensorfold:num_requests_waiting 0 +# HELP tensorfold:kv_cache_usage_perc A stream's cache occupancy under vLLM's name; same streams and ratios as tensorfold:kv_cache_usage_ratio. +# TYPE tensorfold:kv_cache_usage_perc gauge +tensorfold:kv_cache_usage_perc{stream="0"} 0 +# HELP tensorfold:spec_decode_num_draft_tokens_total Draft tokens verified on finished requests, this server's single draft counter. +# TYPE tensorfold:spec_decode_num_draft_tokens_total counter +tensorfold:spec_decode_num_draft_tokens_total 0 +# HELP tensorfold:spec_decode_num_accepted_tokens_total Draft tokens kept on finished requests. +# TYPE tensorfold:spec_decode_num_accepted_tokens_total counter +tensorfold:spec_decode_num_accepted_tokens_total 0 +# HELP tensorfold:e2e_request_latency_seconds Seconds from arrival to the reply leaving, under vLLM's name. +# TYPE tensorfold:e2e_request_latency_seconds histogram +tensorfold:e2e_request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="10"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="30"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="60"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="120"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="300"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:e2e_request_latency_seconds_sum 9.011446 +tensorfold:e2e_request_latency_seconds_count 2 +# HELP tensorfold:request_decode_time_seconds Seconds a finished request spent decoding, under vLLM's name. +# TYPE tensorfold:request_decode_time_seconds histogram +tensorfold:request_decode_time_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="10"} 2 +tensorfold:request_decode_time_seconds_bucket{le="30"} 2 +tensorfold:request_decode_time_seconds_bucket{le="60"} 2 +tensorfold:request_decode_time_seconds_bucket{le="120"} 2 +tensorfold:request_decode_time_seconds_bucket{le="300"} 2 +tensorfold:request_decode_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_time_seconds_sum 0.000291 +tensorfold:request_decode_time_seconds_count 2 +# HELP tensorfold:request_prefill_time_seconds Seconds a finished request's prompt pass took, under vLLM's name. +# TYPE tensorfold:request_prefill_time_seconds histogram +tensorfold:request_prefill_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.5"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="10"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="30"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="60"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="120"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_time_seconds_sum 9.01005 +tensorfold:request_prefill_time_seconds_count 2 +# HELP tensorfold:client_disconnections_total Requests a client left before the reply left the server. +# TYPE tensorfold:client_disconnections_total counter +tensorfold:client_disconnections_total 0 +# HELP tensorfold:preemptions_total Requests that had to give a lane up to a later one. +# TYPE tensorfold:preemptions_total counter +tensorfold:preemptions_total 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-2048-r1-samples.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-2048-r1-samples.jsonl new file mode 100644 index 0000000000..cd04c57fd4 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-2048-r1-samples.jsonl @@ -0,0 +1,20 @@ +{"t_s": 0.0, "VmRSS_bytes": 59617280, "VmHWM_bytes": 59617280, "Pss_bytes": 59594752, "vram_used_bytes": 187670528, "vram_total_bytes": 4294967296, "gtt_used_bytes": 31657984, "gtt_total_bytes": 193273528320} +{"t_s": 1.03, "VmRSS_bytes": 8405745664, "VmHWM_bytes": 8405745664, "Pss_bytes": 8442693632, "vram_used_bytes": 188698624, "vram_total_bytes": 4294967296, "gtt_used_bytes": 5188067328, "gtt_total_bytes": 193273528320} +{"t_s": 2.08, "VmRSS_bytes": 16045449216, "VmHWM_bytes": 16045449216, "Pss_bytes": 16043599872, "vram_used_bytes": 189194240, "vram_total_bytes": 4294967296, "gtt_used_bytes": 13375348736, "gtt_total_bytes": 193273528320} +{"t_s": 3.16, "VmRSS_bytes": 22685360128, "VmHWM_bytes": 22685360128, "Pss_bytes": 22708152320, "vram_used_bytes": 189640704, "vram_total_bytes": 4294967296, "gtt_used_bytes": 19928948736, "gtt_total_bytes": 193273528320} +{"t_s": 4.25, "VmRSS_bytes": 29699645440, "VmHWM_bytes": 29699645440, "Pss_bytes": 29697271808, "vram_used_bytes": 190205952, "vram_total_bytes": 4294967296, "gtt_used_bytes": 28124618752, "gtt_total_bytes": 193273528320} +{"t_s": 5.37, "VmRSS_bytes": 38213062656, "VmHWM_bytes": 38213062656, "Pss_bytes": 38270654464, "vram_used_bytes": 190795776, "vram_total_bytes": 4294967296, "gtt_used_bytes": 36318191616, "gtt_total_bytes": 193273528320} +{"t_s": 6.5, "VmRSS_bytes": 46270939136, "VmHWM_bytes": 46270939136, "Pss_bytes": 46281410560, "vram_used_bytes": 191328256, "vram_total_bytes": 4294967296, "gtt_used_bytes": 44513861632, "gtt_total_bytes": 193273528320} +{"t_s": 7.65, "VmRSS_bytes": 54706384896, "VmHWM_bytes": 54706384896, "Pss_bytes": 54776887296, "vram_used_bytes": 191913984, "vram_total_bytes": 4294967296, "gtt_used_bytes": 52707434496, "gtt_total_bytes": 193273528320} +{"t_s": 8.83, "VmRSS_bytes": 62292234240, "VmHWM_bytes": 62292234240, "Pss_bytes": 62335735808, "vram_used_bytes": 192479232, "vram_total_bytes": 4294967296, "gtt_used_bytes": 60901007360, "gtt_total_bytes": 193273528320} +{"t_s": 10.02, "VmRSS_bytes": 71197851648, "VmHWM_bytes": 71197851648, "Pss_bytes": 71195478016, "vram_used_bytes": 193044480, "vram_total_bytes": 4294967296, "gtt_used_bytes": 69096677376, "gtt_total_bytes": 193273528320} +{"t_s": 11.22, "VmRSS_bytes": 78865256448, "VmHWM_bytes": 78865256448, "Pss_bytes": 78880708608, "vram_used_bytes": 193634304, "vram_total_bytes": 4294967296, "gtt_used_bytes": 77283958784, "gtt_total_bytes": 193273528320} +{"t_s": 12.44, "VmRSS_bytes": 80830251008, "VmHWM_bytes": 82468945920, "Pss_bytes": 80840062976, "vram_used_bytes": 195014656, "vram_total_bytes": 4294967296, "gtt_used_bytes": 83992748032, "gtt_total_bytes": 193273528320} +{"t_s": 13.68, "VmRSS_bytes": 81026981888, "VmHWM_bytes": 82468945920, "Pss_bytes": 81024604160, "vram_used_bytes": 195014656, "vram_total_bytes": 4294967296, "gtt_used_bytes": 83992748032, "gtt_total_bytes": 193273528320} +{"t_s": 14.9, "VmRSS_bytes": 81243410432, "VmHWM_bytes": 82468945920, "Pss_bytes": 81305229312, "vram_used_bytes": 195014656, "vram_total_bytes": 4294967296, "gtt_used_bytes": 83999039488, "gtt_total_bytes": 193273528320} +{"t_s": 16.15, "VmRSS_bytes": 81412251648, "VmHWM_bytes": 82468945920, "Pss_bytes": 81409873920, "vram_used_bytes": 195014656, "vram_total_bytes": 4294967296, "gtt_used_bytes": 83999039488, "gtt_total_bytes": 193273528320} +{"t_s": 17.37, "VmRSS_bytes": 81417699328, "VmHWM_bytes": 82468945920, "Pss_bytes": 81475000320, "vram_used_bytes": 195014656, "vram_total_bytes": 4294967296, "gtt_used_bytes": 83999039488, "gtt_total_bytes": 193273528320} +{"t_s": 18.61, "VmRSS_bytes": 81799155712, "VmHWM_bytes": 82468945920, "Pss_bytes": 81802254336, "vram_used_bytes": 195014656, "vram_total_bytes": 4294967296, "gtt_used_bytes": 83999039488, "gtt_total_bytes": 193273528320} +{"t_s": 19.86, "VmRSS_bytes": 81804636160, "VmHWM_bytes": 82468945920, "Pss_bytes": 81802258432, "vram_used_bytes": 195014656, "vram_total_bytes": 4294967296, "gtt_used_bytes": 83999039488, "gtt_total_bytes": 193273528320} +{"t_s": 21.1, "VmRSS_bytes": 81804636160, "VmHWM_bytes": 82468945920, "Pss_bytes": 81802242048, "vram_used_bytes": 195014656, "vram_total_bytes": 4294967296, "gtt_used_bytes": 83992748032, "gtt_total_bytes": 193273528320} +{"t_s": 22.15, "VmRSS_bytes": 20416765952, "VmHWM_bytes": 82468945920, "Pss_bytes": 19789408256, "vram_used_bytes": 194883584, "vram_total_bytes": 4294967296, "gtt_used_bytes": 198942720, "gtt_total_bytes": 193273528320} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-2048-r2-memory-endpoint.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-2048-r2-memory-endpoint.json new file mode 100644 index 0000000000..1babacb168 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-2048-r2-memory-endpoint.json @@ -0,0 +1 @@ +{"schema_version": 1, "context_window": 10240, "context_fitted": false, "device": {"active_bytes": 83111398848, "cache_bytes": 0, "peak_bytes": 83116795332, "peak_scope": "since_start_or_health_reset"}} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-2048-r2-metrics.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-2048-r2-metrics.txt new file mode 100644 index 0000000000..7f48fd1831 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-2048-r2-metrics.txt @@ -0,0 +1,220 @@ +# HELP tensorfold:requests_running Requests in prefill or decode. +# TYPE tensorfold:requests_running gauge +tensorfold:requests_running 0 +# HELP tensorfold:requests_waiting Requests queued or held until a lane is free. +# TYPE tensorfold:requests_waiting gauge +tensorfold:requests_waiting 0 +# HELP tensorfold:generation_tokens_running Generated tokens held by live streams. +# TYPE tensorfold:generation_tokens_running gauge +tensorfold:generation_tokens_running 0 +# HELP tensorfold:prompt_tokens_total Prompt tokens of finished requests. +# TYPE tensorfold:prompt_tokens_total counter +tensorfold:prompt_tokens_total 2304 +# HELP tensorfold:generation_tokens_total Generated tokens of finished requests. +# TYPE tensorfold:generation_tokens_total counter +tensorfold:generation_tokens_total 2 +# HELP tensorfold:kv_cache_usage_ratio Tokens in a stream cache divided by that stream's context window. +# TYPE tensorfold:kv_cache_usage_ratio gauge +tensorfold:kv_cache_usage_ratio{pool="0"} 0 +# HELP tensorfold:mtp_drafted_total Draft tokens verified on finished requests. +# TYPE tensorfold:mtp_drafted_total counter +tensorfold:mtp_drafted_total 0 +# HELP tensorfold:mtp_accepted_total Draft tokens kept on finished requests. +# TYPE tensorfold:mtp_accepted_total counter +tensorfold:mtp_accepted_total 0 +# HELP tensorfold:request_latency_seconds Seconds from arrival to the reply leaving. +# TYPE tensorfold:request_latency_seconds histogram +tensorfold:request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:request_latency_seconds_bucket{le="1"} 0 +tensorfold:request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:request_latency_seconds_bucket{le="5"} 1 +tensorfold:request_latency_seconds_bucket{le="10"} 2 +tensorfold:request_latency_seconds_bucket{le="30"} 2 +tensorfold:request_latency_seconds_bucket{le="60"} 2 +tensorfold:request_latency_seconds_bucket{le="120"} 2 +tensorfold:request_latency_seconds_bucket{le="300"} 2 +tensorfold:request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:request_latency_seconds_sum 8.799855 +tensorfold:request_latency_seconds_count 2 +# HELP tensorfold:time_to_first_token_seconds Seconds from arrival to the first generated token. +# TYPE tensorfold:time_to_first_token_seconds histogram +tensorfold:time_to_first_token_seconds_bucket{le="0.01"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.05"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.25"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.5"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="2.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="10"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="30"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="60"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="120"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="300"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="+Inf"} 2 +tensorfold:time_to_first_token_seconds_sum 8.799575 +tensorfold:time_to_first_token_seconds_count 2 +# HELP tensorfold:request_decode_seconds Seconds a finished request spent decoding. Its sum over generation_tokens_total is the decode rate. +# TYPE tensorfold:request_decode_seconds histogram +tensorfold:request_decode_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_seconds_bucket{le="1"} 2 +tensorfold:request_decode_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_seconds_bucket{le="5"} 2 +tensorfold:request_decode_seconds_bucket{le="10"} 2 +tensorfold:request_decode_seconds_bucket{le="30"} 2 +tensorfold:request_decode_seconds_bucket{le="60"} 2 +tensorfold:request_decode_seconds_bucket{le="120"} 2 +tensorfold:request_decode_seconds_bucket{le="300"} 2 +tensorfold:request_decode_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_seconds_sum 0.00028 +tensorfold:request_decode_seconds_count 2 +# HELP tensorfold:request_time_per_output_token_seconds Seconds from the first generated token to the last, divided by the tokens less one. +# TYPE tensorfold:request_time_per_output_token_seconds histogram +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.005"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.01"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.015"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.02"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.03"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.04"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.05"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.15"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.2"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.3"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.5"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="+Inf"} 0 +tensorfold:request_time_per_output_token_seconds_sum 0 +tensorfold:request_time_per_output_token_seconds_count 0 +# HELP tensorfold:decode_rounds_total Decode rounds used by finished requests. +# TYPE tensorfold:decode_rounds_total counter +tensorfold:decode_rounds_total 0 +# HELP tensorfold:request_prefill_seconds Seconds a finished request's prompt pass took. +# TYPE tensorfold:request_prefill_seconds histogram +tensorfold:request_prefill_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.5"} 0 +tensorfold:request_prefill_seconds_bucket{le="1"} 0 +tensorfold:request_prefill_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_seconds_bucket{le="10"} 2 +tensorfold:request_prefill_seconds_bucket{le="30"} 2 +tensorfold:request_prefill_seconds_bucket{le="60"} 2 +tensorfold:request_prefill_seconds_bucket{le="120"} 2 +tensorfold:request_prefill_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_seconds_sum 8.798429 +tensorfold:request_prefill_seconds_count 2 +# HELP tensorfold:process_resident_bytes Current resident set (VmRSS); device memory is not in it, so it is not a physical footprint (Linux). +# TYPE tensorfold:process_resident_bytes gauge +tensorfold:process_resident_bytes 81806905344 +# HELP tensorfold:process_resident_anon_bytes Current resident anonymous memory (RssAnon): heap, stacks and private maps (Linux). +# TYPE tensorfold:process_resident_anon_bytes gauge +tensorfold:process_resident_anon_bytes 305135616 +# HELP tensorfold:process_resident_file_bytes Current resident file-backed memory (RssFile): the binary, libraries and mapped files (Linux). +# TYPE tensorfold:process_resident_file_bytes gauge +tensorfold:process_resident_file_bytes 81389867008 +# HELP tensorfold:process_resident_shmem_bytes Current resident shared memory (RssShmem): System V shared memory, tmpfs maps and shared anonymous maps (Linux). +# TYPE tensorfold:process_resident_shmem_bytes gauge +tensorfold:process_resident_shmem_bytes 111902720 +# HELP tensorfold:process_resident_peak_bytes Kernel lifetime peak resident set (VmHWM); never reset by health (Linux). +# TYPE tensorfold:process_resident_peak_bytes gauge +tensorfold:process_resident_peak_bytes 82470608896 +# HELP tensorfold:device_memory_bytes Device memory the engine holds now: weights, caches and live streams; only where the backend counts it (CUDA). +# TYPE tensorfold:device_memory_bytes gauge +tensorfold:device_memory_bytes 83111398848 +# HELP tensorfold:device_memory_peak_bytes The most device memory the engine has held since start or the last /health?reset_peak=1. +# TYPE tensorfold:device_memory_peak_bytes gauge +tensorfold:device_memory_peak_bytes 83116795332 +# HELP tensorfold:pinned_memory_bytes Pinned host memory the engine holds now: staging buffers and windows; only where the backend counts it (CUDA). +# TYPE tensorfold:pinned_memory_bytes gauge +tensorfold:pinned_memory_bytes 0 +# HELP tensorfold:num_requests_running Requests in prefill or decode. A mirror of tensorfold:requests_running. +# TYPE tensorfold:num_requests_running gauge +tensorfold:num_requests_running 0 +# HELP tensorfold:num_requests_waiting Requests queued or held until a lane is free. A mirror of tensorfold:requests_waiting. +# TYPE tensorfold:num_requests_waiting gauge +tensorfold:num_requests_waiting 0 +# HELP tensorfold:kv_cache_usage_perc A stream's cache occupancy under vLLM's name; same streams and ratios as tensorfold:kv_cache_usage_ratio. +# TYPE tensorfold:kv_cache_usage_perc gauge +tensorfold:kv_cache_usage_perc{stream="0"} 0 +# HELP tensorfold:spec_decode_num_draft_tokens_total Draft tokens verified on finished requests, this server's single draft counter. +# TYPE tensorfold:spec_decode_num_draft_tokens_total counter +tensorfold:spec_decode_num_draft_tokens_total 0 +# HELP tensorfold:spec_decode_num_accepted_tokens_total Draft tokens kept on finished requests. +# TYPE tensorfold:spec_decode_num_accepted_tokens_total counter +tensorfold:spec_decode_num_accepted_tokens_total 0 +# HELP tensorfold:e2e_request_latency_seconds Seconds from arrival to the reply leaving, under vLLM's name. +# TYPE tensorfold:e2e_request_latency_seconds histogram +tensorfold:e2e_request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="10"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="30"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="60"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="120"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="300"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:e2e_request_latency_seconds_sum 8.799855 +tensorfold:e2e_request_latency_seconds_count 2 +# HELP tensorfold:request_decode_time_seconds Seconds a finished request spent decoding, under vLLM's name. +# TYPE tensorfold:request_decode_time_seconds histogram +tensorfold:request_decode_time_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="10"} 2 +tensorfold:request_decode_time_seconds_bucket{le="30"} 2 +tensorfold:request_decode_time_seconds_bucket{le="60"} 2 +tensorfold:request_decode_time_seconds_bucket{le="120"} 2 +tensorfold:request_decode_time_seconds_bucket{le="300"} 2 +tensorfold:request_decode_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_time_seconds_sum 0.00028 +tensorfold:request_decode_time_seconds_count 2 +# HELP tensorfold:request_prefill_time_seconds Seconds a finished request's prompt pass took, under vLLM's name. +# TYPE tensorfold:request_prefill_time_seconds histogram +tensorfold:request_prefill_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.5"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="10"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="30"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="60"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="120"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_time_seconds_sum 8.798429 +tensorfold:request_prefill_time_seconds_count 2 +# HELP tensorfold:client_disconnections_total Requests a client left before the reply left the server. +# TYPE tensorfold:client_disconnections_total counter +tensorfold:client_disconnections_total 0 +# HELP tensorfold:preemptions_total Requests that had to give a lane up to a later one. +# TYPE tensorfold:preemptions_total counter +tensorfold:preemptions_total 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-2048-r2-samples.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-2048-r2-samples.jsonl new file mode 100644 index 0000000000..bbdab69a56 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-2048-r2-samples.jsonl @@ -0,0 +1,19 @@ +{"t_s": 0.0, "VmRSS_bytes": 42110976, "VmHWM_bytes": 42110976, "Pss_bytes": 40607744, "vram_used_bytes": 187670528, "vram_total_bytes": 4294967296, "gtt_used_bytes": 31657984, "gtt_total_bytes": 193273528320} +{"t_s": 1.03, "VmRSS_bytes": 8567418880, "VmHWM_bytes": 8567418880, "Pss_bytes": 8564989952, "vram_used_bytes": 188686336, "vram_total_bytes": 4294967296, "gtt_used_bytes": 6718988288, "gtt_total_bytes": 193273528320} +{"t_s": 2.08, "VmRSS_bytes": 16669528064, "VmHWM_bytes": 16669528064, "Pss_bytes": 16675880960, "vram_used_bytes": 189214720, "vram_total_bytes": 4294967296, "gtt_used_bytes": 13381640192, "gtt_total_bytes": 193273528320} +{"t_s": 3.17, "VmRSS_bytes": 24215969792, "VmHWM_bytes": 24215969792, "Pss_bytes": 24249651200, "vram_used_bytes": 189775872, "vram_total_bytes": 4294967296, "gtt_used_bytes": 21568921600, "gtt_total_bytes": 193273528320} +{"t_s": 4.27, "VmRSS_bytes": 29249327104, "VmHWM_bytes": 29249327104, "Pss_bytes": 29307977728, "vram_used_bytes": 190140416, "vram_total_bytes": 4294967296, "gtt_used_bytes": 26490937344, "gtt_total_bytes": 193273528320} +{"t_s": 5.39, "VmRSS_bytes": 37232013312, "VmHWM_bytes": 37232013312, "Pss_bytes": 37238300672, "vram_used_bytes": 190697472, "vram_total_bytes": 4294967296, "gtt_used_bytes": 34684510208, "gtt_total_bytes": 193273528320} +{"t_s": 6.53, "VmRSS_bytes": 45351735296, "VmHWM_bytes": 45351735296, "Pss_bytes": 45349306368, "vram_used_bytes": 191258624, "vram_total_bytes": 4294967296, "gtt_used_bytes": 42878083072, "gtt_total_bytes": 193273528320} +{"t_s": 7.68, "VmRSS_bytes": 53687549952, "VmHWM_bytes": 53687549952, "Pss_bytes": 53718675456, "vram_used_bytes": 191819776, "vram_total_bytes": 4294967296, "gtt_used_bytes": 51067461632, "gtt_total_bytes": 193273528320} +{"t_s": 8.86, "VmRSS_bytes": 61664509952, "VmHWM_bytes": 61664509952, "Pss_bytes": 61784633344, "vram_used_bytes": 192385024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 59261034496, "gtt_total_bytes": 193273528320} +{"t_s": 10.06, "VmRSS_bytes": 69996638208, "VmHWM_bytes": 69996638208, "Pss_bytes": 70029074432, "vram_used_bytes": 192958464, "vram_total_bytes": 4294967296, "gtt_used_bytes": 67456704512, "gtt_total_bytes": 193273528320} +{"t_s": 11.28, "VmRSS_bytes": 77835034624, "VmHWM_bytes": 77835034624, "Pss_bytes": 77856591872, "vram_used_bytes": 193527808, "vram_total_bytes": 4294967296, "gtt_used_bytes": 75650277376, "gtt_total_bytes": 193273528320} +{"t_s": 12.51, "VmRSS_bytes": 80835137536, "VmHWM_bytes": 82470608896, "Pss_bytes": 80846331904, "vram_used_bytes": 195035136, "vram_total_bytes": 4294967296, "gtt_used_bytes": 83992748032, "gtt_total_bytes": 193273528320} +{"t_s": 13.77, "VmRSS_bytes": 81029824512, "VmHWM_bytes": 82470608896, "Pss_bytes": 81027387392, "vram_used_bytes": 195035136, "vram_total_bytes": 4294967296, "gtt_used_bytes": 83992748032, "gtt_total_bytes": 193273528320} +{"t_s": 15.01, "VmRSS_bytes": 81302519808, "VmHWM_bytes": 82470608896, "Pss_bytes": 81365340160, "vram_used_bytes": 195035136, "vram_total_bytes": 4294967296, "gtt_used_bytes": 83999039488, "gtt_total_bytes": 193273528320} +{"t_s": 16.28, "VmRSS_bytes": 81416335360, "VmHWM_bytes": 82470608896, "Pss_bytes": 81413898240, "vram_used_bytes": 195035136, "vram_total_bytes": 4294967296, "gtt_used_bytes": 83999039488, "gtt_total_bytes": 193273528320} +{"t_s": 17.52, "VmRSS_bytes": 81483046912, "VmHWM_bytes": 82470608896, "Pss_bytes": 81547399168, "vram_used_bytes": 195035136, "vram_total_bytes": 4294967296, "gtt_used_bytes": 83999039488, "gtt_total_bytes": 193273528320} +{"t_s": 18.79, "VmRSS_bytes": 81807069184, "VmHWM_bytes": 82470608896, "Pss_bytes": 81804632064, "vram_used_bytes": 195035136, "vram_total_bytes": 4294967296, "gtt_used_bytes": 83999039488, "gtt_total_bytes": 193273528320} +{"t_s": 20.06, "VmRSS_bytes": 81807069184, "VmHWM_bytes": 82470608896, "Pss_bytes": 81804632064, "vram_used_bytes": 195035136, "vram_total_bytes": 4294967296, "gtt_used_bytes": 83999039488, "gtt_total_bytes": 193273528320} +{"t_s": 21.31, "VmRSS_bytes": 81806716928, "VmHWM_bytes": 82470608896, "Pss_bytes": 81804286976, "vram_used_bytes": 195035136, "vram_total_bytes": 4294967296, "gtt_used_bytes": 83992748032, "gtt_total_bytes": 193273528320} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-261888-r1-memory-endpoint.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-261888-r1-memory-endpoint.json new file mode 100644 index 0000000000..7d8a588b25 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-261888-r1-memory-endpoint.json @@ -0,0 +1 @@ +{"schema_version": 1, "context_window": 262144, "context_fitted": false, "device": {"active_bytes": 90269502912, "cache_bytes": 0, "peak_bytes": 90890200516, "peak_scope": "since_start_or_health_reset"}} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-261888-r1-metrics.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-261888-r1-metrics.txt new file mode 100644 index 0000000000..8f93c4d846 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-261888-r1-metrics.txt @@ -0,0 +1,220 @@ +# HELP tensorfold:requests_running Requests in prefill or decode. +# TYPE tensorfold:requests_running gauge +tensorfold:requests_running 0 +# HELP tensorfold:requests_waiting Requests queued or held until a lane is free. +# TYPE tensorfold:requests_waiting gauge +tensorfold:requests_waiting 0 +# HELP tensorfold:generation_tokens_running Generated tokens held by live streams. +# TYPE tensorfold:generation_tokens_running gauge +tensorfold:generation_tokens_running 0 +# HELP tensorfold:prompt_tokens_total Prompt tokens of finished requests. +# TYPE tensorfold:prompt_tokens_total counter +tensorfold:prompt_tokens_total 262144 +# HELP tensorfold:generation_tokens_total Generated tokens of finished requests. +# TYPE tensorfold:generation_tokens_total counter +tensorfold:generation_tokens_total 2 +# HELP tensorfold:kv_cache_usage_ratio Tokens in a stream cache divided by that stream's context window. +# TYPE tensorfold:kv_cache_usage_ratio gauge +tensorfold:kv_cache_usage_ratio{pool="0"} 0 +# HELP tensorfold:mtp_drafted_total Draft tokens verified on finished requests. +# TYPE tensorfold:mtp_drafted_total counter +tensorfold:mtp_drafted_total 0 +# HELP tensorfold:mtp_accepted_total Draft tokens kept on finished requests. +# TYPE tensorfold:mtp_accepted_total counter +tensorfold:mtp_accepted_total 0 +# HELP tensorfold:request_latency_seconds Seconds from arrival to the reply leaving. +# TYPE tensorfold:request_latency_seconds histogram +tensorfold:request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:request_latency_seconds_bucket{le="1"} 0 +tensorfold:request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:request_latency_seconds_bucket{le="5"} 1 +tensorfold:request_latency_seconds_bucket{le="10"} 1 +tensorfold:request_latency_seconds_bucket{le="30"} 1 +tensorfold:request_latency_seconds_bucket{le="60"} 1 +tensorfold:request_latency_seconds_bucket{le="120"} 1 +tensorfold:request_latency_seconds_bucket{le="300"} 1 +tensorfold:request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:request_latency_seconds_sum 1070.655254 +tensorfold:request_latency_seconds_count 2 +# HELP tensorfold:time_to_first_token_seconds Seconds from arrival to the first generated token. +# TYPE tensorfold:time_to_first_token_seconds histogram +tensorfold:time_to_first_token_seconds_bucket{le="0.01"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.05"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.25"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.5"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="2.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="10"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="30"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="60"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="120"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="300"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="+Inf"} 2 +tensorfold:time_to_first_token_seconds_sum 1070.654883 +tensorfold:time_to_first_token_seconds_count 2 +# HELP tensorfold:request_decode_seconds Seconds a finished request spent decoding. Its sum over generation_tokens_total is the decode rate. +# TYPE tensorfold:request_decode_seconds histogram +tensorfold:request_decode_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_seconds_bucket{le="1"} 2 +tensorfold:request_decode_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_seconds_bucket{le="5"} 2 +tensorfold:request_decode_seconds_bucket{le="10"} 2 +tensorfold:request_decode_seconds_bucket{le="30"} 2 +tensorfold:request_decode_seconds_bucket{le="60"} 2 +tensorfold:request_decode_seconds_bucket{le="120"} 2 +tensorfold:request_decode_seconds_bucket{le="300"} 2 +tensorfold:request_decode_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_seconds_sum 0.000371 +tensorfold:request_decode_seconds_count 2 +# HELP tensorfold:request_time_per_output_token_seconds Seconds from the first generated token to the last, divided by the tokens less one. +# TYPE tensorfold:request_time_per_output_token_seconds histogram +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.005"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.01"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.015"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.02"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.03"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.04"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.05"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.15"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.2"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.3"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.5"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="+Inf"} 0 +tensorfold:request_time_per_output_token_seconds_sum 0 +tensorfold:request_time_per_output_token_seconds_count 0 +# HELP tensorfold:decode_rounds_total Decode rounds used by finished requests. +# TYPE tensorfold:decode_rounds_total counter +tensorfold:decode_rounds_total 0 +# HELP tensorfold:request_prefill_seconds Seconds a finished request's prompt pass took. +# TYPE tensorfold:request_prefill_seconds histogram +tensorfold:request_prefill_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.5"} 0 +tensorfold:request_prefill_seconds_bucket{le="1"} 0 +tensorfold:request_prefill_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_seconds_bucket{le="60"} 1 +tensorfold:request_prefill_seconds_bucket{le="120"} 1 +tensorfold:request_prefill_seconds_bucket{le="300"} 1 +tensorfold:request_prefill_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_seconds_sum 1070.652189 +tensorfold:request_prefill_seconds_count 2 +# HELP tensorfold:process_resident_bytes Current resident set (VmRSS); device memory is not in it, so it is not a physical footprint (Linux). +# TYPE tensorfold:process_resident_bytes gauge +tensorfold:process_resident_bytes 93074989056 +# HELP tensorfold:process_resident_anon_bytes Current resident anonymous memory (RssAnon): heap, stacks and private maps (Linux). +# TYPE tensorfold:process_resident_anon_bytes gauge +tensorfold:process_resident_anon_bytes 306552832 +# HELP tensorfold:process_resident_file_bytes Current resident file-backed memory (RssFile): the binary, libraries and mapped files (Linux). +# TYPE tensorfold:process_resident_file_bytes gauge +tensorfold:process_resident_file_bytes 92656533504 +# HELP tensorfold:process_resident_shmem_bytes Current resident shared memory (RssShmem): System V shared memory, tmpfs maps and shared anonymous maps (Linux). +# TYPE tensorfold:process_resident_shmem_bytes gauge +tensorfold:process_resident_shmem_bytes 111902720 +# HELP tensorfold:process_resident_peak_bytes Kernel lifetime peak resident set (VmHWM); never reset by health (Linux). +# TYPE tensorfold:process_resident_peak_bytes gauge +tensorfold:process_resident_peak_bytes 93097451520 +# HELP tensorfold:device_memory_bytes Device memory the engine holds now: weights, caches and live streams; only where the backend counts it (CUDA). +# TYPE tensorfold:device_memory_bytes gauge +tensorfold:device_memory_bytes 90269502912 +# HELP tensorfold:device_memory_peak_bytes The most device memory the engine has held since start or the last /health?reset_peak=1. +# TYPE tensorfold:device_memory_peak_bytes gauge +tensorfold:device_memory_peak_bytes 90890200516 +# HELP tensorfold:pinned_memory_bytes Pinned host memory the engine holds now: staging buffers and windows; only where the backend counts it (CUDA). +# TYPE tensorfold:pinned_memory_bytes gauge +tensorfold:pinned_memory_bytes 0 +# HELP tensorfold:num_requests_running Requests in prefill or decode. A mirror of tensorfold:requests_running. +# TYPE tensorfold:num_requests_running gauge +tensorfold:num_requests_running 0 +# HELP tensorfold:num_requests_waiting Requests queued or held until a lane is free. A mirror of tensorfold:requests_waiting. +# TYPE tensorfold:num_requests_waiting gauge +tensorfold:num_requests_waiting 0 +# HELP tensorfold:kv_cache_usage_perc A stream's cache occupancy under vLLM's name; same streams and ratios as tensorfold:kv_cache_usage_ratio. +# TYPE tensorfold:kv_cache_usage_perc gauge +tensorfold:kv_cache_usage_perc{stream="0"} 0 +# HELP tensorfold:spec_decode_num_draft_tokens_total Draft tokens verified on finished requests, this server's single draft counter. +# TYPE tensorfold:spec_decode_num_draft_tokens_total counter +tensorfold:spec_decode_num_draft_tokens_total 0 +# HELP tensorfold:spec_decode_num_accepted_tokens_total Draft tokens kept on finished requests. +# TYPE tensorfold:spec_decode_num_accepted_tokens_total counter +tensorfold:spec_decode_num_accepted_tokens_total 0 +# HELP tensorfold:e2e_request_latency_seconds Seconds from arrival to the reply leaving, under vLLM's name. +# TYPE tensorfold:e2e_request_latency_seconds histogram +tensorfold:e2e_request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="10"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="30"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="60"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="120"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="300"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:e2e_request_latency_seconds_sum 1070.655254 +tensorfold:e2e_request_latency_seconds_count 2 +# HELP tensorfold:request_decode_time_seconds Seconds a finished request spent decoding, under vLLM's name. +# TYPE tensorfold:request_decode_time_seconds histogram +tensorfold:request_decode_time_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="10"} 2 +tensorfold:request_decode_time_seconds_bucket{le="30"} 2 +tensorfold:request_decode_time_seconds_bucket{le="60"} 2 +tensorfold:request_decode_time_seconds_bucket{le="120"} 2 +tensorfold:request_decode_time_seconds_bucket{le="300"} 2 +tensorfold:request_decode_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_time_seconds_sum 0.000371 +tensorfold:request_decode_time_seconds_count 2 +# HELP tensorfold:request_prefill_time_seconds Seconds a finished request's prompt pass took, under vLLM's name. +# TYPE tensorfold:request_prefill_time_seconds histogram +tensorfold:request_prefill_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.5"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="60"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="120"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="300"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_time_seconds_sum 1070.652189 +tensorfold:request_prefill_time_seconds_count 2 +# HELP tensorfold:client_disconnections_total Requests a client left before the reply left the server. +# TYPE tensorfold:client_disconnections_total counter +tensorfold:client_disconnections_total 0 +# HELP tensorfold:preemptions_total Requests that had to give a lane up to a later one. +# TYPE tensorfold:preemptions_total counter +tensorfold:preemptions_total 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-261888-r1-samples.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-261888-r1-samples.jsonl new file mode 100644 index 0000000000..ba65035e0e --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-261888-r1-samples.jsonl @@ -0,0 +1,821 @@ +{"t_s": 0.0, "VmRSS_bytes": 40419328, "VmHWM_bytes": 40419328, "Pss_bytes": 38785024, "vram_used_bytes": 187670528, "vram_total_bytes": 4294967296, "gtt_used_bytes": 31657984, "gtt_total_bytes": 193273528320} +{"t_s": 1.02, "VmRSS_bytes": 6170730496, "VmHWM_bytes": 6170730496, "Pss_bytes": 6189584384, "vram_used_bytes": 188612608, "vram_total_bytes": 4294967296, "gtt_used_bytes": 3545997312, "gtt_total_bytes": 193273528320} +{"t_s": 2.06, "VmRSS_bytes": 11041869824, "VmHWM_bytes": 11041869824, "Pss_bytes": 11063083008, "vram_used_bytes": 188874752, "vram_total_bytes": 4294967296, "gtt_used_bytes": 8461721600, "gtt_total_bytes": 193273528320} +{"t_s": 3.12, "VmRSS_bytes": 15947644928, "VmHWM_bytes": 15947644928, "Pss_bytes": 15948525568, "vram_used_bytes": 189202432, "vram_total_bytes": 4294967296, "gtt_used_bytes": 13375348736, "gtt_total_bytes": 193273528320} +{"t_s": 4.19, "VmRSS_bytes": 21543051264, "VmHWM_bytes": 21543051264, "Pss_bytes": 21540671488, "vram_used_bytes": 189562880, "vram_total_bytes": 4294967296, "gtt_used_bytes": 19243180032, "gtt_total_bytes": 193273528320} +{"t_s": 5.29, "VmRSS_bytes": 29701242880, "VmHWM_bytes": 29701242880, "Pss_bytes": 29698863104, "vram_used_bytes": 190193664, "vram_total_bytes": 4294967296, "gtt_used_bytes": 28124618752, "gtt_total_bytes": 193273528320} +{"t_s": 6.39, "VmRSS_bytes": 39103594496, "VmHWM_bytes": 39103594496, "Pss_bytes": 39157706752, "vram_used_bytes": 190738432, "vram_total_bytes": 4294967296, "gtt_used_bytes": 36324483072, "gtt_total_bytes": 193273528320} +{"t_s": 7.51, "VmRSS_bytes": 47450234880, "VmHWM_bytes": 47450234880, "Pss_bytes": 47469219840, "vram_used_bytes": 191242240, "vram_total_bytes": 4294967296, "gtt_used_bytes": 44513861632, "gtt_total_bytes": 193273528320} +{"t_s": 8.65, "VmRSS_bytes": 55607726080, "VmHWM_bytes": 55607726080, "Pss_bytes": 55605346304, "vram_used_bytes": 191795200, "vram_total_bytes": 4294967296, "gtt_used_bytes": 54183829504, "gtt_total_bytes": 193273528320} +{"t_s": 9.81, "VmRSS_bytes": 63766781952, "VmHWM_bytes": 63766781952, "Pss_bytes": 63764402176, "vram_used_bytes": 192446464, "vram_total_bytes": 4294967296, "gtt_used_bytes": 62540980224, "gtt_total_bytes": 193273528320} +{"t_s": 10.99, "VmRSS_bytes": 73496346624, "VmHWM_bytes": 73496346624, "Pss_bytes": 73493966848, "vram_used_bytes": 193069056, "vram_total_bytes": 4294967296, "gtt_used_bytes": 72370331648, "gtt_total_bytes": 193273528320} +{"t_s": 12.19, "VmRSS_bytes": 80814170112, "VmHWM_bytes": 82471530496, "Pss_bytes": 80818066432, "vram_used_bytes": 194514944, "vram_total_bytes": 4294967296, "gtt_used_bytes": 89021718528, "gtt_total_bytes": 193273528320} +{"t_s": 13.4, "VmRSS_bytes": 80826191872, "VmHWM_bytes": 82471530496, "Pss_bytes": 80823803904, "vram_used_bytes": 194490368, "vram_total_bytes": 4294967296, "gtt_used_bytes": 91152424960, "gtt_total_bytes": 193273528320} +{"t_s": 14.59, "VmRSS_bytes": 80941064192, "VmHWM_bytes": 82471530496, "Pss_bytes": 80990826496, "vram_used_bytes": 194490368, "vram_total_bytes": 4294967296, "gtt_used_bytes": 91152424960, "gtt_total_bytes": 193273528320} +{"t_s": 15.79, "VmRSS_bytes": 81112842240, "VmHWM_bytes": 82471530496, "Pss_bytes": 81171419136, "vram_used_bytes": 194404352, "vram_total_bytes": 4294967296, "gtt_used_bytes": 91773181952, "gtt_total_bytes": 193273528320} +{"t_s": 17.02, "VmRSS_bytes": 81453072384, "VmHWM_bytes": 82471530496, "Pss_bytes": 81450684416, "vram_used_bytes": 194404352, "vram_total_bytes": 4294967296, "gtt_used_bytes": 91773181952, "gtt_total_bytes": 193273528320} +{"t_s": 18.24, "VmRSS_bytes": 81453072384, "VmHWM_bytes": 82471530496, "Pss_bytes": 81450684416, "vram_used_bytes": 194404352, "vram_total_bytes": 4294967296, "gtt_used_bytes": 91773181952, "gtt_total_bytes": 193273528320} +{"t_s": 19.45, "VmRSS_bytes": 81671892992, "VmHWM_bytes": 82471530496, "Pss_bytes": 81730170880, "vram_used_bytes": 194404352, "vram_total_bytes": 4294967296, "gtt_used_bytes": 91773181952, "gtt_total_bytes": 193273528320} +{"t_s": 20.68, "VmRSS_bytes": 81850728448, "VmHWM_bytes": 82471530496, "Pss_bytes": 81848340480, "vram_used_bytes": 194404352, "vram_total_bytes": 4294967296, "gtt_used_bytes": 91773181952, "gtt_total_bytes": 193273528320} +{"t_s": 21.91, "VmRSS_bytes": 81850728448, "VmHWM_bytes": 82471530496, "Pss_bytes": 81848340480, "vram_used_bytes": 194404352, "vram_total_bytes": 4294967296, "gtt_used_bytes": 91773181952, "gtt_total_bytes": 193273528320} +{"t_s": 23.12, "VmRSS_bytes": 81979666432, "VmHWM_bytes": 82471530496, "Pss_bytes": 82028290048, "vram_used_bytes": 194404352, "vram_total_bytes": 4294967296, "gtt_used_bytes": 91773181952, "gtt_total_bytes": 193273528320} +{"t_s": 24.35, "VmRSS_bytes": 82253262848, "VmHWM_bytes": 82471530496, "Pss_bytes": 82250874880, "vram_used_bytes": 194404352, "vram_total_bytes": 4294967296, "gtt_used_bytes": 91773181952, "gtt_total_bytes": 193273528320} +{"t_s": 25.59, "VmRSS_bytes": 82253262848, "VmHWM_bytes": 82471530496, "Pss_bytes": 82250874880, "vram_used_bytes": 194404352, "vram_total_bytes": 4294967296, "gtt_used_bytes": 91773181952, "gtt_total_bytes": 193273528320} +{"t_s": 26.81, "VmRSS_bytes": 82253262848, "VmHWM_bytes": 82471530496, "Pss_bytes": 82251419648, "vram_used_bytes": 194404352, "vram_total_bytes": 4294967296, "gtt_used_bytes": 91773181952, "gtt_total_bytes": 193273528320} +{"t_s": 28.02, "VmRSS_bytes": 82521423872, "VmHWM_bytes": 82521423872, "Pss_bytes": 82562031616, "vram_used_bytes": 194404352, "vram_total_bytes": 4294967296, "gtt_used_bytes": 91773181952, "gtt_total_bytes": 193273528320} +{"t_s": 29.26, "VmRSS_bytes": 82604990464, "VmHWM_bytes": 82604990464, "Pss_bytes": 82602601472, "vram_used_bytes": 194404352, "vram_total_bytes": 4294967296, "gtt_used_bytes": 91773181952, "gtt_total_bytes": 193273528320} +{"t_s": 30.5, "VmRSS_bytes": 82604990464, "VmHWM_bytes": 82604990464, "Pss_bytes": 82602601472, "vram_used_bytes": 194404352, "vram_total_bytes": 4294967296, "gtt_used_bytes": 91773181952, "gtt_total_bytes": 193273528320} +{"t_s": 31.72, "VmRSS_bytes": 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"vram_used_bytes": 194404352, "vram_total_bytes": 4294967296, "gtt_used_bytes": 91152424960, "gtt_total_bytes": 193273528320} +{"t_s": 1085.21, "VmRSS_bytes": 79122518016, "VmHWM_bytes": 93097451520, "Pss_bytes": 77038779392, "vram_used_bytes": 194244608, "vram_total_bytes": 4294967296, "gtt_used_bytes": 198942720, "gtt_total_bytes": 193273528320} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-261888-r2-memory-endpoint.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-261888-r2-memory-endpoint.json new file mode 100644 index 0000000000..7d8a588b25 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-261888-r2-memory-endpoint.json @@ -0,0 +1 @@ +{"schema_version": 1, "context_window": 262144, "context_fitted": false, "device": {"active_bytes": 90269502912, "cache_bytes": 0, "peak_bytes": 90890200516, "peak_scope": "since_start_or_health_reset"}} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-261888-r2-metrics.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-261888-r2-metrics.txt new file mode 100644 index 0000000000..de055b7de8 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-261888-r2-metrics.txt @@ -0,0 +1,220 @@ +# HELP tensorfold:requests_running Requests in prefill or decode. +# TYPE tensorfold:requests_running gauge +tensorfold:requests_running 0 +# HELP tensorfold:requests_waiting Requests queued or held until a lane is free. +# TYPE tensorfold:requests_waiting gauge +tensorfold:requests_waiting 0 +# HELP tensorfold:generation_tokens_running Generated tokens held by live streams. +# TYPE tensorfold:generation_tokens_running gauge +tensorfold:generation_tokens_running 0 +# HELP tensorfold:prompt_tokens_total Prompt tokens of finished requests. +# TYPE tensorfold:prompt_tokens_total counter +tensorfold:prompt_tokens_total 262144 +# HELP tensorfold:generation_tokens_total Generated tokens of finished requests. +# TYPE tensorfold:generation_tokens_total counter +tensorfold:generation_tokens_total 2 +# HELP tensorfold:kv_cache_usage_ratio Tokens in a stream cache divided by that stream's context window. +# TYPE tensorfold:kv_cache_usage_ratio gauge +tensorfold:kv_cache_usage_ratio{pool="0"} 0 +# HELP tensorfold:mtp_drafted_total Draft tokens verified on finished requests. +# TYPE tensorfold:mtp_drafted_total counter +tensorfold:mtp_drafted_total 0 +# HELP tensorfold:mtp_accepted_total Draft tokens kept on finished requests. +# TYPE tensorfold:mtp_accepted_total counter +tensorfold:mtp_accepted_total 0 +# HELP tensorfold:request_latency_seconds Seconds from arrival to the reply leaving. +# TYPE tensorfold:request_latency_seconds histogram +tensorfold:request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:request_latency_seconds_bucket{le="1"} 0 +tensorfold:request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:request_latency_seconds_bucket{le="5"} 1 +tensorfold:request_latency_seconds_bucket{le="10"} 1 +tensorfold:request_latency_seconds_bucket{le="30"} 1 +tensorfold:request_latency_seconds_bucket{le="60"} 1 +tensorfold:request_latency_seconds_bucket{le="120"} 1 +tensorfold:request_latency_seconds_bucket{le="300"} 1 +tensorfold:request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:request_latency_seconds_sum 1073.476247 +tensorfold:request_latency_seconds_count 2 +# HELP tensorfold:time_to_first_token_seconds Seconds from arrival to the first generated token. +# TYPE tensorfold:time_to_first_token_seconds histogram +tensorfold:time_to_first_token_seconds_bucket{le="0.01"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.05"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.25"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.5"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="2.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="10"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="30"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="60"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="120"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="300"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="+Inf"} 2 +tensorfold:time_to_first_token_seconds_sum 1073.475628 +tensorfold:time_to_first_token_seconds_count 2 +# HELP tensorfold:request_decode_seconds Seconds a finished request spent decoding. Its sum over generation_tokens_total is the decode rate. +# TYPE tensorfold:request_decode_seconds histogram +tensorfold:request_decode_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_seconds_bucket{le="1"} 2 +tensorfold:request_decode_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_seconds_bucket{le="5"} 2 +tensorfold:request_decode_seconds_bucket{le="10"} 2 +tensorfold:request_decode_seconds_bucket{le="30"} 2 +tensorfold:request_decode_seconds_bucket{le="60"} 2 +tensorfold:request_decode_seconds_bucket{le="120"} 2 +tensorfold:request_decode_seconds_bucket{le="300"} 2 +tensorfold:request_decode_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_seconds_sum 0.000619 +tensorfold:request_decode_seconds_count 2 +# HELP tensorfold:request_time_per_output_token_seconds Seconds from the first generated token to the last, divided by the tokens less one. +# TYPE tensorfold:request_time_per_output_token_seconds histogram +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.005"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.01"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.015"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.02"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.03"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.04"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.05"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.15"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.2"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.3"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.5"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="+Inf"} 0 +tensorfold:request_time_per_output_token_seconds_sum 0 +tensorfold:request_time_per_output_token_seconds_count 0 +# HELP tensorfold:decode_rounds_total Decode rounds used by finished requests. +# TYPE tensorfold:decode_rounds_total counter +tensorfold:decode_rounds_total 0 +# HELP tensorfold:request_prefill_seconds Seconds a finished request's prompt pass took. +# TYPE tensorfold:request_prefill_seconds histogram +tensorfold:request_prefill_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.5"} 0 +tensorfold:request_prefill_seconds_bucket{le="1"} 0 +tensorfold:request_prefill_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_seconds_bucket{le="60"} 1 +tensorfold:request_prefill_seconds_bucket{le="120"} 1 +tensorfold:request_prefill_seconds_bucket{le="300"} 1 +tensorfold:request_prefill_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_seconds_sum 1073.473456 +tensorfold:request_prefill_seconds_count 2 +# HELP tensorfold:process_resident_bytes Current resident set (VmRSS); device memory is not in it, so it is not a physical footprint (Linux). +# TYPE tensorfold:process_resident_bytes gauge +tensorfold:process_resident_bytes 93050257408 +# HELP tensorfold:process_resident_anon_bytes Current resident anonymous memory (RssAnon): heap, stacks and private maps (Linux). +# TYPE tensorfold:process_resident_anon_bytes gauge +tensorfold:process_resident_anon_bytes 307433472 +# HELP tensorfold:process_resident_file_bytes Current resident file-backed memory (RssFile): the binary, libraries and mapped files (Linux). +# TYPE tensorfold:process_resident_file_bytes gauge +tensorfold:process_resident_file_bytes 92630921216 +# HELP tensorfold:process_resident_shmem_bytes Current resident shared memory (RssShmem): System V shared memory, tmpfs maps and shared anonymous maps (Linux). +# TYPE tensorfold:process_resident_shmem_bytes gauge +tensorfold:process_resident_shmem_bytes 111902720 +# HELP tensorfold:process_resident_peak_bytes Kernel lifetime peak resident set (VmHWM); never reset by health (Linux). +# TYPE tensorfold:process_resident_peak_bytes gauge +tensorfold:process_resident_peak_bytes 93071581184 +# HELP tensorfold:device_memory_bytes Device memory the engine holds now: weights, caches and live streams; only where the backend counts it (CUDA). +# TYPE tensorfold:device_memory_bytes gauge +tensorfold:device_memory_bytes 90269502912 +# HELP tensorfold:device_memory_peak_bytes The most device memory the engine has held since start or the last /health?reset_peak=1. +# TYPE tensorfold:device_memory_peak_bytes gauge +tensorfold:device_memory_peak_bytes 90890200516 +# HELP tensorfold:pinned_memory_bytes Pinned host memory the engine holds now: staging buffers and windows; only where the backend counts it (CUDA). +# TYPE tensorfold:pinned_memory_bytes gauge +tensorfold:pinned_memory_bytes 0 +# HELP tensorfold:num_requests_running Requests in prefill or decode. A mirror of tensorfold:requests_running. +# TYPE tensorfold:num_requests_running gauge +tensorfold:num_requests_running 0 +# HELP tensorfold:num_requests_waiting Requests queued or held until a lane is free. A mirror of tensorfold:requests_waiting. +# TYPE tensorfold:num_requests_waiting gauge +tensorfold:num_requests_waiting 0 +# HELP tensorfold:kv_cache_usage_perc A stream's cache occupancy under vLLM's name; same streams and ratios as tensorfold:kv_cache_usage_ratio. +# TYPE tensorfold:kv_cache_usage_perc gauge +tensorfold:kv_cache_usage_perc{stream="0"} 0 +# HELP tensorfold:spec_decode_num_draft_tokens_total Draft tokens verified on finished requests, this server's single draft counter. +# TYPE tensorfold:spec_decode_num_draft_tokens_total counter +tensorfold:spec_decode_num_draft_tokens_total 0 +# HELP tensorfold:spec_decode_num_accepted_tokens_total Draft tokens kept on finished requests. +# TYPE tensorfold:spec_decode_num_accepted_tokens_total counter +tensorfold:spec_decode_num_accepted_tokens_total 0 +# HELP tensorfold:e2e_request_latency_seconds Seconds from arrival to the reply leaving, under vLLM's name. +# TYPE tensorfold:e2e_request_latency_seconds histogram +tensorfold:e2e_request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="10"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="30"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="60"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="120"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="300"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:e2e_request_latency_seconds_sum 1073.476247 +tensorfold:e2e_request_latency_seconds_count 2 +# HELP tensorfold:request_decode_time_seconds Seconds a finished request spent decoding, under vLLM's name. +# TYPE tensorfold:request_decode_time_seconds histogram +tensorfold:request_decode_time_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="10"} 2 +tensorfold:request_decode_time_seconds_bucket{le="30"} 2 +tensorfold:request_decode_time_seconds_bucket{le="60"} 2 +tensorfold:request_decode_time_seconds_bucket{le="120"} 2 +tensorfold:request_decode_time_seconds_bucket{le="300"} 2 +tensorfold:request_decode_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_time_seconds_sum 0.000619 +tensorfold:request_decode_time_seconds_count 2 +# HELP tensorfold:request_prefill_time_seconds Seconds a finished request's prompt pass took, under vLLM's name. +# TYPE tensorfold:request_prefill_time_seconds histogram +tensorfold:request_prefill_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.5"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="60"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="120"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="300"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_time_seconds_sum 1073.473456 +tensorfold:request_prefill_time_seconds_count 2 +# HELP tensorfold:client_disconnections_total Requests a client left before the reply left the server. +# TYPE tensorfold:client_disconnections_total counter +tensorfold:client_disconnections_total 0 +# HELP tensorfold:preemptions_total Requests that had to give a lane up to a later one. +# TYPE tensorfold:preemptions_total counter +tensorfold:preemptions_total 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-261888-r2-samples.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-261888-r2-samples.jsonl new file mode 100644 index 0000000000..481932c93c --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-261888-r2-samples.jsonl @@ -0,0 +1,786 @@ +{"t_s": 0.0, "VmRSS_bytes": 40546304, "VmHWM_bytes": 40546304, "Pss_bytes": 38754304, "vram_used_bytes": 187670528, "vram_total_bytes": 4294967296, "gtt_used_bytes": 31657984, "gtt_total_bytes": 193273528320} +{"t_s": 1.03, "VmRSS_bytes": 8570408960, "VmHWM_bytes": 8570408960, "Pss_bytes": 8568118272, "vram_used_bytes": 188694528, "vram_total_bytes": 4294967296, "gtt_used_bytes": 6135980032, "gtt_total_bytes": 193273528320} +{"t_s": 2.09, "VmRSS_bytes": 15775985664, "VmHWM_bytes": 15775985664, "Pss_bytes": 15934061568, "vram_used_bytes": 189186048, "vram_total_bytes": 4294967296, "gtt_used_bytes": 13375348736, "gtt_total_bytes": 193273528320} +{"t_s": 3.19, "VmRSS_bytes": 21852557312, "VmHWM_bytes": 21852557312, "Pss_bytes": 21859703808, "vram_used_bytes": 189644800, "vram_total_bytes": 4294967296, "gtt_used_bytes": 19928948736, "gtt_total_bytes": 193273528320} +{"t_s": 4.3, "VmRSS_bytes": 27011112960, "VmHWM_bytes": 27011112960, "Pss_bytes": 27023830016, "vram_used_bytes": 190021632, "vram_total_bytes": 4294967296, "gtt_used_bytes": 24844673024, "gtt_total_bytes": 193273528320} +{"t_s": 5.43, "VmRSS_bytes": 32301735936, "VmHWM_bytes": 32301735936, "Pss_bytes": 32326183936, "vram_used_bytes": 190324736, "vram_total_bytes": 4294967296, "gtt_used_bytes": 29764591616, "gtt_total_bytes": 193273528320} +{"t_s": 6.57, "VmRSS_bytes": 38621392896, "VmHWM_bytes": 38621392896, "Pss_bytes": 38652984320, "vram_used_bytes": 190791680, "vram_total_bytes": 4294967296, "gtt_used_bytes": 36324483072, "gtt_total_bytes": 193273528320} +{"t_s": 7.74, "VmRSS_bytes": 46344777728, "VmHWM_bytes": 46344777728, "Pss_bytes": 46373223424, "vram_used_bytes": 191307776, "vram_total_bytes": 4294967296, "gtt_used_bytes": 44513861632, "gtt_total_bytes": 193273528320} +{"t_s": 8.92, "VmRSS_bytes": 55353954304, "VmHWM_bytes": 55353954304, "Pss_bytes": 55477230592, "vram_used_bytes": 191897600, "vram_total_bytes": 4294967296, "gtt_used_bytes": 52707434496, "gtt_total_bytes": 193273528320} +{"t_s": 10.11, "VmRSS_bytes": 63497404416, "VmHWM_bytes": 63497404416, "Pss_bytes": 63522900992, "vram_used_bytes": 192434176, "vram_total_bytes": 4294967296, "gtt_used_bytes": 60901007360, "gtt_total_bytes": 193273528320} +{"t_s": 11.33, "VmRSS_bytes": 71876395008, "VmHWM_bytes": 71876395008, "Pss_bytes": 71874104320, "vram_used_bytes": 193077248, "vram_total_bytes": 4294967296, "gtt_used_bytes": 70730358784, "gtt_total_bytes": 193273528320} +{"t_s": 12.57, "VmRSS_bytes": 82472726528, "VmHWM_bytes": 82472726528, "Pss_bytes": 82470435840, "vram_used_bytes": 194482176, "vram_total_bytes": 4294967296, "gtt_used_bytes": 80570195968, "gtt_total_bytes": 193273528320} +{"t_s": 13.81, "VmRSS_bytes": 80846405632, "VmHWM_bytes": 82473586688, "Pss_bytes": 80857586688, "vram_used_bytes": 194637824, "vram_total_bytes": 4294967296, "gtt_used_bytes": 91152424960, "gtt_total_bytes": 193273528320} +{"t_s": 15.07, "VmRSS_bytes": 81031749632, "VmHWM_bytes": 82473586688, "Pss_bytes": 81029453824, "vram_used_bytes": 194637824, "vram_total_bytes": 4294967296, "gtt_used_bytes": 91152424960, "gtt_total_bytes": 193273528320} +{"t_s": 16.32, "VmRSS_bytes": 81299861504, "VmHWM_bytes": 82473586688, "Pss_bytes": 81367129088, "vram_used_bytes": 194551808, "vram_total_bytes": 4294967296, "gtt_used_bytes": 91773181952, "gtt_total_bytes": 193273528320} +{"t_s": 17.59, "VmRSS_bytes": 81441579008, "VmHWM_bytes": 82473586688, "Pss_bytes": 81439284224, "vram_used_bytes": 194551808, "vram_total_bytes": 4294967296, "gtt_used_bytes": 91773181952, "gtt_total_bytes": 193273528320} +{"t_s": 18.84, "VmRSS_bytes": 81485078528, "VmHWM_bytes": 82473586688, "Pss_bytes": 81550142464, "vram_used_bytes": 194551808, "vram_total_bytes": 4294967296, "gtt_used_bytes": 91773181952, "gtt_total_bytes": 193273528320} +{"t_s": 20.12, "VmRSS_bytes": 81832239104, "VmHWM_bytes": 82473586688, "Pss_bytes": 81829944320, "vram_used_bytes": 194551808, "vram_total_bytes": 4294967296, "gtt_used_bytes": 91773181952, "gtt_total_bytes": 193273528320} +{"t_s": 21.4, "VmRSS_bytes": 81832239104, "VmHWM_bytes": 82473586688, "Pss_bytes": 81829944320, "vram_used_bytes": 194551808, "vram_total_bytes": 4294967296, "gtt_used_bytes": 91773181952, "gtt_total_bytes": 193273528320} +{"t_s": 22.65, "VmRSS_bytes": 81869873152, "VmHWM_bytes": 82473586688, "Pss_bytes": 81933498368, "vram_used_bytes": 194551808, "vram_total_bytes": 4294967296, "gtt_used_bytes": 91773181952, "gtt_total_bytes": 193273528320} +{"t_s": 23.93, "VmRSS_bytes": 82216972288, "VmHWM_bytes": 82473586688, "Pss_bytes": 82226392064, "vram_used_bytes": 194551808, "vram_total_bytes": 4294967296, "gtt_used_bytes": 91773181952, "gtt_total_bytes": 193273528320} +{"t_s": 25.22, "VmRSS_bytes": 82228985856, "VmHWM_bytes": 82473586688, "Pss_bytes": 82226691072, "vram_used_bytes": 194551808, "vram_total_bytes": 4294967296, "gtt_used_bytes": 91773181952, "gtt_total_bytes": 193273528320} +{"t_s": 26.49, "VmRSS_bytes": 82228985856, "VmHWM_bytes": 82473586688, "Pss_bytes": 82226691072, "vram_used_bytes": 194551808, "vram_total_bytes": 4294967296, "gtt_used_bytes": 91773181952, "gtt_total_bytes": 193273528320} +{"t_s": 27.76, "VmRSS_bytes": 82459570176, "VmHWM_bytes": 82473586688, "Pss_bytes": 82511121408, "vram_used_bytes": 194551808, "vram_total_bytes": 4294967296, "gtt_used_bytes": 91773181952, "gtt_total_bytes": 193273528320} +{"t_s": 29.04, "VmRSS_bytes": 82575187968, "VmHWM_bytes": 82575187968, "Pss_bytes": 82572893184, "vram_used_bytes": 194551808, "vram_total_bytes": 4294967296, "gtt_used_bytes": 91773181952, "gtt_total_bytes": 193273528320} +{"t_s": 30.33, "VmRSS_bytes": 82575187968, "VmHWM_bytes": 82575187968, "Pss_bytes": 82572893184, "vram_used_bytes": 194551808, "vram_total_bytes": 4294967296, "gtt_used_bytes": 91773181952, "gtt_total_bytes": 193273528320} +{"t_s": 31.6, "VmRSS_bytes": 82667974656, "VmHWM_bytes": 82667974656, "Pss_bytes": 82716634112, "vram_used_bytes": 194551808, "vram_total_bytes": 4294967296, "gtt_used_bytes": 91773181952, "gtt_total_bytes": 193273528320} +{"t_s": 32.9, "VmRSS_bytes": 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"vram_used_bytes": 194551808, "vram_total_bytes": 4294967296, "gtt_used_bytes": 91773181952, "gtt_total_bytes": 193273528320} +{"t_s": 1060.55, "VmRSS_bytes": 92932268032, "VmHWM_bytes": 92932268032, "Pss_bytes": 92929971200, "vram_used_bytes": 194551808, "vram_total_bytes": 4294967296, "gtt_used_bytes": 91773181952, "gtt_total_bytes": 193273528320} +{"t_s": 1062.15, "VmRSS_bytes": 92932268032, "VmHWM_bytes": 92932268032, "Pss_bytes": 92929971200, "vram_used_bytes": 194551808, "vram_total_bytes": 4294967296, "gtt_used_bytes": 91773181952, "gtt_total_bytes": 193273528320} +{"t_s": 1063.69, "VmRSS_bytes": 92932268032, "VmHWM_bytes": 92932268032, "Pss_bytes": 92931802112, "vram_used_bytes": 194551808, "vram_total_bytes": 4294967296, "gtt_used_bytes": 91773181952, "gtt_total_bytes": 193273528320} +{"t_s": 1065.17, "VmRSS_bytes": 92956344320, "VmHWM_bytes": 92956344320, "Pss_bytes": 92954047488, "vram_used_bytes": 194551808, "vram_total_bytes": 4294967296, "gtt_used_bytes": 91773181952, "gtt_total_bytes": 193273528320} +{"t_s": 1066.77, "VmRSS_bytes": 92956344320, "VmHWM_bytes": 92956344320, "Pss_bytes": 92954047488, "vram_used_bytes": 194551808, "vram_total_bytes": 4294967296, "gtt_used_bytes": 91773181952, "gtt_total_bytes": 193273528320} +{"t_s": 1068.34, "VmRSS_bytes": 92956344320, "VmHWM_bytes": 92956344320, "Pss_bytes": 92954117120, "vram_used_bytes": 194551808, "vram_total_bytes": 4294967296, "gtt_used_bytes": 91773181952, "gtt_total_bytes": 193273528320} +{"t_s": 1069.83, "VmRSS_bytes": 92988944384, "VmHWM_bytes": 92988944384, "Pss_bytes": 92986647552, "vram_used_bytes": 194551808, "vram_total_bytes": 4294967296, "gtt_used_bytes": 91773181952, "gtt_total_bytes": 193273528320} +{"t_s": 1071.41, "VmRSS_bytes": 92988944384, "VmHWM_bytes": 92988944384, "Pss_bytes": 92986647552, "vram_used_bytes": 194551808, "vram_total_bytes": 4294967296, "gtt_used_bytes": 91773181952, "gtt_total_bytes": 193273528320} +{"t_s": 1073.0, "VmRSS_bytes": 92988944384, "VmHWM_bytes": 92988944384, "Pss_bytes": 92986647552, "vram_used_bytes": 194551808, "vram_total_bytes": 4294967296, "gtt_used_bytes": 91773181952, "gtt_total_bytes": 193273528320} +{"t_s": 1074.47, "VmRSS_bytes": 93028077568, "VmHWM_bytes": 93028077568, "Pss_bytes": 93025780736, "vram_used_bytes": 194551808, "vram_total_bytes": 4294967296, "gtt_used_bytes": 91773181952, "gtt_total_bytes": 193273528320} +{"t_s": 1075.99, "VmRSS_bytes": 93028077568, "VmHWM_bytes": 93028077568, "Pss_bytes": 93025780736, "vram_used_bytes": 194551808, "vram_total_bytes": 4294967296, "gtt_used_bytes": 91773181952, "gtt_total_bytes": 193273528320} +{"t_s": 1077.59, "VmRSS_bytes": 93028077568, "VmHWM_bytes": 93028077568, "Pss_bytes": 93025780736, "vram_used_bytes": 194551808, "vram_total_bytes": 4294967296, "gtt_used_bytes": 91773181952, "gtt_total_bytes": 193273528320} +{"t_s": 1079.05, "VmRSS_bytes": 93054033920, "VmHWM_bytes": 93054033920, "Pss_bytes": 93051737088, "vram_used_bytes": 194551808, "vram_total_bytes": 4294967296, "gtt_used_bytes": 91773181952, "gtt_total_bytes": 193273528320} +{"t_s": 1080.61, "VmRSS_bytes": 93054033920, "VmHWM_bytes": 93054033920, "Pss_bytes": 93051737088, "vram_used_bytes": 194551808, "vram_total_bytes": 4294967296, "gtt_used_bytes": 91773181952, "gtt_total_bytes": 193273528320} +{"t_s": 1082.23, "VmRSS_bytes": 93054033920, "VmHWM_bytes": 93054033920, "Pss_bytes": 93051737088, "vram_used_bytes": 194551808, "vram_total_bytes": 4294967296, "gtt_used_bytes": 91773181952, "gtt_total_bytes": 193273528320} +{"t_s": 1083.69, "VmRSS_bytes": 93074849792, "VmHWM_bytes": 93074849792, "Pss_bytes": 93072552960, "vram_used_bytes": 194551808, "vram_total_bytes": 4294967296, "gtt_used_bytes": 91773181952, "gtt_total_bytes": 193273528320} +{"t_s": 1085.29, "VmRSS_bytes": 93074849792, "VmHWM_bytes": 93074849792, "Pss_bytes": 93072552960, "vram_used_bytes": 194551808, "vram_total_bytes": 4294967296, "gtt_used_bytes": 91773181952, "gtt_total_bytes": 193273528320} +{"t_s": 1086.77, "VmRSS_bytes": 93074849792, "VmHWM_bytes": 93074849792, "Pss_bytes": 93072557056, "vram_used_bytes": 194551808, "vram_total_bytes": 4294967296, "gtt_used_bytes": 91152424960, "gtt_total_bytes": 193273528320} +{"t_s": 1088.11, "VmRSS_bytes": 85891567616, "VmHWM_bytes": 93071581184, "Pss_bytes": 85339262976, "vram_used_bytes": 194396160, "vram_total_bytes": 4294967296, "gtt_used_bytes": 198942720, "gtt_total_bytes": 193273528320} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-32768-r1-memory-endpoint.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-32768-r1-memory-endpoint.json new file mode 100644 index 0000000000..b0eda569cf --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-32768-r1-memory-endpoint.json @@ -0,0 +1 @@ +{"schema_version": 1, "context_window": 40960, "context_fitted": false, "device": {"active_bytes": 83984338368, "cache_bytes": 0, "peak_bytes": 84062479812, "peak_scope": "since_start_or_health_reset"}} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-32768-r1-metrics.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-32768-r1-metrics.txt new file mode 100644 index 0000000000..c359dcde2f --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-32768-r1-metrics.txt @@ -0,0 +1,220 @@ +# HELP tensorfold:requests_running Requests in prefill or decode. +# TYPE tensorfold:requests_running gauge +tensorfold:requests_running 0 +# HELP tensorfold:requests_waiting Requests queued or held until a lane is free. +# TYPE tensorfold:requests_waiting gauge +tensorfold:requests_waiting 0 +# HELP tensorfold:generation_tokens_running Generated tokens held by live streams. +# TYPE tensorfold:generation_tokens_running gauge +tensorfold:generation_tokens_running 0 +# HELP tensorfold:prompt_tokens_total Prompt tokens of finished requests. +# TYPE tensorfold:prompt_tokens_total counter +tensorfold:prompt_tokens_total 33024 +# HELP tensorfold:generation_tokens_total Generated tokens of finished requests. +# TYPE tensorfold:generation_tokens_total counter +tensorfold:generation_tokens_total 2 +# HELP tensorfold:kv_cache_usage_ratio Tokens in a stream cache divided by that stream's context window. +# TYPE tensorfold:kv_cache_usage_ratio gauge +tensorfold:kv_cache_usage_ratio{pool="0"} 0 +# HELP tensorfold:mtp_drafted_total Draft tokens verified on finished requests. +# TYPE tensorfold:mtp_drafted_total counter +tensorfold:mtp_drafted_total 0 +# HELP tensorfold:mtp_accepted_total Draft tokens kept on finished requests. +# TYPE tensorfold:mtp_accepted_total counter +tensorfold:mtp_accepted_total 0 +# HELP tensorfold:request_latency_seconds Seconds from arrival to the reply leaving. +# TYPE tensorfold:request_latency_seconds histogram +tensorfold:request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:request_latency_seconds_bucket{le="1"} 0 +tensorfold:request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:request_latency_seconds_bucket{le="5"} 1 +tensorfold:request_latency_seconds_bucket{le="10"} 1 +tensorfold:request_latency_seconds_bucket{le="30"} 1 +tensorfold:request_latency_seconds_bucket{le="60"} 1 +tensorfold:request_latency_seconds_bucket{le="120"} 1 +tensorfold:request_latency_seconds_bucket{le="300"} 2 +tensorfold:request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:request_latency_seconds_sum 127.965288 +tensorfold:request_latency_seconds_count 2 +# HELP tensorfold:time_to_first_token_seconds Seconds from arrival to the first generated token. +# TYPE tensorfold:time_to_first_token_seconds histogram +tensorfold:time_to_first_token_seconds_bucket{le="0.01"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.05"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.25"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.5"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="2.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="10"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="30"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="60"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="120"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="300"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="+Inf"} 2 +tensorfold:time_to_first_token_seconds_sum 127.964988 +tensorfold:time_to_first_token_seconds_count 2 +# HELP tensorfold:request_decode_seconds Seconds a finished request spent decoding. Its sum over generation_tokens_total is the decode rate. +# TYPE tensorfold:request_decode_seconds histogram +tensorfold:request_decode_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_seconds_bucket{le="1"} 2 +tensorfold:request_decode_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_seconds_bucket{le="5"} 2 +tensorfold:request_decode_seconds_bucket{le="10"} 2 +tensorfold:request_decode_seconds_bucket{le="30"} 2 +tensorfold:request_decode_seconds_bucket{le="60"} 2 +tensorfold:request_decode_seconds_bucket{le="120"} 2 +tensorfold:request_decode_seconds_bucket{le="300"} 2 +tensorfold:request_decode_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_seconds_sum 0.0003 +tensorfold:request_decode_seconds_count 2 +# HELP tensorfold:request_time_per_output_token_seconds Seconds from the first generated token to the last, divided by the tokens less one. +# TYPE tensorfold:request_time_per_output_token_seconds histogram +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.005"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.01"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.015"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.02"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.03"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.04"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.05"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.15"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.2"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.3"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.5"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="+Inf"} 0 +tensorfold:request_time_per_output_token_seconds_sum 0 +tensorfold:request_time_per_output_token_seconds_count 0 +# HELP tensorfold:decode_rounds_total Decode rounds used by finished requests. +# TYPE tensorfold:decode_rounds_total counter +tensorfold:decode_rounds_total 0 +# HELP tensorfold:request_prefill_seconds Seconds a finished request's prompt pass took. +# TYPE tensorfold:request_prefill_seconds histogram +tensorfold:request_prefill_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.5"} 0 +tensorfold:request_prefill_seconds_bucket{le="1"} 0 +tensorfold:request_prefill_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_seconds_bucket{le="60"} 1 +tensorfold:request_prefill_seconds_bucket{le="120"} 1 +tensorfold:request_prefill_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_seconds_sum 127.963934 +tensorfold:request_prefill_seconds_count 2 +# HELP tensorfold:process_resident_bytes Current resident set (VmRSS); device memory is not in it, so it is not a physical footprint (Linux). +# TYPE tensorfold:process_resident_bytes gauge +tensorfold:process_resident_bytes 85689819136 +# HELP tensorfold:process_resident_anon_bytes Current resident anonymous memory (RssAnon): heap, stacks and private maps (Linux). +# TYPE tensorfold:process_resident_anon_bytes gauge +tensorfold:process_resident_anon_bytes 307642368 +# HELP tensorfold:process_resident_file_bytes Current resident file-backed memory (RssFile): the binary, libraries and mapped files (Linux). +# TYPE tensorfold:process_resident_file_bytes gauge +tensorfold:process_resident_file_bytes 85270274048 +# HELP tensorfold:process_resident_shmem_bytes Current resident shared memory (RssShmem): System V shared memory, tmpfs maps and shared anonymous maps (Linux). +# TYPE tensorfold:process_resident_shmem_bytes gauge +tensorfold:process_resident_shmem_bytes 111902720 +# HELP tensorfold:process_resident_peak_bytes Kernel lifetime peak resident set (VmHWM); never reset by health (Linux). +# TYPE tensorfold:process_resident_peak_bytes gauge +tensorfold:process_resident_peak_bytes 85689819136 +# HELP tensorfold:device_memory_bytes Device memory the engine holds now: weights, caches and live streams; only where the backend counts it (CUDA). +# TYPE tensorfold:device_memory_bytes gauge +tensorfold:device_memory_bytes 83984338368 +# HELP tensorfold:device_memory_peak_bytes The most device memory the engine has held since start or the last /health?reset_peak=1. +# TYPE tensorfold:device_memory_peak_bytes gauge +tensorfold:device_memory_peak_bytes 84062479812 +# HELP tensorfold:pinned_memory_bytes Pinned host memory the engine holds now: staging buffers and windows; only where the backend counts it (CUDA). +# TYPE tensorfold:pinned_memory_bytes gauge +tensorfold:pinned_memory_bytes 0 +# HELP tensorfold:num_requests_running Requests in prefill or decode. A mirror of tensorfold:requests_running. +# TYPE tensorfold:num_requests_running gauge +tensorfold:num_requests_running 0 +# HELP tensorfold:num_requests_waiting Requests queued or held until a lane is free. A mirror of tensorfold:requests_waiting. +# TYPE tensorfold:num_requests_waiting gauge +tensorfold:num_requests_waiting 0 +# HELP tensorfold:kv_cache_usage_perc A stream's cache occupancy under vLLM's name; same streams and ratios as tensorfold:kv_cache_usage_ratio. +# TYPE tensorfold:kv_cache_usage_perc gauge +tensorfold:kv_cache_usage_perc{stream="0"} 0 +# HELP tensorfold:spec_decode_num_draft_tokens_total Draft tokens verified on finished requests, this server's single draft counter. +# TYPE tensorfold:spec_decode_num_draft_tokens_total counter +tensorfold:spec_decode_num_draft_tokens_total 0 +# HELP tensorfold:spec_decode_num_accepted_tokens_total Draft tokens kept on finished requests. +# TYPE tensorfold:spec_decode_num_accepted_tokens_total counter +tensorfold:spec_decode_num_accepted_tokens_total 0 +# HELP tensorfold:e2e_request_latency_seconds Seconds from arrival to the reply leaving, under vLLM's name. +# TYPE tensorfold:e2e_request_latency_seconds histogram +tensorfold:e2e_request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="10"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="30"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="60"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="120"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="300"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:e2e_request_latency_seconds_sum 127.965288 +tensorfold:e2e_request_latency_seconds_count 2 +# HELP tensorfold:request_decode_time_seconds Seconds a finished request spent decoding, under vLLM's name. +# TYPE tensorfold:request_decode_time_seconds histogram +tensorfold:request_decode_time_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="10"} 2 +tensorfold:request_decode_time_seconds_bucket{le="30"} 2 +tensorfold:request_decode_time_seconds_bucket{le="60"} 2 +tensorfold:request_decode_time_seconds_bucket{le="120"} 2 +tensorfold:request_decode_time_seconds_bucket{le="300"} 2 +tensorfold:request_decode_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_time_seconds_sum 0.0003 +tensorfold:request_decode_time_seconds_count 2 +# HELP tensorfold:request_prefill_time_seconds Seconds a finished request's prompt pass took, under vLLM's name. +# TYPE tensorfold:request_prefill_time_seconds histogram +tensorfold:request_prefill_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.5"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="60"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="120"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_time_seconds_sum 127.963934 +tensorfold:request_prefill_time_seconds_count 2 +# HELP tensorfold:client_disconnections_total Requests a client left before the reply left the server. +# TYPE tensorfold:client_disconnections_total counter +tensorfold:client_disconnections_total 0 +# HELP tensorfold:preemptions_total Requests that had to give a lane up to a later one. +# TYPE tensorfold:preemptions_total counter +tensorfold:preemptions_total 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-32768-r1-samples.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-32768-r1-samples.jsonl new file mode 100644 index 0000000000..f595e5a55b --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-32768-r1-samples.jsonl @@ -0,0 +1,111 @@ +{"t_s": 0.0, "VmRSS_bytes": 54992896, "VmHWM_bytes": 54992896, "Pss_bytes": 53604352, 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"vram_used_bytes": 195272704, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 92.37, "VmRSS_bytes": 84770783232, "VmHWM_bytes": 84770783232, "Pss_bytes": 84768371712, "vram_used_bytes": 195272704, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 93.69, "VmRSS_bytes": 84770783232, "VmHWM_bytes": 84770783232, "Pss_bytes": 84768371712, "vram_used_bytes": 195272704, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 94.99, "VmRSS_bytes": 84770783232, "VmHWM_bytes": 84770783232, "Pss_bytes": 84774518784, "vram_used_bytes": 195272704, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 96.33, "VmRSS_bytes": 84904779776, "VmHWM_bytes": 84904779776, "Pss_bytes": 84902367232, "vram_used_bytes": 195272704, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 97.66, "VmRSS_bytes": 84904779776, "VmHWM_bytes": 84904779776, "Pss_bytes": 84902368256, "vram_used_bytes": 195272704, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 98.97, "VmRSS_bytes": 84904779776, "VmHWM_bytes": 84904779776, "Pss_bytes": 84902368256, "vram_used_bytes": 195272704, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 100.3, "VmRSS_bytes": 84967677952, "VmHWM_bytes": 84967677952, "Pss_bytes": 84965266432, "vram_used_bytes": 195272704, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 101.63, "VmRSS_bytes": 84967677952, "VmHWM_bytes": 84967677952, "Pss_bytes": 84965266432, "vram_used_bytes": 195272704, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 102.94, "VmRSS_bytes": 84967677952, "VmHWM_bytes": 84967677952, "Pss_bytes": 84966732800, "vram_used_bytes": 195272704, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 104.28, "VmRSS_bytes": 84995117056, "VmHWM_bytes": 84995117056, "Pss_bytes": 84992703488, "vram_used_bytes": 195272704, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 105.61, "VmRSS_bytes": 84995117056, "VmHWM_bytes": 84995117056, "Pss_bytes": 84992705536, "vram_used_bytes": 195272704, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 106.91, "VmRSS_bytes": 85025087488, "VmHWM_bytes": 85025087488, "Pss_bytes": 85051429888, "vram_used_bytes": 195272704, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 108.25, "VmRSS_bytes": 85067141120, "VmHWM_bytes": 85067141120, "Pss_bytes": 85064729600, "vram_used_bytes": 195272704, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 109.59, "VmRSS_bytes": 85067141120, "VmHWM_bytes": 85067141120, "Pss_bytes": 85064729600, "vram_used_bytes": 195272704, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 110.92, "VmRSS_bytes": 85109399552, "VmHWM_bytes": 85109399552, "Pss_bytes": 85106988032, "vram_used_bytes": 195272704, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 112.25, "VmRSS_bytes": 85109399552, "VmHWM_bytes": 85109399552, "Pss_bytes": 85106988032, "vram_used_bytes": 195272704, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 113.57, "VmRSS_bytes": 85109399552, "VmHWM_bytes": 85109399552, "Pss_bytes": 85107057664, "vram_used_bytes": 195272704, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 114.91, "VmRSS_bytes": 85169459200, "VmHWM_bytes": 85169459200, "Pss_bytes": 85167047680, "vram_used_bytes": 195272704, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 116.24, "VmRSS_bytes": 85169459200, "VmHWM_bytes": 85169459200, "Pss_bytes": 85167047680, "vram_used_bytes": 195272704, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 117.56, "VmRSS_bytes": 85186732032, "VmHWM_bytes": 85186732032, "Pss_bytes": 85214913536, "vram_used_bytes": 195272704, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 118.9, "VmRSS_bytes": 85242904576, "VmHWM_bytes": 85242904576, "Pss_bytes": 85240493056, "vram_used_bytes": 195272704, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 120.24, "VmRSS_bytes": 85242904576, "VmHWM_bytes": 85242904576, "Pss_bytes": 85240492032, "vram_used_bytes": 195272704, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 121.55, "VmRSS_bytes": 85272793088, "VmHWM_bytes": 85272793088, "Pss_bytes": 85297632256, "vram_used_bytes": 195272704, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 122.89, "VmRSS_bytes": 85332082688, "VmHWM_bytes": 85332082688, "Pss_bytes": 85329671168, "vram_used_bytes": 195272704, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 124.22, "VmRSS_bytes": 85332082688, "VmHWM_bytes": 85332082688, "Pss_bytes": 85329671168, "vram_used_bytes": 195272704, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 125.54, "VmRSS_bytes": 85367173120, "VmHWM_bytes": 85367173120, "Pss_bytes": 85394785280, "vram_used_bytes": 195272704, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 126.87, "VmRSS_bytes": 85445427200, "VmHWM_bytes": 85445427200, "Pss_bytes": 85443015680, "vram_used_bytes": 195272704, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 128.22, "VmRSS_bytes": 85445427200, "VmHWM_bytes": 85445427200, "Pss_bytes": 85443015680, "vram_used_bytes": 195272704, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 129.54, "VmRSS_bytes": 85455945728, "VmHWM_bytes": 85455945728, "Pss_bytes": 85478732800, "vram_used_bytes": 195272704, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 130.87, "VmRSS_bytes": 85525114880, "VmHWM_bytes": 85525114880, "Pss_bytes": 85522703360, "vram_used_bytes": 195272704, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 132.22, "VmRSS_bytes": 85525114880, "VmHWM_bytes": 85525114880, "Pss_bytes": 85522703360, "vram_used_bytes": 195272704, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 133.54, "VmRSS_bytes": 85535309824, "VmHWM_bytes": 85535309824, "Pss_bytes": 85556122624, "vram_used_bytes": 195272704, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 134.88, "VmRSS_bytes": 85616168960, "VmHWM_bytes": 85616168960, "Pss_bytes": 85613757440, "vram_used_bytes": 195272704, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 136.22, "VmRSS_bytes": 85616168960, "VmHWM_bytes": 85616168960, "Pss_bytes": 85613757440, "vram_used_bytes": 195272704, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 137.53, "VmRSS_bytes": 85616238592, "VmHWM_bytes": 85616238592, "Pss_bytes": 85634765824, "vram_used_bytes": 195272704, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 138.88, "VmRSS_bytes": 85691727872, "VmHWM_bytes": 85691727872, "Pss_bytes": 85689316352, "vram_used_bytes": 195272704, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 140.22, "VmRSS_bytes": 85691727872, "VmHWM_bytes": 85691727872, "Pss_bytes": 85689316352, "vram_used_bytes": 195272704, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 141.53, "VmRSS_bytes": 85689630720, "VmHWM_bytes": 85689630720, "Pss_bytes": 85687392256, "vram_used_bytes": 195272704, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84867260416, "gtt_total_bytes": 193273528320} +{"t_s": 142.7, "VmRSS_bytes": 56873443328, "VmHWM_bytes": 85687906304, "Pss_bytes": 56052951040, "vram_used_bytes": 195137536, "vram_total_bytes": 4294967296, "gtt_used_bytes": 198942720, "gtt_total_bytes": 193273528320} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-32768-r2-memory-endpoint.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-32768-r2-memory-endpoint.json new file mode 100644 index 0000000000..b0eda569cf --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-32768-r2-memory-endpoint.json @@ -0,0 +1 @@ +{"schema_version": 1, "context_window": 40960, "context_fitted": false, "device": {"active_bytes": 83984338368, "cache_bytes": 0, "peak_bytes": 84062479812, "peak_scope": "since_start_or_health_reset"}} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-32768-r2-metrics.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-32768-r2-metrics.txt new file mode 100644 index 0000000000..e49be59186 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-32768-r2-metrics.txt @@ -0,0 +1,220 @@ +# HELP tensorfold:requests_running Requests in prefill or decode. +# TYPE tensorfold:requests_running gauge +tensorfold:requests_running 0 +# HELP tensorfold:requests_waiting Requests queued or held until a lane is free. +# TYPE tensorfold:requests_waiting gauge +tensorfold:requests_waiting 0 +# HELP tensorfold:generation_tokens_running Generated tokens held by live streams. +# TYPE tensorfold:generation_tokens_running gauge +tensorfold:generation_tokens_running 0 +# HELP tensorfold:prompt_tokens_total Prompt tokens of finished requests. +# TYPE tensorfold:prompt_tokens_total counter +tensorfold:prompt_tokens_total 33024 +# HELP tensorfold:generation_tokens_total Generated tokens of finished requests. +# TYPE tensorfold:generation_tokens_total counter +tensorfold:generation_tokens_total 2 +# HELP tensorfold:kv_cache_usage_ratio Tokens in a stream cache divided by that stream's context window. +# TYPE tensorfold:kv_cache_usage_ratio gauge +tensorfold:kv_cache_usage_ratio{pool="0"} 0 +# HELP tensorfold:mtp_drafted_total Draft tokens verified on finished requests. +# TYPE tensorfold:mtp_drafted_total counter +tensorfold:mtp_drafted_total 0 +# HELP tensorfold:mtp_accepted_total Draft tokens kept on finished requests. +# TYPE tensorfold:mtp_accepted_total counter +tensorfold:mtp_accepted_total 0 +# HELP tensorfold:request_latency_seconds Seconds from arrival to the reply leaving. +# TYPE tensorfold:request_latency_seconds histogram +tensorfold:request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:request_latency_seconds_bucket{le="1"} 0 +tensorfold:request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:request_latency_seconds_bucket{le="5"} 1 +tensorfold:request_latency_seconds_bucket{le="10"} 1 +tensorfold:request_latency_seconds_bucket{le="30"} 1 +tensorfold:request_latency_seconds_bucket{le="60"} 1 +tensorfold:request_latency_seconds_bucket{le="120"} 1 +tensorfold:request_latency_seconds_bucket{le="300"} 2 +tensorfold:request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:request_latency_seconds_sum 127.687612 +tensorfold:request_latency_seconds_count 2 +# HELP tensorfold:time_to_first_token_seconds Seconds from arrival to the first generated token. +# TYPE tensorfold:time_to_first_token_seconds histogram +tensorfold:time_to_first_token_seconds_bucket{le="0.01"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.05"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.25"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.5"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="2.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="10"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="30"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="60"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="120"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="300"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="+Inf"} 2 +tensorfold:time_to_first_token_seconds_sum 127.687301 +tensorfold:time_to_first_token_seconds_count 2 +# HELP tensorfold:request_decode_seconds Seconds a finished request spent decoding. Its sum over generation_tokens_total is the decode rate. +# TYPE tensorfold:request_decode_seconds histogram +tensorfold:request_decode_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_seconds_bucket{le="1"} 2 +tensorfold:request_decode_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_seconds_bucket{le="5"} 2 +tensorfold:request_decode_seconds_bucket{le="10"} 2 +tensorfold:request_decode_seconds_bucket{le="30"} 2 +tensorfold:request_decode_seconds_bucket{le="60"} 2 +tensorfold:request_decode_seconds_bucket{le="120"} 2 +tensorfold:request_decode_seconds_bucket{le="300"} 2 +tensorfold:request_decode_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_seconds_sum 0.000311 +tensorfold:request_decode_seconds_count 2 +# HELP tensorfold:request_time_per_output_token_seconds Seconds from the first generated token to the last, divided by the tokens less one. +# TYPE tensorfold:request_time_per_output_token_seconds histogram +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.005"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.01"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.015"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.02"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.03"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.04"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.05"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.15"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.2"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.3"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.5"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="+Inf"} 0 +tensorfold:request_time_per_output_token_seconds_sum 0 +tensorfold:request_time_per_output_token_seconds_count 0 +# HELP tensorfold:decode_rounds_total Decode rounds used by finished requests. +# TYPE tensorfold:decode_rounds_total counter +tensorfold:decode_rounds_total 0 +# HELP tensorfold:request_prefill_seconds Seconds a finished request's prompt pass took. +# TYPE tensorfold:request_prefill_seconds histogram +tensorfold:request_prefill_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.5"} 0 +tensorfold:request_prefill_seconds_bucket{le="1"} 0 +tensorfold:request_prefill_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_seconds_bucket{le="60"} 1 +tensorfold:request_prefill_seconds_bucket{le="120"} 1 +tensorfold:request_prefill_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_seconds_sum 127.685412 +tensorfold:request_prefill_seconds_count 2 +# HELP tensorfold:process_resident_bytes Current resident set (VmRSS); device memory is not in it, so it is not a physical footprint (Linux). +# TYPE tensorfold:process_resident_bytes gauge +tensorfold:process_resident_bytes 85686591488 +# HELP tensorfold:process_resident_anon_bytes Current resident anonymous memory (RssAnon): heap, stacks and private maps (Linux). +# TYPE tensorfold:process_resident_anon_bytes gauge +tensorfold:process_resident_anon_bytes 306556928 +# HELP tensorfold:process_resident_file_bytes Current resident file-backed memory (RssFile): the binary, libraries and mapped files (Linux). +# TYPE tensorfold:process_resident_file_bytes gauge +tensorfold:process_resident_file_bytes 85268131840 +# HELP tensorfold:process_resident_shmem_bytes Current resident shared memory (RssShmem): System V shared memory, tmpfs maps and shared anonymous maps (Linux). +# TYPE tensorfold:process_resident_shmem_bytes gauge +tensorfold:process_resident_shmem_bytes 111902720 +# HELP tensorfold:process_resident_peak_bytes Kernel lifetime peak resident set (VmHWM); never reset by health (Linux). +# TYPE tensorfold:process_resident_peak_bytes gauge +tensorfold:process_resident_peak_bytes 85686591488 +# HELP tensorfold:device_memory_bytes Device memory the engine holds now: weights, caches and live streams; only where the backend counts it (CUDA). +# TYPE tensorfold:device_memory_bytes gauge +tensorfold:device_memory_bytes 83984338368 +# HELP tensorfold:device_memory_peak_bytes The most device memory the engine has held since start or the last /health?reset_peak=1. +# TYPE tensorfold:device_memory_peak_bytes gauge +tensorfold:device_memory_peak_bytes 84062479812 +# HELP tensorfold:pinned_memory_bytes Pinned host memory the engine holds now: staging buffers and windows; only where the backend counts it (CUDA). +# TYPE tensorfold:pinned_memory_bytes gauge +tensorfold:pinned_memory_bytes 0 +# HELP tensorfold:num_requests_running Requests in prefill or decode. A mirror of tensorfold:requests_running. +# TYPE tensorfold:num_requests_running gauge +tensorfold:num_requests_running 0 +# HELP tensorfold:num_requests_waiting Requests queued or held until a lane is free. A mirror of tensorfold:requests_waiting. +# TYPE tensorfold:num_requests_waiting gauge +tensorfold:num_requests_waiting 0 +# HELP tensorfold:kv_cache_usage_perc A stream's cache occupancy under vLLM's name; same streams and ratios as tensorfold:kv_cache_usage_ratio. +# TYPE tensorfold:kv_cache_usage_perc gauge +tensorfold:kv_cache_usage_perc{stream="0"} 0 +# HELP tensorfold:spec_decode_num_draft_tokens_total Draft tokens verified on finished requests, this server's single draft counter. +# TYPE tensorfold:spec_decode_num_draft_tokens_total counter +tensorfold:spec_decode_num_draft_tokens_total 0 +# HELP tensorfold:spec_decode_num_accepted_tokens_total Draft tokens kept on finished requests. +# TYPE tensorfold:spec_decode_num_accepted_tokens_total counter +tensorfold:spec_decode_num_accepted_tokens_total 0 +# HELP tensorfold:e2e_request_latency_seconds Seconds from arrival to the reply leaving, under vLLM's name. +# TYPE tensorfold:e2e_request_latency_seconds histogram +tensorfold:e2e_request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="10"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="30"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="60"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="120"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="300"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:e2e_request_latency_seconds_sum 127.687612 +tensorfold:e2e_request_latency_seconds_count 2 +# HELP tensorfold:request_decode_time_seconds Seconds a finished request spent decoding, under vLLM's name. +# TYPE tensorfold:request_decode_time_seconds histogram +tensorfold:request_decode_time_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="10"} 2 +tensorfold:request_decode_time_seconds_bucket{le="30"} 2 +tensorfold:request_decode_time_seconds_bucket{le="60"} 2 +tensorfold:request_decode_time_seconds_bucket{le="120"} 2 +tensorfold:request_decode_time_seconds_bucket{le="300"} 2 +tensorfold:request_decode_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_time_seconds_sum 0.000311 +tensorfold:request_decode_time_seconds_count 2 +# HELP tensorfold:request_prefill_time_seconds Seconds a finished request's prompt pass took, under vLLM's name. +# TYPE tensorfold:request_prefill_time_seconds histogram +tensorfold:request_prefill_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.5"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="60"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="120"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_time_seconds_sum 127.685412 +tensorfold:request_prefill_time_seconds_count 2 +# HELP tensorfold:client_disconnections_total Requests a client left before the reply left the server. +# TYPE tensorfold:client_disconnections_total counter +tensorfold:client_disconnections_total 0 +# HELP tensorfold:preemptions_total Requests that had to give a lane up to a later one. +# TYPE tensorfold:preemptions_total counter +tensorfold:preemptions_total 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-32768-r2-samples.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-32768-r2-samples.jsonl new file mode 100644 index 0000000000..21c11408e2 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-32768-r2-samples.jsonl @@ -0,0 +1,109 @@ +{"t_s": 0.0, "VmRSS_bytes": 46084096, "VmHWM_bytes": 46084096, "Pss_bytes": 44343296, "vram_used_bytes": 187670528, "vram_total_bytes": 4294967296, "gtt_used_bytes": 31657984, "gtt_total_bytes": 193273528320} +{"t_s": 1.03, "VmRSS_bytes": 8015114240, "VmHWM_bytes": 8015114240, "Pss_bytes": 8037271552, "vram_used_bytes": 188698624, "vram_total_bytes": 4294967296, "gtt_used_bytes": 5181775872, "gtt_total_bytes": 193273528320} +{"t_s": 2.09, "VmRSS_bytes": 15253852160, "VmHWM_bytes": 15253852160, "Pss_bytes": 15445940224, "vram_used_bytes": 189194240, "vram_total_bytes": 4294967296, "gtt_used_bytes": 13375348736, "gtt_total_bytes": 193273528320} +{"t_s": 3.17, "VmRSS_bytes": 22828838912, "VmHWM_bytes": 22828838912, "Pss_bytes": 22894905344, "vram_used_bytes": 189640704, "vram_total_bytes": 4294967296, "gtt_used_bytes": 19935240192, "gtt_total_bytes": 193273528320} +{"t_s": 4.29, "VmRSS_bytes": 29700538368, "VmHWM_bytes": 29700538368, "Pss_bytes": 29698118656, "vram_used_bytes": 190205952, "vram_total_bytes": 4294967296, "gtt_used_bytes": 28124618752, "gtt_total_bytes": 193273528320} +{"t_s": 5.44, "VmRSS_bytes": 37865009152, "VmHWM_bytes": 37865009152, "Pss_bytes": 37930288128, "vram_used_bytes": 190799872, "vram_total_bytes": 4294967296, "gtt_used_bytes": 36318191616, "gtt_total_bytes": 193273528320} +{"t_s": 6.6, "VmRSS_bytes": 45875957760, "VmHWM_bytes": 45875957760, "Pss_bytes": 45873538048, "vram_used_bytes": 191246336, "vram_total_bytes": 4294967296, "gtt_used_bytes": 43719041024, "gtt_total_bytes": 193273528320} +{"t_s": 7.79, "VmRSS_bytes": 52725735424, "VmHWM_bytes": 52725735424, "Pss_bytes": 52753462272, "vram_used_bytes": 191815680, "vram_total_bytes": 4294967296, "gtt_used_bytes": 51067461632, "gtt_total_bytes": 193273528320} +{"t_s": 9.0, "VmRSS_bytes": 60734152704, "VmHWM_bytes": 60734152704, "Pss_bytes": 60780950528, "vram_used_bytes": 192380928, "vram_total_bytes": 4294967296, "gtt_used_bytes": 59261034496, "gtt_total_bytes": 193273528320} +{"t_s": 10.24, "VmRSS_bytes": 68630663168, "VmHWM_bytes": 68630663168, "Pss_bytes": 68628243456, "vram_used_bytes": 192954368, "vram_total_bytes": 4294967296, "gtt_used_bytes": 67456704512, "gtt_total_bytes": 193273528320} +{"t_s": 11.51, "VmRSS_bytes": 76741574656, "VmHWM_bytes": 76741574656, "Pss_bytes": 76739154944, "vram_used_bytes": 193527808, "vram_total_bytes": 4294967296, "gtt_used_bytes": 75650277376, "gtt_total_bytes": 193273528320} +{"t_s": 12.77, "VmRSS_bytes": 80822206464, "VmHWM_bytes": 82470707200, "Pss_bytes": 80819786752, "vram_used_bytes": 195497984, "vram_total_bytes": 4294967296, "gtt_used_bytes": 83107749888, "gtt_total_bytes": 193273528320} +{"t_s": 14.04, "VmRSS_bytes": 80866263040, "VmHWM_bytes": 82470707200, "Pss_bytes": 80922440704, "vram_used_bytes": 195276800, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84867260416, "gtt_total_bytes": 193273528320} +{"t_s": 15.32, "VmRSS_bytes": 81033568256, "VmHWM_bytes": 82470707200, "Pss_bytes": 81113814016, "vram_used_bytes": 195268608, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 16.64, "VmRSS_bytes": 81418752000, "VmHWM_bytes": 82470707200, "Pss_bytes": 81416328192, "vram_used_bytes": 195268608, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 17.96, "VmRSS_bytes": 81418752000, "VmHWM_bytes": 82470707200, "Pss_bytes": 81416328192, "vram_used_bytes": 195268608, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 19.24, "VmRSS_bytes": 81675296768, "VmHWM_bytes": 82470707200, "Pss_bytes": 81756935168, "vram_used_bytes": 195268608, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 20.55, "VmRSS_bytes": 81810141184, "VmHWM_bytes": 82470707200, "Pss_bytes": 81807717376, "vram_used_bytes": 195268608, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 21.86, "VmRSS_bytes": 81810141184, "VmHWM_bytes": 82470707200, "Pss_bytes": 81807717376, "vram_used_bytes": 195268608, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 23.15, "VmRSS_bytes": 82069807104, "VmHWM_bytes": 82470707200, "Pss_bytes": 82141094912, "vram_used_bytes": 195268608, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 24.46, "VmRSS_bytes": 82208051200, "VmHWM_bytes": 82470707200, "Pss_bytes": 82205628416, "vram_used_bytes": 195268608, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 25.77, "VmRSS_bytes": 82208051200, "VmHWM_bytes": 82470707200, "Pss_bytes": 82205628416, "vram_used_bytes": 195268608, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 27.06, "VmRSS_bytes": 82320449536, "VmHWM_bytes": 82470707200, "Pss_bytes": 82381580288, "vram_used_bytes": 195268608, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 28.37, "VmRSS_bytes": 82555113472, "VmHWM_bytes": 82555113472, "Pss_bytes": 82552690688, "vram_used_bytes": 195268608, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 29.69, "VmRSS_bytes": 82555113472, "VmHWM_bytes": 82555113472, "Pss_bytes": 82552690688, "vram_used_bytes": 195268608, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 30.98, "VmRSS_bytes": 82566803456, "VmHWM_bytes": 82566803456, "Pss_bytes": 82615248896, "vram_used_bytes": 195268608, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 32.3, "VmRSS_bytes": 82752024576, "VmHWM_bytes": 82752024576, "Pss_bytes": 82749601792, "vram_used_bytes": 195268608, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 33.62, "VmRSS_bytes": 82752024576, "VmHWM_bytes": 82752024576, "Pss_bytes": 82749601792, "vram_used_bytes": 195268608, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 34.91, "VmRSS_bytes": 82766864384, "VmHWM_bytes": 82766864384, "Pss_bytes": 82816182272, "vram_used_bytes": 195268608, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 36.22, "VmRSS_bytes": 83033284608, "VmHWM_bytes": 83033284608, "Pss_bytes": 83068557312, "vram_used_bytes": 195268608, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 37.55, "VmRSS_bytes": 83070980096, "VmHWM_bytes": 83070980096, "Pss_bytes": 83068557312, "vram_used_bytes": 195268608, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 38.86, "VmRSS_bytes": 83070980096, "VmHWM_bytes": 83070980096, "Pss_bytes": 83068557312, "vram_used_bytes": 195268608, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 40.18, "VmRSS_bytes": 83184275456, "VmHWM_bytes": 83184275456, "Pss_bytes": 83181852672, "vram_used_bytes": 195268608, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 41.5, "VmRSS_bytes": 83184275456, "VmHWM_bytes": 83184275456, "Pss_bytes": 83181852672, "vram_used_bytes": 195268608, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 42.8, "VmRSS_bytes": 83184275456, "VmHWM_bytes": 83184275456, "Pss_bytes": 83199019008, "vram_used_bytes": 195268608, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 44.11, "VmRSS_bytes": 83281346560, "VmHWM_bytes": 83281346560, "Pss_bytes": 83278923776, "vram_used_bytes": 195268608, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 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"gtt_total_bytes": 193273528320} +{"t_s": 140.14, "VmRSS_bytes": 85688500224, "VmHWM_bytes": 85688500224, "Pss_bytes": 85686078464, "vram_used_bytes": 195268608, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84946952192, "gtt_total_bytes": 193273528320} +{"t_s": 141.48, "VmRSS_bytes": 85686403072, "VmHWM_bytes": 85686403072, "Pss_bytes": 85683992576, "vram_used_bytes": 195268608, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84867260416, "gtt_total_bytes": 193273528320} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-65536-r1-memory-endpoint.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-65536-r1-memory-endpoint.json new file mode 100644 index 0000000000..ae37e72b48 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-65536-r1-memory-endpoint.json @@ -0,0 +1 @@ +{"schema_version": 1, "context_window": 73728, "context_fitted": false, "device": {"active_bytes": 84915473856, "cache_bytes": 0, "peak_bytes": 85071209924, "peak_scope": "since_start_or_health_reset"}} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-65536-r1-metrics.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-65536-r1-metrics.txt new file mode 100644 index 0000000000..41e3daad55 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-65536-r1-metrics.txt @@ -0,0 +1,220 @@ +# HELP tensorfold:requests_running Requests in prefill or decode. +# TYPE tensorfold:requests_running gauge +tensorfold:requests_running 0 +# HELP tensorfold:requests_waiting Requests queued or held until a lane is free. +# TYPE tensorfold:requests_waiting gauge +tensorfold:requests_waiting 0 +# HELP tensorfold:generation_tokens_running Generated tokens held by live streams. +# TYPE tensorfold:generation_tokens_running gauge +tensorfold:generation_tokens_running 0 +# HELP tensorfold:prompt_tokens_total Prompt tokens of finished requests. +# TYPE tensorfold:prompt_tokens_total counter +tensorfold:prompt_tokens_total 65792 +# HELP tensorfold:generation_tokens_total Generated tokens of finished requests. +# TYPE tensorfold:generation_tokens_total counter +tensorfold:generation_tokens_total 2 +# HELP tensorfold:kv_cache_usage_ratio Tokens in a stream cache divided by that stream's context window. +# TYPE tensorfold:kv_cache_usage_ratio gauge +tensorfold:kv_cache_usage_ratio{pool="0"} 0 +# HELP tensorfold:mtp_drafted_total Draft tokens verified on finished requests. +# TYPE tensorfold:mtp_drafted_total counter +tensorfold:mtp_drafted_total 0 +# HELP tensorfold:mtp_accepted_total Draft tokens kept on finished requests. +# TYPE tensorfold:mtp_accepted_total counter +tensorfold:mtp_accepted_total 0 +# HELP tensorfold:request_latency_seconds Seconds from arrival to the reply leaving. +# TYPE tensorfold:request_latency_seconds histogram +tensorfold:request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:request_latency_seconds_bucket{le="1"} 0 +tensorfold:request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:request_latency_seconds_bucket{le="5"} 1 +tensorfold:request_latency_seconds_bucket{le="10"} 1 +tensorfold:request_latency_seconds_bucket{le="30"} 1 +tensorfold:request_latency_seconds_bucket{le="60"} 1 +tensorfold:request_latency_seconds_bucket{le="120"} 1 +tensorfold:request_latency_seconds_bucket{le="300"} 2 +tensorfold:request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:request_latency_seconds_sum 254.837831 +tensorfold:request_latency_seconds_count 2 +# HELP tensorfold:time_to_first_token_seconds Seconds from arrival to the first generated token. +# TYPE tensorfold:time_to_first_token_seconds histogram +tensorfold:time_to_first_token_seconds_bucket{le="0.01"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.05"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.25"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.5"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="2.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="10"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="30"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="60"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="120"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="300"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="+Inf"} 2 +tensorfold:time_to_first_token_seconds_sum 254.837554 +tensorfold:time_to_first_token_seconds_count 2 +# HELP tensorfold:request_decode_seconds Seconds a finished request spent decoding. Its sum over generation_tokens_total is the decode rate. +# TYPE tensorfold:request_decode_seconds histogram +tensorfold:request_decode_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_seconds_bucket{le="1"} 2 +tensorfold:request_decode_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_seconds_bucket{le="5"} 2 +tensorfold:request_decode_seconds_bucket{le="10"} 2 +tensorfold:request_decode_seconds_bucket{le="30"} 2 +tensorfold:request_decode_seconds_bucket{le="60"} 2 +tensorfold:request_decode_seconds_bucket{le="120"} 2 +tensorfold:request_decode_seconds_bucket{le="300"} 2 +tensorfold:request_decode_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_seconds_sum 0.000278 +tensorfold:request_decode_seconds_count 2 +# HELP tensorfold:request_time_per_output_token_seconds Seconds from the first generated token to the last, divided by the tokens less one. +# TYPE tensorfold:request_time_per_output_token_seconds histogram +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.005"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.01"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.015"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.02"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.03"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.04"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.05"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.15"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.2"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.3"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.5"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="+Inf"} 0 +tensorfold:request_time_per_output_token_seconds_sum 0 +tensorfold:request_time_per_output_token_seconds_count 0 +# HELP tensorfold:decode_rounds_total Decode rounds used by finished requests. +# TYPE tensorfold:decode_rounds_total counter +tensorfold:decode_rounds_total 0 +# HELP tensorfold:request_prefill_seconds Seconds a finished request's prompt pass took. +# TYPE tensorfold:request_prefill_seconds histogram +tensorfold:request_prefill_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.5"} 0 +tensorfold:request_prefill_seconds_bucket{le="1"} 0 +tensorfold:request_prefill_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_seconds_bucket{le="60"} 1 +tensorfold:request_prefill_seconds_bucket{le="120"} 1 +tensorfold:request_prefill_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_seconds_sum 254.836515 +tensorfold:request_prefill_seconds_count 2 +# HELP tensorfold:process_resident_bytes Current resident set (VmRSS); device memory is not in it, so it is not a physical footprint (Linux). +# TYPE tensorfold:process_resident_bytes gauge +tensorfold:process_resident_bytes 87664140288 +# HELP tensorfold:process_resident_anon_bytes Current resident anonymous memory (RssAnon): heap, stacks and private maps (Linux). +# TYPE tensorfold:process_resident_anon_bytes gauge +tensorfold:process_resident_anon_bytes 305688576 +# HELP tensorfold:process_resident_file_bytes Current resident file-backed memory (RssFile): the binary, libraries and mapped files (Linux). +# TYPE tensorfold:process_resident_file_bytes gauge +tensorfold:process_resident_file_bytes 87246548992 +# HELP tensorfold:process_resident_shmem_bytes Current resident shared memory (RssShmem): System V shared memory, tmpfs maps and shared anonymous maps (Linux). +# TYPE tensorfold:process_resident_shmem_bytes gauge +tensorfold:process_resident_shmem_bytes 111902720 +# HELP tensorfold:process_resident_peak_bytes Kernel lifetime peak resident set (VmHWM); never reset by health (Linux). +# TYPE tensorfold:process_resident_peak_bytes gauge +tensorfold:process_resident_peak_bytes 87664140288 +# HELP tensorfold:device_memory_bytes Device memory the engine holds now: weights, caches and live streams; only where the backend counts it (CUDA). +# TYPE tensorfold:device_memory_bytes gauge +tensorfold:device_memory_bytes 84915473856 +# HELP tensorfold:device_memory_peak_bytes The most device memory the engine has held since start or the last /health?reset_peak=1. +# TYPE tensorfold:device_memory_peak_bytes gauge +tensorfold:device_memory_peak_bytes 85071209924 +# HELP tensorfold:pinned_memory_bytes Pinned host memory the engine holds now: staging buffers and windows; only where the backend counts it (CUDA). +# TYPE tensorfold:pinned_memory_bytes gauge +tensorfold:pinned_memory_bytes 0 +# HELP tensorfold:num_requests_running Requests in prefill or decode. A mirror of tensorfold:requests_running. +# TYPE tensorfold:num_requests_running gauge +tensorfold:num_requests_running 0 +# HELP tensorfold:num_requests_waiting Requests queued or held until a lane is free. A mirror of tensorfold:requests_waiting. +# TYPE tensorfold:num_requests_waiting gauge +tensorfold:num_requests_waiting 0 +# HELP tensorfold:kv_cache_usage_perc A stream's cache occupancy under vLLM's name; same streams and ratios as tensorfold:kv_cache_usage_ratio. +# TYPE tensorfold:kv_cache_usage_perc gauge +tensorfold:kv_cache_usage_perc{stream="0"} 0 +# HELP tensorfold:spec_decode_num_draft_tokens_total Draft tokens verified on finished requests, this server's single draft counter. +# TYPE tensorfold:spec_decode_num_draft_tokens_total counter +tensorfold:spec_decode_num_draft_tokens_total 0 +# HELP tensorfold:spec_decode_num_accepted_tokens_total Draft tokens kept on finished requests. +# TYPE tensorfold:spec_decode_num_accepted_tokens_total counter +tensorfold:spec_decode_num_accepted_tokens_total 0 +# HELP tensorfold:e2e_request_latency_seconds Seconds from arrival to the reply leaving, under vLLM's name. +# TYPE tensorfold:e2e_request_latency_seconds histogram +tensorfold:e2e_request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="10"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="30"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="60"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="120"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="300"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:e2e_request_latency_seconds_sum 254.837831 +tensorfold:e2e_request_latency_seconds_count 2 +# HELP tensorfold:request_decode_time_seconds Seconds a finished request spent decoding, under vLLM's name. +# TYPE tensorfold:request_decode_time_seconds histogram +tensorfold:request_decode_time_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="10"} 2 +tensorfold:request_decode_time_seconds_bucket{le="30"} 2 +tensorfold:request_decode_time_seconds_bucket{le="60"} 2 +tensorfold:request_decode_time_seconds_bucket{le="120"} 2 +tensorfold:request_decode_time_seconds_bucket{le="300"} 2 +tensorfold:request_decode_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_time_seconds_sum 0.000278 +tensorfold:request_decode_time_seconds_count 2 +# HELP tensorfold:request_prefill_time_seconds Seconds a finished request's prompt pass took, under vLLM's name. +# TYPE tensorfold:request_prefill_time_seconds histogram +tensorfold:request_prefill_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.5"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="60"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="120"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_time_seconds_sum 254.836515 +tensorfold:request_prefill_time_seconds_count 2 +# HELP tensorfold:client_disconnections_total Requests a client left before the reply left the server. +# TYPE tensorfold:client_disconnections_total counter +tensorfold:client_disconnections_total 0 +# HELP tensorfold:preemptions_total Requests that had to give a lane up to a later one. +# TYPE tensorfold:preemptions_total counter +tensorfold:preemptions_total 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-65536-r1-samples.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-65536-r1-samples.jsonl new file mode 100644 index 0000000000..5ff8276684 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-65536-r1-samples.jsonl @@ -0,0 +1,216 @@ +{"t_s": 0.0, "VmRSS_bytes": 40337408, "VmHWM_bytes": 40337408, "Pss_bytes": 38744064, "vram_used_bytes": 187670528, "vram_total_bytes": 4294967296, "gtt_used_bytes": 31657984, "gtt_total_bytes": 193273528320} +{"t_s": 1.02, "VmRSS_bytes": 6112182272, "VmHWM_bytes": 6112182272, "Pss_bytes": 6133436416, "vram_used_bytes": 188604416, "vram_total_bytes": 4294967296, "gtt_used_bytes": 3545997312, "gtt_total_bytes": 193273528320} +{"t_s": 2.06, "VmRSS_bytes": 13437079552, "VmHWM_bytes": 13437079552, "Pss_bytes": 13434740736, "vram_used_bytes": 188968960, "vram_total_bytes": 4294967296, "gtt_used_bytes": 10948943872, "gtt_total_bytes": 193273528320} +{"t_s": 3.12, "VmRSS_bytes": 21543518208, "VmHWM_bytes": 21543518208, "Pss_bytes": 21541179392, "vram_used_bytes": 189476864, "vram_total_bytes": 4294967296, "gtt_used_bytes": 19136225280, "gtt_total_bytes": 193273528320} +{"t_s": 4.19, "VmRSS_bytes": 29532983296, "VmHWM_bytes": 29532983296, "Pss_bytes": 29547356160, "vram_used_bytes": 190013440, "vram_total_bytes": 4294967296, "gtt_used_bytes": 26490937344, "gtt_total_bytes": 193273528320} +{"t_s": 5.27, "VmRSS_bytes": 37766541312, "VmHWM_bytes": 37766541312, "Pss_bytes": 37764202496, "vram_used_bytes": 190525440, "vram_total_bytes": 4294967296, "gtt_used_bytes": 35632422912, "gtt_total_bytes": 193273528320} +{"t_s": 6.37, "VmRSS_bytes": 45877288960, "VmHWM_bytes": 45877288960, "Pss_bytes": 45874950144, "vram_used_bytes": 191057920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 44409004032, "gtt_total_bytes": 193273528320} +{"t_s": 7.5, "VmRSS_bytes": 52409614336, "VmHWM_bytes": 52409614336, "Pss_bytes": 52407275520, "vram_used_bytes": 191586304, "vram_total_bytes": 4294967296, "gtt_used_bytes": 51061170176, "gtt_total_bytes": 193273528320} +{"t_s": 8.65, "VmRSS_bytes": 58382118912, "VmHWM_bytes": 58382118912, "Pss_bytes": 58398654464, "vram_used_bytes": 191901696, "vram_total_bytes": 4294967296, "gtt_used_bytes": 55987380224, "gtt_total_bytes": 193273528320} +{"t_s": 9.81, "VmRSS_bytes": 66372063232, "VmHWM_bytes": 66372063232, "Pss_bytes": 66397511680, "vram_used_bytes": 192454656, "vram_total_bytes": 4294967296, "gtt_used_bytes": 64176758784, "gtt_total_bytes": 193273528320} +{"t_s": 10.98, "VmRSS_bytes": 74761027584, "VmHWM_bytes": 74761027584, "Pss_bytes": 74772058112, "vram_used_bytes": 193007616, "vram_total_bytes": 4294967296, "gtt_used_bytes": 72370331648, "gtt_total_bytes": 193273528320} +{"t_s": 12.17, "VmRSS_bytes": 80813780992, "VmHWM_bytes": 82470862848, "Pss_bytes": 80818704384, "vram_used_bytes": 194367488, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84139548672, "gtt_total_bytes": 193273528320} +{"t_s": 13.36, "VmRSS_bytes": 80827531264, "VmHWM_bytes": 82470862848, "Pss_bytes": 80834494464, "vram_used_bytes": 194383872, "vram_total_bytes": 4294967296, "gtt_used_bytes": 85798395904, "gtt_total_bytes": 193273528320} +{"t_s": 14.56, "VmRSS_bytes": 81008685056, "VmHWM_bytes": 82470862848, "Pss_bytes": 81026973696, "vram_used_bytes": 194383872, "vram_total_bytes": 4294967296, "gtt_used_bytes": 85798395904, "gtt_total_bytes": 193273528320} +{"t_s": 15.76, "VmRSS_bytes": 81154523136, "VmHWM_bytes": 82470862848, "Pss_bytes": 81209008128, "vram_used_bytes": 194383872, "vram_total_bytes": 4294967296, "gtt_used_bytes": 85955682304, "gtt_total_bytes": 193273528320} +{"t_s": 16.98, "VmRSS_bytes": 81423851520, "VmHWM_bytes": 82470862848, "Pss_bytes": 81421507584, "vram_used_bytes": 194383872, "vram_total_bytes": 4294967296, "gtt_used_bytes": 85955682304, "gtt_total_bytes": 193273528320} +{"t_s": 18.2, "VmRSS_bytes": 81424433152, "VmHWM_bytes": 82470862848, "Pss_bytes": 81422090240, "vram_used_bytes": 194383872, "vram_total_bytes": 4294967296, "gtt_used_bytes": 85955682304, "gtt_total_bytes": 193273528320} +{"t_s": 19.4, "VmRSS_bytes": 81706938368, "VmHWM_bytes": 82470862848, "Pss_bytes": 81762988032, "vram_used_bytes": 194383872, "vram_total_bytes": 4294967296, "gtt_used_bytes": 85955682304, "gtt_total_bytes": 193273528320} +{"t_s": 20.63, "VmRSS_bytes": 81818501120, "VmHWM_bytes": 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@@ +{"schema_version": 1, "context_window": 73728, "context_fitted": false, "device": {"active_bytes": 84915473856, "cache_bytes": 0, "peak_bytes": 85071209924, "peak_scope": "since_start_or_health_reset"}} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-65536-r2-metrics.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-65536-r2-metrics.txt new file mode 100644 index 0000000000..704a254d8e --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-65536-r2-metrics.txt @@ -0,0 +1,220 @@ +# HELP tensorfold:requests_running Requests in prefill or decode. +# TYPE tensorfold:requests_running gauge +tensorfold:requests_running 0 +# HELP tensorfold:requests_waiting Requests queued or held until a lane is free. +# TYPE tensorfold:requests_waiting gauge +tensorfold:requests_waiting 0 +# HELP tensorfold:generation_tokens_running Generated tokens held by live streams. +# TYPE tensorfold:generation_tokens_running gauge +tensorfold:generation_tokens_running 0 +# HELP tensorfold:prompt_tokens_total Prompt tokens of finished requests. +# TYPE tensorfold:prompt_tokens_total counter +tensorfold:prompt_tokens_total 65792 +# HELP tensorfold:generation_tokens_total Generated tokens of finished requests. +# TYPE tensorfold:generation_tokens_total counter +tensorfold:generation_tokens_total 2 +# HELP tensorfold:kv_cache_usage_ratio Tokens in a stream cache divided by that stream's context window. +# TYPE tensorfold:kv_cache_usage_ratio gauge +tensorfold:kv_cache_usage_ratio{pool="0"} 0 +# HELP tensorfold:mtp_drafted_total Draft tokens verified on finished requests. +# TYPE tensorfold:mtp_drafted_total counter +tensorfold:mtp_drafted_total 0 +# HELP tensorfold:mtp_accepted_total Draft tokens kept on finished requests. +# TYPE tensorfold:mtp_accepted_total counter +tensorfold:mtp_accepted_total 0 +# HELP tensorfold:request_latency_seconds Seconds from arrival to the reply leaving. +# TYPE tensorfold:request_latency_seconds histogram +tensorfold:request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:request_latency_seconds_bucket{le="1"} 0 +tensorfold:request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:request_latency_seconds_bucket{le="5"} 1 +tensorfold:request_latency_seconds_bucket{le="10"} 1 +tensorfold:request_latency_seconds_bucket{le="30"} 1 +tensorfold:request_latency_seconds_bucket{le="60"} 1 +tensorfold:request_latency_seconds_bucket{le="120"} 1 +tensorfold:request_latency_seconds_bucket{le="300"} 2 +tensorfold:request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:request_latency_seconds_sum 254.7149 +tensorfold:request_latency_seconds_count 2 +# HELP tensorfold:time_to_first_token_seconds Seconds from arrival to the first generated token. +# TYPE tensorfold:time_to_first_token_seconds histogram +tensorfold:time_to_first_token_seconds_bucket{le="0.01"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.05"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.25"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.5"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="2.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="10"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="30"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="60"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="120"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="300"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="+Inf"} 2 +tensorfold:time_to_first_token_seconds_sum 254.714505 +tensorfold:time_to_first_token_seconds_count 2 +# HELP tensorfold:request_decode_seconds Seconds a finished request spent decoding. Its sum over generation_tokens_total is the decode rate. +# TYPE tensorfold:request_decode_seconds histogram +tensorfold:request_decode_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_seconds_bucket{le="1"} 2 +tensorfold:request_decode_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_seconds_bucket{le="5"} 2 +tensorfold:request_decode_seconds_bucket{le="10"} 2 +tensorfold:request_decode_seconds_bucket{le="30"} 2 +tensorfold:request_decode_seconds_bucket{le="60"} 2 +tensorfold:request_decode_seconds_bucket{le="120"} 2 +tensorfold:request_decode_seconds_bucket{le="300"} 2 +tensorfold:request_decode_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_seconds_sum 0.000395 +tensorfold:request_decode_seconds_count 2 +# HELP tensorfold:request_time_per_output_token_seconds Seconds from the first generated token to the last, divided by the tokens less one. +# TYPE tensorfold:request_time_per_output_token_seconds histogram +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.005"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.01"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.015"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.02"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.03"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.04"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.05"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.15"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.2"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.3"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.5"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="+Inf"} 0 +tensorfold:request_time_per_output_token_seconds_sum 0 +tensorfold:request_time_per_output_token_seconds_count 0 +# HELP tensorfold:decode_rounds_total Decode rounds used by finished requests. +# TYPE tensorfold:decode_rounds_total counter +tensorfold:decode_rounds_total 0 +# HELP tensorfold:request_prefill_seconds Seconds a finished request's prompt pass took. +# TYPE tensorfold:request_prefill_seconds histogram +tensorfold:request_prefill_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.5"} 0 +tensorfold:request_prefill_seconds_bucket{le="1"} 0 +tensorfold:request_prefill_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_seconds_bucket{le="60"} 1 +tensorfold:request_prefill_seconds_bucket{le="120"} 1 +tensorfold:request_prefill_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_seconds_sum 254.712666 +tensorfold:request_prefill_seconds_count 2 +# HELP tensorfold:process_resident_bytes Current resident set (VmRSS); device memory is not in it, so it is not a physical footprint (Linux). +# TYPE tensorfold:process_resident_bytes gauge +tensorfold:process_resident_bytes 87653912576 +# HELP tensorfold:process_resident_anon_bytes Current resident anonymous memory (RssAnon): heap, stacks and private maps (Linux). +# TYPE tensorfold:process_resident_anon_bytes gauge +tensorfold:process_resident_anon_bytes 304463872 +# HELP tensorfold:process_resident_file_bytes Current resident file-backed memory (RssFile): the binary, libraries and mapped files (Linux). +# TYPE tensorfold:process_resident_file_bytes gauge +tensorfold:process_resident_file_bytes 87237545984 +# HELP tensorfold:process_resident_shmem_bytes Current resident shared memory (RssShmem): System V shared memory, tmpfs maps and shared anonymous maps (Linux). +# TYPE tensorfold:process_resident_shmem_bytes gauge +tensorfold:process_resident_shmem_bytes 111902720 +# HELP tensorfold:process_resident_peak_bytes Kernel lifetime peak resident set (VmHWM); never reset by health (Linux). +# TYPE tensorfold:process_resident_peak_bytes gauge +tensorfold:process_resident_peak_bytes 87654645760 +# HELP tensorfold:device_memory_bytes Device memory the engine holds now: weights, caches and live streams; only where the backend counts it (CUDA). +# TYPE tensorfold:device_memory_bytes gauge +tensorfold:device_memory_bytes 84915473856 +# HELP tensorfold:device_memory_peak_bytes The most device memory the engine has held since start or the last /health?reset_peak=1. +# TYPE tensorfold:device_memory_peak_bytes gauge +tensorfold:device_memory_peak_bytes 85071209924 +# HELP tensorfold:pinned_memory_bytes Pinned host memory the engine holds now: staging buffers and windows; only where the backend counts it (CUDA). +# TYPE tensorfold:pinned_memory_bytes gauge +tensorfold:pinned_memory_bytes 0 +# HELP tensorfold:num_requests_running Requests in prefill or decode. A mirror of tensorfold:requests_running. +# TYPE tensorfold:num_requests_running gauge +tensorfold:num_requests_running 0 +# HELP tensorfold:num_requests_waiting Requests queued or held until a lane is free. A mirror of tensorfold:requests_waiting. +# TYPE tensorfold:num_requests_waiting gauge +tensorfold:num_requests_waiting 0 +# HELP tensorfold:kv_cache_usage_perc A stream's cache occupancy under vLLM's name; same streams and ratios as tensorfold:kv_cache_usage_ratio. +# TYPE tensorfold:kv_cache_usage_perc gauge +tensorfold:kv_cache_usage_perc{stream="0"} 0 +# HELP tensorfold:spec_decode_num_draft_tokens_total Draft tokens verified on finished requests, this server's single draft counter. +# TYPE tensorfold:spec_decode_num_draft_tokens_total counter +tensorfold:spec_decode_num_draft_tokens_total 0 +# HELP tensorfold:spec_decode_num_accepted_tokens_total Draft tokens kept on finished requests. +# TYPE tensorfold:spec_decode_num_accepted_tokens_total counter +tensorfold:spec_decode_num_accepted_tokens_total 0 +# HELP tensorfold:e2e_request_latency_seconds Seconds from arrival to the reply leaving, under vLLM's name. +# TYPE tensorfold:e2e_request_latency_seconds histogram +tensorfold:e2e_request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="10"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="30"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="60"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="120"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="300"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:e2e_request_latency_seconds_sum 254.7149 +tensorfold:e2e_request_latency_seconds_count 2 +# HELP tensorfold:request_decode_time_seconds Seconds a finished request spent decoding, under vLLM's name. +# TYPE tensorfold:request_decode_time_seconds histogram +tensorfold:request_decode_time_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="10"} 2 +tensorfold:request_decode_time_seconds_bucket{le="30"} 2 +tensorfold:request_decode_time_seconds_bucket{le="60"} 2 +tensorfold:request_decode_time_seconds_bucket{le="120"} 2 +tensorfold:request_decode_time_seconds_bucket{le="300"} 2 +tensorfold:request_decode_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_time_seconds_sum 0.000395 +tensorfold:request_decode_time_seconds_count 2 +# HELP tensorfold:request_prefill_time_seconds Seconds a finished request's prompt pass took, under vLLM's name. +# TYPE tensorfold:request_prefill_time_seconds histogram +tensorfold:request_prefill_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.5"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="60"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="120"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_time_seconds_sum 254.712666 +tensorfold:request_prefill_time_seconds_count 2 +# HELP tensorfold:client_disconnections_total Requests a client left before the reply left the server. +# TYPE tensorfold:client_disconnections_total counter +tensorfold:client_disconnections_total 0 +# HELP tensorfold:preemptions_total Requests that had to give a lane up to a later one. +# TYPE tensorfold:preemptions_total counter +tensorfold:preemptions_total 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-65536-r2-samples.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-65536-r2-samples.jsonl new file mode 100644 index 0000000000..7018eb0d20 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-65536-r2-samples.jsonl @@ -0,0 +1,208 @@ +{"t_s": 0.0, "VmRSS_bytes": 46329856, "VmHWM_bytes": 46329856, "Pss_bytes": 46092288, "vram_used_bytes": 187670528, "vram_total_bytes": 4294967296, "gtt_used_bytes": 31657984, "gtt_total_bytes": 193273528320} +{"t_s": 1.03, "VmRSS_bytes": 8079060992, "VmHWM_bytes": 8079060992, "Pss_bytes": 8113976320, "vram_used_bytes": 188706816, "vram_total_bytes": 4294967296, "gtt_used_bytes": 5181775872, "gtt_total_bytes": 193273528320} +{"t_s": 2.08, "VmRSS_bytes": 12910452736, "VmHWM_bytes": 12910452736, "Pss_bytes": 12920140800, "vram_used_bytes": 189001728, "vram_total_bytes": 4294967296, "gtt_used_bytes": 10101694464, "gtt_total_bytes": 193273528320} +{"t_s": 3.15, "VmRSS_bytes": 19963621376, "VmHWM_bytes": 19963621376, "Pss_bytes": 19961246720, "vram_used_bytes": 189538304, "vram_total_bytes": 4294967296, "gtt_used_bytes": 18288975872, "gtt_total_bytes": 193273528320} +{"t_s": 4.25, "VmRSS_bytes": 28114673664, "VmHWM_bytes": 28114673664, "Pss_bytes": 28158182400, "vram_used_bytes": 190107648, "vram_total_bytes": 4294967296, "gtt_used_bytes": 26484645888, "gtt_total_bytes": 193273528320} +{"t_s": 5.36, "VmRSS_bytes": 36720992256, "VmHWM_bytes": 36720992256, "Pss_bytes": 36800275456, "vram_used_bytes": 190623744, "vram_total_bytes": 4294967296, "gtt_used_bytes": 34678218752, "gtt_total_bytes": 193273528320} +{"t_s": 6.49, "VmRSS_bytes": 45388009472, "VmHWM_bytes": 45388009472, "Pss_bytes": 45404771328, "vram_used_bytes": 191172608, "vram_total_bytes": 4294967296, "gtt_used_bytes": 42878083072, "gtt_total_bytes": 193273528320} +{"t_s": 7.65, "VmRSS_bytes": 53159407616, "VmHWM_bytes": 53159407616, "Pss_bytes": 53193536512, "vram_used_bytes": 191729664, "vram_total_bytes": 4294967296, "gtt_used_bytes": 51067461632, "gtt_total_bytes": 193273528320} +{"t_s": 8.82, "VmRSS_bytes": 60115369984, "VmHWM_bytes": 60115369984, "Pss_bytes": 60128199680, "vram_used_bytes": 192176128, "vram_total_bytes": 4294967296, "gtt_used_bytes": 57621061632, "gtt_total_bytes": 193273528320} +{"t_s": 10.02, "VmRSS_bytes": 68028186624, "VmHWM_bytes": 68028186624, "Pss_bytes": 68048135168, "vram_used_bytes": 192729088, "vram_total_bytes": 4294967296, "gtt_used_bytes": 65816731648, "gtt_total_bytes": 193273528320} +{"t_s": 11.24, "VmRSS_bytes": 76166225920, "VmHWM_bytes": 76166225920, "Pss_bytes": 76163851264, "vram_used_bytes": 193298432, "vram_total_bytes": 4294967296, "gtt_used_bytes": 74010304512, "gtt_total_bytes": 193273528320} +{"t_s": 12.46, "VmRSS_bytes": 80819544064, "VmHWM_bytes": 82467549184, "Pss_bytes": 80816530432, "vram_used_bytes": 194633728, "vram_total_bytes": 4294967296, "gtt_used_bytes": 83107749888, "gtt_total_bytes": 193273528320} +{"t_s": 13.69, "VmRSS_bytes": 80840892416, "VmHWM_bytes": 82467549184, "Pss_bytes": 80851315712, "vram_used_bytes": 194641920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 85798395904, "gtt_total_bytes": 193273528320} +{"t_s": 14.94, "VmRSS_bytes": 81028718592, "VmHWM_bytes": 82467549184, "Pss_bytes": 81026333696, "vram_used_bytes": 194641920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 85798395904, "gtt_total_bytes": 193273528320} +{"t_s": 16.18, "VmRSS_bytes": 81316016128, "VmHWM_bytes": 82467549184, "Pss_bytes": 81377700864, "vram_used_bytes": 194641920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 85955682304, "gtt_total_bytes": 193273528320} +{"t_s": 17.45, "VmRSS_bytes": 81419251712, "VmHWM_bytes": 82467549184, "Pss_bytes": 81416866816, "vram_used_bytes": 194641920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 85955682304, "gtt_total_bytes": 193273528320} +{"t_s": 18.68, "VmRSS_bytes": 81494859776, "VmHWM_bytes": 82467549184, "Pss_bytes": 81557773312, "vram_used_bytes": 194641920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 85955682304, "gtt_total_bytes": 193273528320} +{"t_s": 19.95, "VmRSS_bytes": 81810591744, "VmHWM_bytes": 82467549184, "Pss_bytes": 81808206848, "vram_used_bytes": 194641920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 85955682304, "gtt_total_bytes": 193273528320} +{"t_s": 21.22, "VmRSS_bytes": 81810591744, "VmHWM_bytes": 82467549184, "Pss_bytes": 81808206848, "vram_used_bytes": 194641920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 85955682304, "gtt_total_bytes": 193273528320} +{"t_s": 22.46, "VmRSS_bytes": 81848315904, "VmHWM_bytes": 82467549184, "Pss_bytes": 81901161472, "vram_used_bytes": 194641920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 85955682304, "gtt_total_bytes": 193273528320} +{"t_s": 23.72, "VmRSS_bytes": 82182127616, "VmHWM_bytes": 82467549184, "Pss_bytes": 82205498368, "vram_used_bytes": 194641920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 85955682304, "gtt_total_bytes": 193273528320} +{"t_s": 25.01, "VmRSS_bytes": 82208256000, "VmHWM_bytes": 82467549184, "Pss_bytes": 82205871104, "vram_used_bytes": 194641920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 85955682304, "gtt_total_bytes": 193273528320} +{"t_s": 26.29, "VmRSS_bytes": 82208256000, "VmHWM_bytes": 82467549184, "Pss_bytes": 82205871104, "vram_used_bytes": 194641920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 85955682304, "gtt_total_bytes": 193273528320} +{"t_s": 27.54, "VmRSS_bytes": 82387517440, "VmHWM_bytes": 82467549184, "Pss_bytes": 82436889600, "vram_used_bytes": 194641920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 85955682304, "gtt_total_bytes": 193273528320} +{"t_s": 28.81, "VmRSS_bytes": 82555138048, "VmHWM_bytes": 82555138048, "Pss_bytes": 82552753152, "vram_used_bytes": 194641920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 85955682304, "gtt_total_bytes": 193273528320} +{"t_s": 30.08, "VmRSS_bytes": 82555138048, "VmHWM_bytes": 82555138048, "Pss_bytes": 82552753152, "vram_used_bytes": 194641920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 85955682304, "gtt_total_bytes": 193273528320} +{"t_s": 31.34, "VmRSS_bytes": 82583121920, "VmHWM_bytes": 82583121920, "Pss_bytes": 82626165760, "vram_used_bytes": 194641920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 85955682304, "gtt_total_bytes": 193273528320} +{"t_s": 32.62, "VmRSS_bytes": 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"vram_used_bytes": 194641920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 85955682304, "gtt_total_bytes": 193273528320} +{"t_s": 224.65, "VmRSS_bytes": 86964400128, "VmHWM_bytes": 86964400128, "Pss_bytes": 86962015232, "vram_used_bytes": 194641920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 85955682304, "gtt_total_bytes": 193273528320} +{"t_s": 225.99, "VmRSS_bytes": 86964400128, "VmHWM_bytes": 86964400128, "Pss_bytes": 86962015232, "vram_used_bytes": 194641920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 85955682304, "gtt_total_bytes": 193273528320} +{"t_s": 227.31, "VmRSS_bytes": 86964400128, "VmHWM_bytes": 86964400128, "Pss_bytes": 86973361152, "vram_used_bytes": 194641920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 85955682304, "gtt_total_bytes": 193273528320} +{"t_s": 228.64, "VmRSS_bytes": 86995947520, "VmHWM_bytes": 86995947520, "Pss_bytes": 86993562624, "vram_used_bytes": 194641920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 85955682304, "gtt_total_bytes": 193273528320} +{"t_s": 229.96, "VmRSS_bytes": 86995947520, "VmHWM_bytes": 86995947520, "Pss_bytes": 86993562624, "vram_used_bytes": 194641920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 85955682304, "gtt_total_bytes": 193273528320} +{"t_s": 231.28, "VmRSS_bytes": 87009824768, "VmHWM_bytes": 87009824768, "Pss_bytes": 87029554176, "vram_used_bytes": 194641920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 85955682304, "gtt_total_bytes": 193273528320} +{"t_s": 232.63, "VmRSS_bytes": 87061389312, "VmHWM_bytes": 87061389312, "Pss_bytes": 87059004416, "vram_used_bytes": 194641920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 85955682304, "gtt_total_bytes": 193273528320} +{"t_s": 233.97, "VmRSS_bytes": 87061389312, "VmHWM_bytes": 87061389312, "Pss_bytes": 87059004416, "vram_used_bytes": 194641920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 85955682304, "gtt_total_bytes": 193273528320} +{"t_s": 235.27, "VmRSS_bytes": 87067660288, "VmHWM_bytes": 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"gtt_used_bytes": 85955682304, "gtt_total_bytes": 193273528320} +{"t_s": 241.93, "VmRSS_bytes": 87221456896, "VmHWM_bytes": 87221456896, "Pss_bytes": 87219072000, "vram_used_bytes": 194641920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 85955682304, "gtt_total_bytes": 193273528320} +{"t_s": 243.24, "VmRSS_bytes": 87221456896, "VmHWM_bytes": 87221456896, "Pss_bytes": 87223933952, "vram_used_bytes": 194641920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 85955682304, "gtt_total_bytes": 193273528320} +{"t_s": 244.57, "VmRSS_bytes": 87318429696, "VmHWM_bytes": 87318429696, "Pss_bytes": 87316044800, "vram_used_bytes": 194641920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 85955682304, "gtt_total_bytes": 193273528320} +{"t_s": 245.91, "VmRSS_bytes": 87318429696, "VmHWM_bytes": 87318429696, "Pss_bytes": 87316041728, "vram_used_bytes": 194641920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 85955682304, "gtt_total_bytes": 193273528320} +{"t_s": 247.25, "VmRSS_bytes": 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"vram_total_bytes": 4294967296, "gtt_used_bytes": 85955682304, "gtt_total_bytes": 193273528320} +{"t_s": 253.95, "VmRSS_bytes": 87463256064, "VmHWM_bytes": 87463256064, "Pss_bytes": 87460871168, "vram_used_bytes": 194641920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 85955682304, "gtt_total_bytes": 193273528320} +{"t_s": 255.31, "VmRSS_bytes": 87463256064, "VmHWM_bytes": 87463256064, "Pss_bytes": 87460871168, "vram_used_bytes": 194641920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 85955682304, "gtt_total_bytes": 193273528320} +{"t_s": 256.64, "VmRSS_bytes": 87514890240, "VmHWM_bytes": 87514890240, "Pss_bytes": 87539440640, "vram_used_bytes": 194641920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 85955682304, "gtt_total_bytes": 193273528320} +{"t_s": 257.99, "VmRSS_bytes": 87547768832, "VmHWM_bytes": 87547768832, "Pss_bytes": 87545383936, "vram_used_bytes": 194641920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 85955682304, "gtt_total_bytes": 193273528320} 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"vram_used_bytes": 194641920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 85955682304, "gtt_total_bytes": 193273528320} +{"t_s": 266.0, "VmRSS_bytes": 87657930752, "VmHWM_bytes": 87657930752, "Pss_bytes": 87655545856, "vram_used_bytes": 194641920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 85955682304, "gtt_total_bytes": 193273528320} +{"t_s": 267.35, "VmRSS_bytes": 87657930752, "VmHWM_bytes": 87657930752, "Pss_bytes": 87655545856, "vram_used_bytes": 194641920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 85955682304, "gtt_total_bytes": 193273528320} +{"t_s": 268.66, "VmRSS_bytes": 87584919552, "VmHWM_bytes": 87654645760, "Pss_bytes": 87582542848, "vram_used_bytes": 194502656, "vram_total_bytes": 4294967296, "gtt_used_bytes": 41424756736, "gtt_total_bytes": 193273528320} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-8192-r1-memory-endpoint.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-8192-r1-memory-endpoint.json new file mode 100644 index 0000000000..7d0bc4d723 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-8192-r1-memory-endpoint.json @@ -0,0 +1 @@ +{"schema_version": 1, "context_window": 16384, "context_fitted": false, "device": {"active_bytes": 83285986752, "cache_bytes": 0, "peak_bytes": 83305932228, "peak_scope": "since_start_or_health_reset"}} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-8192-r1-metrics.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-8192-r1-metrics.txt new file mode 100644 index 0000000000..ece50cf3bd --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-8192-r1-metrics.txt @@ -0,0 +1,220 @@ +# HELP tensorfold:requests_running Requests in prefill or decode. +# TYPE tensorfold:requests_running gauge +tensorfold:requests_running 0 +# HELP tensorfold:requests_waiting Requests queued or held until a lane is free. +# TYPE tensorfold:requests_waiting gauge +tensorfold:requests_waiting 0 +# HELP tensorfold:generation_tokens_running Generated tokens held by live streams. +# TYPE tensorfold:generation_tokens_running gauge +tensorfold:generation_tokens_running 0 +# HELP tensorfold:prompt_tokens_total Prompt tokens of finished requests. +# TYPE tensorfold:prompt_tokens_total counter +tensorfold:prompt_tokens_total 8448 +# HELP tensorfold:generation_tokens_total Generated tokens of finished requests. +# TYPE tensorfold:generation_tokens_total counter +tensorfold:generation_tokens_total 2 +# HELP tensorfold:kv_cache_usage_ratio Tokens in a stream cache divided by that stream's context window. +# TYPE tensorfold:kv_cache_usage_ratio gauge +tensorfold:kv_cache_usage_ratio{pool="0"} 0 +# HELP tensorfold:mtp_drafted_total Draft tokens verified on finished requests. +# TYPE tensorfold:mtp_drafted_total counter +tensorfold:mtp_drafted_total 0 +# HELP tensorfold:mtp_accepted_total Draft tokens kept on finished requests. +# TYPE tensorfold:mtp_accepted_total counter +tensorfold:mtp_accepted_total 0 +# HELP tensorfold:request_latency_seconds Seconds from arrival to the reply leaving. +# TYPE tensorfold:request_latency_seconds histogram +tensorfold:request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:request_latency_seconds_bucket{le="1"} 0 +tensorfold:request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:request_latency_seconds_bucket{le="5"} 1 +tensorfold:request_latency_seconds_bucket{le="10"} 1 +tensorfold:request_latency_seconds_bucket{le="30"} 1 +tensorfold:request_latency_seconds_bucket{le="60"} 2 +tensorfold:request_latency_seconds_bucket{le="120"} 2 +tensorfold:request_latency_seconds_bucket{le="300"} 2 +tensorfold:request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:request_latency_seconds_sum 33.369347 +tensorfold:request_latency_seconds_count 2 +# HELP tensorfold:time_to_first_token_seconds Seconds from arrival to the first generated token. +# TYPE tensorfold:time_to_first_token_seconds histogram +tensorfold:time_to_first_token_seconds_bucket{le="0.01"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.05"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.25"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.5"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="2.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="10"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="30"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="60"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="120"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="300"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="+Inf"} 2 +tensorfold:time_to_first_token_seconds_sum 33.369066 +tensorfold:time_to_first_token_seconds_count 2 +# HELP tensorfold:request_decode_seconds Seconds a finished request spent decoding. Its sum over generation_tokens_total is the decode rate. +# TYPE tensorfold:request_decode_seconds histogram +tensorfold:request_decode_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_seconds_bucket{le="1"} 2 +tensorfold:request_decode_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_seconds_bucket{le="5"} 2 +tensorfold:request_decode_seconds_bucket{le="10"} 2 +tensorfold:request_decode_seconds_bucket{le="30"} 2 +tensorfold:request_decode_seconds_bucket{le="60"} 2 +tensorfold:request_decode_seconds_bucket{le="120"} 2 +tensorfold:request_decode_seconds_bucket{le="300"} 2 +tensorfold:request_decode_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_seconds_sum 0.000281 +tensorfold:request_decode_seconds_count 2 +# HELP tensorfold:request_time_per_output_token_seconds Seconds from the first generated token to the last, divided by the tokens less one. +# TYPE tensorfold:request_time_per_output_token_seconds histogram +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.005"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.01"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.015"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.02"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.03"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.04"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.05"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.15"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.2"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.3"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.5"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="+Inf"} 0 +tensorfold:request_time_per_output_token_seconds_sum 0 +tensorfold:request_time_per_output_token_seconds_count 0 +# HELP tensorfold:decode_rounds_total Decode rounds used by finished requests. +# TYPE tensorfold:decode_rounds_total counter +tensorfold:decode_rounds_total 0 +# HELP tensorfold:request_prefill_seconds Seconds a finished request's prompt pass took. +# TYPE tensorfold:request_prefill_seconds histogram +tensorfold:request_prefill_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.5"} 0 +tensorfold:request_prefill_seconds_bucket{le="1"} 0 +tensorfold:request_prefill_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_seconds_bucket{le="60"} 2 +tensorfold:request_prefill_seconds_bucket{le="120"} 2 +tensorfold:request_prefill_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_seconds_sum 33.367957 +tensorfold:request_prefill_seconds_count 2 +# HELP tensorfold:process_resident_bytes Current resident set (VmRSS); device memory is not in it, so it is not a physical footprint (Linux). +# TYPE tensorfold:process_resident_bytes gauge +tensorfold:process_resident_bytes 83276947456 +# HELP tensorfold:process_resident_anon_bytes Current resident anonymous memory (RssAnon): heap, stacks and private maps (Linux). +# TYPE tensorfold:process_resident_anon_bytes gauge +tensorfold:process_resident_anon_bytes 305344512 +# HELP tensorfold:process_resident_file_bytes Current resident file-backed memory (RssFile): the binary, libraries and mapped files (Linux). +# TYPE tensorfold:process_resident_file_bytes gauge +tensorfold:process_resident_file_bytes 82859700224 +# HELP tensorfold:process_resident_shmem_bytes Current resident shared memory (RssShmem): System V shared memory, tmpfs maps and shared anonymous maps (Linux). +# TYPE tensorfold:process_resident_shmem_bytes gauge +tensorfold:process_resident_shmem_bytes 111902720 +# HELP tensorfold:process_resident_peak_bytes Kernel lifetime peak resident set (VmHWM); never reset by health (Linux). +# TYPE tensorfold:process_resident_peak_bytes gauge +tensorfold:process_resident_peak_bytes 83276947456 +# HELP tensorfold:device_memory_bytes Device memory the engine holds now: weights, caches and live streams; only where the backend counts it (CUDA). +# TYPE tensorfold:device_memory_bytes gauge +tensorfold:device_memory_bytes 83285986752 +# HELP tensorfold:device_memory_peak_bytes The most device memory the engine has held since start or the last /health?reset_peak=1. +# TYPE tensorfold:device_memory_peak_bytes gauge +tensorfold:device_memory_peak_bytes 83305932228 +# HELP tensorfold:pinned_memory_bytes Pinned host memory the engine holds now: staging buffers and windows; only where the backend counts it (CUDA). +# TYPE tensorfold:pinned_memory_bytes gauge +tensorfold:pinned_memory_bytes 0 +# HELP tensorfold:num_requests_running Requests in prefill or decode. A mirror of tensorfold:requests_running. +# TYPE tensorfold:num_requests_running gauge +tensorfold:num_requests_running 0 +# HELP tensorfold:num_requests_waiting Requests queued or held until a lane is free. A mirror of tensorfold:requests_waiting. +# TYPE tensorfold:num_requests_waiting gauge +tensorfold:num_requests_waiting 0 +# HELP tensorfold:kv_cache_usage_perc A stream's cache occupancy under vLLM's name; same streams and ratios as tensorfold:kv_cache_usage_ratio. +# TYPE tensorfold:kv_cache_usage_perc gauge +tensorfold:kv_cache_usage_perc{stream="0"} 0 +# HELP tensorfold:spec_decode_num_draft_tokens_total Draft tokens verified on finished requests, this server's single draft counter. +# TYPE tensorfold:spec_decode_num_draft_tokens_total counter +tensorfold:spec_decode_num_draft_tokens_total 0 +# HELP tensorfold:spec_decode_num_accepted_tokens_total Draft tokens kept on finished requests. +# TYPE tensorfold:spec_decode_num_accepted_tokens_total counter +tensorfold:spec_decode_num_accepted_tokens_total 0 +# HELP tensorfold:e2e_request_latency_seconds Seconds from arrival to the reply leaving, under vLLM's name. +# TYPE tensorfold:e2e_request_latency_seconds histogram +tensorfold:e2e_request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="10"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="30"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="60"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="120"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="300"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:e2e_request_latency_seconds_sum 33.369347 +tensorfold:e2e_request_latency_seconds_count 2 +# HELP tensorfold:request_decode_time_seconds Seconds a finished request spent decoding, under vLLM's name. +# TYPE tensorfold:request_decode_time_seconds histogram +tensorfold:request_decode_time_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="10"} 2 +tensorfold:request_decode_time_seconds_bucket{le="30"} 2 +tensorfold:request_decode_time_seconds_bucket{le="60"} 2 +tensorfold:request_decode_time_seconds_bucket{le="120"} 2 +tensorfold:request_decode_time_seconds_bucket{le="300"} 2 +tensorfold:request_decode_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_time_seconds_sum 0.000281 +tensorfold:request_decode_time_seconds_count 2 +# HELP tensorfold:request_prefill_time_seconds Seconds a finished request's prompt pass took, under vLLM's name. +# TYPE tensorfold:request_prefill_time_seconds histogram +tensorfold:request_prefill_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.5"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="60"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="120"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_time_seconds_sum 33.367957 +tensorfold:request_prefill_time_seconds_count 2 +# HELP tensorfold:client_disconnections_total Requests a client left before the reply left the server. +# TYPE tensorfold:client_disconnections_total counter +tensorfold:client_disconnections_total 0 +# HELP tensorfold:preemptions_total Requests that had to give a lane up to a later one. +# TYPE tensorfold:preemptions_total counter +tensorfold:preemptions_total 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-8192-r1-samples.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-8192-r1-samples.jsonl new file mode 100644 index 0000000000..7f9bad2a3c --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-8192-r1-samples.jsonl @@ -0,0 +1,39 @@ +{"t_s": 0.0, "VmRSS_bytes": 34476032, "VmHWM_bytes": 34476032, "Pss_bytes": 32713728, "vram_used_bytes": 187670528, "vram_total_bytes": 4294967296, "gtt_used_bytes": 31657984, "gtt_total_bytes": 193273528320} +{"t_s": 1.03, "VmRSS_bytes": 8568025088, "VmHWM_bytes": 8568025088, "Pss_bytes": 8567070720, "vram_used_bytes": 188678144, "vram_total_bytes": 4294967296, "gtt_used_bytes": 6777708544, "gtt_total_bytes": 193273528320} +{"t_s": 2.08, "VmRSS_bytes": 16678211584, "VmHWM_bytes": 16678211584, "Pss_bytes": 16675864576, "vram_used_bytes": 189198336, "vram_total_bytes": 4294967296, "gtt_used_bytes": 14222598144, "gtt_total_bytes": 193273528320} +{"t_s": 3.16, "VmRSS_bytes": 24263122944, "VmHWM_bytes": 24263122944, "Pss_bytes": 24260775936, "vram_used_bytes": 189763584, "vram_total_bytes": 4294967296, "gtt_used_bytes": 21575213056, "gtt_total_bytes": 193273528320} +{"t_s": 4.28, "VmRSS_bytes": 32233635840, "VmHWM_bytes": 32233635840, "Pss_bytes": 32267988992, "vram_used_bytes": 190324736, "vram_total_bytes": 4294967296, "gtt_used_bytes": 29770883072, "gtt_total_bytes": 193273528320} +{"t_s": 5.41, "VmRSS_bytes": 38958501888, "VmHWM_bytes": 38958501888, "Pss_bytes": 38981189632, "vram_used_bytes": 190799872, "vram_total_bytes": 4294967296, "gtt_used_bytes": 36324483072, "gtt_total_bytes": 193273528320} +{"t_s": 6.56, "VmRSS_bytes": 44055166976, "VmHWM_bytes": 44055166976, "Pss_bytes": 44104462336, "vram_used_bytes": 191135744, "vram_total_bytes": 4294967296, "gtt_used_bytes": 41238110208, "gtt_total_bytes": 193273528320} +{"t_s": 7.73, "VmRSS_bytes": 50991022080, "VmHWM_bytes": 50991022080, "Pss_bytes": 51004813312, "vram_used_bytes": 191680512, "vram_total_bytes": 4294967296, "gtt_used_bytes": 49433780224, "gtt_total_bytes": 193273528320} +{"t_s": 8.91, "VmRSS_bytes": 60256428032, "VmHWM_bytes": 60256428032, "Pss_bytes": 60270333952, "vram_used_bytes": 192258048, "vram_total_bytes": 4294967296, "gtt_used_bytes": 57621061632, "gtt_total_bytes": 193273528320} +{"t_s": 10.11, "VmRSS_bytes": 68057878528, "VmHWM_bytes": 68057878528, "Pss_bytes": 68055531520, "vram_used_bytes": 192819200, "vram_total_bytes": 4294967296, "gtt_used_bytes": 65816731648, "gtt_total_bytes": 193273528320} +{"t_s": 11.33, "VmRSS_bytes": 76365385728, "VmHWM_bytes": 76365385728, "Pss_bytes": 76388204544, "vram_used_bytes": 193396736, "vram_total_bytes": 4294967296, "gtt_used_bytes": 74010304512, "gtt_total_bytes": 193273528320} +{"t_s": 12.57, "VmRSS_bytes": 80822951936, "VmHWM_bytes": 82470334464, "Pss_bytes": 80820604928, "vram_used_bytes": 195137536, "vram_total_bytes": 4294967296, "gtt_used_bytes": 83107749888, "gtt_total_bytes": 193273528320} +{"t_s": 13.81, "VmRSS_bytes": 80851337216, "VmHWM_bytes": 82470334464, "Pss_bytes": 80866443264, "vram_used_bytes": 194998272, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84168908800, "gtt_total_bytes": 193273528320} +{"t_s": 15.07, "VmRSS_bytes": 81028411392, "VmHWM_bytes": 82470334464, "Pss_bytes": 81026060288, "vram_used_bytes": 194998272, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84168908800, "gtt_total_bytes": 193273528320} +{"t_s": 16.32, "VmRSS_bytes": 81348694016, "VmHWM_bytes": 82470334464, "Pss_bytes": 81412886528, "vram_used_bytes": 194998272, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84189880320, "gtt_total_bytes": 193273528320} +{"t_s": 17.59, "VmRSS_bytes": 81415577600, "VmHWM_bytes": 82470334464, "Pss_bytes": 81413226496, "vram_used_bytes": 194998272, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84189880320, "gtt_total_bytes": 193273528320} +{"t_s": 18.84, "VmRSS_bytes": 81530650624, "VmHWM_bytes": 82470334464, "Pss_bytes": 81600258048, "vram_used_bytes": 194998272, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84189880320, "gtt_total_bytes": 193273528320} +{"t_s": 20.12, "VmRSS_bytes": 81806680064, "VmHWM_bytes": 82470334464, "Pss_bytes": 81804328960, "vram_used_bytes": 194998272, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84189880320, "gtt_total_bytes": 193273528320} +{"t_s": 21.4, "VmRSS_bytes": 81806680064, "VmHWM_bytes": 82470334464, "Pss_bytes": 81804328960, "vram_used_bytes": 194998272, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84189880320, "gtt_total_bytes": 193273528320} +{"t_s": 22.65, "VmRSS_bytes": 81885650944, "VmHWM_bytes": 82470334464, "Pss_bytes": 81943527424, "vram_used_bytes": 194998272, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84189880320, "gtt_total_bytes": 193273528320} +{"t_s": 23.93, "VmRSS_bytes": 82204311552, "VmHWM_bytes": 82470334464, "Pss_bytes": 82201960448, "vram_used_bytes": 194998272, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84189880320, "gtt_total_bytes": 193273528320} +{"t_s": 25.21, "VmRSS_bytes": 82204311552, "VmHWM_bytes": 82470334464, "Pss_bytes": 82201960448, "vram_used_bytes": 194998272, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84189880320, "gtt_total_bytes": 193273528320} +{"t_s": 26.47, "VmRSS_bytes": 82204311552, "VmHWM_bytes": 82470334464, "Pss_bytes": 82202099712, "vram_used_bytes": 194998272, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84189880320, "gtt_total_bytes": 193273528320} +{"t_s": 27.73, "VmRSS_bytes": 82465849344, "VmHWM_bytes": 82470334464, "Pss_bytes": 82516733952, "vram_used_bytes": 194998272, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84189880320, "gtt_total_bytes": 193273528320} +{"t_s": 29.02, "VmRSS_bytes": 82550829056, "VmHWM_bytes": 82550829056, "Pss_bytes": 82548477952, "vram_used_bytes": 194998272, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84189880320, "gtt_total_bytes": 193273528320} +{"t_s": 30.31, "VmRSS_bytes": 82550829056, "VmHWM_bytes": 82550829056, "Pss_bytes": 82548477952, "vram_used_bytes": 194998272, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84189880320, "gtt_total_bytes": 193273528320} +{"t_s": 31.57, "VmRSS_bytes": 82663124992, "VmHWM_bytes": 82663124992, "Pss_bytes": 82713092096, "vram_used_bytes": 194998272, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84189880320, "gtt_total_bytes": 193273528320} +{"t_s": 32.85, "VmRSS_bytes": 82748461056, "VmHWM_bytes": 82748461056, "Pss_bytes": 82746109952, "vram_used_bytes": 194998272, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84189880320, "gtt_total_bytes": 193273528320} +{"t_s": 34.14, "VmRSS_bytes": 82748461056, "VmHWM_bytes": 82748461056, "Pss_bytes": 82746109952, "vram_used_bytes": 194998272, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84189880320, "gtt_total_bytes": 193273528320} +{"t_s": 35.4, "VmRSS_bytes": 82843901952, "VmHWM_bytes": 82843901952, "Pss_bytes": 82886168576, "vram_used_bytes": 194998272, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84189880320, "gtt_total_bytes": 193273528320} +{"t_s": 36.68, "VmRSS_bytes": 83067052032, "VmHWM_bytes": 83067052032, "Pss_bytes": 83064700928, "vram_used_bytes": 194998272, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84189880320, "gtt_total_bytes": 193273528320} +{"t_s": 37.97, "VmRSS_bytes": 83067052032, "VmHWM_bytes": 83067052032, "Pss_bytes": 83064700928, "vram_used_bytes": 194998272, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84189880320, "gtt_total_bytes": 193273528320} +{"t_s": 39.24, "VmRSS_bytes": 83067052032, "VmHWM_bytes": 83067052032, "Pss_bytes": 83064836096, "vram_used_bytes": 194998272, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84189880320, "gtt_total_bytes": 193273528320} +{"t_s": 40.53, "VmRSS_bytes": 83180355584, "VmHWM_bytes": 83180355584, "Pss_bytes": 83178004480, "vram_used_bytes": 194998272, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84189880320, "gtt_total_bytes": 193273528320} +{"t_s": 41.82, "VmRSS_bytes": 83180625920, "VmHWM_bytes": 83180625920, "Pss_bytes": 83178274816, "vram_used_bytes": 194998272, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84189880320, "gtt_total_bytes": 193273528320} +{"t_s": 43.1, "VmRSS_bytes": 83180625920, "VmHWM_bytes": 83180625920, "Pss_bytes": 83205259264, "vram_used_bytes": 194998272, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84189880320, "gtt_total_bytes": 193273528320} +{"t_s": 44.38, "VmRSS_bytes": 83277688832, "VmHWM_bytes": 83277688832, "Pss_bytes": 83275337728, "vram_used_bytes": 194998272, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84189880320, "gtt_total_bytes": 193273528320} +{"t_s": 45.67, "VmRSS_bytes": 83277688832, "VmHWM_bytes": 83277688832, "Pss_bytes": 83275337728, "vram_used_bytes": 194998272, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84189880320, "gtt_total_bytes": 193273528320} +{"t_s": 46.94, "VmRSS_bytes": 83276759040, "VmHWM_bytes": 83276759040, "Pss_bytes": 83274414080, "vram_used_bytes": 194998272, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84168908800, "gtt_total_bytes": 193273528320} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-8192-r2-memory-endpoint.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-8192-r2-memory-endpoint.json new file mode 100644 index 0000000000..7d0bc4d723 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-8192-r2-memory-endpoint.json @@ -0,0 +1 @@ +{"schema_version": 1, "context_window": 16384, "context_fitted": false, "device": {"active_bytes": 83285986752, "cache_bytes": 0, "peak_bytes": 83305932228, "peak_scope": "since_start_or_health_reset"}} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-8192-r2-metrics.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-8192-r2-metrics.txt new file mode 100644 index 0000000000..480273a247 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-8192-r2-metrics.txt @@ -0,0 +1,220 @@ +# HELP tensorfold:requests_running Requests in prefill or decode. +# TYPE tensorfold:requests_running gauge +tensorfold:requests_running 0 +# HELP tensorfold:requests_waiting Requests queued or held until a lane is free. +# TYPE tensorfold:requests_waiting gauge +tensorfold:requests_waiting 0 +# HELP tensorfold:generation_tokens_running Generated tokens held by live streams. +# TYPE tensorfold:generation_tokens_running gauge +tensorfold:generation_tokens_running 0 +# HELP tensorfold:prompt_tokens_total Prompt tokens of finished requests. +# TYPE tensorfold:prompt_tokens_total counter +tensorfold:prompt_tokens_total 8448 +# HELP tensorfold:generation_tokens_total Generated tokens of finished requests. +# TYPE tensorfold:generation_tokens_total counter +tensorfold:generation_tokens_total 2 +# HELP tensorfold:kv_cache_usage_ratio Tokens in a stream cache divided by that stream's context window. +# TYPE tensorfold:kv_cache_usage_ratio gauge +tensorfold:kv_cache_usage_ratio{pool="0"} 0 +# HELP tensorfold:mtp_drafted_total Draft tokens verified on finished requests. +# TYPE tensorfold:mtp_drafted_total counter +tensorfold:mtp_drafted_total 0 +# HELP tensorfold:mtp_accepted_total Draft tokens kept on finished requests. +# TYPE tensorfold:mtp_accepted_total counter +tensorfold:mtp_accepted_total 0 +# HELP tensorfold:request_latency_seconds Seconds from arrival to the reply leaving. +# TYPE tensorfold:request_latency_seconds histogram +tensorfold:request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:request_latency_seconds_bucket{le="1"} 0 +tensorfold:request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:request_latency_seconds_bucket{le="5"} 1 +tensorfold:request_latency_seconds_bucket{le="10"} 1 +tensorfold:request_latency_seconds_bucket{le="30"} 1 +tensorfold:request_latency_seconds_bucket{le="60"} 2 +tensorfold:request_latency_seconds_bucket{le="120"} 2 +tensorfold:request_latency_seconds_bucket{le="300"} 2 +tensorfold:request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:request_latency_seconds_sum 33.314619 +tensorfold:request_latency_seconds_count 2 +# HELP tensorfold:time_to_first_token_seconds Seconds from arrival to the first generated token. +# TYPE tensorfold:time_to_first_token_seconds histogram +tensorfold:time_to_first_token_seconds_bucket{le="0.01"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.05"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.25"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.5"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="2.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="10"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="30"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="60"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="120"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="300"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="+Inf"} 2 +tensorfold:time_to_first_token_seconds_sum 33.3143 +tensorfold:time_to_first_token_seconds_count 2 +# HELP tensorfold:request_decode_seconds Seconds a finished request spent decoding. Its sum over generation_tokens_total is the decode rate. +# TYPE tensorfold:request_decode_seconds histogram +tensorfold:request_decode_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_seconds_bucket{le="1"} 2 +tensorfold:request_decode_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_seconds_bucket{le="5"} 2 +tensorfold:request_decode_seconds_bucket{le="10"} 2 +tensorfold:request_decode_seconds_bucket{le="30"} 2 +tensorfold:request_decode_seconds_bucket{le="60"} 2 +tensorfold:request_decode_seconds_bucket{le="120"} 2 +tensorfold:request_decode_seconds_bucket{le="300"} 2 +tensorfold:request_decode_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_seconds_sum 0.000319 +tensorfold:request_decode_seconds_count 2 +# HELP tensorfold:request_time_per_output_token_seconds Seconds from the first generated token to the last, divided by the tokens less one. +# TYPE tensorfold:request_time_per_output_token_seconds histogram +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.005"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.01"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.015"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.02"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.03"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.04"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.05"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.15"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.2"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.3"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.5"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="+Inf"} 0 +tensorfold:request_time_per_output_token_seconds_sum 0 +tensorfold:request_time_per_output_token_seconds_count 0 +# HELP tensorfold:decode_rounds_total Decode rounds used by finished requests. +# TYPE tensorfold:decode_rounds_total counter +tensorfold:decode_rounds_total 0 +# HELP tensorfold:request_prefill_seconds Seconds a finished request's prompt pass took. +# TYPE tensorfold:request_prefill_seconds histogram +tensorfold:request_prefill_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.5"} 0 +tensorfold:request_prefill_seconds_bucket{le="1"} 0 +tensorfold:request_prefill_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_seconds_bucket{le="60"} 2 +tensorfold:request_prefill_seconds_bucket{le="120"} 2 +tensorfold:request_prefill_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_seconds_sum 33.312169 +tensorfold:request_prefill_seconds_count 2 +# HELP tensorfold:process_resident_bytes Current resident set (VmRSS); device memory is not in it, so it is not a physical footprint (Linux). +# TYPE tensorfold:process_resident_bytes gauge +tensorfold:process_resident_bytes 83279384576 +# HELP tensorfold:process_resident_anon_bytes Current resident anonymous memory (RssAnon): heap, stacks and private maps (Linux). +# TYPE tensorfold:process_resident_anon_bytes gauge +tensorfold:process_resident_anon_bytes 308518912 +# HELP tensorfold:process_resident_file_bytes Current resident file-backed memory (RssFile): the binary, libraries and mapped files (Linux). +# TYPE tensorfold:process_resident_file_bytes gauge +tensorfold:process_resident_file_bytes 82858962944 +# HELP tensorfold:process_resident_shmem_bytes Current resident shared memory (RssShmem): System V shared memory, tmpfs maps and shared anonymous maps (Linux). +# TYPE tensorfold:process_resident_shmem_bytes gauge +tensorfold:process_resident_shmem_bytes 111902720 +# HELP tensorfold:process_resident_peak_bytes Kernel lifetime peak resident set (VmHWM); never reset by health (Linux). +# TYPE tensorfold:process_resident_peak_bytes gauge +tensorfold:process_resident_peak_bytes 83279384576 +# HELP tensorfold:device_memory_bytes Device memory the engine holds now: weights, caches and live streams; only where the backend counts it (CUDA). +# TYPE tensorfold:device_memory_bytes gauge +tensorfold:device_memory_bytes 83285986752 +# HELP tensorfold:device_memory_peak_bytes The most device memory the engine has held since start or the last /health?reset_peak=1. +# TYPE tensorfold:device_memory_peak_bytes gauge +tensorfold:device_memory_peak_bytes 83305932228 +# HELP tensorfold:pinned_memory_bytes Pinned host memory the engine holds now: staging buffers and windows; only where the backend counts it (CUDA). +# TYPE tensorfold:pinned_memory_bytes gauge +tensorfold:pinned_memory_bytes 0 +# HELP tensorfold:num_requests_running Requests in prefill or decode. A mirror of tensorfold:requests_running. +# TYPE tensorfold:num_requests_running gauge +tensorfold:num_requests_running 0 +# HELP tensorfold:num_requests_waiting Requests queued or held until a lane is free. A mirror of tensorfold:requests_waiting. +# TYPE tensorfold:num_requests_waiting gauge +tensorfold:num_requests_waiting 0 +# HELP tensorfold:kv_cache_usage_perc A stream's cache occupancy under vLLM's name; same streams and ratios as tensorfold:kv_cache_usage_ratio. +# TYPE tensorfold:kv_cache_usage_perc gauge +tensorfold:kv_cache_usage_perc{stream="0"} 0 +# HELP tensorfold:spec_decode_num_draft_tokens_total Draft tokens verified on finished requests, this server's single draft counter. +# TYPE tensorfold:spec_decode_num_draft_tokens_total counter +tensorfold:spec_decode_num_draft_tokens_total 0 +# HELP tensorfold:spec_decode_num_accepted_tokens_total Draft tokens kept on finished requests. +# TYPE tensorfold:spec_decode_num_accepted_tokens_total counter +tensorfold:spec_decode_num_accepted_tokens_total 0 +# HELP tensorfold:e2e_request_latency_seconds Seconds from arrival to the reply leaving, under vLLM's name. +# TYPE tensorfold:e2e_request_latency_seconds histogram +tensorfold:e2e_request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="10"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="30"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="60"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="120"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="300"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:e2e_request_latency_seconds_sum 33.314619 +tensorfold:e2e_request_latency_seconds_count 2 +# HELP tensorfold:request_decode_time_seconds Seconds a finished request spent decoding, under vLLM's name. +# TYPE tensorfold:request_decode_time_seconds histogram +tensorfold:request_decode_time_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="10"} 2 +tensorfold:request_decode_time_seconds_bucket{le="30"} 2 +tensorfold:request_decode_time_seconds_bucket{le="60"} 2 +tensorfold:request_decode_time_seconds_bucket{le="120"} 2 +tensorfold:request_decode_time_seconds_bucket{le="300"} 2 +tensorfold:request_decode_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_time_seconds_sum 0.000319 +tensorfold:request_decode_time_seconds_count 2 +# HELP tensorfold:request_prefill_time_seconds Seconds a finished request's prompt pass took, under vLLM's name. +# TYPE tensorfold:request_prefill_time_seconds histogram +tensorfold:request_prefill_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.5"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="60"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="120"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_time_seconds_sum 33.312169 +tensorfold:request_prefill_time_seconds_count 2 +# HELP tensorfold:client_disconnections_total Requests a client left before the reply left the server. +# TYPE tensorfold:client_disconnections_total counter +tensorfold:client_disconnections_total 0 +# HELP tensorfold:preemptions_total Requests that had to give a lane up to a later one. +# TYPE tensorfold:preemptions_total counter +tensorfold:preemptions_total 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-8192-r2-samples.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-8192-r2-samples.jsonl new file mode 100644 index 0000000000..0bad450503 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-base-8192-r2-samples.jsonl @@ -0,0 +1,39 @@ +{"t_s": 0.0, "VmRSS_bytes": 47210496, "VmHWM_bytes": 47210496, "Pss_bytes": 45212672, "vram_used_bytes": 187670528, "vram_total_bytes": 4294967296, "gtt_used_bytes": 31657984, "gtt_total_bytes": 193273528320} +{"t_s": 1.03, "VmRSS_bytes": 8044273664, "VmHWM_bytes": 8044273664, "Pss_bytes": 8041973760, "vram_used_bytes": 188706816, "vram_total_bytes": 4294967296, "gtt_used_bytes": 5181775872, "gtt_total_bytes": 193273528320} +{"t_s": 2.09, "VmRSS_bytes": 15787114496, "VmHWM_bytes": 15787114496, "Pss_bytes": 15894128640, "vram_used_bytes": 189202432, "vram_total_bytes": 4294967296, "gtt_used_bytes": 13375348736, "gtt_total_bytes": 193273528320} +{"t_s": 3.17, "VmRSS_bytes": 22783840256, "VmHWM_bytes": 22783840256, "Pss_bytes": 22814382080, "vram_used_bytes": 189652992, "vram_total_bytes": 4294967296, "gtt_used_bytes": 19935240192, "gtt_total_bytes": 193273528320} +{"t_s": 4.29, "VmRSS_bytes": 29890715648, "VmHWM_bytes": 29890715648, "Pss_bytes": 29902022656, "vram_used_bytes": 190222336, "vram_total_bytes": 4294967296, "gtt_used_bytes": 28124618752, "gtt_total_bytes": 193273528320} +{"t_s": 5.43, "VmRSS_bytes": 38364471296, "VmHWM_bytes": 38364471296, "Pss_bytes": 38430328832, "vram_used_bytes": 190812160, "vram_total_bytes": 4294967296, "gtt_used_bytes": 36324483072, "gtt_total_bytes": 193273528320} +{"t_s": 6.6, "VmRSS_bytes": 45922398208, "VmHWM_bytes": 45922398208, "Pss_bytes": 45920096256, "vram_used_bytes": 191348736, "vram_total_bytes": 4294967296, "gtt_used_bytes": 44513861632, "gtt_total_bytes": 193273528320} +{"t_s": 7.79, "VmRSS_bytes": 54727483392, "VmHWM_bytes": 54727483392, "Pss_bytes": 54798321664, "vram_used_bytes": 191946752, "vram_total_bytes": 4294967296, "gtt_used_bytes": 52707434496, "gtt_total_bytes": 193273528320} +{"t_s": 9.0, "VmRSS_bytes": 62503739392, "VmHWM_bytes": 62503739392, "Pss_bytes": 62524704768, "vram_used_bytes": 192503808, "vram_total_bytes": 4294967296, "gtt_used_bytes": 60901007360, "gtt_total_bytes": 193273528320} +{"t_s": 10.23, "VmRSS_bytes": 71098769408, "VmHWM_bytes": 71098769408, "Pss_bytes": 71147526144, "vram_used_bytes": 193069056, "vram_total_bytes": 4294967296, "gtt_used_bytes": 69096677376, "gtt_total_bytes": 193273528320} +{"t_s": 11.46, "VmRSS_bytes": 78349545472, "VmHWM_bytes": 78349545472, "Pss_bytes": 78355245056, "vram_used_bytes": 193658880, "vram_total_bytes": 4294967296, "gtt_used_bytes": 77277667328, "gtt_total_bytes": 193273528320} +{"t_s": 12.7, "VmRSS_bytes": 80825131008, "VmHWM_bytes": 82473537536, "Pss_bytes": 80822830080, "vram_used_bytes": 195518464, "vram_total_bytes": 4294967296, "gtt_used_bytes": 83107749888, "gtt_total_bytes": 193273528320} +{"t_s": 13.96, "VmRSS_bytes": 80865009664, "VmHWM_bytes": 82473537536, "Pss_bytes": 80899169280, "vram_used_bytes": 195387392, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84168908800, "gtt_total_bytes": 193273528320} +{"t_s": 15.23, "VmRSS_bytes": 81030537216, "VmHWM_bytes": 82473537536, "Pss_bytes": 81028189184, "vram_used_bytes": 195387392, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84168908800, "gtt_total_bytes": 193273528320} +{"t_s": 16.49, "VmRSS_bytes": 81354690560, "VmHWM_bytes": 82473537536, "Pss_bytes": 81415068672, "vram_used_bytes": 195387392, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84189880320, "gtt_total_bytes": 193273528320} +{"t_s": 17.79, "VmRSS_bytes": 81417715712, "VmHWM_bytes": 82473537536, "Pss_bytes": 81415408640, "vram_used_bytes": 195387392, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84189880320, "gtt_total_bytes": 193273528320} +{"t_s": 19.06, "VmRSS_bytes": 81542746112, "VmHWM_bytes": 82473537536, "Pss_bytes": 81614146560, "vram_used_bytes": 195387392, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84189880320, "gtt_total_bytes": 193273528320} +{"t_s": 20.36, "VmRSS_bytes": 81810210816, "VmHWM_bytes": 82473537536, "Pss_bytes": 81807903744, "vram_used_bytes": 195387392, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84189880320, "gtt_total_bytes": 193273528320} +{"t_s": 21.65, "VmRSS_bytes": 81810210816, "VmHWM_bytes": 82473537536, "Pss_bytes": 81807900672, "vram_used_bytes": 195387392, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84189880320, "gtt_total_bytes": 193273528320} +{"t_s": 22.92, "VmRSS_bytes": 81944670208, "VmHWM_bytes": 82473537536, "Pss_bytes": 82008043520, "vram_used_bytes": 195387392, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84189880320, "gtt_total_bytes": 193273528320} +{"t_s": 24.21, "VmRSS_bytes": 82207899648, "VmHWM_bytes": 82473537536, "Pss_bytes": 82205593600, "vram_used_bytes": 195387392, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84189880320, "gtt_total_bytes": 193273528320} +{"t_s": 25.5, "VmRSS_bytes": 82207899648, "VmHWM_bytes": 82473537536, "Pss_bytes": 82205593600, "vram_used_bytes": 195387392, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84189880320, "gtt_total_bytes": 193273528320} +{"t_s": 26.77, "VmRSS_bytes": 82208034816, "VmHWM_bytes": 82473537536, "Pss_bytes": 82250805248, "vram_used_bytes": 195387392, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84189880320, "gtt_total_bytes": 193273528320} +{"t_s": 28.05, "VmRSS_bytes": 82504482816, "VmHWM_bytes": 82504482816, "Pss_bytes": 82552037376, "vram_used_bytes": 195387392, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84189880320, "gtt_total_bytes": 193273528320} +{"t_s": 29.35, "VmRSS_bytes": 82554408960, "VmHWM_bytes": 82554408960, "Pss_bytes": 82552102912, "vram_used_bytes": 195387392, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84189880320, "gtt_total_bytes": 193273528320} +{"t_s": 30.65, "VmRSS_bytes": 82554408960, "VmHWM_bytes": 82554408960, "Pss_bytes": 82552102912, "vram_used_bytes": 195387392, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84189880320, "gtt_total_bytes": 193273528320} +{"t_s": 31.94, "VmRSS_bytes": 82733809664, "VmHWM_bytes": 82733809664, "Pss_bytes": 82748911616, "vram_used_bytes": 195387392, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84189880320, "gtt_total_bytes": 193273528320} +{"t_s": 33.24, "VmRSS_bytes": 82751221760, "VmHWM_bytes": 82751221760, "Pss_bytes": 82748915712, "vram_used_bytes": 195387392, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84189880320, "gtt_total_bytes": 193273528320} +{"t_s": 34.53, "VmRSS_bytes": 82751221760, "VmHWM_bytes": 82751221760, "Pss_bytes": 82748915712, "vram_used_bytes": 195387392, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84189880320, "gtt_total_bytes": 193273528320} +{"t_s": 35.82, "VmRSS_bytes": 82917355520, "VmHWM_bytes": 82917355520, "Pss_bytes": 82967248896, "vram_used_bytes": 195387392, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84189880320, "gtt_total_bytes": 193273528320} +{"t_s": 37.12, "VmRSS_bytes": 83069808640, "VmHWM_bytes": 83069808640, "Pss_bytes": 83067502592, "vram_used_bytes": 195387392, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84189880320, "gtt_total_bytes": 193273528320} +{"t_s": 38.43, "VmRSS_bytes": 83069808640, "VmHWM_bytes": 83069808640, "Pss_bytes": 83067502592, "vram_used_bytes": 195387392, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84189880320, "gtt_total_bytes": 193273528320} +{"t_s": 39.71, "VmRSS_bytes": 83092561920, "VmHWM_bytes": 83092561920, "Pss_bytes": 83131990016, "vram_used_bytes": 195387392, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84189880320, "gtt_total_bytes": 193273528320} +{"t_s": 41.01, "VmRSS_bytes": 83183112192, "VmHWM_bytes": 83183112192, "Pss_bytes": 83180806144, "vram_used_bytes": 195387392, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84189880320, "gtt_total_bytes": 193273528320} +{"t_s": 42.32, "VmRSS_bytes": 83183112192, "VmHWM_bytes": 83183112192, "Pss_bytes": 83180806144, "vram_used_bytes": 195387392, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84189880320, "gtt_total_bytes": 193273528320} +{"t_s": 43.61, "VmRSS_bytes": 83244675072, "VmHWM_bytes": 83244675072, "Pss_bytes": 83277815808, "vram_used_bytes": 195387392, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84189880320, "gtt_total_bytes": 193273528320} +{"t_s": 44.91, "VmRSS_bytes": 83280134144, "VmHWM_bytes": 83280134144, "Pss_bytes": 83277828096, "vram_used_bytes": 195387392, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84189880320, "gtt_total_bytes": 193273528320} +{"t_s": 46.22, "VmRSS_bytes": 83280134144, "VmHWM_bytes": 83280134144, "Pss_bytes": 83277828096, "vram_used_bytes": 195387392, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84189880320, "gtt_total_bytes": 193273528320} +{"t_s": 47.49, "VmRSS_bytes": 79609094144, "VmHWM_bytes": 83277139968, "Pss_bytes": 79372637184, "vram_used_bytes": 195252224, "vram_total_bytes": 4294967296, "gtt_used_bytes": 198942720, "gtt_total_bytes": 193273528320} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-131072-r1-memory-endpoint.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-131072-r1-memory-endpoint.json new file mode 100644 index 0000000000..16d2eeddba --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-131072-r1-memory-endpoint.json @@ -0,0 +1 @@ +{"schema_version": 1, "context_window": 139264, "context_fitted": false, "device": {"active_bytes": 91232258708, "cache_bytes": 0, "peak_bytes": 91543357348, "peak_scope": "since_start_or_health_reset"}} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-131072-r1-metrics.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-131072-r1-metrics.txt new file mode 100644 index 0000000000..6cbb4b0932 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-131072-r1-metrics.txt @@ -0,0 +1,220 @@ +# HELP tensorfold:requests_running Requests in prefill or decode. +# TYPE tensorfold:requests_running gauge +tensorfold:requests_running 0 +# HELP tensorfold:requests_waiting Requests queued or held until a lane is free. +# TYPE tensorfold:requests_waiting gauge +tensorfold:requests_waiting 0 +# HELP tensorfold:generation_tokens_running Generated tokens held by live streams. +# TYPE tensorfold:generation_tokens_running gauge +tensorfold:generation_tokens_running 0 +# HELP tensorfold:prompt_tokens_total Prompt tokens of finished requests. +# TYPE tensorfold:prompt_tokens_total counter +tensorfold:prompt_tokens_total 131328 +# HELP tensorfold:generation_tokens_total Generated tokens of finished requests. +# TYPE tensorfold:generation_tokens_total counter +tensorfold:generation_tokens_total 2 +# HELP tensorfold:kv_cache_usage_ratio Tokens in a stream cache divided by that stream's context window. +# TYPE tensorfold:kv_cache_usage_ratio gauge +tensorfold:kv_cache_usage_ratio{pool="0"} 0 +# HELP tensorfold:mtp_drafted_total Draft tokens verified on finished requests. +# TYPE tensorfold:mtp_drafted_total counter +tensorfold:mtp_drafted_total 0 +# HELP tensorfold:mtp_accepted_total Draft tokens kept on finished requests. +# TYPE tensorfold:mtp_accepted_total counter +tensorfold:mtp_accepted_total 0 +# HELP tensorfold:request_latency_seconds Seconds from arrival to the reply leaving. +# TYPE tensorfold:request_latency_seconds histogram +tensorfold:request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:request_latency_seconds_bucket{le="0.5"} 1 +tensorfold:request_latency_seconds_bucket{le="1"} 1 +tensorfold:request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:request_latency_seconds_bucket{le="5"} 1 +tensorfold:request_latency_seconds_bucket{le="10"} 1 +tensorfold:request_latency_seconds_bucket{le="30"} 1 +tensorfold:request_latency_seconds_bucket{le="60"} 1 +tensorfold:request_latency_seconds_bucket{le="120"} 1 +tensorfold:request_latency_seconds_bucket{le="300"} 2 +tensorfold:request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:request_latency_seconds_sum 278.310725 +tensorfold:request_latency_seconds_count 2 +# HELP tensorfold:time_to_first_token_seconds Seconds from arrival to the first generated token. +# TYPE tensorfold:time_to_first_token_seconds histogram +tensorfold:time_to_first_token_seconds_bucket{le="0.01"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.05"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.25"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="1"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="2.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="10"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="30"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="60"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="120"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="300"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="+Inf"} 2 +tensorfold:time_to_first_token_seconds_sum 278.31028 +tensorfold:time_to_first_token_seconds_count 2 +# HELP tensorfold:request_decode_seconds Seconds a finished request spent decoding. Its sum over generation_tokens_total is the decode rate. +# TYPE tensorfold:request_decode_seconds histogram +tensorfold:request_decode_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_seconds_bucket{le="1"} 2 +tensorfold:request_decode_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_seconds_bucket{le="5"} 2 +tensorfold:request_decode_seconds_bucket{le="10"} 2 +tensorfold:request_decode_seconds_bucket{le="30"} 2 +tensorfold:request_decode_seconds_bucket{le="60"} 2 +tensorfold:request_decode_seconds_bucket{le="120"} 2 +tensorfold:request_decode_seconds_bucket{le="300"} 2 +tensorfold:request_decode_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_seconds_sum 0.000445 +tensorfold:request_decode_seconds_count 2 +# HELP tensorfold:request_time_per_output_token_seconds Seconds from the first generated token to the last, divided by the tokens less one. +# TYPE tensorfold:request_time_per_output_token_seconds histogram +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.005"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.01"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.015"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.02"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.03"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.04"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.05"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.15"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.2"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.3"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.5"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="+Inf"} 0 +tensorfold:request_time_per_output_token_seconds_sum 0 +tensorfold:request_time_per_output_token_seconds_count 0 +# HELP tensorfold:decode_rounds_total Decode rounds used by finished requests. +# TYPE tensorfold:decode_rounds_total counter +tensorfold:decode_rounds_total 0 +# HELP tensorfold:request_prefill_seconds Seconds a finished request's prompt pass took. +# TYPE tensorfold:request_prefill_seconds histogram +tensorfold:request_prefill_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="1"} 1 +tensorfold:request_prefill_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_seconds_bucket{le="60"} 1 +tensorfold:request_prefill_seconds_bucket{le="120"} 1 +tensorfold:request_prefill_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_seconds_sum 278.308383 +tensorfold:request_prefill_seconds_count 2 +# HELP tensorfold:process_resident_bytes Current resident set (VmRSS); device memory is not in it, so it is not a physical footprint (Linux). +# TYPE tensorfold:process_resident_bytes gauge +tensorfold:process_resident_bytes 101683367936 +# HELP tensorfold:process_resident_anon_bytes Current resident anonymous memory (RssAnon): heap, stacks and private maps (Linux). +# TYPE tensorfold:process_resident_anon_bytes gauge +tensorfold:process_resident_anon_bytes 32370016256 +# HELP tensorfold:process_resident_file_bytes Current resident file-backed memory (RssFile): the binary, libraries and mapped files (Linux). +# TYPE tensorfold:process_resident_file_bytes gauge +tensorfold:process_resident_file_bytes 69179088896 +# HELP tensorfold:process_resident_shmem_bytes Current resident shared memory (RssShmem): System V shared memory, tmpfs maps and shared anonymous maps (Linux). +# TYPE tensorfold:process_resident_shmem_bytes gauge +tensorfold:process_resident_shmem_bytes 134262784 +# HELP tensorfold:process_resident_peak_bytes Kernel lifetime peak resident set (VmHWM); never reset by health (Linux). +# TYPE tensorfold:process_resident_peak_bytes gauge +tensorfold:process_resident_peak_bytes 111924826112 +# HELP tensorfold:device_memory_bytes Device memory the engine holds now: weights, caches and live streams; only where the backend counts it (CUDA). +# TYPE tensorfold:device_memory_bytes gauge +tensorfold:device_memory_bytes 91232258708 +# HELP tensorfold:device_memory_peak_bytes The most device memory the engine has held since start or the last /health?reset_peak=1. +# TYPE tensorfold:device_memory_peak_bytes gauge +tensorfold:device_memory_peak_bytes 91543357348 +# HELP tensorfold:pinned_memory_bytes Pinned host memory the engine holds now: staging buffers and windows; only where the backend counts it (CUDA). +# TYPE tensorfold:pinned_memory_bytes gauge +tensorfold:pinned_memory_bytes 0 +# HELP tensorfold:num_requests_running Requests in prefill or decode. A mirror of tensorfold:requests_running. +# TYPE tensorfold:num_requests_running gauge +tensorfold:num_requests_running 0 +# HELP tensorfold:num_requests_waiting Requests queued or held until a lane is free. A mirror of tensorfold:requests_waiting. +# TYPE tensorfold:num_requests_waiting gauge +tensorfold:num_requests_waiting 0 +# HELP tensorfold:kv_cache_usage_perc A stream's cache occupancy under vLLM's name; same streams and ratios as tensorfold:kv_cache_usage_ratio. +# TYPE tensorfold:kv_cache_usage_perc gauge +tensorfold:kv_cache_usage_perc{stream="0"} 0 +# HELP tensorfold:spec_decode_num_draft_tokens_total Draft tokens verified on finished requests, this server's single draft counter. +# TYPE tensorfold:spec_decode_num_draft_tokens_total counter +tensorfold:spec_decode_num_draft_tokens_total 0 +# HELP tensorfold:spec_decode_num_accepted_tokens_total Draft tokens kept on finished requests. +# TYPE tensorfold:spec_decode_num_accepted_tokens_total counter +tensorfold:spec_decode_num_accepted_tokens_total 0 +# HELP tensorfold:e2e_request_latency_seconds Seconds from arrival to the reply leaving, under vLLM's name. +# TYPE tensorfold:e2e_request_latency_seconds histogram +tensorfold:e2e_request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="1"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="10"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="30"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="60"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="120"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="300"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:e2e_request_latency_seconds_sum 278.310725 +tensorfold:e2e_request_latency_seconds_count 2 +# HELP tensorfold:request_decode_time_seconds Seconds a finished request spent decoding, under vLLM's name. +# TYPE tensorfold:request_decode_time_seconds histogram +tensorfold:request_decode_time_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="10"} 2 +tensorfold:request_decode_time_seconds_bucket{le="30"} 2 +tensorfold:request_decode_time_seconds_bucket{le="60"} 2 +tensorfold:request_decode_time_seconds_bucket{le="120"} 2 +tensorfold:request_decode_time_seconds_bucket{le="300"} 2 +tensorfold:request_decode_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_time_seconds_sum 0.000445 +tensorfold:request_decode_time_seconds_count 2 +# HELP tensorfold:request_prefill_time_seconds Seconds a finished request's prompt pass took, under vLLM's name. +# TYPE tensorfold:request_prefill_time_seconds histogram +tensorfold:request_prefill_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="1"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="60"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="120"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_time_seconds_sum 278.308383 +tensorfold:request_prefill_time_seconds_count 2 +# HELP tensorfold:client_disconnections_total Requests a client left before the reply left the server. +# TYPE tensorfold:client_disconnections_total counter +tensorfold:client_disconnections_total 0 +# HELP tensorfold:preemptions_total Requests that had to give a lane up to a later one. +# TYPE tensorfold:preemptions_total counter +tensorfold:preemptions_total 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-131072-r1-samples.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-131072-r1-samples.jsonl new file mode 100644 index 0000000000..1e27d4703e --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-131072-r1-samples.jsonl @@ -0,0 +1,240 @@ +{"t_s": 0.0, "VmRSS_bytes": 73015296, "VmHWM_bytes": 73015296, "Pss_bytes": 70915072, 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"vram_used_bytes": 203366400, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 265.75, "VmRSS_bytes": 101692022784, "VmHWM_bytes": 111924826112, "Pss_bytes": 101689575424, "vram_used_bytes": 203366400, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 267.05, "VmRSS_bytes": 101692022784, "VmHWM_bytes": 111924826112, "Pss_bytes": 101689578496, "vram_used_bytes": 203366400, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 268.33, "VmRSS_bytes": 101692022784, "VmHWM_bytes": 111924826112, "Pss_bytes": 101689578496, "vram_used_bytes": 203366400, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 269.62, "VmRSS_bytes": 101692022784, "VmHWM_bytes": 111924826112, "Pss_bytes": 101689578496, "vram_used_bytes": 203366400, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 270.92, "VmRSS_bytes": 101692022784, "VmHWM_bytes": 111924826112, "Pss_bytes": 101689578496, "vram_used_bytes": 203366400, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 272.19, "VmRSS_bytes": 101692022784, "VmHWM_bytes": 111924826112, "Pss_bytes": 101689578496, "vram_used_bytes": 203366400, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 273.47, "VmRSS_bytes": 101692022784, "VmHWM_bytes": 111924826112, "Pss_bytes": 101689578496, "vram_used_bytes": 203366400, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 274.78, "VmRSS_bytes": 101692022784, "VmHWM_bytes": 111924826112, "Pss_bytes": 101689578496, "vram_used_bytes": 203366400, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 276.06, "VmRSS_bytes": 101692022784, "VmHWM_bytes": 111924826112, "Pss_bytes": 101689578496, "vram_used_bytes": 203366400, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 277.34, "VmRSS_bytes": 101692022784, "VmHWM_bytes": 111924826112, "Pss_bytes": 101689578496, "vram_used_bytes": 203366400, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 278.63, "VmRSS_bytes": 101692022784, "VmHWM_bytes": 111924826112, "Pss_bytes": 101689619456, "vram_used_bytes": 203366400, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 279.91, "VmRSS_bytes": 101692022784, "VmHWM_bytes": 111924826112, "Pss_bytes": 101689578496, "vram_used_bytes": 203366400, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 281.21, "VmRSS_bytes": 101692022784, "VmHWM_bytes": 111924826112, "Pss_bytes": 101689578496, "vram_used_bytes": 203366400, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 282.5, "VmRSS_bytes": 101692022784, "VmHWM_bytes": 111924826112, "Pss_bytes": 101689578496, "vram_used_bytes": 203366400, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 283.77, "VmRSS_bytes": 101692022784, "VmHWM_bytes": 111924826112, "Pss_bytes": 101689578496, "vram_used_bytes": 203366400, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 285.07, "VmRSS_bytes": 101692022784, "VmHWM_bytes": 111924826112, "Pss_bytes": 101689578496, "vram_used_bytes": 203366400, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 286.37, "VmRSS_bytes": 101692022784, "VmHWM_bytes": 111924826112, "Pss_bytes": 101689578496, "vram_used_bytes": 203366400, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 287.64, "VmRSS_bytes": 101691760640, "VmHWM_bytes": 111924826112, "Pss_bytes": 101689316352, "vram_used_bytes": 203366400, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 288.94, "VmRSS_bytes": 101691760640, "VmHWM_bytes": 111924826112, "Pss_bytes": 101689316352, "vram_used_bytes": 203366400, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 290.24, "VmRSS_bytes": 101691760640, "VmHWM_bytes": 111924826112, "Pss_bytes": 101689316352, "vram_used_bytes": 203366400, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 291.52, "VmRSS_bytes": 101691760640, "VmHWM_bytes": 111924826112, "Pss_bytes": 101689316352, "vram_used_bytes": 203366400, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 292.81, "VmRSS_bytes": 101691760640, "VmHWM_bytes": 111924826112, "Pss_bytes": 101689313280, "vram_used_bytes": 203366400, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 294.11, "VmRSS_bytes": 101691760640, "VmHWM_bytes": 111924826112, "Pss_bytes": 101689313280, "vram_used_bytes": 203366400, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 295.38, "VmRSS_bytes": 101691760640, "VmHWM_bytes": 111924826112, "Pss_bytes": 101689313280, "vram_used_bytes": 203366400, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 296.67, "VmRSS_bytes": 101691760640, "VmHWM_bytes": 111924826112, "Pss_bytes": 101689313280, "vram_used_bytes": 203366400, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 297.96, "VmRSS_bytes": 101690974208, "VmHWM_bytes": 111924826112, "Pss_bytes": 101688526848, "vram_used_bytes": 203366400, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 299.24, "VmRSS_bytes": 101690974208, "VmHWM_bytes": 111924826112, "Pss_bytes": 101688519680, "vram_used_bytes": 203366400, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 300.54, "VmRSS_bytes": 101690974208, "VmHWM_bytes": 111924826112, "Pss_bytes": 101688526848, "vram_used_bytes": 203366400, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 301.83, "VmRSS_bytes": 101690974208, "VmHWM_bytes": 111924826112, "Pss_bytes": 101688526848, "vram_used_bytes": 203366400, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 303.12, "VmRSS_bytes": 101690974208, "VmHWM_bytes": 111924826112, "Pss_bytes": 101688526848, "vram_used_bytes": 203366400, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 304.42, "VmRSS_bytes": 101690974208, "VmHWM_bytes": 111924826112, "Pss_bytes": 101688526848, "vram_used_bytes": 203366400, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 305.72, "VmRSS_bytes": 101690974208, "VmHWM_bytes": 111924826112, "Pss_bytes": 101688526848, "vram_used_bytes": 203366400, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 307.0, "VmRSS_bytes": 101683179520, "VmHWM_bytes": 111924826112, "Pss_bytes": 101680742400, "vram_used_bytes": 203366400, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92200919040, "gtt_total_bytes": 193273528320} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-131072-r2-memory-endpoint.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-131072-r2-memory-endpoint.json new file mode 100644 index 0000000000..16d2eeddba --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-131072-r2-memory-endpoint.json @@ -0,0 +1 @@ +{"schema_version": 1, "context_window": 139264, "context_fitted": false, "device": {"active_bytes": 91232258708, "cache_bytes": 0, "peak_bytes": 91543357348, "peak_scope": "since_start_or_health_reset"}} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-131072-r2-metrics.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-131072-r2-metrics.txt new file mode 100644 index 0000000000..0f04e7f8fc --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-131072-r2-metrics.txt @@ -0,0 +1,220 @@ +# HELP tensorfold:requests_running Requests in prefill or decode. +# TYPE tensorfold:requests_running gauge +tensorfold:requests_running 0 +# HELP tensorfold:requests_waiting Requests queued or held until a lane is free. +# TYPE tensorfold:requests_waiting gauge +tensorfold:requests_waiting 0 +# HELP tensorfold:generation_tokens_running Generated tokens held by live streams. +# TYPE tensorfold:generation_tokens_running gauge +tensorfold:generation_tokens_running 0 +# HELP tensorfold:prompt_tokens_total Prompt tokens of finished requests. +# TYPE tensorfold:prompt_tokens_total counter +tensorfold:prompt_tokens_total 131328 +# HELP tensorfold:generation_tokens_total Generated tokens of finished requests. +# TYPE tensorfold:generation_tokens_total counter +tensorfold:generation_tokens_total 2 +# HELP tensorfold:kv_cache_usage_ratio Tokens in a stream cache divided by that stream's context window. +# TYPE tensorfold:kv_cache_usage_ratio gauge +tensorfold:kv_cache_usage_ratio{pool="0"} 0 +# HELP tensorfold:mtp_drafted_total Draft tokens verified on finished requests. +# TYPE tensorfold:mtp_drafted_total counter +tensorfold:mtp_drafted_total 0 +# HELP tensorfold:mtp_accepted_total Draft tokens kept on finished requests. +# TYPE tensorfold:mtp_accepted_total counter +tensorfold:mtp_accepted_total 0 +# HELP tensorfold:request_latency_seconds Seconds from arrival to the reply leaving. +# TYPE tensorfold:request_latency_seconds histogram +tensorfold:request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:request_latency_seconds_bucket{le="0.5"} 1 +tensorfold:request_latency_seconds_bucket{le="1"} 1 +tensorfold:request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:request_latency_seconds_bucket{le="5"} 1 +tensorfold:request_latency_seconds_bucket{le="10"} 1 +tensorfold:request_latency_seconds_bucket{le="30"} 1 +tensorfold:request_latency_seconds_bucket{le="60"} 1 +tensorfold:request_latency_seconds_bucket{le="120"} 1 +tensorfold:request_latency_seconds_bucket{le="300"} 2 +tensorfold:request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:request_latency_seconds_sum 278.437859 +tensorfold:request_latency_seconds_count 2 +# HELP tensorfold:time_to_first_token_seconds Seconds from arrival to the first generated token. +# TYPE tensorfold:time_to_first_token_seconds histogram +tensorfold:time_to_first_token_seconds_bucket{le="0.01"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.05"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.25"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="1"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="2.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="10"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="30"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="60"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="120"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="300"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="+Inf"} 2 +tensorfold:time_to_first_token_seconds_sum 278.437445 +tensorfold:time_to_first_token_seconds_count 2 +# HELP tensorfold:request_decode_seconds Seconds a finished request spent decoding. Its sum over generation_tokens_total is the decode rate. +# TYPE tensorfold:request_decode_seconds histogram +tensorfold:request_decode_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_seconds_bucket{le="1"} 2 +tensorfold:request_decode_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_seconds_bucket{le="5"} 2 +tensorfold:request_decode_seconds_bucket{le="10"} 2 +tensorfold:request_decode_seconds_bucket{le="30"} 2 +tensorfold:request_decode_seconds_bucket{le="60"} 2 +tensorfold:request_decode_seconds_bucket{le="120"} 2 +tensorfold:request_decode_seconds_bucket{le="300"} 2 +tensorfold:request_decode_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_seconds_sum 0.000414 +tensorfold:request_decode_seconds_count 2 +# HELP tensorfold:request_time_per_output_token_seconds Seconds from the first generated token to the last, divided by the tokens less one. +# TYPE tensorfold:request_time_per_output_token_seconds histogram +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.005"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.01"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.015"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.02"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.03"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.04"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.05"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.15"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.2"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.3"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.5"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="+Inf"} 0 +tensorfold:request_time_per_output_token_seconds_sum 0 +tensorfold:request_time_per_output_token_seconds_count 0 +# HELP tensorfold:decode_rounds_total Decode rounds used by finished requests. +# TYPE tensorfold:decode_rounds_total counter +tensorfold:decode_rounds_total 0 +# HELP tensorfold:request_prefill_seconds Seconds a finished request's prompt pass took. +# TYPE tensorfold:request_prefill_seconds histogram +tensorfold:request_prefill_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="1"} 1 +tensorfold:request_prefill_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_seconds_bucket{le="60"} 1 +tensorfold:request_prefill_seconds_bucket{le="120"} 1 +tensorfold:request_prefill_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_seconds_sum 278.435908 +tensorfold:request_prefill_seconds_count 2 +# HELP tensorfold:process_resident_bytes Current resident set (VmRSS); device memory is not in it, so it is not a physical footprint (Linux). +# TYPE tensorfold:process_resident_bytes gauge +tensorfold:process_resident_bytes 99028066304 +# HELP tensorfold:process_resident_anon_bytes Current resident anonymous memory (RssAnon): heap, stacks and private maps (Linux). +# TYPE tensorfold:process_resident_anon_bytes gauge +tensorfold:process_resident_anon_bytes 32369213440 +# HELP tensorfold:process_resident_file_bytes Current resident file-backed memory (RssFile): the binary, libraries and mapped files (Linux). +# TYPE tensorfold:process_resident_file_bytes gauge +tensorfold:process_resident_file_bytes 66524590080 +# HELP tensorfold:process_resident_shmem_bytes Current resident shared memory (RssShmem): System V shared memory, tmpfs maps and shared anonymous maps (Linux). +# TYPE tensorfold:process_resident_shmem_bytes gauge +tensorfold:process_resident_shmem_bytes 134262784 +# HELP tensorfold:process_resident_peak_bytes Kernel lifetime peak resident set (VmHWM); never reset by health (Linux). +# TYPE tensorfold:process_resident_peak_bytes gauge +tensorfold:process_resident_peak_bytes 110989012992 +# HELP tensorfold:device_memory_bytes Device memory the engine holds now: weights, caches and live streams; only where the backend counts it (CUDA). +# TYPE tensorfold:device_memory_bytes gauge +tensorfold:device_memory_bytes 91232258708 +# HELP tensorfold:device_memory_peak_bytes The most device memory the engine has held since start or the last /health?reset_peak=1. +# TYPE tensorfold:device_memory_peak_bytes gauge +tensorfold:device_memory_peak_bytes 91543357348 +# HELP tensorfold:pinned_memory_bytes Pinned host memory the engine holds now: staging buffers and windows; only where the backend counts it (CUDA). +# TYPE tensorfold:pinned_memory_bytes gauge +tensorfold:pinned_memory_bytes 0 +# HELP tensorfold:num_requests_running Requests in prefill or decode. A mirror of tensorfold:requests_running. +# TYPE tensorfold:num_requests_running gauge +tensorfold:num_requests_running 0 +# HELP tensorfold:num_requests_waiting Requests queued or held until a lane is free. A mirror of tensorfold:requests_waiting. +# TYPE tensorfold:num_requests_waiting gauge +tensorfold:num_requests_waiting 0 +# HELP tensorfold:kv_cache_usage_perc A stream's cache occupancy under vLLM's name; same streams and ratios as tensorfold:kv_cache_usage_ratio. +# TYPE tensorfold:kv_cache_usage_perc gauge +tensorfold:kv_cache_usage_perc{stream="0"} 0 +# HELP tensorfold:spec_decode_num_draft_tokens_total Draft tokens verified on finished requests, this server's single draft counter. +# TYPE tensorfold:spec_decode_num_draft_tokens_total counter +tensorfold:spec_decode_num_draft_tokens_total 0 +# HELP tensorfold:spec_decode_num_accepted_tokens_total Draft tokens kept on finished requests. +# TYPE tensorfold:spec_decode_num_accepted_tokens_total counter +tensorfold:spec_decode_num_accepted_tokens_total 0 +# HELP tensorfold:e2e_request_latency_seconds Seconds from arrival to the reply leaving, under vLLM's name. +# TYPE tensorfold:e2e_request_latency_seconds histogram +tensorfold:e2e_request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="1"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="10"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="30"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="60"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="120"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="300"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:e2e_request_latency_seconds_sum 278.437859 +tensorfold:e2e_request_latency_seconds_count 2 +# HELP tensorfold:request_decode_time_seconds Seconds a finished request spent decoding, under vLLM's name. +# TYPE tensorfold:request_decode_time_seconds histogram +tensorfold:request_decode_time_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="10"} 2 +tensorfold:request_decode_time_seconds_bucket{le="30"} 2 +tensorfold:request_decode_time_seconds_bucket{le="60"} 2 +tensorfold:request_decode_time_seconds_bucket{le="120"} 2 +tensorfold:request_decode_time_seconds_bucket{le="300"} 2 +tensorfold:request_decode_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_time_seconds_sum 0.000414 +tensorfold:request_decode_time_seconds_count 2 +# HELP tensorfold:request_prefill_time_seconds Seconds a finished request's prompt pass took, under vLLM's name. +# TYPE tensorfold:request_prefill_time_seconds histogram +tensorfold:request_prefill_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="1"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="60"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="120"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_time_seconds_sum 278.435908 +tensorfold:request_prefill_time_seconds_count 2 +# HELP tensorfold:client_disconnections_total Requests a client left before the reply left the server. +# TYPE tensorfold:client_disconnections_total counter +tensorfold:client_disconnections_total 0 +# HELP tensorfold:preemptions_total Requests that had to give a lane up to a later one. +# TYPE tensorfold:preemptions_total counter +tensorfold:preemptions_total 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-131072-r2-samples.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-131072-r2-samples.jsonl new file mode 100644 index 0000000000..70b73e2508 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-131072-r2-samples.jsonl @@ -0,0 +1,236 @@ +{"t_s": 0.0, "VmRSS_bytes": 73175040, "VmHWM_bytes": 73175040, "Pss_bytes": 71069696, 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"vram_used_bytes": 199041024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 255.84, "VmRSS_bytes": 99036213248, "VmHWM_bytes": 110989012992, "Pss_bytes": 99033852928, "vram_used_bytes": 199041024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 257.14, "VmRSS_bytes": 99036213248, "VmHWM_bytes": 110989012992, "Pss_bytes": 99033852928, "vram_used_bytes": 199041024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 258.45, "VmRSS_bytes": 99036213248, "VmHWM_bytes": 110989012992, "Pss_bytes": 99033852928, "vram_used_bytes": 199041024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 259.79, "VmRSS_bytes": 99036213248, "VmHWM_bytes": 110989012992, "Pss_bytes": 99033852928, "vram_used_bytes": 199041024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 261.1, "VmRSS_bytes": 99036213248, "VmHWM_bytes": 110989012992, "Pss_bytes": 99033852928, "vram_used_bytes": 199041024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 262.41, "VmRSS_bytes": 99036213248, "VmHWM_bytes": 110989012992, "Pss_bytes": 99033852928, "vram_used_bytes": 199041024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 263.74, "VmRSS_bytes": 99036213248, "VmHWM_bytes": 110989012992, "Pss_bytes": 99033851904, "vram_used_bytes": 199041024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 265.06, "VmRSS_bytes": 99036213248, "VmHWM_bytes": 110989012992, "Pss_bytes": 99033851904, "vram_used_bytes": 199041024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 266.36, "VmRSS_bytes": 99036213248, "VmHWM_bytes": 110989012992, "Pss_bytes": 99033851904, "vram_used_bytes": 199041024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 267.67, "VmRSS_bytes": 99036213248, "VmHWM_bytes": 110989012992, "Pss_bytes": 99033851904, "vram_used_bytes": 199041024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 269.01, "VmRSS_bytes": 99036213248, "VmHWM_bytes": 110989012992, "Pss_bytes": 99033851904, "vram_used_bytes": 199041024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 270.31, "VmRSS_bytes": 99036213248, "VmHWM_bytes": 110989012992, "Pss_bytes": 99033849856, "vram_used_bytes": 199041024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 271.61, "VmRSS_bytes": 99036213248, "VmHWM_bytes": 110989012992, "Pss_bytes": 99033851904, "vram_used_bytes": 199041024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 272.94, "VmRSS_bytes": 99036213248, "VmHWM_bytes": 110989012992, "Pss_bytes": 99033851904, "vram_used_bytes": 199041024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 274.25, "VmRSS_bytes": 99036213248, "VmHWM_bytes": 110989012992, "Pss_bytes": 99033851904, "vram_used_bytes": 199041024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 275.55, "VmRSS_bytes": 99036213248, "VmHWM_bytes": 110989012992, "Pss_bytes": 99033851904, "vram_used_bytes": 199041024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 276.88, "VmRSS_bytes": 99036213248, "VmHWM_bytes": 110989012992, "Pss_bytes": 99033851904, "vram_used_bytes": 199041024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 278.19, "VmRSS_bytes": 99036213248, "VmHWM_bytes": 110989012992, "Pss_bytes": 99033851904, "vram_used_bytes": 199041024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 279.49, "VmRSS_bytes": 99036213248, "VmHWM_bytes": 110989012992, "Pss_bytes": 99033851904, "vram_used_bytes": 199041024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 280.82, "VmRSS_bytes": 99036213248, "VmHWM_bytes": 110989012992, "Pss_bytes": 99033851904, "vram_used_bytes": 199041024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 282.14, "VmRSS_bytes": 99036213248, "VmHWM_bytes": 110989012992, "Pss_bytes": 99033851904, "vram_used_bytes": 199041024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 283.44, "VmRSS_bytes": 99036213248, "VmHWM_bytes": 110989012992, "Pss_bytes": 99033851904, "vram_used_bytes": 199041024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 284.75, "VmRSS_bytes": 99036213248, "VmHWM_bytes": 110989012992, "Pss_bytes": 99033851904, "vram_used_bytes": 199041024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 286.08, "VmRSS_bytes": 99036213248, "VmHWM_bytes": 110989012992, "Pss_bytes": 99033851904, "vram_used_bytes": 199041024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 287.39, "VmRSS_bytes": 99036213248, "VmHWM_bytes": 110989012992, "Pss_bytes": 99033851904, "vram_used_bytes": 199041024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 288.69, "VmRSS_bytes": 99036213248, "VmHWM_bytes": 110989012992, "Pss_bytes": 99033851904, "vram_used_bytes": 199041024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 290.02, "VmRSS_bytes": 99036213248, "VmHWM_bytes": 110989012992, "Pss_bytes": 99033851904, "vram_used_bytes": 199041024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 291.34, "VmRSS_bytes": 99036213248, "VmHWM_bytes": 110989012992, "Pss_bytes": 99033851904, "vram_used_bytes": 199041024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 292.65, "VmRSS_bytes": 99036213248, "VmHWM_bytes": 110989012992, "Pss_bytes": 99033851904, "vram_used_bytes": 199041024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 293.96, "VmRSS_bytes": 99036213248, "VmHWM_bytes": 110989012992, "Pss_bytes": 99033851904, "vram_used_bytes": 199041024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 295.29, "VmRSS_bytes": 99036213248, "VmHWM_bytes": 110989012992, "Pss_bytes": 99033851904, "vram_used_bytes": 199041024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 296.59, "VmRSS_bytes": 99036213248, "VmHWM_bytes": 110989012992, "Pss_bytes": 99033851904, "vram_used_bytes": 199041024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 297.9, "VmRSS_bytes": 99036213248, "VmHWM_bytes": 110989012992, "Pss_bytes": 99033851904, "vram_used_bytes": 199041024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 299.24, "VmRSS_bytes": 99036213248, "VmHWM_bytes": 110989012992, "Pss_bytes": 99033851904, "vram_used_bytes": 199041024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 300.54, "VmRSS_bytes": 99036213248, "VmHWM_bytes": 110989012992, "Pss_bytes": 99033851904, "vram_used_bytes": 199041024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 301.84, "VmRSS_bytes": 99036213248, "VmHWM_bytes": 110989012992, "Pss_bytes": 99033851904, "vram_used_bytes": 199041024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 303.17, "VmRSS_bytes": 99036213248, "VmHWM_bytes": 110989012992, "Pss_bytes": 99033851904, "vram_used_bytes": 199041024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 304.48, "VmRSS_bytes": 99036213248, "VmHWM_bytes": 110989012992, "Pss_bytes": 99033851904, "vram_used_bytes": 199041024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 305.78, "VmRSS_bytes": 99036213248, "VmHWM_bytes": 110989012992, "Pss_bytes": 99033851904, "vram_used_bytes": 199041024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 307.1, "VmRSS_bytes": 99036213248, "VmHWM_bytes": 110989012992, "Pss_bytes": 99033851904, "vram_used_bytes": 199041024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 92513394688, "gtt_total_bytes": 193273528320} +{"t_s": 308.4, "VmRSS_bytes": 98949877760, "VmHWM_bytes": 110989012992, "Pss_bytes": 98947530752, "vram_used_bytes": 194682880, "vram_total_bytes": 4294967296, "gtt_used_bytes": 61040570368, "gtt_total_bytes": 193273528320} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-2048-r1-memory-endpoint.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-2048-r1-memory-endpoint.json new file mode 100644 index 0000000000..a56240b905 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-2048-r1-memory-endpoint.json @@ -0,0 +1 @@ +{"schema_version": 1, "context_window": 10240, "context_fitted": false, "device": {"active_bytes": 87565912724, "cache_bytes": 0, "peak_bytes": 87571482532, "peak_scope": "since_start_or_health_reset"}} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-2048-r1-metrics.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-2048-r1-metrics.txt new file mode 100644 index 0000000000..842ff7a665 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-2048-r1-metrics.txt @@ -0,0 +1,220 @@ +# HELP tensorfold:requests_running Requests in prefill or decode. +# TYPE tensorfold:requests_running gauge +tensorfold:requests_running 0 +# HELP tensorfold:requests_waiting Requests queued or held until a lane is free. +# TYPE tensorfold:requests_waiting gauge +tensorfold:requests_waiting 0 +# HELP tensorfold:generation_tokens_running Generated tokens held by live streams. +# TYPE tensorfold:generation_tokens_running gauge +tensorfold:generation_tokens_running 0 +# HELP tensorfold:prompt_tokens_total Prompt tokens of finished requests. +# TYPE tensorfold:prompt_tokens_total counter +tensorfold:prompt_tokens_total 2304 +# HELP tensorfold:generation_tokens_total Generated tokens of finished requests. +# TYPE tensorfold:generation_tokens_total counter +tensorfold:generation_tokens_total 2 +# HELP tensorfold:kv_cache_usage_ratio Tokens in a stream cache divided by that stream's context window. +# TYPE tensorfold:kv_cache_usage_ratio gauge +tensorfold:kv_cache_usage_ratio{pool="0"} 0 +# HELP tensorfold:mtp_drafted_total Draft tokens verified on finished requests. +# TYPE tensorfold:mtp_drafted_total counter +tensorfold:mtp_drafted_total 0 +# HELP tensorfold:mtp_accepted_total Draft tokens kept on finished requests. +# TYPE tensorfold:mtp_accepted_total counter +tensorfold:mtp_accepted_total 0 +# HELP tensorfold:request_latency_seconds Seconds from arrival to the reply leaving. +# TYPE tensorfold:request_latency_seconds histogram +tensorfold:request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:request_latency_seconds_bucket{le="0.5"} 1 +tensorfold:request_latency_seconds_bucket{le="1"} 1 +tensorfold:request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:request_latency_seconds_bucket{le="5"} 2 +tensorfold:request_latency_seconds_bucket{le="10"} 2 +tensorfold:request_latency_seconds_bucket{le="30"} 2 +tensorfold:request_latency_seconds_bucket{le="60"} 2 +tensorfold:request_latency_seconds_bucket{le="120"} 2 +tensorfold:request_latency_seconds_bucket{le="300"} 2 +tensorfold:request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:request_latency_seconds_sum 3.448033 +tensorfold:request_latency_seconds_count 2 +# HELP tensorfold:time_to_first_token_seconds Seconds from arrival to the first generated token. +# TYPE tensorfold:time_to_first_token_seconds histogram +tensorfold:time_to_first_token_seconds_bucket{le="0.01"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.05"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.25"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="1"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="2.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="5"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="10"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="30"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="60"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="120"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="300"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="+Inf"} 2 +tensorfold:time_to_first_token_seconds_sum 3.444594 +tensorfold:time_to_first_token_seconds_count 2 +# HELP tensorfold:request_decode_seconds Seconds a finished request spent decoding. Its sum over generation_tokens_total is the decode rate. +# TYPE tensorfold:request_decode_seconds histogram +tensorfold:request_decode_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_seconds_bucket{le="1"} 2 +tensorfold:request_decode_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_seconds_bucket{le="5"} 2 +tensorfold:request_decode_seconds_bucket{le="10"} 2 +tensorfold:request_decode_seconds_bucket{le="30"} 2 +tensorfold:request_decode_seconds_bucket{le="60"} 2 +tensorfold:request_decode_seconds_bucket{le="120"} 2 +tensorfold:request_decode_seconds_bucket{le="300"} 2 +tensorfold:request_decode_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_seconds_sum 0.003439 +tensorfold:request_decode_seconds_count 2 +# HELP tensorfold:request_time_per_output_token_seconds Seconds from the first generated token to the last, divided by the tokens less one. +# TYPE tensorfold:request_time_per_output_token_seconds histogram +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.005"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.01"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.015"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.02"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.03"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.04"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.05"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.15"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.2"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.3"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.5"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="+Inf"} 0 +tensorfold:request_time_per_output_token_seconds_sum 0 +tensorfold:request_time_per_output_token_seconds_count 0 +# HELP tensorfold:decode_rounds_total Decode rounds used by finished requests. +# TYPE tensorfold:decode_rounds_total counter +tensorfold:decode_rounds_total 0 +# HELP tensorfold:request_prefill_seconds Seconds a finished request's prompt pass took. +# TYPE tensorfold:request_prefill_seconds histogram +tensorfold:request_prefill_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="1"} 1 +tensorfold:request_prefill_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="5"} 2 +tensorfold:request_prefill_seconds_bucket{le="10"} 2 +tensorfold:request_prefill_seconds_bucket{le="30"} 2 +tensorfold:request_prefill_seconds_bucket{le="60"} 2 +tensorfold:request_prefill_seconds_bucket{le="120"} 2 +tensorfold:request_prefill_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_seconds_sum 3.442612 +tensorfold:request_prefill_seconds_count 2 +# HELP tensorfold:process_resident_bytes Current resident set (VmRSS); device memory is not in it, so it is not a physical footprint (Linux). +# TYPE tensorfold:process_resident_bytes gauge +tensorfold:process_resident_bytes 105745997824 +# HELP tensorfold:process_resident_anon_bytes Current resident anonymous memory (RssAnon): heap, stacks and private maps (Linux). +# TYPE tensorfold:process_resident_anon_bytes gauge +tensorfold:process_resident_anon_bytes 32360394752 +# HELP tensorfold:process_resident_file_bytes Current resident file-backed memory (RssFile): the binary, libraries and mapped files (Linux). +# TYPE tensorfold:process_resident_file_bytes gauge +tensorfold:process_resident_file_bytes 73251340288 +# HELP tensorfold:process_resident_shmem_bytes Current resident shared memory (RssShmem): System V shared memory, tmpfs maps and shared anonymous maps (Linux). +# TYPE tensorfold:process_resident_shmem_bytes gauge +tensorfold:process_resident_shmem_bytes 134262784 +# HELP tensorfold:process_resident_peak_bytes Kernel lifetime peak resident set (VmHWM); never reset by health (Linux). +# TYPE tensorfold:process_resident_peak_bytes gauge +tensorfold:process_resident_peak_bytes 109025759232 +# HELP tensorfold:device_memory_bytes Device memory the engine holds now: weights, caches and live streams; only where the backend counts it (CUDA). +# TYPE tensorfold:device_memory_bytes gauge +tensorfold:device_memory_bytes 87565912724 +# HELP tensorfold:device_memory_peak_bytes The most device memory the engine has held since start or the last /health?reset_peak=1. +# TYPE tensorfold:device_memory_peak_bytes gauge +tensorfold:device_memory_peak_bytes 87571482532 +# HELP tensorfold:pinned_memory_bytes Pinned host memory the engine holds now: staging buffers and windows; only where the backend counts it (CUDA). +# TYPE tensorfold:pinned_memory_bytes gauge +tensorfold:pinned_memory_bytes 0 +# HELP tensorfold:num_requests_running Requests in prefill or decode. A mirror of tensorfold:requests_running. +# TYPE tensorfold:num_requests_running gauge +tensorfold:num_requests_running 0 +# HELP tensorfold:num_requests_waiting Requests queued or held until a lane is free. A mirror of tensorfold:requests_waiting. +# TYPE tensorfold:num_requests_waiting gauge +tensorfold:num_requests_waiting 0 +# HELP tensorfold:kv_cache_usage_perc A stream's cache occupancy under vLLM's name; same streams and ratios as tensorfold:kv_cache_usage_ratio. +# TYPE tensorfold:kv_cache_usage_perc gauge +tensorfold:kv_cache_usage_perc{stream="0"} 0 +# HELP tensorfold:spec_decode_num_draft_tokens_total Draft tokens verified on finished requests, this server's single draft counter. +# TYPE tensorfold:spec_decode_num_draft_tokens_total counter +tensorfold:spec_decode_num_draft_tokens_total 0 +# HELP tensorfold:spec_decode_num_accepted_tokens_total Draft tokens kept on finished requests. +# TYPE tensorfold:spec_decode_num_accepted_tokens_total counter +tensorfold:spec_decode_num_accepted_tokens_total 0 +# HELP tensorfold:e2e_request_latency_seconds Seconds from arrival to the reply leaving, under vLLM's name. +# TYPE tensorfold:e2e_request_latency_seconds histogram +tensorfold:e2e_request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="1"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="5"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="10"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="30"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="60"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="120"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="300"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:e2e_request_latency_seconds_sum 3.448033 +tensorfold:e2e_request_latency_seconds_count 2 +# HELP tensorfold:request_decode_time_seconds Seconds a finished request spent decoding, under vLLM's name. +# TYPE tensorfold:request_decode_time_seconds histogram +tensorfold:request_decode_time_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="10"} 2 +tensorfold:request_decode_time_seconds_bucket{le="30"} 2 +tensorfold:request_decode_time_seconds_bucket{le="60"} 2 +tensorfold:request_decode_time_seconds_bucket{le="120"} 2 +tensorfold:request_decode_time_seconds_bucket{le="300"} 2 +tensorfold:request_decode_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_time_seconds_sum 0.003439 +tensorfold:request_decode_time_seconds_count 2 +# HELP tensorfold:request_prefill_time_seconds Seconds a finished request's prompt pass took, under vLLM's name. +# TYPE tensorfold:request_prefill_time_seconds histogram +tensorfold:request_prefill_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="1"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="5"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="10"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="30"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="60"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="120"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_time_seconds_sum 3.442612 +tensorfold:request_prefill_time_seconds_count 2 +# HELP tensorfold:client_disconnections_total Requests a client left before the reply left the server. +# TYPE tensorfold:client_disconnections_total counter +tensorfold:client_disconnections_total 0 +# HELP tensorfold:preemptions_total Requests that had to give a lane up to a later one. +# TYPE tensorfold:preemptions_total counter +tensorfold:preemptions_total 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-2048-r1-samples.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-2048-r1-samples.jsonl new file mode 100644 index 0000000000..fdf9b8711e --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-2048-r1-samples.jsonl @@ -0,0 +1,27 @@ +{"t_s": 0.0, "VmRSS_bytes": 75272192, "VmHWM_bytes": 75272192, "Pss_bytes": 72965120, "vram_used_bytes": 187682816, "vram_total_bytes": 4294967296, "gtt_used_bytes": 31657984, "gtt_total_bytes": 193273528320} +{"t_s": 1.03, "VmRSS_bytes": 10223316992, "VmHWM_bytes": 10223316992, "Pss_bytes": 10220860416, "vram_used_bytes": 188805120, "vram_total_bytes": 4294967296, "gtt_used_bytes": 7692677120, "gtt_total_bytes": 193273528320} +{"t_s": 2.07, "VmRSS_bytes": 18381799424, "VmHWM_bytes": 18381799424, "Pss_bytes": 18379342848, "vram_used_bytes": 189468672, "vram_total_bytes": 4294967296, "gtt_used_bytes": 16699944960, "gtt_total_bytes": 193273528320} +{"t_s": 3.14, "VmRSS_bytes": 27596992512, "VmHWM_bytes": 27596992512, "Pss_bytes": 27614983168, "vram_used_bytes": 190062592, "vram_total_bytes": 4294967296, "gtt_used_bytes": 24916586496, "gtt_total_bytes": 193273528320} +{"t_s": 4.23, "VmRSS_bytes": 36222611456, "VmHWM_bytes": 36222611456, "Pss_bytes": 36220154880, "vram_used_bytes": 190705664, "vram_total_bytes": 4294967296, "gtt_used_bytes": 34769006592, "gtt_total_bytes": 193273528320} +{"t_s": 5.32, "VmRSS_bytes": 45909413888, "VmHWM_bytes": 45909413888, "Pss_bytes": 45906932736, "vram_used_bytes": 191266816, "vram_total_bytes": 4294967296, "gtt_used_bytes": 43834994688, "gtt_total_bytes": 193273528320} +{"t_s": 6.45, "VmRSS_bytes": 54064611328, "VmHWM_bytes": 54064611328, "Pss_bytes": 54108292096, "vram_used_bytes": 191938560, "vram_total_bytes": 4294967296, "gtt_used_bytes": 52844359680, "gtt_total_bytes": 193273528320} +{"t_s": 7.6, "VmRSS_bytes": 63798833152, "VmHWM_bytes": 63798833152, "Pss_bytes": 63796376576, "vram_used_bytes": 192630784, "vram_total_bytes": 4294967296, "gtt_used_bytes": 62703071232, "gtt_total_bytes": 193273528320} +{"t_s": 8.76, "VmRSS_bytes": 73528184832, "VmHWM_bytes": 73528184832, "Pss_bytes": 73525711872, "vram_used_bytes": 193318912, "vram_total_bytes": 4294967296, "gtt_used_bytes": 72557588480, "gtt_total_bytes": 193273528320} +{"t_s": 9.94, "VmRSS_bytes": 81254641664, "VmHWM_bytes": 82502762496, "Pss_bytes": 81277350912, "vram_used_bytes": 194994176, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 11.12, "VmRSS_bytes": 85024051200, "VmHWM_bytes": 85183909888, "Pss_bytes": 85009384448, "vram_used_bytes": 194994176, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 12.3, "VmRSS_bytes": 88924393472, "VmHWM_bytes": 88924393472, "Pss_bytes": 88870437888, "vram_used_bytes": 194994176, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 13.48, "VmRSS_bytes": 92565860352, "VmHWM_bytes": 92565860352, "Pss_bytes": 92487906304, "vram_used_bytes": 194994176, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 14.7, "VmRSS_bytes": 93736656896, "VmHWM_bytes": 94433050624, "Pss_bytes": 93249152000, "vram_used_bytes": 194994176, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 15.88, "VmRSS_bytes": 95374000128, "VmHWM_bytes": 95537545216, "Pss_bytes": 95362159616, "vram_used_bytes": 194994176, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 17.07, "VmRSS_bytes": 98500653056, "VmHWM_bytes": 98537455616, "Pss_bytes": 98337215488, "vram_used_bytes": 194994176, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 18.28, "VmRSS_bytes": 101397360640, "VmHWM_bytes": 101538070528, "Pss_bytes": 101387969536, "vram_used_bytes": 194994176, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 19.49, "VmRSS_bytes": 104362180608, "VmHWM_bytes": 104536772608, "Pss_bytes": 104363205632, "vram_used_bytes": 194994176, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 20.72, "VmRSS_bytes": 107189788672, "VmHWM_bytes": 107280900096, "Pss_bytes": 107332428800, "vram_used_bytes": 194994176, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 22.56, "VmRSS_bytes": 108498034688, "VmHWM_bytes": 109025759232, "Pss_bytes": 106159354880, "vram_used_bytes": 206184448, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88070221824, "gtt_total_bytes": 193273528320} +{"t_s": 23.82, "VmRSS_bytes": 105736540160, "VmHWM_bytes": 109025759232, "Pss_bytes": 105734028288, "vram_used_bytes": 206217216, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88531525632, "gtt_total_bytes": 193273528320} +{"t_s": 25.08, "VmRSS_bytes": 105741189120, "VmHWM_bytes": 109025759232, "Pss_bytes": 105738673152, "vram_used_bytes": 206221312, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88533000192, "gtt_total_bytes": 193273528320} +{"t_s": 26.31, "VmRSS_bytes": 105743376384, "VmHWM_bytes": 109025759232, "Pss_bytes": 105741011968, "vram_used_bytes": 206221312, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88533000192, "gtt_total_bytes": 193273528320} +{"t_s": 27.57, "VmRSS_bytes": 105746018304, "VmHWM_bytes": 109025759232, "Pss_bytes": 105743477760, "vram_used_bytes": 206221312, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88539291648, "gtt_total_bytes": 193273528320} +{"t_s": 28.83, "VmRSS_bytes": 105746149376, "VmHWM_bytes": 109025759232, "Pss_bytes": 105743608832, "vram_used_bytes": 206221312, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88539291648, "gtt_total_bytes": 193273528320} +{"t_s": 30.06, "VmRSS_bytes": 105745805312, "VmHWM_bytes": 109025759232, "Pss_bytes": 105743466496, "vram_used_bytes": 206221312, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88533000192, "gtt_total_bytes": 193273528320} +{"t_s": 31.25, "VmRSS_bytes": 70105976832, "VmHWM_bytes": 109025759232, "Pss_bytes": 65139408896, "vram_used_bytes": 194990080, "vram_total_bytes": 4294967296, "gtt_used_bytes": 204288000, "gtt_total_bytes": 193273528320} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-2048-r2-memory-endpoint.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-2048-r2-memory-endpoint.json new file mode 100644 index 0000000000..a56240b905 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-2048-r2-memory-endpoint.json @@ -0,0 +1 @@ +{"schema_version": 1, "context_window": 10240, "context_fitted": false, "device": {"active_bytes": 87565912724, "cache_bytes": 0, "peak_bytes": 87571482532, "peak_scope": "since_start_or_health_reset"}} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-2048-r2-metrics.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-2048-r2-metrics.txt new file mode 100644 index 0000000000..1e5cf71b68 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-2048-r2-metrics.txt @@ -0,0 +1,220 @@ +# HELP tensorfold:requests_running Requests in prefill or decode. +# TYPE tensorfold:requests_running gauge +tensorfold:requests_running 0 +# HELP tensorfold:requests_waiting Requests queued or held until a lane is free. +# TYPE tensorfold:requests_waiting gauge +tensorfold:requests_waiting 0 +# HELP tensorfold:generation_tokens_running Generated tokens held by live streams. +# TYPE tensorfold:generation_tokens_running gauge +tensorfold:generation_tokens_running 0 +# HELP tensorfold:prompt_tokens_total Prompt tokens of finished requests. +# TYPE tensorfold:prompt_tokens_total counter +tensorfold:prompt_tokens_total 2304 +# HELP tensorfold:generation_tokens_total Generated tokens of finished requests. +# TYPE tensorfold:generation_tokens_total counter +tensorfold:generation_tokens_total 2 +# HELP tensorfold:kv_cache_usage_ratio Tokens in a stream cache divided by that stream's context window. +# TYPE tensorfold:kv_cache_usage_ratio gauge +tensorfold:kv_cache_usage_ratio{pool="0"} 0 +# HELP tensorfold:mtp_drafted_total Draft tokens verified on finished requests. +# TYPE tensorfold:mtp_drafted_total counter +tensorfold:mtp_drafted_total 0 +# HELP tensorfold:mtp_accepted_total Draft tokens kept on finished requests. +# TYPE tensorfold:mtp_accepted_total counter +tensorfold:mtp_accepted_total 0 +# HELP tensorfold:request_latency_seconds Seconds from arrival to the reply leaving. +# TYPE tensorfold:request_latency_seconds histogram +tensorfold:request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:request_latency_seconds_bucket{le="0.5"} 1 +tensorfold:request_latency_seconds_bucket{le="1"} 1 +tensorfold:request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:request_latency_seconds_bucket{le="5"} 2 +tensorfold:request_latency_seconds_bucket{le="10"} 2 +tensorfold:request_latency_seconds_bucket{le="30"} 2 +tensorfold:request_latency_seconds_bucket{le="60"} 2 +tensorfold:request_latency_seconds_bucket{le="120"} 2 +tensorfold:request_latency_seconds_bucket{le="300"} 2 +tensorfold:request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:request_latency_seconds_sum 3.471054 +tensorfold:request_latency_seconds_count 2 +# HELP tensorfold:time_to_first_token_seconds Seconds from arrival to the first generated token. +# TYPE tensorfold:time_to_first_token_seconds histogram +tensorfold:time_to_first_token_seconds_bucket{le="0.01"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.05"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.25"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="1"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="2.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="5"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="10"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="30"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="60"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="120"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="300"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="+Inf"} 2 +tensorfold:time_to_first_token_seconds_sum 3.470817 +tensorfold:time_to_first_token_seconds_count 2 +# HELP tensorfold:request_decode_seconds Seconds a finished request spent decoding. Its sum over generation_tokens_total is the decode rate. +# TYPE tensorfold:request_decode_seconds histogram +tensorfold:request_decode_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_seconds_bucket{le="1"} 2 +tensorfold:request_decode_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_seconds_bucket{le="5"} 2 +tensorfold:request_decode_seconds_bucket{le="10"} 2 +tensorfold:request_decode_seconds_bucket{le="30"} 2 +tensorfold:request_decode_seconds_bucket{le="60"} 2 +tensorfold:request_decode_seconds_bucket{le="120"} 2 +tensorfold:request_decode_seconds_bucket{le="300"} 2 +tensorfold:request_decode_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_seconds_sum 0.000237 +tensorfold:request_decode_seconds_count 2 +# HELP tensorfold:request_time_per_output_token_seconds Seconds from the first generated token to the last, divided by the tokens less one. +# TYPE tensorfold:request_time_per_output_token_seconds histogram +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.005"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.01"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.015"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.02"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.03"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.04"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.05"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.15"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.2"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.3"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.5"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="+Inf"} 0 +tensorfold:request_time_per_output_token_seconds_sum 0 +tensorfold:request_time_per_output_token_seconds_count 0 +# HELP tensorfold:decode_rounds_total Decode rounds used by finished requests. +# TYPE tensorfold:decode_rounds_total counter +tensorfold:decode_rounds_total 0 +# HELP tensorfold:request_prefill_seconds Seconds a finished request's prompt pass took. +# TYPE tensorfold:request_prefill_seconds histogram +tensorfold:request_prefill_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="1"} 1 +tensorfold:request_prefill_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="5"} 2 +tensorfold:request_prefill_seconds_bucket{le="10"} 2 +tensorfold:request_prefill_seconds_bucket{le="30"} 2 +tensorfold:request_prefill_seconds_bucket{le="60"} 2 +tensorfold:request_prefill_seconds_bucket{le="120"} 2 +tensorfold:request_prefill_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_seconds_sum 3.469759 +tensorfold:request_prefill_seconds_count 2 +# HELP tensorfold:process_resident_bytes Current resident set (VmRSS); device memory is not in it, so it is not a physical footprint (Linux). +# TYPE tensorfold:process_resident_bytes gauge +tensorfold:process_resident_bytes 106205614080 +# HELP tensorfold:process_resident_anon_bytes Current resident anonymous memory (RssAnon): heap, stacks and private maps (Linux). +# TYPE tensorfold:process_resident_anon_bytes gauge +tensorfold:process_resident_anon_bytes 32366465024 +# HELP tensorfold:process_resident_file_bytes Current resident file-backed memory (RssFile): the binary, libraries and mapped files (Linux). +# TYPE tensorfold:process_resident_file_bytes gauge +tensorfold:process_resident_file_bytes 73704886272 +# HELP tensorfold:process_resident_shmem_bytes Current resident shared memory (RssShmem): System V shared memory, tmpfs maps and shared anonymous maps (Linux). +# TYPE tensorfold:process_resident_shmem_bytes gauge +tensorfold:process_resident_shmem_bytes 134262784 +# HELP tensorfold:process_resident_peak_bytes Kernel lifetime peak resident set (VmHWM); never reset by health (Linux). +# TYPE tensorfold:process_resident_peak_bytes gauge +tensorfold:process_resident_peak_bytes 111916331008 +# HELP tensorfold:device_memory_bytes Device memory the engine holds now: weights, caches and live streams; only where the backend counts it (CUDA). +# TYPE tensorfold:device_memory_bytes gauge +tensorfold:device_memory_bytes 87565912724 +# HELP tensorfold:device_memory_peak_bytes The most device memory the engine has held since start or the last /health?reset_peak=1. +# TYPE tensorfold:device_memory_peak_bytes gauge +tensorfold:device_memory_peak_bytes 87571482532 +# HELP tensorfold:pinned_memory_bytes Pinned host memory the engine holds now: staging buffers and windows; only where the backend counts it (CUDA). +# TYPE tensorfold:pinned_memory_bytes gauge +tensorfold:pinned_memory_bytes 0 +# HELP tensorfold:num_requests_running Requests in prefill or decode. A mirror of tensorfold:requests_running. +# TYPE tensorfold:num_requests_running gauge +tensorfold:num_requests_running 0 +# HELP tensorfold:num_requests_waiting Requests queued or held until a lane is free. A mirror of tensorfold:requests_waiting. +# TYPE tensorfold:num_requests_waiting gauge +tensorfold:num_requests_waiting 0 +# HELP tensorfold:kv_cache_usage_perc A stream's cache occupancy under vLLM's name; same streams and ratios as tensorfold:kv_cache_usage_ratio. +# TYPE tensorfold:kv_cache_usage_perc gauge +tensorfold:kv_cache_usage_perc{stream="0"} 0 +# HELP tensorfold:spec_decode_num_draft_tokens_total Draft tokens verified on finished requests, this server's single draft counter. +# TYPE tensorfold:spec_decode_num_draft_tokens_total counter +tensorfold:spec_decode_num_draft_tokens_total 0 +# HELP tensorfold:spec_decode_num_accepted_tokens_total Draft tokens kept on finished requests. +# TYPE tensorfold:spec_decode_num_accepted_tokens_total counter +tensorfold:spec_decode_num_accepted_tokens_total 0 +# HELP tensorfold:e2e_request_latency_seconds Seconds from arrival to the reply leaving, under vLLM's name. +# TYPE tensorfold:e2e_request_latency_seconds histogram +tensorfold:e2e_request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="1"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="5"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="10"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="30"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="60"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="120"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="300"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:e2e_request_latency_seconds_sum 3.471054 +tensorfold:e2e_request_latency_seconds_count 2 +# HELP tensorfold:request_decode_time_seconds Seconds a finished request spent decoding, under vLLM's name. +# TYPE tensorfold:request_decode_time_seconds histogram +tensorfold:request_decode_time_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="10"} 2 +tensorfold:request_decode_time_seconds_bucket{le="30"} 2 +tensorfold:request_decode_time_seconds_bucket{le="60"} 2 +tensorfold:request_decode_time_seconds_bucket{le="120"} 2 +tensorfold:request_decode_time_seconds_bucket{le="300"} 2 +tensorfold:request_decode_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_time_seconds_sum 0.000237 +tensorfold:request_decode_time_seconds_count 2 +# HELP tensorfold:request_prefill_time_seconds Seconds a finished request's prompt pass took, under vLLM's name. +# TYPE tensorfold:request_prefill_time_seconds histogram +tensorfold:request_prefill_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="1"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="5"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="10"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="30"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="60"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="120"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_time_seconds_sum 3.469759 +tensorfold:request_prefill_time_seconds_count 2 +# HELP tensorfold:client_disconnections_total Requests a client left before the reply left the server. +# TYPE tensorfold:client_disconnections_total counter +tensorfold:client_disconnections_total 0 +# HELP tensorfold:preemptions_total Requests that had to give a lane up to a later one. +# TYPE tensorfold:preemptions_total counter +tensorfold:preemptions_total 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-2048-r2-samples.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-2048-r2-samples.jsonl new file mode 100644 index 0000000000..d5ba7adebe --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-2048-r2-samples.jsonl @@ -0,0 +1,26 @@ +{"t_s": 0.0, "VmRSS_bytes": 75628544, "VmHWM_bytes": 75628544, "Pss_bytes": 73407488, "vram_used_bytes": 187682816, "vram_total_bytes": 4294967296, "gtt_used_bytes": 31657984, "gtt_total_bytes": 193273528320} +{"t_s": 1.03, "VmRSS_bytes": 10056478720, "VmHWM_bytes": 10056478720, "Pss_bytes": 10094992384, "vram_used_bytes": 188801024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 6847524864, "gtt_total_bytes": 193273528320} +{"t_s": 2.09, "VmRSS_bytes": 18382143488, "VmHWM_bytes": 18382143488, "Pss_bytes": 18379697152, "vram_used_bytes": 189468672, "vram_total_bytes": 4294967296, "gtt_used_bytes": 16699944960, "gtt_total_bytes": 193273528320} +{"t_s": 3.18, "VmRSS_bytes": 27538288640, "VmHWM_bytes": 27538288640, "Pss_bytes": 27538529280, "vram_used_bytes": 190058496, "vram_total_bytes": 4294967296, "gtt_used_bytes": 24916586496, "gtt_total_bytes": 193273528320} +{"t_s": 4.29, "VmRSS_bytes": 36222955520, "VmHWM_bytes": 36222955520, "Pss_bytes": 36220509184, "vram_used_bytes": 190713856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 34769006592, "gtt_total_bytes": 193273528320} +{"t_s": 5.41, "VmRSS_bytes": 45909757952, "VmHWM_bytes": 45909757952, "Pss_bytes": 45907311616, "vram_used_bytes": 191279104, "vram_total_bytes": 4294967296, "gtt_used_bytes": 43941949440, "gtt_total_bytes": 193273528320} +{"t_s": 6.57, "VmRSS_bytes": 54064889856, "VmHWM_bytes": 54064889856, "Pss_bytes": 54074764288, "vram_used_bytes": 191954944, "vram_total_bytes": 4294967296, "gtt_used_bytes": 52844359680, "gtt_total_bytes": 193273528320} +{"t_s": 7.75, "VmRSS_bytes": 63799177216, "VmHWM_bytes": 63799177216, "Pss_bytes": 63796730880, "vram_used_bytes": 192643072, "vram_total_bytes": 4294967296, "gtt_used_bytes": 62703071232, "gtt_total_bytes": 193273528320} +{"t_s": 8.95, "VmRSS_bytes": 73528528896, "VmHWM_bytes": 73528528896, "Pss_bytes": 73526082560, "vram_used_bytes": 193331200, "vram_total_bytes": 4294967296, "gtt_used_bytes": 72557588480, "gtt_total_bytes": 193273528320} +{"t_s": 10.17, "VmRSS_bytes": 81529778176, "VmHWM_bytes": 82503155712, "Pss_bytes": 81527331840, "vram_used_bytes": 195026944, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 11.38, "VmRSS_bytes": 85736329216, "VmHWM_bytes": 85934116864, "Pss_bytes": 85836332032, "vram_used_bytes": 195026944, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 12.61, "VmRSS_bytes": 90004131840, "VmHWM_bytes": 90004131840, "Pss_bytes": 89985588224, "vram_used_bytes": 195026944, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 13.83, "VmRSS_bytes": 94080102400, "VmHWM_bytes": 94080102400, "Pss_bytes": 94038543360, "vram_used_bytes": 195026944, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 15.05, "VmRSS_bytes": 98130989056, "VmHWM_bytes": 98192654336, "Pss_bytes": 98147200000, "vram_used_bytes": 195026944, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 16.28, "VmRSS_bytes": 101360906240, "VmHWM_bytes": 101619138560, "Pss_bytes": 101049838592, "vram_used_bytes": 195026944, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 17.51, "VmRSS_bytes": 104662450176, "VmHWM_bytes": 104718700544, "Pss_bytes": 104705793024, "vram_used_bytes": 195026944, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 18.74, "VmRSS_bytes": 108164952064, "VmHWM_bytes": 108164952064, "Pss_bytes": 108019203072, "vram_used_bytes": 195026944, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 20.15, "VmRSS_bytes": 110349410304, "VmHWM_bytes": 110453633024, "Pss_bytes": 110334618624, "vram_used_bytes": 195031040, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 21.61, "VmRSS_bytes": 111560765440, "VmHWM_bytes": 111916331008, "Pss_bytes": 106654256128, "vram_used_bytes": 203644928, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88070221824, "gtt_total_bytes": 193273528320} +{"t_s": 22.87, "VmRSS_bytes": 106196295680, "VmHWM_bytes": 111916331008, "Pss_bytes": 106193803264, "vram_used_bytes": 203706368, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88531525632, "gtt_total_bytes": 193273528320} +{"t_s": 24.14, "VmRSS_bytes": 106200956928, "VmHWM_bytes": 111916331008, "Pss_bytes": 106198452224, "vram_used_bytes": 203714560, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88533000192, "gtt_total_bytes": 193273528320} +{"t_s": 25.4, "VmRSS_bytes": 106202861568, "VmHWM_bytes": 111916331008, "Pss_bytes": 106200356864, "vram_used_bytes": 203714560, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88533000192, "gtt_total_bytes": 193273528320} +{"t_s": 26.66, "VmRSS_bytes": 106204790784, "VmHWM_bytes": 111916331008, "Pss_bytes": 106202227712, "vram_used_bytes": 203714560, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88533000192, "gtt_total_bytes": 193273528320} +{"t_s": 27.94, "VmRSS_bytes": 106205765632, "VmHWM_bytes": 111916331008, "Pss_bytes": 106203249664, "vram_used_bytes": 203714560, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88539291648, "gtt_total_bytes": 193273528320} +{"t_s": 29.22, "VmRSS_bytes": 106205765632, "VmHWM_bytes": 111916331008, "Pss_bytes": 106203249664, "vram_used_bytes": 203714560, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88539291648, "gtt_total_bytes": 193273528320} +{"t_s": 30.47, "VmRSS_bytes": 106194518016, "VmHWM_bytes": 111916331008, "Pss_bytes": 106124902400, "vram_used_bytes": 194998272, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81622020096, "gtt_total_bytes": 193273528320} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-261888-r1-memory-endpoint.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-261888-r1-memory-endpoint.json new file mode 100644 index 0000000000..c1da980631 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-261888-r1-memory-endpoint.json @@ -0,0 +1 @@ +{"schema_version": 1, "context_window": 262144, "context_fitted": false, "device": {"active_bytes": 94724016788, "cache_bytes": 0, "peak_bytes": 95344887716, "peak_scope": "since_start_or_health_reset"}} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-261888-r1-metrics.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-261888-r1-metrics.txt new file mode 100644 index 0000000000..9ac3ec2608 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-261888-r1-metrics.txt @@ -0,0 +1,220 @@ +# HELP tensorfold:requests_running Requests in prefill or decode. +# TYPE tensorfold:requests_running gauge +tensorfold:requests_running 0 +# HELP tensorfold:requests_waiting Requests queued or held until a lane is free. +# TYPE tensorfold:requests_waiting gauge +tensorfold:requests_waiting 0 +# HELP tensorfold:generation_tokens_running Generated tokens held by live streams. +# TYPE tensorfold:generation_tokens_running gauge +tensorfold:generation_tokens_running 0 +# HELP tensorfold:prompt_tokens_total Prompt tokens of finished requests. +# TYPE tensorfold:prompt_tokens_total counter +tensorfold:prompt_tokens_total 262144 +# HELP tensorfold:generation_tokens_total Generated tokens of finished requests. +# TYPE tensorfold:generation_tokens_total counter +tensorfold:generation_tokens_total 2 +# HELP tensorfold:kv_cache_usage_ratio Tokens in a stream cache divided by that stream's context window. +# TYPE tensorfold:kv_cache_usage_ratio gauge +tensorfold:kv_cache_usage_ratio{pool="0"} 0 +# HELP tensorfold:mtp_drafted_total Draft tokens verified on finished requests. +# TYPE tensorfold:mtp_drafted_total counter +tensorfold:mtp_drafted_total 0 +# HELP tensorfold:mtp_accepted_total Draft tokens kept on finished requests. +# TYPE tensorfold:mtp_accepted_total counter +tensorfold:mtp_accepted_total 0 +# HELP tensorfold:request_latency_seconds Seconds from arrival to the reply leaving. +# TYPE tensorfold:request_latency_seconds histogram +tensorfold:request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:request_latency_seconds_bucket{le="0.5"} 1 +tensorfold:request_latency_seconds_bucket{le="1"} 1 +tensorfold:request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:request_latency_seconds_bucket{le="5"} 1 +tensorfold:request_latency_seconds_bucket{le="10"} 1 +tensorfold:request_latency_seconds_bucket{le="30"} 1 +tensorfold:request_latency_seconds_bucket{le="60"} 1 +tensorfold:request_latency_seconds_bucket{le="120"} 1 +tensorfold:request_latency_seconds_bucket{le="300"} 1 +tensorfold:request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:request_latency_seconds_sum 598.985804 +tensorfold:request_latency_seconds_count 2 +# HELP tensorfold:time_to_first_token_seconds Seconds from arrival to the first generated token. +# TYPE tensorfold:time_to_first_token_seconds histogram +tensorfold:time_to_first_token_seconds_bucket{le="0.01"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.05"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.25"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="1"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="2.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="10"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="30"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="60"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="120"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="300"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="+Inf"} 2 +tensorfold:time_to_first_token_seconds_sum 598.984999 +tensorfold:time_to_first_token_seconds_count 2 +# HELP tensorfold:request_decode_seconds Seconds a finished request spent decoding. Its sum over generation_tokens_total is the decode rate. +# TYPE tensorfold:request_decode_seconds histogram +tensorfold:request_decode_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_seconds_bucket{le="1"} 2 +tensorfold:request_decode_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_seconds_bucket{le="5"} 2 +tensorfold:request_decode_seconds_bucket{le="10"} 2 +tensorfold:request_decode_seconds_bucket{le="30"} 2 +tensorfold:request_decode_seconds_bucket{le="60"} 2 +tensorfold:request_decode_seconds_bucket{le="120"} 2 +tensorfold:request_decode_seconds_bucket{le="300"} 2 +tensorfold:request_decode_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_seconds_sum 0.000805 +tensorfold:request_decode_seconds_count 2 +# HELP tensorfold:request_time_per_output_token_seconds Seconds from the first generated token to the last, divided by the tokens less one. +# TYPE tensorfold:request_time_per_output_token_seconds histogram +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.005"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.01"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.015"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.02"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.03"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.04"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.05"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.15"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.2"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.3"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.5"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="+Inf"} 0 +tensorfold:request_time_per_output_token_seconds_sum 0 +tensorfold:request_time_per_output_token_seconds_count 0 +# HELP tensorfold:decode_rounds_total Decode rounds used by finished requests. +# TYPE tensorfold:decode_rounds_total counter +tensorfold:decode_rounds_total 0 +# HELP tensorfold:request_prefill_seconds Seconds a finished request's prompt pass took. +# TYPE tensorfold:request_prefill_seconds histogram +tensorfold:request_prefill_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="1"} 1 +tensorfold:request_prefill_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_seconds_bucket{le="60"} 1 +tensorfold:request_prefill_seconds_bucket{le="120"} 1 +tensorfold:request_prefill_seconds_bucket{le="300"} 1 +tensorfold:request_prefill_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_seconds_sum 598.983538 +tensorfold:request_prefill_seconds_count 2 +# HELP tensorfold:process_resident_bytes Current resident set (VmRSS); device memory is not in it, so it is not a physical footprint (Linux). +# TYPE tensorfold:process_resident_bytes gauge +tensorfold:process_resident_bytes 96287174656 +# HELP tensorfold:process_resident_anon_bytes Current resident anonymous memory (RssAnon): heap, stacks and private maps (Linux). +# TYPE tensorfold:process_resident_anon_bytes gauge +tensorfold:process_resident_anon_bytes 32368582656 +# HELP tensorfold:process_resident_file_bytes Current resident file-backed memory (RssFile): the binary, libraries and mapped files (Linux). +# TYPE tensorfold:process_resident_file_bytes gauge +tensorfold:process_resident_file_bytes 63784329216 +# HELP tensorfold:process_resident_shmem_bytes Current resident shared memory (RssShmem): System V shared memory, tmpfs maps and shared anonymous maps (Linux). +# TYPE tensorfold:process_resident_shmem_bytes gauge +tensorfold:process_resident_shmem_bytes 134262784 +# HELP tensorfold:process_resident_peak_bytes Kernel lifetime peak resident set (VmHWM); never reset by health (Linux). +# TYPE tensorfold:process_resident_peak_bytes gauge +tensorfold:process_resident_peak_bytes 112836476928 +# HELP tensorfold:device_memory_bytes Device memory the engine holds now: weights, caches and live streams; only where the backend counts it (CUDA). +# TYPE tensorfold:device_memory_bytes gauge +tensorfold:device_memory_bytes 94724016788 +# HELP tensorfold:device_memory_peak_bytes The most device memory the engine has held since start or the last /health?reset_peak=1. +# TYPE tensorfold:device_memory_peak_bytes gauge +tensorfold:device_memory_peak_bytes 95344887716 +# HELP tensorfold:pinned_memory_bytes Pinned host memory the engine holds now: staging buffers and windows; only where the backend counts it (CUDA). +# TYPE tensorfold:pinned_memory_bytes gauge +tensorfold:pinned_memory_bytes 0 +# HELP tensorfold:num_requests_running Requests in prefill or decode. A mirror of tensorfold:requests_running. +# TYPE tensorfold:num_requests_running gauge +tensorfold:num_requests_running 0 +# HELP tensorfold:num_requests_waiting Requests queued or held until a lane is free. A mirror of tensorfold:requests_waiting. +# TYPE tensorfold:num_requests_waiting gauge +tensorfold:num_requests_waiting 0 +# HELP tensorfold:kv_cache_usage_perc A stream's cache occupancy under vLLM's name; same streams and ratios as tensorfold:kv_cache_usage_ratio. +# TYPE tensorfold:kv_cache_usage_perc gauge +tensorfold:kv_cache_usage_perc{stream="0"} 0 +# HELP tensorfold:spec_decode_num_draft_tokens_total Draft tokens verified on finished requests, this server's single draft counter. +# TYPE tensorfold:spec_decode_num_draft_tokens_total counter +tensorfold:spec_decode_num_draft_tokens_total 0 +# HELP tensorfold:spec_decode_num_accepted_tokens_total Draft tokens kept on finished requests. +# TYPE tensorfold:spec_decode_num_accepted_tokens_total counter +tensorfold:spec_decode_num_accepted_tokens_total 0 +# HELP tensorfold:e2e_request_latency_seconds Seconds from arrival to the reply leaving, under vLLM's name. +# TYPE tensorfold:e2e_request_latency_seconds histogram +tensorfold:e2e_request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="1"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="10"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="30"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="60"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="120"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="300"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:e2e_request_latency_seconds_sum 598.985804 +tensorfold:e2e_request_latency_seconds_count 2 +# HELP tensorfold:request_decode_time_seconds Seconds a finished request spent decoding, under vLLM's name. +# TYPE tensorfold:request_decode_time_seconds histogram +tensorfold:request_decode_time_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="10"} 2 +tensorfold:request_decode_time_seconds_bucket{le="30"} 2 +tensorfold:request_decode_time_seconds_bucket{le="60"} 2 +tensorfold:request_decode_time_seconds_bucket{le="120"} 2 +tensorfold:request_decode_time_seconds_bucket{le="300"} 2 +tensorfold:request_decode_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_time_seconds_sum 0.000805 +tensorfold:request_decode_time_seconds_count 2 +# HELP tensorfold:request_prefill_time_seconds Seconds a finished request's prompt pass took, under vLLM's name. +# TYPE tensorfold:request_prefill_time_seconds histogram +tensorfold:request_prefill_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="1"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="60"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="120"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="300"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_time_seconds_sum 598.983538 +tensorfold:request_prefill_time_seconds_count 2 +# HELP tensorfold:client_disconnections_total Requests a client left before the reply left the server. +# TYPE tensorfold:client_disconnections_total counter +tensorfold:client_disconnections_total 0 +# HELP tensorfold:preemptions_total Requests that had to give a lane up to a later one. +# TYPE tensorfold:preemptions_total counter +tensorfold:preemptions_total 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-261888-r1-samples.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-261888-r1-samples.jsonl new file mode 100644 index 0000000000..e2b5cea9aa --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-261888-r1-samples.jsonl @@ -0,0 +1,529 @@ +{"t_s": 0.0, "VmRSS_bytes": 75452416, "VmHWM_bytes": 75452416, "Pss_bytes": 73502720, "vram_used_bytes": 187682816, "vram_total_bytes": 4294967296, "gtt_used_bytes": 31657984, "gtt_total_bytes": 193273528320} +{"t_s": 1.01, "VmRSS_bytes": 5431836672, "VmHWM_bytes": 5431836672, "Pss_bytes": 5436871680, "vram_used_bytes": 188624896, "vram_total_bytes": 4294967296, "gtt_used_bytes": 3557093376, "gtt_total_bytes": 193273528320} +{"t_s": 2.03, "VmRSS_bytes": 10229608448, "VmHWM_bytes": 10229608448, "Pss_bytes": 10227434496, "vram_used_bytes": 188776448, "vram_total_bytes": 4294967296, "gtt_used_bytes": 8441360384, "gtt_total_bytes": 193273528320} +{"t_s": 3.06, "VmRSS_bytes": 15011598336, "VmHWM_bytes": 15011598336, "Pss_bytes": 15039833088, "vram_used_bytes": 189063168, "vram_total_bytes": 4294967296, "gtt_used_bytes": 11773734912, "gtt_total_bytes": 193273528320} +{"t_s": 4.1, "VmRSS_bytes": 19549396992, "VmHWM_bytes": 19549396992, "Pss_bytes": 19551417344, "vram_used_bytes": 189382656, "vram_total_bytes": 4294967296, "gtt_used_bytes": 16699944960, "gtt_total_bytes": 193273528320} +{"t_s": 5.15, "VmRSS_bytes": 24303206400, "VmHWM_bytes": 24303206400, "Pss_bytes": 24303133696, "vram_used_bytes": 189685760, "vram_total_bytes": 4294967296, "gtt_used_bytes": 21626155008, "gtt_total_bytes": 193273528320} +{"t_s": 6.22, "VmRSS_bytes": 29064609792, "VmHWM_bytes": 29064609792, "Pss_bytes": 29064463360, "vram_used_bytes": 190025728, "vram_total_bytes": 4294967296, "gtt_used_bytes": 26554462208, "gtt_total_bytes": 193273528320} +{"t_s": 7.29, "VmRSS_bytes": 33962569728, "VmHWM_bytes": 33962569728, "Pss_bytes": 33991721984, "vram_used_bytes": 190337024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 31480672256, "gtt_total_bytes": 193273528320} +{"t_s": 8.37, "VmRSS_bytes": 38903296000, "VmHWM_bytes": 38903296000, "Pss_bytes": 38901122048, "vram_used_bytes": 190656512, "vram_total_bytes": 4294967296, "gtt_used_bytes": 36413173760, "gtt_total_bytes": 193273528320} +{"t_s": 9.46, "VmRSS_bytes": 43768467456, "VmHWM_bytes": 43768467456, "Pss_bytes": 43766293504, "vram_used_bytes": 190963712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 41339383808, "gtt_total_bytes": 193273528320} +{"t_s": 10.57, "VmRSS_bytes": 48699293696, "VmHWM_bytes": 48699293696, "Pss_bytes": 48709702656, "vram_used_bytes": 191254528, "vram_total_bytes": 4294967296, "gtt_used_bytes": 46273982464, "gtt_total_bytes": 193273528320} +{"t_s": 11.68, "VmRSS_bytes": 53597929472, "VmHWM_bytes": 53597929472, "Pss_bytes": 53599949824, "vram_used_bytes": 191582208, "vram_total_bytes": 4294967296, "gtt_used_bytes": 51200192512, "gtt_total_bytes": 193273528320} +{"t_s": 12.8, "VmRSS_bytes": 58571522048, "VmHWM_bytes": 58571522048, "Pss_bytes": 58580620288, "vram_used_bytes": 191881216, "vram_total_bytes": 4294967296, "gtt_used_bytes": 56132694016, "gtt_total_bytes": 193273528320} +{"t_s": 13.93, "VmRSS_bytes": 63426588672, "VmHWM_bytes": 63426588672, "Pss_bytes": 63432803328, "vram_used_bytes": 192225280, "vram_total_bytes": 4294967296, "gtt_used_bytes": 61058904064, "gtt_total_bytes": 193273528320} +{"t_s": 15.06, "VmRSS_bytes": 68318539776, "VmHWM_bytes": 68318539776, "Pss_bytes": 68324754432, "vram_used_bytes": 192536576, "vram_total_bytes": 4294967296, "gtt_used_bytes": 65987211264, "gtt_total_bytes": 193273528320} +{"t_s": 16.21, "VmRSS_bytes": 72996319232, "VmHWM_bytes": 72996319232, "Pss_bytes": 72997815296, "vram_used_bytes": 192860160, "vram_total_bytes": 4294967296, "gtt_used_bytes": 70913421312, "gtt_total_bytes": 193273528320} +{"t_s": 17.38, "VmRSS_bytes": 78011047936, "VmHWM_bytes": 78011047936, "Pss_bytes": 78017262592, "vram_used_bytes": 193179648, "vram_total_bytes": 4294967296, "gtt_used_bytes": 75845922816, "gtt_total_bytes": 193273528320} +{"t_s": 18.54, "VmRSS_bytes": 81036476416, "VmHWM_bytes": 82509107200, "Pss_bytes": 81033221120, "vram_used_bytes": 194281472, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 19.71, "VmRSS_bytes": 84144230400, "VmHWM_bytes": 84144230400, "Pss_bytes": 84040136704, "vram_used_bytes": 194281472, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 20.87, "VmRSS_bytes": 86789308416, "VmHWM_bytes": 86940680192, "Pss_bytes": 86766196736, "vram_used_bytes": 194281472, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 22.03, "VmRSS_bytes": 89850675200, "VmHWM_bytes": 89850675200, "Pss_bytes": 89742673920, "vram_used_bytes": 194281472, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 23.2, "VmRSS_bytes": 92645818368, "VmHWM_bytes": 92645818368, "Pss_bytes": 92555565056, "vram_used_bytes": 194281472, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 24.37, "VmRSS_bytes": 95245443072, "VmHWM_bytes": 95443705856, "Pss_bytes": 95243323392, "vram_used_bytes": 194281472, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 25.54, "VmRSS_bytes": 97576697856, "VmHWM_bytes": 97693081600, "Pss_bytes": 97493968896, "vram_used_bytes": 194281472, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 26.72, "VmRSS_bytes": 99758948352, "VmHWM_bytes": 99758948352, "Pss_bytes": 99744212992, "vram_used_bytes": 194281472, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 27.91, "VmRSS_bytes": 102034640896, "VmHWM_bytes": 102034640896, "Pss_bytes": 101994784768, "vram_used_bytes": 194281472, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 29.1, "VmRSS_bytes": 104433012736, "VmHWM_bytes": 104433012736, "Pss_bytes": 104244840448, "vram_used_bytes": 194281472, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 30.3, "VmRSS_bytes": 106561699840, "VmHWM_bytes": 106561699840, "Pss_bytes": 106495367168, "vram_used_bytes": 194281472, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 31.51, "VmRSS_bytes": 108932472832, "VmHWM_bytes": 108932472832, "Pss_bytes": 108745541632, "vram_used_bytes": 194281472, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 32.73, "VmRSS_bytes": 111403888640, "VmHWM_bytes": 111444541440, "Pss_bytes": 111489751040, "vram_used_bytes": 194281472, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 33.96, "VmRSS_bytes": 112568807424, "VmHWM_bytes": 112568807424, "Pss_bytes": 112634931200, "vram_used_bytes": 194306048, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 35.21, "VmRSS_bytes": 97226133504, "VmHWM_bytes": 112836476928, "Pss_bytes": 97223902208, "vram_used_bytes": 203456512, 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"vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 608.9, "VmRSS_bytes": 96306864128, "VmHWM_bytes": 112836476928, "Pss_bytes": 96304624640, "vram_used_bytes": 203399168, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 610.11, "VmRSS_bytes": 96306864128, "VmHWM_bytes": 112836476928, "Pss_bytes": 96304624640, "vram_used_bytes": 203399168, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 611.33, "VmRSS_bytes": 96306864128, "VmHWM_bytes": 112836476928, "Pss_bytes": 96304624640, "vram_used_bytes": 203399168, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 612.55, "VmRSS_bytes": 96306864128, "VmHWM_bytes": 112836476928, "Pss_bytes": 96304624640, "vram_used_bytes": 203399168, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 613.77, "VmRSS_bytes": 96306864128, "VmHWM_bytes": 112836476928, "Pss_bytes": 96304624640, "vram_used_bytes": 203399168, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 615.0, "VmRSS_bytes": 96306864128, "VmHWM_bytes": 112836476928, "Pss_bytes": 96304624640, "vram_used_bytes": 203399168, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 616.21, "VmRSS_bytes": 96306864128, "VmHWM_bytes": 112836476928, "Pss_bytes": 96304624640, "vram_used_bytes": 203399168, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 617.42, "VmRSS_bytes": 96306864128, "VmHWM_bytes": 112836476928, "Pss_bytes": 96304624640, "vram_used_bytes": 203399168, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 618.65, "VmRSS_bytes": 96306864128, "VmHWM_bytes": 112836476928, "Pss_bytes": 96304624640, "vram_used_bytes": 203399168, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 619.87, "VmRSS_bytes": 96306864128, "VmHWM_bytes": 112836476928, "Pss_bytes": 96304624640, "vram_used_bytes": 203399168, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 621.09, "VmRSS_bytes": 96306864128, "VmHWM_bytes": 112836476928, "Pss_bytes": 96304624640, "vram_used_bytes": 203399168, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 622.3, "VmRSS_bytes": 96306864128, "VmHWM_bytes": 112836476928, "Pss_bytes": 96304624640, "vram_used_bytes": 203399168, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 623.51, "VmRSS_bytes": 96306864128, "VmHWM_bytes": 112836476928, "Pss_bytes": 96304624640, "vram_used_bytes": 203399168, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 624.75, "VmRSS_bytes": 96306864128, "VmHWM_bytes": 112836476928, "Pss_bytes": 96304624640, "vram_used_bytes": 203399168, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 625.95, "VmRSS_bytes": 96306864128, "VmHWM_bytes": 112836476928, "Pss_bytes": 96304624640, "vram_used_bytes": 203399168, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 627.16, "VmRSS_bytes": 96306864128, "VmHWM_bytes": 112836476928, "Pss_bytes": 96304624640, "vram_used_bytes": 203399168, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 628.38, "VmRSS_bytes": 96306864128, "VmHWM_bytes": 112836476928, "Pss_bytes": 96304624640, "vram_used_bytes": 203399168, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 629.59, "VmRSS_bytes": 96306864128, "VmHWM_bytes": 112836476928, "Pss_bytes": 96304624640, "vram_used_bytes": 203399168, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 630.82, "VmRSS_bytes": 96306864128, "VmHWM_bytes": 112836476928, "Pss_bytes": 96304624640, "vram_used_bytes": 203399168, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 632.03, "VmRSS_bytes": 96306864128, "VmHWM_bytes": 112836476928, "Pss_bytes": 96304624640, "vram_used_bytes": 203399168, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 633.26, "VmRSS_bytes": 96306864128, "VmHWM_bytes": 112836476928, "Pss_bytes": 96304624640, "vram_used_bytes": 203399168, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 634.47, "VmRSS_bytes": 96306864128, "VmHWM_bytes": 112836476928, "Pss_bytes": 96304624640, "vram_used_bytes": 203399168, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 635.7, "VmRSS_bytes": 96306864128, "VmHWM_bytes": 112836476928, "Pss_bytes": 96304624640, "vram_used_bytes": 203399168, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 636.9, "VmRSS_bytes": 96306864128, "VmHWM_bytes": 112836476928, "Pss_bytes": 96304624640, "vram_used_bytes": 203399168, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 638.1, "VmRSS_bytes": 96306864128, "VmHWM_bytes": 112836476928, "Pss_bytes": 96304624640, "vram_used_bytes": 203399168, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 639.25, "VmRSS_bytes": 80759078912, "VmHWM_bytes": 112836476928, "Pss_bytes": 78456555520, "vram_used_bytes": 194347008, "vram_total_bytes": 4294967296, "gtt_used_bytes": 204288000, "gtt_total_bytes": 193273528320} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-261888-r2-memory-endpoint.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-261888-r2-memory-endpoint.json new file mode 100644 index 0000000000..c1da980631 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-261888-r2-memory-endpoint.json @@ -0,0 +1 @@ +{"schema_version": 1, "context_window": 262144, "context_fitted": false, "device": {"active_bytes": 94724016788, "cache_bytes": 0, "peak_bytes": 95344887716, "peak_scope": "since_start_or_health_reset"}} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-261888-r2-metrics.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-261888-r2-metrics.txt new file mode 100644 index 0000000000..f0b58183a7 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-261888-r2-metrics.txt @@ -0,0 +1,220 @@ +# HELP tensorfold:requests_running Requests in prefill or decode. +# TYPE tensorfold:requests_running gauge +tensorfold:requests_running 0 +# HELP tensorfold:requests_waiting Requests queued or held until a lane is free. +# TYPE tensorfold:requests_waiting gauge +tensorfold:requests_waiting 0 +# HELP tensorfold:generation_tokens_running Generated tokens held by live streams. +# TYPE tensorfold:generation_tokens_running gauge +tensorfold:generation_tokens_running 0 +# HELP tensorfold:prompt_tokens_total Prompt tokens of finished requests. +# TYPE tensorfold:prompt_tokens_total counter +tensorfold:prompt_tokens_total 262144 +# HELP tensorfold:generation_tokens_total Generated tokens of finished requests. +# TYPE tensorfold:generation_tokens_total counter +tensorfold:generation_tokens_total 2 +# HELP tensorfold:kv_cache_usage_ratio Tokens in a stream cache divided by that stream's context window. +# TYPE tensorfold:kv_cache_usage_ratio gauge +tensorfold:kv_cache_usage_ratio{pool="0"} 0 +# HELP tensorfold:mtp_drafted_total Draft tokens verified on finished requests. +# TYPE tensorfold:mtp_drafted_total counter +tensorfold:mtp_drafted_total 0 +# HELP tensorfold:mtp_accepted_total Draft tokens kept on finished requests. +# TYPE tensorfold:mtp_accepted_total counter +tensorfold:mtp_accepted_total 0 +# HELP tensorfold:request_latency_seconds Seconds from arrival to the reply leaving. +# TYPE tensorfold:request_latency_seconds histogram +tensorfold:request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:request_latency_seconds_bucket{le="0.5"} 1 +tensorfold:request_latency_seconds_bucket{le="1"} 1 +tensorfold:request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:request_latency_seconds_bucket{le="5"} 1 +tensorfold:request_latency_seconds_bucket{le="10"} 1 +tensorfold:request_latency_seconds_bucket{le="30"} 1 +tensorfold:request_latency_seconds_bucket{le="60"} 1 +tensorfold:request_latency_seconds_bucket{le="120"} 1 +tensorfold:request_latency_seconds_bucket{le="300"} 1 +tensorfold:request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:request_latency_seconds_sum 599.593843 +tensorfold:request_latency_seconds_count 2 +# HELP tensorfold:time_to_first_token_seconds Seconds from arrival to the first generated token. +# TYPE tensorfold:time_to_first_token_seconds histogram +tensorfold:time_to_first_token_seconds_bucket{le="0.01"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.05"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.25"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="1"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="2.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="10"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="30"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="60"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="120"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="300"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="+Inf"} 2 +tensorfold:time_to_first_token_seconds_sum 599.593312 +tensorfold:time_to_first_token_seconds_count 2 +# HELP tensorfold:request_decode_seconds Seconds a finished request spent decoding. Its sum over generation_tokens_total is the decode rate. +# TYPE tensorfold:request_decode_seconds histogram +tensorfold:request_decode_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_seconds_bucket{le="1"} 2 +tensorfold:request_decode_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_seconds_bucket{le="5"} 2 +tensorfold:request_decode_seconds_bucket{le="10"} 2 +tensorfold:request_decode_seconds_bucket{le="30"} 2 +tensorfold:request_decode_seconds_bucket{le="60"} 2 +tensorfold:request_decode_seconds_bucket{le="120"} 2 +tensorfold:request_decode_seconds_bucket{le="300"} 2 +tensorfold:request_decode_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_seconds_sum 0.00053 +tensorfold:request_decode_seconds_count 2 +# HELP tensorfold:request_time_per_output_token_seconds Seconds from the first generated token to the last, divided by the tokens less one. +# TYPE tensorfold:request_time_per_output_token_seconds histogram +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.005"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.01"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.015"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.02"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.03"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.04"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.05"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.15"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.2"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.3"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.5"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="+Inf"} 0 +tensorfold:request_time_per_output_token_seconds_sum 0 +tensorfold:request_time_per_output_token_seconds_count 0 +# HELP tensorfold:decode_rounds_total Decode rounds used by finished requests. +# TYPE tensorfold:decode_rounds_total counter +tensorfold:decode_rounds_total 0 +# HELP tensorfold:request_prefill_seconds Seconds a finished request's prompt pass took. +# TYPE tensorfold:request_prefill_seconds histogram +tensorfold:request_prefill_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="1"} 1 +tensorfold:request_prefill_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_seconds_bucket{le="60"} 1 +tensorfold:request_prefill_seconds_bucket{le="120"} 1 +tensorfold:request_prefill_seconds_bucket{le="300"} 1 +tensorfold:request_prefill_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_seconds_sum 599.591101 +tensorfold:request_prefill_seconds_count 2 +# HELP tensorfold:process_resident_bytes Current resident set (VmRSS); device memory is not in it, so it is not a physical footprint (Linux). +# TYPE tensorfold:process_resident_bytes gauge +tensorfold:process_resident_bytes 94698901504 +# HELP tensorfold:process_resident_anon_bytes Current resident anonymous memory (RssAnon): heap, stacks and private maps (Linux). +# TYPE tensorfold:process_resident_anon_bytes gauge +tensorfold:process_resident_anon_bytes 32368680960 +# HELP tensorfold:process_resident_file_bytes Current resident file-backed memory (RssFile): the binary, libraries and mapped files (Linux). +# TYPE tensorfold:process_resident_file_bytes gauge +tensorfold:process_resident_file_bytes 62195957760 +# HELP tensorfold:process_resident_shmem_bytes Current resident shared memory (RssShmem): System V shared memory, tmpfs maps and shared anonymous maps (Linux). +# TYPE tensorfold:process_resident_shmem_bytes gauge +tensorfold:process_resident_shmem_bytes 134262784 +# HELP tensorfold:process_resident_peak_bytes Kernel lifetime peak resident set (VmHWM); never reset by health (Linux). +# TYPE tensorfold:process_resident_peak_bytes gauge +tensorfold:process_resident_peak_bytes 110381305856 +# HELP tensorfold:device_memory_bytes Device memory the engine holds now: weights, caches and live streams; only where the backend counts it (CUDA). +# TYPE tensorfold:device_memory_bytes gauge +tensorfold:device_memory_bytes 94724016788 +# HELP tensorfold:device_memory_peak_bytes The most device memory the engine has held since start or the last /health?reset_peak=1. +# TYPE tensorfold:device_memory_peak_bytes gauge +tensorfold:device_memory_peak_bytes 95344887716 +# HELP tensorfold:pinned_memory_bytes Pinned host memory the engine holds now: staging buffers and windows; only where the backend counts it (CUDA). +# TYPE tensorfold:pinned_memory_bytes gauge +tensorfold:pinned_memory_bytes 0 +# HELP tensorfold:num_requests_running Requests in prefill or decode. A mirror of tensorfold:requests_running. +# TYPE tensorfold:num_requests_running gauge +tensorfold:num_requests_running 0 +# HELP tensorfold:num_requests_waiting Requests queued or held until a lane is free. A mirror of tensorfold:requests_waiting. +# TYPE tensorfold:num_requests_waiting gauge +tensorfold:num_requests_waiting 0 +# HELP tensorfold:kv_cache_usage_perc A stream's cache occupancy under vLLM's name; same streams and ratios as tensorfold:kv_cache_usage_ratio. +# TYPE tensorfold:kv_cache_usage_perc gauge +tensorfold:kv_cache_usage_perc{stream="0"} 0 +# HELP tensorfold:spec_decode_num_draft_tokens_total Draft tokens verified on finished requests, this server's single draft counter. +# TYPE tensorfold:spec_decode_num_draft_tokens_total counter +tensorfold:spec_decode_num_draft_tokens_total 0 +# HELP tensorfold:spec_decode_num_accepted_tokens_total Draft tokens kept on finished requests. +# TYPE tensorfold:spec_decode_num_accepted_tokens_total counter +tensorfold:spec_decode_num_accepted_tokens_total 0 +# HELP tensorfold:e2e_request_latency_seconds Seconds from arrival to the reply leaving, under vLLM's name. +# TYPE tensorfold:e2e_request_latency_seconds histogram +tensorfold:e2e_request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="1"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="10"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="30"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="60"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="120"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="300"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:e2e_request_latency_seconds_sum 599.593843 +tensorfold:e2e_request_latency_seconds_count 2 +# HELP tensorfold:request_decode_time_seconds Seconds a finished request spent decoding, under vLLM's name. +# TYPE tensorfold:request_decode_time_seconds histogram +tensorfold:request_decode_time_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="10"} 2 +tensorfold:request_decode_time_seconds_bucket{le="30"} 2 +tensorfold:request_decode_time_seconds_bucket{le="60"} 2 +tensorfold:request_decode_time_seconds_bucket{le="120"} 2 +tensorfold:request_decode_time_seconds_bucket{le="300"} 2 +tensorfold:request_decode_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_time_seconds_sum 0.00053 +tensorfold:request_decode_time_seconds_count 2 +# HELP tensorfold:request_prefill_time_seconds Seconds a finished request's prompt pass took, under vLLM's name. +# TYPE tensorfold:request_prefill_time_seconds histogram +tensorfold:request_prefill_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="1"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="60"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="120"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="300"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_time_seconds_sum 599.591101 +tensorfold:request_prefill_time_seconds_count 2 +# HELP tensorfold:client_disconnections_total Requests a client left before the reply left the server. +# TYPE tensorfold:client_disconnections_total counter +tensorfold:client_disconnections_total 0 +# HELP tensorfold:preemptions_total Requests that had to give a lane up to a later one. +# TYPE tensorfold:preemptions_total counter +tensorfold:preemptions_total 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-261888-r2-samples.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-261888-r2-samples.jsonl new file mode 100644 index 0000000000..75812574e7 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-261888-r2-samples.jsonl @@ -0,0 +1,487 @@ +{"t_s": 0.0, "VmRSS_bytes": 74235904, "VmHWM_bytes": 74235904, "Pss_bytes": 72283136, 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110381305856, "Pss_bytes": 94726304768, "vram_used_bytes": 201371648, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 592.24, "VmRSS_bytes": 94728622080, "VmHWM_bytes": 110381305856, "Pss_bytes": 94726305792, "vram_used_bytes": 201371648, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 593.66, "VmRSS_bytes": 94728622080, "VmHWM_bytes": 110381305856, "Pss_bytes": 94726305792, "vram_used_bytes": 201371648, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 594.93, "VmRSS_bytes": 94728622080, "VmHWM_bytes": 110381305856, "Pss_bytes": 94726305792, "vram_used_bytes": 201371648, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 596.33, "VmRSS_bytes": 94728622080, "VmHWM_bytes": 110381305856, "Pss_bytes": 94726305792, "vram_used_bytes": 201371648, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 597.62, "VmRSS_bytes": 94728622080, "VmHWM_bytes": 110381305856, "Pss_bytes": 94726305792, "vram_used_bytes": 201371648, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 599.01, "VmRSS_bytes": 94728622080, "VmHWM_bytes": 110381305856, "Pss_bytes": 94726305792, "vram_used_bytes": 201371648, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 600.3, "VmRSS_bytes": 94728622080, "VmHWM_bytes": 110381305856, "Pss_bytes": 94726305792, "vram_used_bytes": 201371648, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 601.68, "VmRSS_bytes": 94728622080, "VmHWM_bytes": 110381305856, "Pss_bytes": 94726305792, "vram_used_bytes": 201371648, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 603.02, "VmRSS_bytes": 94728622080, "VmHWM_bytes": 110381305856, "Pss_bytes": 94726305792, "vram_used_bytes": 201371648, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 604.37, "VmRSS_bytes": 94728622080, "VmHWM_bytes": 110381305856, "Pss_bytes": 94726305792, "vram_used_bytes": 201371648, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 605.76, "VmRSS_bytes": 94728622080, "VmHWM_bytes": 110381305856, "Pss_bytes": 94726305792, "vram_used_bytes": 201371648, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 607.06, "VmRSS_bytes": 94728622080, "VmHWM_bytes": 110381305856, "Pss_bytes": 94726305792, "vram_used_bytes": 201371648, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 608.47, "VmRSS_bytes": 94728622080, "VmHWM_bytes": 110381305856, "Pss_bytes": 94726305792, "vram_used_bytes": 201371648, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 609.75, "VmRSS_bytes": 94728622080, "VmHWM_bytes": 110381305856, "Pss_bytes": 94726305792, "vram_used_bytes": 201371648, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 611.18, "VmRSS_bytes": 94728622080, "VmHWM_bytes": 110381305856, "Pss_bytes": 94726305792, "vram_used_bytes": 201371648, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 612.45, "VmRSS_bytes": 94728622080, "VmHWM_bytes": 110381305856, "Pss_bytes": 94726305792, "vram_used_bytes": 201371648, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 613.87, "VmRSS_bytes": 94720233472, "VmHWM_bytes": 110381305856, "Pss_bytes": 94717917184, "vram_used_bytes": 201371648, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 615.15, "VmRSS_bytes": 94720233472, "VmHWM_bytes": 110381305856, "Pss_bytes": 94717917184, "vram_used_bytes": 201371648, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 616.53, "VmRSS_bytes": 94720233472, "VmHWM_bytes": 110381305856, "Pss_bytes": 94717917184, "vram_used_bytes": 201371648, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 617.8, "VmRSS_bytes": 94720233472, "VmHWM_bytes": 110381305856, "Pss_bytes": 94717917184, "vram_used_bytes": 201371648, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 619.17, "VmRSS_bytes": 94720233472, "VmHWM_bytes": 110381305856, "Pss_bytes": 94717916160, "vram_used_bytes": 201371648, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 620.52, "VmRSS_bytes": 94720233472, "VmHWM_bytes": 110381305856, "Pss_bytes": 94717917184, "vram_used_bytes": 201371648, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 621.82, "VmRSS_bytes": 94720233472, "VmHWM_bytes": 110381305856, "Pss_bytes": 94717917184, "vram_used_bytes": 201371648, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 623.23, "VmRSS_bytes": 94720233472, "VmHWM_bytes": 110381305856, "Pss_bytes": 94717917184, "vram_used_bytes": 201371648, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 624.54, "VmRSS_bytes": 94720233472, "VmHWM_bytes": 110381305856, "Pss_bytes": 94717917184, "vram_used_bytes": 201371648, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 625.87, "VmRSS_bytes": 94720233472, "VmHWM_bytes": 110381305856, "Pss_bytes": 94717917184, "vram_used_bytes": 201371648, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 627.28, "VmRSS_bytes": 94720233472, "VmHWM_bytes": 110381305856, "Pss_bytes": 94717917184, "vram_used_bytes": 201371648, "vram_total_bytes": 4294967296, "gtt_used_bytes": 96313434112, "gtt_total_bytes": 193273528320} +{"t_s": 628.52, "VmRSS_bytes": 94620712960, "VmHWM_bytes": 110381305856, "Pss_bytes": 94618397696, "vram_used_bytes": 194510848, "vram_total_bytes": 4294967296, "gtt_used_bytes": 60468047872, "gtt_total_bytes": 193273528320} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-32768-r1-memory-endpoint.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-32768-r1-memory-endpoint.json new file mode 100644 index 0000000000..51093e5008 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-32768-r1-memory-endpoint.json @@ -0,0 +1 @@ +{"schema_version": 1, "context_window": 40960, "context_fitted": false, "device": {"active_bytes": 88438852244, "cache_bytes": 0, "peak_bytes": 88517167012, "peak_scope": "since_start_or_health_reset"}} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-32768-r1-metrics.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-32768-r1-metrics.txt new file mode 100644 index 0000000000..cb7620907c --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-32768-r1-metrics.txt @@ -0,0 +1,220 @@ +# HELP tensorfold:requests_running Requests in prefill or decode. +# TYPE tensorfold:requests_running gauge +tensorfold:requests_running 0 +# HELP tensorfold:requests_waiting Requests queued or held until a lane is free. +# TYPE tensorfold:requests_waiting gauge +tensorfold:requests_waiting 0 +# HELP tensorfold:generation_tokens_running Generated tokens held by live streams. +# TYPE tensorfold:generation_tokens_running gauge +tensorfold:generation_tokens_running 0 +# HELP tensorfold:prompt_tokens_total Prompt tokens of finished requests. +# TYPE tensorfold:prompt_tokens_total counter +tensorfold:prompt_tokens_total 33024 +# HELP tensorfold:generation_tokens_total Generated tokens of finished requests. +# TYPE tensorfold:generation_tokens_total counter +tensorfold:generation_tokens_total 2 +# HELP tensorfold:kv_cache_usage_ratio Tokens in a stream cache divided by that stream's context window. +# TYPE tensorfold:kv_cache_usage_ratio gauge +tensorfold:kv_cache_usage_ratio{pool="0"} 0 +# HELP tensorfold:mtp_drafted_total Draft tokens verified on finished requests. +# TYPE tensorfold:mtp_drafted_total counter +tensorfold:mtp_drafted_total 0 +# HELP tensorfold:mtp_accepted_total Draft tokens kept on finished requests. +# TYPE tensorfold:mtp_accepted_total counter +tensorfold:mtp_accepted_total 0 +# HELP tensorfold:request_latency_seconds Seconds from arrival to the reply leaving. +# TYPE tensorfold:request_latency_seconds histogram +tensorfold:request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:request_latency_seconds_bucket{le="0.5"} 1 +tensorfold:request_latency_seconds_bucket{le="1"} 1 +tensorfold:request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:request_latency_seconds_bucket{le="5"} 1 +tensorfold:request_latency_seconds_bucket{le="10"} 1 +tensorfold:request_latency_seconds_bucket{le="30"} 1 +tensorfold:request_latency_seconds_bucket{le="60"} 1 +tensorfold:request_latency_seconds_bucket{le="120"} 2 +tensorfold:request_latency_seconds_bucket{le="300"} 2 +tensorfold:request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:request_latency_seconds_sum 64.367859 +tensorfold:request_latency_seconds_count 2 +# HELP tensorfold:time_to_first_token_seconds Seconds from arrival to the first generated token. +# TYPE tensorfold:time_to_first_token_seconds histogram +tensorfold:time_to_first_token_seconds_bucket{le="0.01"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.05"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.25"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="1"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="2.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="10"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="30"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="60"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="120"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="300"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="+Inf"} 2 +tensorfold:time_to_first_token_seconds_sum 64.367612 +tensorfold:time_to_first_token_seconds_count 2 +# HELP tensorfold:request_decode_seconds Seconds a finished request spent decoding. Its sum over generation_tokens_total is the decode rate. +# TYPE tensorfold:request_decode_seconds histogram +tensorfold:request_decode_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_seconds_bucket{le="1"} 2 +tensorfold:request_decode_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_seconds_bucket{le="5"} 2 +tensorfold:request_decode_seconds_bucket{le="10"} 2 +tensorfold:request_decode_seconds_bucket{le="30"} 2 +tensorfold:request_decode_seconds_bucket{le="60"} 2 +tensorfold:request_decode_seconds_bucket{le="120"} 2 +tensorfold:request_decode_seconds_bucket{le="300"} 2 +tensorfold:request_decode_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_seconds_sum 0.000246 +tensorfold:request_decode_seconds_count 2 +# HELP tensorfold:request_time_per_output_token_seconds Seconds from the first generated token to the last, divided by the tokens less one. +# TYPE tensorfold:request_time_per_output_token_seconds histogram +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.005"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.01"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.015"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.02"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.03"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.04"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.05"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.15"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.2"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.3"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.5"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="+Inf"} 0 +tensorfold:request_time_per_output_token_seconds_sum 0 +tensorfold:request_time_per_output_token_seconds_count 0 +# HELP tensorfold:decode_rounds_total Decode rounds used by finished requests. +# TYPE tensorfold:decode_rounds_total counter +tensorfold:decode_rounds_total 0 +# HELP tensorfold:request_prefill_seconds Seconds a finished request's prompt pass took. +# TYPE tensorfold:request_prefill_seconds histogram +tensorfold:request_prefill_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="1"} 1 +tensorfold:request_prefill_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_seconds_bucket{le="60"} 1 +tensorfold:request_prefill_seconds_bucket{le="120"} 2 +tensorfold:request_prefill_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_seconds_sum 64.366626 +tensorfold:request_prefill_seconds_count 2 +# HELP tensorfold:process_resident_bytes Current resident set (VmRSS); device memory is not in it, so it is not a physical footprint (Linux). +# TYPE tensorfold:process_resident_bytes gauge +tensorfold:process_resident_bytes 103617994752 +# HELP tensorfold:process_resident_anon_bytes Current resident anonymous memory (RssAnon): heap, stacks and private maps (Linux). +# TYPE tensorfold:process_resident_anon_bytes gauge +tensorfold:process_resident_anon_bytes 32364847104 +# HELP tensorfold:process_resident_file_bytes Current resident file-backed memory (RssFile): the binary, libraries and mapped files (Linux). +# TYPE tensorfold:process_resident_file_bytes gauge +tensorfold:process_resident_file_bytes 71118884864 +# HELP tensorfold:process_resident_shmem_bytes Current resident shared memory (RssShmem): System V shared memory, tmpfs maps and shared anonymous maps (Linux). +# TYPE tensorfold:process_resident_shmem_bytes gauge +tensorfold:process_resident_shmem_bytes 134262784 +# HELP tensorfold:process_resident_peak_bytes Kernel lifetime peak resident set (VmHWM); never reset by health (Linux). +# TYPE tensorfold:process_resident_peak_bytes gauge +tensorfold:process_resident_peak_bytes 112783532032 +# HELP tensorfold:device_memory_bytes Device memory the engine holds now: weights, caches and live streams; only where the backend counts it (CUDA). +# TYPE tensorfold:device_memory_bytes gauge +tensorfold:device_memory_bytes 88438852244 +# HELP tensorfold:device_memory_peak_bytes The most device memory the engine has held since start or the last /health?reset_peak=1. +# TYPE tensorfold:device_memory_peak_bytes gauge +tensorfold:device_memory_peak_bytes 88517167012 +# HELP tensorfold:pinned_memory_bytes Pinned host memory the engine holds now: staging buffers and windows; only where the backend counts it (CUDA). +# TYPE tensorfold:pinned_memory_bytes gauge +tensorfold:pinned_memory_bytes 0 +# HELP tensorfold:num_requests_running Requests in prefill or decode. A mirror of tensorfold:requests_running. +# TYPE tensorfold:num_requests_running gauge +tensorfold:num_requests_running 0 +# HELP tensorfold:num_requests_waiting Requests queued or held until a lane is free. A mirror of tensorfold:requests_waiting. +# TYPE tensorfold:num_requests_waiting gauge +tensorfold:num_requests_waiting 0 +# HELP tensorfold:kv_cache_usage_perc A stream's cache occupancy under vLLM's name; same streams and ratios as tensorfold:kv_cache_usage_ratio. +# TYPE tensorfold:kv_cache_usage_perc gauge +tensorfold:kv_cache_usage_perc{stream="0"} 0 +# HELP tensorfold:spec_decode_num_draft_tokens_total Draft tokens verified on finished requests, this server's single draft counter. +# TYPE tensorfold:spec_decode_num_draft_tokens_total counter +tensorfold:spec_decode_num_draft_tokens_total 0 +# HELP tensorfold:spec_decode_num_accepted_tokens_total Draft tokens kept on finished requests. +# TYPE tensorfold:spec_decode_num_accepted_tokens_total counter +tensorfold:spec_decode_num_accepted_tokens_total 0 +# HELP tensorfold:e2e_request_latency_seconds Seconds from arrival to the reply leaving, under vLLM's name. +# TYPE tensorfold:e2e_request_latency_seconds histogram +tensorfold:e2e_request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="1"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="10"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="30"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="60"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="120"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="300"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:e2e_request_latency_seconds_sum 64.367859 +tensorfold:e2e_request_latency_seconds_count 2 +# HELP tensorfold:request_decode_time_seconds Seconds a finished request spent decoding, under vLLM's name. +# TYPE tensorfold:request_decode_time_seconds histogram +tensorfold:request_decode_time_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="10"} 2 +tensorfold:request_decode_time_seconds_bucket{le="30"} 2 +tensorfold:request_decode_time_seconds_bucket{le="60"} 2 +tensorfold:request_decode_time_seconds_bucket{le="120"} 2 +tensorfold:request_decode_time_seconds_bucket{le="300"} 2 +tensorfold:request_decode_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_time_seconds_sum 0.000246 +tensorfold:request_decode_time_seconds_count 2 +# HELP tensorfold:request_prefill_time_seconds Seconds a finished request's prompt pass took, under vLLM's name. +# TYPE tensorfold:request_prefill_time_seconds histogram +tensorfold:request_prefill_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="1"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="60"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="120"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_time_seconds_sum 64.366626 +tensorfold:request_prefill_time_seconds_count 2 +# HELP tensorfold:client_disconnections_total Requests a client left before the reply left the server. +# TYPE tensorfold:client_disconnections_total counter +tensorfold:client_disconnections_total 0 +# HELP tensorfold:preemptions_total Requests that had to give a lane up to a later one. +# TYPE tensorfold:preemptions_total counter +tensorfold:preemptions_total 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-32768-r1-samples.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-32768-r1-samples.jsonl new file mode 100644 index 0000000000..d068bc4847 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-32768-r1-samples.jsonl @@ -0,0 +1,75 @@ +{"t_s": 0.0, "VmRSS_bytes": 74469376, "VmHWM_bytes": 74469376, "Pss_bytes": 72377344, "vram_used_bytes": 187682816, "vram_total_bytes": 4294967296, "gtt_used_bytes": 31657984, "gtt_total_bytes": 193273528320} +{"t_s": 1.04, "VmRSS_bytes": 9698021376, "VmHWM_bytes": 9698021376, "Pss_bytes": 9695706112, "vram_used_bytes": 188813312, "vram_total_bytes": 4294967296, "gtt_used_bytes": 6841233408, "gtt_total_bytes": 193273528320} +{"t_s": 2.1, "VmRSS_bytes": 18334785536, "VmHWM_bytes": 18334785536, "Pss_bytes": 18332470272, "vram_used_bytes": 189370368, "vram_total_bytes": 4294967296, "gtt_used_bytes": 16542658560, "gtt_total_bytes": 193273528320} +{"t_s": 3.2, "VmRSS_bytes": 26489593856, "VmHWM_bytes": 26489593856, "Pss_bytes": 26487278592, "vram_used_bytes": 190074880, "vram_total_bytes": 4294967296, "gtt_used_bytes": 24910295040, "gtt_total_bytes": 193273528320} +{"t_s": 4.32, "VmRSS_bytes": 36090847232, "VmHWM_bytes": 36090847232, "Pss_bytes": 36107144192, "vram_used_bytes": 190611456, "vram_total_bytes": 4294967296, "gtt_used_bytes": 33131130880, "gtt_total_bytes": 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112783532032, "Pss_bytes": 103617490944, "vram_used_bytes": 210567168, "vram_total_bytes": 4294967296, "gtt_used_bytes": 89487204352, "gtt_total_bytes": 193273528320} +{"t_s": 67.6, "VmRSS_bytes": 103619874816, "VmHWM_bytes": 112783532032, "Pss_bytes": 103617490944, "vram_used_bytes": 210567168, "vram_total_bytes": 4294967296, "gtt_used_bytes": 89487204352, "gtt_total_bytes": 193273528320} +{"t_s": 68.85, "VmRSS_bytes": 103619874816, "VmHWM_bytes": 112783532032, "Pss_bytes": 103617498112, "vram_used_bytes": 210567168, "vram_total_bytes": 4294967296, "gtt_used_bytes": 89487204352, "gtt_total_bytes": 193273528320} +{"t_s": 70.09, "VmRSS_bytes": 103619874816, "VmHWM_bytes": 112783532032, "Pss_bytes": 103617498112, "vram_used_bytes": 210567168, "vram_total_bytes": 4294967296, "gtt_used_bytes": 89487204352, "gtt_total_bytes": 193273528320} +{"t_s": 71.33, "VmRSS_bytes": 103619874816, "VmHWM_bytes": 112783532032, "Pss_bytes": 103617498112, "vram_used_bytes": 210567168, "vram_total_bytes": 4294967296, "gtt_used_bytes": 89487204352, "gtt_total_bytes": 193273528320} +{"t_s": 72.59, "VmRSS_bytes": 103619874816, "VmHWM_bytes": 112783532032, "Pss_bytes": 103617498112, "vram_used_bytes": 210567168, "vram_total_bytes": 4294967296, "gtt_used_bytes": 89487204352, "gtt_total_bytes": 193273528320} +{"t_s": 73.86, "VmRSS_bytes": 103619874816, "VmHWM_bytes": 112783532032, "Pss_bytes": 103617498112, "vram_used_bytes": 210567168, "vram_total_bytes": 4294967296, "gtt_used_bytes": 89487204352, "gtt_total_bytes": 193273528320} +{"t_s": 75.11, "VmRSS_bytes": 103619874816, "VmHWM_bytes": 112783532032, "Pss_bytes": 103617518592, "vram_used_bytes": 210567168, "vram_total_bytes": 4294967296, "gtt_used_bytes": 89487204352, "gtt_total_bytes": 193273528320} +{"t_s": 76.36, "VmRSS_bytes": 103619874816, "VmHWM_bytes": 112783532032, "Pss_bytes": 103617498112, "vram_used_bytes": 210567168, "vram_total_bytes": 4294967296, "gtt_used_bytes": 89487204352, "gtt_total_bytes": 193273528320} +{"t_s": 77.6, "VmRSS_bytes": 103619874816, "VmHWM_bytes": 112783532032, "Pss_bytes": 103617498112, "vram_used_bytes": 210567168, "vram_total_bytes": 4294967296, "gtt_used_bytes": 89487204352, "gtt_total_bytes": 193273528320} +{"t_s": 78.86, "VmRSS_bytes": 103619874816, "VmHWM_bytes": 112783532032, "Pss_bytes": 103617498112, "vram_used_bytes": 210567168, "vram_total_bytes": 4294967296, "gtt_used_bytes": 89487204352, "gtt_total_bytes": 193273528320} +{"t_s": 80.13, "VmRSS_bytes": 103619874816, "VmHWM_bytes": 112783532032, "Pss_bytes": 103617498112, "vram_used_bytes": 210567168, "vram_total_bytes": 4294967296, "gtt_used_bytes": 89487204352, "gtt_total_bytes": 193273528320} +{"t_s": 81.39, "VmRSS_bytes": 103619874816, "VmHWM_bytes": 112783532032, "Pss_bytes": 103617498112, "vram_used_bytes": 210567168, "vram_total_bytes": 4294967296, "gtt_used_bytes": 89487204352, "gtt_total_bytes": 193273528320} +{"t_s": 82.64, "VmRSS_bytes": 103619874816, "VmHWM_bytes": 112783532032, "Pss_bytes": 103617498112, "vram_used_bytes": 210567168, "vram_total_bytes": 4294967296, "gtt_used_bytes": 89487204352, "gtt_total_bytes": 193273528320} +{"t_s": 83.89, "VmRSS_bytes": 103619874816, "VmHWM_bytes": 112783532032, "Pss_bytes": 103617498112, "vram_used_bytes": 210567168, "vram_total_bytes": 4294967296, "gtt_used_bytes": 89487204352, "gtt_total_bytes": 193273528320} +{"t_s": 85.14, "VmRSS_bytes": 103619874816, "VmHWM_bytes": 112783532032, "Pss_bytes": 103617498112, "vram_used_bytes": 210567168, "vram_total_bytes": 4294967296, "gtt_used_bytes": 89487204352, "gtt_total_bytes": 193273528320} +{"t_s": 86.41, "VmRSS_bytes": 103619874816, "VmHWM_bytes": 112783532032, "Pss_bytes": 103617498112, "vram_used_bytes": 210567168, "vram_total_bytes": 4294967296, "gtt_used_bytes": 89487204352, "gtt_total_bytes": 193273528320} +{"t_s": 87.68, "VmRSS_bytes": 103619874816, "VmHWM_bytes": 112783532032, "Pss_bytes": 103617498112, "vram_used_bytes": 210567168, "vram_total_bytes": 4294967296, "gtt_used_bytes": 89487204352, "gtt_total_bytes": 193273528320} +{"t_s": 88.93, "VmRSS_bytes": 103619874816, "VmHWM_bytes": 112783532032, "Pss_bytes": 103617498112, "vram_used_bytes": 210567168, "vram_total_bytes": 4294967296, "gtt_used_bytes": 89487204352, "gtt_total_bytes": 193273528320} +{"t_s": 90.18, "VmRSS_bytes": 103619874816, "VmHWM_bytes": 112783532032, "Pss_bytes": 103617498112, "vram_used_bytes": 210567168, "vram_total_bytes": 4294967296, "gtt_used_bytes": 89487204352, "gtt_total_bytes": 193273528320} +{"t_s": 91.42, "VmRSS_bytes": 103619874816, "VmHWM_bytes": 112783532032, "Pss_bytes": 103617498112, "vram_used_bytes": 210567168, "vram_total_bytes": 4294967296, "gtt_used_bytes": 89487204352, "gtt_total_bytes": 193273528320} +{"t_s": 92.66, "VmRSS_bytes": 103539806208, "VmHWM_bytes": 112783532032, "Pss_bytes": 103537421312, "vram_used_bytes": 195284992, "vram_total_bytes": 4294967296, "gtt_used_bytes": 4811730944, "gtt_total_bytes": 193273528320} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-32768-r2-memory-endpoint.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-32768-r2-memory-endpoint.json new file mode 100644 index 0000000000..51093e5008 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-32768-r2-memory-endpoint.json @@ -0,0 +1 @@ +{"schema_version": 1, "context_window": 40960, "context_fitted": false, "device": {"active_bytes": 88438852244, "cache_bytes": 0, "peak_bytes": 88517167012, "peak_scope": "since_start_or_health_reset"}} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-32768-r2-metrics.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-32768-r2-metrics.txt new file mode 100644 index 0000000000..fea9b9c7b5 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-32768-r2-metrics.txt @@ -0,0 +1,220 @@ +# HELP tensorfold:requests_running Requests in prefill or decode. +# TYPE tensorfold:requests_running gauge +tensorfold:requests_running 0 +# HELP tensorfold:requests_waiting Requests queued or held until a lane is free. +# TYPE tensorfold:requests_waiting gauge +tensorfold:requests_waiting 0 +# HELP tensorfold:generation_tokens_running Generated tokens held by live streams. +# TYPE tensorfold:generation_tokens_running gauge +tensorfold:generation_tokens_running 0 +# HELP tensorfold:prompt_tokens_total Prompt tokens of finished requests. +# TYPE tensorfold:prompt_tokens_total counter +tensorfold:prompt_tokens_total 33024 +# HELP tensorfold:generation_tokens_total Generated tokens of finished requests. +# TYPE tensorfold:generation_tokens_total counter +tensorfold:generation_tokens_total 2 +# HELP tensorfold:kv_cache_usage_ratio Tokens in a stream cache divided by that stream's context window. +# TYPE tensorfold:kv_cache_usage_ratio gauge +tensorfold:kv_cache_usage_ratio{pool="0"} 0 +# HELP tensorfold:mtp_drafted_total Draft tokens verified on finished requests. +# TYPE tensorfold:mtp_drafted_total counter +tensorfold:mtp_drafted_total 0 +# HELP tensorfold:mtp_accepted_total Draft tokens kept on finished requests. +# TYPE tensorfold:mtp_accepted_total counter +tensorfold:mtp_accepted_total 0 +# HELP tensorfold:request_latency_seconds Seconds from arrival to the reply leaving. +# TYPE tensorfold:request_latency_seconds histogram +tensorfold:request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:request_latency_seconds_bucket{le="0.5"} 1 +tensorfold:request_latency_seconds_bucket{le="1"} 1 +tensorfold:request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:request_latency_seconds_bucket{le="5"} 1 +tensorfold:request_latency_seconds_bucket{le="10"} 1 +tensorfold:request_latency_seconds_bucket{le="30"} 1 +tensorfold:request_latency_seconds_bucket{le="60"} 1 +tensorfold:request_latency_seconds_bucket{le="120"} 2 +tensorfold:request_latency_seconds_bucket{le="300"} 2 +tensorfold:request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:request_latency_seconds_sum 64.120222 +tensorfold:request_latency_seconds_count 2 +# HELP tensorfold:time_to_first_token_seconds Seconds from arrival to the first generated token. +# TYPE tensorfold:time_to_first_token_seconds histogram +tensorfold:time_to_first_token_seconds_bucket{le="0.01"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.05"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.25"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="1"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="2.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="10"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="30"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="60"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="120"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="300"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="+Inf"} 2 +tensorfold:time_to_first_token_seconds_sum 64.119913 +tensorfold:time_to_first_token_seconds_count 2 +# HELP tensorfold:request_decode_seconds Seconds a finished request spent decoding. Its sum over generation_tokens_total is the decode rate. +# TYPE tensorfold:request_decode_seconds histogram +tensorfold:request_decode_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_seconds_bucket{le="1"} 2 +tensorfold:request_decode_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_seconds_bucket{le="5"} 2 +tensorfold:request_decode_seconds_bucket{le="10"} 2 +tensorfold:request_decode_seconds_bucket{le="30"} 2 +tensorfold:request_decode_seconds_bucket{le="60"} 2 +tensorfold:request_decode_seconds_bucket{le="120"} 2 +tensorfold:request_decode_seconds_bucket{le="300"} 2 +tensorfold:request_decode_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_seconds_sum 0.000309 +tensorfold:request_decode_seconds_count 2 +# HELP tensorfold:request_time_per_output_token_seconds Seconds from the first generated token to the last, divided by the tokens less one. +# TYPE tensorfold:request_time_per_output_token_seconds histogram +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.005"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.01"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.015"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.02"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.03"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.04"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.05"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.15"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.2"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.3"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.5"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="+Inf"} 0 +tensorfold:request_time_per_output_token_seconds_sum 0 +tensorfold:request_time_per_output_token_seconds_count 0 +# HELP tensorfold:decode_rounds_total Decode rounds used by finished requests. +# TYPE tensorfold:decode_rounds_total counter +tensorfold:decode_rounds_total 0 +# HELP tensorfold:request_prefill_seconds Seconds a finished request's prompt pass took. +# TYPE tensorfold:request_prefill_seconds histogram +tensorfold:request_prefill_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="1"} 1 +tensorfold:request_prefill_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_seconds_bucket{le="60"} 1 +tensorfold:request_prefill_seconds_bucket{le="120"} 2 +tensorfold:request_prefill_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_seconds_sum 64.118912 +tensorfold:request_prefill_seconds_count 2 +# HELP tensorfold:process_resident_bytes Current resident set (VmRSS); device memory is not in it, so it is not a physical footprint (Linux). +# TYPE tensorfold:process_resident_bytes gauge +tensorfold:process_resident_bytes 104150597632 +# HELP tensorfold:process_resident_anon_bytes Current resident anonymous memory (RssAnon): heap, stacks and private maps (Linux). +# TYPE tensorfold:process_resident_anon_bytes gauge +tensorfold:process_resident_anon_bytes 32371363840 +# HELP tensorfold:process_resident_file_bytes Current resident file-backed memory (RssFile): the binary, libraries and mapped files (Linux). +# TYPE tensorfold:process_resident_file_bytes gauge +tensorfold:process_resident_file_bytes 71644971008 +# HELP tensorfold:process_resident_shmem_bytes Current resident shared memory (RssShmem): System V shared memory, tmpfs maps and shared anonymous maps (Linux). +# TYPE tensorfold:process_resident_shmem_bytes gauge +tensorfold:process_resident_shmem_bytes 134262784 +# HELP tensorfold:process_resident_peak_bytes Kernel lifetime peak resident set (VmHWM); never reset by health (Linux). +# TYPE tensorfold:process_resident_peak_bytes gauge +tensorfold:process_resident_peak_bytes 112690528256 +# HELP tensorfold:device_memory_bytes Device memory the engine holds now: weights, caches and live streams; only where the backend counts it (CUDA). +# TYPE tensorfold:device_memory_bytes gauge +tensorfold:device_memory_bytes 88438852244 +# HELP tensorfold:device_memory_peak_bytes The most device memory the engine has held since start or the last /health?reset_peak=1. +# TYPE tensorfold:device_memory_peak_bytes gauge +tensorfold:device_memory_peak_bytes 88517167012 +# HELP tensorfold:pinned_memory_bytes Pinned host memory the engine holds now: staging buffers and windows; only where the backend counts it (CUDA). +# TYPE tensorfold:pinned_memory_bytes gauge +tensorfold:pinned_memory_bytes 0 +# HELP tensorfold:num_requests_running Requests in prefill or decode. A mirror of tensorfold:requests_running. +# TYPE tensorfold:num_requests_running gauge +tensorfold:num_requests_running 0 +# HELP tensorfold:num_requests_waiting Requests queued or held until a lane is free. A mirror of tensorfold:requests_waiting. +# TYPE tensorfold:num_requests_waiting gauge +tensorfold:num_requests_waiting 0 +# HELP tensorfold:kv_cache_usage_perc A stream's cache occupancy under vLLM's name; same streams and ratios as tensorfold:kv_cache_usage_ratio. +# TYPE tensorfold:kv_cache_usage_perc gauge +tensorfold:kv_cache_usage_perc{stream="0"} 0 +# HELP tensorfold:spec_decode_num_draft_tokens_total Draft tokens verified on finished requests, this server's single draft counter. +# TYPE tensorfold:spec_decode_num_draft_tokens_total counter +tensorfold:spec_decode_num_draft_tokens_total 0 +# HELP tensorfold:spec_decode_num_accepted_tokens_total Draft tokens kept on finished requests. +# TYPE tensorfold:spec_decode_num_accepted_tokens_total counter +tensorfold:spec_decode_num_accepted_tokens_total 0 +# HELP tensorfold:e2e_request_latency_seconds Seconds from arrival to the reply leaving, under vLLM's name. +# TYPE tensorfold:e2e_request_latency_seconds histogram +tensorfold:e2e_request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="1"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="10"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="30"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="60"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="120"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="300"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:e2e_request_latency_seconds_sum 64.120222 +tensorfold:e2e_request_latency_seconds_count 2 +# HELP tensorfold:request_decode_time_seconds Seconds a finished request spent decoding, under vLLM's name. +# TYPE tensorfold:request_decode_time_seconds histogram +tensorfold:request_decode_time_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="10"} 2 +tensorfold:request_decode_time_seconds_bucket{le="30"} 2 +tensorfold:request_decode_time_seconds_bucket{le="60"} 2 +tensorfold:request_decode_time_seconds_bucket{le="120"} 2 +tensorfold:request_decode_time_seconds_bucket{le="300"} 2 +tensorfold:request_decode_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_time_seconds_sum 0.000309 +tensorfold:request_decode_time_seconds_count 2 +# HELP tensorfold:request_prefill_time_seconds Seconds a finished request's prompt pass took, under vLLM's name. +# TYPE tensorfold:request_prefill_time_seconds histogram +tensorfold:request_prefill_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="1"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="60"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="120"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_time_seconds_sum 64.118912 +tensorfold:request_prefill_time_seconds_count 2 +# HELP tensorfold:client_disconnections_total Requests a client left before the reply left the server. +# TYPE tensorfold:client_disconnections_total counter +tensorfold:client_disconnections_total 0 +# HELP tensorfold:preemptions_total Requests that had to give a lane up to a later one. +# TYPE tensorfold:preemptions_total counter +tensorfold:preemptions_total 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-32768-r2-samples.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-32768-r2-samples.jsonl new file mode 100644 index 0000000000..20ed5a6f2c --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-32768-r2-samples.jsonl @@ -0,0 +1,75 @@ +{"t_s": 0.0, "VmRSS_bytes": 74301440, "VmHWM_bytes": 74301440, "Pss_bytes": 72313856, "vram_used_bytes": 187682816, "vram_total_bytes": 4294967296, "gtt_used_bytes": 31657984, "gtt_total_bytes": 193273528320} +{"t_s": 1.04, "VmRSS_bytes": 9415917568, "VmHWM_bytes": 9415917568, "Pss_bytes": 9501644800, "vram_used_bytes": 188801024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 6841233408, "gtt_total_bytes": 193273528320} +{"t_s": 2.1, "VmRSS_bytes": 18252828672, "VmHWM_bytes": 18252828672, "Pss_bytes": 18330494976, "vram_used_bytes": 189358080, "vram_total_bytes": 4294967296, "gtt_used_bytes": 15062069248, "gtt_total_bytes": 193273528320} +{"t_s": 3.19, "VmRSS_bytes": 26452201472, "VmHWM_bytes": 26452201472, "Pss_bytes": 26449847296, "vram_used_bytes": 189931520, "vram_total_bytes": 4294967296, "gtt_used_bytes": 24228720640, "gtt_total_bytes": 193273528320} +{"t_s": 4.33, "VmRSS_bytes": 34606223360, "VmHWM_bytes": 34606223360, "Pss_bytes": 34603870208, "vram_used_bytes": 190603264, "vram_total_bytes": 4294967296, "gtt_used_bytes": 33124839424, "gtt_total_bytes": 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"vram_used_bytes": 208826368, "vram_total_bytes": 4294967296, "gtt_used_bytes": 89487204352, "gtt_total_bytes": 193273528320} +{"t_s": 85.61, "VmRSS_bytes": 104152477696, "VmHWM_bytes": 112690528256, "Pss_bytes": 104150063104, "vram_used_bytes": 208826368, "vram_total_bytes": 4294967296, "gtt_used_bytes": 89487204352, "gtt_total_bytes": 193273528320} +{"t_s": 86.88, "VmRSS_bytes": 104152477696, "VmHWM_bytes": 112690528256, "Pss_bytes": 104150062080, "vram_used_bytes": 208826368, "vram_total_bytes": 4294967296, "gtt_used_bytes": 89487204352, "gtt_total_bytes": 193273528320} +{"t_s": 88.17, "VmRSS_bytes": 104152477696, "VmHWM_bytes": 112690528256, "Pss_bytes": 104150063104, "vram_used_bytes": 208826368, "vram_total_bytes": 4294967296, "gtt_used_bytes": 89487204352, "gtt_total_bytes": 193273528320} +{"t_s": 89.47, "VmRSS_bytes": 104152477696, "VmHWM_bytes": 112690528256, "Pss_bytes": 104150062080, "vram_used_bytes": 208826368, "vram_total_bytes": 4294967296, "gtt_used_bytes": 89487204352, "gtt_total_bytes": 193273528320} +{"t_s": 90.76, "VmRSS_bytes": 104152477696, "VmHWM_bytes": 112690528256, "Pss_bytes": 104150062080, "vram_used_bytes": 208826368, "vram_total_bytes": 4294967296, "gtt_used_bytes": 89487204352, "gtt_total_bytes": 193273528320} +{"t_s": 92.03, "VmRSS_bytes": 104152477696, "VmHWM_bytes": 112690528256, "Pss_bytes": 104150062080, "vram_used_bytes": 208826368, "vram_total_bytes": 4294967296, "gtt_used_bytes": 89487204352, "gtt_total_bytes": 193273528320} +{"t_s": 93.3, "VmRSS_bytes": 104152477696, "VmHWM_bytes": 112690528256, "Pss_bytes": 104150062080, "vram_used_bytes": 208826368, "vram_total_bytes": 4294967296, "gtt_used_bytes": 89487204352, "gtt_total_bytes": 193273528320} +{"t_s": 94.52, "VmRSS_bytes": 98190331904, "VmHWM_bytes": 112690528256, "Pss_bytes": 95569853440, "vram_used_bytes": 195268608, "vram_total_bytes": 4294967296, "gtt_used_bytes": 204288000, "gtt_total_bytes": 193273528320} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-65536-r1-memory-endpoint.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-65536-r1-memory-endpoint.json new file mode 100644 index 0000000000..88a8909495 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-65536-r1-memory-endpoint.json @@ -0,0 +1 @@ +{"schema_version": 1, "context_window": 73728, "context_fitted": false, "device": {"active_bytes": 89369987732, "cache_bytes": 0, "peak_bytes": 89525897124, "peak_scope": "since_start_or_health_reset"}} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-65536-r1-metrics.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-65536-r1-metrics.txt new file mode 100644 index 0000000000..fc149f5c8c --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-65536-r1-metrics.txt @@ -0,0 +1,220 @@ +# HELP tensorfold:requests_running Requests in prefill or decode. +# TYPE tensorfold:requests_running gauge +tensorfold:requests_running 0 +# HELP tensorfold:requests_waiting Requests queued or held until a lane is free. +# TYPE tensorfold:requests_waiting gauge +tensorfold:requests_waiting 0 +# HELP tensorfold:generation_tokens_running Generated tokens held by live streams. +# TYPE tensorfold:generation_tokens_running gauge +tensorfold:generation_tokens_running 0 +# HELP tensorfold:prompt_tokens_total Prompt tokens of finished requests. +# TYPE tensorfold:prompt_tokens_total counter +tensorfold:prompt_tokens_total 65792 +# HELP tensorfold:generation_tokens_total Generated tokens of finished requests. +# TYPE tensorfold:generation_tokens_total counter +tensorfold:generation_tokens_total 2 +# HELP tensorfold:kv_cache_usage_ratio Tokens in a stream cache divided by that stream's context window. +# TYPE tensorfold:kv_cache_usage_ratio gauge +tensorfold:kv_cache_usage_ratio{pool="0"} 0 +# HELP tensorfold:mtp_drafted_total Draft tokens verified on finished requests. +# TYPE tensorfold:mtp_drafted_total counter +tensorfold:mtp_drafted_total 0 +# HELP tensorfold:mtp_accepted_total Draft tokens kept on finished requests. +# TYPE tensorfold:mtp_accepted_total counter +tensorfold:mtp_accepted_total 0 +# HELP tensorfold:request_latency_seconds Seconds from arrival to the reply leaving. +# TYPE tensorfold:request_latency_seconds histogram +tensorfold:request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:request_latency_seconds_bucket{le="0.5"} 1 +tensorfold:request_latency_seconds_bucket{le="1"} 1 +tensorfold:request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:request_latency_seconds_bucket{le="5"} 1 +tensorfold:request_latency_seconds_bucket{le="10"} 1 +tensorfold:request_latency_seconds_bucket{le="30"} 1 +tensorfold:request_latency_seconds_bucket{le="60"} 1 +tensorfold:request_latency_seconds_bucket{le="120"} 1 +tensorfold:request_latency_seconds_bucket{le="300"} 2 +tensorfold:request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:request_latency_seconds_sum 132.251103 +tensorfold:request_latency_seconds_count 2 +# HELP tensorfold:time_to_first_token_seconds Seconds from arrival to the first generated token. +# TYPE tensorfold:time_to_first_token_seconds histogram +tensorfold:time_to_first_token_seconds_bucket{le="0.01"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.05"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.25"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="1"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="2.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="10"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="30"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="60"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="120"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="300"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="+Inf"} 2 +tensorfold:time_to_first_token_seconds_sum 132.250795 +tensorfold:time_to_first_token_seconds_count 2 +# HELP tensorfold:request_decode_seconds Seconds a finished request spent decoding. Its sum over generation_tokens_total is the decode rate. +# TYPE tensorfold:request_decode_seconds histogram +tensorfold:request_decode_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_seconds_bucket{le="1"} 2 +tensorfold:request_decode_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_seconds_bucket{le="5"} 2 +tensorfold:request_decode_seconds_bucket{le="10"} 2 +tensorfold:request_decode_seconds_bucket{le="30"} 2 +tensorfold:request_decode_seconds_bucket{le="60"} 2 +tensorfold:request_decode_seconds_bucket{le="120"} 2 +tensorfold:request_decode_seconds_bucket{le="300"} 2 +tensorfold:request_decode_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_seconds_sum 0.000308 +tensorfold:request_decode_seconds_count 2 +# HELP tensorfold:request_time_per_output_token_seconds Seconds from the first generated token to the last, divided by the tokens less one. +# TYPE tensorfold:request_time_per_output_token_seconds histogram +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.005"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.01"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.015"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.02"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.03"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.04"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.05"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.15"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.2"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.3"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.5"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="+Inf"} 0 +tensorfold:request_time_per_output_token_seconds_sum 0 +tensorfold:request_time_per_output_token_seconds_count 0 +# HELP tensorfold:decode_rounds_total Decode rounds used by finished requests. +# TYPE tensorfold:decode_rounds_total counter +tensorfold:decode_rounds_total 0 +# HELP tensorfold:request_prefill_seconds Seconds a finished request's prompt pass took. +# TYPE tensorfold:request_prefill_seconds histogram +tensorfold:request_prefill_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="1"} 1 +tensorfold:request_prefill_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_seconds_bucket{le="60"} 1 +tensorfold:request_prefill_seconds_bucket{le="120"} 1 +tensorfold:request_prefill_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_seconds_sum 132.249425 +tensorfold:request_prefill_seconds_count 2 +# HELP tensorfold:process_resident_bytes Current resident set (VmRSS); device memory is not in it, so it is not a physical footprint (Linux). +# TYPE tensorfold:process_resident_bytes gauge +tensorfold:process_resident_bytes 103798587392 +# HELP tensorfold:process_resident_anon_bytes Current resident anonymous memory (RssAnon): heap, stacks and private maps (Linux). +# TYPE tensorfold:process_resident_anon_bytes gauge +tensorfold:process_resident_anon_bytes 32369029120 +# HELP tensorfold:process_resident_file_bytes Current resident file-backed memory (RssFile): the binary, libraries and mapped files (Linux). +# TYPE tensorfold:process_resident_file_bytes gauge +tensorfold:process_resident_file_bytes 71295295488 +# HELP tensorfold:process_resident_shmem_bytes Current resident shared memory (RssShmem): System V shared memory, tmpfs maps and shared anonymous maps (Linux). +# TYPE tensorfold:process_resident_shmem_bytes gauge +tensorfold:process_resident_shmem_bytes 134262784 +# HELP tensorfold:process_resident_peak_bytes Kernel lifetime peak resident set (VmHWM); never reset by health (Linux). +# TYPE tensorfold:process_resident_peak_bytes gauge +tensorfold:process_resident_peak_bytes 112649281536 +# HELP tensorfold:device_memory_bytes Device memory the engine holds now: weights, caches and live streams; only where the backend counts it (CUDA). +# TYPE tensorfold:device_memory_bytes gauge +tensorfold:device_memory_bytes 89369987732 +# HELP tensorfold:device_memory_peak_bytes The most device memory the engine has held since start or the last /health?reset_peak=1. +# TYPE tensorfold:device_memory_peak_bytes gauge +tensorfold:device_memory_peak_bytes 89525897124 +# HELP tensorfold:pinned_memory_bytes Pinned host memory the engine holds now: staging buffers and windows; only where the backend counts it (CUDA). +# TYPE tensorfold:pinned_memory_bytes gauge +tensorfold:pinned_memory_bytes 0 +# HELP tensorfold:num_requests_running Requests in prefill or decode. A mirror of tensorfold:requests_running. +# TYPE tensorfold:num_requests_running gauge +tensorfold:num_requests_running 0 +# HELP tensorfold:num_requests_waiting Requests queued or held until a lane is free. A mirror of tensorfold:requests_waiting. +# TYPE tensorfold:num_requests_waiting gauge +tensorfold:num_requests_waiting 0 +# HELP tensorfold:kv_cache_usage_perc A stream's cache occupancy under vLLM's name; same streams and ratios as tensorfold:kv_cache_usage_ratio. +# TYPE tensorfold:kv_cache_usage_perc gauge +tensorfold:kv_cache_usage_perc{stream="0"} 0 +# HELP tensorfold:spec_decode_num_draft_tokens_total Draft tokens verified on finished requests, this server's single draft counter. +# TYPE tensorfold:spec_decode_num_draft_tokens_total counter +tensorfold:spec_decode_num_draft_tokens_total 0 +# HELP tensorfold:spec_decode_num_accepted_tokens_total Draft tokens kept on finished requests. +# TYPE tensorfold:spec_decode_num_accepted_tokens_total counter +tensorfold:spec_decode_num_accepted_tokens_total 0 +# HELP tensorfold:e2e_request_latency_seconds Seconds from arrival to the reply leaving, under vLLM's name. +# TYPE tensorfold:e2e_request_latency_seconds histogram +tensorfold:e2e_request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="1"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="10"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="30"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="60"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="120"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="300"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:e2e_request_latency_seconds_sum 132.251103 +tensorfold:e2e_request_latency_seconds_count 2 +# HELP tensorfold:request_decode_time_seconds Seconds a finished request spent decoding, under vLLM's name. +# TYPE tensorfold:request_decode_time_seconds histogram +tensorfold:request_decode_time_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="10"} 2 +tensorfold:request_decode_time_seconds_bucket{le="30"} 2 +tensorfold:request_decode_time_seconds_bucket{le="60"} 2 +tensorfold:request_decode_time_seconds_bucket{le="120"} 2 +tensorfold:request_decode_time_seconds_bucket{le="300"} 2 +tensorfold:request_decode_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_time_seconds_sum 0.000308 +tensorfold:request_decode_time_seconds_count 2 +# HELP tensorfold:request_prefill_time_seconds Seconds a finished request's prompt pass took, under vLLM's name. +# TYPE tensorfold:request_prefill_time_seconds histogram +tensorfold:request_prefill_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="1"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="60"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="120"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_time_seconds_sum 132.249425 +tensorfold:request_prefill_time_seconds_count 2 +# HELP tensorfold:client_disconnections_total Requests a client left before the reply left the server. +# TYPE tensorfold:client_disconnections_total counter +tensorfold:client_disconnections_total 0 +# HELP tensorfold:preemptions_total Requests that had to give a lane up to a later one. +# TYPE tensorfold:preemptions_total counter +tensorfold:preemptions_total 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-65536-r1-samples.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-65536-r1-samples.jsonl new file mode 100644 index 0000000000..38abeaad98 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-65536-r1-samples.jsonl @@ -0,0 +1,143 @@ +{"t_s": 0.0, "VmRSS_bytes": 69443584, "VmHWM_bytes": 70238208, "Pss_bytes": 68436992, "vram_used_bytes": 187670528, "vram_total_bytes": 4294967296, "gtt_used_bytes": 31657984, "gtt_total_bytes": 193273528320} +{"t_s": 1.01, "VmRSS_bytes": 5437198336, "VmHWM_bytes": 5437198336, "Pss_bytes": 5441060864, "vram_used_bytes": 188649472, "vram_total_bytes": 4294967296, "gtt_used_bytes": 3557093376, "gtt_total_bytes": 193273528320} +{"t_s": 2.04, "VmRSS_bytes": 10238377984, "VmHWM_bytes": 10238377984, "Pss_bytes": 10236014592, "vram_used_bytes": 188801024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 8445554688, "gtt_total_bytes": 193273528320} +{"t_s": 3.07, "VmRSS_bytes": 15046254592, "VmHWM_bytes": 15046254592, "Pss_bytes": 15063552000, "vram_used_bytes": 189079552, "vram_total_bytes": 4294967296, "gtt_used_bytes": 11773734912, "gtt_total_bytes": 193273528320} +{"t_s": 4.11, "VmRSS_bytes": 19647557632, "VmHWM_bytes": 19647557632, "Pss_bytes": 19653582848, "vram_used_bytes": 189394944, "vram_total_bytes": 4294967296, "gtt_used_bytes": 16699944960, "gtt_total_bytes": 193273528320} +{"t_s": 5.17, "VmRSS_bytes": 24411394048, "VmHWM_bytes": 24411394048, "Pss_bytes": 24413224960, "vram_used_bytes": 189710336, "vram_total_bytes": 4294967296, "gtt_used_bytes": 21626155008, "gtt_total_bytes": 193273528320} +{"t_s": 6.24, "VmRSS_bytes": 29227061248, "VmHWM_bytes": 29227061248, "Pss_bytes": 29258252288, "vram_used_bytes": 190042112, "vram_total_bytes": 4294967296, "gtt_used_bytes": 26554462208, "gtt_total_bytes": 193273528320} +{"t_s": 7.31, "VmRSS_bytes": 34164158464, "VmHWM_bytes": 34164158464, "Pss_bytes": 34174377984, "vram_used_bytes": 190345216, "vram_total_bytes": 4294967296, "gtt_used_bytes": 31486963712, "gtt_total_bytes": 193273528320} +{"t_s": 8.39, "VmRSS_bytes": 39122763776, "VmHWM_bytes": 39122763776, "Pss_bytes": 39140061184, "vram_used_bytes": 190664704, "vram_total_bytes": 4294967296, "gtt_used_bytes": 36419465216, "gtt_total_bytes": 193273528320} +{"t_s": 9.48, "VmRSS_bytes": 43939938304, "VmHWM_bytes": 43939938304, "Pss_bytes": 43966672896, "vram_used_bytes": 190984192, "vram_total_bytes": 4294967296, "gtt_used_bytes": 41345675264, "gtt_total_bytes": 193273528320} +{"t_s": 10.59, "VmRSS_bytes": 48818360320, "VmHWM_bytes": 48818360320, "Pss_bytes": 48832774144, "vram_used_bytes": 191283200, "vram_total_bytes": 4294967296, "gtt_used_bytes": 46273982464, "gtt_total_bytes": 193273528320} +{"t_s": 11.7, "VmRSS_bytes": 54025469952, "VmHWM_bytes": 54025469952, "Pss_bytes": 54023116800, "vram_used_bytes": 191623168, "vram_total_bytes": 4294967296, "gtt_used_bytes": 52152299520, "gtt_total_bytes": 193273528320} +{"t_s": 12.84, "VmRSS_bytes": 58441011200, "VmHWM_bytes": 58441011200, "Pss_bytes": 58449143808, "vram_used_bytes": 191930368, "vram_total_bytes": 4294967296, "gtt_used_bytes": 56132694016, "gtt_total_bytes": 193273528320} +{"t_s": 13.98, "VmRSS_bytes": 63375785984, "VmHWM_bytes": 63375785984, "Pss_bytes": 63376578560, "vram_used_bytes": 192266240, "vram_total_bytes": 4294967296, "gtt_used_bytes": 61058904064, 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193273528320} +{"t_s": 171.35, "VmRSS_bytes": 103805657088, "VmHWM_bytes": 112649281536, "Pss_bytes": 103803249664, "vram_used_bytes": 206614528, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90338648064, "gtt_total_bytes": 193273528320} +{"t_s": 172.51, "VmRSS_bytes": 92768882688, "VmHWM_bytes": 112649281536, "Pss_bytes": 85967808512, "vram_used_bytes": 194375680, "vram_total_bytes": 4294967296, "gtt_used_bytes": 204288000, "gtt_total_bytes": 193273528320} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-65536-r2-memory-endpoint.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-65536-r2-memory-endpoint.json new file mode 100644 index 0000000000..88a8909495 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-65536-r2-memory-endpoint.json @@ -0,0 +1 @@ +{"schema_version": 1, "context_window": 73728, "context_fitted": false, "device": {"active_bytes": 89369987732, "cache_bytes": 0, "peak_bytes": 89525897124, "peak_scope": "since_start_or_health_reset"}} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-65536-r2-metrics.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-65536-r2-metrics.txt new file mode 100644 index 0000000000..bbcb6dfe1d --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-65536-r2-metrics.txt @@ -0,0 +1,220 @@ +# HELP tensorfold:requests_running Requests in prefill or decode. +# TYPE tensorfold:requests_running gauge +tensorfold:requests_running 0 +# HELP tensorfold:requests_waiting Requests queued or held until a lane is free. +# TYPE tensorfold:requests_waiting gauge +tensorfold:requests_waiting 0 +# HELP tensorfold:generation_tokens_running Generated tokens held by live streams. +# TYPE tensorfold:generation_tokens_running gauge +tensorfold:generation_tokens_running 0 +# HELP tensorfold:prompt_tokens_total Prompt tokens of finished requests. +# TYPE tensorfold:prompt_tokens_total counter +tensorfold:prompt_tokens_total 65792 +# HELP tensorfold:generation_tokens_total Generated tokens of finished requests. +# TYPE tensorfold:generation_tokens_total counter +tensorfold:generation_tokens_total 2 +# HELP tensorfold:kv_cache_usage_ratio Tokens in a stream cache divided by that stream's context window. +# TYPE tensorfold:kv_cache_usage_ratio gauge +tensorfold:kv_cache_usage_ratio{pool="0"} 0 +# HELP tensorfold:mtp_drafted_total Draft tokens verified on finished requests. +# TYPE tensorfold:mtp_drafted_total counter +tensorfold:mtp_drafted_total 0 +# HELP tensorfold:mtp_accepted_total Draft tokens kept on finished requests. +# TYPE tensorfold:mtp_accepted_total counter +tensorfold:mtp_accepted_total 0 +# HELP tensorfold:request_latency_seconds Seconds from arrival to the reply leaving. +# TYPE tensorfold:request_latency_seconds histogram +tensorfold:request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:request_latency_seconds_bucket{le="0.5"} 1 +tensorfold:request_latency_seconds_bucket{le="1"} 1 +tensorfold:request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:request_latency_seconds_bucket{le="5"} 1 +tensorfold:request_latency_seconds_bucket{le="10"} 1 +tensorfold:request_latency_seconds_bucket{le="30"} 1 +tensorfold:request_latency_seconds_bucket{le="60"} 1 +tensorfold:request_latency_seconds_bucket{le="120"} 1 +tensorfold:request_latency_seconds_bucket{le="300"} 2 +tensorfold:request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:request_latency_seconds_sum 132.513997 +tensorfold:request_latency_seconds_count 2 +# HELP tensorfold:time_to_first_token_seconds Seconds from arrival to the first generated token. +# TYPE tensorfold:time_to_first_token_seconds histogram +tensorfold:time_to_first_token_seconds_bucket{le="0.01"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.05"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.25"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="1"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="2.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="10"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="30"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="60"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="120"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="300"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="+Inf"} 2 +tensorfold:time_to_first_token_seconds_sum 132.513498 +tensorfold:time_to_first_token_seconds_count 2 +# HELP tensorfold:request_decode_seconds Seconds a finished request spent decoding. Its sum over generation_tokens_total is the decode rate. +# TYPE tensorfold:request_decode_seconds histogram +tensorfold:request_decode_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_seconds_bucket{le="1"} 2 +tensorfold:request_decode_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_seconds_bucket{le="5"} 2 +tensorfold:request_decode_seconds_bucket{le="10"} 2 +tensorfold:request_decode_seconds_bucket{le="30"} 2 +tensorfold:request_decode_seconds_bucket{le="60"} 2 +tensorfold:request_decode_seconds_bucket{le="120"} 2 +tensorfold:request_decode_seconds_bucket{le="300"} 2 +tensorfold:request_decode_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_seconds_sum 0.000499 +tensorfold:request_decode_seconds_count 2 +# HELP tensorfold:request_time_per_output_token_seconds Seconds from the first generated token to the last, divided by the tokens less one. +# TYPE tensorfold:request_time_per_output_token_seconds histogram +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.005"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.01"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.015"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.02"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.03"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.04"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.05"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.15"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.2"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.3"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.5"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="+Inf"} 0 +tensorfold:request_time_per_output_token_seconds_sum 0 +tensorfold:request_time_per_output_token_seconds_count 0 +# HELP tensorfold:decode_rounds_total Decode rounds used by finished requests. +# TYPE tensorfold:decode_rounds_total counter +tensorfold:decode_rounds_total 0 +# HELP tensorfold:request_prefill_seconds Seconds a finished request's prompt pass took. +# TYPE tensorfold:request_prefill_seconds histogram +tensorfold:request_prefill_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="1"} 1 +tensorfold:request_prefill_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_seconds_bucket{le="60"} 1 +tensorfold:request_prefill_seconds_bucket{le="120"} 1 +tensorfold:request_prefill_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_seconds_sum 132.512586 +tensorfold:request_prefill_seconds_count 2 +# HELP tensorfold:process_resident_bytes Current resident set (VmRSS); device memory is not in it, so it is not a physical footprint (Linux). +# TYPE tensorfold:process_resident_bytes gauge +tensorfold:process_resident_bytes 102473277440 +# HELP tensorfold:process_resident_anon_bytes Current resident anonymous memory (RssAnon): heap, stacks and private maps (Linux). +# TYPE tensorfold:process_resident_anon_bytes gauge +tensorfold:process_resident_anon_bytes 32370434048 +# HELP tensorfold:process_resident_file_bytes Current resident file-backed memory (RssFile): the binary, libraries and mapped files (Linux). +# TYPE tensorfold:process_resident_file_bytes gauge +tensorfold:process_resident_file_bytes 69968580608 +# HELP tensorfold:process_resident_shmem_bytes Current resident shared memory (RssShmem): System V shared memory, tmpfs maps and shared anonymous maps (Linux). +# TYPE tensorfold:process_resident_shmem_bytes gauge +tensorfold:process_resident_shmem_bytes 134262784 +# HELP tensorfold:process_resident_peak_bytes Kernel lifetime peak resident set (VmHWM); never reset by health (Linux). +# TYPE tensorfold:process_resident_peak_bytes gauge +tensorfold:process_resident_peak_bytes 111409418240 +# HELP tensorfold:device_memory_bytes Device memory the engine holds now: weights, caches and live streams; only where the backend counts it (CUDA). +# TYPE tensorfold:device_memory_bytes gauge +tensorfold:device_memory_bytes 89369987732 +# HELP tensorfold:device_memory_peak_bytes The most device memory the engine has held since start or the last /health?reset_peak=1. +# TYPE tensorfold:device_memory_peak_bytes gauge +tensorfold:device_memory_peak_bytes 89525897124 +# HELP tensorfold:pinned_memory_bytes Pinned host memory the engine holds now: staging buffers and windows; only where the backend counts it (CUDA). +# TYPE tensorfold:pinned_memory_bytes gauge +tensorfold:pinned_memory_bytes 0 +# HELP tensorfold:num_requests_running Requests in prefill or decode. A mirror of tensorfold:requests_running. +# TYPE tensorfold:num_requests_running gauge +tensorfold:num_requests_running 0 +# HELP tensorfold:num_requests_waiting Requests queued or held until a lane is free. A mirror of tensorfold:requests_waiting. +# TYPE tensorfold:num_requests_waiting gauge +tensorfold:num_requests_waiting 0 +# HELP tensorfold:kv_cache_usage_perc A stream's cache occupancy under vLLM's name; same streams and ratios as tensorfold:kv_cache_usage_ratio. +# TYPE tensorfold:kv_cache_usage_perc gauge +tensorfold:kv_cache_usage_perc{stream="0"} 0 +# HELP tensorfold:spec_decode_num_draft_tokens_total Draft tokens verified on finished requests, this server's single draft counter. +# TYPE tensorfold:spec_decode_num_draft_tokens_total counter +tensorfold:spec_decode_num_draft_tokens_total 0 +# HELP tensorfold:spec_decode_num_accepted_tokens_total Draft tokens kept on finished requests. +# TYPE tensorfold:spec_decode_num_accepted_tokens_total counter +tensorfold:spec_decode_num_accepted_tokens_total 0 +# HELP tensorfold:e2e_request_latency_seconds Seconds from arrival to the reply leaving, under vLLM's name. +# TYPE tensorfold:e2e_request_latency_seconds histogram +tensorfold:e2e_request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="1"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="10"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="30"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="60"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="120"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="300"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:e2e_request_latency_seconds_sum 132.513997 +tensorfold:e2e_request_latency_seconds_count 2 +# HELP tensorfold:request_decode_time_seconds Seconds a finished request spent decoding, under vLLM's name. +# TYPE tensorfold:request_decode_time_seconds histogram +tensorfold:request_decode_time_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="10"} 2 +tensorfold:request_decode_time_seconds_bucket{le="30"} 2 +tensorfold:request_decode_time_seconds_bucket{le="60"} 2 +tensorfold:request_decode_time_seconds_bucket{le="120"} 2 +tensorfold:request_decode_time_seconds_bucket{le="300"} 2 +tensorfold:request_decode_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_time_seconds_sum 0.000499 +tensorfold:request_decode_time_seconds_count 2 +# HELP tensorfold:request_prefill_time_seconds Seconds a finished request's prompt pass took, under vLLM's name. +# TYPE tensorfold:request_prefill_time_seconds histogram +tensorfold:request_prefill_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="1"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="60"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="120"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_time_seconds_sum 132.512586 +tensorfold:request_prefill_time_seconds_count 2 +# HELP tensorfold:client_disconnections_total Requests a client left before the reply left the server. +# TYPE tensorfold:client_disconnections_total counter +tensorfold:client_disconnections_total 0 +# HELP tensorfold:preemptions_total Requests that had to give a lane up to a later one. +# TYPE tensorfold:preemptions_total counter +tensorfold:preemptions_total 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-65536-r2-samples.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-65536-r2-samples.jsonl new file mode 100644 index 0000000000..5cf8f5a971 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-65536-r2-samples.jsonl @@ -0,0 +1,128 @@ +{"t_s": 0.0, "VmRSS_bytes": 74448896, "VmHWM_bytes": 74448896, "Pss_bytes": 72417280, "vram_used_bytes": 187682816, "vram_total_bytes": 4294967296, "gtt_used_bytes": 31657984, "gtt_total_bytes": 193273528320} +{"t_s": 1.03, "VmRSS_bytes": 10062249984, "VmHWM_bytes": 10062249984, "Pss_bytes": 10096796672, "vram_used_bytes": 188792832, "vram_total_bytes": 4294967296, "gtt_used_bytes": 6847524864, "gtt_total_bytes": 193273528320} +{"t_s": 2.09, "VmRSS_bytes": 18380771328, "VmHWM_bytes": 18380771328, "Pss_bytes": 18378552320, "vram_used_bytes": 189407232, "vram_total_bytes": 4294967296, "gtt_used_bytes": 16699944960, "gtt_total_bytes": 193273528320} +{"t_s": 3.16, "VmRSS_bytes": 27577942016, "VmHWM_bytes": 27577942016, "Pss_bytes": 27597349888, "vram_used_bytes": 189952000, "vram_total_bytes": 4294967296, "gtt_used_bytes": 24916586496, "gtt_total_bytes": 193273528320} +{"t_s": 4.25, "VmRSS_bytes": 36221517824, "VmHWM_bytes": 36221517824, "Pss_bytes": 36219298816, "vram_used_bytes": 190554112, "vram_total_bytes": 4294967296, "gtt_used_bytes": 34769006592, "gtt_total_bytes": 193273528320} +{"t_s": 5.36, "VmRSS_bytes": 45908320256, "VmHWM_bytes": 45908320256, "Pss_bytes": 45906101248, "vram_used_bytes": 191090688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 43941949440, "gtt_total_bytes": 193273528320} +{"t_s": 6.49, "VmRSS_bytes": 54018228224, "VmHWM_bytes": 54018228224, "Pss_bytes": 54016402432, "vram_used_bytes": 191635456, "vram_total_bytes": 4294967296, "gtt_used_bytes": 52794028032, "gtt_total_bytes": 193273528320} +{"t_s": 7.65, "VmRSS_bytes": 62170927104, "VmHWM_bytes": 62170927104, "Pss_bytes": 62170412032, "vram_used_bytes": 192274432, "vram_total_bytes": 4294967296, "gtt_used_bytes": 61058904064, "gtt_total_bytes": 193273528320} +{"t_s": 8.83, "VmRSS_bytes": 71904047104, "VmHWM_bytes": 71904047104, "Pss_bytes": 71901828096, "vram_used_bytes": 192929792, "vram_total_bytes": 4294967296, "gtt_used_bytes": 70913421312, "gtt_total_bytes": 193273528320} +{"t_s": 10.03, "VmRSS_bytes": 82500239360, "VmHWM_bytes": 82500239360, "Pss_bytes": 82498020352, "vram_used_bytes": 194322432, "vram_total_bytes": 4294967296, "gtt_used_bytes": 79937466368, "gtt_total_bytes": 193273528320} +{"t_s": 11.22, "VmRSS_bytes": 84610703360, "VmHWM_bytes": 84610703360, "Pss_bytes": 84483302400, "vram_used_bytes": 194359296, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 12.41, "VmRSS_bytes": 87985205248, "VmHWM_bytes": 88183189504, "Pss_bytes": 88165856256, "vram_used_bytes": 194359296, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 13.6, "VmRSS_bytes": 91776446464, "VmHWM_bytes": 91776446464, "Pss_bytes": 91733488640, "vram_used_bytes": 194359296, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 14.8, "VmRSS_bytes": 95355478016, "VmHWM_bytes": 95355478016, "Pss_bytes": 95235814400, "vram_used_bytes": 194359296, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 15.99, "VmRSS_bytes": 98891247616, "VmHWM_bytes": 98891247616, "Pss_bytes": 98787521536, "vram_used_bytes": 194359296, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 17.19, "VmRSS_bytes": 100887408640, "VmHWM_bytes": 100971704320, "Pss_bytes": 100760298496, "vram_used_bytes": 194371584, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 18.41, "VmRSS_bytes": 103474606080, "VmHWM_bytes": 103474606080, "Pss_bytes": 103488390144, "vram_used_bytes": 194371584, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 19.64, "VmRSS_bytes": 106448990208, "VmHWM_bytes": 106471407616, "Pss_bytes": 106521617408, "vram_used_bytes": 194375680, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 20.9, "VmRSS_bytes": 109273165824, "VmHWM_bytes": 109470064640, "Pss_bytes": 109270918144, "vram_used_bytes": 194375680, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 22.88, "VmRSS_bytes": 111183015936, "VmHWM_bytes": 111409418240, "Pss_bytes": 109551453184, "vram_used_bytes": 198844416, "vram_total_bytes": 4294967296, "gtt_used_bytes": 83922055168, "gtt_total_bytes": 193273528320} +{"t_s": 24.16, "VmRSS_bytes": 102789931008, "VmHWM_bytes": 111409418240, "Pss_bytes": 102787653632, "vram_used_bytes": 200900608, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90334552064, "gtt_total_bytes": 193273528320} +{"t_s": 25.43, "VmRSS_bytes": 102611210240, "VmHWM_bytes": 111409418240, "Pss_bytes": 102608932864, "vram_used_bytes": 200908800, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90338279424, "gtt_total_bytes": 193273528320} +{"t_s": 26.76, "VmRSS_bytes": 102614274048, "VmHWM_bytes": 111409418240, "Pss_bytes": 102612000768, "vram_used_bytes": 200908800, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90338648064, "gtt_total_bytes": 193273528320} +{"t_s": 28.02, "VmRSS_bytes": 102623358976, "VmHWM_bytes": 111409418240, "Pss_bytes": 102621077504, "vram_used_bytes": 200880128, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90495934464, "gtt_total_bytes": 193273528320} +{"t_s": 29.29, "VmRSS_bytes": 102623358976, "VmHWM_bytes": 111409418240, "Pss_bytes": 102621077504, "vram_used_bytes": 200880128, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90495934464, "gtt_total_bytes": 193273528320} +{"t_s": 30.58, "VmRSS_bytes": 102623358976, "VmHWM_bytes": 111409418240, "Pss_bytes": 102621077504, "vram_used_bytes": 200880128, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90495934464, "gtt_total_bytes": 193273528320} +{"t_s": 31.84, "VmRSS_bytes": 102623358976, "VmHWM_bytes": 111409418240, "Pss_bytes": 102621077504, "vram_used_bytes": 200880128, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90495934464, "gtt_total_bytes": 193273528320} +{"t_s": 33.11, "VmRSS_bytes": 102623358976, "VmHWM_bytes": 111409418240, "Pss_bytes": 102621077504, "vram_used_bytes": 200880128, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90495934464, "gtt_total_bytes": 193273528320} +{"t_s": 34.39, "VmRSS_bytes": 102627426304, "VmHWM_bytes": 111409418240, "Pss_bytes": 102625138688, "vram_used_bytes": 200880128, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90495934464, "gtt_total_bytes": 193273528320} +{"t_s": 35.66, "VmRSS_bytes": 102628110336, "VmHWM_bytes": 111409418240, "Pss_bytes": 102625826816, "vram_used_bytes": 200880128, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90495934464, "gtt_total_bytes": 193273528320} +{"t_s": 36.93, "VmRSS_bytes": 102628110336, "VmHWM_bytes": 111409418240, "Pss_bytes": 102625826816, "vram_used_bytes": 200880128, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90495934464, "gtt_total_bytes": 193273528320} +{"t_s": 38.18, "VmRSS_bytes": 102628110336, "VmHWM_bytes": 111409418240, "Pss_bytes": 102625826816, 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"VmRSS_bytes": 102523932672, "VmHWM_bytes": 111409418240, "Pss_bytes": 102521646080, "vram_used_bytes": 200880128, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90495934464, "gtt_total_bytes": 193273528320} +{"t_s": 134.81, "VmRSS_bytes": 102523932672, "VmHWM_bytes": 111409418240, "Pss_bytes": 102521646080, "vram_used_bytes": 200880128, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90495934464, "gtt_total_bytes": 193273528320} +{"t_s": 136.1, "VmRSS_bytes": 102523932672, "VmHWM_bytes": 111409418240, "Pss_bytes": 102521649152, "vram_used_bytes": 200880128, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90495934464, "gtt_total_bytes": 193273528320} +{"t_s": 137.35, "VmRSS_bytes": 102523932672, "VmHWM_bytes": 111409418240, "Pss_bytes": 102521649152, "vram_used_bytes": 200880128, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90495934464, "gtt_total_bytes": 193273528320} +{"t_s": 138.61, "VmRSS_bytes": 102523932672, "VmHWM_bytes": 111409418240, "Pss_bytes": 102521649152, "vram_used_bytes": 200880128, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90495934464, "gtt_total_bytes": 193273528320} +{"t_s": 139.87, "VmRSS_bytes": 102523932672, "VmHWM_bytes": 111409418240, "Pss_bytes": 102521649152, "vram_used_bytes": 200880128, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90495934464, "gtt_total_bytes": 193273528320} +{"t_s": 141.16, "VmRSS_bytes": 102523932672, "VmHWM_bytes": 111409418240, "Pss_bytes": 102521649152, "vram_used_bytes": 200880128, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90495934464, "gtt_total_bytes": 193273528320} +{"t_s": 142.44, "VmRSS_bytes": 102523932672, "VmHWM_bytes": 111409418240, "Pss_bytes": 102521915392, "vram_used_bytes": 200880128, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90495934464, "gtt_total_bytes": 193273528320} +{"t_s": 143.69, "VmRSS_bytes": 102523932672, "VmHWM_bytes": 111409418240, "Pss_bytes": 102521649152, "vram_used_bytes": 200880128, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90495934464, "gtt_total_bytes": 193273528320} +{"t_s": 144.96, "VmRSS_bytes": 102523932672, "VmHWM_bytes": 111409418240, "Pss_bytes": 102521649152, "vram_used_bytes": 200880128, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90495934464, "gtt_total_bytes": 193273528320} +{"t_s": 146.25, "VmRSS_bytes": 102523932672, "VmHWM_bytes": 111409418240, "Pss_bytes": 102521649152, "vram_used_bytes": 200880128, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90495934464, "gtt_total_bytes": 193273528320} +{"t_s": 147.52, "VmRSS_bytes": 102477271040, "VmHWM_bytes": 111409418240, "Pss_bytes": 102474987520, "vram_used_bytes": 200880128, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90495934464, "gtt_total_bytes": 193273528320} +{"t_s": 148.78, "VmRSS_bytes": 102477271040, "VmHWM_bytes": 111409418240, "Pss_bytes": 102474987520, "vram_used_bytes": 200880128, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90495934464, "gtt_total_bytes": 193273528320} +{"t_s": 150.04, "VmRSS_bytes": 102477271040, "VmHWM_bytes": 111409418240, "Pss_bytes": 102474987520, "vram_used_bytes": 200880128, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90495934464, "gtt_total_bytes": 193273528320} +{"t_s": 151.32, "VmRSS_bytes": 102477271040, "VmHWM_bytes": 111409418240, "Pss_bytes": 102474987520, "vram_used_bytes": 200880128, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90495934464, "gtt_total_bytes": 193273528320} +{"t_s": 152.6, "VmRSS_bytes": 102477271040, "VmHWM_bytes": 111409418240, "Pss_bytes": 102474987520, "vram_used_bytes": 200880128, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90495934464, "gtt_total_bytes": 193273528320} +{"t_s": 153.87, "VmRSS_bytes": 102477271040, "VmHWM_bytes": 111409418240, "Pss_bytes": 102474987520, "vram_used_bytes": 200880128, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90495934464, "gtt_total_bytes": 193273528320} +{"t_s": 155.13, "VmRSS_bytes": 102477271040, "VmHWM_bytes": 111409418240, "Pss_bytes": 102474987520, "vram_used_bytes": 200880128, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90495934464, "gtt_total_bytes": 193273528320} +{"t_s": 156.4, "VmRSS_bytes": 102477271040, "VmHWM_bytes": 111409418240, "Pss_bytes": 102474986496, "vram_used_bytes": 200880128, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90495934464, "gtt_total_bytes": 193273528320} +{"t_s": 157.68, "VmRSS_bytes": 102477271040, "VmHWM_bytes": 111409418240, "Pss_bytes": 102474987520, "vram_used_bytes": 200880128, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90495934464, "gtt_total_bytes": 193273528320} +{"t_s": 158.95, "VmRSS_bytes": 102477271040, "VmHWM_bytes": 111409418240, "Pss_bytes": 102474987520, "vram_used_bytes": 200880128, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90495934464, "gtt_total_bytes": 193273528320} +{"t_s": 160.22, "VmRSS_bytes": 102473089024, "VmHWM_bytes": 111409418240, "Pss_bytes": 102470804480, "vram_used_bytes": 200880128, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90338648064, "gtt_total_bytes": 193273528320} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-8192-r1-memory-endpoint.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-8192-r1-memory-endpoint.json new file mode 100644 index 0000000000..2bf64bb228 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-8192-r1-memory-endpoint.json @@ -0,0 +1 @@ +{"schema_version": 1, "context_window": 16384, "context_fitted": false, "device": {"active_bytes": 87740500628, "cache_bytes": 0, "peak_bytes": 87760619428, "peak_scope": "since_start_or_health_reset"}} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-8192-r1-metrics.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-8192-r1-metrics.txt new file mode 100644 index 0000000000..9a1d3c0c59 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-8192-r1-metrics.txt @@ -0,0 +1,220 @@ +# HELP tensorfold:requests_running Requests in prefill or decode. +# TYPE tensorfold:requests_running gauge +tensorfold:requests_running 0 +# HELP tensorfold:requests_waiting Requests queued or held until a lane is free. +# TYPE tensorfold:requests_waiting gauge +tensorfold:requests_waiting 0 +# HELP tensorfold:generation_tokens_running Generated tokens held by live streams. +# TYPE tensorfold:generation_tokens_running gauge +tensorfold:generation_tokens_running 0 +# HELP tensorfold:prompt_tokens_total Prompt tokens of finished requests. +# TYPE tensorfold:prompt_tokens_total counter +tensorfold:prompt_tokens_total 8448 +# HELP tensorfold:generation_tokens_total Generated tokens of finished requests. +# TYPE tensorfold:generation_tokens_total counter +tensorfold:generation_tokens_total 2 +# HELP tensorfold:kv_cache_usage_ratio Tokens in a stream cache divided by that stream's context window. +# TYPE tensorfold:kv_cache_usage_ratio gauge +tensorfold:kv_cache_usage_ratio{pool="0"} 0 +# HELP tensorfold:mtp_drafted_total Draft tokens verified on finished requests. +# TYPE tensorfold:mtp_drafted_total counter +tensorfold:mtp_drafted_total 0 +# HELP tensorfold:mtp_accepted_total Draft tokens kept on finished requests. +# TYPE tensorfold:mtp_accepted_total counter +tensorfold:mtp_accepted_total 0 +# HELP tensorfold:request_latency_seconds Seconds from arrival to the reply leaving. +# TYPE tensorfold:request_latency_seconds histogram +tensorfold:request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:request_latency_seconds_bucket{le="0.5"} 1 +tensorfold:request_latency_seconds_bucket{le="1"} 1 +tensorfold:request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:request_latency_seconds_bucket{le="5"} 1 +tensorfold:request_latency_seconds_bucket{le="10"} 1 +tensorfold:request_latency_seconds_bucket{le="30"} 2 +tensorfold:request_latency_seconds_bucket{le="60"} 2 +tensorfold:request_latency_seconds_bucket{le="120"} 2 +tensorfold:request_latency_seconds_bucket{le="300"} 2 +tensorfold:request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:request_latency_seconds_sum 15.086255 +tensorfold:request_latency_seconds_count 2 +# HELP tensorfold:time_to_first_token_seconds Seconds from arrival to the first generated token. +# TYPE tensorfold:time_to_first_token_seconds histogram +tensorfold:time_to_first_token_seconds_bucket{le="0.01"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.05"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.25"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="1"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="2.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="10"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="30"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="60"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="120"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="300"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="+Inf"} 2 +tensorfold:time_to_first_token_seconds_sum 14.983249 +tensorfold:time_to_first_token_seconds_count 2 +# HELP tensorfold:request_decode_seconds Seconds a finished request spent decoding. Its sum over generation_tokens_total is the decode rate. +# TYPE tensorfold:request_decode_seconds histogram +tensorfold:request_decode_seconds_bucket{le="0.01"} 1 +tensorfold:request_decode_seconds_bucket{le="0.05"} 1 +tensorfold:request_decode_seconds_bucket{le="0.1"} 1 +tensorfold:request_decode_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_seconds_bucket{le="1"} 2 +tensorfold:request_decode_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_seconds_bucket{le="5"} 2 +tensorfold:request_decode_seconds_bucket{le="10"} 2 +tensorfold:request_decode_seconds_bucket{le="30"} 2 +tensorfold:request_decode_seconds_bucket{le="60"} 2 +tensorfold:request_decode_seconds_bucket{le="120"} 2 +tensorfold:request_decode_seconds_bucket{le="300"} 2 +tensorfold:request_decode_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_seconds_sum 0.103006 +tensorfold:request_decode_seconds_count 2 +# HELP tensorfold:request_time_per_output_token_seconds Seconds from the first generated token to the last, divided by the tokens less one. +# TYPE tensorfold:request_time_per_output_token_seconds histogram +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.005"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.01"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.015"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.02"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.03"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.04"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.05"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.15"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.2"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.3"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.5"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="+Inf"} 0 +tensorfold:request_time_per_output_token_seconds_sum 0 +tensorfold:request_time_per_output_token_seconds_count 0 +# HELP tensorfold:decode_rounds_total Decode rounds used by finished requests. +# TYPE tensorfold:decode_rounds_total counter +tensorfold:decode_rounds_total 0 +# HELP tensorfold:request_prefill_seconds Seconds a finished request's prompt pass took. +# TYPE tensorfold:request_prefill_seconds histogram +tensorfold:request_prefill_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="1"} 1 +tensorfold:request_prefill_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_seconds_bucket{le="30"} 2 +tensorfold:request_prefill_seconds_bucket{le="60"} 2 +tensorfold:request_prefill_seconds_bucket{le="120"} 2 +tensorfold:request_prefill_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_seconds_sum 14.980829 +tensorfold:request_prefill_seconds_count 2 +# HELP tensorfold:process_resident_bytes Current resident set (VmRSS); device memory is not in it, so it is not a physical footprint (Linux). +# TYPE tensorfold:process_resident_bytes gauge +tensorfold:process_resident_bytes 104799797248 +# HELP tensorfold:process_resident_anon_bytes Current resident anonymous memory (RssAnon): heap, stacks and private maps (Linux). +# TYPE tensorfold:process_resident_anon_bytes gauge +tensorfold:process_resident_anon_bytes 32366706688 +# HELP tensorfold:process_resident_file_bytes Current resident file-backed memory (RssFile): the binary, libraries and mapped files (Linux). +# TYPE tensorfold:process_resident_file_bytes gauge +tensorfold:process_resident_file_bytes 72298827776 +# HELP tensorfold:process_resident_shmem_bytes Current resident shared memory (RssShmem): System V shared memory, tmpfs maps and shared anonymous maps (Linux). +# TYPE tensorfold:process_resident_shmem_bytes gauge +tensorfold:process_resident_shmem_bytes 134262784 +# HELP tensorfold:process_resident_peak_bytes Kernel lifetime peak resident set (VmHWM); never reset by health (Linux). +# TYPE tensorfold:process_resident_peak_bytes gauge +tensorfold:process_resident_peak_bytes 112803840000 +# HELP tensorfold:device_memory_bytes Device memory the engine holds now: weights, caches and live streams; only where the backend counts it (CUDA). +# TYPE tensorfold:device_memory_bytes gauge +tensorfold:device_memory_bytes 87740500628 +# HELP tensorfold:device_memory_peak_bytes The most device memory the engine has held since start or the last /health?reset_peak=1. +# TYPE tensorfold:device_memory_peak_bytes gauge +tensorfold:device_memory_peak_bytes 87760619428 +# HELP tensorfold:pinned_memory_bytes Pinned host memory the engine holds now: staging buffers and windows; only where the backend counts it (CUDA). +# TYPE tensorfold:pinned_memory_bytes gauge +tensorfold:pinned_memory_bytes 0 +# HELP tensorfold:num_requests_running Requests in prefill or decode. A mirror of tensorfold:requests_running. +# TYPE tensorfold:num_requests_running gauge +tensorfold:num_requests_running 0 +# HELP tensorfold:num_requests_waiting Requests queued or held until a lane is free. A mirror of tensorfold:requests_waiting. +# TYPE tensorfold:num_requests_waiting gauge +tensorfold:num_requests_waiting 0 +# HELP tensorfold:kv_cache_usage_perc A stream's cache occupancy under vLLM's name; same streams and ratios as tensorfold:kv_cache_usage_ratio. +# TYPE tensorfold:kv_cache_usage_perc gauge +tensorfold:kv_cache_usage_perc{stream="0"} 0 +# HELP tensorfold:spec_decode_num_draft_tokens_total Draft tokens verified on finished requests, this server's single draft counter. +# TYPE tensorfold:spec_decode_num_draft_tokens_total counter +tensorfold:spec_decode_num_draft_tokens_total 0 +# HELP tensorfold:spec_decode_num_accepted_tokens_total Draft tokens kept on finished requests. +# TYPE tensorfold:spec_decode_num_accepted_tokens_total counter +tensorfold:spec_decode_num_accepted_tokens_total 0 +# HELP tensorfold:e2e_request_latency_seconds Seconds from arrival to the reply leaving, under vLLM's name. +# TYPE tensorfold:e2e_request_latency_seconds histogram +tensorfold:e2e_request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="1"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="10"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="30"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="60"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="120"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="300"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:e2e_request_latency_seconds_sum 15.086255 +tensorfold:e2e_request_latency_seconds_count 2 +# HELP tensorfold:request_decode_time_seconds Seconds a finished request spent decoding, under vLLM's name. +# TYPE tensorfold:request_decode_time_seconds histogram +tensorfold:request_decode_time_seconds_bucket{le="0.01"} 1 +tensorfold:request_decode_time_seconds_bucket{le="0.05"} 1 +tensorfold:request_decode_time_seconds_bucket{le="0.1"} 1 +tensorfold:request_decode_time_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="10"} 2 +tensorfold:request_decode_time_seconds_bucket{le="30"} 2 +tensorfold:request_decode_time_seconds_bucket{le="60"} 2 +tensorfold:request_decode_time_seconds_bucket{le="120"} 2 +tensorfold:request_decode_time_seconds_bucket{le="300"} 2 +tensorfold:request_decode_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_time_seconds_sum 0.103006 +tensorfold:request_decode_time_seconds_count 2 +# HELP tensorfold:request_prefill_time_seconds Seconds a finished request's prompt pass took, under vLLM's name. +# TYPE tensorfold:request_prefill_time_seconds histogram +tensorfold:request_prefill_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="1"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="30"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="60"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="120"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_time_seconds_sum 14.980829 +tensorfold:request_prefill_time_seconds_count 2 +# HELP tensorfold:client_disconnections_total Requests a client left before the reply left the server. +# TYPE tensorfold:client_disconnections_total counter +tensorfold:client_disconnections_total 0 +# HELP tensorfold:preemptions_total Requests that had to give a lane up to a later one. +# TYPE tensorfold:preemptions_total counter +tensorfold:preemptions_total 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-8192-r1-samples.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-8192-r1-samples.jsonl new file mode 100644 index 0000000000..b6920259d2 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-8192-r1-samples.jsonl @@ -0,0 +1,35 @@ +{"t_s": 0.0, "VmRSS_bytes": 64557056, "VmHWM_bytes": 64557056, "Pss_bytes": 62179328, "vram_used_bytes": 187682816, "vram_total_bytes": 4294967296, "gtt_used_bytes": 31657984, "gtt_total_bytes": 193273528320} +{"t_s": 1.04, "VmRSS_bytes": 9747177472, "VmHWM_bytes": 9747177472, "Pss_bytes": 9776394240, "vram_used_bytes": 188801024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 6847524864, "gtt_total_bytes": 193273528320} +{"t_s": 2.09, "VmRSS_bytes": 18353074176, "VmHWM_bytes": 18353074176, "Pss_bytes": 18357518336, "vram_used_bytes": 189419520, "vram_total_bytes": 4294967296, "gtt_used_bytes": 16676876288, "gtt_total_bytes": 193273528320} +{"t_s": 3.19, "VmRSS_bytes": 26493661184, "VmHWM_bytes": 26493661184, "Pss_bytes": 26491153408, "vram_used_bytes": 190070784, "vram_total_bytes": 4294967296, "gtt_used_bytes": 24910295040, "gtt_total_bytes": 193273528320} +{"t_s": 4.3, "VmRSS_bytes": 36178997248, "VmHWM_bytes": 36178997248, "Pss_bytes": 36176494592, "vram_used_bytes": 190607360, "vram_total_bytes": 4294967296, "gtt_used_bytes": 34083237888, "gtt_total_bytes": 193273528320} +{"t_s": 5.45, "VmRSS_bytes": 44338298880, "VmHWM_bytes": 44338298880, "Pss_bytes": 44343136256, "vram_used_bytes": 191287296, "vram_total_bytes": 4294967296, "gtt_used_bytes": 42989842432, "gtt_total_bytes": 193273528320} +{"t_s": 6.62, "VmRSS_bytes": 54068588544, "VmHWM_bytes": 54068588544, "Pss_bytes": 54066085888, "vram_used_bytes": 191967232, "vram_total_bytes": 4294967296, "gtt_used_bytes": 52844359680, "gtt_total_bytes": 193273528320} +{"t_s": 7.83, "VmRSS_bytes": 63802875904, "VmHWM_bytes": 63802875904, "Pss_bytes": 63800373248, "vram_used_bytes": 192655360, "vram_total_bytes": 4294967296, "gtt_used_bytes": 62703071232, "gtt_total_bytes": 193273528320} +{"t_s": 9.04, "VmRSS_bytes": 73532227584, "VmHWM_bytes": 73532227584, "Pss_bytes": 73529724928, "vram_used_bytes": 193343488, "vram_total_bytes": 4294967296, "gtt_used_bytes": 72557588480, "gtt_total_bytes": 193273528320} +{"t_s": 10.27, "VmRSS_bytes": 81399226368, "VmHWM_bytes": 82507984896, "Pss_bytes": 81638658048, "vram_used_bytes": 195043328, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 11.5, "VmRSS_bytes": 85886689280, "VmHWM_bytes": 85886689280, "Pss_bytes": 85737574400, "vram_used_bytes": 195043328, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 12.74, "VmRSS_bytes": 90135191552, "VmHWM_bytes": 90135191552, "Pss_bytes": 89989156864, "vram_used_bytes": 195043328, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 13.97, "VmRSS_bytes": 94055804928, "VmHWM_bytes": 94189969408, "Pss_bytes": 94039302144, "vram_used_bytes": 195043328, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 15.2, "VmRSS_bytes": 98436509696, "VmHWM_bytes": 98436509696, "Pss_bytes": 98370781184, "vram_used_bytes": 195043328, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 16.44, "VmRSS_bytes": 102494269440, "VmHWM_bytes": 102692970496, "Pss_bytes": 102491836416, "vram_used_bytes": 195043328, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 17.67, "VmRSS_bytes": 106849980416, "VmHWM_bytes": 106942980096, "Pss_bytes": 106742722560, "vram_used_bytes": 195043328, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 18.93, "VmRSS_bytes": 110337183744, "VmHWM_bytes": 110403522560, "Pss_bytes": 110424342528, "vram_used_bytes": 195043328, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 20.19, "VmRSS_bytes": 112314363904, "VmHWM_bytes": 112314363904, "Pss_bytes": 112354439168, "vram_used_bytes": 195047424, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 21.47, "VmRSS_bytes": 104783458304, "VmHWM_bytes": 112803840000, "Pss_bytes": 104780908544, "vram_used_bytes": 200687616, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88703959040, "gtt_total_bytes": 193273528320} +{"t_s": 22.75, "VmRSS_bytes": 104789766144, "VmHWM_bytes": 112803840000, "Pss_bytes": 104787216384, "vram_used_bytes": 200699904, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88708423680, "gtt_total_bytes": 193273528320} +{"t_s": 24.07, "VmRSS_bytes": 104794361856, "VmHWM_bytes": 112803840000, "Pss_bytes": 104791808000, "vram_used_bytes": 200699904, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88709160960, "gtt_total_bytes": 193273528320} +{"t_s": 25.31, "VmRSS_bytes": 104794992640, "VmHWM_bytes": 112803840000, "Pss_bytes": 104792612864, "vram_used_bytes": 200699904, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88709160960, "gtt_total_bytes": 193273528320} +{"t_s": 26.58, "VmRSS_bytes": 104799686656, "VmHWM_bytes": 112803840000, "Pss_bytes": 104797126656, "vram_used_bytes": 200695808, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88730132480, "gtt_total_bytes": 193273528320} +{"t_s": 27.84, "VmRSS_bytes": 104799686656, "VmHWM_bytes": 112803840000, "Pss_bytes": 104797126656, "vram_used_bytes": 200695808, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88730132480, "gtt_total_bytes": 193273528320} +{"t_s": 29.1, "VmRSS_bytes": 104799686656, "VmHWM_bytes": 112803840000, "Pss_bytes": 104797126656, "vram_used_bytes": 200695808, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88730132480, "gtt_total_bytes": 193273528320} +{"t_s": 30.38, "VmRSS_bytes": 104799686656, "VmHWM_bytes": 112803840000, "Pss_bytes": 104797126656, "vram_used_bytes": 200695808, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88730132480, "gtt_total_bytes": 193273528320} +{"t_s": 31.64, "VmRSS_bytes": 104799686656, "VmHWM_bytes": 112803840000, "Pss_bytes": 104797126656, "vram_used_bytes": 200695808, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88730132480, "gtt_total_bytes": 193273528320} +{"t_s": 32.88, "VmRSS_bytes": 104800505856, "VmHWM_bytes": 112803840000, "Pss_bytes": 104797945856, "vram_used_bytes": 200695808, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88730132480, "gtt_total_bytes": 193273528320} +{"t_s": 34.12, "VmRSS_bytes": 104800505856, "VmHWM_bytes": 112803840000, "Pss_bytes": 104797945856, "vram_used_bytes": 200695808, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88730132480, "gtt_total_bytes": 193273528320} +{"t_s": 35.37, "VmRSS_bytes": 104800505856, "VmHWM_bytes": 112803840000, "Pss_bytes": 104797945856, "vram_used_bytes": 200695808, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88730132480, "gtt_total_bytes": 193273528320} +{"t_s": 36.63, "VmRSS_bytes": 104800505856, "VmHWM_bytes": 112803840000, "Pss_bytes": 104797945856, "vram_used_bytes": 200695808, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88730132480, "gtt_total_bytes": 193273528320} +{"t_s": 37.89, "VmRSS_bytes": 104800505856, "VmHWM_bytes": 112803840000, "Pss_bytes": 104797945856, "vram_used_bytes": 200695808, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88730132480, "gtt_total_bytes": 193273528320} +{"t_s": 39.16, "VmRSS_bytes": 104800505856, "VmHWM_bytes": 112803840000, "Pss_bytes": 104797945856, "vram_used_bytes": 200695808, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88730132480, "gtt_total_bytes": 193273528320} +{"t_s": 40.41, "VmRSS_bytes": 104800505856, "VmHWM_bytes": 112803840000, "Pss_bytes": 104797446144, "vram_used_bytes": 200695808, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88709160960, "gtt_total_bytes": 193273528320} +{"t_s": 41.53, "VmRSS_bytes": 41489289216, "VmHWM_bytes": 112803840000, "Pss_bytes": 38299533312, "vram_used_bytes": 194977792, "vram_total_bytes": 4294967296, "gtt_used_bytes": 204288000, "gtt_total_bytes": 193273528320} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-8192-r2-memory-endpoint.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-8192-r2-memory-endpoint.json new file mode 100644 index 0000000000..2bf64bb228 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-8192-r2-memory-endpoint.json @@ -0,0 +1 @@ +{"schema_version": 1, "context_window": 16384, "context_fitted": false, "device": {"active_bytes": 87740500628, "cache_bytes": 0, "peak_bytes": 87760619428, "peak_scope": "since_start_or_health_reset"}} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-8192-r2-metrics.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-8192-r2-metrics.txt new file mode 100644 index 0000000000..466778da77 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-8192-r2-metrics.txt @@ -0,0 +1,220 @@ +# HELP tensorfold:requests_running Requests in prefill or decode. +# TYPE tensorfold:requests_running gauge +tensorfold:requests_running 0 +# HELP tensorfold:requests_waiting Requests queued or held until a lane is free. +# TYPE tensorfold:requests_waiting gauge +tensorfold:requests_waiting 0 +# HELP tensorfold:generation_tokens_running Generated tokens held by live streams. +# TYPE tensorfold:generation_tokens_running gauge +tensorfold:generation_tokens_running 0 +# HELP tensorfold:prompt_tokens_total Prompt tokens of finished requests. +# TYPE tensorfold:prompt_tokens_total counter +tensorfold:prompt_tokens_total 8448 +# HELP tensorfold:generation_tokens_total Generated tokens of finished requests. +# TYPE tensorfold:generation_tokens_total counter +tensorfold:generation_tokens_total 2 +# HELP tensorfold:kv_cache_usage_ratio Tokens in a stream cache divided by that stream's context window. +# TYPE tensorfold:kv_cache_usage_ratio gauge +tensorfold:kv_cache_usage_ratio{pool="0"} 0 +# HELP tensorfold:mtp_drafted_total Draft tokens verified on finished requests. +# TYPE tensorfold:mtp_drafted_total counter +tensorfold:mtp_drafted_total 0 +# HELP tensorfold:mtp_accepted_total Draft tokens kept on finished requests. +# TYPE tensorfold:mtp_accepted_total counter +tensorfold:mtp_accepted_total 0 +# HELP tensorfold:request_latency_seconds Seconds from arrival to the reply leaving. +# TYPE tensorfold:request_latency_seconds histogram +tensorfold:request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:request_latency_seconds_bucket{le="0.5"} 1 +tensorfold:request_latency_seconds_bucket{le="1"} 1 +tensorfold:request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:request_latency_seconds_bucket{le="5"} 1 +tensorfold:request_latency_seconds_bucket{le="10"} 1 +tensorfold:request_latency_seconds_bucket{le="30"} 2 +tensorfold:request_latency_seconds_bucket{le="60"} 2 +tensorfold:request_latency_seconds_bucket{le="120"} 2 +tensorfold:request_latency_seconds_bucket{le="300"} 2 +tensorfold:request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:request_latency_seconds_sum 15.139886 +tensorfold:request_latency_seconds_count 2 +# HELP tensorfold:time_to_first_token_seconds Seconds from arrival to the first generated token. +# TYPE tensorfold:time_to_first_token_seconds histogram +tensorfold:time_to_first_token_seconds_bucket{le="0.01"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.05"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.25"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="1"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="2.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="10"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="30"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="60"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="120"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="300"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="+Inf"} 2 +tensorfold:time_to_first_token_seconds_sum 15.139669 +tensorfold:time_to_first_token_seconds_count 2 +# HELP tensorfold:request_decode_seconds Seconds a finished request spent decoding. Its sum over generation_tokens_total is the decode rate. +# TYPE tensorfold:request_decode_seconds histogram +tensorfold:request_decode_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_seconds_bucket{le="1"} 2 +tensorfold:request_decode_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_seconds_bucket{le="5"} 2 +tensorfold:request_decode_seconds_bucket{le="10"} 2 +tensorfold:request_decode_seconds_bucket{le="30"} 2 +tensorfold:request_decode_seconds_bucket{le="60"} 2 +tensorfold:request_decode_seconds_bucket{le="120"} 2 +tensorfold:request_decode_seconds_bucket{le="300"} 2 +tensorfold:request_decode_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_seconds_sum 0.000216 +tensorfold:request_decode_seconds_count 2 +# HELP tensorfold:request_time_per_output_token_seconds Seconds from the first generated token to the last, divided by the tokens less one. +# TYPE tensorfold:request_time_per_output_token_seconds histogram +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.005"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.01"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.015"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.02"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.03"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.04"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.05"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.15"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.2"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.3"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.5"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="+Inf"} 0 +tensorfold:request_time_per_output_token_seconds_sum 0 +tensorfold:request_time_per_output_token_seconds_count 0 +# HELP tensorfold:decode_rounds_total Decode rounds used by finished requests. +# TYPE tensorfold:decode_rounds_total counter +tensorfold:decode_rounds_total 0 +# HELP tensorfold:request_prefill_seconds Seconds a finished request's prompt pass took. +# TYPE tensorfold:request_prefill_seconds histogram +tensorfold:request_prefill_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="1"} 1 +tensorfold:request_prefill_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_seconds_bucket{le="30"} 2 +tensorfold:request_prefill_seconds_bucket{le="60"} 2 +tensorfold:request_prefill_seconds_bucket{le="120"} 2 +tensorfold:request_prefill_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_seconds_sum 15.138666 +tensorfold:request_prefill_seconds_count 2 +# HELP tensorfold:process_resident_bytes Current resident set (VmRSS); device memory is not in it, so it is not a physical footprint (Linux). +# TYPE tensorfold:process_resident_bytes gauge +tensorfold:process_resident_bytes 104562606080 +# HELP tensorfold:process_resident_anon_bytes Current resident anonymous memory (RssAnon): heap, stacks and private maps (Linux). +# TYPE tensorfold:process_resident_anon_bytes gauge +tensorfold:process_resident_anon_bytes 32370335744 +# HELP tensorfold:process_resident_file_bytes Current resident file-backed memory (RssFile): the binary, libraries and mapped files (Linux). +# TYPE tensorfold:process_resident_file_bytes gauge +tensorfold:process_resident_file_bytes 72058007552 +# HELP tensorfold:process_resident_shmem_bytes Current resident shared memory (RssShmem): System V shared memory, tmpfs maps and shared anonymous maps (Linux). +# TYPE tensorfold:process_resident_shmem_bytes gauge +tensorfold:process_resident_shmem_bytes 134262784 +# HELP tensorfold:process_resident_peak_bytes Kernel lifetime peak resident set (VmHWM); never reset by health (Linux). +# TYPE tensorfold:process_resident_peak_bytes gauge +tensorfold:process_resident_peak_bytes 112731201536 +# HELP tensorfold:device_memory_bytes Device memory the engine holds now: weights, caches and live streams; only where the backend counts it (CUDA). +# TYPE tensorfold:device_memory_bytes gauge +tensorfold:device_memory_bytes 87740500628 +# HELP tensorfold:device_memory_peak_bytes The most device memory the engine has held since start or the last /health?reset_peak=1. +# TYPE tensorfold:device_memory_peak_bytes gauge +tensorfold:device_memory_peak_bytes 87760619428 +# HELP tensorfold:pinned_memory_bytes Pinned host memory the engine holds now: staging buffers and windows; only where the backend counts it (CUDA). +# TYPE tensorfold:pinned_memory_bytes gauge +tensorfold:pinned_memory_bytes 0 +# HELP tensorfold:num_requests_running Requests in prefill or decode. A mirror of tensorfold:requests_running. +# TYPE tensorfold:num_requests_running gauge +tensorfold:num_requests_running 0 +# HELP tensorfold:num_requests_waiting Requests queued or held until a lane is free. A mirror of tensorfold:requests_waiting. +# TYPE tensorfold:num_requests_waiting gauge +tensorfold:num_requests_waiting 0 +# HELP tensorfold:kv_cache_usage_perc A stream's cache occupancy under vLLM's name; same streams and ratios as tensorfold:kv_cache_usage_ratio. +# TYPE tensorfold:kv_cache_usage_perc gauge +tensorfold:kv_cache_usage_perc{stream="0"} 0 +# HELP tensorfold:spec_decode_num_draft_tokens_total Draft tokens verified on finished requests, this server's single draft counter. +# TYPE tensorfold:spec_decode_num_draft_tokens_total counter +tensorfold:spec_decode_num_draft_tokens_total 0 +# HELP tensorfold:spec_decode_num_accepted_tokens_total Draft tokens kept on finished requests. +# TYPE tensorfold:spec_decode_num_accepted_tokens_total counter +tensorfold:spec_decode_num_accepted_tokens_total 0 +# HELP tensorfold:e2e_request_latency_seconds Seconds from arrival to the reply leaving, under vLLM's name. +# TYPE tensorfold:e2e_request_latency_seconds histogram +tensorfold:e2e_request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="1"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="10"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="30"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="60"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="120"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="300"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:e2e_request_latency_seconds_sum 15.139886 +tensorfold:e2e_request_latency_seconds_count 2 +# HELP tensorfold:request_decode_time_seconds Seconds a finished request spent decoding, under vLLM's name. +# TYPE tensorfold:request_decode_time_seconds histogram +tensorfold:request_decode_time_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="10"} 2 +tensorfold:request_decode_time_seconds_bucket{le="30"} 2 +tensorfold:request_decode_time_seconds_bucket{le="60"} 2 +tensorfold:request_decode_time_seconds_bucket{le="120"} 2 +tensorfold:request_decode_time_seconds_bucket{le="300"} 2 +tensorfold:request_decode_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_time_seconds_sum 0.000216 +tensorfold:request_decode_time_seconds_count 2 +# HELP tensorfold:request_prefill_time_seconds Seconds a finished request's prompt pass took, under vLLM's name. +# TYPE tensorfold:request_prefill_time_seconds histogram +tensorfold:request_prefill_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="1"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="30"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="60"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="120"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_time_seconds_sum 15.138666 +tensorfold:request_prefill_time_seconds_count 2 +# HELP tensorfold:client_disconnections_total Requests a client left before the reply left the server. +# TYPE tensorfold:client_disconnections_total counter +tensorfold:client_disconnections_total 0 +# HELP tensorfold:preemptions_total Requests that had to give a lane up to a later one. +# TYPE tensorfold:preemptions_total counter +tensorfold:preemptions_total 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-8192-r2-samples.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-8192-r2-samples.jsonl new file mode 100644 index 0000000000..07dc8d9460 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/cold-new-8192-r2-samples.jsonl @@ -0,0 +1,36 @@ +{"t_s": 0.0, "VmRSS_bytes": 75173888, "VmHWM_bytes": 75173888, "Pss_bytes": 73015296, "vram_used_bytes": 187682816, "vram_total_bytes": 4294967296, "gtt_used_bytes": 31657984, "gtt_total_bytes": 193273528320} +{"t_s": 1.04, "VmRSS_bytes": 9592393728, "VmHWM_bytes": 9592393728, "Pss_bytes": 9622030336, "vram_used_bytes": 188792832, "vram_total_bytes": 4294967296, "gtt_used_bytes": 6841233408, "gtt_total_bytes": 193273528320} +{"t_s": 2.09, "VmRSS_bytes": 18339913728, "VmHWM_bytes": 18339913728, "Pss_bytes": 18337503232, "vram_used_bytes": 189349888, "vram_total_bytes": 4294967296, "gtt_used_bytes": 16014176256, "gtt_total_bytes": 193273528320} +{"t_s": 3.19, "VmRSS_bytes": 26494722048, "VmHWM_bytes": 26494722048, "Pss_bytes": 26492311552, "vram_used_bytes": 190058496, "vram_total_bytes": 4294967296, "gtt_used_bytes": 24910295040, "gtt_total_bytes": 193273528320} +{"t_s": 4.3, "VmRSS_bytes": 36180058112, "VmHWM_bytes": 36180058112, "Pss_bytes": 36177647616, "vram_used_bytes": 190595072, "vram_total_bytes": 4294967296, "gtt_used_bytes": 33135325184, "gtt_total_bytes": 193273528320} +{"t_s": 5.44, "VmRSS_bytes": 44292268032, "VmHWM_bytes": 44292268032, "Pss_bytes": 44289854464, "vram_used_bytes": 191172608, "vram_total_bytes": 4294967296, "gtt_used_bytes": 42297782272, "gtt_total_bytes": 193273528320} +{"t_s": 6.62, "VmRSS_bytes": 52446842880, "VmHWM_bytes": 52446842880, "Pss_bytes": 52444430336, "vram_used_bytes": 191840256, "vram_total_bytes": 4294967296, "gtt_used_bytes": 51200192512, "gtt_total_bytes": 193273528320} +{"t_s": 7.83, "VmRSS_bytes": 62178893824, "VmHWM_bytes": 62178893824, "Pss_bytes": 62177267712, "vram_used_bytes": 192516096, "vram_total_bytes": 4294967296, "gtt_used_bytes": 61058904064, "gtt_total_bytes": 193273528320} +{"t_s": 9.05, "VmRSS_bytes": 71910047744, "VmHWM_bytes": 71910047744, "Pss_bytes": 71907637248, "vram_used_bytes": 193208320, "vram_total_bytes": 4294967296, "gtt_used_bytes": 70913421312, "gtt_total_bytes": 193273528320} +{"t_s": 10.29, "VmRSS_bytes": 82244358144, "VmHWM_bytes": 82244358144, "Pss_bytes": 82380621824, "vram_used_bytes": 194994176, "vram_total_bytes": 4294967296, "gtt_used_bytes": 79933272064, "gtt_total_bytes": 193273528320} +{"t_s": 11.54, "VmRSS_bytes": 84862693376, "VmHWM_bytes": 84862693376, "Pss_bytes": 84917118976, "vram_used_bytes": 195031040, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 12.78, "VmRSS_bytes": 89025318912, "VmHWM_bytes": 89025318912, "Pss_bytes": 89069430784, "vram_used_bytes": 195031040, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 14.02, "VmRSS_bytes": 93268705280, "VmHWM_bytes": 93268705280, "Pss_bytes": 93319067648, "vram_used_bytes": 195031040, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 15.26, "VmRSS_bytes": 97372917760, "VmHWM_bytes": 97372917760, "Pss_bytes": 97350883328, "vram_used_bytes": 195031040, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 16.5, "VmRSS_bytes": 101415378944, "VmHWM_bytes": 101443117056, "Pss_bytes": 101398124544, "vram_used_bytes": 195031040, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 17.76, "VmRSS_bytes": 105290194944, "VmHWM_bytes": 105443954688, "Pss_bytes": 105268545536, "vram_used_bytes": 195031040, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 19.01, "VmRSS_bytes": 109170298880, "VmHWM_bytes": 109170298880, "Pss_bytes": 109050263552, "vram_used_bytes": 195031040, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 20.43, "VmRSS_bytes": 111917654016, "VmHWM_bytes": 111925907456, "Pss_bytes": 111783577600, "vram_used_bytes": 195031040, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 21.89, "VmRSS_bytes": 112369827840, "VmHWM_bytes": 112731201536, "Pss_bytes": 112144992256, "vram_used_bytes": 195063808, "vram_total_bytes": 4294967296, "gtt_used_bytes": 82246430720, "gtt_total_bytes": 193273528320} +{"t_s": 23.14, "VmRSS_bytes": 105160617984, "VmHWM_bytes": 112731201536, "Pss_bytes": 105159853056, "vram_used_bytes": 206110720, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88703561728, "gtt_total_bytes": 193273528320} +{"t_s": 24.4, "VmRSS_bytes": 105201172480, "VmHWM_bytes": 112731201536, "Pss_bytes": 105198904320, "vram_used_bytes": 206172160, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88707686400, "gtt_total_bytes": 193273528320} +{"t_s": 25.67, "VmRSS_bytes": 105205895168, "VmHWM_bytes": 112731201536, "Pss_bytes": 105203549184, "vram_used_bytes": 206176256, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88708792320, "gtt_total_bytes": 193273528320} +{"t_s": 26.92, "VmRSS_bytes": 105209577472, "VmHWM_bytes": 112731201536, "Pss_bytes": 105207231488, "vram_used_bytes": 206176256, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88709160960, "gtt_total_bytes": 193273528320} +{"t_s": 28.16, "VmRSS_bytes": 104563240960, "VmHWM_bytes": 112731201536, "Pss_bytes": 104560886784, "vram_used_bytes": 206172160, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88730132480, "gtt_total_bytes": 193273528320} +{"t_s": 29.41, "VmRSS_bytes": 104563240960, "VmHWM_bytes": 112731201536, "Pss_bytes": 104560886784, "vram_used_bytes": 206172160, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88730132480, "gtt_total_bytes": 193273528320} +{"t_s": 30.68, "VmRSS_bytes": 104563240960, "VmHWM_bytes": 112731201536, "Pss_bytes": 104560886784, "vram_used_bytes": 206172160, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88730132480, "gtt_total_bytes": 193273528320} +{"t_s": 31.93, "VmRSS_bytes": 104563240960, "VmHWM_bytes": 112731201536, "Pss_bytes": 104560886784, "vram_used_bytes": 206172160, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88730132480, "gtt_total_bytes": 193273528320} +{"t_s": 33.18, "VmRSS_bytes": 104563240960, "VmHWM_bytes": 112731201536, "Pss_bytes": 104560886784, "vram_used_bytes": 206172160, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88730132480, "gtt_total_bytes": 193273528320} +{"t_s": 34.44, "VmRSS_bytes": 104562634752, "VmHWM_bytes": 112731201536, "Pss_bytes": 104560280576, "vram_used_bytes": 206159872, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88730132480, "gtt_total_bytes": 193273528320} +{"t_s": 35.68, "VmRSS_bytes": 104563322880, "VmHWM_bytes": 112731201536, "Pss_bytes": 104560967680, "vram_used_bytes": 206159872, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88730132480, "gtt_total_bytes": 193273528320} +{"t_s": 36.93, "VmRSS_bytes": 104563322880, "VmHWM_bytes": 112731201536, "Pss_bytes": 104560967680, "vram_used_bytes": 206159872, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88730132480, "gtt_total_bytes": 193273528320} +{"t_s": 38.17, "VmRSS_bytes": 104563322880, "VmHWM_bytes": 112731201536, "Pss_bytes": 104560968704, "vram_used_bytes": 206159872, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88730132480, "gtt_total_bytes": 193273528320} +{"t_s": 39.41, "VmRSS_bytes": 104563322880, "VmHWM_bytes": 112731201536, "Pss_bytes": 104560968704, "vram_used_bytes": 206159872, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88730132480, "gtt_total_bytes": 193273528320} +{"t_s": 40.66, "VmRSS_bytes": 104563322880, "VmHWM_bytes": 112731201536, "Pss_bytes": 104560968704, "vram_used_bytes": 206159872, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88730132480, "gtt_total_bytes": 193273528320} +{"t_s": 41.92, "VmRSS_bytes": 104563322880, "VmHWM_bytes": 112731201536, "Pss_bytes": 104560968704, "vram_used_bytes": 206159872, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88730132480, "gtt_total_bytes": 193273528320} +{"t_s": 43.16, "VmRSS_bytes": 104484417536, "VmHWM_bytes": 112731201536, "Pss_bytes": 104482085888, "vram_used_bytes": 195338240, "vram_total_bytes": 4294967296, "gtt_used_bytes": 24793395200, "gtt_total_bytes": 193273528320} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-drafts-base-r1-memory-endpoint.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-drafts-base-r1-memory-endpoint.json new file mode 100644 index 0000000000..8bb426e488 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-drafts-base-r1-memory-endpoint.json @@ -0,0 +1 @@ +{"schema_version": 1, "context_window": 19456, "context_fitted": false, "device": {"active_bytes": 83373280704, "cache_bytes": 0, "peak_bytes": 83415047364, "peak_scope": "since_start_or_health_reset"}} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-drafts-base-r1-metrics.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-drafts-base-r1-metrics.txt new file mode 100644 index 0000000000..4585057f15 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-drafts-base-r1-metrics.txt @@ -0,0 +1,220 @@ +# HELP tensorfold:requests_running Requests in prefill or decode. +# TYPE tensorfold:requests_running gauge +tensorfold:requests_running 0 +# HELP tensorfold:requests_waiting Requests queued or held until a lane is free. +# TYPE tensorfold:requests_waiting gauge +tensorfold:requests_waiting 0 +# HELP tensorfold:generation_tokens_running Generated tokens held by live streams. +# TYPE tensorfold:generation_tokens_running gauge +tensorfold:generation_tokens_running 0 +# HELP tensorfold:prompt_tokens_total Prompt tokens of finished requests. +# TYPE tensorfold:prompt_tokens_total counter +tensorfold:prompt_tokens_total 114688 +# HELP tensorfold:generation_tokens_total Generated tokens of finished requests. +# TYPE tensorfold:generation_tokens_total counter +tensorfold:generation_tokens_total 3856 +# HELP tensorfold:kv_cache_usage_ratio Tokens in a stream cache divided by that stream's context window. +# TYPE tensorfold:kv_cache_usage_ratio gauge +tensorfold:kv_cache_usage_ratio{pool="0"} 0 +# HELP tensorfold:mtp_drafted_total Draft tokens verified on finished requests. +# TYPE tensorfold:mtp_drafted_total counter +tensorfold:mtp_drafted_total 2809 +# HELP tensorfold:mtp_accepted_total Draft tokens kept on finished requests. +# TYPE tensorfold:mtp_accepted_total counter +tensorfold:mtp_accepted_total 1912 +# HELP tensorfold:request_latency_seconds Seconds from arrival to the reply leaving. +# TYPE tensorfold:request_latency_seconds histogram +tensorfold:request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:request_latency_seconds_bucket{le="1"} 0 +tensorfold:request_latency_seconds_bucket{le="2.5"} 0 +tensorfold:request_latency_seconds_bucket{le="5"} 0 +tensorfold:request_latency_seconds_bucket{le="10"} 0 +tensorfold:request_latency_seconds_bucket{le="30"} 0 +tensorfold:request_latency_seconds_bucket{le="60"} 3 +tensorfold:request_latency_seconds_bucket{le="120"} 7 +tensorfold:request_latency_seconds_bucket{le="300"} 7 +tensorfold:request_latency_seconds_bucket{le="+Inf"} 7 +tensorfold:request_latency_seconds_sum 445.556285 +tensorfold:request_latency_seconds_count 7 +# HELP tensorfold:time_to_first_token_seconds Seconds from arrival to the first generated token. +# TYPE tensorfold:time_to_first_token_seconds histogram +tensorfold:time_to_first_token_seconds_bucket{le="0.01"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.05"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.25"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.5"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="2.5"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="5"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="10"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="30"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="60"} 6 +tensorfold:time_to_first_token_seconds_bucket{le="120"} 7 +tensorfold:time_to_first_token_seconds_bucket{le="300"} 7 +tensorfold:time_to_first_token_seconds_bucket{le="+Inf"} 7 +tensorfold:time_to_first_token_seconds_sum 343.168424 +tensorfold:time_to_first_token_seconds_count 7 +# HELP tensorfold:request_decode_seconds Seconds a finished request spent decoding. Its sum over generation_tokens_total is the decode rate. +# TYPE tensorfold:request_decode_seconds histogram +tensorfold:request_decode_seconds_bucket{le="0.01"} 0 +tensorfold:request_decode_seconds_bucket{le="0.05"} 0 +tensorfold:request_decode_seconds_bucket{le="0.1"} 0 +tensorfold:request_decode_seconds_bucket{le="0.25"} 0 +tensorfold:request_decode_seconds_bucket{le="0.5"} 1 +tensorfold:request_decode_seconds_bucket{le="1"} 1 +tensorfold:request_decode_seconds_bucket{le="2.5"} 1 +tensorfold:request_decode_seconds_bucket{le="5"} 1 +tensorfold:request_decode_seconds_bucket{le="10"} 4 +tensorfold:request_decode_seconds_bucket{le="30"} 7 +tensorfold:request_decode_seconds_bucket{le="60"} 7 +tensorfold:request_decode_seconds_bucket{le="120"} 7 +tensorfold:request_decode_seconds_bucket{le="300"} 7 +tensorfold:request_decode_seconds_bucket{le="+Inf"} 7 +tensorfold:request_decode_seconds_sum 102.387861 +tensorfold:request_decode_seconds_count 7 +# HELP tensorfold:request_time_per_output_token_seconds Seconds from the first generated token to the last, divided by the tokens less one. +# TYPE tensorfold:request_time_per_output_token_seconds histogram +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.005"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.01"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.015"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.02"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.025"} 3 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.03"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.04"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.05"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.075"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.1"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.15"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.2"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.3"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.5"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="1"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="+Inf"} 7 +tensorfold:request_time_per_output_token_seconds_sum 0.180349 +tensorfold:request_time_per_output_token_seconds_count 7 +# HELP tensorfold:decode_rounds_total Decode rounds used by finished requests. +# TYPE tensorfold:decode_rounds_total counter +tensorfold:decode_rounds_total 1937 +# HELP tensorfold:request_prefill_seconds Seconds a finished request's prompt pass took. +# TYPE tensorfold:request_prefill_seconds histogram +tensorfold:request_prefill_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.5"} 0 +tensorfold:request_prefill_seconds_bucket{le="1"} 0 +tensorfold:request_prefill_seconds_bucket{le="2.5"} 0 +tensorfold:request_prefill_seconds_bucket{le="5"} 0 +tensorfold:request_prefill_seconds_bucket{le="10"} 0 +tensorfold:request_prefill_seconds_bucket{le="30"} 0 +tensorfold:request_prefill_seconds_bucket{le="60"} 6 +tensorfold:request_prefill_seconds_bucket{le="120"} 7 +tensorfold:request_prefill_seconds_bucket{le="300"} 7 +tensorfold:request_prefill_seconds_bucket{le="+Inf"} 7 +tensorfold:request_prefill_seconds_sum 343.164485 +tensorfold:request_prefill_seconds_count 7 +# HELP tensorfold:process_resident_bytes Current resident set (VmRSS); device memory is not in it, so it is not a physical footprint (Linux). +# TYPE tensorfold:process_resident_bytes gauge +tensorfold:process_resident_bytes 84455440384 +# HELP tensorfold:process_resident_anon_bytes Current resident anonymous memory (RssAnon): heap, stacks and private maps (Linux). +# TYPE tensorfold:process_resident_anon_bytes gauge +tensorfold:process_resident_anon_bytes 315187200 +# HELP tensorfold:process_resident_file_bytes Current resident file-backed memory (RssFile): the binary, libraries and mapped files (Linux). +# TYPE tensorfold:process_resident_file_bytes gauge +tensorfold:process_resident_file_bytes 84028350464 +# HELP tensorfold:process_resident_shmem_bytes Current resident shared memory (RssShmem): System V shared memory, tmpfs maps and shared anonymous maps (Linux). +# TYPE tensorfold:process_resident_shmem_bytes gauge +tensorfold:process_resident_shmem_bytes 111902720 +# HELP tensorfold:process_resident_peak_bytes Kernel lifetime peak resident set (VmHWM); never reset by health (Linux). +# TYPE tensorfold:process_resident_peak_bytes gauge +tensorfold:process_resident_peak_bytes 84455440384 +# HELP tensorfold:device_memory_bytes Device memory the engine holds now: weights, caches and live streams; only where the backend counts it (CUDA). +# TYPE tensorfold:device_memory_bytes gauge +tensorfold:device_memory_bytes 83373280704 +# HELP tensorfold:device_memory_peak_bytes The most device memory the engine has held since start or the last /health?reset_peak=1. +# TYPE tensorfold:device_memory_peak_bytes gauge +tensorfold:device_memory_peak_bytes 83415047364 +# HELP tensorfold:pinned_memory_bytes Pinned host memory the engine holds now: staging buffers and windows; only where the backend counts it (CUDA). +# TYPE tensorfold:pinned_memory_bytes gauge +tensorfold:pinned_memory_bytes 0 +# HELP tensorfold:num_requests_running Requests in prefill or decode. A mirror of tensorfold:requests_running. +# TYPE tensorfold:num_requests_running gauge +tensorfold:num_requests_running 0 +# HELP tensorfold:num_requests_waiting Requests queued or held until a lane is free. A mirror of tensorfold:requests_waiting. +# TYPE tensorfold:num_requests_waiting gauge +tensorfold:num_requests_waiting 0 +# HELP tensorfold:kv_cache_usage_perc A stream's cache occupancy under vLLM's name; same streams and ratios as tensorfold:kv_cache_usage_ratio. +# TYPE tensorfold:kv_cache_usage_perc gauge +tensorfold:kv_cache_usage_perc{stream="0"} 0 +# HELP tensorfold:spec_decode_num_draft_tokens_total Draft tokens verified on finished requests, this server's single draft counter. +# TYPE tensorfold:spec_decode_num_draft_tokens_total counter +tensorfold:spec_decode_num_draft_tokens_total 2809 +# HELP tensorfold:spec_decode_num_accepted_tokens_total Draft tokens kept on finished requests. +# TYPE tensorfold:spec_decode_num_accepted_tokens_total counter +tensorfold:spec_decode_num_accepted_tokens_total 1912 +# HELP tensorfold:e2e_request_latency_seconds Seconds from arrival to the reply leaving, under vLLM's name. +# TYPE tensorfold:e2e_request_latency_seconds histogram +tensorfold:e2e_request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="2.5"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="5"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="10"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="30"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="60"} 3 +tensorfold:e2e_request_latency_seconds_bucket{le="120"} 7 +tensorfold:e2e_request_latency_seconds_bucket{le="300"} 7 +tensorfold:e2e_request_latency_seconds_bucket{le="+Inf"} 7 +tensorfold:e2e_request_latency_seconds_sum 445.556285 +tensorfold:e2e_request_latency_seconds_count 7 +# HELP tensorfold:request_decode_time_seconds Seconds a finished request spent decoding, under vLLM's name. +# TYPE tensorfold:request_decode_time_seconds histogram +tensorfold:request_decode_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.5"} 1 +tensorfold:request_decode_time_seconds_bucket{le="1"} 1 +tensorfold:request_decode_time_seconds_bucket{le="2.5"} 1 +tensorfold:request_decode_time_seconds_bucket{le="5"} 1 +tensorfold:request_decode_time_seconds_bucket{le="10"} 4 +tensorfold:request_decode_time_seconds_bucket{le="30"} 7 +tensorfold:request_decode_time_seconds_bucket{le="60"} 7 +tensorfold:request_decode_time_seconds_bucket{le="120"} 7 +tensorfold:request_decode_time_seconds_bucket{le="300"} 7 +tensorfold:request_decode_time_seconds_bucket{le="+Inf"} 7 +tensorfold:request_decode_time_seconds_sum 102.387861 +tensorfold:request_decode_time_seconds_count 7 +# HELP tensorfold:request_prefill_time_seconds Seconds a finished request's prompt pass took, under vLLM's name. +# TYPE tensorfold:request_prefill_time_seconds histogram +tensorfold:request_prefill_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.5"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="2.5"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="5"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="10"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="30"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="60"} 6 +tensorfold:request_prefill_time_seconds_bucket{le="120"} 7 +tensorfold:request_prefill_time_seconds_bucket{le="300"} 7 +tensorfold:request_prefill_time_seconds_bucket{le="+Inf"} 7 +tensorfold:request_prefill_time_seconds_sum 343.164485 +tensorfold:request_prefill_time_seconds_count 7 +# HELP tensorfold:client_disconnections_total Requests a client left before the reply left the server. +# TYPE tensorfold:client_disconnections_total counter +tensorfold:client_disconnections_total 0 +# HELP tensorfold:preemptions_total Requests that had to give a lane up to a later one. +# TYPE tensorfold:preemptions_total counter +tensorfold:preemptions_total 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-drafts-base-r1-samples.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-drafts-base-r1-samples.jsonl new file mode 100644 index 0000000000..03ac539774 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-drafts-base-r1-samples.jsonl @@ -0,0 +1,357 @@ +{"t_s": 0.0, "VmRSS_bytes": 34115584, "VmHWM_bytes": 34115584, "Pss_bytes": 32520192, "vram_used_bytes": 187670528, "vram_total_bytes": 4294967296, "gtt_used_bytes": 31657984, "gtt_total_bytes": 193273528320} +{"t_s": 1.03, "VmRSS_bytes": 8570310656, "VmHWM_bytes": 8570310656, "Pss_bytes": 8567951360, "vram_used_bytes": 188674048, "vram_total_bytes": 4294967296, "gtt_used_bytes": 6242934784, "gtt_total_bytes": 193273528320} +{"t_s": 2.09, "VmRSS_bytes": 13480742912, "VmHWM_bytes": 13480742912, "Pss_bytes": 13479301120, "vram_used_bytes": 189087744, "vram_total_bytes": 4294967296, "gtt_used_bytes": 11735375872, "gtt_total_bytes": 193273528320} +{"t_s": 3.16, "VmRSS_bytes": 19926040576, "VmHWM_bytes": 19926040576, "Pss_bytes": 19923681280, "vram_used_bytes": 189427712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 18247032832, "gtt_total_bytes": 193273528320} +{"t_s": 4.26, "VmRSS_bytes": 27249901568, "VmHWM_bytes": 27249901568, "Pss_bytes": 27293822976, "vram_used_bytes": 190009344, "vram_total_bytes": 4294967296, "gtt_used_bytes": 24844673024, "gtt_total_bytes": 193273528320} +{"t_s": 5.37, "VmRSS_bytes": 35495763968, "VmHWM_bytes": 35495763968, "Pss_bytes": 35528159232, "vram_used_bytes": 190496768, "vram_total_bytes": 4294967296, "gtt_used_bytes": 33044537344, "gtt_total_bytes": 193273528320} +{"t_s": 6.5, "VmRSS_bytes": 43014963200, "VmHWM_bytes": 43014963200, "Pss_bytes": 43036700672, "vram_used_bytes": 191053824, "vram_total_bytes": 4294967296, "gtt_used_bytes": 41238110208, "gtt_total_bytes": 193273528320} +{"t_s": 7.66, "VmRSS_bytes": 51183042560, "VmHWM_bytes": 51183042560, "Pss_bytes": 51199163392, "vram_used_bytes": 191590400, "vram_total_bytes": 4294967296, "gtt_used_bytes": 49433780224, "gtt_total_bytes": 193273528320} +{"t_s": 8.86, "VmRSS_bytes": 58899619840, "VmHWM_bytes": 58899619840, "Pss_bytes": 58897260544, "vram_used_bytes": 192155648, "vram_total_bytes": 4294967296, "gtt_used_bytes": 57621061632, "gtt_total_bytes": 193273528320} +{"t_s": 10.05, "VmRSS_bytes": 68060758016, "VmHWM_bytes": 68060758016, "Pss_bytes": 68058398720, "vram_used_bytes": 192708608, "vram_total_bytes": 4294967296, "gtt_used_bytes": 65816731648, "gtt_total_bytes": 193273528320} +{"t_s": 11.26, "VmRSS_bytes": 76702457856, "VmHWM_bytes": 76702457856, "Pss_bytes": 76702068736, "vram_used_bytes": 193286144, "vram_total_bytes": 4294967296, "gtt_used_bytes": 75604140032, "gtt_total_bytes": 193273528320} +{"t_s": 12.48, "VmRSS_bytes": 80825622528, "VmHWM_bytes": 82473451520, "Pss_bytes": 80823263232, "vram_used_bytes": 194539520, "vram_total_bytes": 4294967296, "gtt_used_bytes": 83107749888, "gtt_total_bytes": 193273528320} +{"t_s": 13.7, "VmRSS_bytes": 80849772544, "VmHWM_bytes": 82473451520, "Pss_bytes": 80860295168, "vram_used_bytes": 194387968, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84292640768, "gtt_total_bytes": 193273528320} +{"t_s": 14.93, "VmRSS_bytes": 81120370688, "VmHWM_bytes": 82473451520, "Pss_bytes": 81186336768, "vram_used_bytes": 194387968, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84292640768, "gtt_total_bytes": 193273528320} +{"t_s": 16.2, "VmRSS_bytes": 81416413184, "VmHWM_bytes": 82473451520, "Pss_bytes": 81414049792, "vram_used_bytes": 194387968, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84292640768, "gtt_total_bytes": 193273528320} +{"t_s": 17.46, "VmRSS_bytes": 81416413184, "VmHWM_bytes": 82473451520, "Pss_bytes": 81414049792, "vram_used_bytes": 194387968, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84292640768, "gtt_total_bytes": 193273528320} +{"t_s": 18.7, "VmRSS_bytes": 81699778560, "VmHWM_bytes": 82473451520, "Pss_bytes": 81765371904, "vram_used_bytes": 194387968, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84292640768, "gtt_total_bytes": 193273528320} +{"t_s": 19.96, "VmRSS_bytes": 81806909440, "VmHWM_bytes": 82473451520, "Pss_bytes": 81804546048, "vram_used_bytes": 194387968, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84292640768, "gtt_total_bytes": 193273528320} +{"t_s": 21.22, "VmRSS_bytes": 81806909440, "VmHWM_bytes": 82473451520, "Pss_bytes": 81804546048, "vram_used_bytes": 194387968, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84292640768, "gtt_total_bytes": 193273528320} +{"t_s": 22.46, "VmRSS_bytes": 82011451392, "VmHWM_bytes": 82473451520, "Pss_bytes": 82066034688, "vram_used_bytes": 194387968, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84292640768, "gtt_total_bytes": 193273528320} +{"t_s": 23.73, "VmRSS_bytes": 82203942912, "VmHWM_bytes": 82473451520, "Pss_bytes": 82201579520, "vram_used_bytes": 194387968, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84292640768, "gtt_total_bytes": 193273528320} +{"t_s": 25.01, "VmRSS_bytes": 82203942912, "VmHWM_bytes": 82473451520, "Pss_bytes": 82201579520, "vram_used_bytes": 194387968, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84292640768, "gtt_total_bytes": 193273528320} +{"t_s": 26.27, "VmRSS_bytes": 82261168128, "VmHWM_bytes": 82473451520, "Pss_bytes": 82321448960, "vram_used_bytes": 194387968, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84292640768, "gtt_total_bytes": 193273528320} +{"t_s": 27.54, "VmRSS_bytes": 82549682176, "VmHWM_bytes": 82549682176, "Pss_bytes": 82547318784, "vram_used_bytes": 194387968, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84292640768, "gtt_total_bytes": 193273528320} +{"t_s": 28.81, "VmRSS_bytes": 82549682176, "VmHWM_bytes": 82549682176, "Pss_bytes": 82547316736, "vram_used_bytes": 194387968, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84292640768, "gtt_total_bytes": 193273528320} +{"t_s": 30.08, "VmRSS_bytes": 82549682176, "VmHWM_bytes": 82549682176, "Pss_bytes": 82547388416, "vram_used_bytes": 194387968, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84292640768, "gtt_total_bytes": 193273528320} +{"t_s": 31.35, "VmRSS_bytes": 82746408960, "VmHWM_bytes": 82746408960, "Pss_bytes": 82744045568, "vram_used_bytes": 194387968, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84292640768, "gtt_total_bytes": 193273528320} +{"t_s": 32.63, "VmRSS_bytes": 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"vram_total_bytes": 4294967296, "gtt_used_bytes": 84296003584, "gtt_total_bytes": 193273528320} +{"t_s": 400.92, "VmRSS_bytes": 84456267776, "VmHWM_bytes": 84456267776, "Pss_bytes": 84453853184, "vram_used_bytes": 194392064, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84296003584, "gtt_total_bytes": 193273528320} +{"t_s": 402.22, "VmRSS_bytes": 84456267776, "VmHWM_bytes": 84456267776, "Pss_bytes": 84453853184, "vram_used_bytes": 194392064, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84296003584, "gtt_total_bytes": 193273528320} +{"t_s": 403.52, "VmRSS_bytes": 84456267776, "VmHWM_bytes": 84456267776, "Pss_bytes": 84453853184, "vram_used_bytes": 194392064, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84296003584, "gtt_total_bytes": 193273528320} +{"t_s": 404.81, "VmRSS_bytes": 84456267776, "VmHWM_bytes": 84456267776, "Pss_bytes": 84453853184, "vram_used_bytes": 194392064, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84296003584, "gtt_total_bytes": 193273528320} 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"gtt_total_bytes": 193273528320} +{"t_s": 458.64, "VmRSS_bytes": 84459413504, "VmHWM_bytes": 84459413504, "Pss_bytes": 84456933376, "vram_used_bytes": 194392064, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84254060544, "gtt_total_bytes": 193273528320} +{"t_s": 459.78, "VmRSS_bytes": 38597910528, "VmHWM_bytes": 84455137280, "Pss_bytes": 35447552000, "vram_used_bytes": 194260992, "vram_total_bytes": 4294967296, "gtt_used_bytes": 198942720, "gtt_total_bytes": 193273528320} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-drafts-base-r2-memory-endpoint.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-drafts-base-r2-memory-endpoint.json new file mode 100644 index 0000000000..8bb426e488 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-drafts-base-r2-memory-endpoint.json @@ -0,0 +1 @@ +{"schema_version": 1, "context_window": 19456, "context_fitted": false, "device": {"active_bytes": 83373280704, "cache_bytes": 0, "peak_bytes": 83415047364, "peak_scope": "since_start_or_health_reset"}} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-drafts-base-r2-metrics.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-drafts-base-r2-metrics.txt new file mode 100644 index 0000000000..76e9d24058 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-drafts-base-r2-metrics.txt @@ -0,0 +1,220 @@ +# HELP tensorfold:requests_running Requests in prefill or decode. +# TYPE tensorfold:requests_running gauge +tensorfold:requests_running 0 +# HELP tensorfold:requests_waiting Requests queued or held until a lane is free. +# TYPE tensorfold:requests_waiting gauge +tensorfold:requests_waiting 0 +# HELP tensorfold:generation_tokens_running Generated tokens held by live streams. +# TYPE tensorfold:generation_tokens_running gauge +tensorfold:generation_tokens_running 0 +# HELP tensorfold:prompt_tokens_total Prompt tokens of finished requests. +# TYPE tensorfold:prompt_tokens_total counter +tensorfold:prompt_tokens_total 114688 +# HELP tensorfold:generation_tokens_total Generated tokens of finished requests. +# TYPE tensorfold:generation_tokens_total counter +tensorfold:generation_tokens_total 3856 +# HELP tensorfold:kv_cache_usage_ratio Tokens in a stream cache divided by that stream's context window. +# TYPE tensorfold:kv_cache_usage_ratio gauge +tensorfold:kv_cache_usage_ratio{pool="0"} 0 +# HELP tensorfold:mtp_drafted_total Draft tokens verified on finished requests. +# TYPE tensorfold:mtp_drafted_total counter +tensorfold:mtp_drafted_total 2809 +# HELP tensorfold:mtp_accepted_total Draft tokens kept on finished requests. +# TYPE tensorfold:mtp_accepted_total counter +tensorfold:mtp_accepted_total 1912 +# HELP tensorfold:request_latency_seconds Seconds from arrival to the reply leaving. +# TYPE tensorfold:request_latency_seconds histogram +tensorfold:request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:request_latency_seconds_bucket{le="1"} 0 +tensorfold:request_latency_seconds_bucket{le="2.5"} 0 +tensorfold:request_latency_seconds_bucket{le="5"} 0 +tensorfold:request_latency_seconds_bucket{le="10"} 0 +tensorfold:request_latency_seconds_bucket{le="30"} 0 +tensorfold:request_latency_seconds_bucket{le="60"} 3 +tensorfold:request_latency_seconds_bucket{le="120"} 7 +tensorfold:request_latency_seconds_bucket{le="300"} 7 +tensorfold:request_latency_seconds_bucket{le="+Inf"} 7 +tensorfold:request_latency_seconds_sum 447.408569 +tensorfold:request_latency_seconds_count 7 +# HELP tensorfold:time_to_first_token_seconds Seconds from arrival to the first generated token. +# TYPE tensorfold:time_to_first_token_seconds histogram +tensorfold:time_to_first_token_seconds_bucket{le="0.01"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.05"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.25"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.5"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="2.5"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="5"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="10"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="30"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="60"} 6 +tensorfold:time_to_first_token_seconds_bucket{le="120"} 7 +tensorfold:time_to_first_token_seconds_bucket{le="300"} 7 +tensorfold:time_to_first_token_seconds_bucket{le="+Inf"} 7 +tensorfold:time_to_first_token_seconds_sum 344.195694 +tensorfold:time_to_first_token_seconds_count 7 +# HELP tensorfold:request_decode_seconds Seconds a finished request spent decoding. Its sum over generation_tokens_total is the decode rate. +# TYPE tensorfold:request_decode_seconds histogram +tensorfold:request_decode_seconds_bucket{le="0.01"} 0 +tensorfold:request_decode_seconds_bucket{le="0.05"} 0 +tensorfold:request_decode_seconds_bucket{le="0.1"} 0 +tensorfold:request_decode_seconds_bucket{le="0.25"} 0 +tensorfold:request_decode_seconds_bucket{le="0.5"} 1 +tensorfold:request_decode_seconds_bucket{le="1"} 1 +tensorfold:request_decode_seconds_bucket{le="2.5"} 1 +tensorfold:request_decode_seconds_bucket{le="5"} 1 +tensorfold:request_decode_seconds_bucket{le="10"} 4 +tensorfold:request_decode_seconds_bucket{le="30"} 7 +tensorfold:request_decode_seconds_bucket{le="60"} 7 +tensorfold:request_decode_seconds_bucket{le="120"} 7 +tensorfold:request_decode_seconds_bucket{le="300"} 7 +tensorfold:request_decode_seconds_bucket{le="+Inf"} 7 +tensorfold:request_decode_seconds_sum 103.212875 +tensorfold:request_decode_seconds_count 7 +# HELP tensorfold:request_time_per_output_token_seconds Seconds from the first generated token to the last, divided by the tokens less one. +# TYPE tensorfold:request_time_per_output_token_seconds histogram +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.005"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.01"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.015"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.02"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.025"} 2 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.03"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.04"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.05"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.075"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.1"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.15"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.2"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.3"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.5"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="1"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="+Inf"} 7 +tensorfold:request_time_per_output_token_seconds_sum 0.18109 +tensorfold:request_time_per_output_token_seconds_count 7 +# HELP tensorfold:decode_rounds_total Decode rounds used by finished requests. +# TYPE tensorfold:decode_rounds_total counter +tensorfold:decode_rounds_total 1937 +# HELP tensorfold:request_prefill_seconds Seconds a finished request's prompt pass took. +# TYPE tensorfold:request_prefill_seconds histogram +tensorfold:request_prefill_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.5"} 0 +tensorfold:request_prefill_seconds_bucket{le="1"} 0 +tensorfold:request_prefill_seconds_bucket{le="2.5"} 0 +tensorfold:request_prefill_seconds_bucket{le="5"} 0 +tensorfold:request_prefill_seconds_bucket{le="10"} 0 +tensorfold:request_prefill_seconds_bucket{le="30"} 0 +tensorfold:request_prefill_seconds_bucket{le="60"} 6 +tensorfold:request_prefill_seconds_bucket{le="120"} 7 +tensorfold:request_prefill_seconds_bucket{le="300"} 7 +tensorfold:request_prefill_seconds_bucket{le="+Inf"} 7 +tensorfold:request_prefill_seconds_sum 344.191671 +tensorfold:request_prefill_seconds_count 7 +# HELP tensorfold:process_resident_bytes Current resident set (VmRSS); device memory is not in it, so it is not a physical footprint (Linux). +# TYPE tensorfold:process_resident_bytes gauge +tensorfold:process_resident_bytes 84473008128 +# HELP tensorfold:process_resident_anon_bytes Current resident anonymous memory (RssAnon): heap, stacks and private maps (Linux). +# TYPE tensorfold:process_resident_anon_bytes gauge +tensorfold:process_resident_anon_bytes 316772352 +# HELP tensorfold:process_resident_file_bytes Current resident file-backed memory (RssFile): the binary, libraries and mapped files (Linux). +# TYPE tensorfold:process_resident_file_bytes gauge +tensorfold:process_resident_file_bytes 84044333056 +# HELP tensorfold:process_resident_shmem_bytes Current resident shared memory (RssShmem): System V shared memory, tmpfs maps and shared anonymous maps (Linux). +# TYPE tensorfold:process_resident_shmem_bytes gauge +tensorfold:process_resident_shmem_bytes 111902720 +# HELP tensorfold:process_resident_peak_bytes Kernel lifetime peak resident set (VmHWM); never reset by health (Linux). +# TYPE tensorfold:process_resident_peak_bytes gauge +tensorfold:process_resident_peak_bytes 84473393152 +# HELP tensorfold:device_memory_bytes Device memory the engine holds now: weights, caches and live streams; only where the backend counts it (CUDA). +# TYPE tensorfold:device_memory_bytes gauge +tensorfold:device_memory_bytes 83373280704 +# HELP tensorfold:device_memory_peak_bytes The most device memory the engine has held since start or the last /health?reset_peak=1. +# TYPE tensorfold:device_memory_peak_bytes gauge +tensorfold:device_memory_peak_bytes 83415047364 +# HELP tensorfold:pinned_memory_bytes Pinned host memory the engine holds now: staging buffers and windows; only where the backend counts it (CUDA). +# TYPE tensorfold:pinned_memory_bytes gauge +tensorfold:pinned_memory_bytes 0 +# HELP tensorfold:num_requests_running Requests in prefill or decode. A mirror of tensorfold:requests_running. +# TYPE tensorfold:num_requests_running gauge +tensorfold:num_requests_running 0 +# HELP tensorfold:num_requests_waiting Requests queued or held until a lane is free. A mirror of tensorfold:requests_waiting. +# TYPE tensorfold:num_requests_waiting gauge +tensorfold:num_requests_waiting 0 +# HELP tensorfold:kv_cache_usage_perc A stream's cache occupancy under vLLM's name; same streams and ratios as tensorfold:kv_cache_usage_ratio. +# TYPE tensorfold:kv_cache_usage_perc gauge +tensorfold:kv_cache_usage_perc{stream="0"} 0 +# HELP tensorfold:spec_decode_num_draft_tokens_total Draft tokens verified on finished requests, this server's single draft counter. +# TYPE tensorfold:spec_decode_num_draft_tokens_total counter +tensorfold:spec_decode_num_draft_tokens_total 2809 +# HELP tensorfold:spec_decode_num_accepted_tokens_total Draft tokens kept on finished requests. +# TYPE tensorfold:spec_decode_num_accepted_tokens_total counter +tensorfold:spec_decode_num_accepted_tokens_total 1912 +# HELP tensorfold:e2e_request_latency_seconds Seconds from arrival to the reply leaving, under vLLM's name. +# TYPE tensorfold:e2e_request_latency_seconds histogram +tensorfold:e2e_request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="2.5"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="5"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="10"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="30"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="60"} 3 +tensorfold:e2e_request_latency_seconds_bucket{le="120"} 7 +tensorfold:e2e_request_latency_seconds_bucket{le="300"} 7 +tensorfold:e2e_request_latency_seconds_bucket{le="+Inf"} 7 +tensorfold:e2e_request_latency_seconds_sum 447.408569 +tensorfold:e2e_request_latency_seconds_count 7 +# HELP tensorfold:request_decode_time_seconds Seconds a finished request spent decoding, under vLLM's name. +# TYPE tensorfold:request_decode_time_seconds histogram +tensorfold:request_decode_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.5"} 1 +tensorfold:request_decode_time_seconds_bucket{le="1"} 1 +tensorfold:request_decode_time_seconds_bucket{le="2.5"} 1 +tensorfold:request_decode_time_seconds_bucket{le="5"} 1 +tensorfold:request_decode_time_seconds_bucket{le="10"} 4 +tensorfold:request_decode_time_seconds_bucket{le="30"} 7 +tensorfold:request_decode_time_seconds_bucket{le="60"} 7 +tensorfold:request_decode_time_seconds_bucket{le="120"} 7 +tensorfold:request_decode_time_seconds_bucket{le="300"} 7 +tensorfold:request_decode_time_seconds_bucket{le="+Inf"} 7 +tensorfold:request_decode_time_seconds_sum 103.212875 +tensorfold:request_decode_time_seconds_count 7 +# HELP tensorfold:request_prefill_time_seconds Seconds a finished request's prompt pass took, under vLLM's name. +# TYPE tensorfold:request_prefill_time_seconds histogram +tensorfold:request_prefill_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.5"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="2.5"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="5"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="10"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="30"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="60"} 6 +tensorfold:request_prefill_time_seconds_bucket{le="120"} 7 +tensorfold:request_prefill_time_seconds_bucket{le="300"} 7 +tensorfold:request_prefill_time_seconds_bucket{le="+Inf"} 7 +tensorfold:request_prefill_time_seconds_sum 344.191671 +tensorfold:request_prefill_time_seconds_count 7 +# HELP tensorfold:client_disconnections_total Requests a client left before the reply left the server. +# TYPE tensorfold:client_disconnections_total counter +tensorfold:client_disconnections_total 0 +# HELP tensorfold:preemptions_total Requests that had to give a lane up to a later one. +# TYPE tensorfold:preemptions_total counter +tensorfold:preemptions_total 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-drafts-base-r2-samples.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-drafts-base-r2-samples.jsonl new file mode 100644 index 0000000000..753aef6de5 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-drafts-base-r2-samples.jsonl @@ -0,0 +1,348 @@ +{"t_s": 0.0, "VmRSS_bytes": 46182400, "VmHWM_bytes": 46182400, "Pss_bytes": 45908992, "vram_used_bytes": 187670528, "vram_total_bytes": 4294967296, "gtt_used_bytes": 31657984, "gtt_total_bytes": 193273528320} +{"t_s": 1.03, "VmRSS_bytes": 8615030784, "VmHWM_bytes": 8615030784, "Pss_bytes": 8612856832, "vram_used_bytes": 188772352, "vram_total_bytes": 4294967296, "gtt_used_bytes": 6821748736, "gtt_total_bytes": 193273528320} +{"t_s": 2.11, "VmRSS_bytes": 16153243648, "VmHWM_bytes": 16153243648, "Pss_bytes": 16151069696, "vram_used_bytes": 189202432, "vram_total_bytes": 4294967296, "gtt_used_bytes": 13381640192, "gtt_total_bytes": 193273528320} +{"t_s": 3.22, "VmRSS_bytes": 23213301760, "VmHWM_bytes": 23213301760, "Pss_bytes": 23211127808, "vram_used_bytes": 189771776, "vram_total_bytes": 4294967296, "gtt_used_bytes": 21568921600, "gtt_total_bytes": 193273528320} +{"t_s": 4.36, "VmRSS_bytes": 28381892608, "VmHWM_bytes": 28381892608, "Pss_bytes": 28428478464, "vram_used_bytes": 190140416, "vram_total_bytes": 4294967296, "gtt_used_bytes": 26484645888, "gtt_total_bytes": 193273528320} +{"t_s": 5.5, "VmRSS_bytes": 36077256704, "VmHWM_bytes": 36077256704, "Pss_bytes": 36088190976, "vram_used_bytes": 190550016, "vram_total_bytes": 4294967296, "gtt_used_bytes": 33044537344, "gtt_total_bytes": 193273528320} +{"t_s": 6.67, "VmRSS_bytes": 43354001408, "VmHWM_bytes": 43354001408, "Pss_bytes": 43394959360, "vram_used_bytes": 191111168, "vram_total_bytes": 4294967296, "gtt_used_bytes": 41238110208, "gtt_total_bytes": 193273528320} +{"t_s": 7.85, "VmRSS_bytes": 51488100352, "VmHWM_bytes": 51488100352, "Pss_bytes": 51518072832, "vram_used_bytes": 191651840, "vram_total_bytes": 4294967296, "gtt_used_bytes": 49433780224, "gtt_total_bytes": 193273528320} +{"t_s": 9.07, "VmRSS_bytes": 58971688960, "VmHWM_bytes": 58971688960, "Pss_bytes": 59011852288, "vram_used_bytes": 192217088, "vram_total_bytes": 4294967296, "gtt_used_bytes": 57621061632, "gtt_total_bytes": 193273528320} +{"t_s": 10.29, "VmRSS_bytes": 68584058880, "VmHWM_bytes": 68584058880, "Pss_bytes": 68581885952, "vram_used_bytes": 192770048, "vram_total_bytes": 4294967296, "gtt_used_bytes": 66657689600, "gtt_total_bytes": 193273528320} +{"t_s": 11.53, "VmRSS_bytes": 76552925184, "VmHWM_bytes": 76552925184, "Pss_bytes": 76584568832, "vram_used_bytes": 193318912, "vram_total_bytes": 4294967296, "gtt_used_bytes": 74010304512, "gtt_total_bytes": 193273528320} +{"t_s": 12.78, "VmRSS_bytes": 80823648256, "VmHWM_bytes": 82471059456, "Pss_bytes": 80821475328, "vram_used_bytes": 194621440, "vram_total_bytes": 4294967296, "gtt_used_bytes": 83107749888, "gtt_total_bytes": 193273528320} +{"t_s": 14.04, "VmRSS_bytes": 80869646336, "VmHWM_bytes": 82471059456, "Pss_bytes": 80912148480, "vram_used_bytes": 194473984, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84292640768, "gtt_total_bytes": 193273528320} +{"t_s": 15.3, "VmRSS_bytes": 81232105472, "VmHWM_bytes": 82471059456, "Pss_bytes": 81309468672, "vram_used_bytes": 194473984, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84292640768, "gtt_total_bytes": 193273528320} +{"t_s": 16.61, "VmRSS_bytes": 81417322496, "VmHWM_bytes": 82471059456, "Pss_bytes": 81415145472, "vram_used_bytes": 194473984, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84292640768, "gtt_total_bytes": 193273528320} +{"t_s": 17.88, "VmRSS_bytes": 81436561408, "VmHWM_bytes": 82471059456, "Pss_bytes": 81512667136, "vram_used_bytes": 194473984, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84292640768, "gtt_total_bytes": 193273528320} +{"t_s": 19.17, "VmRSS_bytes": 81809166336, "VmHWM_bytes": 82471059456, "Pss_bytes": 81806989312, "vram_used_bytes": 194473984, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84292640768, "gtt_total_bytes": 193273528320} +{"t_s": 20.47, "VmRSS_bytes": 81809166336, "VmHWM_bytes": 82471059456, "Pss_bytes": 81806989312, "vram_used_bytes": 194473984, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84292640768, "gtt_total_bytes": 193273528320} +{"t_s": 21.75, "VmRSS_bytes": 81825705984, "VmHWM_bytes": 82471059456, "Pss_bytes": 81883461632, "vram_used_bytes": 194473984, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84292640768, "gtt_total_bytes": 193273528320} +{"t_s": 23.04, "VmRSS_bytes": 82169323520, "VmHWM_bytes": 82471059456, "Pss_bytes": 82204993536, "vram_used_bytes": 194473984, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84292640768, "gtt_total_bytes": 193273528320} +{"t_s": 24.35, "VmRSS_bytes": 82207555584, "VmHWM_bytes": 82471059456, "Pss_bytes": 82205378560, "vram_used_bytes": 194473984, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84292640768, "gtt_total_bytes": 193273528320} +{"t_s": 25.65, "VmRSS_bytes": 82207555584, "VmHWM_bytes": 82471059456, "Pss_bytes": 82205378560, "vram_used_bytes": 194473984, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84292640768, "gtt_total_bytes": 193273528320} +{"t_s": 26.94, "VmRSS_bytes": 82390159360, "VmHWM_bytes": 82471059456, "Pss_bytes": 82447546368, "vram_used_bytes": 194473984, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84292640768, "gtt_total_bytes": 193273528320} +{"t_s": 28.24, "VmRSS_bytes": 82555510784, "VmHWM_bytes": 82555510784, "Pss_bytes": 82553333760, "vram_used_bytes": 194473984, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84292640768, "gtt_total_bytes": 193273528320} +{"t_s": 29.55, "VmRSS_bytes": 82555510784, "VmHWM_bytes": 82555510784, "Pss_bytes": 82553333760, "vram_used_bytes": 194473984, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84292640768, "gtt_total_bytes": 193273528320} +{"t_s": 30.83, "VmRSS_bytes": 82606362624, "VmHWM_bytes": 82606362624, "Pss_bytes": 82658031616, "vram_used_bytes": 194473984, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84292640768, "gtt_total_bytes": 193273528320} +{"t_s": 32.13, "VmRSS_bytes": 82753245184, "VmHWM_bytes": 82753245184, "Pss_bytes": 82751068160, "vram_used_bytes": 194473984, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84292640768, "gtt_total_bytes": 193273528320} +{"t_s": 33.43, "VmRSS_bytes": 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84477190144, "VmHWM_bytes": 84477190144, "Pss_bytes": 84474881024, "vram_used_bytes": 194469888, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84254060544, "gtt_total_bytes": 193273528320} +{"t_s": 461.63, "VmRSS_bytes": 51096453120, "VmHWM_bytes": 84473393152, "Pss_bytes": 45756872704, "vram_used_bytes": 194334720, "vram_total_bytes": 4294967296, "gtt_used_bytes": 198942720, "gtt_total_bytes": 193273528320} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-drafts-new-r1-memory-endpoint.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-drafts-new-r1-memory-endpoint.json new file mode 100644 index 0000000000..3a2e215b16 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-drafts-new-r1-memory-endpoint.json @@ -0,0 +1 @@ +{"schema_version": 1, "context_window": 19456, "context_fitted": false, "device": {"active_bytes": 87827794580, "cache_bytes": 0, "peak_bytes": 87869734564, "peak_scope": "since_start_or_health_reset"}} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-drafts-new-r1-metrics.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-drafts-new-r1-metrics.txt new file mode 100644 index 0000000000..1b914e8faf --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-drafts-new-r1-metrics.txt @@ -0,0 +1,220 @@ +# HELP tensorfold:requests_running Requests in prefill or decode. +# TYPE tensorfold:requests_running gauge +tensorfold:requests_running 0 +# HELP tensorfold:requests_waiting Requests queued or held until a lane is free. +# TYPE tensorfold:requests_waiting gauge +tensorfold:requests_waiting 0 +# HELP tensorfold:generation_tokens_running Generated tokens held by live streams. +# TYPE tensorfold:generation_tokens_running gauge +tensorfold:generation_tokens_running 0 +# HELP tensorfold:prompt_tokens_total Prompt tokens of finished requests. +# TYPE tensorfold:prompt_tokens_total counter +tensorfold:prompt_tokens_total 114688 +# HELP tensorfold:generation_tokens_total Generated tokens of finished requests. +# TYPE tensorfold:generation_tokens_total counter +tensorfold:generation_tokens_total 3856 +# HELP tensorfold:kv_cache_usage_ratio Tokens in a stream cache divided by that stream's context window. +# TYPE tensorfold:kv_cache_usage_ratio gauge +tensorfold:kv_cache_usage_ratio{pool="0"} 0 +# HELP tensorfold:mtp_drafted_total Draft tokens verified on finished requests. +# TYPE tensorfold:mtp_drafted_total counter +tensorfold:mtp_drafted_total 3853 +# HELP tensorfold:mtp_accepted_total Draft tokens kept on finished requests. +# TYPE tensorfold:mtp_accepted_total counter +tensorfold:mtp_accepted_total 2380 +# HELP tensorfold:request_latency_seconds Seconds from arrival to the reply leaving. +# TYPE tensorfold:request_latency_seconds histogram +tensorfold:request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:request_latency_seconds_bucket{le="1"} 0 +tensorfold:request_latency_seconds_bucket{le="2.5"} 0 +tensorfold:request_latency_seconds_bucket{le="5"} 0 +tensorfold:request_latency_seconds_bucket{le="10"} 0 +tensorfold:request_latency_seconds_bucket{le="30"} 0 +tensorfold:request_latency_seconds_bucket{le="60"} 7 +tensorfold:request_latency_seconds_bucket{le="120"} 7 +tensorfold:request_latency_seconds_bucket{le="300"} 7 +tensorfold:request_latency_seconds_bucket{le="+Inf"} 7 +tensorfold:request_latency_seconds_sum 293.738441 +tensorfold:request_latency_seconds_count 7 +# HELP tensorfold:time_to_first_token_seconds Seconds from arrival to the first generated token. +# TYPE tensorfold:time_to_first_token_seconds histogram +tensorfold:time_to_first_token_seconds_bucket{le="0.01"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.05"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.25"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.5"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="2.5"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="5"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="10"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="30"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="60"} 7 +tensorfold:time_to_first_token_seconds_bucket{le="120"} 7 +tensorfold:time_to_first_token_seconds_bucket{le="300"} 7 +tensorfold:time_to_first_token_seconds_bucket{le="+Inf"} 7 +tensorfold:time_to_first_token_seconds_sum 216.455952 +tensorfold:time_to_first_token_seconds_count 7 +# HELP tensorfold:request_decode_seconds Seconds a finished request spent decoding. Its sum over generation_tokens_total is the decode rate. +# TYPE tensorfold:request_decode_seconds histogram +tensorfold:request_decode_seconds_bucket{le="0.01"} 0 +tensorfold:request_decode_seconds_bucket{le="0.05"} 0 +tensorfold:request_decode_seconds_bucket{le="0.1"} 0 +tensorfold:request_decode_seconds_bucket{le="0.25"} 0 +tensorfold:request_decode_seconds_bucket{le="0.5"} 1 +tensorfold:request_decode_seconds_bucket{le="1"} 1 +tensorfold:request_decode_seconds_bucket{le="2.5"} 1 +tensorfold:request_decode_seconds_bucket{le="5"} 4 +tensorfold:request_decode_seconds_bucket{le="10"} 4 +tensorfold:request_decode_seconds_bucket{le="30"} 7 +tensorfold:request_decode_seconds_bucket{le="60"} 7 +tensorfold:request_decode_seconds_bucket{le="120"} 7 +tensorfold:request_decode_seconds_bucket{le="300"} 7 +tensorfold:request_decode_seconds_bucket{le="+Inf"} 7 +tensorfold:request_decode_seconds_sum 77.282489 +tensorfold:request_decode_seconds_count 7 +# HELP tensorfold:request_time_per_output_token_seconds Seconds from the first generated token to the last, divided by the tokens less one. +# TYPE tensorfold:request_time_per_output_token_seconds histogram +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.005"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.01"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.015"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.02"} 3 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.025"} 6 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.03"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.04"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.05"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.075"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.1"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.15"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.2"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.3"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.5"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="1"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="+Inf"} 7 +tensorfold:request_time_per_output_token_seconds_sum 0.144479 +tensorfold:request_time_per_output_token_seconds_count 7 +# HELP tensorfold:decode_rounds_total Decode rounds used by finished requests. +# TYPE tensorfold:decode_rounds_total counter +tensorfold:decode_rounds_total 1472 +# HELP tensorfold:request_prefill_seconds Seconds a finished request's prompt pass took. +# TYPE tensorfold:request_prefill_seconds histogram +tensorfold:request_prefill_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.5"} 0 +tensorfold:request_prefill_seconds_bucket{le="1"} 0 +tensorfold:request_prefill_seconds_bucket{le="2.5"} 0 +tensorfold:request_prefill_seconds_bucket{le="5"} 0 +tensorfold:request_prefill_seconds_bucket{le="10"} 0 +tensorfold:request_prefill_seconds_bucket{le="30"} 0 +tensorfold:request_prefill_seconds_bucket{le="60"} 7 +tensorfold:request_prefill_seconds_bucket{le="120"} 7 +tensorfold:request_prefill_seconds_bucket{le="300"} 7 +tensorfold:request_prefill_seconds_bucket{le="+Inf"} 7 +tensorfold:request_prefill_seconds_sum 216.452242 +tensorfold:request_prefill_seconds_count 7 +# HELP tensorfold:process_resident_bytes Current resident set (VmRSS); device memory is not in it, so it is not a physical footprint (Linux). +# TYPE tensorfold:process_resident_bytes gauge +tensorfold:process_resident_bytes 103305601024 +# HELP tensorfold:process_resident_anon_bytes Current resident anonymous memory (RssAnon): heap, stacks and private maps (Linux). +# TYPE tensorfold:process_resident_anon_bytes gauge +tensorfold:process_resident_anon_bytes 32370999296 +# HELP tensorfold:process_resident_file_bytes Current resident file-backed memory (RssFile): the binary, libraries and mapped files (Linux). +# TYPE tensorfold:process_resident_file_bytes gauge +tensorfold:process_resident_file_bytes 70800338944 +# HELP tensorfold:process_resident_shmem_bytes Current resident shared memory (RssShmem): System V shared memory, tmpfs maps and shared anonymous maps (Linux). +# TYPE tensorfold:process_resident_shmem_bytes gauge +tensorfold:process_resident_shmem_bytes 134262784 +# HELP tensorfold:process_resident_peak_bytes Kernel lifetime peak resident set (VmHWM); never reset by health (Linux). +# TYPE tensorfold:process_resident_peak_bytes gauge +tensorfold:process_resident_peak_bytes 110358818816 +# HELP tensorfold:device_memory_bytes Device memory the engine holds now: weights, caches and live streams; only where the backend counts it (CUDA). +# TYPE tensorfold:device_memory_bytes gauge +tensorfold:device_memory_bytes 87827794580 +# HELP tensorfold:device_memory_peak_bytes The most device memory the engine has held since start or the last /health?reset_peak=1. +# TYPE tensorfold:device_memory_peak_bytes gauge +tensorfold:device_memory_peak_bytes 87869734564 +# HELP tensorfold:pinned_memory_bytes Pinned host memory the engine holds now: staging buffers and windows; only where the backend counts it (CUDA). +# TYPE tensorfold:pinned_memory_bytes gauge +tensorfold:pinned_memory_bytes 0 +# HELP tensorfold:num_requests_running Requests in prefill or decode. A mirror of tensorfold:requests_running. +# TYPE tensorfold:num_requests_running gauge +tensorfold:num_requests_running 0 +# HELP tensorfold:num_requests_waiting Requests queued or held until a lane is free. A mirror of tensorfold:requests_waiting. +# TYPE tensorfold:num_requests_waiting gauge +tensorfold:num_requests_waiting 0 +# HELP tensorfold:kv_cache_usage_perc A stream's cache occupancy under vLLM's name; same streams and ratios as tensorfold:kv_cache_usage_ratio. +# TYPE tensorfold:kv_cache_usage_perc gauge +tensorfold:kv_cache_usage_perc{stream="0"} 0 +# HELP tensorfold:spec_decode_num_draft_tokens_total Draft tokens verified on finished requests, this server's single draft counter. +# TYPE tensorfold:spec_decode_num_draft_tokens_total counter +tensorfold:spec_decode_num_draft_tokens_total 3853 +# HELP tensorfold:spec_decode_num_accepted_tokens_total Draft tokens kept on finished requests. +# TYPE tensorfold:spec_decode_num_accepted_tokens_total counter +tensorfold:spec_decode_num_accepted_tokens_total 2380 +# HELP tensorfold:e2e_request_latency_seconds Seconds from arrival to the reply leaving, under vLLM's name. +# TYPE tensorfold:e2e_request_latency_seconds histogram +tensorfold:e2e_request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="2.5"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="5"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="10"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="30"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="60"} 7 +tensorfold:e2e_request_latency_seconds_bucket{le="120"} 7 +tensorfold:e2e_request_latency_seconds_bucket{le="300"} 7 +tensorfold:e2e_request_latency_seconds_bucket{le="+Inf"} 7 +tensorfold:e2e_request_latency_seconds_sum 293.738441 +tensorfold:e2e_request_latency_seconds_count 7 +# HELP tensorfold:request_decode_time_seconds Seconds a finished request spent decoding, under vLLM's name. +# TYPE tensorfold:request_decode_time_seconds histogram +tensorfold:request_decode_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.5"} 1 +tensorfold:request_decode_time_seconds_bucket{le="1"} 1 +tensorfold:request_decode_time_seconds_bucket{le="2.5"} 1 +tensorfold:request_decode_time_seconds_bucket{le="5"} 4 +tensorfold:request_decode_time_seconds_bucket{le="10"} 4 +tensorfold:request_decode_time_seconds_bucket{le="30"} 7 +tensorfold:request_decode_time_seconds_bucket{le="60"} 7 +tensorfold:request_decode_time_seconds_bucket{le="120"} 7 +tensorfold:request_decode_time_seconds_bucket{le="300"} 7 +tensorfold:request_decode_time_seconds_bucket{le="+Inf"} 7 +tensorfold:request_decode_time_seconds_sum 77.282489 +tensorfold:request_decode_time_seconds_count 7 +# HELP tensorfold:request_prefill_time_seconds Seconds a finished request's prompt pass took, under vLLM's name. +# TYPE tensorfold:request_prefill_time_seconds histogram +tensorfold:request_prefill_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.5"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="2.5"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="5"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="10"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="30"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="60"} 7 +tensorfold:request_prefill_time_seconds_bucket{le="120"} 7 +tensorfold:request_prefill_time_seconds_bucket{le="300"} 7 +tensorfold:request_prefill_time_seconds_bucket{le="+Inf"} 7 +tensorfold:request_prefill_time_seconds_sum 216.452242 +tensorfold:request_prefill_time_seconds_count 7 +# HELP tensorfold:client_disconnections_total Requests a client left before the reply left the server. +# TYPE tensorfold:client_disconnections_total counter +tensorfold:client_disconnections_total 0 +# HELP tensorfold:preemptions_total Requests that had to give a lane up to a later one. +# TYPE tensorfold:preemptions_total counter +tensorfold:preemptions_total 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-drafts-new-r1-samples.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-drafts-new-r1-samples.jsonl new file mode 100644 index 0000000000..ddc7488075 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-drafts-new-r1-samples.jsonl @@ -0,0 +1,259 @@ +{"t_s": 0.0, "VmRSS_bytes": 74178560, "VmHWM_bytes": 74178560, "Pss_bytes": 72133632, "vram_used_bytes": 187682816, "vram_total_bytes": 4294967296, "gtt_used_bytes": 31657984, "gtt_total_bytes": 193273528320} +{"t_s": 1.04, "VmRSS_bytes": 9696354304, "VmHWM_bytes": 9696354304, "Pss_bytes": 9694009344, "vram_used_bytes": 188796928, "vram_total_bytes": 4294967296, "gtt_used_bytes": 6841233408, "gtt_total_bytes": 193273528320} +{"t_s": 2.09, "VmRSS_bytes": 18332987392, "VmHWM_bytes": 18332987392, "Pss_bytes": 18330642432, "vram_used_bytes": 189325312, "vram_total_bytes": 4294967296, "gtt_used_bytes": 16121131008, "gtt_total_bytes": 193273528320} +{"t_s": 3.16, "VmRSS_bytes": 26529542144, "VmHWM_bytes": 26529542144, "Pss_bytes": 26545547264, "vram_used_bytes": 189992960, "vram_total_bytes": 4294967296, "gtt_used_bytes": 24910295040, "gtt_total_bytes": 193273528320} +{"t_s": 4.25, "VmRSS_bytes": 36173131776, "VmHWM_bytes": 36173131776, "Pss_bytes": 36170786816, "vram_used_bytes": 190472192, "vram_total_bytes": 4294967296, "gtt_used_bytes": 33976283136, "gtt_total_bytes": 193273528320} +{"t_s": 5.36, "VmRSS_bytes": 44330074112, "VmHWM_bytes": 44330074112, "Pss_bytes": 44329367552, "vram_used_bytes": 191102976, "vram_total_bytes": 4294967296, "gtt_used_bytes": 42983550976, "gtt_total_bytes": 193273528320} +{"t_s": 6.49, "VmRSS_bytes": 53577031680, "VmHWM_bytes": 53577031680, "Pss_bytes": 53601622016, "vram_used_bytes": 191655936, "vram_total_bytes": 4294967296, "gtt_used_bytes": 51200192512, "gtt_total_bytes": 193273528320} +{"t_s": 7.63, "VmRSS_bytes": 62125170688, "VmHWM_bytes": 62125170688, "Pss_bytes": 62122825728, "vram_used_bytes": 192188416, "vram_total_bytes": 4294967296, "gtt_used_bytes": 60366843904, "gtt_total_bytes": 193273528320} +{"t_s": 8.81, "VmRSS_bytes": 70444212224, "VmHWM_bytes": 70444212224, "Pss_bytes": 70504257536, "vram_used_bytes": 192835584, "vram_total_bytes": 4294967296, "gtt_used_bytes": 69275545600, "gtt_total_bytes": 193273528320} +{"t_s": 9.99, "VmRSS_bytes": 80765423616, "VmHWM_bytes": 80765423616, "Pss_bytes": 80763078656, "vram_used_bytes": 194068480, "vram_total_bytes": 4294967296, "gtt_used_bytes": 79878746112, "gtt_total_bytes": 193273528320} +{"t_s": 11.18, "VmRSS_bytes": 84103114752, "VmHWM_bytes": 84103114752, "Pss_bytes": 84056598528, "vram_used_bytes": 194191360, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 12.37, "VmRSS_bytes": 88020877312, "VmHWM_bytes": 88020877312, "Pss_bytes": 87982155776, "vram_used_bytes": 194191360, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 13.56, "VmRSS_bytes": 91920601088, "VmHWM_bytes": 91920601088, "Pss_bytes": 91817232384, "vram_used_bytes": 194191360, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 14.76, "VmRSS_bytes": 95662825472, "VmHWM_bytes": 95662825472, "Pss_bytes": 95562057728, "vram_used_bytes": 194191360, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 15.95, "VmRSS_bytes": 99266416640, "VmHWM_bytes": 99435458560, "Pss_bytes": 99259906048, "vram_used_bytes": 194191360, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 17.15, "VmRSS_bytes": 100125413376, "VmHWM_bytes": 100906713088, "Pss_bytes": 100110518272, "vram_used_bytes": 194273280, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 18.34, "VmRSS_bytes": 103461785600, "VmHWM_bytes": 103461785600, "Pss_bytes": 103412160512, "vram_used_bytes": 194310144, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 19.56, "VmRSS_bytes": 106450350080, "VmHWM_bytes": 106612420608, "Pss_bytes": 106437437440, "vram_used_bytes": 194310144, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 20.8, "VmRSS_bytes": 109577240576, "VmHWM_bytes": 109609447424, "Pss_bytes": 109756315648, "vram_used_bytes": 194310144, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 22.34, "VmRSS_bytes": 108726329344, "VmHWM_bytes": 110358818816, "Pss_bytes": 105029258240, "vram_used_bytes": 204312576, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88070221824, "gtt_total_bytes": 193273528320} +{"t_s": 23.61, "VmRSS_bytes": 103284891648, "VmHWM_bytes": 110358818816, "Pss_bytes": 103282488320, "vram_used_bytes": 204873728, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88793669632, "gtt_total_bytes": 193273528320} +{"t_s": 24.86, "VmRSS_bytes": 103289520128, "VmHWM_bytes": 110358818816, "Pss_bytes": 103287116800, "vram_used_bytes": 204873728, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88794775552, "gtt_total_bytes": 193273528320} +{"t_s": 26.08, "VmRSS_bytes": 103291871232, "VmHWM_bytes": 110358818816, "Pss_bytes": 103289467904, "vram_used_bytes": 204873728, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88795144192, "gtt_total_bytes": 193273528320} +{"t_s": 27.33, "VmRSS_bytes": 103298691072, "VmHWM_bytes": 110358818816, "Pss_bytes": 103296283648, "vram_used_bytes": 204869632, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88834990080, "gtt_total_bytes": 193273528320} +{"t_s": 28.59, "VmRSS_bytes": 103298691072, "VmHWM_bytes": 110358818816, "Pss_bytes": 103296283648, "vram_used_bytes": 204869632, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88834990080, "gtt_total_bytes": 193273528320} +{"t_s": 29.82, "VmRSS_bytes": 103298691072, "VmHWM_bytes": 110358818816, "Pss_bytes": 103296283648, "vram_used_bytes": 204869632, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88834990080, "gtt_total_bytes": 193273528320} +{"t_s": 31.06, "VmRSS_bytes": 103298691072, "VmHWM_bytes": 110358818816, "Pss_bytes": 103296283648, "vram_used_bytes": 204869632, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88834990080, "gtt_total_bytes": 193273528320} +{"t_s": 32.3, "VmRSS_bytes": 103298691072, "VmHWM_bytes": 110358818816, "Pss_bytes": 103296283648, "vram_used_bytes": 204869632, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88834990080, "gtt_total_bytes": 193273528320} +{"t_s": 33.55, "VmRSS_bytes": 103299383296, "VmHWM_bytes": 110358818816, "Pss_bytes": 103296975872, "vram_used_bytes": 204869632, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88834990080, "gtt_total_bytes": 193273528320} +{"t_s": 34.79, "VmRSS_bytes": 103299383296, "VmHWM_bytes": 110358818816, "Pss_bytes": 103296975872, "vram_used_bytes": 204869632, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88834990080, "gtt_total_bytes": 193273528320} +{"t_s": 36.03, "VmRSS_bytes": 103299383296, "VmHWM_bytes": 110358818816, "Pss_bytes": 103296975872, "vram_used_bytes": 204869632, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88834990080, "gtt_total_bytes": 193273528320} +{"t_s": 37.26, "VmRSS_bytes": 103300136960, "VmHWM_bytes": 110358818816, 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88837087232, "gtt_total_bytes": 193273528320} +{"t_s": 311.14, "VmRSS_bytes": 103309213696, "VmHWM_bytes": 110358818816, "Pss_bytes": 103306814464, "vram_used_bytes": 204865536, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88837087232, "gtt_total_bytes": 193273528320} +{"t_s": 312.43, "VmRSS_bytes": 103309254656, "VmHWM_bytes": 110358818816, "Pss_bytes": 103306855424, "vram_used_bytes": 204865536, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88837087232, "gtt_total_bytes": 193273528320} +{"t_s": 313.72, "VmRSS_bytes": 103309299712, "VmHWM_bytes": 110358818816, "Pss_bytes": 103306892288, "vram_used_bytes": 204865536, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88837087232, "gtt_total_bytes": 193273528320} +{"t_s": 315.01, "VmRSS_bytes": 103309340672, "VmHWM_bytes": 110358818816, "Pss_bytes": 103306953728, "vram_used_bytes": 204865536, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88837087232, "gtt_total_bytes": 193273528320} +{"t_s": 316.29, "VmRSS_bytes": 103309389824, "VmHWM_bytes": 110358818816, "Pss_bytes": 103306986496, "vram_used_bytes": 204865536, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88837087232, "gtt_total_bytes": 193273528320} +{"t_s": 317.56, "VmRSS_bytes": 103309418496, "VmHWM_bytes": 110358818816, "Pss_bytes": 103307023360, "vram_used_bytes": 204865536, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88837087232, "gtt_total_bytes": 193273528320} +{"t_s": 318.84, "VmRSS_bytes": 103309463552, "VmHWM_bytes": 110358818816, "Pss_bytes": 103307056128, "vram_used_bytes": 204865536, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88837087232, "gtt_total_bytes": 193273528320} +{"t_s": 320.08, "VmRSS_bytes": 103309496320, "VmHWM_bytes": 110358818816, "Pss_bytes": 103306957824, "vram_used_bytes": 204865536, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88795144192, "gtt_total_bytes": 193273528320} +{"t_s": 321.27, "VmRSS_bytes": 69964935168, "VmHWM_bytes": 110358818816, "Pss_bytes": 67643588608, "vram_used_bytes": 194363392, "vram_total_bytes": 4294967296, "gtt_used_bytes": 204288000, "gtt_total_bytes": 193273528320} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-drafts-new-r2-memory-endpoint.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-drafts-new-r2-memory-endpoint.json new file mode 100644 index 0000000000..3a2e215b16 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-drafts-new-r2-memory-endpoint.json @@ -0,0 +1 @@ +{"schema_version": 1, "context_window": 19456, "context_fitted": false, "device": {"active_bytes": 87827794580, "cache_bytes": 0, "peak_bytes": 87869734564, "peak_scope": "since_start_or_health_reset"}} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-drafts-new-r2-metrics.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-drafts-new-r2-metrics.txt new file mode 100644 index 0000000000..a7098da96d --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-drafts-new-r2-metrics.txt @@ -0,0 +1,220 @@ +# HELP tensorfold:requests_running Requests in prefill or decode. +# TYPE tensorfold:requests_running gauge +tensorfold:requests_running 0 +# HELP tensorfold:requests_waiting Requests queued or held until a lane is free. +# TYPE tensorfold:requests_waiting gauge +tensorfold:requests_waiting 0 +# HELP tensorfold:generation_tokens_running Generated tokens held by live streams. +# TYPE tensorfold:generation_tokens_running gauge +tensorfold:generation_tokens_running 0 +# HELP tensorfold:prompt_tokens_total Prompt tokens of finished requests. +# TYPE tensorfold:prompt_tokens_total counter +tensorfold:prompt_tokens_total 114688 +# HELP tensorfold:generation_tokens_total Generated tokens of finished requests. +# TYPE tensorfold:generation_tokens_total counter +tensorfold:generation_tokens_total 3856 +# HELP tensorfold:kv_cache_usage_ratio Tokens in a stream cache divided by that stream's context window. +# TYPE tensorfold:kv_cache_usage_ratio gauge +tensorfold:kv_cache_usage_ratio{pool="0"} 0 +# HELP tensorfold:mtp_drafted_total Draft tokens verified on finished requests. +# TYPE tensorfold:mtp_drafted_total counter +tensorfold:mtp_drafted_total 3853 +# HELP tensorfold:mtp_accepted_total Draft tokens kept on finished requests. +# TYPE tensorfold:mtp_accepted_total counter +tensorfold:mtp_accepted_total 2380 +# HELP tensorfold:request_latency_seconds Seconds from arrival to the reply leaving. +# TYPE tensorfold:request_latency_seconds histogram +tensorfold:request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:request_latency_seconds_bucket{le="1"} 0 +tensorfold:request_latency_seconds_bucket{le="2.5"} 0 +tensorfold:request_latency_seconds_bucket{le="5"} 0 +tensorfold:request_latency_seconds_bucket{le="10"} 0 +tensorfold:request_latency_seconds_bucket{le="30"} 0 +tensorfold:request_latency_seconds_bucket{le="60"} 7 +tensorfold:request_latency_seconds_bucket{le="120"} 7 +tensorfold:request_latency_seconds_bucket{le="300"} 7 +tensorfold:request_latency_seconds_bucket{le="+Inf"} 7 +tensorfold:request_latency_seconds_sum 294.849711 +tensorfold:request_latency_seconds_count 7 +# HELP tensorfold:time_to_first_token_seconds Seconds from arrival to the first generated token. +# TYPE tensorfold:time_to_first_token_seconds histogram +tensorfold:time_to_first_token_seconds_bucket{le="0.01"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.05"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.25"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.5"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="2.5"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="5"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="10"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="30"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="60"} 7 +tensorfold:time_to_first_token_seconds_bucket{le="120"} 7 +tensorfold:time_to_first_token_seconds_bucket{le="300"} 7 +tensorfold:time_to_first_token_seconds_bucket{le="+Inf"} 7 +tensorfold:time_to_first_token_seconds_sum 216.072719 +tensorfold:time_to_first_token_seconds_count 7 +# HELP tensorfold:request_decode_seconds Seconds a finished request spent decoding. Its sum over generation_tokens_total is the decode rate. +# TYPE tensorfold:request_decode_seconds histogram +tensorfold:request_decode_seconds_bucket{le="0.01"} 0 +tensorfold:request_decode_seconds_bucket{le="0.05"} 0 +tensorfold:request_decode_seconds_bucket{le="0.1"} 0 +tensorfold:request_decode_seconds_bucket{le="0.25"} 0 +tensorfold:request_decode_seconds_bucket{le="0.5"} 1 +tensorfold:request_decode_seconds_bucket{le="1"} 1 +tensorfold:request_decode_seconds_bucket{le="2.5"} 1 +tensorfold:request_decode_seconds_bucket{le="5"} 2 +tensorfold:request_decode_seconds_bucket{le="10"} 4 +tensorfold:request_decode_seconds_bucket{le="30"} 7 +tensorfold:request_decode_seconds_bucket{le="60"} 7 +tensorfold:request_decode_seconds_bucket{le="120"} 7 +tensorfold:request_decode_seconds_bucket{le="300"} 7 +tensorfold:request_decode_seconds_bucket{le="+Inf"} 7 +tensorfold:request_decode_seconds_sum 78.776992 +tensorfold:request_decode_seconds_count 7 +# HELP tensorfold:request_time_per_output_token_seconds Seconds from the first generated token to the last, divided by the tokens less one. +# TYPE tensorfold:request_time_per_output_token_seconds histogram +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.005"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.01"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.015"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.02"} 4 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.025"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.03"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.04"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.05"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.075"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.1"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.15"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.2"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.3"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.5"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="1"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="+Inf"} 7 +tensorfold:request_time_per_output_token_seconds_sum 0.137828 +tensorfold:request_time_per_output_token_seconds_count 7 +# HELP tensorfold:decode_rounds_total Decode rounds used by finished requests. +# TYPE tensorfold:decode_rounds_total counter +tensorfold:decode_rounds_total 1472 +# HELP tensorfold:request_prefill_seconds Seconds a finished request's prompt pass took. +# TYPE tensorfold:request_prefill_seconds histogram +tensorfold:request_prefill_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.5"} 0 +tensorfold:request_prefill_seconds_bucket{le="1"} 0 +tensorfold:request_prefill_seconds_bucket{le="2.5"} 0 +tensorfold:request_prefill_seconds_bucket{le="5"} 0 +tensorfold:request_prefill_seconds_bucket{le="10"} 0 +tensorfold:request_prefill_seconds_bucket{le="30"} 0 +tensorfold:request_prefill_seconds_bucket{le="60"} 7 +tensorfold:request_prefill_seconds_bucket{le="120"} 7 +tensorfold:request_prefill_seconds_bucket{le="300"} 7 +tensorfold:request_prefill_seconds_bucket{le="+Inf"} 7 +tensorfold:request_prefill_seconds_sum 216.068814 +tensorfold:request_prefill_seconds_count 7 +# HELP tensorfold:process_resident_bytes Current resident set (VmRSS); device memory is not in it, so it is not a physical footprint (Linux). +# TYPE tensorfold:process_resident_bytes gauge +tensorfold:process_resident_bytes 105216520192 +# HELP tensorfold:process_resident_anon_bytes Current resident anonymous memory (RssAnon): heap, stacks and private maps (Linux). +# TYPE tensorfold:process_resident_anon_bytes gauge +tensorfold:process_resident_anon_bytes 32371437568 +# HELP tensorfold:process_resident_file_bytes Current resident file-backed memory (RssFile): the binary, libraries and mapped files (Linux). +# TYPE tensorfold:process_resident_file_bytes gauge +tensorfold:process_resident_file_bytes 72710819840 +# HELP tensorfold:process_resident_shmem_bytes Current resident shared memory (RssShmem): System V shared memory, tmpfs maps and shared anonymous maps (Linux). +# TYPE tensorfold:process_resident_shmem_bytes gauge +tensorfold:process_resident_shmem_bytes 134262784 +# HELP tensorfold:process_resident_peak_bytes Kernel lifetime peak resident set (VmHWM); never reset by health (Linux). +# TYPE tensorfold:process_resident_peak_bytes gauge +tensorfold:process_resident_peak_bytes 112494862336 +# HELP tensorfold:device_memory_bytes Device memory the engine holds now: weights, caches and live streams; only where the backend counts it (CUDA). +# TYPE tensorfold:device_memory_bytes gauge +tensorfold:device_memory_bytes 87827794580 +# HELP tensorfold:device_memory_peak_bytes The most device memory the engine has held since start or the last /health?reset_peak=1. +# TYPE tensorfold:device_memory_peak_bytes gauge +tensorfold:device_memory_peak_bytes 87869734564 +# HELP tensorfold:pinned_memory_bytes Pinned host memory the engine holds now: staging buffers and windows; only where the backend counts it (CUDA). +# TYPE tensorfold:pinned_memory_bytes gauge +tensorfold:pinned_memory_bytes 0 +# HELP tensorfold:num_requests_running Requests in prefill or decode. A mirror of tensorfold:requests_running. +# TYPE tensorfold:num_requests_running gauge +tensorfold:num_requests_running 0 +# HELP tensorfold:num_requests_waiting Requests queued or held until a lane is free. A mirror of tensorfold:requests_waiting. +# TYPE tensorfold:num_requests_waiting gauge +tensorfold:num_requests_waiting 0 +# HELP tensorfold:kv_cache_usage_perc A stream's cache occupancy under vLLM's name; same streams and ratios as tensorfold:kv_cache_usage_ratio. +# TYPE tensorfold:kv_cache_usage_perc gauge +tensorfold:kv_cache_usage_perc{stream="0"} 0 +# HELP tensorfold:spec_decode_num_draft_tokens_total Draft tokens verified on finished requests, this server's single draft counter. +# TYPE tensorfold:spec_decode_num_draft_tokens_total counter +tensorfold:spec_decode_num_draft_tokens_total 3853 +# HELP tensorfold:spec_decode_num_accepted_tokens_total Draft tokens kept on finished requests. +# TYPE tensorfold:spec_decode_num_accepted_tokens_total counter +tensorfold:spec_decode_num_accepted_tokens_total 2380 +# HELP tensorfold:e2e_request_latency_seconds Seconds from arrival to the reply leaving, under vLLM's name. +# TYPE tensorfold:e2e_request_latency_seconds histogram +tensorfold:e2e_request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="2.5"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="5"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="10"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="30"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="60"} 7 +tensorfold:e2e_request_latency_seconds_bucket{le="120"} 7 +tensorfold:e2e_request_latency_seconds_bucket{le="300"} 7 +tensorfold:e2e_request_latency_seconds_bucket{le="+Inf"} 7 +tensorfold:e2e_request_latency_seconds_sum 294.849711 +tensorfold:e2e_request_latency_seconds_count 7 +# HELP tensorfold:request_decode_time_seconds Seconds a finished request spent decoding, under vLLM's name. +# TYPE tensorfold:request_decode_time_seconds histogram +tensorfold:request_decode_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.5"} 1 +tensorfold:request_decode_time_seconds_bucket{le="1"} 1 +tensorfold:request_decode_time_seconds_bucket{le="2.5"} 1 +tensorfold:request_decode_time_seconds_bucket{le="5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="10"} 4 +tensorfold:request_decode_time_seconds_bucket{le="30"} 7 +tensorfold:request_decode_time_seconds_bucket{le="60"} 7 +tensorfold:request_decode_time_seconds_bucket{le="120"} 7 +tensorfold:request_decode_time_seconds_bucket{le="300"} 7 +tensorfold:request_decode_time_seconds_bucket{le="+Inf"} 7 +tensorfold:request_decode_time_seconds_sum 78.776992 +tensorfold:request_decode_time_seconds_count 7 +# HELP tensorfold:request_prefill_time_seconds Seconds a finished request's prompt pass took, under vLLM's name. +# TYPE tensorfold:request_prefill_time_seconds histogram +tensorfold:request_prefill_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.5"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="2.5"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="5"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="10"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="30"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="60"} 7 +tensorfold:request_prefill_time_seconds_bucket{le="120"} 7 +tensorfold:request_prefill_time_seconds_bucket{le="300"} 7 +tensorfold:request_prefill_time_seconds_bucket{le="+Inf"} 7 +tensorfold:request_prefill_time_seconds_sum 216.068814 +tensorfold:request_prefill_time_seconds_count 7 +# HELP tensorfold:client_disconnections_total Requests a client left before the reply left the server. +# TYPE tensorfold:client_disconnections_total counter +tensorfold:client_disconnections_total 0 +# HELP tensorfold:preemptions_total Requests that had to give a lane up to a later one. +# TYPE tensorfold:preemptions_total counter +tensorfold:preemptions_total 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-drafts-new-r2-samples.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-drafts-new-r2-samples.jsonl new file mode 100644 index 0000000000..073fbbf1a8 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-drafts-new-r2-samples.jsonl @@ -0,0 +1,252 @@ +{"t_s": 0.0, "VmRSS_bytes": 73011200, "VmHWM_bytes": 73011200, "Pss_bytes": 70842368, 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"vram_used_bytes": 201768960, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88837087232, "gtt_total_bytes": 193273528320} +{"t_s": 283.11, "VmRSS_bytes": 105266937856, "VmHWM_bytes": 112494862336, "Pss_bytes": 105264545792, "vram_used_bytes": 201768960, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88837087232, "gtt_total_bytes": 193273528320} +{"t_s": 284.37, "VmRSS_bytes": 105266937856, "VmHWM_bytes": 112494862336, "Pss_bytes": 105264545792, "vram_used_bytes": 201768960, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88837087232, "gtt_total_bytes": 193273528320} +{"t_s": 285.65, "VmRSS_bytes": 105266937856, "VmHWM_bytes": 112494862336, "Pss_bytes": 105264545792, "vram_used_bytes": 201768960, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88837087232, "gtt_total_bytes": 193273528320} +{"t_s": 286.93, "VmRSS_bytes": 105266937856, "VmHWM_bytes": 112494862336, "Pss_bytes": 105264545792, "vram_used_bytes": 201768960, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88837087232, "gtt_total_bytes": 193273528320} +{"t_s": 288.23, "VmRSS_bytes": 105266937856, "VmHWM_bytes": 112494862336, "Pss_bytes": 105264545792, "vram_used_bytes": 201768960, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88837087232, "gtt_total_bytes": 193273528320} +{"t_s": 289.52, "VmRSS_bytes": 105266937856, "VmHWM_bytes": 112494862336, "Pss_bytes": 105264545792, "vram_used_bytes": 201768960, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88837087232, "gtt_total_bytes": 193273528320} +{"t_s": 290.81, "VmRSS_bytes": 105266937856, "VmHWM_bytes": 112494862336, "Pss_bytes": 105264545792, "vram_used_bytes": 201768960, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88837087232, "gtt_total_bytes": 193273528320} +{"t_s": 292.09, "VmRSS_bytes": 105217327104, "VmHWM_bytes": 112494862336, "Pss_bytes": 105214935040, "vram_used_bytes": 201768960, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88837087232, "gtt_total_bytes": 193273528320} +{"t_s": 293.35, "VmRSS_bytes": 105217327104, "VmHWM_bytes": 112494862336, "Pss_bytes": 105214935040, "vram_used_bytes": 201768960, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88837087232, "gtt_total_bytes": 193273528320} +{"t_s": 294.62, "VmRSS_bytes": 105217327104, "VmHWM_bytes": 112494862336, "Pss_bytes": 105214935040, "vram_used_bytes": 201768960, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88837087232, "gtt_total_bytes": 193273528320} +{"t_s": 295.89, "VmRSS_bytes": 105217327104, "VmHWM_bytes": 112494862336, "Pss_bytes": 105214935040, "vram_used_bytes": 201768960, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88837087232, "gtt_total_bytes": 193273528320} +{"t_s": 297.17, "VmRSS_bytes": 105217327104, "VmHWM_bytes": 112494862336, "Pss_bytes": 105214935040, "vram_used_bytes": 201768960, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88837087232, "gtt_total_bytes": 193273528320} +{"t_s": 298.46, "VmRSS_bytes": 105217327104, "VmHWM_bytes": 112494862336, "Pss_bytes": 105214935040, "vram_used_bytes": 201768960, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88837087232, "gtt_total_bytes": 193273528320} +{"t_s": 299.76, "VmRSS_bytes": 105217327104, "VmHWM_bytes": 112494862336, "Pss_bytes": 105214935040, "vram_used_bytes": 201768960, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88837087232, "gtt_total_bytes": 193273528320} +{"t_s": 301.06, "VmRSS_bytes": 105217327104, "VmHWM_bytes": 112494862336, "Pss_bytes": 105214935040, "vram_used_bytes": 201768960, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88837087232, "gtt_total_bytes": 193273528320} +{"t_s": 302.35, "VmRSS_bytes": 105217327104, "VmHWM_bytes": 112494862336, "Pss_bytes": 105214943232, "vram_used_bytes": 201768960, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88837087232, "gtt_total_bytes": 193273528320} +{"t_s": 303.69, "VmRSS_bytes": 105219813376, "VmHWM_bytes": 112494862336, "Pss_bytes": 105217433600, "vram_used_bytes": 201768960, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88837087232, "gtt_total_bytes": 193273528320} +{"t_s": 305.02, "VmRSS_bytes": 105219854336, "VmHWM_bytes": 112494862336, "Pss_bytes": 105217466368, "vram_used_bytes": 201768960, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88837087232, "gtt_total_bytes": 193273528320} +{"t_s": 306.36, "VmRSS_bytes": 105219899392, "VmHWM_bytes": 112494862336, "Pss_bytes": 105217515520, "vram_used_bytes": 201768960, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88837087232, "gtt_total_bytes": 193273528320} +{"t_s": 307.71, "VmRSS_bytes": 105219936256, "VmHWM_bytes": 112494862336, "Pss_bytes": 105217548288, "vram_used_bytes": 201768960, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88837087232, "gtt_total_bytes": 193273528320} +{"t_s": 309.04, "VmRSS_bytes": 105219981312, "VmHWM_bytes": 112494862336, "Pss_bytes": 105217601536, "vram_used_bytes": 201768960, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88837087232, "gtt_total_bytes": 193273528320} +{"t_s": 310.38, "VmRSS_bytes": 105220022272, "VmHWM_bytes": 112494862336, "Pss_bytes": 105217638400, "vram_used_bytes": 201768960, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88837087232, "gtt_total_bytes": 193273528320} +{"t_s": 311.72, "VmRSS_bytes": 105220063232, "VmHWM_bytes": 112494862336, "Pss_bytes": 105217683456, "vram_used_bytes": 201768960, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88837087232, "gtt_total_bytes": 193273528320} +{"t_s": 313.06, "VmRSS_bytes": 105220104192, "VmHWM_bytes": 112494862336, "Pss_bytes": 105217716224, "vram_used_bytes": 201768960, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88837087232, "gtt_total_bytes": 193273528320} +{"t_s": 314.37, "VmRSS_bytes": 105220141056, "VmHWM_bytes": 112494862336, "Pss_bytes": 105217744896, "vram_used_bytes": 201768960, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88837087232, "gtt_total_bytes": 193273528320} +{"t_s": 315.69, "VmRSS_bytes": 105220173824, "VmHWM_bytes": 112494862336, "Pss_bytes": 105217785856, "vram_used_bytes": 201768960, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88837087232, "gtt_total_bytes": 193273528320} +{"t_s": 317.04, "VmRSS_bytes": 105220227072, "VmHWM_bytes": 112494862336, "Pss_bytes": 105217847296, "vram_used_bytes": 201768960, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88837087232, "gtt_total_bytes": 193273528320} +{"t_s": 318.35, "VmRSS_bytes": 105220272128, "VmHWM_bytes": 112494862336, "Pss_bytes": 105217888256, "vram_used_bytes": 201768960, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88837087232, "gtt_total_bytes": 193273528320} +{"t_s": 319.68, "VmRSS_bytes": 105220308992, "VmHWM_bytes": 112494862336, "Pss_bytes": 105217925120, "vram_used_bytes": 201768960, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88837087232, "gtt_total_bytes": 193273528320} +{"t_s": 320.99, "VmRSS_bytes": 105220349952, "VmHWM_bytes": 112494862336, "Pss_bytes": 105217966080, "vram_used_bytes": 201768960, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88837087232, "gtt_total_bytes": 193273528320} +{"t_s": 322.3, "VmRSS_bytes": 105220378624, "VmHWM_bytes": 112494862336, "Pss_bytes": 105217998848, "vram_used_bytes": 201768960, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88837087232, "gtt_total_bytes": 193273528320} +{"t_s": 323.58, "VmRSS_bytes": 105216327680, "VmHWM_bytes": 112494862336, "Pss_bytes": 105213935616, "vram_used_bytes": 201768960, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88795144192, "gtt_total_bytes": 193273528320} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-serial-base-r1-memory-endpoint.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-serial-base-r1-memory-endpoint.json new file mode 100644 index 0000000000..8bb426e488 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-serial-base-r1-memory-endpoint.json @@ -0,0 +1 @@ +{"schema_version": 1, "context_window": 19456, "context_fitted": false, "device": {"active_bytes": 83373280704, "cache_bytes": 0, "peak_bytes": 83415047364, "peak_scope": "since_start_or_health_reset"}} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-serial-base-r1-metrics.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-serial-base-r1-metrics.txt new file mode 100644 index 0000000000..6f7d03657f --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-serial-base-r1-metrics.txt @@ -0,0 +1,220 @@ +# HELP tensorfold:requests_running Requests in prefill or decode. +# TYPE tensorfold:requests_running gauge +tensorfold:requests_running 0 +# HELP tensorfold:requests_waiting Requests queued or held until a lane is free. +# TYPE tensorfold:requests_waiting gauge +tensorfold:requests_waiting 0 +# HELP tensorfold:generation_tokens_running Generated tokens held by live streams. +# TYPE tensorfold:generation_tokens_running gauge +tensorfold:generation_tokens_running 0 +# HELP tensorfold:prompt_tokens_total Prompt tokens of finished requests. +# TYPE tensorfold:prompt_tokens_total counter +tensorfold:prompt_tokens_total 114688 +# HELP tensorfold:generation_tokens_total Generated tokens of finished requests. +# TYPE tensorfold:generation_tokens_total counter +tensorfold:generation_tokens_total 3856 +# HELP tensorfold:kv_cache_usage_ratio Tokens in a stream cache divided by that stream's context window. +# TYPE tensorfold:kv_cache_usage_ratio gauge +tensorfold:kv_cache_usage_ratio{pool="0"} 0 +# HELP tensorfold:mtp_drafted_total Draft tokens verified on finished requests. +# TYPE tensorfold:mtp_drafted_total counter +tensorfold:mtp_drafted_total 0 +# HELP tensorfold:mtp_accepted_total Draft tokens kept on finished requests. +# TYPE tensorfold:mtp_accepted_total counter +tensorfold:mtp_accepted_total 0 +# HELP tensorfold:request_latency_seconds Seconds from arrival to the reply leaving. +# TYPE tensorfold:request_latency_seconds histogram +tensorfold:request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:request_latency_seconds_bucket{le="1"} 0 +tensorfold:request_latency_seconds_bucket{le="2.5"} 0 +tensorfold:request_latency_seconds_bucket{le="5"} 0 +tensorfold:request_latency_seconds_bucket{le="10"} 0 +tensorfold:request_latency_seconds_bucket{le="30"} 0 +tensorfold:request_latency_seconds_bucket{le="60"} 3 +tensorfold:request_latency_seconds_bucket{le="120"} 7 +tensorfold:request_latency_seconds_bucket{le="300"} 7 +tensorfold:request_latency_seconds_bucket{le="+Inf"} 7 +tensorfold:request_latency_seconds_sum 474.430733 +tensorfold:request_latency_seconds_count 7 +# HELP tensorfold:time_to_first_token_seconds Seconds from arrival to the first generated token. +# TYPE tensorfold:time_to_first_token_seconds histogram +tensorfold:time_to_first_token_seconds_bucket{le="0.01"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.05"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.25"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.5"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="2.5"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="5"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="10"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="30"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="60"} 6 +tensorfold:time_to_first_token_seconds_bucket{le="120"} 7 +tensorfold:time_to_first_token_seconds_bucket{le="300"} 7 +tensorfold:time_to_first_token_seconds_bucket{le="+Inf"} 7 +tensorfold:time_to_first_token_seconds_sum 343.008227 +tensorfold:time_to_first_token_seconds_count 7 +# HELP tensorfold:request_decode_seconds Seconds a finished request spent decoding. Its sum over generation_tokens_total is the decode rate. +# TYPE tensorfold:request_decode_seconds histogram +tensorfold:request_decode_seconds_bucket{le="0.01"} 0 +tensorfold:request_decode_seconds_bucket{le="0.05"} 0 +tensorfold:request_decode_seconds_bucket{le="0.1"} 0 +tensorfold:request_decode_seconds_bucket{le="0.25"} 0 +tensorfold:request_decode_seconds_bucket{le="0.5"} 0 +tensorfold:request_decode_seconds_bucket{le="1"} 1 +tensorfold:request_decode_seconds_bucket{le="2.5"} 1 +tensorfold:request_decode_seconds_bucket{le="5"} 1 +tensorfold:request_decode_seconds_bucket{le="10"} 4 +tensorfold:request_decode_seconds_bucket{le="30"} 4 +tensorfold:request_decode_seconds_bucket{le="60"} 7 +tensorfold:request_decode_seconds_bucket{le="120"} 7 +tensorfold:request_decode_seconds_bucket{le="300"} 7 +tensorfold:request_decode_seconds_bucket{le="+Inf"} 7 +tensorfold:request_decode_seconds_sum 131.422506 +tensorfold:request_decode_seconds_count 7 +# HELP tensorfold:request_time_per_output_token_seconds Seconds from the first generated token to the last, divided by the tokens less one. +# TYPE tensorfold:request_time_per_output_token_seconds histogram +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.005"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.01"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.015"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.02"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.03"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.04"} 6 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.05"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.075"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.1"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.15"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.2"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.3"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.5"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="1"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="+Inf"} 7 +tensorfold:request_time_per_output_token_seconds_sum 0.246629 +tensorfold:request_time_per_output_token_seconds_count 7 +# HELP tensorfold:decode_rounds_total Decode rounds used by finished requests. +# TYPE tensorfold:decode_rounds_total counter +tensorfold:decode_rounds_total 3849 +# HELP tensorfold:request_prefill_seconds Seconds a finished request's prompt pass took. +# TYPE tensorfold:request_prefill_seconds histogram +tensorfold:request_prefill_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.5"} 0 +tensorfold:request_prefill_seconds_bucket{le="1"} 0 +tensorfold:request_prefill_seconds_bucket{le="2.5"} 0 +tensorfold:request_prefill_seconds_bucket{le="5"} 0 +tensorfold:request_prefill_seconds_bucket{le="10"} 0 +tensorfold:request_prefill_seconds_bucket{le="30"} 0 +tensorfold:request_prefill_seconds_bucket{le="60"} 6 +tensorfold:request_prefill_seconds_bucket{le="120"} 7 +tensorfold:request_prefill_seconds_bucket{le="300"} 7 +tensorfold:request_prefill_seconds_bucket{le="+Inf"} 7 +tensorfold:request_prefill_seconds_sum 343.004744 +tensorfold:request_prefill_seconds_count 7 +# HELP tensorfold:process_resident_bytes Current resident set (VmRSS); device memory is not in it, so it is not a physical footprint (Linux). +# TYPE tensorfold:process_resident_bytes gauge +tensorfold:process_resident_bytes 84446007296 +# HELP tensorfold:process_resident_anon_bytes Current resident anonymous memory (RssAnon): heap, stacks and private maps (Linux). +# TYPE tensorfold:process_resident_anon_bytes gauge +tensorfold:process_resident_anon_bytes 307408896 +# HELP tensorfold:process_resident_file_bytes Current resident file-backed memory (RssFile): the binary, libraries and mapped files (Linux). +# TYPE tensorfold:process_resident_file_bytes gauge +tensorfold:process_resident_file_bytes 84026695680 +# HELP tensorfold:process_resident_shmem_bytes Current resident shared memory (RssShmem): System V shared memory, tmpfs maps and shared anonymous maps (Linux). +# TYPE tensorfold:process_resident_shmem_bytes gauge +tensorfold:process_resident_shmem_bytes 111902720 +# HELP tensorfold:process_resident_peak_bytes Kernel lifetime peak resident set (VmHWM); never reset by health (Linux). +# TYPE tensorfold:process_resident_peak_bytes gauge +tensorfold:process_resident_peak_bytes 84446007296 +# HELP tensorfold:device_memory_bytes Device memory the engine holds now: weights, caches and live streams; only where the backend counts it (CUDA). +# TYPE tensorfold:device_memory_bytes gauge +tensorfold:device_memory_bytes 83373280704 +# HELP tensorfold:device_memory_peak_bytes The most device memory the engine has held since start or the last /health?reset_peak=1. +# TYPE tensorfold:device_memory_peak_bytes gauge +tensorfold:device_memory_peak_bytes 83415047364 +# HELP tensorfold:pinned_memory_bytes Pinned host memory the engine holds now: staging buffers and windows; only where the backend counts it (CUDA). +# TYPE tensorfold:pinned_memory_bytes gauge +tensorfold:pinned_memory_bytes 0 +# HELP tensorfold:num_requests_running Requests in prefill or decode. A mirror of tensorfold:requests_running. +# TYPE tensorfold:num_requests_running gauge +tensorfold:num_requests_running 0 +# HELP tensorfold:num_requests_waiting Requests queued or held until a lane is free. A mirror of tensorfold:requests_waiting. +# TYPE tensorfold:num_requests_waiting gauge +tensorfold:num_requests_waiting 0 +# HELP tensorfold:kv_cache_usage_perc A stream's cache occupancy under vLLM's name; same streams and ratios as tensorfold:kv_cache_usage_ratio. +# TYPE tensorfold:kv_cache_usage_perc gauge +tensorfold:kv_cache_usage_perc{stream="0"} 0 +# HELP tensorfold:spec_decode_num_draft_tokens_total Draft tokens verified on finished requests, this server's single draft counter. +# TYPE tensorfold:spec_decode_num_draft_tokens_total counter +tensorfold:spec_decode_num_draft_tokens_total 0 +# HELP tensorfold:spec_decode_num_accepted_tokens_total Draft tokens kept on finished requests. +# TYPE tensorfold:spec_decode_num_accepted_tokens_total counter +tensorfold:spec_decode_num_accepted_tokens_total 0 +# HELP tensorfold:e2e_request_latency_seconds Seconds from arrival to the reply leaving, under vLLM's name. +# TYPE tensorfold:e2e_request_latency_seconds histogram +tensorfold:e2e_request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="2.5"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="5"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="10"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="30"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="60"} 3 +tensorfold:e2e_request_latency_seconds_bucket{le="120"} 7 +tensorfold:e2e_request_latency_seconds_bucket{le="300"} 7 +tensorfold:e2e_request_latency_seconds_bucket{le="+Inf"} 7 +tensorfold:e2e_request_latency_seconds_sum 474.430733 +tensorfold:e2e_request_latency_seconds_count 7 +# HELP tensorfold:request_decode_time_seconds Seconds a finished request spent decoding, under vLLM's name. +# TYPE tensorfold:request_decode_time_seconds histogram +tensorfold:request_decode_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.5"} 0 +tensorfold:request_decode_time_seconds_bucket{le="1"} 1 +tensorfold:request_decode_time_seconds_bucket{le="2.5"} 1 +tensorfold:request_decode_time_seconds_bucket{le="5"} 1 +tensorfold:request_decode_time_seconds_bucket{le="10"} 4 +tensorfold:request_decode_time_seconds_bucket{le="30"} 4 +tensorfold:request_decode_time_seconds_bucket{le="60"} 7 +tensorfold:request_decode_time_seconds_bucket{le="120"} 7 +tensorfold:request_decode_time_seconds_bucket{le="300"} 7 +tensorfold:request_decode_time_seconds_bucket{le="+Inf"} 7 +tensorfold:request_decode_time_seconds_sum 131.422506 +tensorfold:request_decode_time_seconds_count 7 +# HELP tensorfold:request_prefill_time_seconds Seconds a finished request's prompt pass took, under vLLM's name. +# TYPE tensorfold:request_prefill_time_seconds histogram +tensorfold:request_prefill_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.5"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="2.5"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="5"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="10"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="30"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="60"} 6 +tensorfold:request_prefill_time_seconds_bucket{le="120"} 7 +tensorfold:request_prefill_time_seconds_bucket{le="300"} 7 +tensorfold:request_prefill_time_seconds_bucket{le="+Inf"} 7 +tensorfold:request_prefill_time_seconds_sum 343.004744 +tensorfold:request_prefill_time_seconds_count 7 +# HELP tensorfold:client_disconnections_total Requests a client left before the reply left the server. +# TYPE tensorfold:client_disconnections_total counter +tensorfold:client_disconnections_total 0 +# HELP tensorfold:preemptions_total Requests that had to give a lane up to a later one. +# TYPE tensorfold:preemptions_total counter +tensorfold:preemptions_total 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-serial-base-r1-samples.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-serial-base-r1-samples.jsonl new file mode 100644 index 0000000000..37c05b52b9 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-serial-base-r1-samples.jsonl @@ -0,0 +1,388 @@ +{"t_s": 0.0, "VmRSS_bytes": 40427520, "VmHWM_bytes": 40427520, "Pss_bytes": 38740992, 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"peak_scope": "since_start_or_health_reset"}} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-serial-base-r2-metrics.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-serial-base-r2-metrics.txt new file mode 100644 index 0000000000..b1fdf0dd47 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-serial-base-r2-metrics.txt @@ -0,0 +1,220 @@ +# HELP tensorfold:requests_running Requests in prefill or decode. +# TYPE tensorfold:requests_running gauge +tensorfold:requests_running 0 +# HELP tensorfold:requests_waiting Requests queued or held until a lane is free. +# TYPE tensorfold:requests_waiting gauge +tensorfold:requests_waiting 0 +# HELP tensorfold:generation_tokens_running Generated tokens held by live streams. +# TYPE tensorfold:generation_tokens_running gauge +tensorfold:generation_tokens_running 0 +# HELP tensorfold:prompt_tokens_total Prompt tokens of finished requests. +# TYPE tensorfold:prompt_tokens_total counter +tensorfold:prompt_tokens_total 114688 +# HELP tensorfold:generation_tokens_total Generated tokens of finished requests. +# TYPE tensorfold:generation_tokens_total counter +tensorfold:generation_tokens_total 3856 +# HELP tensorfold:kv_cache_usage_ratio Tokens in a stream cache divided by that stream's context window. +# TYPE tensorfold:kv_cache_usage_ratio gauge +tensorfold:kv_cache_usage_ratio{pool="0"} 0 +# HELP tensorfold:mtp_drafted_total Draft tokens verified on finished requests. +# TYPE tensorfold:mtp_drafted_total counter +tensorfold:mtp_drafted_total 0 +# HELP tensorfold:mtp_accepted_total Draft tokens kept on finished requests. +# TYPE tensorfold:mtp_accepted_total counter +tensorfold:mtp_accepted_total 0 +# HELP tensorfold:request_latency_seconds Seconds from arrival to the reply leaving. +# TYPE tensorfold:request_latency_seconds histogram +tensorfold:request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:request_latency_seconds_bucket{le="1"} 0 +tensorfold:request_latency_seconds_bucket{le="2.5"} 0 +tensorfold:request_latency_seconds_bucket{le="5"} 0 +tensorfold:request_latency_seconds_bucket{le="10"} 0 +tensorfold:request_latency_seconds_bucket{le="30"} 0 +tensorfold:request_latency_seconds_bucket{le="60"} 3 +tensorfold:request_latency_seconds_bucket{le="120"} 7 +tensorfold:request_latency_seconds_bucket{le="300"} 7 +tensorfold:request_latency_seconds_bucket{le="+Inf"} 7 +tensorfold:request_latency_seconds_sum 477.87143 +tensorfold:request_latency_seconds_count 7 +# HELP tensorfold:time_to_first_token_seconds Seconds from arrival to the first generated token. +# TYPE tensorfold:time_to_first_token_seconds histogram +tensorfold:time_to_first_token_seconds_bucket{le="0.01"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.05"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.25"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.5"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="2.5"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="5"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="10"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="30"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="60"} 6 +tensorfold:time_to_first_token_seconds_bucket{le="120"} 7 +tensorfold:time_to_first_token_seconds_bucket{le="300"} 7 +tensorfold:time_to_first_token_seconds_bucket{le="+Inf"} 7 +tensorfold:time_to_first_token_seconds_sum 343.945481 +tensorfold:time_to_first_token_seconds_count 7 +# HELP tensorfold:request_decode_seconds Seconds a finished request spent decoding. Its sum over generation_tokens_total is the decode rate. +# TYPE tensorfold:request_decode_seconds histogram +tensorfold:request_decode_seconds_bucket{le="0.01"} 0 +tensorfold:request_decode_seconds_bucket{le="0.05"} 0 +tensorfold:request_decode_seconds_bucket{le="0.1"} 0 +tensorfold:request_decode_seconds_bucket{le="0.25"} 0 +tensorfold:request_decode_seconds_bucket{le="0.5"} 0 +tensorfold:request_decode_seconds_bucket{le="1"} 1 +tensorfold:request_decode_seconds_bucket{le="2.5"} 1 +tensorfold:request_decode_seconds_bucket{le="5"} 1 +tensorfold:request_decode_seconds_bucket{le="10"} 4 +tensorfold:request_decode_seconds_bucket{le="30"} 4 +tensorfold:request_decode_seconds_bucket{le="60"} 7 +tensorfold:request_decode_seconds_bucket{le="120"} 7 +tensorfold:request_decode_seconds_bucket{le="300"} 7 +tensorfold:request_decode_seconds_bucket{le="+Inf"} 7 +tensorfold:request_decode_seconds_sum 133.925949 +tensorfold:request_decode_seconds_count 7 +# HELP tensorfold:request_time_per_output_token_seconds Seconds from the first generated token to the last, divided by the tokens less one. +# TYPE tensorfold:request_time_per_output_token_seconds histogram +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.005"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.01"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.015"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.02"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.03"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.04"} 6 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.05"} 6 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.075"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.1"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.15"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.2"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.3"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.5"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="1"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="+Inf"} 7 +tensorfold:request_time_per_output_token_seconds_sum 0.259709 +tensorfold:request_time_per_output_token_seconds_count 7 +# HELP tensorfold:decode_rounds_total Decode rounds used by finished requests. +# TYPE tensorfold:decode_rounds_total counter +tensorfold:decode_rounds_total 3849 +# HELP tensorfold:request_prefill_seconds Seconds a finished request's prompt pass took. +# TYPE tensorfold:request_prefill_seconds histogram +tensorfold:request_prefill_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.5"} 0 +tensorfold:request_prefill_seconds_bucket{le="1"} 0 +tensorfold:request_prefill_seconds_bucket{le="2.5"} 0 +tensorfold:request_prefill_seconds_bucket{le="5"} 0 +tensorfold:request_prefill_seconds_bucket{le="10"} 0 +tensorfold:request_prefill_seconds_bucket{le="30"} 0 +tensorfold:request_prefill_seconds_bucket{le="60"} 6 +tensorfold:request_prefill_seconds_bucket{le="120"} 7 +tensorfold:request_prefill_seconds_bucket{le="300"} 7 +tensorfold:request_prefill_seconds_bucket{le="+Inf"} 7 +tensorfold:request_prefill_seconds_sum 343.942177 +tensorfold:request_prefill_seconds_count 7 +# HELP tensorfold:process_resident_bytes Current resident set (VmRSS); device memory is not in it, so it is not a physical footprint (Linux). +# TYPE tensorfold:process_resident_bytes gauge +tensorfold:process_resident_bytes 84414324736 +# HELP tensorfold:process_resident_anon_bytes Current resident anonymous memory (RssAnon): heap, stacks and private maps (Linux). +# TYPE tensorfold:process_resident_anon_bytes gauge +tensorfold:process_resident_anon_bytes 305639424 +# HELP tensorfold:process_resident_file_bytes Current resident file-backed memory (RssFile): the binary, libraries and mapped files (Linux). +# TYPE tensorfold:process_resident_file_bytes gauge +tensorfold:process_resident_file_bytes 83996782592 +# HELP tensorfold:process_resident_shmem_bytes Current resident shared memory (RssShmem): System V shared memory, tmpfs maps and shared anonymous maps (Linux). +# TYPE tensorfold:process_resident_shmem_bytes gauge +tensorfold:process_resident_shmem_bytes 111902720 +# HELP tensorfold:process_resident_peak_bytes Kernel lifetime peak resident set (VmHWM); never reset by health (Linux). +# TYPE tensorfold:process_resident_peak_bytes gauge +tensorfold:process_resident_peak_bytes 84414324736 +# HELP tensorfold:device_memory_bytes Device memory the engine holds now: weights, caches and live streams; only where the backend counts it (CUDA). +# TYPE tensorfold:device_memory_bytes gauge +tensorfold:device_memory_bytes 83373280704 +# HELP tensorfold:device_memory_peak_bytes The most device memory the engine has held since start or the last /health?reset_peak=1. +# TYPE tensorfold:device_memory_peak_bytes gauge +tensorfold:device_memory_peak_bytes 83415047364 +# HELP tensorfold:pinned_memory_bytes Pinned host memory the engine holds now: staging buffers and windows; only where the backend counts it (CUDA). +# TYPE tensorfold:pinned_memory_bytes gauge +tensorfold:pinned_memory_bytes 0 +# HELP tensorfold:num_requests_running Requests in prefill or decode. A mirror of tensorfold:requests_running. +# TYPE tensorfold:num_requests_running gauge +tensorfold:num_requests_running 0 +# HELP tensorfold:num_requests_waiting Requests queued or held until a lane is free. A mirror of tensorfold:requests_waiting. +# TYPE tensorfold:num_requests_waiting gauge +tensorfold:num_requests_waiting 0 +# HELP tensorfold:kv_cache_usage_perc A stream's cache occupancy under vLLM's name; same streams and ratios as tensorfold:kv_cache_usage_ratio. +# TYPE tensorfold:kv_cache_usage_perc gauge +tensorfold:kv_cache_usage_perc{stream="0"} 0 +# HELP tensorfold:spec_decode_num_draft_tokens_total Draft tokens verified on finished requests, this server's single draft counter. +# TYPE tensorfold:spec_decode_num_draft_tokens_total counter +tensorfold:spec_decode_num_draft_tokens_total 0 +# HELP tensorfold:spec_decode_num_accepted_tokens_total Draft tokens kept on finished requests. +# TYPE tensorfold:spec_decode_num_accepted_tokens_total counter +tensorfold:spec_decode_num_accepted_tokens_total 0 +# HELP tensorfold:e2e_request_latency_seconds Seconds from arrival to the reply leaving, under vLLM's name. +# TYPE tensorfold:e2e_request_latency_seconds histogram +tensorfold:e2e_request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="2.5"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="5"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="10"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="30"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="60"} 3 +tensorfold:e2e_request_latency_seconds_bucket{le="120"} 7 +tensorfold:e2e_request_latency_seconds_bucket{le="300"} 7 +tensorfold:e2e_request_latency_seconds_bucket{le="+Inf"} 7 +tensorfold:e2e_request_latency_seconds_sum 477.87143 +tensorfold:e2e_request_latency_seconds_count 7 +# HELP tensorfold:request_decode_time_seconds Seconds a finished request spent decoding, under vLLM's name. +# TYPE tensorfold:request_decode_time_seconds histogram +tensorfold:request_decode_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.5"} 0 +tensorfold:request_decode_time_seconds_bucket{le="1"} 1 +tensorfold:request_decode_time_seconds_bucket{le="2.5"} 1 +tensorfold:request_decode_time_seconds_bucket{le="5"} 1 +tensorfold:request_decode_time_seconds_bucket{le="10"} 4 +tensorfold:request_decode_time_seconds_bucket{le="30"} 4 +tensorfold:request_decode_time_seconds_bucket{le="60"} 7 +tensorfold:request_decode_time_seconds_bucket{le="120"} 7 +tensorfold:request_decode_time_seconds_bucket{le="300"} 7 +tensorfold:request_decode_time_seconds_bucket{le="+Inf"} 7 +tensorfold:request_decode_time_seconds_sum 133.925949 +tensorfold:request_decode_time_seconds_count 7 +# HELP tensorfold:request_prefill_time_seconds Seconds a finished request's prompt pass took, under vLLM's name. +# TYPE tensorfold:request_prefill_time_seconds histogram +tensorfold:request_prefill_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.5"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="2.5"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="5"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="10"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="30"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="60"} 6 +tensorfold:request_prefill_time_seconds_bucket{le="120"} 7 +tensorfold:request_prefill_time_seconds_bucket{le="300"} 7 +tensorfold:request_prefill_time_seconds_bucket{le="+Inf"} 7 +tensorfold:request_prefill_time_seconds_sum 343.942177 +tensorfold:request_prefill_time_seconds_count 7 +# HELP tensorfold:client_disconnections_total Requests a client left before the reply left the server. +# TYPE tensorfold:client_disconnections_total counter +tensorfold:client_disconnections_total 0 +# HELP tensorfold:preemptions_total Requests that had to give a lane up to a later one. +# TYPE tensorfold:preemptions_total counter +tensorfold:preemptions_total 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-serial-base-r2-samples.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-serial-base-r2-samples.jsonl new file mode 100644 index 0000000000..97077ef153 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-serial-base-r2-samples.jsonl @@ -0,0 +1,374 @@ +{"t_s": 0.0, "VmRSS_bytes": 45088768, "VmHWM_bytes": 45088768, "Pss_bytes": 45777920, "vram_used_bytes": 187670528, "vram_total_bytes": 4294967296, "gtt_used_bytes": 31657984, "gtt_total_bytes": 193273528320} +{"t_s": 1.03, "VmRSS_bytes": 8609292288, "VmHWM_bytes": 8609292288, "Pss_bytes": 8609478656, "vram_used_bytes": 188768256, "vram_total_bytes": 4294967296, "gtt_used_bytes": 6821748736, "gtt_total_bytes": 193273528320} +{"t_s": 2.11, "VmRSS_bytes": 15959298048, "VmHWM_bytes": 15959298048, "Pss_bytes": 15964260352, "vram_used_bytes": 189206528, "vram_total_bytes": 4294967296, "gtt_used_bytes": 13375348736, "gtt_total_bytes": 193273528320} +{"t_s": 3.21, "VmRSS_bytes": 20980629504, "VmHWM_bytes": 20980629504, "Pss_bytes": 20998576128, "vram_used_bytes": 189558784, "vram_total_bytes": 4294967296, "gtt_used_bytes": 18288975872, "gtt_total_bytes": 193273528320} +{"t_s": 4.31, "VmRSS_bytes": 27922161664, "VmHWM_bytes": 27922161664, "Pss_bytes": 27927590912, "vram_used_bytes": 190038016, "vram_total_bytes": 4294967296, "gtt_used_bytes": 24850964480, "gtt_total_bytes": 193273528320} +{"t_s": 5.44, "VmRSS_bytes": 35794563072, "VmHWM_bytes": 35794563072, "Pss_bytes": 35907602432, "vram_used_bytes": 190533632, "vram_total_bytes": 4294967296, "gtt_used_bytes": 33044537344, "gtt_total_bytes": 193273528320} +{"t_s": 6.58, "VmRSS_bytes": 43619635200, "VmHWM_bytes": 43619635200, "Pss_bytes": 43617462272, "vram_used_bytes": 191090688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 41238110208, "gtt_total_bytes": 193273528320} +{"t_s": 7.75, "VmRSS_bytes": 51718643712, "VmHWM_bytes": 51718643712, "Pss_bytes": 51757053952, "vram_used_bytes": 191631360, "vram_total_bytes": 4294967296, "gtt_used_bytes": 49433780224, "gtt_total_bytes": 193273528320} +{"t_s": 8.95, "VmRSS_bytes": 59253309440, "VmHWM_bytes": 59253309440, "Pss_bytes": 59301992448, "vram_used_bytes": 192196608, "vram_total_bytes": 4294967296, "gtt_used_bytes": 57621061632, "gtt_total_bytes": 193273528320} +{"t_s": 10.17, "VmRSS_bytes": 68465762304, "VmHWM_bytes": 68465762304, "Pss_bytes": 68471126016, "vram_used_bytes": 192741376, "vram_total_bytes": 4294967296, "gtt_used_bytes": 65816731648, "gtt_total_bytes": 193273528320} +{"t_s": 11.39, "VmRSS_bytes": 76454420480, "VmHWM_bytes": 76454420480, "Pss_bytes": 76479248384, "vram_used_bytes": 193290240, "vram_total_bytes": 4294967296, "gtt_used_bytes": 74010304512, "gtt_total_bytes": 193273528320} +{"t_s": 12.63, "VmRSS_bytes": 80817946624, "VmHWM_bytes": 82465857536, "Pss_bytes": 80815773696, "vram_used_bytes": 194596864, "vram_total_bytes": 4294967296, "gtt_used_bytes": 83107749888, "gtt_total_bytes": 193273528320} +{"t_s": 13.88, "VmRSS_bytes": 80852578304, "VmHWM_bytes": 82465857536, "Pss_bytes": 80880351232, "vram_used_bytes": 194445312, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84292640768, "gtt_total_bytes": 193273528320} +{"t_s": 15.14, "VmRSS_bytes": 81203261440, "VmHWM_bytes": 82465857536, "Pss_bytes": 81275356160, "vram_used_bytes": 194445312, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84292640768, "gtt_total_bytes": 193273528320} +{"t_s": 16.43, "VmRSS_bytes": 81414770688, "VmHWM_bytes": 82465857536, "Pss_bytes": 81412592640, "vram_used_bytes": 194445312, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84292640768, "gtt_total_bytes": 193273528320} +{"t_s": 17.7, "VmRSS_bytes": 81414770688, "VmHWM_bytes": 82465857536, "Pss_bytes": 81467425792, "vram_used_bytes": 194445312, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84292640768, "gtt_total_bytes": 193273528320} +{"t_s": 18.97, "VmRSS_bytes": 81793159168, "VmHWM_bytes": 82465857536, "Pss_bytes": 81803445248, "vram_used_bytes": 194445312, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84292640768, "gtt_total_bytes": 193273528320} +{"t_s": 20.27, "VmRSS_bytes": 81805643776, "VmHWM_bytes": 82465857536, "Pss_bytes": 81803465728, "vram_used_bytes": 194445312, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84292640768, "gtt_total_bytes": 193273528320} +{"t_s": 21.53, "VmRSS_bytes": 81805643776, "VmHWM_bytes": 82465857536, "Pss_bytes": 81817355264, "vram_used_bytes": 194445312, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84292640768, "gtt_total_bytes": 193273528320} +{"t_s": 22.79, "VmRSS_bytes": 82093117440, "VmHWM_bytes": 82465857536, "Pss_bytes": 82152420352, "vram_used_bytes": 194445312, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84292640768, "gtt_total_bytes": 193273528320} +{"t_s": 24.07, "VmRSS_bytes": 82203054080, "VmHWM_bytes": 82465857536, "Pss_bytes": 82200876032, "vram_used_bytes": 194445312, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84292640768, "gtt_total_bytes": 193273528320} +{"t_s": 25.35, "VmRSS_bytes": 82203054080, "VmHWM_bytes": 82465857536, "Pss_bytes": 82200877056, "vram_used_bytes": 194445312, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84292640768, "gtt_total_bytes": 193273528320} +{"t_s": 26.61, "VmRSS_bytes": 82313502720, "VmHWM_bytes": 82465857536, "Pss_bytes": 82368223232, "vram_used_bytes": 194445312, "vram_total_bytes": 4294967296, 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"gtt_total_bytes": 193273528320} +{"t_s": 479.58, "VmRSS_bytes": 84415733760, "VmHWM_bytes": 84415733760, "Pss_bytes": 84413510656, "vram_used_bytes": 194449408, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84295147520, "gtt_total_bytes": 193273528320} +{"t_s": 480.96, "VmRSS_bytes": 84415778816, "VmHWM_bytes": 84415778816, "Pss_bytes": 84413551616, "vram_used_bytes": 194449408, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84295147520, "gtt_total_bytes": 193273528320} +{"t_s": 482.35, "VmRSS_bytes": 84415815680, "VmHWM_bytes": 84415815680, "Pss_bytes": 84413588480, "vram_used_bytes": 194449408, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84295147520, "gtt_total_bytes": 193273528320} +{"t_s": 483.74, "VmRSS_bytes": 84415844352, "VmHWM_bytes": 84415844352, "Pss_bytes": 84413629440, "vram_used_bytes": 194449408, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84295147520, "gtt_total_bytes": 193273528320} +{"t_s": 485.11, "VmRSS_bytes": 84415893504, "VmHWM_bytes": 84415893504, "Pss_bytes": 84413666304, "vram_used_bytes": 194449408, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84295147520, "gtt_total_bytes": 193273528320} +{"t_s": 486.5, "VmRSS_bytes": 84415922176, "VmHWM_bytes": 84415922176, "Pss_bytes": 84413694976, "vram_used_bytes": 194449408, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84295147520, "gtt_total_bytes": 193273528320} +{"t_s": 487.88, "VmRSS_bytes": 84415959040, "VmHWM_bytes": 84415959040, "Pss_bytes": 84413731840, "vram_used_bytes": 194449408, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84295147520, "gtt_total_bytes": 193273528320} +{"t_s": 489.23, "VmRSS_bytes": 84415991808, "VmHWM_bytes": 84415991808, "Pss_bytes": 84413760512, "vram_used_bytes": 194449408, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84295147520, "gtt_total_bytes": 193273528320} +{"t_s": 490.61, "VmRSS_bytes": 84416024576, "VmHWM_bytes": 84416024576, "Pss_bytes": 84413793280, "vram_used_bytes": 194449408, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84295147520, "gtt_total_bytes": 193273528320} +{"t_s": 491.9, "VmRSS_bytes": 84345286656, "VmHWM_bytes": 84411084800, "Pss_bytes": 84343048192, "vram_used_bytes": 194318336, "vram_total_bytes": 4294967296, "gtt_used_bytes": 475766784, "gtt_total_bytes": 193273528320} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-serial-new-r1-memory-endpoint.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-serial-new-r1-memory-endpoint.json new file mode 100644 index 0000000000..d99e95430f --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-serial-new-r1-memory-endpoint.json @@ -0,0 +1 @@ +{"schema_version": 1, "context_window": 19456, "context_fitted": false, "device": {"active_bytes": 87827794580, "cache_bytes": 0, "peak_bytes": 87828499364, "peak_scope": "since_start_or_health_reset"}} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-serial-new-r1-metrics.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-serial-new-r1-metrics.txt new file mode 100644 index 0000000000..6eddfe4160 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-serial-new-r1-metrics.txt @@ -0,0 +1,220 @@ +# HELP tensorfold:requests_running Requests in prefill or decode. +# TYPE tensorfold:requests_running gauge +tensorfold:requests_running 0 +# HELP tensorfold:requests_waiting Requests queued or held until a lane is free. +# TYPE tensorfold:requests_waiting gauge +tensorfold:requests_waiting 0 +# HELP tensorfold:generation_tokens_running Generated tokens held by live streams. +# TYPE tensorfold:generation_tokens_running gauge +tensorfold:generation_tokens_running 0 +# HELP tensorfold:prompt_tokens_total Prompt tokens of finished requests. +# TYPE tensorfold:prompt_tokens_total counter +tensorfold:prompt_tokens_total 114688 +# HELP tensorfold:generation_tokens_total Generated tokens of finished requests. +# TYPE tensorfold:generation_tokens_total counter +tensorfold:generation_tokens_total 3856 +# HELP tensorfold:kv_cache_usage_ratio Tokens in a stream cache divided by that stream's context window. +# TYPE tensorfold:kv_cache_usage_ratio gauge +tensorfold:kv_cache_usage_ratio{pool="0"} 0 +# HELP tensorfold:mtp_drafted_total Draft tokens verified on finished requests. +# TYPE tensorfold:mtp_drafted_total counter +tensorfold:mtp_drafted_total 0 +# HELP tensorfold:mtp_accepted_total Draft tokens kept on finished requests. +# TYPE tensorfold:mtp_accepted_total counter +tensorfold:mtp_accepted_total 0 +# HELP tensorfold:request_latency_seconds Seconds from arrival to the reply leaving. +# TYPE tensorfold:request_latency_seconds histogram +tensorfold:request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:request_latency_seconds_bucket{le="1"} 0 +tensorfold:request_latency_seconds_bucket{le="2.5"} 0 +tensorfold:request_latency_seconds_bucket{le="5"} 0 +tensorfold:request_latency_seconds_bucket{le="10"} 0 +tensorfold:request_latency_seconds_bucket{le="30"} 0 +tensorfold:request_latency_seconds_bucket{le="60"} 7 +tensorfold:request_latency_seconds_bucket{le="120"} 7 +tensorfold:request_latency_seconds_bucket{le="300"} 7 +tensorfold:request_latency_seconds_bucket{le="+Inf"} 7 +tensorfold:request_latency_seconds_sum 321.926675 +tensorfold:request_latency_seconds_count 7 +# HELP tensorfold:time_to_first_token_seconds Seconds from arrival to the first generated token. +# TYPE tensorfold:time_to_first_token_seconds histogram +tensorfold:time_to_first_token_seconds_bucket{le="0.01"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.05"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.25"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.5"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="2.5"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="5"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="10"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="30"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="60"} 7 +tensorfold:time_to_first_token_seconds_bucket{le="120"} 7 +tensorfold:time_to_first_token_seconds_bucket{le="300"} 7 +tensorfold:time_to_first_token_seconds_bucket{le="+Inf"} 7 +tensorfold:time_to_first_token_seconds_sum 214.260054 +tensorfold:time_to_first_token_seconds_count 7 +# HELP tensorfold:request_decode_seconds Seconds a finished request spent decoding. Its sum over generation_tokens_total is the decode rate. +# TYPE tensorfold:request_decode_seconds histogram +tensorfold:request_decode_seconds_bucket{le="0.01"} 0 +tensorfold:request_decode_seconds_bucket{le="0.05"} 0 +tensorfold:request_decode_seconds_bucket{le="0.1"} 0 +tensorfold:request_decode_seconds_bucket{le="0.25"} 0 +tensorfold:request_decode_seconds_bucket{le="0.5"} 1 +tensorfold:request_decode_seconds_bucket{le="1"} 1 +tensorfold:request_decode_seconds_bucket{le="2.5"} 1 +tensorfold:request_decode_seconds_bucket{le="5"} 1 +tensorfold:request_decode_seconds_bucket{le="10"} 4 +tensorfold:request_decode_seconds_bucket{le="30"} 7 +tensorfold:request_decode_seconds_bucket{le="60"} 7 +tensorfold:request_decode_seconds_bucket{le="120"} 7 +tensorfold:request_decode_seconds_bucket{le="300"} 7 +tensorfold:request_decode_seconds_bucket{le="+Inf"} 7 +tensorfold:request_decode_seconds_sum 107.666621 +tensorfold:request_decode_seconds_count 7 +# HELP tensorfold:request_time_per_output_token_seconds Seconds from the first generated token to the last, divided by the tokens less one. +# TYPE tensorfold:request_time_per_output_token_seconds histogram +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.005"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.01"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.015"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.02"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.03"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.04"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.05"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.075"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.1"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.15"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.2"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.3"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.5"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="1"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="+Inf"} 7 +tensorfold:request_time_per_output_token_seconds_sum 0.195642 +tensorfold:request_time_per_output_token_seconds_count 7 +# HELP tensorfold:decode_rounds_total Decode rounds used by finished requests. +# TYPE tensorfold:decode_rounds_total counter +tensorfold:decode_rounds_total 3849 +# HELP tensorfold:request_prefill_seconds Seconds a finished request's prompt pass took. +# TYPE tensorfold:request_prefill_seconds histogram +tensorfold:request_prefill_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.5"} 0 +tensorfold:request_prefill_seconds_bucket{le="1"} 0 +tensorfold:request_prefill_seconds_bucket{le="2.5"} 0 +tensorfold:request_prefill_seconds_bucket{le="5"} 0 +tensorfold:request_prefill_seconds_bucket{le="10"} 0 +tensorfold:request_prefill_seconds_bucket{le="30"} 0 +tensorfold:request_prefill_seconds_bucket{le="60"} 7 +tensorfold:request_prefill_seconds_bucket{le="120"} 7 +tensorfold:request_prefill_seconds_bucket{le="300"} 7 +tensorfold:request_prefill_seconds_bucket{le="+Inf"} 7 +tensorfold:request_prefill_seconds_sum 214.139426 +tensorfold:request_prefill_seconds_count 7 +# HELP tensorfold:process_resident_bytes Current resident set (VmRSS); device memory is not in it, so it is not a physical footprint (Linux). +# TYPE tensorfold:process_resident_bytes gauge +tensorfold:process_resident_bytes 105201655808 +# HELP tensorfold:process_resident_anon_bytes Current resident anonymous memory (RssAnon): heap, stacks and private maps (Linux). +# TYPE tensorfold:process_resident_anon_bytes gauge +tensorfold:process_resident_anon_bytes 32367091712 +# HELP tensorfold:process_resident_file_bytes Current resident file-backed memory (RssFile): the binary, libraries and mapped files (Linux). +# TYPE tensorfold:process_resident_file_bytes gauge +tensorfold:process_resident_file_bytes 72700301312 +# HELP tensorfold:process_resident_shmem_bytes Current resident shared memory (RssShmem): System V shared memory, tmpfs maps and shared anonymous maps (Linux). +# TYPE tensorfold:process_resident_shmem_bytes gauge +tensorfold:process_resident_shmem_bytes 134262784 +# HELP tensorfold:process_resident_peak_bytes Kernel lifetime peak resident set (VmHWM); never reset by health (Linux). +# TYPE tensorfold:process_resident_peak_bytes gauge +tensorfold:process_resident_peak_bytes 112717910016 +# HELP tensorfold:device_memory_bytes Device memory the engine holds now: weights, caches and live streams; only where the backend counts it (CUDA). +# TYPE tensorfold:device_memory_bytes gauge +tensorfold:device_memory_bytes 87827794580 +# HELP tensorfold:device_memory_peak_bytes The most device memory the engine has held since start or the last /health?reset_peak=1. +# TYPE tensorfold:device_memory_peak_bytes gauge +tensorfold:device_memory_peak_bytes 87828499364 +# HELP tensorfold:pinned_memory_bytes Pinned host memory the engine holds now: staging buffers and windows; only where the backend counts it (CUDA). +# TYPE tensorfold:pinned_memory_bytes gauge +tensorfold:pinned_memory_bytes 0 +# HELP tensorfold:num_requests_running Requests in prefill or decode. A mirror of tensorfold:requests_running. +# TYPE tensorfold:num_requests_running gauge +tensorfold:num_requests_running 0 +# HELP tensorfold:num_requests_waiting Requests queued or held until a lane is free. A mirror of tensorfold:requests_waiting. +# TYPE tensorfold:num_requests_waiting gauge +tensorfold:num_requests_waiting 0 +# HELP tensorfold:kv_cache_usage_perc A stream's cache occupancy under vLLM's name; same streams and ratios as tensorfold:kv_cache_usage_ratio. +# TYPE tensorfold:kv_cache_usage_perc gauge +tensorfold:kv_cache_usage_perc{stream="0"} 0 +# HELP tensorfold:spec_decode_num_draft_tokens_total Draft tokens verified on finished requests, this server's single draft counter. +# TYPE tensorfold:spec_decode_num_draft_tokens_total counter +tensorfold:spec_decode_num_draft_tokens_total 0 +# HELP tensorfold:spec_decode_num_accepted_tokens_total Draft tokens kept on finished requests. +# TYPE tensorfold:spec_decode_num_accepted_tokens_total counter +tensorfold:spec_decode_num_accepted_tokens_total 0 +# HELP tensorfold:e2e_request_latency_seconds Seconds from arrival to the reply leaving, under vLLM's name. +# TYPE tensorfold:e2e_request_latency_seconds histogram +tensorfold:e2e_request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="2.5"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="5"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="10"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="30"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="60"} 7 +tensorfold:e2e_request_latency_seconds_bucket{le="120"} 7 +tensorfold:e2e_request_latency_seconds_bucket{le="300"} 7 +tensorfold:e2e_request_latency_seconds_bucket{le="+Inf"} 7 +tensorfold:e2e_request_latency_seconds_sum 321.926675 +tensorfold:e2e_request_latency_seconds_count 7 +# HELP tensorfold:request_decode_time_seconds Seconds a finished request spent decoding, under vLLM's name. +# TYPE tensorfold:request_decode_time_seconds histogram +tensorfold:request_decode_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.5"} 1 +tensorfold:request_decode_time_seconds_bucket{le="1"} 1 +tensorfold:request_decode_time_seconds_bucket{le="2.5"} 1 +tensorfold:request_decode_time_seconds_bucket{le="5"} 1 +tensorfold:request_decode_time_seconds_bucket{le="10"} 4 +tensorfold:request_decode_time_seconds_bucket{le="30"} 7 +tensorfold:request_decode_time_seconds_bucket{le="60"} 7 +tensorfold:request_decode_time_seconds_bucket{le="120"} 7 +tensorfold:request_decode_time_seconds_bucket{le="300"} 7 +tensorfold:request_decode_time_seconds_bucket{le="+Inf"} 7 +tensorfold:request_decode_time_seconds_sum 107.666621 +tensorfold:request_decode_time_seconds_count 7 +# HELP tensorfold:request_prefill_time_seconds Seconds a finished request's prompt pass took, under vLLM's name. +# TYPE tensorfold:request_prefill_time_seconds histogram +tensorfold:request_prefill_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.5"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="2.5"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="5"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="10"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="30"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="60"} 7 +tensorfold:request_prefill_time_seconds_bucket{le="120"} 7 +tensorfold:request_prefill_time_seconds_bucket{le="300"} 7 +tensorfold:request_prefill_time_seconds_bucket{le="+Inf"} 7 +tensorfold:request_prefill_time_seconds_sum 214.139426 +tensorfold:request_prefill_time_seconds_count 7 +# HELP tensorfold:client_disconnections_total Requests a client left before the reply left the server. +# TYPE tensorfold:client_disconnections_total counter +tensorfold:client_disconnections_total 0 +# HELP tensorfold:preemptions_total Requests that had to give a lane up to a later one. +# TYPE tensorfold:preemptions_total counter +tensorfold:preemptions_total 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-serial-new-r1-samples.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-serial-new-r1-samples.jsonl new file mode 100644 index 0000000000..9e643a81a1 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-serial-new-r1-samples.jsonl @@ -0,0 +1,291 @@ +{"t_s": 0.0, "VmRSS_bytes": 74838016, "VmHWM_bytes": 74838016, "Pss_bytes": 72761344, 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193273528320} +{"t_s": 356.19, "VmRSS_bytes": 105236369408, "VmHWM_bytes": 112717910016, "Pss_bytes": 105234016256, "vram_used_bytes": 199737344, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88795144192, "gtt_total_bytes": 193273528320} +{"t_s": 357.48, "VmRSS_bytes": 105236144128, "VmHWM_bytes": 112717910016, "Pss_bytes": 105233790976, "vram_used_bytes": 199737344, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88795144192, "gtt_total_bytes": 193273528320} +{"t_s": 358.79, "VmRSS_bytes": 105236189184, "VmHWM_bytes": 112717910016, "Pss_bytes": 105233836032, "vram_used_bytes": 199737344, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88795144192, "gtt_total_bytes": 193273528320} +{"t_s": 360.09, "VmRSS_bytes": 105213812736, "VmHWM_bytes": 112717910016, "Pss_bytes": 105205164032, "vram_used_bytes": 199737344, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88795144192, "gtt_total_bytes": 193273528320} +{"t_s": 361.36, "VmRSS_bytes": 105203359744, "VmHWM_bytes": 112717910016, "Pss_bytes": 105200887808, "vram_used_bytes": 199737344, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88795144192, "gtt_total_bytes": 193273528320} +{"t_s": 362.54, "VmRSS_bytes": 89197465600, "VmHWM_bytes": 112717910016, "Pss_bytes": 87370869760, "vram_used_bytes": 194117632, "vram_total_bytes": 4294967296, "gtt_used_bytes": 204288000, "gtt_total_bytes": 193273528320} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-serial-new-r2-memory-endpoint.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-serial-new-r2-memory-endpoint.json new file mode 100644 index 0000000000..d99e95430f --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-serial-new-r2-memory-endpoint.json @@ -0,0 +1 @@ +{"schema_version": 1, "context_window": 19456, "context_fitted": false, "device": {"active_bytes": 87827794580, "cache_bytes": 0, "peak_bytes": 87828499364, "peak_scope": "since_start_or_health_reset"}} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-serial-new-r2-metrics.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-serial-new-r2-metrics.txt new file mode 100644 index 0000000000..3810edfdfe --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-serial-new-r2-metrics.txt @@ -0,0 +1,220 @@ +# HELP tensorfold:requests_running Requests in prefill or decode. +# TYPE tensorfold:requests_running gauge +tensorfold:requests_running 0 +# HELP tensorfold:requests_waiting Requests queued or held until a lane is free. +# TYPE tensorfold:requests_waiting gauge +tensorfold:requests_waiting 0 +# HELP tensorfold:generation_tokens_running Generated tokens held by live streams. +# TYPE tensorfold:generation_tokens_running gauge +tensorfold:generation_tokens_running 0 +# HELP tensorfold:prompt_tokens_total Prompt tokens of finished requests. +# TYPE tensorfold:prompt_tokens_total counter +tensorfold:prompt_tokens_total 114688 +# HELP tensorfold:generation_tokens_total Generated tokens of finished requests. +# TYPE tensorfold:generation_tokens_total counter +tensorfold:generation_tokens_total 3856 +# HELP tensorfold:kv_cache_usage_ratio Tokens in a stream cache divided by that stream's context window. +# TYPE tensorfold:kv_cache_usage_ratio gauge +tensorfold:kv_cache_usage_ratio{pool="0"} 0 +# HELP tensorfold:mtp_drafted_total Draft tokens verified on finished requests. +# TYPE tensorfold:mtp_drafted_total counter +tensorfold:mtp_drafted_total 0 +# HELP tensorfold:mtp_accepted_total Draft tokens kept on finished requests. +# TYPE tensorfold:mtp_accepted_total counter +tensorfold:mtp_accepted_total 0 +# HELP tensorfold:request_latency_seconds Seconds from arrival to the reply leaving. +# TYPE tensorfold:request_latency_seconds histogram +tensorfold:request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:request_latency_seconds_bucket{le="1"} 0 +tensorfold:request_latency_seconds_bucket{le="2.5"} 0 +tensorfold:request_latency_seconds_bucket{le="5"} 0 +tensorfold:request_latency_seconds_bucket{le="10"} 0 +tensorfold:request_latency_seconds_bucket{le="30"} 0 +tensorfold:request_latency_seconds_bucket{le="60"} 7 +tensorfold:request_latency_seconds_bucket{le="120"} 7 +tensorfold:request_latency_seconds_bucket{le="300"} 7 +tensorfold:request_latency_seconds_bucket{le="+Inf"} 7 +tensorfold:request_latency_seconds_sum 323.357226 +tensorfold:request_latency_seconds_count 7 +# HELP tensorfold:time_to_first_token_seconds Seconds from arrival to the first generated token. +# TYPE tensorfold:time_to_first_token_seconds histogram +tensorfold:time_to_first_token_seconds_bucket{le="0.01"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.05"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.25"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.5"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="2.5"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="5"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="10"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="30"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="60"} 7 +tensorfold:time_to_first_token_seconds_bucket{le="120"} 7 +tensorfold:time_to_first_token_seconds_bucket{le="300"} 7 +tensorfold:time_to_first_token_seconds_bucket{le="+Inf"} 7 +tensorfold:time_to_first_token_seconds_sum 215.18213 +tensorfold:time_to_first_token_seconds_count 7 +# HELP tensorfold:request_decode_seconds Seconds a finished request spent decoding. Its sum over generation_tokens_total is the decode rate. +# TYPE tensorfold:request_decode_seconds histogram +tensorfold:request_decode_seconds_bucket{le="0.01"} 0 +tensorfold:request_decode_seconds_bucket{le="0.05"} 0 +tensorfold:request_decode_seconds_bucket{le="0.1"} 0 +tensorfold:request_decode_seconds_bucket{le="0.25"} 0 +tensorfold:request_decode_seconds_bucket{le="0.5"} 1 +tensorfold:request_decode_seconds_bucket{le="1"} 1 +tensorfold:request_decode_seconds_bucket{le="2.5"} 1 +tensorfold:request_decode_seconds_bucket{le="5"} 1 +tensorfold:request_decode_seconds_bucket{le="10"} 4 +tensorfold:request_decode_seconds_bucket{le="30"} 7 +tensorfold:request_decode_seconds_bucket{le="60"} 7 +tensorfold:request_decode_seconds_bucket{le="120"} 7 +tensorfold:request_decode_seconds_bucket{le="300"} 7 +tensorfold:request_decode_seconds_bucket{le="+Inf"} 7 +tensorfold:request_decode_seconds_sum 108.175096 +tensorfold:request_decode_seconds_count 7 +# HELP tensorfold:request_time_per_output_token_seconds Seconds from the first generated token to the last, divided by the tokens less one. +# TYPE tensorfold:request_time_per_output_token_seconds histogram +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.005"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.01"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.015"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.02"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.03"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.04"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.05"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.075"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.1"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.15"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.2"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.3"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.5"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="1"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="+Inf"} 7 +tensorfold:request_time_per_output_token_seconds_sum 0.196136 +tensorfold:request_time_per_output_token_seconds_count 7 +# HELP tensorfold:decode_rounds_total Decode rounds used by finished requests. +# TYPE tensorfold:decode_rounds_total counter +tensorfold:decode_rounds_total 3849 +# HELP tensorfold:request_prefill_seconds Seconds a finished request's prompt pass took. +# TYPE tensorfold:request_prefill_seconds histogram +tensorfold:request_prefill_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.5"} 0 +tensorfold:request_prefill_seconds_bucket{le="1"} 0 +tensorfold:request_prefill_seconds_bucket{le="2.5"} 0 +tensorfold:request_prefill_seconds_bucket{le="5"} 0 +tensorfold:request_prefill_seconds_bucket{le="10"} 0 +tensorfold:request_prefill_seconds_bucket{le="30"} 0 +tensorfold:request_prefill_seconds_bucket{le="60"} 7 +tensorfold:request_prefill_seconds_bucket{le="120"} 7 +tensorfold:request_prefill_seconds_bucket{le="300"} 7 +tensorfold:request_prefill_seconds_bucket{le="+Inf"} 7 +tensorfold:request_prefill_seconds_sum 215.177528 +tensorfold:request_prefill_seconds_count 7 +# HELP tensorfold:process_resident_bytes Current resident set (VmRSS); device memory is not in it, so it is not a physical footprint (Linux). +# TYPE tensorfold:process_resident_bytes gauge +tensorfold:process_resident_bytes 105292464128 +# HELP tensorfold:process_resident_anon_bytes Current resident anonymous memory (RssAnon): heap, stacks and private maps (Linux). +# TYPE tensorfold:process_resident_anon_bytes gauge +tensorfold:process_resident_anon_bytes 32368443392 +# HELP tensorfold:process_resident_file_bytes Current resident file-backed memory (RssFile): the binary, libraries and mapped files (Linux). +# TYPE tensorfold:process_resident_file_bytes gauge +tensorfold:process_resident_file_bytes 72789757952 +# HELP tensorfold:process_resident_shmem_bytes Current resident shared memory (RssShmem): System V shared memory, tmpfs maps and shared anonymous maps (Linux). +# TYPE tensorfold:process_resident_shmem_bytes gauge +tensorfold:process_resident_shmem_bytes 134262784 +# HELP tensorfold:process_resident_peak_bytes Kernel lifetime peak resident set (VmHWM); never reset by health (Linux). +# TYPE tensorfold:process_resident_peak_bytes gauge +tensorfold:process_resident_peak_bytes 112507715584 +# HELP tensorfold:device_memory_bytes Device memory the engine holds now: weights, caches and live streams; only where the backend counts it (CUDA). +# TYPE tensorfold:device_memory_bytes gauge +tensorfold:device_memory_bytes 87827794580 +# HELP tensorfold:device_memory_peak_bytes The most device memory the engine has held since start or the last /health?reset_peak=1. +# TYPE tensorfold:device_memory_peak_bytes gauge +tensorfold:device_memory_peak_bytes 87828499364 +# HELP tensorfold:pinned_memory_bytes Pinned host memory the engine holds now: staging buffers and windows; only where the backend counts it (CUDA). +# TYPE tensorfold:pinned_memory_bytes gauge +tensorfold:pinned_memory_bytes 0 +# HELP tensorfold:num_requests_running Requests in prefill or decode. A mirror of tensorfold:requests_running. +# TYPE tensorfold:num_requests_running gauge +tensorfold:num_requests_running 0 +# HELP tensorfold:num_requests_waiting Requests queued or held until a lane is free. A mirror of tensorfold:requests_waiting. +# TYPE tensorfold:num_requests_waiting gauge +tensorfold:num_requests_waiting 0 +# HELP tensorfold:kv_cache_usage_perc A stream's cache occupancy under vLLM's name; same streams and ratios as tensorfold:kv_cache_usage_ratio. +# TYPE tensorfold:kv_cache_usage_perc gauge +tensorfold:kv_cache_usage_perc{stream="0"} 0 +# HELP tensorfold:spec_decode_num_draft_tokens_total Draft tokens verified on finished requests, this server's single draft counter. +# TYPE tensorfold:spec_decode_num_draft_tokens_total counter +tensorfold:spec_decode_num_draft_tokens_total 0 +# HELP tensorfold:spec_decode_num_accepted_tokens_total Draft tokens kept on finished requests. +# TYPE tensorfold:spec_decode_num_accepted_tokens_total counter +tensorfold:spec_decode_num_accepted_tokens_total 0 +# HELP tensorfold:e2e_request_latency_seconds Seconds from arrival to the reply leaving, under vLLM's name. +# TYPE tensorfold:e2e_request_latency_seconds histogram +tensorfold:e2e_request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="2.5"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="5"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="10"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="30"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="60"} 7 +tensorfold:e2e_request_latency_seconds_bucket{le="120"} 7 +tensorfold:e2e_request_latency_seconds_bucket{le="300"} 7 +tensorfold:e2e_request_latency_seconds_bucket{le="+Inf"} 7 +tensorfold:e2e_request_latency_seconds_sum 323.357226 +tensorfold:e2e_request_latency_seconds_count 7 +# HELP tensorfold:request_decode_time_seconds Seconds a finished request spent decoding, under vLLM's name. +# TYPE tensorfold:request_decode_time_seconds histogram +tensorfold:request_decode_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.5"} 1 +tensorfold:request_decode_time_seconds_bucket{le="1"} 1 +tensorfold:request_decode_time_seconds_bucket{le="2.5"} 1 +tensorfold:request_decode_time_seconds_bucket{le="5"} 1 +tensorfold:request_decode_time_seconds_bucket{le="10"} 4 +tensorfold:request_decode_time_seconds_bucket{le="30"} 7 +tensorfold:request_decode_time_seconds_bucket{le="60"} 7 +tensorfold:request_decode_time_seconds_bucket{le="120"} 7 +tensorfold:request_decode_time_seconds_bucket{le="300"} 7 +tensorfold:request_decode_time_seconds_bucket{le="+Inf"} 7 +tensorfold:request_decode_time_seconds_sum 108.175096 +tensorfold:request_decode_time_seconds_count 7 +# HELP tensorfold:request_prefill_time_seconds Seconds a finished request's prompt pass took, under vLLM's name. +# TYPE tensorfold:request_prefill_time_seconds histogram +tensorfold:request_prefill_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.5"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="2.5"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="5"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="10"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="30"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="60"} 7 +tensorfold:request_prefill_time_seconds_bucket{le="120"} 7 +tensorfold:request_prefill_time_seconds_bucket{le="300"} 7 +tensorfold:request_prefill_time_seconds_bucket{le="+Inf"} 7 +tensorfold:request_prefill_time_seconds_sum 215.177528 +tensorfold:request_prefill_time_seconds_count 7 +# HELP tensorfold:client_disconnections_total Requests a client left before the reply left the server. +# TYPE tensorfold:client_disconnections_total counter +tensorfold:client_disconnections_total 0 +# HELP tensorfold:preemptions_total Requests that had to give a lane up to a later one. +# TYPE tensorfold:preemptions_total counter +tensorfold:preemptions_total 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-serial-new-r2-samples.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-serial-new-r2-samples.jsonl new file mode 100644 index 0000000000..1315e8068a --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/d16k-serial-new-r2-samples.jsonl @@ -0,0 +1,274 @@ +{"t_s": 0.0, "VmRSS_bytes": 74330112, "VmHWM_bytes": 74330112, "Pss_bytes": 72285184, "vram_used_bytes": 187682816, "vram_total_bytes": 4294967296, "gtt_used_bytes": 31657984, "gtt_total_bytes": 193273528320} +{"t_s": 1.04, "VmRSS_bytes": 9584943104, "VmHWM_bytes": 9584943104, "Pss_bytes": 9621147648, "vram_used_bytes": 188792832, "vram_total_bytes": 4294967296, "gtt_used_bytes": 6841233408, "gtt_total_bytes": 193273528320} +{"t_s": 2.11, "VmRSS_bytes": 18063699968, "VmHWM_bytes": 18063699968, "Pss_bytes": 18088828928, "vram_used_bytes": 189341696, "vram_total_bytes": 4294967296, "gtt_used_bytes": 15062069248, "gtt_total_bytes": 193273528320} +{"t_s": 3.2, "VmRSS_bytes": 26493628416, "VmHWM_bytes": 26493628416, "Pss_bytes": 26491232256, "vram_used_bytes": 190042112, "vram_total_bytes": 4294967296, "gtt_used_bytes": 24910295040, "gtt_total_bytes": 193273528320} +{"t_s": 4.31, "VmRSS_bytes": 36074172416, "VmHWM_bytes": 36074172416, "Pss_bytes": 36071776256, "vram_used_bytes": 190529536, "vram_total_bytes": 4294967296, "gtt_used_bytes": 33131130880, "gtt_total_bytes": 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"gtt_total_bytes": 193273528320} +{"t_s": 350.29, "VmRSS_bytes": 105294155776, "VmHWM_bytes": 112507715584, "Pss_bytes": 105291712512, "vram_used_bytes": 203587584, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88795144192, "gtt_total_bytes": 193273528320} +{"t_s": 351.52, "VmRSS_bytes": 97790590976, "VmHWM_bytes": 112507715584, "Pss_bytes": 96711644160, "vram_used_bytes": 194420736, "vram_total_bytes": 4294967296, "gtt_used_bytes": 204288000, "gtt_total_bytes": 193273528320} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/decode-base-r1-memory-endpoint.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/decode-base-r1-memory-endpoint.json new file mode 100644 index 0000000000..4342988719 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/decode-base-r1-memory-endpoint.json @@ -0,0 +1 @@ +{"schema_version": 1, "context_window": 16384, "context_fitted": false, "device": {"active_bytes": 86454555072, "cache_bytes": 0, "peak_bytes": 86459451856, "peak_scope": "since_start_or_health_reset"}} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/decode-base-r1-metrics.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/decode-base-r1-metrics.txt new file mode 100644 index 0000000000..4bcecd1934 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/decode-base-r1-metrics.txt @@ -0,0 +1,220 @@ +# HELP tensorfold:requests_running Requests in prefill or decode. +# TYPE tensorfold:requests_running gauge +tensorfold:requests_running 0 +# HELP tensorfold:requests_waiting Requests queued or held until a lane is free. +# TYPE tensorfold:requests_waiting gauge +tensorfold:requests_waiting 0 +# HELP tensorfold:generation_tokens_running Generated tokens held by live streams. +# TYPE tensorfold:generation_tokens_running gauge +tensorfold:generation_tokens_running 0 +# HELP tensorfold:prompt_tokens_total Prompt tokens of finished requests. +# TYPE tensorfold:prompt_tokens_total counter +tensorfold:prompt_tokens_total 990 +# HELP tensorfold:generation_tokens_total Generated tokens of finished requests. +# TYPE tensorfold:generation_tokens_total counter +tensorfold:generation_tokens_total 10784 +# HELP tensorfold:kv_cache_usage_ratio Tokens in a stream cache divided by that stream's context window. +# TYPE tensorfold:kv_cache_usage_ratio gauge +tensorfold:kv_cache_usage_ratio{pool="0"} 0 +# HELP tensorfold:mtp_drafted_total Draft tokens verified on finished requests. +# TYPE tensorfold:mtp_drafted_total counter +tensorfold:mtp_drafted_total 9288 +# HELP tensorfold:mtp_accepted_total Draft tokens kept on finished requests. +# TYPE tensorfold:mtp_accepted_total counter +tensorfold:mtp_accepted_total 6589 +# HELP tensorfold:request_latency_seconds Seconds from arrival to the reply leaving. +# TYPE tensorfold:request_latency_seconds histogram +tensorfold:request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:request_latency_seconds_bucket{le="1"} 2 +tensorfold:request_latency_seconds_bucket{le="2.5"} 2 +tensorfold:request_latency_seconds_bucket{le="5"} 3 +tensorfold:request_latency_seconds_bucket{le="10"} 20 +tensorfold:request_latency_seconds_bucket{le="30"} 44 +tensorfold:request_latency_seconds_bucket{le="60"} 44 +tensorfold:request_latency_seconds_bucket{le="120"} 44 +tensorfold:request_latency_seconds_bucket{le="300"} 44 +tensorfold:request_latency_seconds_bucket{le="+Inf"} 44 +tensorfold:request_latency_seconds_sum 417.491219 +tensorfold:request_latency_seconds_count 44 +# HELP tensorfold:time_to_first_token_seconds Seconds from arrival to the first generated token. +# TYPE tensorfold:time_to_first_token_seconds histogram +tensorfold:time_to_first_token_seconds_bucket{le="0.01"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.05"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.25"} 26 +tensorfold:time_to_first_token_seconds_bucket{le="0.5"} 36 +tensorfold:time_to_first_token_seconds_bucket{le="1"} 44 +tensorfold:time_to_first_token_seconds_bucket{le="2.5"} 44 +tensorfold:time_to_first_token_seconds_bucket{le="5"} 44 +tensorfold:time_to_first_token_seconds_bucket{le="10"} 44 +tensorfold:time_to_first_token_seconds_bucket{le="30"} 44 +tensorfold:time_to_first_token_seconds_bucket{le="60"} 44 +tensorfold:time_to_first_token_seconds_bucket{le="120"} 44 +tensorfold:time_to_first_token_seconds_bucket{le="300"} 44 +tensorfold:time_to_first_token_seconds_bucket{le="+Inf"} 44 +tensorfold:time_to_first_token_seconds_sum 15.339567 +tensorfold:time_to_first_token_seconds_count 44 +# HELP tensorfold:request_decode_seconds Seconds a finished request spent decoding. Its sum over generation_tokens_total is the decode rate. +# TYPE tensorfold:request_decode_seconds histogram +tensorfold:request_decode_seconds_bucket{le="0.01"} 0 +tensorfold:request_decode_seconds_bucket{le="0.05"} 0 +tensorfold:request_decode_seconds_bucket{le="0.1"} 0 +tensorfold:request_decode_seconds_bucket{le="0.25"} 0 +tensorfold:request_decode_seconds_bucket{le="0.5"} 1 +tensorfold:request_decode_seconds_bucket{le="1"} 2 +tensorfold:request_decode_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_seconds_bucket{le="5"} 6 +tensorfold:request_decode_seconds_bucket{le="10"} 20 +tensorfold:request_decode_seconds_bucket{le="30"} 44 +tensorfold:request_decode_seconds_bucket{le="60"} 44 +tensorfold:request_decode_seconds_bucket{le="120"} 44 +tensorfold:request_decode_seconds_bucket{le="300"} 44 +tensorfold:request_decode_seconds_bucket{le="+Inf"} 44 +tensorfold:request_decode_seconds_sum 402.151652 +tensorfold:request_decode_seconds_count 44 +# HELP tensorfold:request_time_per_output_token_seconds Seconds from the first generated token to the last, divided by the tokens less one. +# TYPE tensorfold:request_time_per_output_token_seconds histogram +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.005"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.01"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.015"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.02"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.025"} 15 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.03"} 17 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.04"} 20 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.05"} 32 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.075"} 44 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.1"} 44 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.15"} 44 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.2"} 44 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.3"} 44 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.5"} 44 +tensorfold:request_time_per_output_token_seconds_bucket{le="1"} 44 +tensorfold:request_time_per_output_token_seconds_bucket{le="+Inf"} 44 +tensorfold:request_time_per_output_token_seconds_sum 1.636437 +tensorfold:request_time_per_output_token_seconds_count 44 +# HELP tensorfold:decode_rounds_total Decode rounds used by finished requests. +# TYPE tensorfold:decode_rounds_total counter +tensorfold:decode_rounds_total 4171 +# HELP tensorfold:request_prefill_seconds Seconds a finished request's prompt pass took. +# TYPE tensorfold:request_prefill_seconds histogram +tensorfold:request_prefill_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.25"} 32 +tensorfold:request_prefill_seconds_bucket{le="0.5"} 40 +tensorfold:request_prefill_seconds_bucket{le="1"} 44 +tensorfold:request_prefill_seconds_bucket{le="2.5"} 44 +tensorfold:request_prefill_seconds_bucket{le="5"} 44 +tensorfold:request_prefill_seconds_bucket{le="10"} 44 +tensorfold:request_prefill_seconds_bucket{le="30"} 44 +tensorfold:request_prefill_seconds_bucket{le="60"} 44 +tensorfold:request_prefill_seconds_bucket{le="120"} 44 +tensorfold:request_prefill_seconds_bucket{le="300"} 44 +tensorfold:request_prefill_seconds_bucket{le="+Inf"} 44 +tensorfold:request_prefill_seconds_sum 12.057467 +tensorfold:request_prefill_seconds_count 44 +# HELP tensorfold:process_resident_bytes Current resident set (VmRSS); device memory is not in it, so it is not a physical footprint (Linux). +# TYPE tensorfold:process_resident_bytes gauge +tensorfold:process_resident_bytes 81357934592 +# HELP tensorfold:process_resident_anon_bytes Current resident anonymous memory (RssAnon): heap, stacks and private maps (Linux). +# TYPE tensorfold:process_resident_anon_bytes gauge +tensorfold:process_resident_anon_bytes 318464000 +# HELP tensorfold:process_resident_file_bytes Current resident file-backed memory (RssFile): the binary, libraries and mapped files (Linux). +# TYPE tensorfold:process_resident_file_bytes gauge +tensorfold:process_resident_file_bytes 80927567872 +# HELP tensorfold:process_resident_shmem_bytes Current resident shared memory (RssShmem): System V shared memory, tmpfs maps and shared anonymous maps (Linux). +# TYPE tensorfold:process_resident_shmem_bytes gauge +tensorfold:process_resident_shmem_bytes 111902720 +# HELP tensorfold:process_resident_peak_bytes Kernel lifetime peak resident set (VmHWM); never reset by health (Linux). +# TYPE tensorfold:process_resident_peak_bytes gauge +tensorfold:process_resident_peak_bytes 82468204544 +# HELP tensorfold:device_memory_bytes Device memory the engine holds now: weights, caches and live streams; only where the backend counts it (CUDA). +# TYPE tensorfold:device_memory_bytes gauge +tensorfold:device_memory_bytes 86454555072 +# HELP tensorfold:device_memory_peak_bytes The most device memory the engine has held since start or the last /health?reset_peak=1. +# TYPE tensorfold:device_memory_peak_bytes gauge +tensorfold:device_memory_peak_bytes 86459451856 +# HELP tensorfold:pinned_memory_bytes Pinned host memory the engine holds now: staging buffers and windows; only where the backend counts it (CUDA). +# TYPE tensorfold:pinned_memory_bytes gauge +tensorfold:pinned_memory_bytes 0 +# HELP tensorfold:num_requests_running Requests in prefill or decode. A mirror of tensorfold:requests_running. +# TYPE tensorfold:num_requests_running gauge +tensorfold:num_requests_running 0 +# HELP tensorfold:num_requests_waiting Requests queued or held until a lane is free. A mirror of tensorfold:requests_waiting. +# TYPE tensorfold:num_requests_waiting gauge +tensorfold:num_requests_waiting 0 +# HELP tensorfold:kv_cache_usage_perc A stream's cache occupancy under vLLM's name; same streams and ratios as tensorfold:kv_cache_usage_ratio. +# TYPE tensorfold:kv_cache_usage_perc gauge +tensorfold:kv_cache_usage_perc{stream="0"} 0 +# HELP tensorfold:spec_decode_num_draft_tokens_total Draft tokens verified on finished requests, this server's single draft counter. +# TYPE tensorfold:spec_decode_num_draft_tokens_total counter +tensorfold:spec_decode_num_draft_tokens_total 9288 +# HELP tensorfold:spec_decode_num_accepted_tokens_total Draft tokens kept on finished requests. +# TYPE tensorfold:spec_decode_num_accepted_tokens_total counter +tensorfold:spec_decode_num_accepted_tokens_total 6589 +# HELP tensorfold:e2e_request_latency_seconds Seconds from arrival to the reply leaving, under vLLM's name. +# TYPE tensorfold:e2e_request_latency_seconds histogram +tensorfold:e2e_request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="1"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="2.5"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="5"} 3 +tensorfold:e2e_request_latency_seconds_bucket{le="10"} 20 +tensorfold:e2e_request_latency_seconds_bucket{le="30"} 44 +tensorfold:e2e_request_latency_seconds_bucket{le="60"} 44 +tensorfold:e2e_request_latency_seconds_bucket{le="120"} 44 +tensorfold:e2e_request_latency_seconds_bucket{le="300"} 44 +tensorfold:e2e_request_latency_seconds_bucket{le="+Inf"} 44 +tensorfold:e2e_request_latency_seconds_sum 417.491219 +tensorfold:e2e_request_latency_seconds_count 44 +# HELP tensorfold:request_decode_time_seconds Seconds a finished request spent decoding, under vLLM's name. +# TYPE tensorfold:request_decode_time_seconds histogram +tensorfold:request_decode_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.5"} 1 +tensorfold:request_decode_time_seconds_bucket{le="1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="5"} 6 +tensorfold:request_decode_time_seconds_bucket{le="10"} 20 +tensorfold:request_decode_time_seconds_bucket{le="30"} 44 +tensorfold:request_decode_time_seconds_bucket{le="60"} 44 +tensorfold:request_decode_time_seconds_bucket{le="120"} 44 +tensorfold:request_decode_time_seconds_bucket{le="300"} 44 +tensorfold:request_decode_time_seconds_bucket{le="+Inf"} 44 +tensorfold:request_decode_time_seconds_sum 402.151652 +tensorfold:request_decode_time_seconds_count 44 +# HELP tensorfold:request_prefill_time_seconds Seconds a finished request's prompt pass took, under vLLM's name. +# TYPE tensorfold:request_prefill_time_seconds histogram +tensorfold:request_prefill_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.25"} 32 +tensorfold:request_prefill_time_seconds_bucket{le="0.5"} 40 +tensorfold:request_prefill_time_seconds_bucket{le="1"} 44 +tensorfold:request_prefill_time_seconds_bucket{le="2.5"} 44 +tensorfold:request_prefill_time_seconds_bucket{le="5"} 44 +tensorfold:request_prefill_time_seconds_bucket{le="10"} 44 +tensorfold:request_prefill_time_seconds_bucket{le="30"} 44 +tensorfold:request_prefill_time_seconds_bucket{le="60"} 44 +tensorfold:request_prefill_time_seconds_bucket{le="120"} 44 +tensorfold:request_prefill_time_seconds_bucket{le="300"} 44 +tensorfold:request_prefill_time_seconds_bucket{le="+Inf"} 44 +tensorfold:request_prefill_time_seconds_sum 12.057467 +tensorfold:request_prefill_time_seconds_count 44 +# HELP tensorfold:client_disconnections_total Requests a client left before the reply left the server. +# TYPE tensorfold:client_disconnections_total counter +tensorfold:client_disconnections_total 0 +# HELP tensorfold:preemptions_total Requests that had to give a lane up to a later one. +# TYPE tensorfold:preemptions_total counter +tensorfold:preemptions_total 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/decode-base-r1-samples.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/decode-base-r1-samples.jsonl new file mode 100644 index 0000000000..35ec0fe2ee --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/decode-base-r1-samples.jsonl @@ -0,0 +1,153 @@ +{"t_s": 0.0, "VmRSS_bytes": 40148992, "VmHWM_bytes": 40148992, "Pss_bytes": 38781952, "vram_used_bytes": 187670528, "vram_total_bytes": 4294967296, "gtt_used_bytes": 31657984, "gtt_total_bytes": 193273528320} +{"t_s": 1.04, "VmRSS_bytes": 9268465664, "VmHWM_bytes": 9268465664, "Pss_bytes": 9314625536, "vram_used_bytes": 188764160, "vram_total_bytes": 4294967296, "gtt_used_bytes": 6821748736, "gtt_total_bytes": 193273528320} +{"t_s": 2.1, "VmRSS_bytes": 16722829312, "VmHWM_bytes": 16722829312, "Pss_bytes": 16720492544, "vram_used_bytes": 189308928, "vram_total_bytes": 4294967296, "gtt_used_bytes": 15015321600, "gtt_total_bytes": 193273528320} +{"t_s": 3.21, "VmRSS_bytes": 24832974848, "VmHWM_bytes": 24832974848, "Pss_bytes": 24830768128, "vram_used_bytes": 189890560, "vram_total_bytes": 4294967296, "gtt_used_bytes": 23208894464, "gtt_total_bytes": 193273528320} +{"t_s": 4.35, "VmRSS_bytes": 33551310848, "VmHWM_bytes": 33551310848, "Pss_bytes": 33606072320, "vram_used_bytes": 190468096, "vram_total_bytes": 4294967296, "gtt_used_bytes": 31404564480, "gtt_total_bytes": 193273528320} +{"t_s": 5.49, "VmRSS_bytes": 39386300416, "VmHWM_bytes": 39386300416, "Pss_bytes": 39383963648, "vram_used_bytes": 190808064, "vram_total_bytes": 4294967296, "gtt_used_bytes": 37272395776, "gtt_total_bytes": 193273528320} +{"t_s": 6.67, "VmRSS_bytes": 43944464384, "VmHWM_bytes": 43944464384, "Pss_bytes": 44020705280, "vram_used_bytes": 191148032, "vram_total_bytes": 4294967296, "gtt_used_bytes": 41238110208, "gtt_total_bytes": 193273528320} +{"t_s": 7.86, "VmRSS_bytes": 50738765824, "VmHWM_bytes": 50738765824, "Pss_bytes": 50736429056, "vram_used_bytes": 191582208, "vram_total_bytes": 4294967296, "gtt_used_bytes": 48634765312, "gtt_total_bytes": 193273528320} +{"t_s": 9.06, "VmRSS_bytes": 58325184512, "VmHWM_bytes": 58325184512, "Pss_bytes": 58322847744, "vram_used_bytes": 192118784, "vram_total_bytes": 4294967296, "gtt_used_bytes": 55987380224, "gtt_total_bytes": 193273528320} +{"t_s": 10.29, "VmRSS_bytes": 66609037312, "VmHWM_bytes": 66609037312, "Pss_bytes": 66631079936, "vram_used_bytes": 192679936, "vram_total_bytes": 4294967296, "gtt_used_bytes": 64176758784, "gtt_total_bytes": 193273528320} +{"t_s": 11.53, "VmRSS_bytes": 75069267968, "VmHWM_bytes": 75069267968, "Pss_bytes": 75066931200, "vram_used_bytes": 193232896, "vram_total_bytes": 4294967296, "gtt_used_bytes": 73318244352, "gtt_total_bytes": 193273528320} +{"t_s": 12.79, "VmRSS_bytes": 80815697920, "VmHWM_bytes": 82468204544, "Pss_bytes": 80815056896, "vram_used_bytes": 194699264, "vram_total_bytes": 4294967296, "gtt_used_bytes": 83107749888, "gtt_total_bytes": 193273528320} +{"t_s": 14.05, "VmRSS_bytes": 80864137216, "VmHWM_bytes": 82468204544, "Pss_bytes": 80863574016, "vram_used_bytes": 194576384, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84170219520, "gtt_total_bytes": 193273528320} +{"t_s": 15.32, "VmRSS_bytes": 80900706304, "VmHWM_bytes": 82468204544, "Pss_bytes": 80901055488, "vram_used_bytes": 194580480, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84170641408, "gtt_total_bytes": 193273528320} +{"t_s": 16.59, "VmRSS_bytes": 80948617216, "VmHWM_bytes": 82468204544, "Pss_bytes": 80948149248, "vram_used_bytes": 194580480, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84171485184, "gtt_total_bytes": 193273528320} +{"t_s": 17.89, "VmRSS_bytes": 80983195648, "VmHWM_bytes": 82468204544, "Pss_bytes": 80986084352, "vram_used_bytes": 194580480, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84171485184, "gtt_total_bytes": 193273528320} +{"t_s": 19.23, "VmRSS_bytes": 81018523648, "VmHWM_bytes": 82468204544, "Pss_bytes": 81029301248, "vram_used_bytes": 194580480, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84171485184, "gtt_total_bytes": 193273528320} +{"t_s": 20.55, "VmRSS_bytes": 81060937728, "VmHWM_bytes": 82468204544, "Pss_bytes": 81058546688, "vram_used_bytes": 194580480, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84171485184, "gtt_total_bytes": 193273528320} +{"t_s": 21.9, "VmRSS_bytes": 81061011456, "VmHWM_bytes": 82468204544, "Pss_bytes": 81058608128, "vram_used_bytes": 194580480, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84171485184, "gtt_total_bytes": 193273528320} +{"t_s": 23.21, "VmRSS_bytes": 81061056512, "VmHWM_bytes": 82468204544, "Pss_bytes": 81058657280, "vram_used_bytes": 194580480, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84171485184, "gtt_total_bytes": 193273528320} +{"t_s": 24.51, "VmRSS_bytes": 81061101568, "VmHWM_bytes": 82468204544, "Pss_bytes": 81058714624, "vram_used_bytes": 194580480, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84171485184, "gtt_total_bytes": 193273528320} +{"t_s": 25.81, "VmRSS_bytes": 81060950016, "VmHWM_bytes": 82468204544, "Pss_bytes": 81058554880, "vram_used_bytes": 194580480, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84171485184, "gtt_total_bytes": 193273528320} +{"t_s": 27.16, "VmRSS_bytes": 81061003264, "VmHWM_bytes": 82468204544, "Pss_bytes": 81058608128, "vram_used_bytes": 194580480, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84171485184, "gtt_total_bytes": 193273528320} +{"t_s": 28.47, "VmRSS_bytes": 81061060608, "VmHWM_bytes": 82468204544, "Pss_bytes": 81058657280, "vram_used_bytes": 194580480, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84171485184, "gtt_total_bytes": 193273528320} +{"t_s": 29.78, "VmRSS_bytes": 81061097472, "VmHWM_bytes": 82468204544, "Pss_bytes": 81058709504, "vram_used_bytes": 194580480, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84171485184, "gtt_total_bytes": 193273528320} +{"t_s": 31.13, "VmRSS_bytes": 81060958208, "VmHWM_bytes": 82468204544, "Pss_bytes": 81058558976, "vram_used_bytes": 194580480, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84171485184, "gtt_total_bytes": 193273528320} +{"t_s": 32.43, "VmRSS_bytes": 81061011456, "VmHWM_bytes": 82468204544, "Pss_bytes": 81058608128, "vram_used_bytes": 194580480, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84171485184, "gtt_total_bytes": 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"gtt_used_bytes": 87352307712, "gtt_total_bytes": 193273528320} +{"t_s": 139.83, "VmRSS_bytes": 81322414080, "VmHWM_bytes": 82468204544, "Pss_bytes": 81320018944, "vram_used_bytes": 194519040, "vram_total_bytes": 4294967296, "gtt_used_bytes": 87352307712, "gtt_total_bytes": 193273528320} +{"t_s": 141.18, "VmRSS_bytes": 81322475520, "VmHWM_bytes": 82468204544, "Pss_bytes": 81320076288, "vram_used_bytes": 194519040, "vram_total_bytes": 4294967296, "gtt_used_bytes": 87352307712, "gtt_total_bytes": 193273528320} +{"t_s": 142.49, "VmRSS_bytes": 81322524672, "VmHWM_bytes": 82468204544, "Pss_bytes": 81320113152, "vram_used_bytes": 194519040, "vram_total_bytes": 4294967296, "gtt_used_bytes": 87352307712, "gtt_total_bytes": 193273528320} +{"t_s": 143.82, "VmRSS_bytes": 81322586112, "VmHWM_bytes": 82468204544, "Pss_bytes": 81320186880, "vram_used_bytes": 194519040, "vram_total_bytes": 4294967296, "gtt_used_bytes": 87352307712, "gtt_total_bytes": 193273528320} +{"t_s": 145.17, "VmRSS_bytes": 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+{"t_s": 197.84, "VmRSS_bytes": 81359728640, "VmHWM_bytes": 82468204544, "Pss_bytes": 81357321216, "vram_used_bytes": 194527232, "vram_total_bytes": 4294967296, "gtt_used_bytes": 87352872960, "gtt_total_bytes": 193273528320} +{"t_s": 199.11, "VmRSS_bytes": 81357746176, "VmHWM_bytes": 82468204544, "Pss_bytes": 81355347968, "vram_used_bytes": 194527232, "vram_total_bytes": 4294967296, "gtt_used_bytes": 87352872960, "gtt_total_bytes": 193273528320} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/decode-base-r2-memory-endpoint.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/decode-base-r2-memory-endpoint.json new file mode 100644 index 0000000000..4342988719 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/decode-base-r2-memory-endpoint.json @@ -0,0 +1 @@ +{"schema_version": 1, "context_window": 16384, "context_fitted": false, "device": {"active_bytes": 86454555072, "cache_bytes": 0, "peak_bytes": 86459451856, "peak_scope": "since_start_or_health_reset"}} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/decode-base-r2-metrics.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/decode-base-r2-metrics.txt new file mode 100644 index 0000000000..54bddb2ed9 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/decode-base-r2-metrics.txt @@ -0,0 +1,220 @@ +# HELP tensorfold:requests_running Requests in prefill or decode. +# TYPE tensorfold:requests_running gauge +tensorfold:requests_running 0 +# HELP tensorfold:requests_waiting Requests queued or held until a lane is free. +# TYPE tensorfold:requests_waiting gauge +tensorfold:requests_waiting 0 +# HELP tensorfold:generation_tokens_running Generated tokens held by live streams. +# TYPE tensorfold:generation_tokens_running gauge +tensorfold:generation_tokens_running 0 +# HELP tensorfold:prompt_tokens_total Prompt tokens of finished requests. +# TYPE tensorfold:prompt_tokens_total counter +tensorfold:prompt_tokens_total 990 +# HELP tensorfold:generation_tokens_total Generated tokens of finished requests. +# TYPE tensorfold:generation_tokens_total counter +tensorfold:generation_tokens_total 10784 +# HELP tensorfold:kv_cache_usage_ratio Tokens in a stream cache divided by that stream's context window. +# TYPE tensorfold:kv_cache_usage_ratio gauge +tensorfold:kv_cache_usage_ratio{pool="0"} 0 +# HELP tensorfold:mtp_drafted_total Draft tokens verified on finished requests. +# TYPE tensorfold:mtp_drafted_total counter +tensorfold:mtp_drafted_total 9288 +# HELP tensorfold:mtp_accepted_total Draft tokens kept on finished requests. +# TYPE tensorfold:mtp_accepted_total counter +tensorfold:mtp_accepted_total 6589 +# HELP tensorfold:request_latency_seconds Seconds from arrival to the reply leaving. +# TYPE tensorfold:request_latency_seconds histogram +tensorfold:request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:request_latency_seconds_bucket{le="1"} 2 +tensorfold:request_latency_seconds_bucket{le="2.5"} 2 +tensorfold:request_latency_seconds_bucket{le="5"} 3 +tensorfold:request_latency_seconds_bucket{le="10"} 20 +tensorfold:request_latency_seconds_bucket{le="30"} 44 +tensorfold:request_latency_seconds_bucket{le="60"} 44 +tensorfold:request_latency_seconds_bucket{le="120"} 44 +tensorfold:request_latency_seconds_bucket{le="300"} 44 +tensorfold:request_latency_seconds_bucket{le="+Inf"} 44 +tensorfold:request_latency_seconds_sum 421.71509 +tensorfold:request_latency_seconds_count 44 +# HELP tensorfold:time_to_first_token_seconds Seconds from arrival to the first generated token. +# TYPE tensorfold:time_to_first_token_seconds histogram +tensorfold:time_to_first_token_seconds_bucket{le="0.01"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.05"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.25"} 25 +tensorfold:time_to_first_token_seconds_bucket{le="0.5"} 35 +tensorfold:time_to_first_token_seconds_bucket{le="1"} 44 +tensorfold:time_to_first_token_seconds_bucket{le="2.5"} 44 +tensorfold:time_to_first_token_seconds_bucket{le="5"} 44 +tensorfold:time_to_first_token_seconds_bucket{le="10"} 44 +tensorfold:time_to_first_token_seconds_bucket{le="30"} 44 +tensorfold:time_to_first_token_seconds_bucket{le="60"} 44 +tensorfold:time_to_first_token_seconds_bucket{le="120"} 44 +tensorfold:time_to_first_token_seconds_bucket{le="300"} 44 +tensorfold:time_to_first_token_seconds_bucket{le="+Inf"} 44 +tensorfold:time_to_first_token_seconds_sum 15.464994 +tensorfold:time_to_first_token_seconds_count 44 +# HELP tensorfold:request_decode_seconds Seconds a finished request spent decoding. Its sum over generation_tokens_total is the decode rate. +# TYPE tensorfold:request_decode_seconds histogram +tensorfold:request_decode_seconds_bucket{le="0.01"} 0 +tensorfold:request_decode_seconds_bucket{le="0.05"} 0 +tensorfold:request_decode_seconds_bucket{le="0.1"} 0 +tensorfold:request_decode_seconds_bucket{le="0.25"} 0 +tensorfold:request_decode_seconds_bucket{le="0.5"} 1 +tensorfold:request_decode_seconds_bucket{le="1"} 2 +tensorfold:request_decode_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_seconds_bucket{le="5"} 4 +tensorfold:request_decode_seconds_bucket{le="10"} 20 +tensorfold:request_decode_seconds_bucket{le="30"} 44 +tensorfold:request_decode_seconds_bucket{le="60"} 44 +tensorfold:request_decode_seconds_bucket{le="120"} 44 +tensorfold:request_decode_seconds_bucket{le="300"} 44 +tensorfold:request_decode_seconds_bucket{le="+Inf"} 44 +tensorfold:request_decode_seconds_sum 406.250095 +tensorfold:request_decode_seconds_count 44 +# HELP tensorfold:request_time_per_output_token_seconds Seconds from the first generated token to the last, divided by the tokens less one. +# TYPE tensorfold:request_time_per_output_token_seconds histogram +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.005"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.01"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.015"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.02"} 6 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.025"} 16 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.03"} 17 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.04"} 20 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.05"} 32 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.075"} 44 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.1"} 44 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.15"} 44 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.2"} 44 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.3"} 44 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.5"} 44 +tensorfold:request_time_per_output_token_seconds_bucket{le="1"} 44 +tensorfold:request_time_per_output_token_seconds_bucket{le="+Inf"} 44 +tensorfold:request_time_per_output_token_seconds_sum 1.645176 +tensorfold:request_time_per_output_token_seconds_count 44 +# HELP tensorfold:decode_rounds_total Decode rounds used by finished requests. +# TYPE tensorfold:decode_rounds_total counter +tensorfold:decode_rounds_total 4171 +# HELP tensorfold:request_prefill_seconds Seconds a finished request's prompt pass took. +# TYPE tensorfold:request_prefill_seconds histogram +tensorfold:request_prefill_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.25"} 29 +tensorfold:request_prefill_seconds_bucket{le="0.5"} 40 +tensorfold:request_prefill_seconds_bucket{le="1"} 44 +tensorfold:request_prefill_seconds_bucket{le="2.5"} 44 +tensorfold:request_prefill_seconds_bucket{le="5"} 44 +tensorfold:request_prefill_seconds_bucket{le="10"} 44 +tensorfold:request_prefill_seconds_bucket{le="30"} 44 +tensorfold:request_prefill_seconds_bucket{le="60"} 44 +tensorfold:request_prefill_seconds_bucket{le="120"} 44 +tensorfold:request_prefill_seconds_bucket{le="300"} 44 +tensorfold:request_prefill_seconds_bucket{le="+Inf"} 44 +tensorfold:request_prefill_seconds_sum 12.658578 +tensorfold:request_prefill_seconds_count 44 +# HELP tensorfold:process_resident_bytes Current resident set (VmRSS); device memory is not in it, so it is not a physical footprint (Linux). +# TYPE tensorfold:process_resident_bytes gauge +tensorfold:process_resident_bytes 81359650816 +# HELP tensorfold:process_resident_anon_bytes Current resident anonymous memory (RssAnon): heap, stacks and private maps (Linux). +# TYPE tensorfold:process_resident_anon_bytes gauge +tensorfold:process_resident_anon_bytes 318951424 +# HELP tensorfold:process_resident_file_bytes Current resident file-backed memory (RssFile): the binary, libraries and mapped files (Linux). +# TYPE tensorfold:process_resident_file_bytes gauge +tensorfold:process_resident_file_bytes 80928796672 +# HELP tensorfold:process_resident_shmem_bytes Current resident shared memory (RssShmem): System V shared memory, tmpfs maps and shared anonymous maps (Linux). +# TYPE tensorfold:process_resident_shmem_bytes gauge +tensorfold:process_resident_shmem_bytes 111902720 +# HELP tensorfold:process_resident_peak_bytes Kernel lifetime peak resident set (VmHWM); never reset by health (Linux). +# TYPE tensorfold:process_resident_peak_bytes gauge +tensorfold:process_resident_peak_bytes 82468040704 +# HELP tensorfold:device_memory_bytes Device memory the engine holds now: weights, caches and live streams; only where the backend counts it (CUDA). +# TYPE tensorfold:device_memory_bytes gauge +tensorfold:device_memory_bytes 86454555072 +# HELP tensorfold:device_memory_peak_bytes The most device memory the engine has held since start or the last /health?reset_peak=1. +# TYPE tensorfold:device_memory_peak_bytes gauge +tensorfold:device_memory_peak_bytes 86459451856 +# HELP tensorfold:pinned_memory_bytes Pinned host memory the engine holds now: staging buffers and windows; only where the backend counts it (CUDA). +# TYPE tensorfold:pinned_memory_bytes gauge +tensorfold:pinned_memory_bytes 0 +# HELP tensorfold:num_requests_running Requests in prefill or decode. A mirror of tensorfold:requests_running. +# TYPE tensorfold:num_requests_running gauge +tensorfold:num_requests_running 0 +# HELP tensorfold:num_requests_waiting Requests queued or held until a lane is free. A mirror of tensorfold:requests_waiting. +# TYPE tensorfold:num_requests_waiting gauge +tensorfold:num_requests_waiting 0 +# HELP tensorfold:kv_cache_usage_perc A stream's cache occupancy under vLLM's name; same streams and ratios as tensorfold:kv_cache_usage_ratio. +# TYPE tensorfold:kv_cache_usage_perc gauge +tensorfold:kv_cache_usage_perc{stream="0"} 0 +# HELP tensorfold:spec_decode_num_draft_tokens_total Draft tokens verified on finished requests, this server's single draft counter. +# TYPE tensorfold:spec_decode_num_draft_tokens_total counter +tensorfold:spec_decode_num_draft_tokens_total 9288 +# HELP tensorfold:spec_decode_num_accepted_tokens_total Draft tokens kept on finished requests. +# TYPE tensorfold:spec_decode_num_accepted_tokens_total counter +tensorfold:spec_decode_num_accepted_tokens_total 6589 +# HELP tensorfold:e2e_request_latency_seconds Seconds from arrival to the reply leaving, under vLLM's name. +# TYPE tensorfold:e2e_request_latency_seconds histogram +tensorfold:e2e_request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="1"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="2.5"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="5"} 3 +tensorfold:e2e_request_latency_seconds_bucket{le="10"} 20 +tensorfold:e2e_request_latency_seconds_bucket{le="30"} 44 +tensorfold:e2e_request_latency_seconds_bucket{le="60"} 44 +tensorfold:e2e_request_latency_seconds_bucket{le="120"} 44 +tensorfold:e2e_request_latency_seconds_bucket{le="300"} 44 +tensorfold:e2e_request_latency_seconds_bucket{le="+Inf"} 44 +tensorfold:e2e_request_latency_seconds_sum 421.71509 +tensorfold:e2e_request_latency_seconds_count 44 +# HELP tensorfold:request_decode_time_seconds Seconds a finished request spent decoding, under vLLM's name. +# TYPE tensorfold:request_decode_time_seconds histogram +tensorfold:request_decode_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.5"} 1 +tensorfold:request_decode_time_seconds_bucket{le="1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="5"} 4 +tensorfold:request_decode_time_seconds_bucket{le="10"} 20 +tensorfold:request_decode_time_seconds_bucket{le="30"} 44 +tensorfold:request_decode_time_seconds_bucket{le="60"} 44 +tensorfold:request_decode_time_seconds_bucket{le="120"} 44 +tensorfold:request_decode_time_seconds_bucket{le="300"} 44 +tensorfold:request_decode_time_seconds_bucket{le="+Inf"} 44 +tensorfold:request_decode_time_seconds_sum 406.250095 +tensorfold:request_decode_time_seconds_count 44 +# HELP tensorfold:request_prefill_time_seconds Seconds a finished request's prompt pass took, under vLLM's name. +# TYPE tensorfold:request_prefill_time_seconds histogram +tensorfold:request_prefill_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.25"} 29 +tensorfold:request_prefill_time_seconds_bucket{le="0.5"} 40 +tensorfold:request_prefill_time_seconds_bucket{le="1"} 44 +tensorfold:request_prefill_time_seconds_bucket{le="2.5"} 44 +tensorfold:request_prefill_time_seconds_bucket{le="5"} 44 +tensorfold:request_prefill_time_seconds_bucket{le="10"} 44 +tensorfold:request_prefill_time_seconds_bucket{le="30"} 44 +tensorfold:request_prefill_time_seconds_bucket{le="60"} 44 +tensorfold:request_prefill_time_seconds_bucket{le="120"} 44 +tensorfold:request_prefill_time_seconds_bucket{le="300"} 44 +tensorfold:request_prefill_time_seconds_bucket{le="+Inf"} 44 +tensorfold:request_prefill_time_seconds_sum 12.658578 +tensorfold:request_prefill_time_seconds_count 44 +# HELP tensorfold:client_disconnections_total Requests a client left before the reply left the server. +# TYPE tensorfold:client_disconnections_total counter +tensorfold:client_disconnections_total 0 +# HELP tensorfold:preemptions_total Requests that had to give a lane up to a later one. +# TYPE tensorfold:preemptions_total counter +tensorfold:preemptions_total 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/decode-base-r2-samples.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/decode-base-r2-samples.jsonl new file mode 100644 index 0000000000..1540efbfbc --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/decode-base-r2-samples.jsonl @@ -0,0 +1,157 @@ +{"t_s": 0.0, "VmRSS_bytes": 52191232, "VmHWM_bytes": 52191232, "Pss_bytes": 52103168, "vram_used_bytes": 187670528, "vram_total_bytes": 4294967296, "gtt_used_bytes": 31657984, "gtt_total_bytes": 193273528320} +{"t_s": 1.03, "VmRSS_bytes": 8611282944, "VmHWM_bytes": 8611282944, "Pss_bytes": 8618811392, "vram_used_bytes": 188755968, "vram_total_bytes": 4294967296, "gtt_used_bytes": 6821748736, "gtt_total_bytes": 193273528320} +{"t_s": 2.09, "VmRSS_bytes": 16603000832, "VmHWM_bytes": 16603000832, "Pss_bytes": 16621998080, "vram_used_bytes": 189190144, "vram_total_bytes": 4294967296, "gtt_used_bytes": 13381640192, "gtt_total_bytes": 193273528320} +{"t_s": 3.2, "VmRSS_bytes": 23938588672, "VmHWM_bytes": 23938588672, "Pss_bytes": 23976678400, "vram_used_bytes": 189759488, "vram_total_bytes": 4294967296, "gtt_used_bytes": 21575213056, "gtt_total_bytes": 193273528320} +{"t_s": 4.32, "VmRSS_bytes": 32372662272, "VmHWM_bytes": 32372662272, "Pss_bytes": 32370294784, "vram_used_bytes": 190328832, "vram_total_bytes": 4294967296, "gtt_used_bytes": 29770883072, "gtt_total_bytes": 193273528320} +{"t_s": 5.48, "VmRSS_bytes": 39509794816, "VmHWM_bytes": 39509794816, "Pss_bytes": 39610187776, "vram_used_bytes": 190914560, "vram_total_bytes": 4294967296, "gtt_used_bytes": 37951873024, "gtt_total_bytes": 193273528320} +{"t_s": 6.66, "VmRSS_bytes": 44667711488, "VmHWM_bytes": 44667711488, "Pss_bytes": 44726956032, "vram_used_bytes": 191242240, "vram_total_bytes": 4294967296, "gtt_used_bytes": 42871791616, "gtt_total_bytes": 193273528320} +{"t_s": 7.84, "VmRSS_bytes": 46005473280, "VmHWM_bytes": 46005473280, "Pss_bytes": 46003302400, "vram_used_bytes": 191340544, "vram_total_bytes": 4294967296, "gtt_used_bytes": 44507570176, "gtt_total_bytes": 193273528320} +{"t_s": 9.03, "VmRSS_bytes": 46425206784, "VmHWM_bytes": 46425206784, "Pss_bytes": 46423339008, "vram_used_bytes": 191340544, "vram_total_bytes": 4294967296, "gtt_used_bytes": 44507570176, "gtt_total_bytes": 193273528320} +{"t_s": 10.22, "VmRSS_bytes": 46943576064, "VmHWM_bytes": 46943576064, "Pss_bytes": 46942396416, "vram_used_bytes": 191340544, "vram_total_bytes": 4294967296, "gtt_used_bytes": 44507570176, "gtt_total_bytes": 193273528320} +{"t_s": 11.44, "VmRSS_bytes": 51223261184, "VmHWM_bytes": 51223261184, "Pss_bytes": 51237408768, "vram_used_bytes": 191692800, "vram_total_bytes": 4294967296, "gtt_used_bytes": 49433780224, "gtt_total_bytes": 193273528320} +{"t_s": 12.67, "VmRSS_bytes": 58280865792, "VmHWM_bytes": 58280865792, "Pss_bytes": 58322407424, "vram_used_bytes": 192135168, "vram_total_bytes": 4294967296, "gtt_used_bytes": 55987380224, "gtt_total_bytes": 193273528320} +{"t_s": 13.91, "VmRSS_bytes": 66956779520, "VmHWM_bytes": 66956779520, "Pss_bytes": 66954412032, "vram_used_bytes": 192692224, "vram_total_bytes": 4294967296, "gtt_used_bytes": 65124671488, "gtt_total_bytes": 193273528320} +{"t_s": 15.17, "VmRSS_bytes": 75069120512, "VmHWM_bytes": 75069120512, "Pss_bytes": 75066753024, "vram_used_bytes": 193245184, "vram_total_bytes": 4294967296, "gtt_used_bytes": 73955778560, "gtt_total_bytes": 193273528320} +{"t_s": 16.44, "VmRSS_bytes": 80815382528, "VmHWM_bytes": 82468040704, "Pss_bytes": 80815108096, "vram_used_bytes": 194715648, "vram_total_bytes": 4294967296, "gtt_used_bytes": 82038202368, "gtt_total_bytes": 193273528320} +{"t_s": 17.72, "VmRSS_bytes": 80842018816, "VmHWM_bytes": 82468040704, "Pss_bytes": 80856547328, "vram_used_bytes": 194588672, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84168908800, "gtt_total_bytes": 193273528320} +{"t_s": 19.0, "VmRSS_bytes": 80895680512, "VmHWM_bytes": 82468040704, "Pss_bytes": 80893776896, "vram_used_bytes": 194596864, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84170641408, "gtt_total_bytes": 193273528320} +{"t_s": 20.32, "VmRSS_bytes": 80947912704, "VmHWM_bytes": 82468040704, "Pss_bytes": 80952505344, "vram_used_bytes": 194596864, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84171485184, "gtt_total_bytes": 193273528320} +{"t_s": 21.65, "VmRSS_bytes": 80988590080, "VmHWM_bytes": 82468040704, "Pss_bytes": 80990176256, "vram_used_bytes": 194596864, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84171485184, "gtt_total_bytes": 193273528320} +{"t_s": 22.96, "VmRSS_bytes": 81027768320, "VmHWM_bytes": 82468040704, "Pss_bytes": 81030849536, "vram_used_bytes": 194596864, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84171485184, "gtt_total_bytes": 193273528320} +{"t_s": 24.3, "VmRSS_bytes": 81062252544, "VmHWM_bytes": 82468040704, "Pss_bytes": 81059836928, "vram_used_bytes": 194596864, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84171485184, "gtt_total_bytes": 193273528320} +{"t_s": 25.67, "VmRSS_bytes": 81062326272, "VmHWM_bytes": 82468040704, "Pss_bytes": 81059890176, "vram_used_bytes": 194596864, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84171485184, "gtt_total_bytes": 193273528320} +{"t_s": 26.99, "VmRSS_bytes": 81062375424, "VmHWM_bytes": 82468040704, "Pss_bytes": 81059945472, "vram_used_bytes": 194596864, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84171485184, "gtt_total_bytes": 193273528320} +{"t_s": 28.31, "VmRSS_bytes": 81062416384, "VmHWM_bytes": 82468040704, "Pss_bytes": 81060000768, "vram_used_bytes": 194596864, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84171485184, "gtt_total_bytes": 193273528320} +{"t_s": 29.64, "VmRSS_bytes": 81062264832, "VmHWM_bytes": 82468040704, "Pss_bytes": 81059836928, "vram_used_bytes": 194596864, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84171485184, "gtt_total_bytes": 193273528320} +{"t_s": 30.99, "VmRSS_bytes": 81062322176, "VmHWM_bytes": 82468040704, "Pss_bytes": 81059894272, "vram_used_bytes": 194596864, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84171485184, "gtt_total_bytes": 193273528320} +{"t_s": 32.31, "VmRSS_bytes": 81062371328, "VmHWM_bytes": 82468040704, "Pss_bytes": 81059943424, "vram_used_bytes": 194596864, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84171485184, "gtt_total_bytes": 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"vram_total_bytes": 4294967296, "gtt_used_bytes": 87352872960, "gtt_total_bytes": 193273528320} +{"t_s": 205.74, "VmRSS_bytes": 40424022016, "VmHWM_bytes": 82468040704, "Pss_bytes": 35451252736, "vram_used_bytes": 194404352, "vram_total_bytes": 4294967296, "gtt_used_bytes": 200253440, "gtt_total_bytes": 193273528320} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/decode-new-r1-memory-endpoint.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/decode-new-r1-memory-endpoint.json new file mode 100644 index 0000000000..2fdcbb777c --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/decode-new-r1-memory-endpoint.json @@ -0,0 +1 @@ +{"schema_version": 1, "context_window": 16384, "context_fitted": false, "device": {"active_bytes": 89632087748, "cache_bytes": 0, "peak_bytes": 89637677828, "peak_scope": "since_start_or_health_reset"}} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/decode-new-r1-metrics.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/decode-new-r1-metrics.txt new file mode 100644 index 0000000000..049e897603 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/decode-new-r1-metrics.txt @@ -0,0 +1,220 @@ +# HELP tensorfold:requests_running Requests in prefill or decode. +# TYPE tensorfold:requests_running gauge +tensorfold:requests_running 0 +# HELP tensorfold:requests_waiting Requests queued or held until a lane is free. +# TYPE tensorfold:requests_waiting gauge +tensorfold:requests_waiting 0 +# HELP tensorfold:generation_tokens_running Generated tokens held by live streams. +# TYPE tensorfold:generation_tokens_running gauge +tensorfold:generation_tokens_running 0 +# HELP tensorfold:prompt_tokens_total Prompt tokens of finished requests. +# TYPE tensorfold:prompt_tokens_total counter +tensorfold:prompt_tokens_total 990 +# HELP tensorfold:generation_tokens_total Generated tokens of finished requests. +# TYPE tensorfold:generation_tokens_total counter +tensorfold:generation_tokens_total 10784 +# HELP tensorfold:kv_cache_usage_ratio Tokens in a stream cache divided by that stream's context window. +# TYPE tensorfold:kv_cache_usage_ratio gauge +tensorfold:kv_cache_usage_ratio{pool="0"} 0 +# HELP tensorfold:mtp_drafted_total Draft tokens verified on finished requests. +# TYPE tensorfold:mtp_drafted_total counter +tensorfold:mtp_drafted_total 8923 +# HELP tensorfold:mtp_accepted_total Draft tokens kept on finished requests. +# TYPE tensorfold:mtp_accepted_total counter +tensorfold:mtp_accepted_total 6798 +# HELP tensorfold:request_latency_seconds Seconds from arrival to the reply leaving. +# TYPE tensorfold:request_latency_seconds histogram +tensorfold:request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:request_latency_seconds_bucket{le="0.5"} 2 +tensorfold:request_latency_seconds_bucket{le="1"} 2 +tensorfold:request_latency_seconds_bucket{le="2.5"} 2 +tensorfold:request_latency_seconds_bucket{le="5"} 17 +tensorfold:request_latency_seconds_bucket{le="10"} 36 +tensorfold:request_latency_seconds_bucket{le="30"} 44 +tensorfold:request_latency_seconds_bucket{le="60"} 44 +tensorfold:request_latency_seconds_bucket{le="120"} 44 +tensorfold:request_latency_seconds_bucket{le="300"} 44 +tensorfold:request_latency_seconds_bucket{le="+Inf"} 44 +tensorfold:request_latency_seconds_sum 311.565092 +tensorfold:request_latency_seconds_count 44 +# HELP tensorfold:time_to_first_token_seconds Seconds from arrival to the first generated token. +# TYPE tensorfold:time_to_first_token_seconds histogram +tensorfold:time_to_first_token_seconds_bucket{le="0.01"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.05"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.1"} 11 +tensorfold:time_to_first_token_seconds_bucket{le="0.25"} 29 +tensorfold:time_to_first_token_seconds_bucket{le="0.5"} 39 +tensorfold:time_to_first_token_seconds_bucket{le="1"} 44 +tensorfold:time_to_first_token_seconds_bucket{le="2.5"} 44 +tensorfold:time_to_first_token_seconds_bucket{le="5"} 44 +tensorfold:time_to_first_token_seconds_bucket{le="10"} 44 +tensorfold:time_to_first_token_seconds_bucket{le="30"} 44 +tensorfold:time_to_first_token_seconds_bucket{le="60"} 44 +tensorfold:time_to_first_token_seconds_bucket{le="120"} 44 +tensorfold:time_to_first_token_seconds_bucket{le="300"} 44 +tensorfold:time_to_first_token_seconds_bucket{le="+Inf"} 44 +tensorfold:time_to_first_token_seconds_sum 11.36344 +tensorfold:time_to_first_token_seconds_count 44 +# HELP tensorfold:request_decode_seconds Seconds a finished request spent decoding. Its sum over generation_tokens_total is the decode rate. +# TYPE tensorfold:request_decode_seconds histogram +tensorfold:request_decode_seconds_bucket{le="0.01"} 0 +tensorfold:request_decode_seconds_bucket{le="0.05"} 0 +tensorfold:request_decode_seconds_bucket{le="0.1"} 0 +tensorfold:request_decode_seconds_bucket{le="0.25"} 1 +tensorfold:request_decode_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_seconds_bucket{le="1"} 2 +tensorfold:request_decode_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_seconds_bucket{le="5"} 18 +tensorfold:request_decode_seconds_bucket{le="10"} 40 +tensorfold:request_decode_seconds_bucket{le="30"} 44 +tensorfold:request_decode_seconds_bucket{le="60"} 44 +tensorfold:request_decode_seconds_bucket{le="120"} 44 +tensorfold:request_decode_seconds_bucket{le="300"} 44 +tensorfold:request_decode_seconds_bucket{le="+Inf"} 44 +tensorfold:request_decode_seconds_sum 300.201652 +tensorfold:request_decode_seconds_count 44 +# HELP tensorfold:request_time_per_output_token_seconds Seconds from the first generated token to the last, divided by the tokens less one. +# TYPE tensorfold:request_time_per_output_token_seconds histogram +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.005"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.01"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.015"} 7 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.02"} 18 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.025"} 18 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.03"} 20 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.04"} 43 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.05"} 44 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.075"} 44 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.1"} 44 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.15"} 44 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.2"} 44 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.3"} 44 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.5"} 44 +tensorfold:request_time_per_output_token_seconds_bucket{le="1"} 44 +tensorfold:request_time_per_output_token_seconds_bucket{le="+Inf"} 44 +tensorfold:request_time_per_output_token_seconds_sum 1.20689 +tensorfold:request_time_per_output_token_seconds_count 44 +# HELP tensorfold:decode_rounds_total Decode rounds used by finished requests. +# TYPE tensorfold:decode_rounds_total counter +tensorfold:decode_rounds_total 3943 +# HELP tensorfold:request_prefill_seconds Seconds a finished request's prompt pass took. +# TYPE tensorfold:request_prefill_seconds histogram +tensorfold:request_prefill_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.1"} 12 +tensorfold:request_prefill_seconds_bucket{le="0.25"} 33 +tensorfold:request_prefill_seconds_bucket{le="0.5"} 41 +tensorfold:request_prefill_seconds_bucket{le="1"} 44 +tensorfold:request_prefill_seconds_bucket{le="2.5"} 44 +tensorfold:request_prefill_seconds_bucket{le="5"} 44 +tensorfold:request_prefill_seconds_bucket{le="10"} 44 +tensorfold:request_prefill_seconds_bucket{le="30"} 44 +tensorfold:request_prefill_seconds_bucket{le="60"} 44 +tensorfold:request_prefill_seconds_bucket{le="120"} 44 +tensorfold:request_prefill_seconds_bucket{le="300"} 44 +tensorfold:request_prefill_seconds_bucket{le="+Inf"} 44 +tensorfold:request_prefill_seconds_sum 9.600044 +tensorfold:request_prefill_seconds_count 44 +# HELP tensorfold:process_resident_bytes Current resident set (VmRSS); device memory is not in it, so it is not a physical footprint (Linux). +# TYPE tensorfold:process_resident_bytes gauge +tensorfold:process_resident_bytes 103614103552 +# HELP tensorfold:process_resident_anon_bytes Current resident anonymous memory (RssAnon): heap, stacks and private maps (Linux). +# TYPE tensorfold:process_resident_anon_bytes gauge +tensorfold:process_resident_anon_bytes 32380317696 +# HELP tensorfold:process_resident_file_bytes Current resident file-backed memory (RssFile): the binary, libraries and mapped files (Linux). +# TYPE tensorfold:process_resident_file_bytes gauge +tensorfold:process_resident_file_bytes 71099523072 +# HELP tensorfold:process_resident_shmem_bytes Current resident shared memory (RssShmem): System V shared memory, tmpfs maps and shared anonymous maps (Linux). +# TYPE tensorfold:process_resident_shmem_bytes gauge +tensorfold:process_resident_shmem_bytes 134262784 +# HELP tensorfold:process_resident_peak_bytes Kernel lifetime peak resident set (VmHWM); never reset by health (Linux). +# TYPE tensorfold:process_resident_peak_bytes gauge +tensorfold:process_resident_peak_bytes 112417628160 +# HELP tensorfold:device_memory_bytes Device memory the engine holds now: weights, caches and live streams; only where the backend counts it (CUDA). +# TYPE tensorfold:device_memory_bytes gauge +tensorfold:device_memory_bytes 89632087748 +# HELP tensorfold:device_memory_peak_bytes The most device memory the engine has held since start or the last /health?reset_peak=1. +# TYPE tensorfold:device_memory_peak_bytes gauge +tensorfold:device_memory_peak_bytes 89637677828 +# HELP tensorfold:pinned_memory_bytes Pinned host memory the engine holds now: staging buffers and windows; only where the backend counts it (CUDA). +# TYPE tensorfold:pinned_memory_bytes gauge +tensorfold:pinned_memory_bytes 0 +# HELP tensorfold:num_requests_running Requests in prefill or decode. A mirror of tensorfold:requests_running. +# TYPE tensorfold:num_requests_running gauge +tensorfold:num_requests_running 0 +# HELP tensorfold:num_requests_waiting Requests queued or held until a lane is free. A mirror of tensorfold:requests_waiting. +# TYPE tensorfold:num_requests_waiting gauge +tensorfold:num_requests_waiting 0 +# HELP tensorfold:kv_cache_usage_perc A stream's cache occupancy under vLLM's name; same streams and ratios as tensorfold:kv_cache_usage_ratio. +# TYPE tensorfold:kv_cache_usage_perc gauge +tensorfold:kv_cache_usage_perc{stream="0"} 0 +# HELP tensorfold:spec_decode_num_draft_tokens_total Draft tokens verified on finished requests, this server's single draft counter. +# TYPE tensorfold:spec_decode_num_draft_tokens_total counter +tensorfold:spec_decode_num_draft_tokens_total 8923 +# HELP tensorfold:spec_decode_num_accepted_tokens_total Draft tokens kept on finished requests. +# TYPE tensorfold:spec_decode_num_accepted_tokens_total counter +tensorfold:spec_decode_num_accepted_tokens_total 6798 +# HELP tensorfold:e2e_request_latency_seconds Seconds from arrival to the reply leaving, under vLLM's name. +# TYPE tensorfold:e2e_request_latency_seconds histogram +tensorfold:e2e_request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.5"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="1"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="2.5"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="5"} 17 +tensorfold:e2e_request_latency_seconds_bucket{le="10"} 36 +tensorfold:e2e_request_latency_seconds_bucket{le="30"} 44 +tensorfold:e2e_request_latency_seconds_bucket{le="60"} 44 +tensorfold:e2e_request_latency_seconds_bucket{le="120"} 44 +tensorfold:e2e_request_latency_seconds_bucket{le="300"} 44 +tensorfold:e2e_request_latency_seconds_bucket{le="+Inf"} 44 +tensorfold:e2e_request_latency_seconds_sum 311.565092 +tensorfold:e2e_request_latency_seconds_count 44 +# HELP tensorfold:request_decode_time_seconds Seconds a finished request spent decoding, under vLLM's name. +# TYPE tensorfold:request_decode_time_seconds histogram +tensorfold:request_decode_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.25"} 1 +tensorfold:request_decode_time_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="5"} 18 +tensorfold:request_decode_time_seconds_bucket{le="10"} 40 +tensorfold:request_decode_time_seconds_bucket{le="30"} 44 +tensorfold:request_decode_time_seconds_bucket{le="60"} 44 +tensorfold:request_decode_time_seconds_bucket{le="120"} 44 +tensorfold:request_decode_time_seconds_bucket{le="300"} 44 +tensorfold:request_decode_time_seconds_bucket{le="+Inf"} 44 +tensorfold:request_decode_time_seconds_sum 300.201652 +tensorfold:request_decode_time_seconds_count 44 +# HELP tensorfold:request_prefill_time_seconds Seconds a finished request's prompt pass took, under vLLM's name. +# TYPE tensorfold:request_prefill_time_seconds histogram +tensorfold:request_prefill_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.1"} 12 +tensorfold:request_prefill_time_seconds_bucket{le="0.25"} 33 +tensorfold:request_prefill_time_seconds_bucket{le="0.5"} 41 +tensorfold:request_prefill_time_seconds_bucket{le="1"} 44 +tensorfold:request_prefill_time_seconds_bucket{le="2.5"} 44 +tensorfold:request_prefill_time_seconds_bucket{le="5"} 44 +tensorfold:request_prefill_time_seconds_bucket{le="10"} 44 +tensorfold:request_prefill_time_seconds_bucket{le="30"} 44 +tensorfold:request_prefill_time_seconds_bucket{le="60"} 44 +tensorfold:request_prefill_time_seconds_bucket{le="120"} 44 +tensorfold:request_prefill_time_seconds_bucket{le="300"} 44 +tensorfold:request_prefill_time_seconds_bucket{le="+Inf"} 44 +tensorfold:request_prefill_time_seconds_sum 9.600044 +tensorfold:request_prefill_time_seconds_count 44 +# HELP tensorfold:client_disconnections_total Requests a client left before the reply left the server. +# TYPE tensorfold:client_disconnections_total counter +tensorfold:client_disconnections_total 0 +# HELP tensorfold:preemptions_total Requests that had to give a lane up to a later one. +# TYPE tensorfold:preemptions_total counter +tensorfold:preemptions_total 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/decode-new-r1-samples.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/decode-new-r1-samples.jsonl new file mode 100644 index 0000000000..9dc82ad21b --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/decode-new-r1-samples.jsonl @@ -0,0 +1,124 @@ +{"t_s": 0.0, "VmRSS_bytes": 73183232, "VmHWM_bytes": 73183232, "Pss_bytes": 71006208, "vram_used_bytes": 187682816, "vram_total_bytes": 4294967296, "gtt_used_bytes": 31657984, "gtt_total_bytes": 193273528320} +{"t_s": 1.03, "VmRSS_bytes": 10118156288, "VmHWM_bytes": 10118156288, "Pss_bytes": 10123677696, "vram_used_bytes": 188801024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 6847524864, "gtt_total_bytes": 193273528320} +{"t_s": 2.1, "VmRSS_bytes": 18230042624, "VmHWM_bytes": 18230042624, "Pss_bytes": 18332491776, "vram_used_bytes": 189349888, "vram_total_bytes": 4294967296, "gtt_used_bytes": 15062069248, "gtt_total_bytes": 193273528320} +{"t_s": 3.2, "VmRSS_bytes": 26445537280, "VmHWM_bytes": 26445537280, "Pss_bytes": 26443194368, "vram_used_bytes": 189939712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 24811728896, "gtt_total_bytes": 193273528320} +{"t_s": 4.33, "VmRSS_bytes": 34599755776, "VmHWM_bytes": 34599755776, "Pss_bytes": 34702073856, "vram_used_bytes": 190607360, "vram_total_bytes": 4294967296, "gtt_used_bytes": 33131130880, "gtt_total_bytes": 193273528320} +{"t_s": 5.48, "VmRSS_bytes": 44287057920, "VmHWM_bytes": 44287057920, "Pss_bytes": 44284715008, "vram_used_bytes": 191168512, "vram_total_bytes": 4294967296, "gtt_used_bytes": 42880790528, "gtt_total_bytes": 193273528320} +{"t_s": 6.66, "VmRSS_bytes": 52593086464, "VmHWM_bytes": 52593086464, "Pss_bytes": 52611715072, "vram_used_bytes": 191823872, "vram_total_bytes": 4294967296, "gtt_used_bytes": 51200192512, "gtt_total_bytes": 193273528320} +{"t_s": 7.86, "VmRSS_bytes": 62174732288, "VmHWM_bytes": 62174732288, "Pss_bytes": 62172388352, "vram_used_bytes": 192479232, "vram_total_bytes": 4294967296, "gtt_used_bytes": 61058904064, "gtt_total_bytes": 193273528320} +{"t_s": 9.08, "VmRSS_bytes": 71905099776, "VmHWM_bytes": 71905099776, "Pss_bytes": 71902756864, "vram_used_bytes": 193122304, "vram_total_bytes": 4294967296, "gtt_used_bytes": 70913421312, "gtt_total_bytes": 193273528320} +{"t_s": 10.31, "VmRSS_bytes": 82501292032, "VmHWM_bytes": 82501292032, "Pss_bytes": 82498949120, "vram_used_bytes": 194527232, "vram_total_bytes": 4294967296, "gtt_used_bytes": 80778424320, "gtt_total_bytes": 193273528320} +{"t_s": 11.55, "VmRSS_bytes": 84243955712, "VmHWM_bytes": 84243955712, "Pss_bytes": 84232491008, "vram_used_bytes": 194560000, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 12.8, "VmRSS_bytes": 87610445824, "VmHWM_bytes": 87610445824, "Pss_bytes": 87563223040, "vram_used_bytes": 194560000, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 14.04, "VmRSS_bytes": 90767503360, "VmHWM_bytes": 90939662336, "Pss_bytes": 90738728960, "vram_used_bytes": 194560000, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 15.28, "VmRSS_bytes": 93899055104, "VmHWM_bytes": 93899055104, "Pss_bytes": 93741776896, "vram_used_bytes": 194560000, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 16.54, "VmRSS_bytes": 96327946240, "VmHWM_bytes": 96437399552, "Pss_bytes": 96463831040, "vram_used_bytes": 194560000, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 17.84, "VmRSS_bytes": 99135762432, "VmHWM_bytes": 99187261440, "Pss_bytes": 99306491904, "vram_used_bytes": 194560000, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 19.13, "VmRSS_bytes": 102038937600, "VmHWM_bytes": 102186774528, "Pss_bytes": 101986762752, "vram_used_bytes": 194560000, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 20.46, "VmRSS_bytes": 104012345344, "VmHWM_bytes": 104157065216, "Pss_bytes": 104004793344, "vram_used_bytes": 194576384, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 21.8, "VmRSS_bytes": 105931870208, "VmHWM_bytes": 105931870208, "Pss_bytes": 105849848832, "vram_used_bytes": 194576384, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 23.18, "VmRSS_bytes": 108426731520, "VmHWM_bytes": 108552212480, "Pss_bytes": 108713174016, "vram_used_bytes": 194576384, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 24.57, "VmRSS_bytes": 110819467264, "VmHWM_bytes": 110819467264, "Pss_bytes": 110716466176, "vram_used_bytes": 194576384, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 26.01, "VmRSS_bytes": 108478701568, "VmHWM_bytes": 112417628160, "Pss_bytes": 105955374080, "vram_used_bytes": 202969088, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88070221824, "gtt_total_bytes": 193273528320} +{"t_s": 27.42, "VmRSS_bytes": 105500008448, "VmHWM_bytes": 112417628160, "Pss_bytes": 105497608192, "vram_used_bytes": 203001856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88708055040, "gtt_total_bytes": 193273528320} +{"t_s": 28.8, "VmRSS_bytes": 105504661504, "VmHWM_bytes": 112417628160, "Pss_bytes": 105502257152, "vram_used_bytes": 203005952, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88709160960, "gtt_total_bytes": 193273528320} +{"t_s": 30.17, "VmRSS_bytes": 105506881536, "VmHWM_bytes": 112417628160, "Pss_bytes": 105504477184, "vram_used_bytes": 203005952, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88709160960, "gtt_total_bytes": 193273528320} +{"t_s": 31.6, "VmRSS_bytes": 105509412864, "VmHWM_bytes": 112417628160, "Pss_bytes": 105507028992, "vram_used_bytes": 203005952, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88709160960, "gtt_total_bytes": 193273528320} +{"t_s": 33.07, "VmRSS_bytes": 105509490688, "VmHWM_bytes": 112417628160, "Pss_bytes": 105507102720, "vram_used_bytes": 203005952, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88709160960, 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"vram_used_bytes": 203145216, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90617761792, "gtt_total_bytes": 193273528320} +{"t_s": 143.51, "VmRSS_bytes": 103615148032, "VmHWM_bytes": 112417628160, "Pss_bytes": 103612759040, "vram_used_bytes": 203145216, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90617761792, "gtt_total_bytes": 193273528320} +{"t_s": 144.94, "VmRSS_bytes": 103615275008, "VmHWM_bytes": 112417628160, "Pss_bytes": 103612914688, "vram_used_bytes": 203145216, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90617761792, "gtt_total_bytes": 193273528320} +{"t_s": 146.37, "VmRSS_bytes": 103615434752, "VmHWM_bytes": 112417628160, "Pss_bytes": 103613045760, "vram_used_bytes": 203145216, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90617761792, "gtt_total_bytes": 193273528320} +{"t_s": 147.79, "VmRSS_bytes": 103615561728, "VmHWM_bytes": 112417628160, "Pss_bytes": 103613180928, "vram_used_bytes": 203145216, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90617761792, "gtt_total_bytes": 193273528320} +{"t_s": 149.19, "VmRSS_bytes": 103615664128, "VmHWM_bytes": 112417628160, "Pss_bytes": 103613324288, "vram_used_bytes": 203145216, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90617761792, "gtt_total_bytes": 193273528320} +{"t_s": 150.62, "VmRSS_bytes": 103615836160, "VmHWM_bytes": 112417628160, "Pss_bytes": 103613455360, "vram_used_bytes": 203145216, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90617761792, "gtt_total_bytes": 193273528320} +{"t_s": 152.03, "VmRSS_bytes": 103614885888, "VmHWM_bytes": 112417628160, "Pss_bytes": 103612500992, "vram_used_bytes": 203145216, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90617761792, "gtt_total_bytes": 193273528320} +{"t_s": 153.43, "VmRSS_bytes": 103615045632, "VmHWM_bytes": 112417628160, "Pss_bytes": 103612718080, "vram_used_bytes": 203145216, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90617761792, "gtt_total_bytes": 193273528320} +{"t_s": 154.85, "VmRSS_bytes": 103615221760, "VmHWM_bytes": 112417628160, "Pss_bytes": 103612840960, "vram_used_bytes": 203145216, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90617761792, "gtt_total_bytes": 193273528320} +{"t_s": 156.26, "VmRSS_bytes": 103615389696, "VmHWM_bytes": 112417628160, "Pss_bytes": 103613008896, "vram_used_bytes": 203145216, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90617761792, "gtt_total_bytes": 193273528320} +{"t_s": 157.68, "VmRSS_bytes": 103615504384, "VmHWM_bytes": 112417628160, "Pss_bytes": 103613139968, "vram_used_bytes": 203145216, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90617761792, "gtt_total_bytes": 193273528320} +{"t_s": 159.1, "VmRSS_bytes": 103615627264, "VmHWM_bytes": 112417628160, "Pss_bytes": 103613254656, "vram_used_bytes": 203145216, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90617761792, "gtt_total_bytes": 193273528320} +{"t_s": 160.56, "VmRSS_bytes": 103615811584, "VmHWM_bytes": 112417628160, "Pss_bytes": 103613426688, "vram_used_bytes": 203145216, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90617761792, "gtt_total_bytes": 193273528320} +{"t_s": 161.94, "VmRSS_bytes": 103615942656, "VmHWM_bytes": 112417628160, "Pss_bytes": 103612742656, "vram_used_bytes": 203145216, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90617761792, "gtt_total_bytes": 193273528320} +{"t_s": 163.38, "VmRSS_bytes": 103615012864, "VmHWM_bytes": 112417628160, "Pss_bytes": 103612632064, "vram_used_bytes": 203145216, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90617761792, "gtt_total_bytes": 193273528320} +{"t_s": 164.81, "VmRSS_bytes": 103615184896, "VmHWM_bytes": 112417628160, "Pss_bytes": 103612824576, "vram_used_bytes": 203145216, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90617761792, "gtt_total_bytes": 193273528320} +{"t_s": 166.24, "VmRSS_bytes": 103615381504, "VmHWM_bytes": 112417628160, "Pss_bytes": 103612980224, "vram_used_bytes": 203145216, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90617761792, "gtt_total_bytes": 193273528320} +{"t_s": 167.68, "VmRSS_bytes": 103615475712, "VmHWM_bytes": 112417628160, "Pss_bytes": 103613127680, "vram_used_bytes": 203145216, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90617761792, "gtt_total_bytes": 193273528320} +{"t_s": 169.13, "VmRSS_bytes": 103615631360, "VmHWM_bytes": 112417628160, "Pss_bytes": 103613242368, "vram_used_bytes": 203145216, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90617761792, "gtt_total_bytes": 193273528320} +{"t_s": 170.55, "VmRSS_bytes": 103615811584, "VmHWM_bytes": 112417628160, "Pss_bytes": 103613414400, "vram_used_bytes": 203145216, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90617761792, "gtt_total_bytes": 193273528320} +{"t_s": 171.96, "VmRSS_bytes": 103615926272, "VmHWM_bytes": 112417628160, "Pss_bytes": 103611710464, "vram_used_bytes": 203145216, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90617761792, "gtt_total_bytes": 193273528320} +{"t_s": 173.27, "VmRSS_bytes": 100933799936, "VmHWM_bytes": 112417628160, "Pss_bytes": 95033135104, "vram_used_bytes": 194539520, "vram_total_bytes": 4294967296, "gtt_used_bytes": 204288000, "gtt_total_bytes": 193273528320} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/decode-new-r2-memory-endpoint.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/decode-new-r2-memory-endpoint.json new file mode 100644 index 0000000000..2fdcbb777c --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/decode-new-r2-memory-endpoint.json @@ -0,0 +1 @@ +{"schema_version": 1, "context_window": 16384, "context_fitted": false, "device": {"active_bytes": 89632087748, "cache_bytes": 0, "peak_bytes": 89637677828, "peak_scope": "since_start_or_health_reset"}} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/decode-new-r2-metrics.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/decode-new-r2-metrics.txt new file mode 100644 index 0000000000..3322fcd902 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/decode-new-r2-metrics.txt @@ -0,0 +1,220 @@ +# HELP tensorfold:requests_running Requests in prefill or decode. +# TYPE tensorfold:requests_running gauge +tensorfold:requests_running 0 +# HELP tensorfold:requests_waiting Requests queued or held until a lane is free. +# TYPE tensorfold:requests_waiting gauge +tensorfold:requests_waiting 0 +# HELP tensorfold:generation_tokens_running Generated tokens held by live streams. +# TYPE tensorfold:generation_tokens_running gauge +tensorfold:generation_tokens_running 0 +# HELP tensorfold:prompt_tokens_total Prompt tokens of finished requests. +# TYPE tensorfold:prompt_tokens_total counter +tensorfold:prompt_tokens_total 990 +# HELP tensorfold:generation_tokens_total Generated tokens of finished requests. +# TYPE tensorfold:generation_tokens_total counter +tensorfold:generation_tokens_total 10784 +# HELP tensorfold:kv_cache_usage_ratio Tokens in a stream cache divided by that stream's context window. +# TYPE tensorfold:kv_cache_usage_ratio gauge +tensorfold:kv_cache_usage_ratio{pool="0"} 0 +# HELP tensorfold:mtp_drafted_total Draft tokens verified on finished requests. +# TYPE tensorfold:mtp_drafted_total counter +tensorfold:mtp_drafted_total 8923 +# HELP tensorfold:mtp_accepted_total Draft tokens kept on finished requests. +# TYPE tensorfold:mtp_accepted_total counter +tensorfold:mtp_accepted_total 6798 +# HELP tensorfold:request_latency_seconds Seconds from arrival to the reply leaving. +# TYPE tensorfold:request_latency_seconds histogram +tensorfold:request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:request_latency_seconds_bucket{le="0.5"} 2 +tensorfold:request_latency_seconds_bucket{le="1"} 2 +tensorfold:request_latency_seconds_bucket{le="2.5"} 2 +tensorfold:request_latency_seconds_bucket{le="5"} 18 +tensorfold:request_latency_seconds_bucket{le="10"} 36 +tensorfold:request_latency_seconds_bucket{le="30"} 44 +tensorfold:request_latency_seconds_bucket{le="60"} 44 +tensorfold:request_latency_seconds_bucket{le="120"} 44 +tensorfold:request_latency_seconds_bucket{le="300"} 44 +tensorfold:request_latency_seconds_bucket{le="+Inf"} 44 +tensorfold:request_latency_seconds_sum 314.171727 +tensorfold:request_latency_seconds_count 44 +# HELP tensorfold:time_to_first_token_seconds Seconds from arrival to the first generated token. +# TYPE tensorfold:time_to_first_token_seconds histogram +tensorfold:time_to_first_token_seconds_bucket{le="0.01"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.05"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.1"} 12 +tensorfold:time_to_first_token_seconds_bucket{le="0.25"} 27 +tensorfold:time_to_first_token_seconds_bucket{le="0.5"} 39 +tensorfold:time_to_first_token_seconds_bucket{le="1"} 44 +tensorfold:time_to_first_token_seconds_bucket{le="2.5"} 44 +tensorfold:time_to_first_token_seconds_bucket{le="5"} 44 +tensorfold:time_to_first_token_seconds_bucket{le="10"} 44 +tensorfold:time_to_first_token_seconds_bucket{le="30"} 44 +tensorfold:time_to_first_token_seconds_bucket{le="60"} 44 +tensorfold:time_to_first_token_seconds_bucket{le="120"} 44 +tensorfold:time_to_first_token_seconds_bucket{le="300"} 44 +tensorfold:time_to_first_token_seconds_bucket{le="+Inf"} 44 +tensorfold:time_to_first_token_seconds_sum 11.326723 +tensorfold:time_to_first_token_seconds_count 44 +# HELP tensorfold:request_decode_seconds Seconds a finished request spent decoding. Its sum over generation_tokens_total is the decode rate. +# TYPE tensorfold:request_decode_seconds histogram +tensorfold:request_decode_seconds_bucket{le="0.01"} 0 +tensorfold:request_decode_seconds_bucket{le="0.05"} 0 +tensorfold:request_decode_seconds_bucket{le="0.1"} 0 +tensorfold:request_decode_seconds_bucket{le="0.25"} 1 +tensorfold:request_decode_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_seconds_bucket{le="1"} 2 +tensorfold:request_decode_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_seconds_bucket{le="5"} 18 +tensorfold:request_decode_seconds_bucket{le="10"} 37 +tensorfold:request_decode_seconds_bucket{le="30"} 44 +tensorfold:request_decode_seconds_bucket{le="60"} 44 +tensorfold:request_decode_seconds_bucket{le="120"} 44 +tensorfold:request_decode_seconds_bucket{le="300"} 44 +tensorfold:request_decode_seconds_bucket{le="+Inf"} 44 +tensorfold:request_decode_seconds_sum 302.845005 +tensorfold:request_decode_seconds_count 44 +# HELP tensorfold:request_time_per_output_token_seconds Seconds from the first generated token to the last, divided by the tokens less one. +# TYPE tensorfold:request_time_per_output_token_seconds histogram +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.005"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.01"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.015"} 8 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.02"} 18 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.025"} 18 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.03"} 20 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.04"} 41 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.05"} 44 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.075"} 44 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.1"} 44 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.15"} 44 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.2"} 44 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.3"} 44 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.5"} 44 +tensorfold:request_time_per_output_token_seconds_bucket{le="1"} 44 +tensorfold:request_time_per_output_token_seconds_bucket{le="+Inf"} 44 +tensorfold:request_time_per_output_token_seconds_sum 1.209874 +tensorfold:request_time_per_output_token_seconds_count 44 +# HELP tensorfold:decode_rounds_total Decode rounds used by finished requests. +# TYPE tensorfold:decode_rounds_total counter +tensorfold:decode_rounds_total 3943 +# HELP tensorfold:request_prefill_seconds Seconds a finished request's prompt pass took. +# TYPE tensorfold:request_prefill_seconds histogram +tensorfold:request_prefill_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.1"} 13 +tensorfold:request_prefill_seconds_bucket{le="0.25"} 33 +tensorfold:request_prefill_seconds_bucket{le="0.5"} 43 +tensorfold:request_prefill_seconds_bucket{le="1"} 44 +tensorfold:request_prefill_seconds_bucket{le="2.5"} 44 +tensorfold:request_prefill_seconds_bucket{le="5"} 44 +tensorfold:request_prefill_seconds_bucket{le="10"} 44 +tensorfold:request_prefill_seconds_bucket{le="30"} 44 +tensorfold:request_prefill_seconds_bucket{le="60"} 44 +tensorfold:request_prefill_seconds_bucket{le="120"} 44 +tensorfold:request_prefill_seconds_bucket{le="300"} 44 +tensorfold:request_prefill_seconds_bucket{le="+Inf"} 44 +tensorfold:request_prefill_seconds_sum 8.941782 +tensorfold:request_prefill_seconds_count 44 +# HELP tensorfold:process_resident_bytes Current resident set (VmRSS); device memory is not in it, so it is not a physical footprint (Linux). +# TYPE tensorfold:process_resident_bytes gauge +tensorfold:process_resident_bytes 103802384384 +# HELP tensorfold:process_resident_anon_bytes Current resident anonymous memory (RssAnon): heap, stacks and private maps (Linux). +# TYPE tensorfold:process_resident_anon_bytes gauge +tensorfold:process_resident_anon_bytes 32379318272 +# HELP tensorfold:process_resident_file_bytes Current resident file-backed memory (RssFile): the binary, libraries and mapped files (Linux). +# TYPE tensorfold:process_resident_file_bytes gauge +tensorfold:process_resident_file_bytes 71288803328 +# HELP tensorfold:process_resident_shmem_bytes Current resident shared memory (RssShmem): System V shared memory, tmpfs maps and shared anonymous maps (Linux). +# TYPE tensorfold:process_resident_shmem_bytes gauge +tensorfold:process_resident_shmem_bytes 134262784 +# HELP tensorfold:process_resident_peak_bytes Kernel lifetime peak resident set (VmHWM); never reset by health (Linux). +# TYPE tensorfold:process_resident_peak_bytes gauge +tensorfold:process_resident_peak_bytes 112510427136 +# HELP tensorfold:device_memory_bytes Device memory the engine holds now: weights, caches and live streams; only where the backend counts it (CUDA). +# TYPE tensorfold:device_memory_bytes gauge +tensorfold:device_memory_bytes 89632087748 +# HELP tensorfold:device_memory_peak_bytes The most device memory the engine has held since start or the last /health?reset_peak=1. +# TYPE tensorfold:device_memory_peak_bytes gauge +tensorfold:device_memory_peak_bytes 89637677828 +# HELP tensorfold:pinned_memory_bytes Pinned host memory the engine holds now: staging buffers and windows; only where the backend counts it (CUDA). +# TYPE tensorfold:pinned_memory_bytes gauge +tensorfold:pinned_memory_bytes 0 +# HELP tensorfold:num_requests_running Requests in prefill or decode. A mirror of tensorfold:requests_running. +# TYPE tensorfold:num_requests_running gauge +tensorfold:num_requests_running 0 +# HELP tensorfold:num_requests_waiting Requests queued or held until a lane is free. A mirror of tensorfold:requests_waiting. +# TYPE tensorfold:num_requests_waiting gauge +tensorfold:num_requests_waiting 0 +# HELP tensorfold:kv_cache_usage_perc A stream's cache occupancy under vLLM's name; same streams and ratios as tensorfold:kv_cache_usage_ratio. +# TYPE tensorfold:kv_cache_usage_perc gauge +tensorfold:kv_cache_usage_perc{stream="0"} 0 +# HELP tensorfold:spec_decode_num_draft_tokens_total Draft tokens verified on finished requests, this server's single draft counter. +# TYPE tensorfold:spec_decode_num_draft_tokens_total counter +tensorfold:spec_decode_num_draft_tokens_total 8923 +# HELP tensorfold:spec_decode_num_accepted_tokens_total Draft tokens kept on finished requests. +# TYPE tensorfold:spec_decode_num_accepted_tokens_total counter +tensorfold:spec_decode_num_accepted_tokens_total 6798 +# HELP tensorfold:e2e_request_latency_seconds Seconds from arrival to the reply leaving, under vLLM's name. +# TYPE tensorfold:e2e_request_latency_seconds histogram +tensorfold:e2e_request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.5"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="1"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="2.5"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="5"} 18 +tensorfold:e2e_request_latency_seconds_bucket{le="10"} 36 +tensorfold:e2e_request_latency_seconds_bucket{le="30"} 44 +tensorfold:e2e_request_latency_seconds_bucket{le="60"} 44 +tensorfold:e2e_request_latency_seconds_bucket{le="120"} 44 +tensorfold:e2e_request_latency_seconds_bucket{le="300"} 44 +tensorfold:e2e_request_latency_seconds_bucket{le="+Inf"} 44 +tensorfold:e2e_request_latency_seconds_sum 314.171727 +tensorfold:e2e_request_latency_seconds_count 44 +# HELP tensorfold:request_decode_time_seconds Seconds a finished request spent decoding, under vLLM's name. +# TYPE tensorfold:request_decode_time_seconds histogram +tensorfold:request_decode_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_decode_time_seconds_bucket{le="0.25"} 1 +tensorfold:request_decode_time_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="5"} 18 +tensorfold:request_decode_time_seconds_bucket{le="10"} 37 +tensorfold:request_decode_time_seconds_bucket{le="30"} 44 +tensorfold:request_decode_time_seconds_bucket{le="60"} 44 +tensorfold:request_decode_time_seconds_bucket{le="120"} 44 +tensorfold:request_decode_time_seconds_bucket{le="300"} 44 +tensorfold:request_decode_time_seconds_bucket{le="+Inf"} 44 +tensorfold:request_decode_time_seconds_sum 302.845005 +tensorfold:request_decode_time_seconds_count 44 +# HELP tensorfold:request_prefill_time_seconds Seconds a finished request's prompt pass took, under vLLM's name. +# TYPE tensorfold:request_prefill_time_seconds histogram +tensorfold:request_prefill_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.1"} 13 +tensorfold:request_prefill_time_seconds_bucket{le="0.25"} 33 +tensorfold:request_prefill_time_seconds_bucket{le="0.5"} 43 +tensorfold:request_prefill_time_seconds_bucket{le="1"} 44 +tensorfold:request_prefill_time_seconds_bucket{le="2.5"} 44 +tensorfold:request_prefill_time_seconds_bucket{le="5"} 44 +tensorfold:request_prefill_time_seconds_bucket{le="10"} 44 +tensorfold:request_prefill_time_seconds_bucket{le="30"} 44 +tensorfold:request_prefill_time_seconds_bucket{le="60"} 44 +tensorfold:request_prefill_time_seconds_bucket{le="120"} 44 +tensorfold:request_prefill_time_seconds_bucket{le="300"} 44 +tensorfold:request_prefill_time_seconds_bucket{le="+Inf"} 44 +tensorfold:request_prefill_time_seconds_sum 8.941782 +tensorfold:request_prefill_time_seconds_count 44 +# HELP tensorfold:client_disconnections_total Requests a client left before the reply left the server. +# TYPE tensorfold:client_disconnections_total counter +tensorfold:client_disconnections_total 0 +# HELP tensorfold:preemptions_total Requests that had to give a lane up to a later one. +# TYPE tensorfold:preemptions_total counter +tensorfold:preemptions_total 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/decode-new-r2-samples.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/decode-new-r2-samples.jsonl new file mode 100644 index 0000000000..7da9508553 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/decode-new-r2-samples.jsonl @@ -0,0 +1,130 @@ +{"t_s": 0.0, "VmRSS_bytes": 75866112, 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"gtt_used_bytes": 33124839424, "gtt_total_bytes": 193273528320} +{"t_s": 5.52, "VmRSS_bytes": 43824615424, "VmHWM_bytes": 43824615424, "Pss_bytes": 43988965376, "vram_used_bytes": 191188992, "vram_total_bytes": 4294967296, "gtt_used_bytes": 41345675264, "gtt_total_bytes": 193273528320} +{"t_s": 6.71, "VmRSS_bytes": 52397703168, "VmHWM_bytes": 52397703168, "Pss_bytes": 52395460608, "vram_used_bytes": 191750144, "vram_total_bytes": 4294967296, "gtt_used_bytes": 51097432064, "gtt_total_bytes": 193273528320} +{"t_s": 7.94, "VmRSS_bytes": 60721184768, "VmHWM_bytes": 60721184768, "Pss_bytes": 60773074944, "vram_used_bytes": 192405504, "vram_total_bytes": 4294967296, "gtt_used_bytes": 59414736896, "gtt_total_bytes": 193273528320} +{"t_s": 9.18, "VmRSS_bytes": 70286131200, "VmHWM_bytes": 70286131200, "Pss_bytes": 70283888640, "vram_used_bytes": 193040384, "vram_total_bytes": 4294967296, "gtt_used_bytes": 69275545600, "gtt_total_bytes": 193273528320} +{"t_s": 10.43, "VmRSS_bytes": 80002179072, "VmHWM_bytes": 80002179072, "Pss_bytes": 80100599808, "vram_used_bytes": 193851392, "vram_total_bytes": 4294967296, "gtt_used_bytes": 79392206848, "gtt_total_bytes": 193273528320} +{"t_s": 11.69, "VmRSS_bytes": 84016300032, "VmHWM_bytes": 84016300032, "Pss_bytes": 83983439872, "vram_used_bytes": 194609152, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 12.96, "VmRSS_bytes": 88054370304, "VmHWM_bytes": 88186277888, "Pss_bytes": 88035227648, "vram_used_bytes": 194609152, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 14.22, "VmRSS_bytes": 92239126528, "VmHWM_bytes": 92438175744, "Pss_bytes": 92407212032, "vram_used_bytes": 194609152, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 15.49, "VmRSS_bytes": 96399306752, "VmHWM_bytes": 96399306752, "Pss_bytes": 96238643200, "vram_used_bytes": 194609152, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 16.76, "VmRSS_bytes": 100064284672, "VmHWM_bytes": 100190474240, "Pss_bytes": 100099790848, "vram_used_bytes": 194609152, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 18.03, "VmRSS_bytes": 104480694272, "VmHWM_bytes": 104480694272, "Pss_bytes": 104489011200, "vram_used_bytes": 194609152, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 19.32, "VmRSS_bytes": 108243267584, "VmHWM_bytes": 108243267584, "Pss_bytes": 108194838528, "vram_used_bytes": 194609152, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 20.61, "VmRSS_bytes": 111024807936, "VmHWM_bytes": 111024807936, "Pss_bytes": 111084525568, "vram_used_bytes": 194609152, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 22.08, "VmRSS_bytes": 112325464064, "VmHWM_bytes": 112510427136, "Pss_bytes": 112241858560, "vram_used_bytes": 195080192, "vram_total_bytes": 4294967296, "gtt_used_bytes": 82246430720, "gtt_total_bytes": 193273528320} +{"t_s": 23.42, "VmRSS_bytes": 105352765440, "VmHWM_bytes": 112510427136, "Pss_bytes": 105350461440, "vram_used_bytes": 203575296, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88704696320, "gtt_total_bytes": 193273528320} +{"t_s": 24.72, "VmRSS_bytes": 105357709312, "VmHWM_bytes": 112510427136, "Pss_bytes": 105355405312, "vram_used_bytes": 203583488, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88708792320, "gtt_total_bytes": 193273528320} +{"t_s": 26.08, "VmRSS_bytes": 105360478208, "VmHWM_bytes": 112510427136, "Pss_bytes": 105358223360, "vram_used_bytes": 203583488, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88709160960, "gtt_total_bytes": 193273528320} +{"t_s": 27.37, "VmRSS_bytes": 105361444864, "VmHWM_bytes": 112510427136, "Pss_bytes": 105359316992, "vram_used_bytes": 203583488, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88709160960, "gtt_total_bytes": 193273528320} +{"t_s": 28.71, "VmRSS_bytes": 105363828736, "VmHWM_bytes": 112510427136, "Pss_bytes": 105361541120, "vram_used_bytes": 203583488, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88709160960, "gtt_total_bytes": 193273528320} +{"t_s": 30.05, "VmRSS_bytes": 105363894272, "VmHWM_bytes": 112510427136, "Pss_bytes": 105361593344, "vram_used_bytes": 203583488, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88709160960, "gtt_total_bytes": 193273528320} +{"t_s": 31.34, "VmRSS_bytes": 105363955712, "VmHWM_bytes": 112510427136, "Pss_bytes": 105361556480, "vram_used_bytes": 203583488, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88709160960, "gtt_total_bytes": 193273528320} +{"t_s": 32.69, "VmRSS_bytes": 105364140032, "VmHWM_bytes": 112510427136, "Pss_bytes": 105361844224, "vram_used_bytes": 203583488, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88709160960, "gtt_total_bytes": 193273528320} +{"t_s": 34.02, "VmRSS_bytes": 105364197376, "VmHWM_bytes": 112510427136, "Pss_bytes": 105361901568, "vram_used_bytes": 203583488, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88709160960, "gtt_total_bytes": 193273528320} +{"t_s": 35.32, "VmRSS_bytes": 105364262912, "VmHWM_bytes": 112510427136, "Pss_bytes": 105361897472, "vram_used_bytes": 203583488, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88709160960, "gtt_total_bytes": 193273528320} +{"t_s": 36.68, "VmRSS_bytes": 105364140032, "VmHWM_bytes": 112510427136, "Pss_bytes": 105361844224, "vram_used_bytes": 203583488, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88709160960, "gtt_total_bytes": 193273528320} +{"t_s": 38.01, "VmRSS_bytes": 105364197376, "VmHWM_bytes": 112510427136, "Pss_bytes": 105361901568, "vram_used_bytes": 203583488, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88709160960, "gtt_total_bytes": 193273528320} +{"t_s": 39.31, "VmRSS_bytes": 105364299776, "VmHWM_bytes": 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"vram_total_bytes": 4294967296, "gtt_used_bytes": 90617761792, "gtt_total_bytes": 193273528320} +{"t_s": 169.08, "VmRSS_bytes": 103804289024, "VmHWM_bytes": 112510427136, "Pss_bytes": 103801620480, "vram_used_bytes": 203595776, "vram_total_bytes": 4294967296, "gtt_used_bytes": 90617761792, "gtt_total_bytes": 193273528320} +{"t_s": 170.3, "VmRSS_bytes": 59716661248, "VmHWM_bytes": 112510427136, "Pss_bytes": 57412254720, "vram_used_bytes": 194568192, "vram_total_bytes": 4294967296, "gtt_used_bytes": 204288000, "gtt_total_bytes": 193273528320} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-base-r1-memory-endpoint.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-base-r1-memory-endpoint.json new file mode 100644 index 0000000000..586f5af8d2 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-base-r1-memory-endpoint.json @@ -0,0 +1 @@ +{"schema_version": 1, "context_window": 20480, "context_fitted": false, "device": {"active_bytes": 83402378688, "cache_bytes": 0, "peak_bytes": 83441722820, "peak_scope": "since_start_or_health_reset"}} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-base-r1-metrics.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-base-r1-metrics.txt new file mode 100644 index 0000000000..17b21ac8b3 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-base-r1-metrics.txt @@ -0,0 +1,220 @@ +# HELP tensorfold:requests_running Requests in prefill or decode. +# TYPE tensorfold:requests_running gauge +tensorfold:requests_running 0 +# HELP tensorfold:requests_waiting Requests queued or held until a lane is free. +# TYPE tensorfold:requests_waiting gauge +tensorfold:requests_waiting 0 +# HELP tensorfold:generation_tokens_running Generated tokens held by live streams. +# TYPE tensorfold:generation_tokens_running gauge +tensorfold:generation_tokens_running 0 +# HELP tensorfold:prompt_tokens_total Prompt tokens of finished requests. +# TYPE tensorfold:prompt_tokens_total counter +tensorfold:prompt_tokens_total 16640 +# HELP tensorfold:generation_tokens_total Generated tokens of finished requests. +# TYPE tensorfold:generation_tokens_total counter +tensorfold:generation_tokens_total 2 +# HELP tensorfold:kv_cache_usage_ratio Tokens in a stream cache divided by that stream's context window. +# TYPE tensorfold:kv_cache_usage_ratio gauge +tensorfold:kv_cache_usage_ratio{pool="0"} 0 +# HELP tensorfold:mtp_drafted_total Draft tokens verified on finished requests. +# TYPE tensorfold:mtp_drafted_total counter +tensorfold:mtp_drafted_total 0 +# HELP tensorfold:mtp_accepted_total Draft tokens kept on finished requests. +# TYPE tensorfold:mtp_accepted_total counter +tensorfold:mtp_accepted_total 0 +# HELP tensorfold:request_latency_seconds Seconds from arrival to the reply leaving. +# TYPE tensorfold:request_latency_seconds histogram +tensorfold:request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:request_latency_seconds_bucket{le="1"} 1 +tensorfold:request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:request_latency_seconds_bucket{le="5"} 1 +tensorfold:request_latency_seconds_bucket{le="10"} 1 +tensorfold:request_latency_seconds_bucket{le="30"} 1 +tensorfold:request_latency_seconds_bucket{le="60"} 2 +tensorfold:request_latency_seconds_bucket{le="120"} 2 +tensorfold:request_latency_seconds_bucket{le="300"} 2 +tensorfold:request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:request_latency_seconds_sum 47.171496 +tensorfold:request_latency_seconds_count 2 +# HELP tensorfold:time_to_first_token_seconds Seconds from arrival to the first generated token. +# TYPE tensorfold:time_to_first_token_seconds histogram +tensorfold:time_to_first_token_seconds_bucket{le="0.01"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.05"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.25"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.5"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="1"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="2.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="10"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="30"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="60"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="120"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="300"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="+Inf"} 2 +tensorfold:time_to_first_token_seconds_sum 47.171263 +tensorfold:time_to_first_token_seconds_count 2 +# HELP tensorfold:request_decode_seconds Seconds a finished request spent decoding. Its sum over generation_tokens_total is the decode rate. +# TYPE tensorfold:request_decode_seconds histogram +tensorfold:request_decode_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_seconds_bucket{le="1"} 2 +tensorfold:request_decode_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_seconds_bucket{le="5"} 2 +tensorfold:request_decode_seconds_bucket{le="10"} 2 +tensorfold:request_decode_seconds_bucket{le="30"} 2 +tensorfold:request_decode_seconds_bucket{le="60"} 2 +tensorfold:request_decode_seconds_bucket{le="120"} 2 +tensorfold:request_decode_seconds_bucket{le="300"} 2 +tensorfold:request_decode_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_seconds_sum 0.000233 +tensorfold:request_decode_seconds_count 2 +# HELP tensorfold:request_time_per_output_token_seconds Seconds from the first generated token to the last, divided by the tokens less one. +# TYPE tensorfold:request_time_per_output_token_seconds histogram +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.005"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.01"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.015"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.02"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.03"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.04"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.05"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.15"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.2"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.3"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.5"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="+Inf"} 0 +tensorfold:request_time_per_output_token_seconds_sum 0 +tensorfold:request_time_per_output_token_seconds_count 0 +# HELP tensorfold:decode_rounds_total Decode rounds used by finished requests. +# TYPE tensorfold:decode_rounds_total counter +tensorfold:decode_rounds_total 0 +# HELP tensorfold:request_prefill_seconds Seconds a finished request's prompt pass took. +# TYPE tensorfold:request_prefill_seconds histogram +tensorfold:request_prefill_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.5"} 0 +tensorfold:request_prefill_seconds_bucket{le="1"} 1 +tensorfold:request_prefill_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_seconds_bucket{le="60"} 2 +tensorfold:request_prefill_seconds_bucket{le="120"} 2 +tensorfold:request_prefill_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_seconds_sum 47.170323 +tensorfold:request_prefill_seconds_count 2 +# HELP tensorfold:process_resident_bytes Current resident set (VmRSS); device memory is not in it, so it is not a physical footprint (Linux). +# TYPE tensorfold:process_resident_bytes gauge +tensorfold:process_resident_bytes 84331499520 +# HELP tensorfold:process_resident_anon_bytes Current resident anonymous memory (RssAnon): heap, stacks and private maps (Linux). +# TYPE tensorfold:process_resident_anon_bytes gauge +tensorfold:process_resident_anon_bytes 304082944 +# HELP tensorfold:process_resident_file_bytes Current resident file-backed memory (RssFile): the binary, libraries and mapped files (Linux). +# TYPE tensorfold:process_resident_file_bytes gauge +tensorfold:process_resident_file_bytes 83915513856 +# HELP tensorfold:process_resident_shmem_bytes Current resident shared memory (RssShmem): System V shared memory, tmpfs maps and shared anonymous maps (Linux). +# TYPE tensorfold:process_resident_shmem_bytes gauge +tensorfold:process_resident_shmem_bytes 111902720 +# HELP tensorfold:process_resident_peak_bytes Kernel lifetime peak resident set (VmHWM); never reset by health (Linux). +# TYPE tensorfold:process_resident_peak_bytes gauge +tensorfold:process_resident_peak_bytes 84331499520 +# HELP tensorfold:device_memory_bytes Device memory the engine holds now: weights, caches and live streams; only where the backend counts it (CUDA). +# TYPE tensorfold:device_memory_bytes gauge +tensorfold:device_memory_bytes 83402378688 +# HELP tensorfold:device_memory_peak_bytes The most device memory the engine has held since start or the last /health?reset_peak=1. +# TYPE tensorfold:device_memory_peak_bytes gauge +tensorfold:device_memory_peak_bytes 83441722820 +# HELP tensorfold:pinned_memory_bytes Pinned host memory the engine holds now: staging buffers and windows; only where the backend counts it (CUDA). +# TYPE tensorfold:pinned_memory_bytes gauge +tensorfold:pinned_memory_bytes 0 +# HELP tensorfold:num_requests_running Requests in prefill or decode. A mirror of tensorfold:requests_running. +# TYPE tensorfold:num_requests_running gauge +tensorfold:num_requests_running 0 +# HELP tensorfold:num_requests_waiting Requests queued or held until a lane is free. A mirror of tensorfold:requests_waiting. +# TYPE tensorfold:num_requests_waiting gauge +tensorfold:num_requests_waiting 0 +# HELP tensorfold:kv_cache_usage_perc A stream's cache occupancy under vLLM's name; same streams and ratios as tensorfold:kv_cache_usage_ratio. +# TYPE tensorfold:kv_cache_usage_perc gauge +tensorfold:kv_cache_usage_perc{stream="0"} 0 +# HELP tensorfold:spec_decode_num_draft_tokens_total Draft tokens verified on finished requests, this server's single draft counter. +# TYPE tensorfold:spec_decode_num_draft_tokens_total counter +tensorfold:spec_decode_num_draft_tokens_total 0 +# HELP tensorfold:spec_decode_num_accepted_tokens_total Draft tokens kept on finished requests. +# TYPE tensorfold:spec_decode_num_accepted_tokens_total counter +tensorfold:spec_decode_num_accepted_tokens_total 0 +# HELP tensorfold:e2e_request_latency_seconds Seconds from arrival to the reply leaving, under vLLM's name. +# TYPE tensorfold:e2e_request_latency_seconds histogram +tensorfold:e2e_request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="1"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="10"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="30"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="60"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="120"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="300"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:e2e_request_latency_seconds_sum 47.171496 +tensorfold:e2e_request_latency_seconds_count 2 +# HELP tensorfold:request_decode_time_seconds Seconds a finished request spent decoding, under vLLM's name. +# TYPE tensorfold:request_decode_time_seconds histogram +tensorfold:request_decode_time_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="10"} 2 +tensorfold:request_decode_time_seconds_bucket{le="30"} 2 +tensorfold:request_decode_time_seconds_bucket{le="60"} 2 +tensorfold:request_decode_time_seconds_bucket{le="120"} 2 +tensorfold:request_decode_time_seconds_bucket{le="300"} 2 +tensorfold:request_decode_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_time_seconds_sum 0.000233 +tensorfold:request_decode_time_seconds_count 2 +# HELP tensorfold:request_prefill_time_seconds Seconds a finished request's prompt pass took, under vLLM's name. +# TYPE tensorfold:request_prefill_time_seconds histogram +tensorfold:request_prefill_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.5"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="1"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="60"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="120"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_time_seconds_sum 47.170323 +tensorfold:request_prefill_time_seconds_count 2 +# HELP tensorfold:client_disconnections_total Requests a client left before the reply left the server. +# TYPE tensorfold:client_disconnections_total counter +tensorfold:client_disconnections_total 0 +# HELP tensorfold:preemptions_total Requests that had to give a lane up to a later one. +# TYPE tensorfold:preemptions_total counter +tensorfold:preemptions_total 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-base-r1-samples.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-base-r1-samples.jsonl new file mode 100644 index 0000000000..7915faec93 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-base-r1-samples.jsonl @@ -0,0 +1,48 @@ +{"t_s": 0.0, "VmRSS_bytes": 2093056, "VmHWM_bytes": 2093056, "Pss_bytes": 159744, "vram_used_bytes": 187670528, "vram_total_bytes": 4294967296, "gtt_used_bytes": 31657984, "gtt_total_bytes": 193273528320} +{"t_s": 1.04, "VmRSS_bytes": 9660817408, "VmHWM_bytes": 9660817408, "Pss_bytes": 9658502144, "vram_used_bytes": 188764160, "vram_total_bytes": 4294967296, "gtt_used_bytes": 6821748736, "gtt_total_bytes": 193273528320} +{"t_s": 2.11, "VmRSS_bytes": 18030260224, "VmHWM_bytes": 18030260224, "Pss_bytes": 18100689920, "vram_used_bytes": 189304832, "vram_total_bytes": 4294967296, "gtt_used_bytes": 15021613056, "gtt_total_bytes": 193273528320} +{"t_s": 3.2, "VmRSS_bytes": 26408595456, "VmHWM_bytes": 26408595456, "Pss_bytes": 26406280192, "vram_used_bytes": 189890560, "vram_total_bytes": 4294967296, "gtt_used_bytes": 24163098624, "gtt_total_bytes": 193273528320} +{"t_s": 4.33, "VmRSS_bytes": 34563207168, "VmHWM_bytes": 34563207168, "Pss_bytes": 34560891904, "vram_used_bytes": 190537728, "vram_total_bytes": 4294967296, "gtt_used_bytes": 33038245888, "gtt_total_bytes": 193273528320} +{"t_s": 5.47, "VmRSS_bytes": 44197867520, "VmHWM_bytes": 44197867520, "Pss_bytes": 44196404224, "vram_used_bytes": 191098880, "vram_total_bytes": 4294967296, "gtt_used_bytes": 41238110208, "gtt_total_bytes": 193273528320} +{"t_s": 6.65, "VmRSS_bytes": 52405661696, "VmHWM_bytes": 52405661696, "Pss_bytes": 52403346432, "vram_used_bytes": 191766528, "vram_total_bytes": 4294967296, "gtt_used_bytes": 51067461632, "gtt_total_bytes": 193273528320} +{"t_s": 7.85, "VmRSS_bytes": 62138990592, "VmHWM_bytes": 62138990592, "Pss_bytes": 62136675328, "vram_used_bytes": 192446464, "vram_total_bytes": 4294967296, "gtt_used_bytes": 60901007360, "gtt_total_bytes": 193273528320} +{"t_s": 9.07, "VmRSS_bytes": 71869841408, "VmHWM_bytes": 71869841408, "Pss_bytes": 71867526144, "vram_used_bytes": 193093632, "vram_total_bytes": 4294967296, "gtt_used_bytes": 70730358784, "gtt_total_bytes": 193273528320} +{"t_s": 10.3, "VmRSS_bytes": 82466185216, "VmHWM_bytes": 82466185216, "Pss_bytes": 82463869952, "vram_used_bytes": 194863104, "vram_total_bytes": 4294967296, "gtt_used_bytes": 80570195968, "gtt_total_bytes": 193273528320} +{"t_s": 11.56, "VmRSS_bytes": 81073180672, "VmHWM_bytes": 82467528704, "Pss_bytes": 81070861312, "vram_used_bytes": 194883584, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84284252160, "gtt_total_bytes": 193273528320} +{"t_s": 12.84, "VmRSS_bytes": 81577578496, "VmHWM_bytes": 82467528704, "Pss_bytes": 81575259136, "vram_used_bytes": 194879488, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 14.1, "VmRSS_bytes": 82057465856, "VmHWM_bytes": 82467528704, "Pss_bytes": 82055146496, "vram_used_bytes": 194879488, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 15.37, "VmRSS_bytes": 82057465856, "VmHWM_bytes": 82467528704, "Pss_bytes": 82055146496, "vram_used_bytes": 194879488, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 16.65, "VmRSS_bytes": 82519113728, "VmHWM_bytes": 82519113728, "Pss_bytes": 82516794368, "vram_used_bytes": 194879488, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 17.93, "VmRSS_bytes": 82519113728, "VmHWM_bytes": 82519113728, "Pss_bytes": 82516794368, "vram_used_bytes": 194879488, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 19.19, "VmRSS_bytes": 82519113728, "VmHWM_bytes": 82519113728, "Pss_bytes": 82516794368, "vram_used_bytes": 194879488, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 20.48, "VmRSS_bytes": 82896752640, "VmHWM_bytes": 82896752640, "Pss_bytes": 82894433280, "vram_used_bytes": 194879488, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 21.77, "VmRSS_bytes": 82896752640, "VmHWM_bytes": 82896752640, "Pss_bytes": 82894433280, "vram_used_bytes": 194879488, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 23.05, "VmRSS_bytes": 83099209728, "VmHWM_bytes": 83099209728, "Pss_bytes": 83096890368, "vram_used_bytes": 194879488, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 24.33, "VmRSS_bytes": 83099209728, "VmHWM_bytes": 83099209728, "Pss_bytes": 83096890368, "vram_used_bytes": 194879488, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 25.62, "VmRSS_bytes": 83410903040, "VmHWM_bytes": 83410903040, "Pss_bytes": 83408581632, "vram_used_bytes": 194879488, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 26.91, "VmRSS_bytes": 83410903040, "VmHWM_bytes": 83410903040, "Pss_bytes": 83408583680, "vram_used_bytes": 194879488, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 28.18, "VmRSS_bytes": 83410903040, "VmHWM_bytes": 83410903040, "Pss_bytes": 83513854976, "vram_used_bytes": 194879488, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 29.46, "VmRSS_bytes": 83516182528, "VmHWM_bytes": 83516182528, "Pss_bytes": 83513863168, "vram_used_bytes": 194879488, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 30.74, "VmRSS_bytes": 83516182528, "VmHWM_bytes": 83516182528, "Pss_bytes": 83513863168, "vram_used_bytes": 194879488, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 32.02, "VmRSS_bytes": 83604557824, "VmHWM_bytes": 83604557824, "Pss_bytes": 83602238464, "vram_used_bytes": 194879488, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 33.3, "VmRSS_bytes": 83604557824, "VmHWM_bytes": 83604557824, "Pss_bytes": 83602238464, "vram_used_bytes": 194879488, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 34.6, "VmRSS_bytes": 83749773312, "VmHWM_bytes": 83749773312, "Pss_bytes": 83747453952, "vram_used_bytes": 194879488, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 35.88, "VmRSS_bytes": 83749773312, "VmHWM_bytes": 83749773312, "Pss_bytes": 83747453952, "vram_used_bytes": 194879488, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 37.16, "VmRSS_bytes": 83749773312, "VmHWM_bytes": 83749773312, "Pss_bytes": 83861261312, "vram_used_bytes": 194879488, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 38.45, "VmRSS_bytes": 83863588864, "VmHWM_bytes": 83863588864, "Pss_bytes": 83861269504, "vram_used_bytes": 194879488, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 39.73, "VmRSS_bytes": 83863588864, "VmHWM_bytes": 83863588864, "Pss_bytes": 83861269504, "vram_used_bytes": 194879488, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 41.02, "VmRSS_bytes": 83945177088, "VmHWM_bytes": 83945177088, "Pss_bytes": 83942857728, "vram_used_bytes": 194879488, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 42.31, "VmRSS_bytes": 83945177088, "VmHWM_bytes": 83945177088, "Pss_bytes": 83942857728, "vram_used_bytes": 194879488, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 43.59, "VmRSS_bytes": 84034400256, "VmHWM_bytes": 84034400256, "Pss_bytes": 84032080896, "vram_used_bytes": 194879488, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 44.88, "VmRSS_bytes": 84034400256, "VmHWM_bytes": 84034400256, "Pss_bytes": 84032080896, "vram_used_bytes": 194879488, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 46.16, "VmRSS_bytes": 84034400256, "VmHWM_bytes": 84034400256, "Pss_bytes": 84032080896, "vram_used_bytes": 194879488, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 47.45, "VmRSS_bytes": 84113747968, "VmHWM_bytes": 84113747968, "Pss_bytes": 84111426560, "vram_used_bytes": 194879488, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 48.74, "VmRSS_bytes": 84113747968, "VmHWM_bytes": 84113747968, "Pss_bytes": 84111428608, "vram_used_bytes": 194879488, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 50.04, "VmRSS_bytes": 84190126080, "VmHWM_bytes": 84190126080, "Pss_bytes": 84187806720, "vram_used_bytes": 194879488, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 51.33, "VmRSS_bytes": 84190126080, "VmHWM_bytes": 84190126080, "Pss_bytes": 84187806720, "vram_used_bytes": 194879488, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 52.62, "VmRSS_bytes": 84271910912, "VmHWM_bytes": 84271910912, "Pss_bytes": 84269591552, "vram_used_bytes": 194879488, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 53.91, "VmRSS_bytes": 84271910912, "VmHWM_bytes": 84271910912, "Pss_bytes": 84269591552, "vram_used_bytes": 194879488, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 55.19, "VmRSS_bytes": 84271910912, "VmHWM_bytes": 84271910912, "Pss_bytes": 84269591552, "vram_used_bytes": 194879488, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 56.49, "VmRSS_bytes": 84332322816, "VmHWM_bytes": 84332322816, "Pss_bytes": 84330002432, "vram_used_bytes": 194879488, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 57.78, "VmRSS_bytes": 84332322816, "VmHWM_bytes": 84332322816, "Pss_bytes": 84330003456, "vram_used_bytes": 194879488, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 59.06, "VmRSS_bytes": 84262506496, "VmHWM_bytes": 84330569728, "Pss_bytes": 84260188160, "vram_used_bytes": 194748416, "vram_total_bytes": 4294967296, "gtt_used_bytes": 45734404096, "gtt_total_bytes": 193273528320} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-base-r2-memory-endpoint.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-base-r2-memory-endpoint.json new file mode 100644 index 0000000000..586f5af8d2 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-base-r2-memory-endpoint.json @@ -0,0 +1 @@ +{"schema_version": 1, "context_window": 20480, "context_fitted": false, "device": {"active_bytes": 83402378688, "cache_bytes": 0, "peak_bytes": 83441722820, "peak_scope": "since_start_or_health_reset"}} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-base-r2-metrics.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-base-r2-metrics.txt new file mode 100644 index 0000000000..7d968896f5 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-base-r2-metrics.txt @@ -0,0 +1,220 @@ +# HELP tensorfold:requests_running Requests in prefill or decode. +# TYPE tensorfold:requests_running gauge +tensorfold:requests_running 0 +# HELP tensorfold:requests_waiting Requests queued or held until a lane is free. +# TYPE tensorfold:requests_waiting gauge +tensorfold:requests_waiting 0 +# HELP tensorfold:generation_tokens_running Generated tokens held by live streams. +# TYPE tensorfold:generation_tokens_running gauge +tensorfold:generation_tokens_running 0 +# HELP tensorfold:prompt_tokens_total Prompt tokens of finished requests. +# TYPE tensorfold:prompt_tokens_total counter +tensorfold:prompt_tokens_total 16640 +# HELP tensorfold:generation_tokens_total Generated tokens of finished requests. +# TYPE tensorfold:generation_tokens_total counter +tensorfold:generation_tokens_total 2 +# HELP tensorfold:kv_cache_usage_ratio Tokens in a stream cache divided by that stream's context window. +# TYPE tensorfold:kv_cache_usage_ratio gauge +tensorfold:kv_cache_usage_ratio{pool="0"} 0 +# HELP tensorfold:mtp_drafted_total Draft tokens verified on finished requests. +# TYPE tensorfold:mtp_drafted_total counter +tensorfold:mtp_drafted_total 0 +# HELP tensorfold:mtp_accepted_total Draft tokens kept on finished requests. +# TYPE tensorfold:mtp_accepted_total counter +tensorfold:mtp_accepted_total 0 +# HELP tensorfold:request_latency_seconds Seconds from arrival to the reply leaving. +# TYPE tensorfold:request_latency_seconds histogram +tensorfold:request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:request_latency_seconds_bucket{le="1"} 1 +tensorfold:request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:request_latency_seconds_bucket{le="5"} 1 +tensorfold:request_latency_seconds_bucket{le="10"} 1 +tensorfold:request_latency_seconds_bucket{le="30"} 1 +tensorfold:request_latency_seconds_bucket{le="60"} 2 +tensorfold:request_latency_seconds_bucket{le="120"} 2 +tensorfold:request_latency_seconds_bucket{le="300"} 2 +tensorfold:request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:request_latency_seconds_sum 47.167193 +tensorfold:request_latency_seconds_count 2 +# HELP tensorfold:time_to_first_token_seconds Seconds from arrival to the first generated token. +# TYPE tensorfold:time_to_first_token_seconds histogram +tensorfold:time_to_first_token_seconds_bucket{le="0.01"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.05"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.25"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.5"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="1"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="2.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="10"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="30"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="60"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="120"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="300"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="+Inf"} 2 +tensorfold:time_to_first_token_seconds_sum 47.166775 +tensorfold:time_to_first_token_seconds_count 2 +# HELP tensorfold:request_decode_seconds Seconds a finished request spent decoding. Its sum over generation_tokens_total is the decode rate. +# TYPE tensorfold:request_decode_seconds histogram +tensorfold:request_decode_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_seconds_bucket{le="1"} 2 +tensorfold:request_decode_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_seconds_bucket{le="5"} 2 +tensorfold:request_decode_seconds_bucket{le="10"} 2 +tensorfold:request_decode_seconds_bucket{le="30"} 2 +tensorfold:request_decode_seconds_bucket{le="60"} 2 +tensorfold:request_decode_seconds_bucket{le="120"} 2 +tensorfold:request_decode_seconds_bucket{le="300"} 2 +tensorfold:request_decode_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_seconds_sum 0.000418 +tensorfold:request_decode_seconds_count 2 +# HELP tensorfold:request_time_per_output_token_seconds Seconds from the first generated token to the last, divided by the tokens less one. +# TYPE tensorfold:request_time_per_output_token_seconds histogram +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.005"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.01"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.015"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.02"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.03"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.04"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.05"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.15"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.2"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.3"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.5"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="+Inf"} 0 +tensorfold:request_time_per_output_token_seconds_sum 0 +tensorfold:request_time_per_output_token_seconds_count 0 +# HELP tensorfold:decode_rounds_total Decode rounds used by finished requests. +# TYPE tensorfold:decode_rounds_total counter +tensorfold:decode_rounds_total 0 +# HELP tensorfold:request_prefill_seconds Seconds a finished request's prompt pass took. +# TYPE tensorfold:request_prefill_seconds histogram +tensorfold:request_prefill_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.5"} 0 +tensorfold:request_prefill_seconds_bucket{le="1"} 1 +tensorfold:request_prefill_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_seconds_bucket{le="60"} 2 +tensorfold:request_prefill_seconds_bucket{le="120"} 2 +tensorfold:request_prefill_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_seconds_sum 47.165353 +tensorfold:request_prefill_seconds_count 2 +# HELP tensorfold:process_resident_bytes Current resident set (VmRSS); device memory is not in it, so it is not a physical footprint (Linux). +# TYPE tensorfold:process_resident_bytes gauge +tensorfold:process_resident_bytes 84355194880 +# HELP tensorfold:process_resident_anon_bytes Current resident anonymous memory (RssAnon): heap, stacks and private maps (Linux). +# TYPE tensorfold:process_resident_anon_bytes gauge +tensorfold:process_resident_anon_bytes 306782208 +# HELP tensorfold:process_resident_file_bytes Current resident file-backed memory (RssFile): the binary, libraries and mapped files (Linux). +# TYPE tensorfold:process_resident_file_bytes gauge +tensorfold:process_resident_file_bytes 83936509952 +# HELP tensorfold:process_resident_shmem_bytes Current resident shared memory (RssShmem): System V shared memory, tmpfs maps and shared anonymous maps (Linux). +# TYPE tensorfold:process_resident_shmem_bytes gauge +tensorfold:process_resident_shmem_bytes 111902720 +# HELP tensorfold:process_resident_peak_bytes Kernel lifetime peak resident set (VmHWM); never reset by health (Linux). +# TYPE tensorfold:process_resident_peak_bytes gauge +tensorfold:process_resident_peak_bytes 84355194880 +# HELP tensorfold:device_memory_bytes Device memory the engine holds now: weights, caches and live streams; only where the backend counts it (CUDA). +# TYPE tensorfold:device_memory_bytes gauge +tensorfold:device_memory_bytes 83402378688 +# HELP tensorfold:device_memory_peak_bytes The most device memory the engine has held since start or the last /health?reset_peak=1. +# TYPE tensorfold:device_memory_peak_bytes gauge +tensorfold:device_memory_peak_bytes 83441722820 +# HELP tensorfold:pinned_memory_bytes Pinned host memory the engine holds now: staging buffers and windows; only where the backend counts it (CUDA). +# TYPE tensorfold:pinned_memory_bytes gauge +tensorfold:pinned_memory_bytes 0 +# HELP tensorfold:num_requests_running Requests in prefill or decode. A mirror of tensorfold:requests_running. +# TYPE tensorfold:num_requests_running gauge +tensorfold:num_requests_running 0 +# HELP tensorfold:num_requests_waiting Requests queued or held until a lane is free. A mirror of tensorfold:requests_waiting. +# TYPE tensorfold:num_requests_waiting gauge +tensorfold:num_requests_waiting 0 +# HELP tensorfold:kv_cache_usage_perc A stream's cache occupancy under vLLM's name; same streams and ratios as tensorfold:kv_cache_usage_ratio. +# TYPE tensorfold:kv_cache_usage_perc gauge +tensorfold:kv_cache_usage_perc{stream="0"} 0 +# HELP tensorfold:spec_decode_num_draft_tokens_total Draft tokens verified on finished requests, this server's single draft counter. +# TYPE tensorfold:spec_decode_num_draft_tokens_total counter +tensorfold:spec_decode_num_draft_tokens_total 0 +# HELP tensorfold:spec_decode_num_accepted_tokens_total Draft tokens kept on finished requests. +# TYPE tensorfold:spec_decode_num_accepted_tokens_total counter +tensorfold:spec_decode_num_accepted_tokens_total 0 +# HELP tensorfold:e2e_request_latency_seconds Seconds from arrival to the reply leaving, under vLLM's name. +# TYPE tensorfold:e2e_request_latency_seconds histogram +tensorfold:e2e_request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="1"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="10"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="30"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="60"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="120"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="300"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:e2e_request_latency_seconds_sum 47.167193 +tensorfold:e2e_request_latency_seconds_count 2 +# HELP tensorfold:request_decode_time_seconds Seconds a finished request spent decoding, under vLLM's name. +# TYPE tensorfold:request_decode_time_seconds histogram +tensorfold:request_decode_time_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="10"} 2 +tensorfold:request_decode_time_seconds_bucket{le="30"} 2 +tensorfold:request_decode_time_seconds_bucket{le="60"} 2 +tensorfold:request_decode_time_seconds_bucket{le="120"} 2 +tensorfold:request_decode_time_seconds_bucket{le="300"} 2 +tensorfold:request_decode_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_time_seconds_sum 0.000418 +tensorfold:request_decode_time_seconds_count 2 +# HELP tensorfold:request_prefill_time_seconds Seconds a finished request's prompt pass took, under vLLM's name. +# TYPE tensorfold:request_prefill_time_seconds histogram +tensorfold:request_prefill_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.5"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="1"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="60"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="120"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_time_seconds_sum 47.165353 +tensorfold:request_prefill_time_seconds_count 2 +# HELP tensorfold:client_disconnections_total Requests a client left before the reply left the server. +# TYPE tensorfold:client_disconnections_total counter +tensorfold:client_disconnections_total 0 +# HELP tensorfold:preemptions_total Requests that had to give a lane up to a later one. +# TYPE tensorfold:preemptions_total counter +tensorfold:preemptions_total 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-base-r2-samples.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-base-r2-samples.jsonl new file mode 100644 index 0000000000..e73ee1c715 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-base-r2-samples.jsonl @@ -0,0 +1,48 @@ +{"t_s": 0.0, "VmRSS_bytes": 2183168, "VmHWM_bytes": 2183168, "Pss_bytes": 164864, "vram_used_bytes": 187670528, "vram_total_bytes": 4294967296, "gtt_used_bytes": 31657984, "gtt_total_bytes": 193273528320} +{"t_s": 1.04, "VmRSS_bytes": 9540059136, "VmHWM_bytes": 9540059136, "Pss_bytes": 9569979392, "vram_used_bytes": 188784640, "vram_total_bytes": 4294967296, "gtt_used_bytes": 6821748736, "gtt_total_bytes": 193273528320} +{"t_s": 2.11, "VmRSS_bytes": 17886040064, "VmHWM_bytes": 17886040064, "Pss_bytes": 17912945664, "vram_used_bytes": 189337600, "vram_total_bytes": 4294967296, "gtt_used_bytes": 15021613056, "gtt_total_bytes": 193273528320} +{"t_s": 3.21, "VmRSS_bytes": 26411175936, "VmHWM_bytes": 26411175936, "Pss_bytes": 26408721408, "vram_used_bytes": 189919232, "vram_total_bytes": 4294967296, "gtt_used_bytes": 24163098624, "gtt_total_bytes": 193273528320} +{"t_s": 4.34, "VmRSS_bytes": 34565787648, "VmHWM_bytes": 34565787648, "Pss_bytes": 34563333120, "vram_used_bytes": 190570496, "vram_total_bytes": 4294967296, "gtt_used_bytes": 33038245888, "gtt_total_bytes": 193273528320} +{"t_s": 5.48, "VmRSS_bytes": 44201299968, "VmHWM_bytes": 44201299968, "Pss_bytes": 44203695104, "vram_used_bytes": 191131648, "vram_total_bytes": 4294967296, "gtt_used_bytes": 41238110208, "gtt_total_bytes": 193273528320} +{"t_s": 6.66, "VmRSS_bytes": 52408242176, "VmHWM_bytes": 52408242176, "Pss_bytes": 52405787648, "vram_used_bytes": 191795200, "vram_total_bytes": 4294967296, "gtt_used_bytes": 51067461632, "gtt_total_bytes": 193273528320} +{"t_s": 7.86, "VmRSS_bytes": 62139936768, "VmHWM_bytes": 62139936768, "Pss_bytes": 62138924032, "vram_used_bytes": 192475136, "vram_total_bytes": 4294967296, "gtt_used_bytes": 60901007360, "gtt_total_bytes": 193273528320} +{"t_s": 9.08, "VmRSS_bytes": 71872225280, "VmHWM_bytes": 71872225280, "Pss_bytes": 71869770752, "vram_used_bytes": 193171456, "vram_total_bytes": 4294967296, "gtt_used_bytes": 70730358784, "gtt_total_bytes": 193273528320} +{"t_s": 10.31, "VmRSS_bytes": 82468581376, "VmHWM_bytes": 82468581376, "Pss_bytes": 82466126848, "vram_used_bytes": 195170304, "vram_total_bytes": 4294967296, "gtt_used_bytes": 80677150720, "gtt_total_bytes": 193273528320} +{"t_s": 11.56, "VmRSS_bytes": 81078104064, "VmHWM_bytes": 82471129088, "Pss_bytes": 81075646464, "vram_used_bytes": 195186688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84284252160, "gtt_total_bytes": 193273528320} +{"t_s": 12.83, "VmRSS_bytes": 81587503104, "VmHWM_bytes": 82471129088, "Pss_bytes": 81585045504, "vram_used_bytes": 195186688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 14.1, "VmRSS_bytes": 82070421504, "VmHWM_bytes": 82471129088, "Pss_bytes": 82067963904, "vram_used_bytes": 195186688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 15.36, "VmRSS_bytes": 82070421504, "VmHWM_bytes": 82471129088, "Pss_bytes": 82067963904, "vram_used_bytes": 195186688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 16.63, "VmRSS_bytes": 82534240256, "VmHWM_bytes": 82534240256, "Pss_bytes": 82531782656, "vram_used_bytes": 195186688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 17.9, "VmRSS_bytes": 82534240256, "VmHWM_bytes": 82534240256, "Pss_bytes": 82531782656, "vram_used_bytes": 195186688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 19.16, "VmRSS_bytes": 82534240256, "VmHWM_bytes": 82534240256, "Pss_bytes": 82531782656, "vram_used_bytes": 195186688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 20.44, "VmRSS_bytes": 82910363648, "VmHWM_bytes": 82910363648, "Pss_bytes": 82907906048, "vram_used_bytes": 195186688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 21.72, "VmRSS_bytes": 82910363648, "VmHWM_bytes": 82910363648, "Pss_bytes": 82907906048, "vram_used_bytes": 195186688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 23.0, "VmRSS_bytes": 83115528192, "VmHWM_bytes": 83115528192, "Pss_bytes": 83113070592, "vram_used_bytes": 195186688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 24.28, "VmRSS_bytes": 83115528192, "VmHWM_bytes": 83115528192, "Pss_bytes": 83113070592, "vram_used_bytes": 195186688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 25.56, "VmRSS_bytes": 83428319232, "VmHWM_bytes": 83428319232, "Pss_bytes": 83425861632, "vram_used_bytes": 195186688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 26.84, "VmRSS_bytes": 83428319232, "VmHWM_bytes": 83428319232, "Pss_bytes": 83425861632, "vram_used_bytes": 195186688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 28.11, "VmRSS_bytes": 83428319232, "VmHWM_bytes": 83428319232, "Pss_bytes": 83517530112, "vram_used_bytes": 195186688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 29.4, "VmRSS_bytes": 83533803520, "VmHWM_bytes": 83533803520, "Pss_bytes": 83531345920, "vram_used_bytes": 195186688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 30.69, "VmRSS_bytes": 83533803520, "VmHWM_bytes": 83533803520, "Pss_bytes": 83531345920, "vram_used_bytes": 195186688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 31.98, "VmRSS_bytes": 83622522880, "VmHWM_bytes": 83622522880, "Pss_bytes": 83620065280, "vram_used_bytes": 195186688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 33.27, "VmRSS_bytes": 83624333312, "VmHWM_bytes": 83624333312, "Pss_bytes": 83621875712, "vram_used_bytes": 195186688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 34.56, "VmRSS_bytes": 83770613760, "VmHWM_bytes": 83770613760, "Pss_bytes": 83768156160, "vram_used_bytes": 195186688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 35.84, "VmRSS_bytes": 83770613760, "VmHWM_bytes": 83770613760, "Pss_bytes": 83768156160, "vram_used_bytes": 195186688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 37.12, "VmRSS_bytes": 83770613760, "VmHWM_bytes": 83770613760, "Pss_bytes": 83882266624, "vram_used_bytes": 195186688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 38.41, "VmRSS_bytes": 83884740608, "VmHWM_bytes": 83884740608, "Pss_bytes": 83882283008, "vram_used_bytes": 195186688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 39.71, "VmRSS_bytes": 83884740608, "VmHWM_bytes": 83884740608, "Pss_bytes": 83882283008, "vram_used_bytes": 195186688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 41.0, "VmRSS_bytes": 83966656512, "VmHWM_bytes": 83966656512, "Pss_bytes": 83964198912, "vram_used_bytes": 195186688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 42.3, "VmRSS_bytes": 83966656512, "VmHWM_bytes": 83966656512, "Pss_bytes": 83964198912, "vram_used_bytes": 195186688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 43.59, "VmRSS_bytes": 84056457216, "VmHWM_bytes": 84056457216, "Pss_bytes": 84053999616, "vram_used_bytes": 195186688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 44.88, "VmRSS_bytes": 84056457216, "VmHWM_bytes": 84056457216, "Pss_bytes": 84053999616, "vram_used_bytes": 195186688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 46.16, "VmRSS_bytes": 84056457216, "VmHWM_bytes": 84056457216, "Pss_bytes": 84054069248, "vram_used_bytes": 195186688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 47.46, "VmRSS_bytes": 84136333312, "VmHWM_bytes": 84136333312, "Pss_bytes": 84133875712, "vram_used_bytes": 195186688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 48.75, "VmRSS_bytes": 84136333312, "VmHWM_bytes": 84136333312, "Pss_bytes": 84133875712, "vram_used_bytes": 195186688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 50.04, "VmRSS_bytes": 84213391360, "VmHWM_bytes": 84213391360, "Pss_bytes": 84210933760, "vram_used_bytes": 195186688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 51.33, "VmRSS_bytes": 84213391360, "VmHWM_bytes": 84213391360, "Pss_bytes": 84210933760, "vram_used_bytes": 195186688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 52.62, "VmRSS_bytes": 84295487488, "VmHWM_bytes": 84295487488, "Pss_bytes": 84293029888, "vram_used_bytes": 195186688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 53.92, "VmRSS_bytes": 84295487488, "VmHWM_bytes": 84295487488, "Pss_bytes": 84293029888, "vram_used_bytes": 195186688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 55.19, "VmRSS_bytes": 84295487488, "VmHWM_bytes": 84295487488, "Pss_bytes": 84293029888, "vram_used_bytes": 195186688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 56.48, "VmRSS_bytes": 84356018176, "VmHWM_bytes": 84356018176, "Pss_bytes": 84353560576, "vram_used_bytes": 195186688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 57.77, "VmRSS_bytes": 84356018176, "VmHWM_bytes": 84356018176, "Pss_bytes": 84353560576, "vram_used_bytes": 195186688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84324098048, "gtt_total_bytes": 193273528320} +{"t_s": 59.04, "VmRSS_bytes": 84286201856, "VmHWM_bytes": 84353622016, "Pss_bytes": 84283744256, "vram_used_bytes": 195051520, "vram_total_bytes": 4294967296, "gtt_used_bytes": 50595602432, "gtt_total_bytes": 193273528320} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-default-r1-memory-endpoint.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-default-r1-memory-endpoint.json new file mode 100644 index 0000000000..faf691d2fa --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-default-r1-memory-endpoint.json @@ -0,0 +1 @@ +{"schema_version": 1, "context_window": 20480, "context_fitted": false, "device": {"active_bytes": 87856892564, "cache_bytes": 0, "peak_bytes": 87896410020, "peak_scope": "since_start_or_health_reset"}} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-default-r1-metrics.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-default-r1-metrics.txt new file mode 100644 index 0000000000..d36a60c258 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-default-r1-metrics.txt @@ -0,0 +1,220 @@ +# HELP tensorfold:requests_running Requests in prefill or decode. +# TYPE tensorfold:requests_running gauge +tensorfold:requests_running 0 +# HELP tensorfold:requests_waiting Requests queued or held until a lane is free. +# TYPE tensorfold:requests_waiting gauge +tensorfold:requests_waiting 0 +# HELP tensorfold:generation_tokens_running Generated tokens held by live streams. +# TYPE tensorfold:generation_tokens_running gauge +tensorfold:generation_tokens_running 0 +# HELP tensorfold:prompt_tokens_total Prompt tokens of finished requests. +# TYPE tensorfold:prompt_tokens_total counter +tensorfold:prompt_tokens_total 16640 +# HELP tensorfold:generation_tokens_total Generated tokens of finished requests. +# TYPE tensorfold:generation_tokens_total counter +tensorfold:generation_tokens_total 2 +# HELP tensorfold:kv_cache_usage_ratio Tokens in a stream cache divided by that stream's context window. +# TYPE tensorfold:kv_cache_usage_ratio gauge +tensorfold:kv_cache_usage_ratio{pool="0"} 0 +# HELP tensorfold:mtp_drafted_total Draft tokens verified on finished requests. +# TYPE tensorfold:mtp_drafted_total counter +tensorfold:mtp_drafted_total 0 +# HELP tensorfold:mtp_accepted_total Draft tokens kept on finished requests. +# TYPE tensorfold:mtp_accepted_total counter +tensorfold:mtp_accepted_total 0 +# HELP tensorfold:request_latency_seconds Seconds from arrival to the reply leaving. +# TYPE tensorfold:request_latency_seconds histogram +tensorfold:request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:request_latency_seconds_bucket{le="0.5"} 1 +tensorfold:request_latency_seconds_bucket{le="1"} 1 +tensorfold:request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:request_latency_seconds_bucket{le="5"} 1 +tensorfold:request_latency_seconds_bucket{le="10"} 1 +tensorfold:request_latency_seconds_bucket{le="30"} 1 +tensorfold:request_latency_seconds_bucket{le="60"} 2 +tensorfold:request_latency_seconds_bucket{le="120"} 2 +tensorfold:request_latency_seconds_bucket{le="300"} 2 +tensorfold:request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:request_latency_seconds_sum 31.169424 +tensorfold:request_latency_seconds_count 2 +# HELP tensorfold:time_to_first_token_seconds Seconds from arrival to the first generated token. +# TYPE tensorfold:time_to_first_token_seconds histogram +tensorfold:time_to_first_token_seconds_bucket{le="0.01"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.05"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.25"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="1"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="2.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="10"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="30"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="60"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="120"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="300"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="+Inf"} 2 +tensorfold:time_to_first_token_seconds_sum 31.169194 +tensorfold:time_to_first_token_seconds_count 2 +# HELP tensorfold:request_decode_seconds Seconds a finished request spent decoding. Its sum over generation_tokens_total is the decode rate. +# TYPE tensorfold:request_decode_seconds histogram +tensorfold:request_decode_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_seconds_bucket{le="1"} 2 +tensorfold:request_decode_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_seconds_bucket{le="5"} 2 +tensorfold:request_decode_seconds_bucket{le="10"} 2 +tensorfold:request_decode_seconds_bucket{le="30"} 2 +tensorfold:request_decode_seconds_bucket{le="60"} 2 +tensorfold:request_decode_seconds_bucket{le="120"} 2 +tensorfold:request_decode_seconds_bucket{le="300"} 2 +tensorfold:request_decode_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_seconds_sum 0.00023 +tensorfold:request_decode_seconds_count 2 +# HELP tensorfold:request_time_per_output_token_seconds Seconds from the first generated token to the last, divided by the tokens less one. +# TYPE tensorfold:request_time_per_output_token_seconds histogram +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.005"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.01"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.015"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.02"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.03"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.04"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.05"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.15"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.2"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.3"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.5"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="+Inf"} 0 +tensorfold:request_time_per_output_token_seconds_sum 0 +tensorfold:request_time_per_output_token_seconds_count 0 +# HELP tensorfold:decode_rounds_total Decode rounds used by finished requests. +# TYPE tensorfold:decode_rounds_total counter +tensorfold:decode_rounds_total 0 +# HELP tensorfold:request_prefill_seconds Seconds a finished request's prompt pass took. +# TYPE tensorfold:request_prefill_seconds histogram +tensorfold:request_prefill_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="1"} 1 +tensorfold:request_prefill_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_seconds_bucket{le="60"} 2 +tensorfold:request_prefill_seconds_bucket{le="120"} 2 +tensorfold:request_prefill_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_seconds_sum 31.168365 +tensorfold:request_prefill_seconds_count 2 +# HELP tensorfold:process_resident_bytes Current resident set (VmRSS); device memory is not in it, so it is not a physical footprint (Linux). +# TYPE tensorfold:process_resident_bytes gauge +tensorfold:process_resident_bytes 105447247872 +# HELP tensorfold:process_resident_anon_bytes Current resident anonymous memory (RssAnon): heap, stacks and private maps (Linux). +# TYPE tensorfold:process_resident_anon_bytes gauge +tensorfold:process_resident_anon_bytes 32370921472 +# HELP tensorfold:process_resident_file_bytes Current resident file-backed memory (RssFile): the binary, libraries and mapped files (Linux). +# TYPE tensorfold:process_resident_file_bytes gauge +tensorfold:process_resident_file_bytes 72942063616 +# HELP tensorfold:process_resident_shmem_bytes Current resident shared memory (RssShmem): System V shared memory, tmpfs maps and shared anonymous maps (Linux). +# TYPE tensorfold:process_resident_shmem_bytes gauge +tensorfold:process_resident_shmem_bytes 134262784 +# HELP tensorfold:process_resident_peak_bytes Kernel lifetime peak resident set (VmHWM); never reset by health (Linux). +# TYPE tensorfold:process_resident_peak_bytes gauge +tensorfold:process_resident_peak_bytes 112582811648 +# HELP tensorfold:device_memory_bytes Device memory the engine holds now: weights, caches and live streams; only where the backend counts it (CUDA). +# TYPE tensorfold:device_memory_bytes gauge +tensorfold:device_memory_bytes 87856892564 +# HELP tensorfold:device_memory_peak_bytes The most device memory the engine has held since start or the last /health?reset_peak=1. +# TYPE tensorfold:device_memory_peak_bytes gauge +tensorfold:device_memory_peak_bytes 87896410020 +# HELP tensorfold:pinned_memory_bytes Pinned host memory the engine holds now: staging buffers and windows; only where the backend counts it (CUDA). +# TYPE tensorfold:pinned_memory_bytes gauge +tensorfold:pinned_memory_bytes 0 +# HELP tensorfold:num_requests_running Requests in prefill or decode. A mirror of tensorfold:requests_running. +# TYPE tensorfold:num_requests_running gauge +tensorfold:num_requests_running 0 +# HELP tensorfold:num_requests_waiting Requests queued or held until a lane is free. A mirror of tensorfold:requests_waiting. +# TYPE tensorfold:num_requests_waiting gauge +tensorfold:num_requests_waiting 0 +# HELP tensorfold:kv_cache_usage_perc A stream's cache occupancy under vLLM's name; same streams and ratios as tensorfold:kv_cache_usage_ratio. +# TYPE tensorfold:kv_cache_usage_perc gauge +tensorfold:kv_cache_usage_perc{stream="0"} 0 +# HELP tensorfold:spec_decode_num_draft_tokens_total Draft tokens verified on finished requests, this server's single draft counter. +# TYPE tensorfold:spec_decode_num_draft_tokens_total counter +tensorfold:spec_decode_num_draft_tokens_total 0 +# HELP tensorfold:spec_decode_num_accepted_tokens_total Draft tokens kept on finished requests. +# TYPE tensorfold:spec_decode_num_accepted_tokens_total counter +tensorfold:spec_decode_num_accepted_tokens_total 0 +# HELP tensorfold:e2e_request_latency_seconds Seconds from arrival to the reply leaving, under vLLM's name. +# TYPE tensorfold:e2e_request_latency_seconds histogram +tensorfold:e2e_request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="1"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="10"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="30"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="60"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="120"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="300"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:e2e_request_latency_seconds_sum 31.169424 +tensorfold:e2e_request_latency_seconds_count 2 +# HELP tensorfold:request_decode_time_seconds Seconds a finished request spent decoding, under vLLM's name. +# TYPE tensorfold:request_decode_time_seconds histogram +tensorfold:request_decode_time_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="10"} 2 +tensorfold:request_decode_time_seconds_bucket{le="30"} 2 +tensorfold:request_decode_time_seconds_bucket{le="60"} 2 +tensorfold:request_decode_time_seconds_bucket{le="120"} 2 +tensorfold:request_decode_time_seconds_bucket{le="300"} 2 +tensorfold:request_decode_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_time_seconds_sum 0.00023 +tensorfold:request_decode_time_seconds_count 2 +# HELP tensorfold:request_prefill_time_seconds Seconds a finished request's prompt pass took, under vLLM's name. +# TYPE tensorfold:request_prefill_time_seconds histogram +tensorfold:request_prefill_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="1"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="60"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="120"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_time_seconds_sum 31.168365 +tensorfold:request_prefill_time_seconds_count 2 +# HELP tensorfold:client_disconnections_total Requests a client left before the reply left the server. +# TYPE tensorfold:client_disconnections_total counter +tensorfold:client_disconnections_total 0 +# HELP tensorfold:preemptions_total Requests that had to give a lane up to a later one. +# TYPE tensorfold:preemptions_total counter +tensorfold:preemptions_total 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-default-r1-samples.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-default-r1-samples.jsonl new file mode 100644 index 0000000000..f0a6e29e25 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-default-r1-samples.jsonl @@ -0,0 +1,60 @@ +{"t_s": 0.0, "VmRSS_bytes": 76128256, "VmHWM_bytes": 76128256, "Pss_bytes": 74004480, "vram_used_bytes": 187682816, "vram_total_bytes": 4294967296, "gtt_used_bytes": 31657984, "gtt_total_bytes": 193273528320} +{"t_s": 1.01, "VmRSS_bytes": 5415100416, "VmHWM_bytes": 5415100416, "Pss_bytes": 5414731776, "vram_used_bytes": 188620800, "vram_total_bytes": 4294967296, "gtt_used_bytes": 3557093376, "gtt_total_bytes": 193273528320} +{"t_s": 2.03, "VmRSS_bytes": 10230288384, "VmHWM_bytes": 10230288384, "Pss_bytes": 10228011008, "vram_used_bytes": 188755968, "vram_total_bytes": 4294967296, "gtt_used_bytes": 8382640128, "gtt_total_bytes": 193273528320} +{"t_s": 3.06, "VmRSS_bytes": 14954147840, "VmHWM_bytes": 14954147840, "Pss_bytes": 14962814976, "vram_used_bytes": 189034496, "vram_total_bytes": 4294967296, "gtt_used_bytes": 11773734912, "gtt_total_bytes": 193273528320} +{"t_s": 4.1, "VmRSS_bytes": 19520716800, "VmHWM_bytes": 19520716800, "Pss_bytes": 19526828032, "vram_used_bytes": 189349888, "vram_total_bytes": 4294967296, "gtt_used_bytes": 16699944960, "gtt_total_bytes": 193273528320} +{"t_s": 5.16, "VmRSS_bytes": 24303886336, "VmHWM_bytes": 24303886336, "Pss_bytes": 24301608960, "vram_used_bytes": 189665280, "vram_total_bytes": 4294967296, "gtt_used_bytes": 21626155008, "gtt_total_bytes": 193273528320} +{"t_s": 6.23, "VmRSS_bytes": 29065224192, "VmHWM_bytes": 29065224192, "Pss_bytes": 29067018240, "vram_used_bytes": 189988864, "vram_total_bytes": 4294967296, "gtt_used_bytes": 26554462208, "gtt_total_bytes": 193273528320} +{"t_s": 7.3, "VmRSS_bytes": 33930608640, "VmHWM_bytes": 33930608640, "Pss_bytes": 33958219776, "vram_used_bytes": 190296064, "vram_total_bytes": 4294967296, "gtt_used_bytes": 31480672256, "gtt_total_bytes": 193273528320} +{"t_s": 8.39, "VmRSS_bytes": 38693736448, "VmHWM_bytes": 38693736448, "Pss_bytes": 38694076416, "vram_used_bytes": 190623744, "vram_total_bytes": 4294967296, "gtt_used_bytes": 36413173760, "gtt_total_bytes": 193273528320} +{"t_s": 9.5, "VmRSS_bytes": 43579723776, "VmHWM_bytes": 43579723776, "Pss_bytes": 43581902848, "vram_used_bytes": 190935040, "vram_total_bytes": 4294967296, "gtt_used_bytes": 41339383808, "gtt_total_bytes": 193273528320} +{"t_s": 10.62, "VmRSS_bytes": 48635002880, "VmHWM_bytes": 48635002880, "Pss_bytes": 48632725504, "vram_used_bytes": 191246336, "vram_total_bytes": 4294967296, "gtt_used_bytes": 46273982464, "gtt_total_bytes": 193273528320} +{"t_s": 11.74, "VmRSS_bytes": 53615325184, "VmHWM_bytes": 53615325184, "Pss_bytes": 53621436416, "vram_used_bytes": 191578112, "vram_total_bytes": 4294967296, "gtt_used_bytes": 51200192512, "gtt_total_bytes": 193273528320} +{"t_s": 12.87, "VmRSS_bytes": 58565324800, "VmHWM_bytes": 58565324800, "Pss_bytes": 58577989632, "vram_used_bytes": 191873024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 56132694016, "gtt_total_bytes": 193273528320} +{"t_s": 14.01, "VmRSS_bytes": 63405449216, "VmHWM_bytes": 63405449216, "Pss_bytes": 63408152576, "vram_used_bytes": 192200704, "vram_total_bytes": 4294967296, "gtt_used_bytes": 61058904064, "gtt_total_bytes": 193273528320} +{"t_s": 15.16, "VmRSS_bytes": 68302381056, "VmHWM_bytes": 68302381056, "Pss_bytes": 68308492288, "vram_used_bytes": 192512000, "vram_total_bytes": 4294967296, "gtt_used_bytes": 65987211264, "gtt_total_bytes": 193273528320} +{"t_s": 16.32, "VmRSS_bytes": 73022103552, "VmHWM_bytes": 73022103552, "Pss_bytes": 73024020480, "vram_used_bytes": 192823296, "vram_total_bytes": 4294967296, "gtt_used_bytes": 70913421312, "gtt_total_bytes": 193273528320} +{"t_s": 17.48, "VmRSS_bytes": 78036832256, "VmHWM_bytes": 78036832256, "Pss_bytes": 78042943488, "vram_used_bytes": 193134592, "vram_total_bytes": 4294967296, "gtt_used_bytes": 75845922816, "gtt_total_bytes": 193273528320} +{"t_s": 18.66, "VmRSS_bytes": 81053552640, "VmHWM_bytes": 82510254080, "Pss_bytes": 81033732096, "vram_used_bytes": 194162688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 19.82, "VmRSS_bytes": 84178399232, "VmHWM_bytes": 84178399232, "Pss_bytes": 83990315008, "vram_used_bytes": 194162688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 21.0, "VmRSS_bytes": 86745579520, "VmHWM_bytes": 86942826496, "Pss_bytes": 86789435392, "vram_used_bytes": 194162688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 22.17, "VmRSS_bytes": 89550139392, "VmHWM_bytes": 89695133696, "Pss_bytes": 89543667712, "vram_used_bytes": 194162688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 23.34, "VmRSS_bytes": 92625514496, "VmHWM_bytes": 92695592960, "Pss_bytes": 92587270144, "vram_used_bytes": 194162688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 24.52, "VmRSS_bytes": 95498649600, "VmHWM_bytes": 95498649600, "Pss_bytes": 95477972992, "vram_used_bytes": 194162688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 25.69, "VmRSS_bytes": 97919832064, "VmHWM_bytes": 98050453504, "Pss_bytes": 97900777472, "vram_used_bytes": 194162688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 26.87, "VmRSS_bytes": 100196093952, "VmHWM_bytes": 100299522048, "Pss_bytes": 100271734784, "vram_used_bytes": 194162688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 28.06, "VmRSS_bytes": 102708748288, "VmHWM_bytes": 102708748288, "Pss_bytes": 102601613312, "vram_used_bytes": 194162688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 29.27, "VmRSS_bytes": 104947601408, "VmHWM_bytes": 104947601408, "Pss_bytes": 104851779584, "vram_used_bytes": 194162688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 30.47, "VmRSS_bytes": 107226423296, "VmHWM_bytes": 107226423296, "Pss_bytes": 107102453760, "vram_used_bytes": 194162688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 31.69, "VmRSS_bytes": 109540216832, "VmHWM_bytes": 109542211584, "Pss_bytes": 109602312192, "vram_used_bytes": 194162688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 32.93, "VmRSS_bytes": 112119701504, "VmHWM_bytes": 112119701504, "Pss_bytes": 112252408832, "vram_used_bytes": 194166784, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 34.27, "VmRSS_bytes": 109392785408, "VmHWM_bytes": 112582811648, "Pss_bytes": 105856545792, "vram_used_bytes": 200855552, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88070221824, "gtt_total_bytes": 193273528320} +{"t_s": 35.52, "VmRSS_bytes": 105434132480, "VmHWM_bytes": 112582811648, "Pss_bytes": 105431793664, "vram_used_bytes": 200892416, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88823029760, "gtt_total_bytes": 193273528320} +{"t_s": 36.76, "VmRSS_bytes": 105438785536, "VmHWM_bytes": 112582811648, "Pss_bytes": 105436446720, "vram_used_bytes": 200896512, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88824135680, "gtt_total_bytes": 193273528320} +{"t_s": 37.98, "VmRSS_bytes": 105441697792, "VmHWM_bytes": 112582811648, "Pss_bytes": 105439358976, "vram_used_bytes": 200896512, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88824504320, "gtt_total_bytes": 193273528320} +{"t_s": 39.22, "VmRSS_bytes": 105447161856, "VmHWM_bytes": 112582811648, "Pss_bytes": 105444819968, "vram_used_bytes": 200892416, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 40.47, "VmRSS_bytes": 105447161856, "VmHWM_bytes": 112582811648, "Pss_bytes": 105444819968, "vram_used_bytes": 200892416, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 41.7, "VmRSS_bytes": 105447292928, "VmHWM_bytes": 112582811648, "Pss_bytes": 105444951040, "vram_used_bytes": 200892416, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 42.92, "VmRSS_bytes": 105447292928, "VmHWM_bytes": 112582811648, "Pss_bytes": 105444951040, "vram_used_bytes": 200892416, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 44.16, "VmRSS_bytes": 105447292928, "VmHWM_bytes": 112582811648, "Pss_bytes": 105444951040, "vram_used_bytes": 200892416, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 45.4, "VmRSS_bytes": 105447292928, "VmHWM_bytes": 112582811648, "Pss_bytes": 105444951040, "vram_used_bytes": 200892416, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 46.64, "VmRSS_bytes": 105447976960, "VmHWM_bytes": 112582811648, "Pss_bytes": 105445635072, "vram_used_bytes": 200892416, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 47.87, "VmRSS_bytes": 105447976960, "VmHWM_bytes": 112582811648, "Pss_bytes": 105445635072, "vram_used_bytes": 200892416, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 49.09, "VmRSS_bytes": 105447976960, "VmHWM_bytes": 112582811648, "Pss_bytes": 105445635072, "vram_used_bytes": 200892416, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 50.32, "VmRSS_bytes": 105447976960, "VmHWM_bytes": 112582811648, "Pss_bytes": 105445635072, "vram_used_bytes": 200892416, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 51.55, "VmRSS_bytes": 105447976960, "VmHWM_bytes": 112582811648, "Pss_bytes": 105445635072, "vram_used_bytes": 200892416, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 52.79, "VmRSS_bytes": 105447976960, "VmHWM_bytes": 112582811648, "Pss_bytes": 105445635072, "vram_used_bytes": 200892416, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 54.05, "VmRSS_bytes": 105448046592, "VmHWM_bytes": 112582811648, "Pss_bytes": 105445704704, "vram_used_bytes": 200892416, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 55.28, "VmRSS_bytes": 105448046592, "VmHWM_bytes": 112582811648, "Pss_bytes": 105445706752, "vram_used_bytes": 200892416, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 56.51, "VmRSS_bytes": 105448046592, "VmHWM_bytes": 112582811648, "Pss_bytes": 105445706752, "vram_used_bytes": 200892416, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 57.74, "VmRSS_bytes": 105448046592, "VmHWM_bytes": 112582811648, "Pss_bytes": 105445704704, "vram_used_bytes": 200892416, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 58.96, "VmRSS_bytes": 105448046592, "VmHWM_bytes": 112582811648, "Pss_bytes": 105445706752, "vram_used_bytes": 200892416, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 60.21, "VmRSS_bytes": 105448046592, "VmHWM_bytes": 112582811648, "Pss_bytes": 105445706752, "vram_used_bytes": 200892416, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 61.46, "VmRSS_bytes": 105448046592, "VmHWM_bytes": 112582811648, "Pss_bytes": 105445706752, "vram_used_bytes": 200892416, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 62.7, "VmRSS_bytes": 105448046592, "VmHWM_bytes": 112582811648, "Pss_bytes": 105445706752, "vram_used_bytes": 200892416, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 63.94, "VmRSS_bytes": 105448046592, "VmHWM_bytes": 112582811648, "Pss_bytes": 105445706752, "vram_used_bytes": 200892416, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 65.17, "VmRSS_bytes": 105448046592, "VmHWM_bytes": 112582811648, "Pss_bytes": 105445706752, "vram_used_bytes": 200892416, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 66.39, "VmRSS_bytes": 105448046592, "VmHWM_bytes": 112582811648, "Pss_bytes": 105445706752, "vram_used_bytes": 200892416, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 67.61, "VmRSS_bytes": 105448046592, "VmHWM_bytes": 112582811648, "Pss_bytes": 105445706752, "vram_used_bytes": 200892416, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 68.85, "VmRSS_bytes": 105448046592, "VmHWM_bytes": 112582811648, "Pss_bytes": 105445706752, "vram_used_bytes": 200892416, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 70.07, "VmRSS_bytes": 105369059328, "VmHWM_bytes": 112582811648, "Pss_bytes": 105366720512, "vram_used_bytes": 194150400, "vram_total_bytes": 4294967296, "gtt_used_bytes": 45844606976, "gtt_total_bytes": 193273528320} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-default-r2-memory-endpoint.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-default-r2-memory-endpoint.json new file mode 100644 index 0000000000..faf691d2fa --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-default-r2-memory-endpoint.json @@ -0,0 +1 @@ +{"schema_version": 1, "context_window": 20480, "context_fitted": false, "device": {"active_bytes": 87856892564, "cache_bytes": 0, "peak_bytes": 87896410020, "peak_scope": "since_start_or_health_reset"}} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-default-r2-metrics.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-default-r2-metrics.txt new file mode 100644 index 0000000000..f6c9d8f6dc --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-default-r2-metrics.txt @@ -0,0 +1,220 @@ +# HELP tensorfold:requests_running Requests in prefill or decode. +# TYPE tensorfold:requests_running gauge +tensorfold:requests_running 0 +# HELP tensorfold:requests_waiting Requests queued or held until a lane is free. +# TYPE tensorfold:requests_waiting gauge +tensorfold:requests_waiting 0 +# HELP tensorfold:generation_tokens_running Generated tokens held by live streams. +# TYPE tensorfold:generation_tokens_running gauge +tensorfold:generation_tokens_running 0 +# HELP tensorfold:prompt_tokens_total Prompt tokens of finished requests. +# TYPE tensorfold:prompt_tokens_total counter +tensorfold:prompt_tokens_total 16640 +# HELP tensorfold:generation_tokens_total Generated tokens of finished requests. +# TYPE tensorfold:generation_tokens_total counter +tensorfold:generation_tokens_total 2 +# HELP tensorfold:kv_cache_usage_ratio Tokens in a stream cache divided by that stream's context window. +# TYPE tensorfold:kv_cache_usage_ratio gauge +tensorfold:kv_cache_usage_ratio{pool="0"} 0 +# HELP tensorfold:mtp_drafted_total Draft tokens verified on finished requests. +# TYPE tensorfold:mtp_drafted_total counter +tensorfold:mtp_drafted_total 0 +# HELP tensorfold:mtp_accepted_total Draft tokens kept on finished requests. +# TYPE tensorfold:mtp_accepted_total counter +tensorfold:mtp_accepted_total 0 +# HELP tensorfold:request_latency_seconds Seconds from arrival to the reply leaving. +# TYPE tensorfold:request_latency_seconds histogram +tensorfold:request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:request_latency_seconds_bucket{le="0.5"} 1 +tensorfold:request_latency_seconds_bucket{le="1"} 1 +tensorfold:request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:request_latency_seconds_bucket{le="5"} 1 +tensorfold:request_latency_seconds_bucket{le="10"} 1 +tensorfold:request_latency_seconds_bucket{le="30"} 1 +tensorfold:request_latency_seconds_bucket{le="60"} 2 +tensorfold:request_latency_seconds_bucket{le="120"} 2 +tensorfold:request_latency_seconds_bucket{le="300"} 2 +tensorfold:request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:request_latency_seconds_sum 31.265406 +tensorfold:request_latency_seconds_count 2 +# HELP tensorfold:time_to_first_token_seconds Seconds from arrival to the first generated token. +# TYPE tensorfold:time_to_first_token_seconds histogram +tensorfold:time_to_first_token_seconds_bucket{le="0.01"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.05"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.25"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="1"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="2.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="10"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="30"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="60"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="120"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="300"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="+Inf"} 2 +tensorfold:time_to_first_token_seconds_sum 31.265237 +tensorfold:time_to_first_token_seconds_count 2 +# HELP tensorfold:request_decode_seconds Seconds a finished request spent decoding. Its sum over generation_tokens_total is the decode rate. +# TYPE tensorfold:request_decode_seconds histogram +tensorfold:request_decode_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_seconds_bucket{le="1"} 2 +tensorfold:request_decode_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_seconds_bucket{le="5"} 2 +tensorfold:request_decode_seconds_bucket{le="10"} 2 +tensorfold:request_decode_seconds_bucket{le="30"} 2 +tensorfold:request_decode_seconds_bucket{le="60"} 2 +tensorfold:request_decode_seconds_bucket{le="120"} 2 +tensorfold:request_decode_seconds_bucket{le="300"} 2 +tensorfold:request_decode_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_seconds_sum 0.000169 +tensorfold:request_decode_seconds_count 2 +# HELP tensorfold:request_time_per_output_token_seconds Seconds from the first generated token to the last, divided by the tokens less one. +# TYPE tensorfold:request_time_per_output_token_seconds histogram +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.005"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.01"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.015"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.02"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.03"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.04"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.05"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.15"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.2"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.3"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.5"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="+Inf"} 0 +tensorfold:request_time_per_output_token_seconds_sum 0 +tensorfold:request_time_per_output_token_seconds_count 0 +# HELP tensorfold:decode_rounds_total Decode rounds used by finished requests. +# TYPE tensorfold:decode_rounds_total counter +tensorfold:decode_rounds_total 0 +# HELP tensorfold:request_prefill_seconds Seconds a finished request's prompt pass took. +# TYPE tensorfold:request_prefill_seconds histogram +tensorfold:request_prefill_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="1"} 1 +tensorfold:request_prefill_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_seconds_bucket{le="60"} 2 +tensorfold:request_prefill_seconds_bucket{le="120"} 2 +tensorfold:request_prefill_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_seconds_sum 31.264334 +tensorfold:request_prefill_seconds_count 2 +# HELP tensorfold:process_resident_bytes Current resident set (VmRSS); device memory is not in it, so it is not a physical footprint (Linux). +# TYPE tensorfold:process_resident_bytes gauge +tensorfold:process_resident_bytes 104904470528 +# HELP tensorfold:process_resident_anon_bytes Current resident anonymous memory (RssAnon): heap, stacks and private maps (Linux). +# TYPE tensorfold:process_resident_anon_bytes gauge +tensorfold:process_resident_anon_bytes 32365010944 +# HELP tensorfold:process_resident_file_bytes Current resident file-backed memory (RssFile): the binary, libraries and mapped files (Linux). +# TYPE tensorfold:process_resident_file_bytes gauge +tensorfold:process_resident_file_bytes 72405196800 +# HELP tensorfold:process_resident_shmem_bytes Current resident shared memory (RssShmem): System V shared memory, tmpfs maps and shared anonymous maps (Linux). +# TYPE tensorfold:process_resident_shmem_bytes gauge +tensorfold:process_resident_shmem_bytes 134262784 +# HELP tensorfold:process_resident_peak_bytes Kernel lifetime peak resident set (VmHWM); never reset by health (Linux). +# TYPE tensorfold:process_resident_peak_bytes gauge +tensorfold:process_resident_peak_bytes 112344928256 +# HELP tensorfold:device_memory_bytes Device memory the engine holds now: weights, caches and live streams; only where the backend counts it (CUDA). +# TYPE tensorfold:device_memory_bytes gauge +tensorfold:device_memory_bytes 87856892564 +# HELP tensorfold:device_memory_peak_bytes The most device memory the engine has held since start or the last /health?reset_peak=1. +# TYPE tensorfold:device_memory_peak_bytes gauge +tensorfold:device_memory_peak_bytes 87896410020 +# HELP tensorfold:pinned_memory_bytes Pinned host memory the engine holds now: staging buffers and windows; only where the backend counts it (CUDA). +# TYPE tensorfold:pinned_memory_bytes gauge +tensorfold:pinned_memory_bytes 0 +# HELP tensorfold:num_requests_running Requests in prefill or decode. A mirror of tensorfold:requests_running. +# TYPE tensorfold:num_requests_running gauge +tensorfold:num_requests_running 0 +# HELP tensorfold:num_requests_waiting Requests queued or held until a lane is free. A mirror of tensorfold:requests_waiting. +# TYPE tensorfold:num_requests_waiting gauge +tensorfold:num_requests_waiting 0 +# HELP tensorfold:kv_cache_usage_perc A stream's cache occupancy under vLLM's name; same streams and ratios as tensorfold:kv_cache_usage_ratio. +# TYPE tensorfold:kv_cache_usage_perc gauge +tensorfold:kv_cache_usage_perc{stream="0"} 0 +# HELP tensorfold:spec_decode_num_draft_tokens_total Draft tokens verified on finished requests, this server's single draft counter. +# TYPE tensorfold:spec_decode_num_draft_tokens_total counter +tensorfold:spec_decode_num_draft_tokens_total 0 +# HELP tensorfold:spec_decode_num_accepted_tokens_total Draft tokens kept on finished requests. +# TYPE tensorfold:spec_decode_num_accepted_tokens_total counter +tensorfold:spec_decode_num_accepted_tokens_total 0 +# HELP tensorfold:e2e_request_latency_seconds Seconds from arrival to the reply leaving, under vLLM's name. +# TYPE tensorfold:e2e_request_latency_seconds histogram +tensorfold:e2e_request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="1"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="10"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="30"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="60"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="120"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="300"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:e2e_request_latency_seconds_sum 31.265406 +tensorfold:e2e_request_latency_seconds_count 2 +# HELP tensorfold:request_decode_time_seconds Seconds a finished request spent decoding, under vLLM's name. +# TYPE tensorfold:request_decode_time_seconds histogram +tensorfold:request_decode_time_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="10"} 2 +tensorfold:request_decode_time_seconds_bucket{le="30"} 2 +tensorfold:request_decode_time_seconds_bucket{le="60"} 2 +tensorfold:request_decode_time_seconds_bucket{le="120"} 2 +tensorfold:request_decode_time_seconds_bucket{le="300"} 2 +tensorfold:request_decode_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_time_seconds_sum 0.000169 +tensorfold:request_decode_time_seconds_count 2 +# HELP tensorfold:request_prefill_time_seconds Seconds a finished request's prompt pass took, under vLLM's name. +# TYPE tensorfold:request_prefill_time_seconds histogram +tensorfold:request_prefill_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="1"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="60"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="120"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_time_seconds_sum 31.264334 +tensorfold:request_prefill_time_seconds_count 2 +# HELP tensorfold:client_disconnections_total Requests a client left before the reply left the server. +# TYPE tensorfold:client_disconnections_total counter +tensorfold:client_disconnections_total 0 +# HELP tensorfold:preemptions_total Requests that had to give a lane up to a later one. +# TYPE tensorfold:preemptions_total counter +tensorfold:preemptions_total 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-default-r2-samples.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-default-r2-samples.jsonl new file mode 100644 index 0000000000..a9291bf8e1 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-default-r2-samples.jsonl @@ -0,0 +1,49 @@ +{"t_s": 0.0, "VmRSS_bytes": 74055680, "VmHWM_bytes": 74055680, "Pss_bytes": 71972864, "vram_used_bytes": 187682816, "vram_total_bytes": 4294967296, "gtt_used_bytes": 31657984, "gtt_total_bytes": 193273528320} +{"t_s": 1.04, "VmRSS_bytes": 10107785216, "VmHWM_bytes": 10107785216, "Pss_bytes": 10116209664, "vram_used_bytes": 188809216, "vram_total_bytes": 4294967296, "gtt_used_bytes": 6847524864, "gtt_total_bytes": 193273528320} +{"t_s": 2.11, "VmRSS_bytes": 18202763264, "VmHWM_bytes": 18202763264, "Pss_bytes": 18325941248, "vram_used_bytes": 189358080, "vram_total_bytes": 4294967296, "gtt_used_bytes": 15062069248, "gtt_total_bytes": 193273528320} +{"t_s": 3.2, "VmRSS_bytes": 26445848576, "VmHWM_bytes": 26445848576, "Pss_bytes": 26443525120, "vram_used_bytes": 189939712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 24228720640, "gtt_total_bytes": 193273528320} +{"t_s": 4.33, "VmRSS_bytes": 34599936000, "VmHWM_bytes": 34599936000, "Pss_bytes": 34597612544, "vram_used_bytes": 190595072, "vram_total_bytes": 4294967296, "gtt_used_bytes": 33124839424, "gtt_total_bytes": 193273528320} +{"t_s": 5.47, "VmRSS_bytes": 44184805376, "VmHWM_bytes": 44184805376, "Pss_bytes": 44232682496, "vram_used_bytes": 191148032, "vram_total_bytes": 4294967296, "gtt_used_bytes": 41345675264, "gtt_total_bytes": 193273528320} +{"t_s": 6.65, "VmRSS_bytes": 52442009600, "VmHWM_bytes": 52442009600, "Pss_bytes": 52439686144, "vram_used_bytes": 191815680, "vram_total_bytes": 4294967296, "gtt_used_bytes": 51200192512, "gtt_total_bytes": 193273528320} +{"t_s": 7.85, "VmRSS_bytes": 62175043584, "VmHWM_bytes": 62175043584, "Pss_bytes": 62172720128, "vram_used_bytes": 192495616, "vram_total_bytes": 4294967296, "gtt_used_bytes": 61058904064, "gtt_total_bytes": 193273528320} +{"t_s": 9.07, "VmRSS_bytes": 71905411072, "VmHWM_bytes": 71905411072, "Pss_bytes": 71903087616, "vram_used_bytes": 193142784, "vram_total_bytes": 4294967296, "gtt_used_bytes": 70913421312, "gtt_total_bytes": 193273528320} +{"t_s": 10.3, "VmRSS_bytes": 82501726208, "VmHWM_bytes": 82501726208, "Pss_bytes": 82499402752, "vram_used_bytes": 194908160, "vram_total_bytes": 4294967296, "gtt_used_bytes": 80778424320, "gtt_total_bytes": 193273528320} +{"t_s": 11.53, "VmRSS_bytes": 84814180352, "VmHWM_bytes": 84814180352, "Pss_bytes": 84834151424, "vram_used_bytes": 194945024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 12.77, "VmRSS_bytes": 88803979264, "VmHWM_bytes": 88803979264, "Pss_bytes": 88832662528, "vram_used_bytes": 194945024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 14.01, "VmRSS_bytes": 92888215552, "VmHWM_bytes": 92888215552, "Pss_bytes": 92827229184, "vram_used_bytes": 194945024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 15.24, "VmRSS_bytes": 96748462080, "VmHWM_bytes": 96748462080, "Pss_bytes": 96737274880, "vram_used_bytes": 194945024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 16.48, "VmRSS_bytes": 100564885504, "VmHWM_bytes": 100564885504, "Pss_bytes": 100589026304, "vram_used_bytes": 194945024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 17.72, "VmRSS_bytes": 104069902336, "VmHWM_bytes": 104113266688, "Pss_bytes": 103828511744, "vram_used_bytes": 194945024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 18.97, "VmRSS_bytes": 106740445184, "VmHWM_bytes": 106899984384, "Pss_bytes": 106723970048, "vram_used_bytes": 194945024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 20.24, "VmRSS_bytes": 110055739392, "VmHWM_bytes": 110055739392, "Pss_bytes": 109948357632, "vram_used_bytes": 194945024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 22.92, "VmRSS_bytes": 112311951360, "VmHWM_bytes": 112344928256, "Pss_bytes": 112232168448, "vram_used_bytes": 196341760, "vram_total_bytes": 4294967296, "gtt_used_bytes": 82361774080, "gtt_total_bytes": 193273528320} +{"t_s": 24.77, "VmRSS_bytes": 110269231104, "VmHWM_bytes": 112344928256, "Pss_bytes": 105749376000, "vram_used_bytes": 204759040, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88070221824, "gtt_total_bytes": 193273528320} +{"t_s": 26.04, "VmRSS_bytes": 104891269120, "VmHWM_bytes": 112344928256, "Pss_bytes": 104888886272, "vram_used_bytes": 204795904, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88823029760, "gtt_total_bytes": 193273528320} +{"t_s": 27.32, "VmRSS_bytes": 104895918080, "VmHWM_bytes": 112344928256, "Pss_bytes": 104893533184, "vram_used_bytes": 204795904, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88824135680, "gtt_total_bytes": 193273528320} +{"t_s": 28.57, "VmRSS_bytes": 104899047424, "VmHWM_bytes": 112344928256, "Pss_bytes": 104896662528, "vram_used_bytes": 204795904, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88824504320, "gtt_total_bytes": 193273528320} +{"t_s": 29.85, "VmRSS_bytes": 104904515584, "VmHWM_bytes": 112344928256, "Pss_bytes": 104902126592, "vram_used_bytes": 204787712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 31.12, "VmRSS_bytes": 104904515584, "VmHWM_bytes": 112344928256, "Pss_bytes": 104902126592, "vram_used_bytes": 204787712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 32.38, "VmRSS_bytes": 104904515584, "VmHWM_bytes": 112344928256, "Pss_bytes": 104902126592, "vram_used_bytes": 204787712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 33.66, "VmRSS_bytes": 104904515584, "VmHWM_bytes": 112344928256, "Pss_bytes": 104902126592, "vram_used_bytes": 204787712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 34.93, "VmRSS_bytes": 104904515584, "VmHWM_bytes": 112344928256, "Pss_bytes": 104902126592, "vram_used_bytes": 204787712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 36.18, "VmRSS_bytes": 104904515584, "VmHWM_bytes": 112344928256, "Pss_bytes": 104902126592, "vram_used_bytes": 204787712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 37.43, "VmRSS_bytes": 104905199616, "VmHWM_bytes": 112344928256, "Pss_bytes": 104902810624, "vram_used_bytes": 204787712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 38.68, "VmRSS_bytes": 104905199616, "VmHWM_bytes": 112344928256, "Pss_bytes": 104902810624, "vram_used_bytes": 204787712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 39.94, "VmRSS_bytes": 104905199616, "VmHWM_bytes": 112344928256, "Pss_bytes": 104902810624, "vram_used_bytes": 204787712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 41.21, "VmRSS_bytes": 104905199616, "VmHWM_bytes": 112344928256, "Pss_bytes": 104902810624, "vram_used_bytes": 204787712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 42.47, "VmRSS_bytes": 104905199616, "VmHWM_bytes": 112344928256, "Pss_bytes": 104902810624, "vram_used_bytes": 204787712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 43.75, "VmRSS_bytes": 104905199616, "VmHWM_bytes": 112344928256, "Pss_bytes": 104902810624, "vram_used_bytes": 204787712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 45.03, "VmRSS_bytes": 104905269248, "VmHWM_bytes": 112344928256, "Pss_bytes": 104902880256, "vram_used_bytes": 204787712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 46.31, "VmRSS_bytes": 104905269248, "VmHWM_bytes": 112344928256, "Pss_bytes": 104902880256, "vram_used_bytes": 204787712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 47.57, "VmRSS_bytes": 104905269248, "VmHWM_bytes": 112344928256, "Pss_bytes": 104902878208, "vram_used_bytes": 204787712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 48.82, "VmRSS_bytes": 104905269248, "VmHWM_bytes": 112344928256, "Pss_bytes": 104902880256, "vram_used_bytes": 204787712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 50.07, "VmRSS_bytes": 104905269248, "VmHWM_bytes": 112344928256, "Pss_bytes": 104902880256, "vram_used_bytes": 204787712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 51.32, "VmRSS_bytes": 104905269248, "VmHWM_bytes": 112344928256, "Pss_bytes": 104902880256, "vram_used_bytes": 204787712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 52.59, "VmRSS_bytes": 104905269248, "VmHWM_bytes": 112344928256, "Pss_bytes": 104902880256, "vram_used_bytes": 204787712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 53.86, "VmRSS_bytes": 104905269248, "VmHWM_bytes": 112344928256, "Pss_bytes": 104902880256, "vram_used_bytes": 204787712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 55.15, "VmRSS_bytes": 104905269248, "VmHWM_bytes": 112344928256, "Pss_bytes": 104902880256, "vram_used_bytes": 204787712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 56.42, "VmRSS_bytes": 104905269248, "VmHWM_bytes": 112344928256, "Pss_bytes": 104902880256, "vram_used_bytes": 204787712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 57.68, "VmRSS_bytes": 104905269248, "VmHWM_bytes": 112344928256, "Pss_bytes": 104902880256, "vram_used_bytes": 204787712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 58.94, "VmRSS_bytes": 104905269248, "VmHWM_bytes": 112344928256, "Pss_bytes": 104902880256, "vram_used_bytes": 204787712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 60.19, "VmRSS_bytes": 104905269248, "VmHWM_bytes": 112344928256, "Pss_bytes": 104902879232, "vram_used_bytes": 204787712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 61.41, "VmRSS_bytes": 101037510656, "VmHWM_bytes": 112344928256, "Pss_bytes": 96323750912, "vram_used_bytes": 194756608, "vram_total_bytes": 4294967296, "gtt_used_bytes": 204288000, "gtt_total_bytes": 193273528320} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-mapped-cold-r1-memory-endpoint.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-mapped-cold-r1-memory-endpoint.json new file mode 100644 index 0000000000..faf691d2fa --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-mapped-cold-r1-memory-endpoint.json @@ -0,0 +1 @@ +{"schema_version": 1, "context_window": 20480, "context_fitted": false, "device": {"active_bytes": 87856892564, "cache_bytes": 0, "peak_bytes": 87896410020, "peak_scope": "since_start_or_health_reset"}} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-mapped-cold-r1-metrics.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-mapped-cold-r1-metrics.txt new file mode 100644 index 0000000000..2d3e9373ab --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-mapped-cold-r1-metrics.txt @@ -0,0 +1,220 @@ +# HELP tensorfold:requests_running Requests in prefill or decode. +# TYPE tensorfold:requests_running gauge +tensorfold:requests_running 0 +# HELP tensorfold:requests_waiting Requests queued or held until a lane is free. +# TYPE tensorfold:requests_waiting gauge +tensorfold:requests_waiting 0 +# HELP tensorfold:generation_tokens_running Generated tokens held by live streams. +# TYPE tensorfold:generation_tokens_running gauge +tensorfold:generation_tokens_running 0 +# HELP tensorfold:prompt_tokens_total Prompt tokens of finished requests. +# TYPE tensorfold:prompt_tokens_total counter +tensorfold:prompt_tokens_total 16640 +# HELP tensorfold:generation_tokens_total Generated tokens of finished requests. +# TYPE tensorfold:generation_tokens_total counter +tensorfold:generation_tokens_total 2 +# HELP tensorfold:kv_cache_usage_ratio Tokens in a stream cache divided by that stream's context window. +# TYPE tensorfold:kv_cache_usage_ratio gauge +tensorfold:kv_cache_usage_ratio{pool="0"} 0 +# HELP tensorfold:mtp_drafted_total Draft tokens verified on finished requests. +# TYPE tensorfold:mtp_drafted_total counter +tensorfold:mtp_drafted_total 0 +# HELP tensorfold:mtp_accepted_total Draft tokens kept on finished requests. +# TYPE tensorfold:mtp_accepted_total counter +tensorfold:mtp_accepted_total 0 +# HELP tensorfold:request_latency_seconds Seconds from arrival to the reply leaving. +# TYPE tensorfold:request_latency_seconds histogram +tensorfold:request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:request_latency_seconds_bucket{le="1"} 0 +tensorfold:request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:request_latency_seconds_bucket{le="5"} 1 +tensorfold:request_latency_seconds_bucket{le="10"} 1 +tensorfold:request_latency_seconds_bucket{le="30"} 1 +tensorfold:request_latency_seconds_bucket{le="60"} 2 +tensorfold:request_latency_seconds_bucket{le="120"} 2 +tensorfold:request_latency_seconds_bucket{le="300"} 2 +tensorfold:request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:request_latency_seconds_sum 47.952635 +tensorfold:request_latency_seconds_count 2 +# HELP tensorfold:time_to_first_token_seconds Seconds from arrival to the first generated token. +# TYPE tensorfold:time_to_first_token_seconds histogram +tensorfold:time_to_first_token_seconds_bucket{le="0.01"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.05"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.25"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.5"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="2.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="10"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="30"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="60"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="120"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="300"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="+Inf"} 2 +tensorfold:time_to_first_token_seconds_sum 47.952253 +tensorfold:time_to_first_token_seconds_count 2 +# HELP tensorfold:request_decode_seconds Seconds a finished request spent decoding. Its sum over generation_tokens_total is the decode rate. +# TYPE tensorfold:request_decode_seconds histogram +tensorfold:request_decode_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_seconds_bucket{le="1"} 2 +tensorfold:request_decode_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_seconds_bucket{le="5"} 2 +tensorfold:request_decode_seconds_bucket{le="10"} 2 +tensorfold:request_decode_seconds_bucket{le="30"} 2 +tensorfold:request_decode_seconds_bucket{le="60"} 2 +tensorfold:request_decode_seconds_bucket{le="120"} 2 +tensorfold:request_decode_seconds_bucket{le="300"} 2 +tensorfold:request_decode_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_seconds_sum 0.000382 +tensorfold:request_decode_seconds_count 2 +# HELP tensorfold:request_time_per_output_token_seconds Seconds from the first generated token to the last, divided by the tokens less one. +# TYPE tensorfold:request_time_per_output_token_seconds histogram +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.005"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.01"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.015"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.02"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.03"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.04"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.05"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.15"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.2"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.3"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.5"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="+Inf"} 0 +tensorfold:request_time_per_output_token_seconds_sum 0 +tensorfold:request_time_per_output_token_seconds_count 0 +# HELP tensorfold:decode_rounds_total Decode rounds used by finished requests. +# TYPE tensorfold:decode_rounds_total counter +tensorfold:decode_rounds_total 0 +# HELP tensorfold:request_prefill_seconds Seconds a finished request's prompt pass took. +# TYPE tensorfold:request_prefill_seconds histogram +tensorfold:request_prefill_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.5"} 0 +tensorfold:request_prefill_seconds_bucket{le="1"} 0 +tensorfold:request_prefill_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_seconds_bucket{le="60"} 2 +tensorfold:request_prefill_seconds_bucket{le="120"} 2 +tensorfold:request_prefill_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_seconds_sum 47.950984 +tensorfold:request_prefill_seconds_count 2 +# HELP tensorfold:process_resident_bytes Current resident set (VmRSS); device memory is not in it, so it is not a physical footprint (Linux). +# TYPE tensorfold:process_resident_bytes gauge +tensorfold:process_resident_bytes 84364992512 +# HELP tensorfold:process_resident_anon_bytes Current resident anonymous memory (RssAnon): heap, stacks and private maps (Linux). +# TYPE tensorfold:process_resident_anon_bytes gauge +tensorfold:process_resident_anon_bytes 360718336 +# HELP tensorfold:process_resident_file_bytes Current resident file-backed memory (RssFile): the binary, libraries and mapped files (Linux). +# TYPE tensorfold:process_resident_file_bytes gauge +tensorfold:process_resident_file_bytes 83870011392 +# HELP tensorfold:process_resident_shmem_bytes Current resident shared memory (RssShmem): System V shared memory, tmpfs maps and shared anonymous maps (Linux). +# TYPE tensorfold:process_resident_shmem_bytes gauge +tensorfold:process_resident_shmem_bytes 134262784 +# HELP tensorfold:process_resident_peak_bytes Kernel lifetime peak resident set (VmHWM); never reset by health (Linux). +# TYPE tensorfold:process_resident_peak_bytes gauge +tensorfold:process_resident_peak_bytes 84364992512 +# HELP tensorfold:device_memory_bytes Device memory the engine holds now: weights, caches and live streams; only where the backend counts it (CUDA). +# TYPE tensorfold:device_memory_bytes gauge +tensorfold:device_memory_bytes 87856892564 +# HELP tensorfold:device_memory_peak_bytes The most device memory the engine has held since start or the last /health?reset_peak=1. +# TYPE tensorfold:device_memory_peak_bytes gauge +tensorfold:device_memory_peak_bytes 87896410020 +# HELP tensorfold:pinned_memory_bytes Pinned host memory the engine holds now: staging buffers and windows; only where the backend counts it (CUDA). +# TYPE tensorfold:pinned_memory_bytes gauge +tensorfold:pinned_memory_bytes 0 +# HELP tensorfold:num_requests_running Requests in prefill or decode. A mirror of tensorfold:requests_running. +# TYPE tensorfold:num_requests_running gauge +tensorfold:num_requests_running 0 +# HELP tensorfold:num_requests_waiting Requests queued or held until a lane is free. A mirror of tensorfold:requests_waiting. +# TYPE tensorfold:num_requests_waiting gauge +tensorfold:num_requests_waiting 0 +# HELP tensorfold:kv_cache_usage_perc A stream's cache occupancy under vLLM's name; same streams and ratios as tensorfold:kv_cache_usage_ratio. +# TYPE tensorfold:kv_cache_usage_perc gauge +tensorfold:kv_cache_usage_perc{stream="0"} 0 +# HELP tensorfold:spec_decode_num_draft_tokens_total Draft tokens verified on finished requests, this server's single draft counter. +# TYPE tensorfold:spec_decode_num_draft_tokens_total counter +tensorfold:spec_decode_num_draft_tokens_total 0 +# HELP tensorfold:spec_decode_num_accepted_tokens_total Draft tokens kept on finished requests. +# TYPE tensorfold:spec_decode_num_accepted_tokens_total counter +tensorfold:spec_decode_num_accepted_tokens_total 0 +# HELP tensorfold:e2e_request_latency_seconds Seconds from arrival to the reply leaving, under vLLM's name. +# TYPE tensorfold:e2e_request_latency_seconds histogram +tensorfold:e2e_request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="10"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="30"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="60"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="120"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="300"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:e2e_request_latency_seconds_sum 47.952635 +tensorfold:e2e_request_latency_seconds_count 2 +# HELP tensorfold:request_decode_time_seconds Seconds a finished request spent decoding, under vLLM's name. +# TYPE tensorfold:request_decode_time_seconds histogram +tensorfold:request_decode_time_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="10"} 2 +tensorfold:request_decode_time_seconds_bucket{le="30"} 2 +tensorfold:request_decode_time_seconds_bucket{le="60"} 2 +tensorfold:request_decode_time_seconds_bucket{le="120"} 2 +tensorfold:request_decode_time_seconds_bucket{le="300"} 2 +tensorfold:request_decode_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_time_seconds_sum 0.000382 +tensorfold:request_decode_time_seconds_count 2 +# HELP tensorfold:request_prefill_time_seconds Seconds a finished request's prompt pass took, under vLLM's name. +# TYPE tensorfold:request_prefill_time_seconds histogram +tensorfold:request_prefill_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.5"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="60"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="120"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_time_seconds_sum 47.950984 +tensorfold:request_prefill_time_seconds_count 2 +# HELP tensorfold:client_disconnections_total Requests a client left before the reply left the server. +# TYPE tensorfold:client_disconnections_total counter +tensorfold:client_disconnections_total 0 +# HELP tensorfold:preemptions_total Requests that had to give a lane up to a later one. +# TYPE tensorfold:preemptions_total counter +tensorfold:preemptions_total 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-mapped-cold-r1-samples.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-mapped-cold-r1-samples.jsonl new file mode 100644 index 0000000000..3aeed7f47a --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-mapped-cold-r1-samples.jsonl @@ -0,0 +1,56 @@ +{"t_s": 0.0, "VmRSS_bytes": 62967808, "VmHWM_bytes": 62967808, "Pss_bytes": 60831744, "vram_used_bytes": 187670528, "vram_total_bytes": 4294967296, "gtt_used_bytes": 31657984, "gtt_total_bytes": 193273528320} +{"t_s": 1.03, "VmRSS_bytes": 8968261632, "VmHWM_bytes": 8968261632, "Pss_bytes": 8993395712, "vram_used_bytes": 188809216, "vram_total_bytes": 4294967296, "gtt_used_bytes": 6841233408, "gtt_total_bytes": 193273528320} +{"t_s": 2.09, "VmRSS_bytes": 14030282752, "VmHWM_bytes": 14030282752, "Pss_bytes": 14044460032, "vram_used_bytes": 189140992, "vram_total_bytes": 4294967296, "gtt_used_bytes": 11767443456, "gtt_total_bytes": 193273528320} +{"t_s": 3.17, "VmRSS_bytes": 18936623104, "VmHWM_bytes": 18936623104, "Pss_bytes": 18994004992, "vram_used_bytes": 189476864, "vram_total_bytes": 4294967296, "gtt_used_bytes": 16699944960, "gtt_total_bytes": 193273528320} +{"t_s": 4.27, "VmRSS_bytes": 24124841984, "VmHWM_bytes": 24124841984, "Pss_bytes": 24137266176, "vram_used_bytes": 189816832, "vram_total_bytes": 4294967296, "gtt_used_bytes": 21626155008, "gtt_total_bytes": 193273528320} +{"t_s": 5.38, "VmRSS_bytes": 29342887936, "VmHWM_bytes": 29342887936, "Pss_bytes": 29437297664, "vram_used_bytes": 190185472, "vram_total_bytes": 4294967296, "gtt_used_bytes": 26560753664, "gtt_total_bytes": 193273528320} +{"t_s": 6.51, "VmRSS_bytes": 36451028992, "VmHWM_bytes": 36451028992, "Pss_bytes": 36488356864, "vram_used_bytes": 190726144, "vram_total_bytes": 4294967296, "gtt_used_bytes": 34769006592, "gtt_total_bytes": 193273528320} +{"t_s": 7.66, "VmRSS_bytes": 44188479488, "VmHWM_bytes": 44188479488, "Pss_bytes": 44234208256, "vram_used_bytes": 191164416, "vram_total_bytes": 4294967296, "gtt_used_bytes": 41345675264, "gtt_total_bytes": 193273528320} +{"t_s": 8.83, "VmRSS_bytes": 51573149696, "VmHWM_bytes": 51573149696, "Pss_bytes": 51589637120, "vram_used_bytes": 191717376, "vram_total_bytes": 4294967296, "gtt_used_bytes": 49562316800, "gtt_total_bytes": 193273528320} +{"t_s": 10.0, "VmRSS_bytes": 57125576704, "VmHWM_bytes": 57125576704, "Pss_bytes": 57159037952, "vram_used_bytes": 192053248, "vram_total_bytes": 4294967296, "gtt_used_bytes": 54488526848, "gtt_total_bytes": 193273528320} +{"t_s": 11.19, "VmRSS_bytes": 61990797312, "VmHWM_bytes": 61990797312, "Pss_bytes": 62020690944, "vram_used_bytes": 192401408, "vram_total_bytes": 4294967296, "gtt_used_bytes": 59414736896, "gtt_total_bytes": 193273528320} +{"t_s": 12.39, "VmRSS_bytes": 67331383296, "VmHWM_bytes": 67331383296, "Pss_bytes": 67365434368, "vram_used_bytes": 192851968, "vram_total_bytes": 4294967296, "gtt_used_bytes": 65987211264, "gtt_total_bytes": 193273528320} +{"t_s": 13.61, "VmRSS_bytes": 76728438784, "VmHWM_bytes": 76728438784, "Pss_bytes": 76726055936, "vram_used_bytes": 193380352, "vram_total_bytes": 4294967296, "gtt_used_bytes": 75046907904, "gtt_total_bytes": 193273528320} +{"t_s": 14.84, "VmRSS_bytes": 80858251264, "VmHWM_bytes": 82505052160, "Pss_bytes": 80857656320, "vram_used_bytes": 195129344, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88818905088, "gtt_total_bytes": 193273528320} +{"t_s": 16.09, "VmRSS_bytes": 80900456448, "VmHWM_bytes": 82505052160, "Pss_bytes": 80898022400, "vram_used_bytes": 195162112, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88823029760, "gtt_total_bytes": 193273528320} +{"t_s": 17.35, "VmRSS_bytes": 80905105408, "VmHWM_bytes": 82505052160, "Pss_bytes": 80902671360, "vram_used_bytes": 195162112, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88824135680, "gtt_total_bytes": 193273528320} +{"t_s": 18.57, "VmRSS_bytes": 80907358208, "VmHWM_bytes": 82505052160, "Pss_bytes": 80904924160, "vram_used_bytes": 195166208, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88824504320, "gtt_total_bytes": 193273528320} +{"t_s": 19.8, "VmRSS_bytes": 80935194624, "VmHWM_bytes": 82505052160, "Pss_bytes": 80959625216, "vram_used_bytes": 195166208, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88824504320, "gtt_total_bytes": 193273528320} +{"t_s": 21.04, "VmRSS_bytes": 81132093440, "VmHWM_bytes": 82505052160, "Pss_bytes": 81197365248, "vram_used_bytes": 195166208, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 22.29, "VmRSS_bytes": 81532313600, "VmHWM_bytes": 82505052160, "Pss_bytes": 81600100352, "vram_used_bytes": 195166208, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 23.54, "VmRSS_bytes": 81928609792, "VmHWM_bytes": 82505052160, "Pss_bytes": 81990965248, "vram_used_bytes": 195166208, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 24.79, "VmRSS_bytes": 82278240256, "VmHWM_bytes": 82505052160, "Pss_bytes": 82335389696, "vram_used_bytes": 195166208, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 26.05, "VmRSS_bytes": 82596352000, "VmHWM_bytes": 82596352000, "Pss_bytes": 82623698944, "vram_used_bytes": 195166208, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 27.34, "VmRSS_bytes": 82628173824, "VmHWM_bytes": 82628173824, "Pss_bytes": 82625742848, "vram_used_bytes": 195166208, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 28.6, "VmRSS_bytes": 82628173824, "VmHWM_bytes": 82628173824, "Pss_bytes": 82625742848, "vram_used_bytes": 195166208, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 29.87, "VmRSS_bytes": 82628173824, "VmHWM_bytes": 82628173824, "Pss_bytes": 82625742848, "vram_used_bytes": 195166208, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 31.16, "VmRSS_bytes": 82628173824, "VmHWM_bytes": 82628173824, "Pss_bytes": 82625742848, "vram_used_bytes": 195166208, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 32.42, "VmRSS_bytes": 82628173824, "VmHWM_bytes": 82628173824, "Pss_bytes": 82625742848, "vram_used_bytes": 195166208, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 33.67, "VmRSS_bytes": 82792165376, "VmHWM_bytes": 82792165376, "Pss_bytes": 82839046144, "vram_used_bytes": 195166208, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 34.93, "VmRSS_bytes": 83066802176, "VmHWM_bytes": 83066802176, "Pss_bytes": 83110877184, "vram_used_bytes": 195166208, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 36.19, "VmRSS_bytes": 83308429312, "VmHWM_bytes": 83308429312, "Pss_bytes": 83346646016, "vram_used_bytes": 195166208, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 37.45, "VmRSS_bytes": 83357863936, "VmHWM_bytes": 83357863936, "Pss_bytes": 83355431936, "vram_used_bytes": 195166208, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 38.7, "VmRSS_bytes": 83357863936, "VmHWM_bytes": 83357863936, "Pss_bytes": 83355430912, "vram_used_bytes": 195166208, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 39.97, "VmRSS_bytes": 83357863936, "VmHWM_bytes": 83357863936, "Pss_bytes": 83355432960, "vram_used_bytes": 195166208, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 41.24, "VmRSS_bytes": 83357863936, "VmHWM_bytes": 83357863936, "Pss_bytes": 83355432960, "vram_used_bytes": 195166208, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 42.51, "VmRSS_bytes": 83357863936, "VmHWM_bytes": 83357863936, "Pss_bytes": 83355432960, "vram_used_bytes": 195166208, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 43.78, "VmRSS_bytes": 83358560256, "VmHWM_bytes": 83358560256, "Pss_bytes": 83356129280, "vram_used_bytes": 195166208, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 45.05, "VmRSS_bytes": 83463147520, "VmHWM_bytes": 83463147520, "Pss_bytes": 83500525568, "vram_used_bytes": 195166208, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 46.31, "VmRSS_bytes": 83677626368, "VmHWM_bytes": 83677626368, "Pss_bytes": 83711584256, "vram_used_bytes": 195166208, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 47.58, "VmRSS_bytes": 83877068800, "VmHWM_bytes": 83877068800, "Pss_bytes": 83899852800, "vram_used_bytes": 195166208, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 48.84, "VmRSS_bytes": 83902353408, "VmHWM_bytes": 83902353408, "Pss_bytes": 83899922432, "vram_used_bytes": 195166208, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 50.1, "VmRSS_bytes": 83902353408, "VmHWM_bytes": 83902353408, "Pss_bytes": 83899922432, "vram_used_bytes": 195166208, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 51.37, "VmRSS_bytes": 83902353408, "VmHWM_bytes": 83902353408, "Pss_bytes": 83899922432, "vram_used_bytes": 195166208, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 52.63, "VmRSS_bytes": 83902353408, "VmHWM_bytes": 83902353408, "Pss_bytes": 83899922432, "vram_used_bytes": 195166208, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 53.91, "VmRSS_bytes": 83905695744, "VmHWM_bytes": 83905695744, "Pss_bytes": 83903264768, "vram_used_bytes": 195166208, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 55.19, "VmRSS_bytes": 83905695744, "VmHWM_bytes": 83905695744, "Pss_bytes": 83903264768, "vram_used_bytes": 195166208, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 56.45, "VmRSS_bytes": 83983360000, "VmHWM_bytes": 83983360000, "Pss_bytes": 84012005376, "vram_used_bytes": 195166208, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 57.72, "VmRSS_bytes": 84165541888, "VmHWM_bytes": 84165541888, "Pss_bytes": 84195604480, "vram_used_bytes": 195166208, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 59.0, "VmRSS_bytes": 84338843648, "VmHWM_bytes": 84338843648, "Pss_bytes": 84363253760, "vram_used_bytes": 195166208, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 60.27, "VmRSS_bytes": 84365791232, "VmHWM_bytes": 84365791232, "Pss_bytes": 84363360256, "vram_used_bytes": 195166208, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 61.54, "VmRSS_bytes": 84365791232, "VmHWM_bytes": 84365791232, "Pss_bytes": 84363360256, "vram_used_bytes": 195166208, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 62.81, "VmRSS_bytes": 84365791232, "VmHWM_bytes": 84365791232, "Pss_bytes": 84363360256, "vram_used_bytes": 195166208, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 64.09, "VmRSS_bytes": 84365791232, "VmHWM_bytes": 84365791232, "Pss_bytes": 84363360256, "vram_used_bytes": 195166208, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 65.37, "VmRSS_bytes": 84365791232, "VmHWM_bytes": 84365791232, "Pss_bytes": 84363360256, "vram_used_bytes": 195166208, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 66.66, "VmRSS_bytes": 84365791232, "VmHWM_bytes": 84365791232, "Pss_bytes": 84363360256, "vram_used_bytes": 195166208, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 67.93, "VmRSS_bytes": 84286803968, "VmHWM_bytes": 84361736192, "Pss_bytes": 84284375040, "vram_used_bytes": 194998272, "vram_total_bytes": 4294967296, "gtt_used_bytes": 9813438464, "gtt_total_bytes": 193273528320} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-mapped-cold-r2-memory-endpoint.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-mapped-cold-r2-memory-endpoint.json new file mode 100644 index 0000000000..faf691d2fa --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-mapped-cold-r2-memory-endpoint.json @@ -0,0 +1 @@ +{"schema_version": 1, "context_window": 20480, "context_fitted": false, "device": {"active_bytes": 87856892564, "cache_bytes": 0, "peak_bytes": 87896410020, "peak_scope": "since_start_or_health_reset"}} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-mapped-cold-r2-metrics.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-mapped-cold-r2-metrics.txt new file mode 100644 index 0000000000..66114b588c --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-mapped-cold-r2-metrics.txt @@ -0,0 +1,220 @@ +# HELP tensorfold:requests_running Requests in prefill or decode. +# TYPE tensorfold:requests_running gauge +tensorfold:requests_running 0 +# HELP tensorfold:requests_waiting Requests queued or held until a lane is free. +# TYPE tensorfold:requests_waiting gauge +tensorfold:requests_waiting 0 +# HELP tensorfold:generation_tokens_running Generated tokens held by live streams. +# TYPE tensorfold:generation_tokens_running gauge +tensorfold:generation_tokens_running 0 +# HELP tensorfold:prompt_tokens_total Prompt tokens of finished requests. +# TYPE tensorfold:prompt_tokens_total counter +tensorfold:prompt_tokens_total 16640 +# HELP tensorfold:generation_tokens_total Generated tokens of finished requests. +# TYPE tensorfold:generation_tokens_total counter +tensorfold:generation_tokens_total 2 +# HELP tensorfold:kv_cache_usage_ratio Tokens in a stream cache divided by that stream's context window. +# TYPE tensorfold:kv_cache_usage_ratio gauge +tensorfold:kv_cache_usage_ratio{pool="0"} 0 +# HELP tensorfold:mtp_drafted_total Draft tokens verified on finished requests. +# TYPE tensorfold:mtp_drafted_total counter +tensorfold:mtp_drafted_total 0 +# HELP tensorfold:mtp_accepted_total Draft tokens kept on finished requests. +# TYPE tensorfold:mtp_accepted_total counter +tensorfold:mtp_accepted_total 0 +# HELP tensorfold:request_latency_seconds Seconds from arrival to the reply leaving. +# TYPE tensorfold:request_latency_seconds histogram +tensorfold:request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:request_latency_seconds_bucket{le="1"} 0 +tensorfold:request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:request_latency_seconds_bucket{le="5"} 1 +tensorfold:request_latency_seconds_bucket{le="10"} 1 +tensorfold:request_latency_seconds_bucket{le="30"} 1 +tensorfold:request_latency_seconds_bucket{le="60"} 2 +tensorfold:request_latency_seconds_bucket{le="120"} 2 +tensorfold:request_latency_seconds_bucket{le="300"} 2 +tensorfold:request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:request_latency_seconds_sum 47.813649 +tensorfold:request_latency_seconds_count 2 +# HELP tensorfold:time_to_first_token_seconds Seconds from arrival to the first generated token. +# TYPE tensorfold:time_to_first_token_seconds histogram +tensorfold:time_to_first_token_seconds_bucket{le="0.01"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.05"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.25"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.5"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="2.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="10"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="30"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="60"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="120"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="300"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="+Inf"} 2 +tensorfold:time_to_first_token_seconds_sum 47.813301 +tensorfold:time_to_first_token_seconds_count 2 +# HELP tensorfold:request_decode_seconds Seconds a finished request spent decoding. Its sum over generation_tokens_total is the decode rate. +# TYPE tensorfold:request_decode_seconds histogram +tensorfold:request_decode_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_seconds_bucket{le="1"} 2 +tensorfold:request_decode_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_seconds_bucket{le="5"} 2 +tensorfold:request_decode_seconds_bucket{le="10"} 2 +tensorfold:request_decode_seconds_bucket{le="30"} 2 +tensorfold:request_decode_seconds_bucket{le="60"} 2 +tensorfold:request_decode_seconds_bucket{le="120"} 2 +tensorfold:request_decode_seconds_bucket{le="300"} 2 +tensorfold:request_decode_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_seconds_sum 0.000348 +tensorfold:request_decode_seconds_count 2 +# HELP tensorfold:request_time_per_output_token_seconds Seconds from the first generated token to the last, divided by the tokens less one. +# TYPE tensorfold:request_time_per_output_token_seconds histogram +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.005"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.01"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.015"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.02"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.03"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.04"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.05"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.15"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.2"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.3"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.5"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="+Inf"} 0 +tensorfold:request_time_per_output_token_seconds_sum 0 +tensorfold:request_time_per_output_token_seconds_count 0 +# HELP tensorfold:decode_rounds_total Decode rounds used by finished requests. +# TYPE tensorfold:decode_rounds_total counter +tensorfold:decode_rounds_total 0 +# HELP tensorfold:request_prefill_seconds Seconds a finished request's prompt pass took. +# TYPE tensorfold:request_prefill_seconds histogram +tensorfold:request_prefill_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.5"} 0 +tensorfold:request_prefill_seconds_bucket{le="1"} 0 +tensorfold:request_prefill_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_seconds_bucket{le="60"} 2 +tensorfold:request_prefill_seconds_bucket{le="120"} 2 +tensorfold:request_prefill_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_seconds_sum 47.81204 +tensorfold:request_prefill_seconds_count 2 +# HELP tensorfold:process_resident_bytes Current resident set (VmRSS); device memory is not in it, so it is not a physical footprint (Linux). +# TYPE tensorfold:process_resident_bytes gauge +tensorfold:process_resident_bytes 84385976320 +# HELP tensorfold:process_resident_anon_bytes Current resident anonymous memory (RssAnon): heap, stacks and private maps (Linux). +# TYPE tensorfold:process_resident_anon_bytes gauge +tensorfold:process_resident_anon_bytes 360669184 +# HELP tensorfold:process_resident_file_bytes Current resident file-backed memory (RssFile): the binary, libraries and mapped files (Linux). +# TYPE tensorfold:process_resident_file_bytes gauge +tensorfold:process_resident_file_bytes 83891044352 +# HELP tensorfold:process_resident_shmem_bytes Current resident shared memory (RssShmem): System V shared memory, tmpfs maps and shared anonymous maps (Linux). +# TYPE tensorfold:process_resident_shmem_bytes gauge +tensorfold:process_resident_shmem_bytes 134262784 +# HELP tensorfold:process_resident_peak_bytes Kernel lifetime peak resident set (VmHWM); never reset by health (Linux). +# TYPE tensorfold:process_resident_peak_bytes gauge +tensorfold:process_resident_peak_bytes 84385976320 +# HELP tensorfold:device_memory_bytes Device memory the engine holds now: weights, caches and live streams; only where the backend counts it (CUDA). +# TYPE tensorfold:device_memory_bytes gauge +tensorfold:device_memory_bytes 87856892564 +# HELP tensorfold:device_memory_peak_bytes The most device memory the engine has held since start or the last /health?reset_peak=1. +# TYPE tensorfold:device_memory_peak_bytes gauge +tensorfold:device_memory_peak_bytes 87896410020 +# HELP tensorfold:pinned_memory_bytes Pinned host memory the engine holds now: staging buffers and windows; only where the backend counts it (CUDA). +# TYPE tensorfold:pinned_memory_bytes gauge +tensorfold:pinned_memory_bytes 0 +# HELP tensorfold:num_requests_running Requests in prefill or decode. A mirror of tensorfold:requests_running. +# TYPE tensorfold:num_requests_running gauge +tensorfold:num_requests_running 0 +# HELP tensorfold:num_requests_waiting Requests queued or held until a lane is free. A mirror of tensorfold:requests_waiting. +# TYPE tensorfold:num_requests_waiting gauge +tensorfold:num_requests_waiting 0 +# HELP tensorfold:kv_cache_usage_perc A stream's cache occupancy under vLLM's name; same streams and ratios as tensorfold:kv_cache_usage_ratio. +# TYPE tensorfold:kv_cache_usage_perc gauge +tensorfold:kv_cache_usage_perc{stream="0"} 0 +# HELP tensorfold:spec_decode_num_draft_tokens_total Draft tokens verified on finished requests, this server's single draft counter. +# TYPE tensorfold:spec_decode_num_draft_tokens_total counter +tensorfold:spec_decode_num_draft_tokens_total 0 +# HELP tensorfold:spec_decode_num_accepted_tokens_total Draft tokens kept on finished requests. +# TYPE tensorfold:spec_decode_num_accepted_tokens_total counter +tensorfold:spec_decode_num_accepted_tokens_total 0 +# HELP tensorfold:e2e_request_latency_seconds Seconds from arrival to the reply leaving, under vLLM's name. +# TYPE tensorfold:e2e_request_latency_seconds histogram +tensorfold:e2e_request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.5"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="10"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="30"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="60"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="120"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="300"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:e2e_request_latency_seconds_sum 47.813649 +tensorfold:e2e_request_latency_seconds_count 2 +# HELP tensorfold:request_decode_time_seconds Seconds a finished request spent decoding, under vLLM's name. +# TYPE tensorfold:request_decode_time_seconds histogram +tensorfold:request_decode_time_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="10"} 2 +tensorfold:request_decode_time_seconds_bucket{le="30"} 2 +tensorfold:request_decode_time_seconds_bucket{le="60"} 2 +tensorfold:request_decode_time_seconds_bucket{le="120"} 2 +tensorfold:request_decode_time_seconds_bucket{le="300"} 2 +tensorfold:request_decode_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_time_seconds_sum 0.000348 +tensorfold:request_decode_time_seconds_count 2 +# HELP tensorfold:request_prefill_time_seconds Seconds a finished request's prompt pass took, under vLLM's name. +# TYPE tensorfold:request_prefill_time_seconds histogram +tensorfold:request_prefill_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.5"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="60"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="120"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_time_seconds_sum 47.81204 +tensorfold:request_prefill_time_seconds_count 2 +# HELP tensorfold:client_disconnections_total Requests a client left before the reply left the server. +# TYPE tensorfold:client_disconnections_total counter +tensorfold:client_disconnections_total 0 +# HELP tensorfold:preemptions_total Requests that had to give a lane up to a later one. +# TYPE tensorfold:preemptions_total counter +tensorfold:preemptions_total 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-mapped-cold-r2-samples.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-mapped-cold-r2-samples.jsonl new file mode 100644 index 0000000000..c76db35300 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-mapped-cold-r2-samples.jsonl @@ -0,0 +1,56 @@ +{"t_s": 0.0, "VmRSS_bytes": 64618496, "VmHWM_bytes": 64618496, "Pss_bytes": 62483456, "vram_used_bytes": 187670528, "vram_total_bytes": 4294967296, "gtt_used_bytes": 31657984, "gtt_total_bytes": 193273528320} +{"t_s": 1.03, "VmRSS_bytes": 5742366720, "VmHWM_bytes": 5742366720, "Pss_bytes": 5760705536, "vram_used_bytes": 188637184, "vram_total_bytes": 4294967296, "gtt_used_bytes": 3557093376, "gtt_total_bytes": 193273528320} +{"t_s": 2.07, "VmRSS_bytes": 10437386240, "VmHWM_bytes": 10437386240, "Pss_bytes": 10449171456, "vram_used_bytes": 188903424, "vram_total_bytes": 4294967296, "gtt_used_bytes": 8485400576, "gtt_total_bytes": 193273528320} +{"t_s": 3.13, "VmRSS_bytes": 16189759488, "VmHWM_bytes": 16189759488, "Pss_bytes": 16187388928, "vram_used_bytes": 189235200, "vram_total_bytes": 4294967296, "gtt_used_bytes": 13411610624, "gtt_total_bytes": 193273528320} +{"t_s": 4.23, "VmRSS_bytes": 22386167808, "VmHWM_bytes": 22386167808, "Pss_bytes": 22402405376, "vram_used_bytes": 189689856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 19981987840, "gtt_total_bytes": 193273528320} +{"t_s": 5.33, "VmRSS_bytes": 29691592704, "VmHWM_bytes": 29691592704, "Pss_bytes": 29689222144, "vram_used_bytes": 190177280, "vram_total_bytes": 4294967296, "gtt_used_bytes": 27512860672, "gtt_total_bytes": 193273528320} +{"t_s": 6.47, "VmRSS_bytes": 36228136960, "VmHWM_bytes": 36228136960, "Pss_bytes": 36225766400, "vram_used_bytes": 190713856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 34769006592, "gtt_total_bytes": 193273528320} +{"t_s": 7.62, "VmRSS_bytes": 43471785984, "VmHWM_bytes": 43471785984, "Pss_bytes": 43487908864, "vram_used_bytes": 191152128, "vram_total_bytes": 4294967296, "gtt_used_bytes": 41345675264, "gtt_total_bytes": 193273528320} +{"t_s": 8.78, "VmRSS_bytes": 51544293376, "VmHWM_bytes": 51544293376, "Pss_bytes": 51565777920, "vram_used_bytes": 191700992, "vram_total_bytes": 4294967296, "gtt_used_bytes": 49562316800, "gtt_total_bytes": 193273528320} +{"t_s": 9.97, "VmRSS_bytes": 59342782464, "VmHWM_bytes": 59342782464, "Pss_bytes": 59375801344, "vram_used_bytes": 192274432, "vram_total_bytes": 4294967296, "gtt_used_bytes": 57770569728, "gtt_total_bytes": 193273528320} +{"t_s": 11.18, "VmRSS_bytes": 66171305984, "VmHWM_bytes": 66171305984, "Pss_bytes": 66187809792, "vram_used_bytes": 192729088, "vram_total_bytes": 4294967296, "gtt_used_bytes": 64343044096, "gtt_total_bytes": 193273528320} +{"t_s": 12.38, "VmRSS_bytes": 71666925568, "VmHWM_bytes": 71666925568, "Pss_bytes": 71706498048, "vram_used_bytes": 193069056, "vram_total_bytes": 4294967296, "gtt_used_bytes": 69275545600, "gtt_total_bytes": 193273528320} +{"t_s": 13.6, "VmRSS_bytes": 76577128448, "VmHWM_bytes": 76577128448, "Pss_bytes": 76583146496, "vram_used_bytes": 193425408, "vram_total_bytes": 4294967296, "gtt_used_bytes": 74201755648, "gtt_total_bytes": 193273528320} +{"t_s": 14.83, "VmRSS_bytes": 81961644032, "VmHWM_bytes": 81961644032, "Pss_bytes": 81963467776, "vram_used_bytes": 195194880, "vram_total_bytes": 4294967296, "gtt_used_bytes": 79933272064, "gtt_total_bytes": 193273528320} +{"t_s": 16.1, "VmRSS_bytes": 80902451200, "VmHWM_bytes": 82508812288, "Pss_bytes": 80900024320, "vram_used_bytes": 195424256, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88820039680, "gtt_total_bytes": 193273528320} +{"t_s": 17.32, "VmRSS_bytes": 80907370496, "VmHWM_bytes": 82508812288, "Pss_bytes": 80904988672, "vram_used_bytes": 195436544, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88824135680, "gtt_total_bytes": 193273528320} +{"t_s": 18.61, "VmRSS_bytes": 80910430208, "VmHWM_bytes": 82508812288, "Pss_bytes": 80908007424, "vram_used_bytes": 195440640, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88824504320, "gtt_total_bytes": 193273528320} +{"t_s": 19.84, "VmRSS_bytes": 80943386624, "VmHWM_bytes": 82508812288, "Pss_bytes": 80974910464, "vram_used_bytes": 195440640, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88824504320, "gtt_total_bytes": 193273528320} +{"t_s": 21.06, "VmRSS_bytes": 81163698176, "VmHWM_bytes": 82508812288, "Pss_bytes": 81230693376, "vram_used_bytes": 195440640, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 22.3, "VmRSS_bytes": 81565376512, "VmHWM_bytes": 82508812288, "Pss_bytes": 81630856192, "vram_used_bytes": 195440640, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 23.54, "VmRSS_bytes": 81960787968, "VmHWM_bytes": 82508812288, "Pss_bytes": 82021405696, "vram_used_bytes": 195440640, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 24.79, "VmRSS_bytes": 82309746688, "VmHWM_bytes": 82508812288, "Pss_bytes": 82366211072, "vram_used_bytes": 195440640, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 26.06, "VmRSS_bytes": 82625236992, "VmHWM_bytes": 82625236992, "Pss_bytes": 82643870720, "vram_used_bytes": 195440640, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 27.33, "VmRSS_bytes": 82648350720, "VmHWM_bytes": 82648350720, "Pss_bytes": 82645914624, "vram_used_bytes": 195440640, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 28.58, "VmRSS_bytes": 82648350720, "VmHWM_bytes": 82648350720, "Pss_bytes": 82645914624, "vram_used_bytes": 195440640, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 29.86, "VmRSS_bytes": 82648350720, "VmHWM_bytes": 82648350720, "Pss_bytes": 82645914624, "vram_used_bytes": 195440640, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 31.13, "VmRSS_bytes": 82648350720, "VmHWM_bytes": 82648350720, "Pss_bytes": 82645914624, "vram_used_bytes": 195440640, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 32.38, "VmRSS_bytes": 82648350720, "VmHWM_bytes": 82648350720, "Pss_bytes": 82645914624, "vram_used_bytes": 195440640, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 33.63, "VmRSS_bytes": 82832093184, "VmHWM_bytes": 82832093184, "Pss_bytes": 82880001024, "vram_used_bytes": 195440640, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 34.88, "VmRSS_bytes": 83108409344, "VmHWM_bytes": 83108409344, "Pss_bytes": 83145876480, "vram_used_bytes": 195440640, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 36.14, "VmRSS_bytes": 83343065088, "VmHWM_bytes": 83343065088, "Pss_bytes": 83376022528, "vram_used_bytes": 195440640, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 37.4, "VmRSS_bytes": 83379265536, "VmHWM_bytes": 83379265536, "Pss_bytes": 83376829440, "vram_used_bytes": 195440640, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 38.66, "VmRSS_bytes": 83379265536, "VmHWM_bytes": 83379265536, "Pss_bytes": 83376829440, "vram_used_bytes": 195440640, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 39.92, "VmRSS_bytes": 83379265536, "VmHWM_bytes": 83379265536, "Pss_bytes": 83376829440, "vram_used_bytes": 195440640, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 41.18, "VmRSS_bytes": 83379265536, "VmHWM_bytes": 83379265536, "Pss_bytes": 83376828416, "vram_used_bytes": 195440640, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 42.43, "VmRSS_bytes": 83379265536, "VmHWM_bytes": 83379265536, "Pss_bytes": 83376829440, "vram_used_bytes": 195440640, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 43.7, "VmRSS_bytes": 83379265536, "VmHWM_bytes": 83379265536, "Pss_bytes": 83376829440, "vram_used_bytes": 195440640, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 44.95, "VmRSS_bytes": 83485028352, "VmHWM_bytes": 83485028352, "Pss_bytes": 83519423488, "vram_used_bytes": 195440640, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 46.21, "VmRSS_bytes": 83697692672, "VmHWM_bytes": 83697692672, "Pss_bytes": 83730584576, "vram_used_bytes": 195440640, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 47.48, "VmRSS_bytes": 83898679296, "VmHWM_bytes": 83898679296, "Pss_bytes": 83922519040, "vram_used_bytes": 195440640, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 48.74, "VmRSS_bytes": 83925024768, "VmHWM_bytes": 83925024768, "Pss_bytes": 83922588672, "vram_used_bytes": 195440640, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 50.0, "VmRSS_bytes": 83925024768, "VmHWM_bytes": 83925024768, "Pss_bytes": 83922588672, "vram_used_bytes": 195440640, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 51.27, "VmRSS_bytes": 83925024768, "VmHWM_bytes": 83925024768, "Pss_bytes": 83922588672, "vram_used_bytes": 195440640, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 52.54, "VmRSS_bytes": 83925024768, "VmHWM_bytes": 83925024768, "Pss_bytes": 83922588672, "vram_used_bytes": 195440640, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 53.82, "VmRSS_bytes": 83925024768, "VmHWM_bytes": 83925024768, "Pss_bytes": 83922588672, "vram_used_bytes": 195440640, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 55.1, "VmRSS_bytes": 83925024768, "VmHWM_bytes": 83925024768, "Pss_bytes": 83922588672, "vram_used_bytes": 195440640, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 56.37, "VmRSS_bytes": 84009553920, "VmHWM_bytes": 84009553920, "Pss_bytes": 84038161408, "vram_used_bytes": 195440640, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 57.64, "VmRSS_bytes": 84194689024, "VmHWM_bytes": 84194689024, "Pss_bytes": 84223706112, "vram_used_bytes": 195440640, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 58.91, "VmRSS_bytes": 84368379904, "VmHWM_bytes": 84368379904, "Pss_bytes": 84384384000, "vram_used_bytes": 195440640, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 60.19, "VmRSS_bytes": 84386779136, "VmHWM_bytes": 84386779136, "Pss_bytes": 84384343040, "vram_used_bytes": 195440640, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 61.46, "VmRSS_bytes": 84386779136, "VmHWM_bytes": 84386779136, "Pss_bytes": 84384343040, "vram_used_bytes": 195440640, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 62.73, "VmRSS_bytes": 84386779136, "VmHWM_bytes": 84386779136, "Pss_bytes": 84384343040, "vram_used_bytes": 195440640, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 64.0, "VmRSS_bytes": 84386779136, "VmHWM_bytes": 84386779136, "Pss_bytes": 84384343040, "vram_used_bytes": 195440640, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 65.28, "VmRSS_bytes": 84386779136, "VmHWM_bytes": 84386779136, "Pss_bytes": 84384343040, "vram_used_bytes": 195440640, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 66.57, "VmRSS_bytes": 84386779136, "VmHWM_bytes": 84386779136, "Pss_bytes": 84384343040, "vram_used_bytes": 195440640, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 67.84, "VmRSS_bytes": 83526496256, "VmHWM_bytes": 84383375360, "Pss_bytes": 80392046592, "vram_used_bytes": 195272704, "vram_total_bytes": 4294967296, "gtt_used_bytes": 204288000, "gtt_total_bytes": 193273528320} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-mapped-warm-r1-memory-endpoint.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-mapped-warm-r1-memory-endpoint.json new file mode 100644 index 0000000000..faf691d2fa --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-mapped-warm-r1-memory-endpoint.json @@ -0,0 +1 @@ +{"schema_version": 1, "context_window": 20480, "context_fitted": false, "device": {"active_bytes": 87856892564, "cache_bytes": 0, "peak_bytes": 87896410020, "peak_scope": "since_start_or_health_reset"}} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-mapped-warm-r1-metrics.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-mapped-warm-r1-metrics.txt new file mode 100644 index 0000000000..39f9cfeb06 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-mapped-warm-r1-metrics.txt @@ -0,0 +1,220 @@ +# HELP tensorfold:requests_running Requests in prefill or decode. +# TYPE tensorfold:requests_running gauge +tensorfold:requests_running 0 +# HELP tensorfold:requests_waiting Requests queued or held until a lane is free. +# TYPE tensorfold:requests_waiting gauge +tensorfold:requests_waiting 0 +# HELP tensorfold:generation_tokens_running Generated tokens held by live streams. +# TYPE tensorfold:generation_tokens_running gauge +tensorfold:generation_tokens_running 0 +# HELP tensorfold:prompt_tokens_total Prompt tokens of finished requests. +# TYPE tensorfold:prompt_tokens_total counter +tensorfold:prompt_tokens_total 16640 +# HELP tensorfold:generation_tokens_total Generated tokens of finished requests. +# TYPE tensorfold:generation_tokens_total counter +tensorfold:generation_tokens_total 2 +# HELP tensorfold:kv_cache_usage_ratio Tokens in a stream cache divided by that stream's context window. +# TYPE tensorfold:kv_cache_usage_ratio gauge +tensorfold:kv_cache_usage_ratio{pool="0"} 0 +# HELP tensorfold:mtp_drafted_total Draft tokens verified on finished requests. +# TYPE tensorfold:mtp_drafted_total counter +tensorfold:mtp_drafted_total 0 +# HELP tensorfold:mtp_accepted_total Draft tokens kept on finished requests. +# TYPE tensorfold:mtp_accepted_total counter +tensorfold:mtp_accepted_total 0 +# HELP tensorfold:request_latency_seconds Seconds from arrival to the reply leaving. +# TYPE tensorfold:request_latency_seconds histogram +tensorfold:request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:request_latency_seconds_bucket{le="0.5"} 1 +tensorfold:request_latency_seconds_bucket{le="1"} 1 +tensorfold:request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:request_latency_seconds_bucket{le="5"} 1 +tensorfold:request_latency_seconds_bucket{le="10"} 1 +tensorfold:request_latency_seconds_bucket{le="30"} 1 +tensorfold:request_latency_seconds_bucket{le="60"} 2 +tensorfold:request_latency_seconds_bucket{le="120"} 2 +tensorfold:request_latency_seconds_bucket{le="300"} 2 +tensorfold:request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:request_latency_seconds_sum 31.37298 +tensorfold:request_latency_seconds_count 2 +# HELP tensorfold:time_to_first_token_seconds Seconds from arrival to the first generated token. +# TYPE tensorfold:time_to_first_token_seconds histogram +tensorfold:time_to_first_token_seconds_bucket{le="0.01"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.05"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.25"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="1"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="2.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="10"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="30"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="60"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="120"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="300"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="+Inf"} 2 +tensorfold:time_to_first_token_seconds_sum 31.372654 +tensorfold:time_to_first_token_seconds_count 2 +# HELP tensorfold:request_decode_seconds Seconds a finished request spent decoding. Its sum over generation_tokens_total is the decode rate. +# TYPE tensorfold:request_decode_seconds histogram +tensorfold:request_decode_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_seconds_bucket{le="1"} 2 +tensorfold:request_decode_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_seconds_bucket{le="5"} 2 +tensorfold:request_decode_seconds_bucket{le="10"} 2 +tensorfold:request_decode_seconds_bucket{le="30"} 2 +tensorfold:request_decode_seconds_bucket{le="60"} 2 +tensorfold:request_decode_seconds_bucket{le="120"} 2 +tensorfold:request_decode_seconds_bucket{le="300"} 2 +tensorfold:request_decode_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_seconds_sum 0.000326 +tensorfold:request_decode_seconds_count 2 +# HELP tensorfold:request_time_per_output_token_seconds Seconds from the first generated token to the last, divided by the tokens less one. +# TYPE tensorfold:request_time_per_output_token_seconds histogram +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.005"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.01"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.015"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.02"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.03"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.04"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.05"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.15"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.2"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.3"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.5"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="+Inf"} 0 +tensorfold:request_time_per_output_token_seconds_sum 0 +tensorfold:request_time_per_output_token_seconds_count 0 +# HELP tensorfold:decode_rounds_total Decode rounds used by finished requests. +# TYPE tensorfold:decode_rounds_total counter +tensorfold:decode_rounds_total 0 +# HELP tensorfold:request_prefill_seconds Seconds a finished request's prompt pass took. +# TYPE tensorfold:request_prefill_seconds histogram +tensorfold:request_prefill_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="1"} 1 +tensorfold:request_prefill_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_seconds_bucket{le="60"} 2 +tensorfold:request_prefill_seconds_bucket{le="120"} 2 +tensorfold:request_prefill_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_seconds_sum 31.371482 +tensorfold:request_prefill_seconds_count 2 +# HELP tensorfold:process_resident_bytes Current resident set (VmRSS); device memory is not in it, so it is not a physical footprint (Linux). +# TYPE tensorfold:process_resident_bytes gauge +tensorfold:process_resident_bytes 84411973632 +# HELP tensorfold:process_resident_anon_bytes Current resident anonymous memory (RssAnon): heap, stacks and private maps (Linux). +# TYPE tensorfold:process_resident_anon_bytes gauge +tensorfold:process_resident_anon_bytes 356560896 +# HELP tensorfold:process_resident_file_bytes Current resident file-backed memory (RssFile): the binary, libraries and mapped files (Linux). +# TYPE tensorfold:process_resident_file_bytes gauge +tensorfold:process_resident_file_bytes 83921149952 +# HELP tensorfold:process_resident_shmem_bytes Current resident shared memory (RssShmem): System V shared memory, tmpfs maps and shared anonymous maps (Linux). +# TYPE tensorfold:process_resident_shmem_bytes gauge +tensorfold:process_resident_shmem_bytes 134262784 +# HELP tensorfold:process_resident_peak_bytes Kernel lifetime peak resident set (VmHWM); never reset by health (Linux). +# TYPE tensorfold:process_resident_peak_bytes gauge +tensorfold:process_resident_peak_bytes 84411973632 +# HELP tensorfold:device_memory_bytes Device memory the engine holds now: weights, caches and live streams; only where the backend counts it (CUDA). +# TYPE tensorfold:device_memory_bytes gauge +tensorfold:device_memory_bytes 87856892564 +# HELP tensorfold:device_memory_peak_bytes The most device memory the engine has held since start or the last /health?reset_peak=1. +# TYPE tensorfold:device_memory_peak_bytes gauge +tensorfold:device_memory_peak_bytes 87896410020 +# HELP tensorfold:pinned_memory_bytes Pinned host memory the engine holds now: staging buffers and windows; only where the backend counts it (CUDA). +# TYPE tensorfold:pinned_memory_bytes gauge +tensorfold:pinned_memory_bytes 0 +# HELP tensorfold:num_requests_running Requests in prefill or decode. A mirror of tensorfold:requests_running. +# TYPE tensorfold:num_requests_running gauge +tensorfold:num_requests_running 0 +# HELP tensorfold:num_requests_waiting Requests queued or held until a lane is free. A mirror of tensorfold:requests_waiting. +# TYPE tensorfold:num_requests_waiting gauge +tensorfold:num_requests_waiting 0 +# HELP tensorfold:kv_cache_usage_perc A stream's cache occupancy under vLLM's name; same streams and ratios as tensorfold:kv_cache_usage_ratio. +# TYPE tensorfold:kv_cache_usage_perc gauge +tensorfold:kv_cache_usage_perc{stream="0"} 0 +# HELP tensorfold:spec_decode_num_draft_tokens_total Draft tokens verified on finished requests, this server's single draft counter. +# TYPE tensorfold:spec_decode_num_draft_tokens_total counter +tensorfold:spec_decode_num_draft_tokens_total 0 +# HELP tensorfold:spec_decode_num_accepted_tokens_total Draft tokens kept on finished requests. +# TYPE tensorfold:spec_decode_num_accepted_tokens_total counter +tensorfold:spec_decode_num_accepted_tokens_total 0 +# HELP tensorfold:e2e_request_latency_seconds Seconds from arrival to the reply leaving, under vLLM's name. +# TYPE tensorfold:e2e_request_latency_seconds histogram +tensorfold:e2e_request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="1"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="10"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="30"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="60"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="120"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="300"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:e2e_request_latency_seconds_sum 31.37298 +tensorfold:e2e_request_latency_seconds_count 2 +# HELP tensorfold:request_decode_time_seconds Seconds a finished request spent decoding, under vLLM's name. +# TYPE tensorfold:request_decode_time_seconds histogram +tensorfold:request_decode_time_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="10"} 2 +tensorfold:request_decode_time_seconds_bucket{le="30"} 2 +tensorfold:request_decode_time_seconds_bucket{le="60"} 2 +tensorfold:request_decode_time_seconds_bucket{le="120"} 2 +tensorfold:request_decode_time_seconds_bucket{le="300"} 2 +tensorfold:request_decode_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_time_seconds_sum 0.000326 +tensorfold:request_decode_time_seconds_count 2 +# HELP tensorfold:request_prefill_time_seconds Seconds a finished request's prompt pass took, under vLLM's name. +# TYPE tensorfold:request_prefill_time_seconds histogram +tensorfold:request_prefill_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="1"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="60"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="120"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_time_seconds_sum 31.371482 +tensorfold:request_prefill_time_seconds_count 2 +# HELP tensorfold:client_disconnections_total Requests a client left before the reply left the server. +# TYPE tensorfold:client_disconnections_total counter +tensorfold:client_disconnections_total 0 +# HELP tensorfold:preemptions_total Requests that had to give a lane up to a later one. +# TYPE tensorfold:preemptions_total counter +tensorfold:preemptions_total 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-mapped-warm-r1-samples.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-mapped-warm-r1-samples.jsonl new file mode 100644 index 0000000000..f745eab61b --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-mapped-warm-r1-samples.jsonl @@ -0,0 +1,38 @@ +{"t_s": 0.0, "VmRSS_bytes": 73768960, "VmHWM_bytes": 73768960, "Pss_bytes": 71766016, "vram_used_bytes": 187682816, "vram_total_bytes": 4294967296, "gtt_used_bytes": 31657984, "gtt_total_bytes": 193273528320} +{"t_s": 1.04, "VmRSS_bytes": 9994145792, "VmHWM_bytes": 9994145792, "Pss_bytes": 10052282368, "vram_used_bytes": 188805120, "vram_total_bytes": 4294967296, "gtt_used_bytes": 6847524864, "gtt_total_bytes": 193273528320} +{"t_s": 2.11, "VmRSS_bytes": 18167504896, "VmHWM_bytes": 18167504896, "Pss_bytes": 18270402560, "vram_used_bytes": 189358080, "vram_total_bytes": 4294967296, "gtt_used_bytes": 15062069248, "gtt_total_bytes": 193273528320} +{"t_s": 3.2, "VmRSS_bytes": 26444931072, "VmHWM_bytes": 26444931072, "Pss_bytes": 26442708992, "vram_used_bytes": 189943808, "vram_total_bytes": 4294967296, "gtt_used_bytes": 24228720640, "gtt_total_bytes": 193273528320} +{"t_s": 4.33, "VmRSS_bytes": 34599018496, "VmHWM_bytes": 34599018496, "Pss_bytes": 34596796416, "vram_used_bytes": 190595072, "vram_total_bytes": 4294967296, "gtt_used_bytes": 33124839424, "gtt_total_bytes": 193273528320} +{"t_s": 5.48, "VmRSS_bytes": 44109570048, "VmHWM_bytes": 44109570048, "Pss_bytes": 44179437568, "vram_used_bytes": 191156224, "vram_total_bytes": 4294967296, "gtt_used_bytes": 41345675264, "gtt_total_bytes": 193273528320} +{"t_s": 6.65, "VmRSS_bytes": 52441092096, "VmHWM_bytes": 52441092096, "Pss_bytes": 52438870016, "vram_used_bytes": 191827968, "vram_total_bytes": 4294967296, "gtt_used_bytes": 51200192512, "gtt_total_bytes": 193273528320} +{"t_s": 7.85, "VmRSS_bytes": 62174126080, "VmHWM_bytes": 62174126080, "Pss_bytes": 62171904000, "vram_used_bytes": 192507904, "vram_total_bytes": 4294967296, "gtt_used_bytes": 61058904064, "gtt_total_bytes": 193273528320} +{"t_s": 9.07, "VmRSS_bytes": 71904493568, "VmHWM_bytes": 71904493568, "Pss_bytes": 71902271488, "vram_used_bytes": 193150976, "vram_total_bytes": 4294967296, "gtt_used_bytes": 70913421312, "gtt_total_bytes": 193273528320} +{"t_s": 10.3, "VmRSS_bytes": 82500685824, "VmHWM_bytes": 82500685824, "Pss_bytes": 82498460672, "vram_used_bytes": 194920448, "vram_total_bytes": 4294967296, "gtt_used_bytes": 79937466368, "gtt_total_bytes": 193273528320} +{"t_s": 11.57, "VmRSS_bytes": 80897982464, "VmHWM_bytes": 82503135232, "Pss_bytes": 80895695872, "vram_used_bytes": 195149824, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88823029760, "gtt_total_bytes": 193273528320} +{"t_s": 12.83, "VmRSS_bytes": 80903139328, "VmHWM_bytes": 82503135232, "Pss_bytes": 80900852736, "vram_used_bytes": 195153920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88824504320, "gtt_total_bytes": 193273528320} +{"t_s": 14.05, "VmRSS_bytes": 80904884224, "VmHWM_bytes": 82503135232, "Pss_bytes": 80902597632, "vram_used_bytes": 195153920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88824504320, "gtt_total_bytes": 193273528320} +{"t_s": 15.32, "VmRSS_bytes": 82976374784, "VmHWM_bytes": 82976374784, "Pss_bytes": 82974084096, "vram_used_bytes": 195153920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 16.6, "VmRSS_bytes": 82976374784, "VmHWM_bytes": 82976374784, "Pss_bytes": 82974084096, "vram_used_bytes": 195153920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 17.87, "VmRSS_bytes": 82976374784, "VmHWM_bytes": 82976374784, "Pss_bytes": 82974084096, "vram_used_bytes": 195153920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 19.14, "VmRSS_bytes": 82976374784, "VmHWM_bytes": 82976374784, "Pss_bytes": 82974083072, "vram_used_bytes": 195153920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 20.42, "VmRSS_bytes": 82976374784, "VmHWM_bytes": 82976374784, "Pss_bytes": 82974084096, "vram_used_bytes": 195153920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 21.69, "VmRSS_bytes": 83683803136, "VmHWM_bytes": 83683803136, "Pss_bytes": 83681512448, "vram_used_bytes": 195153920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 22.97, "VmRSS_bytes": 83683803136, "VmHWM_bytes": 83683803136, "Pss_bytes": 83681511424, "vram_used_bytes": 195153920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 24.26, "VmRSS_bytes": 83683803136, "VmHWM_bytes": 83683803136, "Pss_bytes": 83681511424, "vram_used_bytes": 195153920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 25.54, "VmRSS_bytes": 83686248448, "VmHWM_bytes": 83686248448, "Pss_bytes": 83683956736, "vram_used_bytes": 195153920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 26.82, "VmRSS_bytes": 83686248448, "VmHWM_bytes": 83686248448, "Pss_bytes": 83683956736, "vram_used_bytes": 195153920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 28.11, "VmRSS_bytes": 83686248448, "VmHWM_bytes": 83686248448, "Pss_bytes": 83683956736, "vram_used_bytes": 195153920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 29.4, "VmRSS_bytes": 83686248448, "VmHWM_bytes": 83686248448, "Pss_bytes": 84113340416, "vram_used_bytes": 195153920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 30.67, "VmRSS_bytes": 84115701760, "VmHWM_bytes": 84115701760, "Pss_bytes": 84113410048, "vram_used_bytes": 195153920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 31.93, "VmRSS_bytes": 84115701760, "VmHWM_bytes": 84115701760, "Pss_bytes": 84113410048, "vram_used_bytes": 195153920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 33.21, "VmRSS_bytes": 84115701760, "VmHWM_bytes": 84115701760, "Pss_bytes": 84113410048, "vram_used_bytes": 195153920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 34.47, "VmRSS_bytes": 84115701760, "VmHWM_bytes": 84115701760, "Pss_bytes": 84113410048, "vram_used_bytes": 195153920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 35.75, "VmRSS_bytes": 84115701760, "VmHWM_bytes": 84115701760, "Pss_bytes": 84113410048, "vram_used_bytes": 195153920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 37.03, "VmRSS_bytes": 84115701760, "VmHWM_bytes": 84115701760, "Pss_bytes": 84113410048, "vram_used_bytes": 195153920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 38.33, "VmRSS_bytes": 84412772352, "VmHWM_bytes": 84412772352, "Pss_bytes": 84410480640, "vram_used_bytes": 195153920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 39.63, "VmRSS_bytes": 84412772352, "VmHWM_bytes": 84412772352, "Pss_bytes": 84410482688, "vram_used_bytes": 195153920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 40.93, "VmRSS_bytes": 84412772352, "VmHWM_bytes": 84412772352, "Pss_bytes": 84410482688, "vram_used_bytes": 195153920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 42.23, "VmRSS_bytes": 84412772352, "VmHWM_bytes": 84412772352, "Pss_bytes": 84410482688, "vram_used_bytes": 195153920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 43.52, "VmRSS_bytes": 84412772352, "VmHWM_bytes": 84412772352, "Pss_bytes": 84410482688, "vram_used_bytes": 195153920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 44.8, "VmRSS_bytes": 84412772352, "VmHWM_bytes": 84412772352, "Pss_bytes": 84410482688, "vram_used_bytes": 195153920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 46.07, "VmRSS_bytes": 84411785216, "VmHWM_bytes": 84411785216, "Pss_bytes": 84409476096, "vram_used_bytes": 195153920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88824504320, "gtt_total_bytes": 193273528320} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-mapped-warm-r2-memory-endpoint.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-mapped-warm-r2-memory-endpoint.json new file mode 100644 index 0000000000..faf691d2fa --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-mapped-warm-r2-memory-endpoint.json @@ -0,0 +1 @@ +{"schema_version": 1, "context_window": 20480, "context_fitted": false, "device": {"active_bytes": 87856892564, "cache_bytes": 0, "peak_bytes": 87896410020, "peak_scope": "since_start_or_health_reset"}} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-mapped-warm-r2-metrics.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-mapped-warm-r2-metrics.txt new file mode 100644 index 0000000000..efc70f84c3 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-mapped-warm-r2-metrics.txt @@ -0,0 +1,220 @@ +# HELP tensorfold:requests_running Requests in prefill or decode. +# TYPE tensorfold:requests_running gauge +tensorfold:requests_running 0 +# HELP tensorfold:requests_waiting Requests queued or held until a lane is free. +# TYPE tensorfold:requests_waiting gauge +tensorfold:requests_waiting 0 +# HELP tensorfold:generation_tokens_running Generated tokens held by live streams. +# TYPE tensorfold:generation_tokens_running gauge +tensorfold:generation_tokens_running 0 +# HELP tensorfold:prompt_tokens_total Prompt tokens of finished requests. +# TYPE tensorfold:prompt_tokens_total counter +tensorfold:prompt_tokens_total 16640 +# HELP tensorfold:generation_tokens_total Generated tokens of finished requests. +# TYPE tensorfold:generation_tokens_total counter +tensorfold:generation_tokens_total 2 +# HELP tensorfold:kv_cache_usage_ratio Tokens in a stream cache divided by that stream's context window. +# TYPE tensorfold:kv_cache_usage_ratio gauge +tensorfold:kv_cache_usage_ratio{pool="0"} 0 +# HELP tensorfold:mtp_drafted_total Draft tokens verified on finished requests. +# TYPE tensorfold:mtp_drafted_total counter +tensorfold:mtp_drafted_total 0 +# HELP tensorfold:mtp_accepted_total Draft tokens kept on finished requests. +# TYPE tensorfold:mtp_accepted_total counter +tensorfold:mtp_accepted_total 0 +# HELP tensorfold:request_latency_seconds Seconds from arrival to the reply leaving. +# TYPE tensorfold:request_latency_seconds histogram +tensorfold:request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:request_latency_seconds_bucket{le="0.5"} 1 +tensorfold:request_latency_seconds_bucket{le="1"} 1 +tensorfold:request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:request_latency_seconds_bucket{le="5"} 1 +tensorfold:request_latency_seconds_bucket{le="10"} 1 +tensorfold:request_latency_seconds_bucket{le="30"} 1 +tensorfold:request_latency_seconds_bucket{le="60"} 2 +tensorfold:request_latency_seconds_bucket{le="120"} 2 +tensorfold:request_latency_seconds_bucket{le="300"} 2 +tensorfold:request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:request_latency_seconds_sum 31.378242 +tensorfold:request_latency_seconds_count 2 +# HELP tensorfold:time_to_first_token_seconds Seconds from arrival to the first generated token. +# TYPE tensorfold:time_to_first_token_seconds histogram +tensorfold:time_to_first_token_seconds_bucket{le="0.01"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.05"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.25"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="1"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="2.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="10"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="30"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="60"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="120"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="300"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="+Inf"} 2 +tensorfold:time_to_first_token_seconds_sum 31.377666 +tensorfold:time_to_first_token_seconds_count 2 +# HELP tensorfold:request_decode_seconds Seconds a finished request spent decoding. Its sum over generation_tokens_total is the decode rate. +# TYPE tensorfold:request_decode_seconds histogram +tensorfold:request_decode_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_seconds_bucket{le="1"} 2 +tensorfold:request_decode_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_seconds_bucket{le="5"} 2 +tensorfold:request_decode_seconds_bucket{le="10"} 2 +tensorfold:request_decode_seconds_bucket{le="30"} 2 +tensorfold:request_decode_seconds_bucket{le="60"} 2 +tensorfold:request_decode_seconds_bucket{le="120"} 2 +tensorfold:request_decode_seconds_bucket{le="300"} 2 +tensorfold:request_decode_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_seconds_sum 0.000576 +tensorfold:request_decode_seconds_count 2 +# HELP tensorfold:request_time_per_output_token_seconds Seconds from the first generated token to the last, divided by the tokens less one. +# TYPE tensorfold:request_time_per_output_token_seconds histogram +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.005"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.01"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.015"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.02"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.03"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.04"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.05"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.15"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.2"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.3"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.5"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="+Inf"} 0 +tensorfold:request_time_per_output_token_seconds_sum 0 +tensorfold:request_time_per_output_token_seconds_count 0 +# HELP tensorfold:decode_rounds_total Decode rounds used by finished requests. +# TYPE tensorfold:decode_rounds_total counter +tensorfold:decode_rounds_total 0 +# HELP tensorfold:request_prefill_seconds Seconds a finished request's prompt pass took. +# TYPE tensorfold:request_prefill_seconds histogram +tensorfold:request_prefill_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="1"} 1 +tensorfold:request_prefill_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_seconds_bucket{le="60"} 2 +tensorfold:request_prefill_seconds_bucket{le="120"} 2 +tensorfold:request_prefill_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_seconds_sum 31.376029 +tensorfold:request_prefill_seconds_count 2 +# HELP tensorfold:process_resident_bytes Current resident set (VmRSS); device memory is not in it, so it is not a physical footprint (Linux). +# TYPE tensorfold:process_resident_bytes gauge +tensorfold:process_resident_bytes 84431622144 +# HELP tensorfold:process_resident_anon_bytes Current resident anonymous memory (RssAnon): heap, stacks and private maps (Linux). +# TYPE tensorfold:process_resident_anon_bytes gauge +tensorfold:process_resident_anon_bytes 355106816 +# HELP tensorfold:process_resident_file_bytes Current resident file-backed memory (RssFile): the binary, libraries and mapped files (Linux). +# TYPE tensorfold:process_resident_file_bytes gauge +tensorfold:process_resident_file_bytes 83942252544 +# HELP tensorfold:process_resident_shmem_bytes Current resident shared memory (RssShmem): System V shared memory, tmpfs maps and shared anonymous maps (Linux). +# TYPE tensorfold:process_resident_shmem_bytes gauge +tensorfold:process_resident_shmem_bytes 134262784 +# HELP tensorfold:process_resident_peak_bytes Kernel lifetime peak resident set (VmHWM); never reset by health (Linux). +# TYPE tensorfold:process_resident_peak_bytes gauge +tensorfold:process_resident_peak_bytes 84431622144 +# HELP tensorfold:device_memory_bytes Device memory the engine holds now: weights, caches and live streams; only where the backend counts it (CUDA). +# TYPE tensorfold:device_memory_bytes gauge +tensorfold:device_memory_bytes 87856892564 +# HELP tensorfold:device_memory_peak_bytes The most device memory the engine has held since start or the last /health?reset_peak=1. +# TYPE tensorfold:device_memory_peak_bytes gauge +tensorfold:device_memory_peak_bytes 87896410020 +# HELP tensorfold:pinned_memory_bytes Pinned host memory the engine holds now: staging buffers and windows; only where the backend counts it (CUDA). +# TYPE tensorfold:pinned_memory_bytes gauge +tensorfold:pinned_memory_bytes 0 +# HELP tensorfold:num_requests_running Requests in prefill or decode. A mirror of tensorfold:requests_running. +# TYPE tensorfold:num_requests_running gauge +tensorfold:num_requests_running 0 +# HELP tensorfold:num_requests_waiting Requests queued or held until a lane is free. A mirror of tensorfold:requests_waiting. +# TYPE tensorfold:num_requests_waiting gauge +tensorfold:num_requests_waiting 0 +# HELP tensorfold:kv_cache_usage_perc A stream's cache occupancy under vLLM's name; same streams and ratios as tensorfold:kv_cache_usage_ratio. +# TYPE tensorfold:kv_cache_usage_perc gauge +tensorfold:kv_cache_usage_perc{stream="0"} 0 +# HELP tensorfold:spec_decode_num_draft_tokens_total Draft tokens verified on finished requests, this server's single draft counter. +# TYPE tensorfold:spec_decode_num_draft_tokens_total counter +tensorfold:spec_decode_num_draft_tokens_total 0 +# HELP tensorfold:spec_decode_num_accepted_tokens_total Draft tokens kept on finished requests. +# TYPE tensorfold:spec_decode_num_accepted_tokens_total counter +tensorfold:spec_decode_num_accepted_tokens_total 0 +# HELP tensorfold:e2e_request_latency_seconds Seconds from arrival to the reply leaving, under vLLM's name. +# TYPE tensorfold:e2e_request_latency_seconds histogram +tensorfold:e2e_request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="1"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="10"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="30"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="60"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="120"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="300"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:e2e_request_latency_seconds_sum 31.378242 +tensorfold:e2e_request_latency_seconds_count 2 +# HELP tensorfold:request_decode_time_seconds Seconds a finished request spent decoding, under vLLM's name. +# TYPE tensorfold:request_decode_time_seconds histogram +tensorfold:request_decode_time_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="10"} 2 +tensorfold:request_decode_time_seconds_bucket{le="30"} 2 +tensorfold:request_decode_time_seconds_bucket{le="60"} 2 +tensorfold:request_decode_time_seconds_bucket{le="120"} 2 +tensorfold:request_decode_time_seconds_bucket{le="300"} 2 +tensorfold:request_decode_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_time_seconds_sum 0.000576 +tensorfold:request_decode_time_seconds_count 2 +# HELP tensorfold:request_prefill_time_seconds Seconds a finished request's prompt pass took, under vLLM's name. +# TYPE tensorfold:request_prefill_time_seconds histogram +tensorfold:request_prefill_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="1"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="60"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="120"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_time_seconds_sum 31.376029 +tensorfold:request_prefill_time_seconds_count 2 +# HELP tensorfold:client_disconnections_total Requests a client left before the reply left the server. +# TYPE tensorfold:client_disconnections_total counter +tensorfold:client_disconnections_total 0 +# HELP tensorfold:preemptions_total Requests that had to give a lane up to a later one. +# TYPE tensorfold:preemptions_total counter +tensorfold:preemptions_total 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-mapped-warm-r2-samples.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-mapped-warm-r2-samples.jsonl new file mode 100644 index 0000000000..16edb999b3 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-mapped-warm-r2-samples.jsonl @@ -0,0 +1,39 @@ +{"t_s": 0.0, "VmRSS_bytes": 72474624, "VmHWM_bytes": 72474624, "Pss_bytes": 70161408, "vram_used_bytes": 187682816, "vram_total_bytes": 4294967296, "gtt_used_bytes": 31657984, "gtt_total_bytes": 193273528320} +{"t_s": 1.04, "VmRSS_bytes": 9813938176, "VmHWM_bytes": 9813938176, "Pss_bytes": 9844787200, "vram_used_bytes": 188801024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 6847524864, "gtt_total_bytes": 193273528320} +{"t_s": 2.11, "VmRSS_bytes": 18201993216, "VmHWM_bytes": 18201993216, "Pss_bytes": 18310889472, "vram_used_bytes": 189353984, "vram_total_bytes": 4294967296, "gtt_used_bytes": 15062069248, "gtt_total_bytes": 193273528320} +{"t_s": 3.21, "VmRSS_bytes": 26443833344, "VmHWM_bytes": 26443833344, "Pss_bytes": 26441390080, "vram_used_bytes": 189939712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 24228720640, "gtt_total_bytes": 193273528320} +{"t_s": 4.34, "VmRSS_bytes": 34597920768, "VmHWM_bytes": 34597920768, "Pss_bytes": 34595477504, "vram_used_bytes": 190590976, "vram_total_bytes": 4294967296, "gtt_used_bytes": 33124839424, "gtt_total_bytes": 193273528320} +{"t_s": 5.48, "VmRSS_bytes": 44151726080, "VmHWM_bytes": 44151726080, "Pss_bytes": 44214294528, "vram_used_bytes": 191152128, "vram_total_bytes": 4294967296, "gtt_used_bytes": 41345675264, "gtt_total_bytes": 193273528320} +{"t_s": 6.65, "VmRSS_bytes": 52439994368, "VmHWM_bytes": 52439994368, "Pss_bytes": 52437551104, "vram_used_bytes": 191823872, "vram_total_bytes": 4294967296, "gtt_used_bytes": 51200192512, "gtt_total_bytes": 193273528320} +{"t_s": 7.83, "VmRSS_bytes": 62149234688, "VmHWM_bytes": 62149234688, "Pss_bytes": 62156163072, "vram_used_bytes": 192479232, "vram_total_bytes": 4294967296, "gtt_used_bytes": 61042126848, "gtt_total_bytes": 193273528320} +{"t_s": 9.03, "VmRSS_bytes": 70688804864, "VmHWM_bytes": 70688804864, "Pss_bytes": 70750062592, "vram_used_bytes": 193073152, "vram_total_bytes": 4294967296, "gtt_used_bytes": 69275545600, "gtt_total_bytes": 193273528320} +{"t_s": 10.25, "VmRSS_bytes": 80685940736, "VmHWM_bytes": 80685940736, "Pss_bytes": 80717182976, "vram_used_bytes": 195002368, "vram_total_bytes": 4294967296, "gtt_used_bytes": 79874551808, "gtt_total_bytes": 193273528320} +{"t_s": 11.49, "VmRSS_bytes": 80895152128, "VmHWM_bytes": 82501787648, "Pss_bytes": 80892650496, "vram_used_bytes": 195420160, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88820408320, "gtt_total_bytes": 193273528320} +{"t_s": 12.72, "VmRSS_bytes": 80900075520, "VmHWM_bytes": 82501787648, "Pss_bytes": 80897573888, "vram_used_bytes": 195428352, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88824135680, "gtt_total_bytes": 193273528320} +{"t_s": 14.02, "VmRSS_bytes": 80902868992, "VmHWM_bytes": 82501787648, "Pss_bytes": 80900371456, "vram_used_bytes": 195428352, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88824504320, "gtt_total_bytes": 193273528320} +{"t_s": 15.24, "VmRSS_bytes": 80903708672, "VmHWM_bytes": 82501787648, "Pss_bytes": 80901207040, "vram_used_bytes": 195428352, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88824504320, "gtt_total_bytes": 193273528320} +{"t_s": 16.51, "VmRSS_bytes": 82989682688, "VmHWM_bytes": 82989682688, "Pss_bytes": 82987173888, "vram_used_bytes": 195428352, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 17.79, "VmRSS_bytes": 82989682688, "VmHWM_bytes": 82989682688, "Pss_bytes": 82987173888, "vram_used_bytes": 195428352, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 19.05, "VmRSS_bytes": 82992021504, "VmHWM_bytes": 82992021504, "Pss_bytes": 82989512704, "vram_used_bytes": 195428352, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 20.33, "VmRSS_bytes": 82992021504, "VmHWM_bytes": 82992021504, "Pss_bytes": 82989512704, "vram_used_bytes": 195428352, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 21.6, "VmRSS_bytes": 82992021504, "VmHWM_bytes": 82992021504, "Pss_bytes": 82989512704, "vram_used_bytes": 195428352, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 22.87, "VmRSS_bytes": 83701858304, "VmHWM_bytes": 83701858304, "Pss_bytes": 83699349504, "vram_used_bytes": 195428352, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 24.15, "VmRSS_bytes": 83701858304, "VmHWM_bytes": 83701858304, "Pss_bytes": 83699349504, "vram_used_bytes": 195428352, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 25.43, "VmRSS_bytes": 83701858304, "VmHWM_bytes": 83701858304, "Pss_bytes": 83699349504, "vram_used_bytes": 195428352, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 26.71, "VmRSS_bytes": 83701858304, "VmHWM_bytes": 83701858304, "Pss_bytes": 83699349504, "vram_used_bytes": 195428352, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 28.0, "VmRSS_bytes": 83701858304, "VmHWM_bytes": 83701858304, "Pss_bytes": 83699349504, "vram_used_bytes": 195428352, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 29.29, "VmRSS_bytes": 83701858304, "VmHWM_bytes": 83701858304, "Pss_bytes": 83699349504, "vram_used_bytes": 195428352, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 30.58, "VmRSS_bytes": 83701858304, "VmHWM_bytes": 83701858304, "Pss_bytes": 84131006464, "vram_used_bytes": 195428352, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 31.85, "VmRSS_bytes": 84133584896, "VmHWM_bytes": 84133584896, "Pss_bytes": 84131076096, "vram_used_bytes": 195428352, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 33.12, "VmRSS_bytes": 84133584896, "VmHWM_bytes": 84133584896, "Pss_bytes": 84131076096, "vram_used_bytes": 195428352, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 34.38, "VmRSS_bytes": 84133584896, "VmHWM_bytes": 84133584896, "Pss_bytes": 84131076096, "vram_used_bytes": 195428352, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 35.65, "VmRSS_bytes": 84133584896, "VmHWM_bytes": 84133584896, "Pss_bytes": 84131076096, "vram_used_bytes": 195428352, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 36.92, "VmRSS_bytes": 84133584896, "VmHWM_bytes": 84133584896, "Pss_bytes": 84131076096, "vram_used_bytes": 195428352, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 38.2, "VmRSS_bytes": 84133584896, "VmHWM_bytes": 84133584896, "Pss_bytes": 84131076096, "vram_used_bytes": 195428352, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 39.5, "VmRSS_bytes": 84432424960, "VmHWM_bytes": 84432424960, "Pss_bytes": 84429916160, "vram_used_bytes": 195428352, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 40.81, "VmRSS_bytes": 84432424960, "VmHWM_bytes": 84432424960, "Pss_bytes": 84429915136, "vram_used_bytes": 195428352, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 42.1, "VmRSS_bytes": 84432424960, "VmHWM_bytes": 84432424960, "Pss_bytes": 84429915136, "vram_used_bytes": 195428352, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 43.39, "VmRSS_bytes": 84432424960, "VmHWM_bytes": 84432424960, "Pss_bytes": 84429916160, "vram_used_bytes": 195428352, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 44.67, "VmRSS_bytes": 84432424960, "VmHWM_bytes": 84432424960, "Pss_bytes": 84429916160, "vram_used_bytes": 195428352, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 45.95, "VmRSS_bytes": 84432424960, "VmHWM_bytes": 84432424960, "Pss_bytes": 84429916160, "vram_used_bytes": 195428352, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88864350208, "gtt_total_bytes": 193273528320} +{"t_s": 47.23, "VmRSS_bytes": 84431433728, "VmHWM_bytes": 84431433728, "Pss_bytes": 84428918784, "vram_used_bytes": 195428352, "vram_total_bytes": 4294967296, "gtt_used_bytes": 88824504320, "gtt_total_bytes": 193273528320} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step1024-mapped-r1-memory-endpoint.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step1024-mapped-r1-memory-endpoint.json new file mode 100644 index 0000000000..d4ff0b5aeb --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step1024-mapped-r1-memory-endpoint.json @@ -0,0 +1 @@ +{"schema_version": 1, "context_window": 20480, "context_fitted": false, "device": {"active_bytes": 83064265364, "cache_bytes": 0, "peak_bytes": 83103782820, "peak_scope": "since_start_or_health_reset"}} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step1024-mapped-r1-metrics.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step1024-mapped-r1-metrics.txt new file mode 100644 index 0000000000..6a46f14d43 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step1024-mapped-r1-metrics.txt @@ -0,0 +1,220 @@ +# HELP tensorfold:requests_running Requests in prefill or decode. +# TYPE tensorfold:requests_running gauge +tensorfold:requests_running 0 +# HELP tensorfold:requests_waiting Requests queued or held until a lane is free. +# TYPE tensorfold:requests_waiting gauge +tensorfold:requests_waiting 0 +# HELP tensorfold:generation_tokens_running Generated tokens held by live streams. +# TYPE tensorfold:generation_tokens_running gauge +tensorfold:generation_tokens_running 0 +# HELP tensorfold:prompt_tokens_total Prompt tokens of finished requests. +# TYPE tensorfold:prompt_tokens_total counter +tensorfold:prompt_tokens_total 16640 +# HELP tensorfold:generation_tokens_total Generated tokens of finished requests. +# TYPE tensorfold:generation_tokens_total counter +tensorfold:generation_tokens_total 2 +# HELP tensorfold:kv_cache_usage_ratio Tokens in a stream cache divided by that stream's context window. +# TYPE tensorfold:kv_cache_usage_ratio gauge +tensorfold:kv_cache_usage_ratio{pool="0"} 0 +# HELP tensorfold:mtp_drafted_total Draft tokens verified on finished requests. +# TYPE tensorfold:mtp_drafted_total counter +tensorfold:mtp_drafted_total 0 +# HELP tensorfold:mtp_accepted_total Draft tokens kept on finished requests. +# TYPE tensorfold:mtp_accepted_total counter +tensorfold:mtp_accepted_total 0 +# HELP tensorfold:request_latency_seconds Seconds from arrival to the reply leaving. +# TYPE tensorfold:request_latency_seconds histogram +tensorfold:request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:request_latency_seconds_bucket{le="0.5"} 1 +tensorfold:request_latency_seconds_bucket{le="1"} 1 +tensorfold:request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:request_latency_seconds_bucket{le="5"} 1 +tensorfold:request_latency_seconds_bucket{le="10"} 1 +tensorfold:request_latency_seconds_bucket{le="30"} 1 +tensorfold:request_latency_seconds_bucket{le="60"} 2 +tensorfold:request_latency_seconds_bucket{le="120"} 2 +tensorfold:request_latency_seconds_bucket{le="300"} 2 +tensorfold:request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:request_latency_seconds_sum 34.56361 +tensorfold:request_latency_seconds_count 2 +# HELP tensorfold:time_to_first_token_seconds Seconds from arrival to the first generated token. +# TYPE tensorfold:time_to_first_token_seconds histogram +tensorfold:time_to_first_token_seconds_bucket{le="0.01"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.05"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.25"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="1"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="2.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="10"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="30"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="60"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="120"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="300"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="+Inf"} 2 +tensorfold:time_to_first_token_seconds_sum 34.563244 +tensorfold:time_to_first_token_seconds_count 2 +# HELP tensorfold:request_decode_seconds Seconds a finished request spent decoding. Its sum over generation_tokens_total is the decode rate. +# TYPE tensorfold:request_decode_seconds histogram +tensorfold:request_decode_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_seconds_bucket{le="1"} 2 +tensorfold:request_decode_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_seconds_bucket{le="5"} 2 +tensorfold:request_decode_seconds_bucket{le="10"} 2 +tensorfold:request_decode_seconds_bucket{le="30"} 2 +tensorfold:request_decode_seconds_bucket{le="60"} 2 +tensorfold:request_decode_seconds_bucket{le="120"} 2 +tensorfold:request_decode_seconds_bucket{le="300"} 2 +tensorfold:request_decode_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_seconds_sum 0.000366 +tensorfold:request_decode_seconds_count 2 +# HELP tensorfold:request_time_per_output_token_seconds Seconds from the first generated token to the last, divided by the tokens less one. +# TYPE tensorfold:request_time_per_output_token_seconds histogram +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.005"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.01"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.015"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.02"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.03"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.04"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.05"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.15"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.2"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.3"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.5"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="+Inf"} 0 +tensorfold:request_time_per_output_token_seconds_sum 0 +tensorfold:request_time_per_output_token_seconds_count 0 +# HELP tensorfold:decode_rounds_total Decode rounds used by finished requests. +# TYPE tensorfold:decode_rounds_total counter +tensorfold:decode_rounds_total 0 +# HELP tensorfold:request_prefill_seconds Seconds a finished request's prompt pass took. +# TYPE tensorfold:request_prefill_seconds histogram +tensorfold:request_prefill_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="1"} 1 +tensorfold:request_prefill_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_seconds_bucket{le="60"} 2 +tensorfold:request_prefill_seconds_bucket{le="120"} 2 +tensorfold:request_prefill_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_seconds_sum 34.561917 +tensorfold:request_prefill_seconds_count 2 +# HELP tensorfold:process_resident_bytes Current resident set (VmRSS); device memory is not in it, so it is not a physical footprint (Linux). +# TYPE tensorfold:process_resident_bytes gauge +tensorfold:process_resident_bytes 84412530688 +# HELP tensorfold:process_resident_anon_bytes Current resident anonymous memory (RssAnon): heap, stacks and private maps (Linux). +# TYPE tensorfold:process_resident_anon_bytes gauge +tensorfold:process_resident_anon_bytes 357167104 +# HELP tensorfold:process_resident_file_bytes Current resident file-backed memory (RssFile): the binary, libraries and mapped files (Linux). +# TYPE tensorfold:process_resident_file_bytes gauge +tensorfold:process_resident_file_bytes 83921100800 +# HELP tensorfold:process_resident_shmem_bytes Current resident shared memory (RssShmem): System V shared memory, tmpfs maps and shared anonymous maps (Linux). +# TYPE tensorfold:process_resident_shmem_bytes gauge +tensorfold:process_resident_shmem_bytes 134262784 +# HELP tensorfold:process_resident_peak_bytes Kernel lifetime peak resident set (VmHWM); never reset by health (Linux). +# TYPE tensorfold:process_resident_peak_bytes gauge +tensorfold:process_resident_peak_bytes 84412530688 +# HELP tensorfold:device_memory_bytes Device memory the engine holds now: weights, caches and live streams; only where the backend counts it (CUDA). +# TYPE tensorfold:device_memory_bytes gauge +tensorfold:device_memory_bytes 83064265364 +# HELP tensorfold:device_memory_peak_bytes The most device memory the engine has held since start or the last /health?reset_peak=1. +# TYPE tensorfold:device_memory_peak_bytes gauge +tensorfold:device_memory_peak_bytes 83103782820 +# HELP tensorfold:pinned_memory_bytes Pinned host memory the engine holds now: staging buffers and windows; only where the backend counts it (CUDA). +# TYPE tensorfold:pinned_memory_bytes gauge +tensorfold:pinned_memory_bytes 0 +# HELP tensorfold:num_requests_running Requests in prefill or decode. A mirror of tensorfold:requests_running. +# TYPE tensorfold:num_requests_running gauge +tensorfold:num_requests_running 0 +# HELP tensorfold:num_requests_waiting Requests queued or held until a lane is free. A mirror of tensorfold:requests_waiting. +# TYPE tensorfold:num_requests_waiting gauge +tensorfold:num_requests_waiting 0 +# HELP tensorfold:kv_cache_usage_perc A stream's cache occupancy under vLLM's name; same streams and ratios as tensorfold:kv_cache_usage_ratio. +# TYPE tensorfold:kv_cache_usage_perc gauge +tensorfold:kv_cache_usage_perc{stream="0"} 0 +# HELP tensorfold:spec_decode_num_draft_tokens_total Draft tokens verified on finished requests, this server's single draft counter. +# TYPE tensorfold:spec_decode_num_draft_tokens_total counter +tensorfold:spec_decode_num_draft_tokens_total 0 +# HELP tensorfold:spec_decode_num_accepted_tokens_total Draft tokens kept on finished requests. +# TYPE tensorfold:spec_decode_num_accepted_tokens_total counter +tensorfold:spec_decode_num_accepted_tokens_total 0 +# HELP tensorfold:e2e_request_latency_seconds Seconds from arrival to the reply leaving, under vLLM's name. +# TYPE tensorfold:e2e_request_latency_seconds histogram +tensorfold:e2e_request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="1"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="10"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="30"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="60"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="120"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="300"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:e2e_request_latency_seconds_sum 34.56361 +tensorfold:e2e_request_latency_seconds_count 2 +# HELP tensorfold:request_decode_time_seconds Seconds a finished request spent decoding, under vLLM's name. +# TYPE tensorfold:request_decode_time_seconds histogram +tensorfold:request_decode_time_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="10"} 2 +tensorfold:request_decode_time_seconds_bucket{le="30"} 2 +tensorfold:request_decode_time_seconds_bucket{le="60"} 2 +tensorfold:request_decode_time_seconds_bucket{le="120"} 2 +tensorfold:request_decode_time_seconds_bucket{le="300"} 2 +tensorfold:request_decode_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_time_seconds_sum 0.000366 +tensorfold:request_decode_time_seconds_count 2 +# HELP tensorfold:request_prefill_time_seconds Seconds a finished request's prompt pass took, under vLLM's name. +# TYPE tensorfold:request_prefill_time_seconds histogram +tensorfold:request_prefill_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="1"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="60"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="120"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_time_seconds_sum 34.561917 +tensorfold:request_prefill_time_seconds_count 2 +# HELP tensorfold:client_disconnections_total Requests a client left before the reply left the server. +# TYPE tensorfold:client_disconnections_total counter +tensorfold:client_disconnections_total 0 +# HELP tensorfold:preemptions_total Requests that had to give a lane up to a later one. +# TYPE tensorfold:preemptions_total counter +tensorfold:preemptions_total 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step1024-mapped-r1-samples.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step1024-mapped-r1-samples.jsonl new file mode 100644 index 0000000000..d9306017f6 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step1024-mapped-r1-samples.jsonl @@ -0,0 +1,41 @@ +{"t_s": 0.0, "VmRSS_bytes": 73318400, "VmHWM_bytes": 73318400, "Pss_bytes": 71202816, "vram_used_bytes": 187682816, "vram_total_bytes": 4294967296, "gtt_used_bytes": 31657984, "gtt_total_bytes": 193273528320} +{"t_s": 1.03, "VmRSS_bytes": 10182995968, "VmHWM_bytes": 10182995968, "Pss_bytes": 10201263104, "vram_used_bytes": 188809216, "vram_total_bytes": 4294967296, "gtt_used_bytes": 6847524864, "gtt_total_bytes": 193273528320} +{"t_s": 2.11, "VmRSS_bytes": 18219843584, "VmHWM_bytes": 18219843584, "Pss_bytes": 18333924352, "vram_used_bytes": 189362176, "vram_total_bytes": 4294967296, "gtt_used_bytes": 15062069248, "gtt_total_bytes": 193273528320} +{"t_s": 3.2, "VmRSS_bytes": 26447003648, "VmHWM_bytes": 26447003648, "Pss_bytes": 26444758016, "vram_used_bytes": 189943808, "vram_total_bytes": 4294967296, "gtt_used_bytes": 24228720640, "gtt_total_bytes": 193273528320} +{"t_s": 4.33, "VmRSS_bytes": 34601091072, "VmHWM_bytes": 34601091072, "Pss_bytes": 34598845440, "vram_used_bytes": 190595072, "vram_total_bytes": 4294967296, "gtt_used_bytes": 33124839424, "gtt_total_bytes": 193273528320} +{"t_s": 5.48, "VmRSS_bytes": 44236226560, "VmHWM_bytes": 44236226560, "Pss_bytes": 44233980928, "vram_used_bytes": 191152128, "vram_total_bytes": 4294967296, "gtt_used_bytes": 41345675264, "gtt_total_bytes": 193273528320} +{"t_s": 6.65, "VmRSS_bytes": 52443164672, "VmHWM_bytes": 52443164672, "Pss_bytes": 52440919040, "vram_used_bytes": 191815680, "vram_total_bytes": 4294967296, "gtt_used_bytes": 51200192512, "gtt_total_bytes": 193273528320} +{"t_s": 7.85, "VmRSS_bytes": 62176198656, "VmHWM_bytes": 62176198656, "Pss_bytes": 62173953024, "vram_used_bytes": 192495616, "vram_total_bytes": 4294967296, "gtt_used_bytes": 61058904064, "gtt_total_bytes": 193273528320} +{"t_s": 9.07, "VmRSS_bytes": 71906643968, "VmHWM_bytes": 71906643968, "Pss_bytes": 71904398336, "vram_used_bytes": 193142784, "vram_total_bytes": 4294967296, "gtt_used_bytes": 70913421312, "gtt_total_bytes": 193273528320} +{"t_s": 10.3, "VmRSS_bytes": 82502832128, "VmHWM_bytes": 82502832128, "Pss_bytes": 82500586496, "vram_used_bytes": 194908160, "vram_total_bytes": 4294967296, "gtt_used_bytes": 80778424320, "gtt_total_bytes": 193273528320} +{"t_s": 11.56, "VmRSS_bytes": 80900132864, "VmHWM_bytes": 82505523200, "Pss_bytes": 80897824768, "vram_used_bytes": 195055616, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84028940288, "gtt_total_bytes": 193273528320} +{"t_s": 12.81, "VmRSS_bytes": 80904785920, "VmHWM_bytes": 82505523200, "Pss_bytes": 80902481920, "vram_used_bytes": 195059712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84030046208, "gtt_total_bytes": 193273528320} +{"t_s": 14.04, "VmRSS_bytes": 80907042816, "VmHWM_bytes": 82505523200, "Pss_bytes": 80904734720, "vram_used_bytes": 195063808, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84030414848, "gtt_total_bytes": 193273528320} +{"t_s": 15.31, "VmRSS_bytes": 81663737856, "VmHWM_bytes": 82505523200, "Pss_bytes": 81661425664, "vram_used_bytes": 195059712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 16.58, "VmRSS_bytes": 82143023104, "VmHWM_bytes": 82505523200, "Pss_bytes": 82140710912, "vram_used_bytes": 195059712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 17.84, "VmRSS_bytes": 82143023104, "VmHWM_bytes": 82505523200, "Pss_bytes": 82557106176, "vram_used_bytes": 195059712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 19.11, "VmRSS_bytes": 82606706688, "VmHWM_bytes": 82606706688, "Pss_bytes": 82604394496, "vram_used_bytes": 195059712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 20.39, "VmRSS_bytes": 82979971072, "VmHWM_bytes": 82979971072, "Pss_bytes": 82977658880, "vram_used_bytes": 195059712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 21.66, "VmRSS_bytes": 82979971072, "VmHWM_bytes": 82979971072, "Pss_bytes": 82977658880, "vram_used_bytes": 195059712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 22.93, "VmRSS_bytes": 83182002176, "VmHWM_bytes": 83182002176, "Pss_bytes": 83179689984, "vram_used_bytes": 195059712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 24.2, "VmRSS_bytes": 83182002176, "VmHWM_bytes": 83182002176, "Pss_bytes": 83179689984, "vram_used_bytes": 195059712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 25.48, "VmRSS_bytes": 83493367808, "VmHWM_bytes": 83493367808, "Pss_bytes": 83491055616, "vram_used_bytes": 195059712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 26.76, "VmRSS_bytes": 83598516224, "VmHWM_bytes": 83598516224, "Pss_bytes": 83596204032, "vram_used_bytes": 195059712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 28.04, "VmRSS_bytes": 83598516224, "VmHWM_bytes": 83598516224, "Pss_bytes": 83596204032, "vram_used_bytes": 195059712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 29.33, "VmRSS_bytes": 83686760448, "VmHWM_bytes": 83686760448, "Pss_bytes": 83684448256, "vram_used_bytes": 195059712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 30.62, "VmRSS_bytes": 83686760448, "VmHWM_bytes": 83686760448, "Pss_bytes": 83684448256, "vram_used_bytes": 195059712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 31.91, "VmRSS_bytes": 83831848960, "VmHWM_bytes": 83831848960, "Pss_bytes": 83829536768, "vram_used_bytes": 195059712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 33.2, "VmRSS_bytes": 83831848960, "VmHWM_bytes": 83831848960, "Pss_bytes": 83943163904, "vram_used_bytes": 195059712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 34.48, "VmRSS_bytes": 83945467904, "VmHWM_bytes": 83945467904, "Pss_bytes": 83943155712, "vram_used_bytes": 195059712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 35.77, "VmRSS_bytes": 84027060224, "VmHWM_bytes": 84027060224, "Pss_bytes": 84024748032, "vram_used_bytes": 195059712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 37.06, "VmRSS_bytes": 84027060224, "VmHWM_bytes": 84027060224, "Pss_bytes": 84024748032, "vram_used_bytes": 195059712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 38.35, "VmRSS_bytes": 84116152320, "VmHWM_bytes": 84116152320, "Pss_bytes": 84113840128, "vram_used_bytes": 195059712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 39.63, "VmRSS_bytes": 84116275200, "VmHWM_bytes": 84116275200, "Pss_bytes": 84113963008, "vram_used_bytes": 195059712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 40.92, "VmRSS_bytes": 84195360768, "VmHWM_bytes": 84195360768, "Pss_bytes": 84193048576, "vram_used_bytes": 195059712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 42.21, "VmRSS_bytes": 84195360768, "VmHWM_bytes": 84195360768, "Pss_bytes": 84269361152, "vram_used_bytes": 195059712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 43.5, "VmRSS_bytes": 84271673344, "VmHWM_bytes": 84271673344, "Pss_bytes": 84269361152, "vram_used_bytes": 195059712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 44.78, "VmRSS_bytes": 84352933888, "VmHWM_bytes": 84352933888, "Pss_bytes": 84350621696, "vram_used_bytes": 195059712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 46.07, "VmRSS_bytes": 84352933888, "VmHWM_bytes": 84352933888, "Pss_bytes": 84350621696, "vram_used_bytes": 195059712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 47.37, "VmRSS_bytes": 84413345792, "VmHWM_bytes": 84413345792, "Pss_bytes": 84411033600, "vram_used_bytes": 195059712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 48.65, "VmRSS_bytes": 84413345792, "VmHWM_bytes": 84413345792, "Pss_bytes": 84411033600, "vram_used_bytes": 195059712, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84030414848, "gtt_total_bytes": 193273528320} +{"t_s": 49.77, "VmRSS_bytes": 45400215552, "VmHWM_bytes": 84412014592, "Pss_bytes": 40475766784, "vram_used_bytes": 194908160, "vram_total_bytes": 4294967296, "gtt_used_bytes": 204288000, "gtt_total_bytes": 193273528320} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step1024-mapped-r2-memory-endpoint.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step1024-mapped-r2-memory-endpoint.json new file mode 100644 index 0000000000..d4ff0b5aeb --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step1024-mapped-r2-memory-endpoint.json @@ -0,0 +1 @@ +{"schema_version": 1, "context_window": 20480, "context_fitted": false, "device": {"active_bytes": 83064265364, "cache_bytes": 0, "peak_bytes": 83103782820, "peak_scope": "since_start_or_health_reset"}} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step1024-mapped-r2-metrics.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step1024-mapped-r2-metrics.txt new file mode 100644 index 0000000000..fa14a58985 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step1024-mapped-r2-metrics.txt @@ -0,0 +1,220 @@ +# HELP tensorfold:requests_running Requests in prefill or decode. +# TYPE tensorfold:requests_running gauge +tensorfold:requests_running 0 +# HELP tensorfold:requests_waiting Requests queued or held until a lane is free. +# TYPE tensorfold:requests_waiting gauge +tensorfold:requests_waiting 0 +# HELP tensorfold:generation_tokens_running Generated tokens held by live streams. +# TYPE tensorfold:generation_tokens_running gauge +tensorfold:generation_tokens_running 0 +# HELP tensorfold:prompt_tokens_total Prompt tokens of finished requests. +# TYPE tensorfold:prompt_tokens_total counter +tensorfold:prompt_tokens_total 16640 +# HELP tensorfold:generation_tokens_total Generated tokens of finished requests. +# TYPE tensorfold:generation_tokens_total counter +tensorfold:generation_tokens_total 2 +# HELP tensorfold:kv_cache_usage_ratio Tokens in a stream cache divided by that stream's context window. +# TYPE tensorfold:kv_cache_usage_ratio gauge +tensorfold:kv_cache_usage_ratio{pool="0"} 0 +# HELP tensorfold:mtp_drafted_total Draft tokens verified on finished requests. +# TYPE tensorfold:mtp_drafted_total counter +tensorfold:mtp_drafted_total 0 +# HELP tensorfold:mtp_accepted_total Draft tokens kept on finished requests. +# TYPE tensorfold:mtp_accepted_total counter +tensorfold:mtp_accepted_total 0 +# HELP tensorfold:request_latency_seconds Seconds from arrival to the reply leaving. +# TYPE tensorfold:request_latency_seconds histogram +tensorfold:request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:request_latency_seconds_bucket{le="0.5"} 1 +tensorfold:request_latency_seconds_bucket{le="1"} 1 +tensorfold:request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:request_latency_seconds_bucket{le="5"} 1 +tensorfold:request_latency_seconds_bucket{le="10"} 1 +tensorfold:request_latency_seconds_bucket{le="30"} 1 +tensorfold:request_latency_seconds_bucket{le="60"} 2 +tensorfold:request_latency_seconds_bucket{le="120"} 2 +tensorfold:request_latency_seconds_bucket{le="300"} 2 +tensorfold:request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:request_latency_seconds_sum 34.565297 +tensorfold:request_latency_seconds_count 2 +# HELP tensorfold:time_to_first_token_seconds Seconds from arrival to the first generated token. +# TYPE tensorfold:time_to_first_token_seconds histogram +tensorfold:time_to_first_token_seconds_bucket{le="0.01"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.05"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.25"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="1"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="2.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="10"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="30"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="60"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="120"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="300"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="+Inf"} 2 +tensorfold:time_to_first_token_seconds_sum 34.564944 +tensorfold:time_to_first_token_seconds_count 2 +# HELP tensorfold:request_decode_seconds Seconds a finished request spent decoding. Its sum over generation_tokens_total is the decode rate. +# TYPE tensorfold:request_decode_seconds histogram +tensorfold:request_decode_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_seconds_bucket{le="1"} 2 +tensorfold:request_decode_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_seconds_bucket{le="5"} 2 +tensorfold:request_decode_seconds_bucket{le="10"} 2 +tensorfold:request_decode_seconds_bucket{le="30"} 2 +tensorfold:request_decode_seconds_bucket{le="60"} 2 +tensorfold:request_decode_seconds_bucket{le="120"} 2 +tensorfold:request_decode_seconds_bucket{le="300"} 2 +tensorfold:request_decode_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_seconds_sum 0.000353 +tensorfold:request_decode_seconds_count 2 +# HELP tensorfold:request_time_per_output_token_seconds Seconds from the first generated token to the last, divided by the tokens less one. +# TYPE tensorfold:request_time_per_output_token_seconds histogram +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.005"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.01"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.015"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.02"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.03"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.04"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.05"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.15"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.2"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.3"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.5"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="+Inf"} 0 +tensorfold:request_time_per_output_token_seconds_sum 0 +tensorfold:request_time_per_output_token_seconds_count 0 +# HELP tensorfold:decode_rounds_total Decode rounds used by finished requests. +# TYPE tensorfold:decode_rounds_total counter +tensorfold:decode_rounds_total 0 +# HELP tensorfold:request_prefill_seconds Seconds a finished request's prompt pass took. +# TYPE tensorfold:request_prefill_seconds histogram +tensorfold:request_prefill_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="1"} 1 +tensorfold:request_prefill_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_seconds_bucket{le="60"} 2 +tensorfold:request_prefill_seconds_bucket{le="120"} 2 +tensorfold:request_prefill_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_seconds_sum 34.563635 +tensorfold:request_prefill_seconds_count 2 +# HELP tensorfold:process_resident_bytes Current resident set (VmRSS); device memory is not in it, so it is not a physical footprint (Linux). +# TYPE tensorfold:process_resident_bytes gauge +tensorfold:process_resident_bytes 84430409728 +# HELP tensorfold:process_resident_anon_bytes Current resident anonymous memory (RssAnon): heap, stacks and private maps (Linux). +# TYPE tensorfold:process_resident_anon_bytes gauge +tensorfold:process_resident_anon_bytes 353746944 +# HELP tensorfold:process_resident_file_bytes Current resident file-backed memory (RssFile): the binary, libraries and mapped files (Linux). +# TYPE tensorfold:process_resident_file_bytes gauge +tensorfold:process_resident_file_bytes 83942400000 +# HELP tensorfold:process_resident_shmem_bytes Current resident shared memory (RssShmem): System V shared memory, tmpfs maps and shared anonymous maps (Linux). +# TYPE tensorfold:process_resident_shmem_bytes gauge +tensorfold:process_resident_shmem_bytes 134262784 +# HELP tensorfold:process_resident_peak_bytes Kernel lifetime peak resident set (VmHWM); never reset by health (Linux). +# TYPE tensorfold:process_resident_peak_bytes gauge +tensorfold:process_resident_peak_bytes 84430409728 +# HELP tensorfold:device_memory_bytes Device memory the engine holds now: weights, caches and live streams; only where the backend counts it (CUDA). +# TYPE tensorfold:device_memory_bytes gauge +tensorfold:device_memory_bytes 83064265364 +# HELP tensorfold:device_memory_peak_bytes The most device memory the engine has held since start or the last /health?reset_peak=1. +# TYPE tensorfold:device_memory_peak_bytes gauge +tensorfold:device_memory_peak_bytes 83103782820 +# HELP tensorfold:pinned_memory_bytes Pinned host memory the engine holds now: staging buffers and windows; only where the backend counts it (CUDA). +# TYPE tensorfold:pinned_memory_bytes gauge +tensorfold:pinned_memory_bytes 0 +# HELP tensorfold:num_requests_running Requests in prefill or decode. A mirror of tensorfold:requests_running. +# TYPE tensorfold:num_requests_running gauge +tensorfold:num_requests_running 0 +# HELP tensorfold:num_requests_waiting Requests queued or held until a lane is free. A mirror of tensorfold:requests_waiting. +# TYPE tensorfold:num_requests_waiting gauge +tensorfold:num_requests_waiting 0 +# HELP tensorfold:kv_cache_usage_perc A stream's cache occupancy under vLLM's name; same streams and ratios as tensorfold:kv_cache_usage_ratio. +# TYPE tensorfold:kv_cache_usage_perc gauge +tensorfold:kv_cache_usage_perc{stream="0"} 0 +# HELP tensorfold:spec_decode_num_draft_tokens_total Draft tokens verified on finished requests, this server's single draft counter. +# TYPE tensorfold:spec_decode_num_draft_tokens_total counter +tensorfold:spec_decode_num_draft_tokens_total 0 +# HELP tensorfold:spec_decode_num_accepted_tokens_total Draft tokens kept on finished requests. +# TYPE tensorfold:spec_decode_num_accepted_tokens_total counter +tensorfold:spec_decode_num_accepted_tokens_total 0 +# HELP tensorfold:e2e_request_latency_seconds Seconds from arrival to the reply leaving, under vLLM's name. +# TYPE tensorfold:e2e_request_latency_seconds histogram +tensorfold:e2e_request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="1"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="10"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="30"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="60"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="120"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="300"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:e2e_request_latency_seconds_sum 34.565297 +tensorfold:e2e_request_latency_seconds_count 2 +# HELP tensorfold:request_decode_time_seconds Seconds a finished request spent decoding, under vLLM's name. +# TYPE tensorfold:request_decode_time_seconds histogram +tensorfold:request_decode_time_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="10"} 2 +tensorfold:request_decode_time_seconds_bucket{le="30"} 2 +tensorfold:request_decode_time_seconds_bucket{le="60"} 2 +tensorfold:request_decode_time_seconds_bucket{le="120"} 2 +tensorfold:request_decode_time_seconds_bucket{le="300"} 2 +tensorfold:request_decode_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_time_seconds_sum 0.000353 +tensorfold:request_decode_time_seconds_count 2 +# HELP tensorfold:request_prefill_time_seconds Seconds a finished request's prompt pass took, under vLLM's name. +# TYPE tensorfold:request_prefill_time_seconds histogram +tensorfold:request_prefill_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="1"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="60"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="120"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_time_seconds_sum 34.563635 +tensorfold:request_prefill_time_seconds_count 2 +# HELP tensorfold:client_disconnections_total Requests a client left before the reply left the server. +# TYPE tensorfold:client_disconnections_total counter +tensorfold:client_disconnections_total 0 +# HELP tensorfold:preemptions_total Requests that had to give a lane up to a later one. +# TYPE tensorfold:preemptions_total counter +tensorfold:preemptions_total 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step1024-mapped-r2-samples.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step1024-mapped-r2-samples.jsonl new file mode 100644 index 0000000000..107380cb3d --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step1024-mapped-r2-samples.jsonl @@ -0,0 +1,41 @@ +{"t_s": 0.0, "VmRSS_bytes": 73453568, "VmHWM_bytes": 73453568, "Pss_bytes": 71242752, "vram_used_bytes": 187682816, "vram_total_bytes": 4294967296, "gtt_used_bytes": 31657984, "gtt_total_bytes": 193273528320} +{"t_s": 1.04, "VmRSS_bytes": 9957421056, "VmHWM_bytes": 9957421056, "Pss_bytes": 9998190592, "vram_used_bytes": 188801024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 6847524864, "gtt_total_bytes": 193273528320} +{"t_s": 2.11, "VmRSS_bytes": 18229874688, "VmHWM_bytes": 18229874688, "Pss_bytes": 18332116992, "vram_used_bytes": 189353984, "vram_total_bytes": 4294967296, "gtt_used_bytes": 15062069248, "gtt_total_bytes": 193273528320} +{"t_s": 3.21, "VmRSS_bytes": 26445500416, "VmHWM_bytes": 26445500416, "Pss_bytes": 26442950656, "vram_used_bytes": 189935616, "vram_total_bytes": 4294967296, "gtt_used_bytes": 24228720640, "gtt_total_bytes": 193273528320} +{"t_s": 4.34, "VmRSS_bytes": 34599587840, "VmHWM_bytes": 34599587840, "Pss_bytes": 34597038080, "vram_used_bytes": 190586880, "vram_total_bytes": 4294967296, "gtt_used_bytes": 33124839424, "gtt_total_bytes": 193273528320} +{"t_s": 5.48, "VmRSS_bytes": 44234723328, "VmHWM_bytes": 44234723328, "Pss_bytes": 44236497920, "vram_used_bytes": 191148032, "vram_total_bytes": 4294967296, "gtt_used_bytes": 41345675264, "gtt_total_bytes": 193273528320} +{"t_s": 6.66, "VmRSS_bytes": 52441661440, "VmHWM_bytes": 52441661440, "Pss_bytes": 52439111680, "vram_used_bytes": 191815680, "vram_total_bytes": 4294967296, "gtt_used_bytes": 51200192512, "gtt_total_bytes": 193273528320} +{"t_s": 7.86, "VmRSS_bytes": 62172008448, "VmHWM_bytes": 62172008448, "Pss_bytes": 62171097088, "vram_used_bytes": 192503808, "vram_total_bytes": 4294967296, "gtt_used_bytes": 61058904064, "gtt_total_bytes": 193273528320} +{"t_s": 9.07, "VmRSS_bytes": 71904866304, "VmHWM_bytes": 71904866304, "Pss_bytes": 71902316544, "vram_used_bytes": 193191936, "vram_total_bytes": 4294967296, "gtt_used_bytes": 70913421312, "gtt_total_bytes": 193273528320} +{"t_s": 10.3, "VmRSS_bytes": 82501054464, "VmHWM_bytes": 82501054464, "Pss_bytes": 82498504704, "vram_used_bytes": 195198976, "vram_total_bytes": 4294967296, "gtt_used_bytes": 80885379072, "gtt_total_bytes": 193273528320} +{"t_s": 11.56, "VmRSS_bytes": 80898490368, "VmHWM_bytes": 82503499776, "Pss_bytes": 80895881216, "vram_used_bytes": 195321856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84028940288, "gtt_total_bytes": 193273528320} +{"t_s": 12.82, "VmRSS_bytes": 80903139328, "VmHWM_bytes": 82503499776, "Pss_bytes": 80900534272, "vram_used_bytes": 195325952, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84030046208, "gtt_total_bytes": 193273528320} +{"t_s": 14.04, "VmRSS_bytes": 80905531392, "VmHWM_bytes": 82503499776, "Pss_bytes": 80902922240, "vram_used_bytes": 195325952, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84030414848, "gtt_total_bytes": 193273528320} +{"t_s": 15.3, "VmRSS_bytes": 81669828608, "VmHWM_bytes": 82503499776, "Pss_bytes": 81667211264, "vram_used_bytes": 195321856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 16.57, "VmRSS_bytes": 82152148992, "VmHWM_bytes": 82503499776, "Pss_bytes": 82149535744, "vram_used_bytes": 195321856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 17.82, "VmRSS_bytes": 82152148992, "VmHWM_bytes": 82503499776, "Pss_bytes": 82567688192, "vram_used_bytes": 195321856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 19.1, "VmRSS_bytes": 82615021568, "VmHWM_bytes": 82615021568, "Pss_bytes": 82612408320, "vram_used_bytes": 195321856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 20.37, "VmRSS_bytes": 82990112768, "VmHWM_bytes": 82990112768, "Pss_bytes": 82987499520, "vram_used_bytes": 195321856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 21.65, "VmRSS_bytes": 82990112768, "VmHWM_bytes": 82990112768, "Pss_bytes": 82987499520, "vram_used_bytes": 195321856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 22.92, "VmRSS_bytes": 83192909824, "VmHWM_bytes": 83192909824, "Pss_bytes": 83190296576, "vram_used_bytes": 195321856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 24.19, "VmRSS_bytes": 83192909824, "VmHWM_bytes": 83192909824, "Pss_bytes": 83190296576, "vram_used_bytes": 195321856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 25.46, "VmRSS_bytes": 83505373184, "VmHWM_bytes": 83505373184, "Pss_bytes": 83502758912, "vram_used_bytes": 195321856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 26.74, "VmRSS_bytes": 83610722304, "VmHWM_bytes": 83610722304, "Pss_bytes": 83608108032, "vram_used_bytes": 195321856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 28.02, "VmRSS_bytes": 83610722304, "VmHWM_bytes": 83610722304, "Pss_bytes": 83608110080, "vram_used_bytes": 195321856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 29.3, "VmRSS_bytes": 83699310592, "VmHWM_bytes": 83699310592, "Pss_bytes": 83696698368, "vram_used_bytes": 195321856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 30.58, "VmRSS_bytes": 83699310592, "VmHWM_bytes": 83699310592, "Pss_bytes": 83696698368, "vram_used_bytes": 195321856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 31.87, "VmRSS_bytes": 83845459968, "VmHWM_bytes": 83845459968, "Pss_bytes": 83842847744, "vram_used_bytes": 195321856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 33.15, "VmRSS_bytes": 83847008256, "VmHWM_bytes": 83847008256, "Pss_bytes": 83958318080, "vram_used_bytes": 195321856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 34.43, "VmRSS_bytes": 83960930304, "VmHWM_bytes": 83960930304, "Pss_bytes": 83958317056, "vram_used_bytes": 195321856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 35.72, "VmRSS_bytes": 84042846208, "VmHWM_bytes": 84042846208, "Pss_bytes": 84040226816, "vram_used_bytes": 195321856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 37.01, "VmRSS_bytes": 84042846208, "VmHWM_bytes": 84042846208, "Pss_bytes": 84040232960, "vram_used_bytes": 195321856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 38.31, "VmRSS_bytes": 84132515840, "VmHWM_bytes": 84132515840, "Pss_bytes": 84129902592, "vram_used_bytes": 195321856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 39.6, "VmRSS_bytes": 84132515840, "VmHWM_bytes": 84132515840, "Pss_bytes": 84129902592, "vram_used_bytes": 195321856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 40.9, "VmRSS_bytes": 84212129792, "VmHWM_bytes": 84212129792, "Pss_bytes": 84209516544, "vram_used_bytes": 195321856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 42.18, "VmRSS_bytes": 84212129792, "VmHWM_bytes": 84212129792, "Pss_bytes": 84286509056, "vram_used_bytes": 195321856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 43.46, "VmRSS_bytes": 84289122304, "VmHWM_bytes": 84289122304, "Pss_bytes": 84286509056, "vram_used_bytes": 195321856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 44.74, "VmRSS_bytes": 84370694144, "VmHWM_bytes": 84370694144, "Pss_bytes": 84368080896, "vram_used_bytes": 195321856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 46.04, "VmRSS_bytes": 84370694144, "VmHWM_bytes": 84370694144, "Pss_bytes": 84368081920, "vram_used_bytes": 195321856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 47.35, "VmRSS_bytes": 84431228928, "VmHWM_bytes": 84431228928, "Pss_bytes": 84428617728, "vram_used_bytes": 195321856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 48.64, "VmRSS_bytes": 84431228928, "VmHWM_bytes": 84431228928, "Pss_bytes": 84428617728, "vram_used_bytes": 195321856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84030414848, "gtt_total_bytes": 193273528320} +{"t_s": 49.77, "VmRSS_bytes": 45812277248, "VmHWM_bytes": 84429209600, "Pss_bytes": 40472399872, "vram_used_bytes": 195186688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 204288000, "gtt_total_bytes": 193273528320} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step1024-r1-memory-endpoint.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step1024-r1-memory-endpoint.json new file mode 100644 index 0000000000..d4ff0b5aeb --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step1024-r1-memory-endpoint.json @@ -0,0 +1 @@ +{"schema_version": 1, "context_window": 20480, "context_fitted": false, "device": {"active_bytes": 83064265364, "cache_bytes": 0, "peak_bytes": 83103782820, "peak_scope": "since_start_or_health_reset"}} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step1024-r1-metrics.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step1024-r1-metrics.txt new file mode 100644 index 0000000000..3d1aa91f8f --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step1024-r1-metrics.txt @@ -0,0 +1,220 @@ +# HELP tensorfold:requests_running Requests in prefill or decode. +# TYPE tensorfold:requests_running gauge +tensorfold:requests_running 0 +# HELP tensorfold:requests_waiting Requests queued or held until a lane is free. +# TYPE tensorfold:requests_waiting gauge +tensorfold:requests_waiting 0 +# HELP tensorfold:generation_tokens_running Generated tokens held by live streams. +# TYPE tensorfold:generation_tokens_running gauge +tensorfold:generation_tokens_running 0 +# HELP tensorfold:prompt_tokens_total Prompt tokens of finished requests. +# TYPE tensorfold:prompt_tokens_total counter +tensorfold:prompt_tokens_total 16640 +# HELP tensorfold:generation_tokens_total Generated tokens of finished requests. +# TYPE tensorfold:generation_tokens_total counter +tensorfold:generation_tokens_total 2 +# HELP tensorfold:kv_cache_usage_ratio Tokens in a stream cache divided by that stream's context window. +# TYPE tensorfold:kv_cache_usage_ratio gauge +tensorfold:kv_cache_usage_ratio{pool="0"} 0 +# HELP tensorfold:mtp_drafted_total Draft tokens verified on finished requests. +# TYPE tensorfold:mtp_drafted_total counter +tensorfold:mtp_drafted_total 0 +# HELP tensorfold:mtp_accepted_total Draft tokens kept on finished requests. +# TYPE tensorfold:mtp_accepted_total counter +tensorfold:mtp_accepted_total 0 +# HELP tensorfold:request_latency_seconds Seconds from arrival to the reply leaving. +# TYPE tensorfold:request_latency_seconds histogram +tensorfold:request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:request_latency_seconds_bucket{le="0.5"} 1 +tensorfold:request_latency_seconds_bucket{le="1"} 1 +tensorfold:request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:request_latency_seconds_bucket{le="5"} 1 +tensorfold:request_latency_seconds_bucket{le="10"} 1 +tensorfold:request_latency_seconds_bucket{le="30"} 1 +tensorfold:request_latency_seconds_bucket{le="60"} 2 +tensorfold:request_latency_seconds_bucket{le="120"} 2 +tensorfold:request_latency_seconds_bucket{le="300"} 2 +tensorfold:request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:request_latency_seconds_sum 34.326942 +tensorfold:request_latency_seconds_count 2 +# HELP tensorfold:time_to_first_token_seconds Seconds from arrival to the first generated token. +# TYPE tensorfold:time_to_first_token_seconds histogram +tensorfold:time_to_first_token_seconds_bucket{le="0.01"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.05"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.25"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="1"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="2.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="10"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="30"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="60"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="120"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="300"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="+Inf"} 2 +tensorfold:time_to_first_token_seconds_sum 34.326553 +tensorfold:time_to_first_token_seconds_count 2 +# HELP tensorfold:request_decode_seconds Seconds a finished request spent decoding. Its sum over generation_tokens_total is the decode rate. +# TYPE tensorfold:request_decode_seconds histogram +tensorfold:request_decode_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_seconds_bucket{le="1"} 2 +tensorfold:request_decode_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_seconds_bucket{le="5"} 2 +tensorfold:request_decode_seconds_bucket{le="10"} 2 +tensorfold:request_decode_seconds_bucket{le="30"} 2 +tensorfold:request_decode_seconds_bucket{le="60"} 2 +tensorfold:request_decode_seconds_bucket{le="120"} 2 +tensorfold:request_decode_seconds_bucket{le="300"} 2 +tensorfold:request_decode_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_seconds_sum 0.000389 +tensorfold:request_decode_seconds_count 2 +# HELP tensorfold:request_time_per_output_token_seconds Seconds from the first generated token to the last, divided by the tokens less one. +# TYPE tensorfold:request_time_per_output_token_seconds histogram +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.005"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.01"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.015"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.02"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.03"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.04"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.05"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.15"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.2"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.3"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.5"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="+Inf"} 0 +tensorfold:request_time_per_output_token_seconds_sum 0 +tensorfold:request_time_per_output_token_seconds_count 0 +# HELP tensorfold:decode_rounds_total Decode rounds used by finished requests. +# TYPE tensorfold:decode_rounds_total counter +tensorfold:decode_rounds_total 0 +# HELP tensorfold:request_prefill_seconds Seconds a finished request's prompt pass took. +# TYPE tensorfold:request_prefill_seconds histogram +tensorfold:request_prefill_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="1"} 1 +tensorfold:request_prefill_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_seconds_bucket{le="60"} 2 +tensorfold:request_prefill_seconds_bucket{le="120"} 2 +tensorfold:request_prefill_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_seconds_sum 34.323486 +tensorfold:request_prefill_seconds_count 2 +# HELP tensorfold:process_resident_bytes Current resident set (VmRSS); device memory is not in it, so it is not a physical footprint (Linux). +# TYPE tensorfold:process_resident_bytes gauge +tensorfold:process_resident_bytes 107683528704 +# HELP tensorfold:process_resident_anon_bytes Current resident anonymous memory (RssAnon): heap, stacks and private maps (Linux). +# TYPE tensorfold:process_resident_anon_bytes gauge +tensorfold:process_resident_anon_bytes 32365834240 +# HELP tensorfold:process_resident_file_bytes Current resident file-backed memory (RssFile): the binary, libraries and mapped files (Linux). +# TYPE tensorfold:process_resident_file_bytes gauge +tensorfold:process_resident_file_bytes 75183431680 +# HELP tensorfold:process_resident_shmem_bytes Current resident shared memory (RssShmem): System V shared memory, tmpfs maps and shared anonymous maps (Linux). +# TYPE tensorfold:process_resident_shmem_bytes gauge +tensorfold:process_resident_shmem_bytes 134262784 +# HELP tensorfold:process_resident_peak_bytes Kernel lifetime peak resident set (VmHWM); never reset by health (Linux). +# TYPE tensorfold:process_resident_peak_bytes gauge +tensorfold:process_resident_peak_bytes 110645571584 +# HELP tensorfold:device_memory_bytes Device memory the engine holds now: weights, caches and live streams; only where the backend counts it (CUDA). +# TYPE tensorfold:device_memory_bytes gauge +tensorfold:device_memory_bytes 83064265364 +# HELP tensorfold:device_memory_peak_bytes The most device memory the engine has held since start or the last /health?reset_peak=1. +# TYPE tensorfold:device_memory_peak_bytes gauge +tensorfold:device_memory_peak_bytes 83103782820 +# HELP tensorfold:pinned_memory_bytes Pinned host memory the engine holds now: staging buffers and windows; only where the backend counts it (CUDA). +# TYPE tensorfold:pinned_memory_bytes gauge +tensorfold:pinned_memory_bytes 0 +# HELP tensorfold:num_requests_running Requests in prefill or decode. A mirror of tensorfold:requests_running. +# TYPE tensorfold:num_requests_running gauge +tensorfold:num_requests_running 0 +# HELP tensorfold:num_requests_waiting Requests queued or held until a lane is free. A mirror of tensorfold:requests_waiting. +# TYPE tensorfold:num_requests_waiting gauge +tensorfold:num_requests_waiting 0 +# HELP tensorfold:kv_cache_usage_perc A stream's cache occupancy under vLLM's name; same streams and ratios as tensorfold:kv_cache_usage_ratio. +# TYPE tensorfold:kv_cache_usage_perc gauge +tensorfold:kv_cache_usage_perc{stream="0"} 0 +# HELP tensorfold:spec_decode_num_draft_tokens_total Draft tokens verified on finished requests, this server's single draft counter. +# TYPE tensorfold:spec_decode_num_draft_tokens_total counter +tensorfold:spec_decode_num_draft_tokens_total 0 +# HELP tensorfold:spec_decode_num_accepted_tokens_total Draft tokens kept on finished requests. +# TYPE tensorfold:spec_decode_num_accepted_tokens_total counter +tensorfold:spec_decode_num_accepted_tokens_total 0 +# HELP tensorfold:e2e_request_latency_seconds Seconds from arrival to the reply leaving, under vLLM's name. +# TYPE tensorfold:e2e_request_latency_seconds histogram +tensorfold:e2e_request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="1"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="10"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="30"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="60"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="120"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="300"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:e2e_request_latency_seconds_sum 34.326942 +tensorfold:e2e_request_latency_seconds_count 2 +# HELP tensorfold:request_decode_time_seconds Seconds a finished request spent decoding, under vLLM's name. +# TYPE tensorfold:request_decode_time_seconds histogram +tensorfold:request_decode_time_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="10"} 2 +tensorfold:request_decode_time_seconds_bucket{le="30"} 2 +tensorfold:request_decode_time_seconds_bucket{le="60"} 2 +tensorfold:request_decode_time_seconds_bucket{le="120"} 2 +tensorfold:request_decode_time_seconds_bucket{le="300"} 2 +tensorfold:request_decode_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_time_seconds_sum 0.000389 +tensorfold:request_decode_time_seconds_count 2 +# HELP tensorfold:request_prefill_time_seconds Seconds a finished request's prompt pass took, under vLLM's name. +# TYPE tensorfold:request_prefill_time_seconds histogram +tensorfold:request_prefill_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="1"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="60"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="120"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_time_seconds_sum 34.323486 +tensorfold:request_prefill_time_seconds_count 2 +# HELP tensorfold:client_disconnections_total Requests a client left before the reply left the server. +# TYPE tensorfold:client_disconnections_total counter +tensorfold:client_disconnections_total 0 +# HELP tensorfold:preemptions_total Requests that had to give a lane up to a later one. +# TYPE tensorfold:preemptions_total counter +tensorfold:preemptions_total 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step1024-r1-samples.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step1024-r1-samples.jsonl new file mode 100644 index 0000000000..378269d286 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step1024-r1-samples.jsonl @@ -0,0 +1,56 @@ +{"t_s": 0.0, "VmRSS_bytes": 58781696, "VmHWM_bytes": 58781696, "Pss_bytes": 58670080, "vram_used_bytes": 187670528, "vram_total_bytes": 4294967296, "gtt_used_bytes": 31657984, "gtt_total_bytes": 193273528320} +{"t_s": 1.02, "VmRSS_bytes": 6123376640, "VmHWM_bytes": 6123376640, "Pss_bytes": 6141165568, "vram_used_bytes": 188645376, "vram_total_bytes": 4294967296, "gtt_used_bytes": 3557093376, "gtt_total_bytes": 193273528320} +{"t_s": 2.06, "VmRSS_bytes": 11850731520, "VmHWM_bytes": 11850731520, "Pss_bytes": 11848335360, "vram_used_bytes": 188899328, "vram_total_bytes": 4294967296, "gtt_used_bytes": 10026807296, "gtt_total_bytes": 193273528320} +{"t_s": 3.11, "VmRSS_bytes": 19827527680, "VmHWM_bytes": 19827527680, "Pss_bytes": 19852394496, "vram_used_bytes": 189403136, "vram_total_bytes": 4294967296, "gtt_used_bytes": 16706236416, "gtt_total_bytes": 193273528320} +{"t_s": 4.18, "VmRSS_bytes": 28015337472, "VmHWM_bytes": 28015337472, "Pss_bytes": 28013927424, "vram_used_bytes": 189964288, "vram_total_bytes": 4294967296, "gtt_used_bytes": 24916586496, "gtt_total_bytes": 193273528320} +{"t_s": 5.27, "VmRSS_bytes": 35753492480, "VmHWM_bytes": 35753492480, "Pss_bytes": 35854061568, "vram_used_bytes": 190459904, "vram_total_bytes": 4294967296, "gtt_used_bytes": 33131130880, "gtt_total_bytes": 193273528320} +{"t_s": 6.39, "VmRSS_bytes": 43555328000, "VmHWM_bytes": 43555328000, "Pss_bytes": 43556796416, "vram_used_bytes": 191008768, "vram_total_bytes": 4294967296, "gtt_used_bytes": 41345675264, "gtt_total_bytes": 193273528320} +{"t_s": 7.52, "VmRSS_bytes": 52400992256, "VmHWM_bytes": 52400992256, "Pss_bytes": 52398596096, "vram_used_bytes": 191561728, "vram_total_bytes": 4294967296, "gtt_used_bytes": 51042906112, "gtt_total_bytes": 193273528320} +{"t_s": 8.67, "VmRSS_bytes": 60554760192, "VmHWM_bytes": 60554760192, "Pss_bytes": 60552364032, "vram_used_bytes": 192180224, "vram_total_bytes": 4294967296, "gtt_used_bytes": 59414736896, "gtt_total_bytes": 193273528320} +{"t_s": 9.84, "VmRSS_bytes": 70289420288, "VmHWM_bytes": 70289420288, "Pss_bytes": 70287024128, "vram_used_bytes": 192798720, "vram_total_bytes": 4294967296, "gtt_used_bytes": 69275545600, "gtt_total_bytes": 193273528320} +{"t_s": 11.02, "VmRSS_bytes": 80474210304, "VmHWM_bytes": 80474210304, "Pss_bytes": 80538923008, "vram_used_bytes": 193921024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 79794860032, "gtt_total_bytes": 193273528320} +{"t_s": 12.2, "VmRSS_bytes": 82904039424, "VmHWM_bytes": 82904039424, "Pss_bytes": 82767425536, "vram_used_bytes": 194244608, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 13.39, "VmRSS_bytes": 85516517376, "VmHWM_bytes": 85516517376, "Pss_bytes": 85487628288, "vram_used_bytes": 194244608, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 14.58, "VmRSS_bytes": 88258777088, "VmHWM_bytes": 88258777088, "Pss_bytes": 88239607808, "vram_used_bytes": 194244608, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 15.76, "VmRSS_bytes": 91118997504, "VmHWM_bytes": 91118997504, "Pss_bytes": 91023384576, "vram_used_bytes": 194244608, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 16.96, "VmRSS_bytes": 93846851584, "VmHWM_bytes": 93846851584, "Pss_bytes": 93739675648, "vram_used_bytes": 194244608, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 18.15, "VmRSS_bytes": 96611405824, "VmHWM_bytes": 96611405824, "Pss_bytes": 96491679744, "vram_used_bytes": 194244608, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 19.34, "VmRSS_bytes": 99387379712, "VmHWM_bytes": 99387379712, "Pss_bytes": 99280474112, "vram_used_bytes": 194244608, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 20.53, "VmRSS_bytes": 102167801856, "VmHWM_bytes": 102167801856, "Pss_bytes": 102063980544, "vram_used_bytes": 194244608, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 21.72, "VmRSS_bytes": 103526907904, "VmHWM_bytes": 103942615040, "Pss_bytes": 103391911936, "vram_used_bytes": 194248704, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 22.92, "VmRSS_bytes": 105446252544, "VmHWM_bytes": 105446252544, "Pss_bytes": 105457475584, "vram_used_bytes": 194248704, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 24.11, "VmRSS_bytes": 107749044224, "VmHWM_bytes": 107749044224, "Pss_bytes": 107716820992, "vram_used_bytes": 194248704, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 25.33, "VmRSS_bytes": 110197727232, "VmHWM_bytes": 110197727232, "Pss_bytes": 110189367296, "vram_used_bytes": 194248704, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 26.55, "VmRSS_bytes": 107668688896, "VmHWM_bytes": 110645571584, "Pss_bytes": 107666239488, "vram_used_bytes": 198414336, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84025581568, "gtt_total_bytes": 193273528320} +{"t_s": 27.81, "VmRSS_bytes": 107674992640, "VmHWM_bytes": 110645571584, "Pss_bytes": 107672551424, "vram_used_bytes": 198422528, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84029308928, "gtt_total_bytes": 193273528320} +{"t_s": 29.07, "VmRSS_bytes": 107679588352, "VmHWM_bytes": 110645571584, "Pss_bytes": 107677143040, "vram_used_bytes": 198430720, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84030414848, "gtt_total_bytes": 193273528320} +{"t_s": 30.29, "VmRSS_bytes": 107680571392, "VmHWM_bytes": 110645571584, "Pss_bytes": 107678299136, "vram_used_bytes": 198430720, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84030414848, "gtt_total_bytes": 193273528320} +{"t_s": 31.53, "VmRSS_bytes": 107683909632, "VmHWM_bytes": 110645571584, "Pss_bytes": 107681453056, "vram_used_bytes": 198426624, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 32.76, "VmRSS_bytes": 107683917824, "VmHWM_bytes": 110645571584, "Pss_bytes": 107681461248, "vram_used_bytes": 198426624, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 33.98, "VmRSS_bytes": 107683917824, "VmHWM_bytes": 110645571584, "Pss_bytes": 107681461248, "vram_used_bytes": 198426624, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 35.21, "VmRSS_bytes": 107684261888, "VmHWM_bytes": 110645571584, "Pss_bytes": 107681805312, "vram_used_bytes": 198426624, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 36.45, "VmRSS_bytes": 107684265984, "VmHWM_bytes": 110645571584, "Pss_bytes": 107681809408, "vram_used_bytes": 198426624, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 37.7, "VmRSS_bytes": 107684265984, "VmHWM_bytes": 110645571584, "Pss_bytes": 107681809408, "vram_used_bytes": 198426624, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 38.94, "VmRSS_bytes": 107684311040, "VmHWM_bytes": 110645571584, "Pss_bytes": 107681854464, "vram_used_bytes": 198426624, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 40.19, "VmRSS_bytes": 107684311040, "VmHWM_bytes": 110645571584, "Pss_bytes": 107681854464, "vram_used_bytes": 198426624, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 41.43, "VmRSS_bytes": 107684311040, "VmHWM_bytes": 110645571584, "Pss_bytes": 107681854464, "vram_used_bytes": 198426624, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 42.66, "VmRSS_bytes": 107684311040, "VmHWM_bytes": 110645571584, "Pss_bytes": 107681854464, "vram_used_bytes": 198426624, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 43.9, "VmRSS_bytes": 107684311040, "VmHWM_bytes": 110645571584, "Pss_bytes": 107681854464, "vram_used_bytes": 198426624, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 45.13, "VmRSS_bytes": 107684311040, "VmHWM_bytes": 110645571584, "Pss_bytes": 107681853440, "vram_used_bytes": 198426624, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 46.36, "VmRSS_bytes": 107684311040, "VmHWM_bytes": 110645571584, "Pss_bytes": 107681854464, "vram_used_bytes": 198426624, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 47.59, "VmRSS_bytes": 107684319232, "VmHWM_bytes": 110645571584, "Pss_bytes": 107681862656, "vram_used_bytes": 198426624, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 48.82, "VmRSS_bytes": 107684319232, "VmHWM_bytes": 110645571584, "Pss_bytes": 107681862656, "vram_used_bytes": 198426624, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 50.06, "VmRSS_bytes": 107684319232, "VmHWM_bytes": 110645571584, "Pss_bytes": 107681862656, "vram_used_bytes": 198426624, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 51.3, "VmRSS_bytes": 107684319232, "VmHWM_bytes": 110645571584, "Pss_bytes": 107681862656, "vram_used_bytes": 198426624, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 52.53, "VmRSS_bytes": 107684319232, "VmHWM_bytes": 110645571584, "Pss_bytes": 107681862656, "vram_used_bytes": 198426624, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 53.76, "VmRSS_bytes": 107684319232, "VmHWM_bytes": 110645571584, "Pss_bytes": 107681862656, "vram_used_bytes": 198426624, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 55.0, "VmRSS_bytes": 107684319232, "VmHWM_bytes": 110645571584, "Pss_bytes": 107681862656, "vram_used_bytes": 198426624, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 56.23, "VmRSS_bytes": 107684319232, "VmHWM_bytes": 110645571584, "Pss_bytes": 107681862656, "vram_used_bytes": 198426624, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 57.47, "VmRSS_bytes": 107684319232, "VmHWM_bytes": 110645571584, "Pss_bytes": 107681862656, "vram_used_bytes": 198426624, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 58.71, "VmRSS_bytes": 107684319232, "VmHWM_bytes": 110645571584, "Pss_bytes": 107681862656, "vram_used_bytes": 198426624, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 59.95, "VmRSS_bytes": 107684319232, "VmHWM_bytes": 110645571584, "Pss_bytes": 107681862656, "vram_used_bytes": 198426624, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 61.19, "VmRSS_bytes": 107684319232, "VmHWM_bytes": 110645571584, "Pss_bytes": 107681862656, "vram_used_bytes": 198426624, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 62.42, "VmRSS_bytes": 107684319232, "VmHWM_bytes": 110645571584, "Pss_bytes": 107681854464, "vram_used_bytes": 198426624, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 63.65, "VmRSS_bytes": 107684319232, "VmHWM_bytes": 110645571584, "Pss_bytes": 107681862656, "vram_used_bytes": 198426624, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 64.87, "VmRSS_bytes": 107683311616, "VmHWM_bytes": 110645571584, "Pss_bytes": 107681007616, "vram_used_bytes": 198426624, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84030414848, "gtt_total_bytes": 193273528320} +{"t_s": 65.94, "VmRSS_bytes": 24577376256, "VmHWM_bytes": 110645571584, "Pss_bytes": 24347027456, "vram_used_bytes": 194260992, "vram_total_bytes": 4294967296, "gtt_used_bytes": 204288000, "gtt_total_bytes": 193273528320} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step1024-r2-memory-endpoint.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step1024-r2-memory-endpoint.json new file mode 100644 index 0000000000..d4ff0b5aeb --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step1024-r2-memory-endpoint.json @@ -0,0 +1 @@ +{"schema_version": 1, "context_window": 20480, "context_fitted": false, "device": {"active_bytes": 83064265364, "cache_bytes": 0, "peak_bytes": 83103782820, "peak_scope": "since_start_or_health_reset"}} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step1024-r2-metrics.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step1024-r2-metrics.txt new file mode 100644 index 0000000000..0e8854d06a --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step1024-r2-metrics.txt @@ -0,0 +1,220 @@ +# HELP tensorfold:requests_running Requests in prefill or decode. +# TYPE tensorfold:requests_running gauge +tensorfold:requests_running 0 +# HELP tensorfold:requests_waiting Requests queued or held until a lane is free. +# TYPE tensorfold:requests_waiting gauge +tensorfold:requests_waiting 0 +# HELP tensorfold:generation_tokens_running Generated tokens held by live streams. +# TYPE tensorfold:generation_tokens_running gauge +tensorfold:generation_tokens_running 0 +# HELP tensorfold:prompt_tokens_total Prompt tokens of finished requests. +# TYPE tensorfold:prompt_tokens_total counter +tensorfold:prompt_tokens_total 16640 +# HELP tensorfold:generation_tokens_total Generated tokens of finished requests. +# TYPE tensorfold:generation_tokens_total counter +tensorfold:generation_tokens_total 2 +# HELP tensorfold:kv_cache_usage_ratio Tokens in a stream cache divided by that stream's context window. +# TYPE tensorfold:kv_cache_usage_ratio gauge +tensorfold:kv_cache_usage_ratio{pool="0"} 0 +# HELP tensorfold:mtp_drafted_total Draft tokens verified on finished requests. +# TYPE tensorfold:mtp_drafted_total counter +tensorfold:mtp_drafted_total 0 +# HELP tensorfold:mtp_accepted_total Draft tokens kept on finished requests. +# TYPE tensorfold:mtp_accepted_total counter +tensorfold:mtp_accepted_total 0 +# HELP tensorfold:request_latency_seconds Seconds from arrival to the reply leaving. +# TYPE tensorfold:request_latency_seconds histogram +tensorfold:request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:request_latency_seconds_bucket{le="0.5"} 1 +tensorfold:request_latency_seconds_bucket{le="1"} 1 +tensorfold:request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:request_latency_seconds_bucket{le="5"} 1 +tensorfold:request_latency_seconds_bucket{le="10"} 1 +tensorfold:request_latency_seconds_bucket{le="30"} 1 +tensorfold:request_latency_seconds_bucket{le="60"} 2 +tensorfold:request_latency_seconds_bucket{le="120"} 2 +tensorfold:request_latency_seconds_bucket{le="300"} 2 +tensorfold:request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:request_latency_seconds_sum 34.277721 +tensorfold:request_latency_seconds_count 2 +# HELP tensorfold:time_to_first_token_seconds Seconds from arrival to the first generated token. +# TYPE tensorfold:time_to_first_token_seconds histogram +tensorfold:time_to_first_token_seconds_bucket{le="0.01"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.05"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.25"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="1"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="2.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="10"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="30"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="60"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="120"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="300"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="+Inf"} 2 +tensorfold:time_to_first_token_seconds_sum 34.277405 +tensorfold:time_to_first_token_seconds_count 2 +# HELP tensorfold:request_decode_seconds Seconds a finished request spent decoding. Its sum over generation_tokens_total is the decode rate. +# TYPE tensorfold:request_decode_seconds histogram +tensorfold:request_decode_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_seconds_bucket{le="1"} 2 +tensorfold:request_decode_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_seconds_bucket{le="5"} 2 +tensorfold:request_decode_seconds_bucket{le="10"} 2 +tensorfold:request_decode_seconds_bucket{le="30"} 2 +tensorfold:request_decode_seconds_bucket{le="60"} 2 +tensorfold:request_decode_seconds_bucket{le="120"} 2 +tensorfold:request_decode_seconds_bucket{le="300"} 2 +tensorfold:request_decode_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_seconds_sum 0.000317 +tensorfold:request_decode_seconds_count 2 +# HELP tensorfold:request_time_per_output_token_seconds Seconds from the first generated token to the last, divided by the tokens less one. +# TYPE tensorfold:request_time_per_output_token_seconds histogram +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.005"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.01"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.015"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.02"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.03"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.04"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.05"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.15"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.2"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.3"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.5"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="+Inf"} 0 +tensorfold:request_time_per_output_token_seconds_sum 0 +tensorfold:request_time_per_output_token_seconds_count 0 +# HELP tensorfold:decode_rounds_total Decode rounds used by finished requests. +# TYPE tensorfold:decode_rounds_total counter +tensorfold:decode_rounds_total 0 +# HELP tensorfold:request_prefill_seconds Seconds a finished request's prompt pass took. +# TYPE tensorfold:request_prefill_seconds histogram +tensorfold:request_prefill_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="1"} 1 +tensorfold:request_prefill_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_seconds_bucket{le="60"} 2 +tensorfold:request_prefill_seconds_bucket{le="120"} 2 +tensorfold:request_prefill_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_seconds_sum 34.276222 +tensorfold:request_prefill_seconds_count 2 +# HELP tensorfold:process_resident_bytes Current resident set (VmRSS); device memory is not in it, so it is not a physical footprint (Linux). +# TYPE tensorfold:process_resident_bytes gauge +tensorfold:process_resident_bytes 107109638144 +# HELP tensorfold:process_resident_anon_bytes Current resident anonymous memory (RssAnon): heap, stacks and private maps (Linux). +# TYPE tensorfold:process_resident_anon_bytes gauge +tensorfold:process_resident_anon_bytes 32364621824 +# HELP tensorfold:process_resident_file_bytes Current resident file-backed memory (RssFile): the binary, libraries and mapped files (Linux). +# TYPE tensorfold:process_resident_file_bytes gauge +tensorfold:process_resident_file_bytes 74610753536 +# HELP tensorfold:process_resident_shmem_bytes Current resident shared memory (RssShmem): System V shared memory, tmpfs maps and shared anonymous maps (Linux). +# TYPE tensorfold:process_resident_shmem_bytes gauge +tensorfold:process_resident_shmem_bytes 134262784 +# HELP tensorfold:process_resident_peak_bytes Kernel lifetime peak resident set (VmHWM); never reset by health (Linux). +# TYPE tensorfold:process_resident_peak_bytes gauge +tensorfold:process_resident_peak_bytes 112674865152 +# HELP tensorfold:device_memory_bytes Device memory the engine holds now: weights, caches and live streams; only where the backend counts it (CUDA). +# TYPE tensorfold:device_memory_bytes gauge +tensorfold:device_memory_bytes 83064265364 +# HELP tensorfold:device_memory_peak_bytes The most device memory the engine has held since start or the last /health?reset_peak=1. +# TYPE tensorfold:device_memory_peak_bytes gauge +tensorfold:device_memory_peak_bytes 83103782820 +# HELP tensorfold:pinned_memory_bytes Pinned host memory the engine holds now: staging buffers and windows; only where the backend counts it (CUDA). +# TYPE tensorfold:pinned_memory_bytes gauge +tensorfold:pinned_memory_bytes 0 +# HELP tensorfold:num_requests_running Requests in prefill or decode. A mirror of tensorfold:requests_running. +# TYPE tensorfold:num_requests_running gauge +tensorfold:num_requests_running 0 +# HELP tensorfold:num_requests_waiting Requests queued or held until a lane is free. A mirror of tensorfold:requests_waiting. +# TYPE tensorfold:num_requests_waiting gauge +tensorfold:num_requests_waiting 0 +# HELP tensorfold:kv_cache_usage_perc A stream's cache occupancy under vLLM's name; same streams and ratios as tensorfold:kv_cache_usage_ratio. +# TYPE tensorfold:kv_cache_usage_perc gauge +tensorfold:kv_cache_usage_perc{stream="0"} 0 +# HELP tensorfold:spec_decode_num_draft_tokens_total Draft tokens verified on finished requests, this server's single draft counter. +# TYPE tensorfold:spec_decode_num_draft_tokens_total counter +tensorfold:spec_decode_num_draft_tokens_total 0 +# HELP tensorfold:spec_decode_num_accepted_tokens_total Draft tokens kept on finished requests. +# TYPE tensorfold:spec_decode_num_accepted_tokens_total counter +tensorfold:spec_decode_num_accepted_tokens_total 0 +# HELP tensorfold:e2e_request_latency_seconds Seconds from arrival to the reply leaving, under vLLM's name. +# TYPE tensorfold:e2e_request_latency_seconds histogram +tensorfold:e2e_request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="1"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="10"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="30"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="60"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="120"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="300"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:e2e_request_latency_seconds_sum 34.277721 +tensorfold:e2e_request_latency_seconds_count 2 +# HELP tensorfold:request_decode_time_seconds Seconds a finished request spent decoding, under vLLM's name. +# TYPE tensorfold:request_decode_time_seconds histogram +tensorfold:request_decode_time_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="10"} 2 +tensorfold:request_decode_time_seconds_bucket{le="30"} 2 +tensorfold:request_decode_time_seconds_bucket{le="60"} 2 +tensorfold:request_decode_time_seconds_bucket{le="120"} 2 +tensorfold:request_decode_time_seconds_bucket{le="300"} 2 +tensorfold:request_decode_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_time_seconds_sum 0.000317 +tensorfold:request_decode_time_seconds_count 2 +# HELP tensorfold:request_prefill_time_seconds Seconds a finished request's prompt pass took, under vLLM's name. +# TYPE tensorfold:request_prefill_time_seconds histogram +tensorfold:request_prefill_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="1"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="30"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="60"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="120"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_time_seconds_sum 34.276222 +tensorfold:request_prefill_time_seconds_count 2 +# HELP tensorfold:client_disconnections_total Requests a client left before the reply left the server. +# TYPE tensorfold:client_disconnections_total counter +tensorfold:client_disconnections_total 0 +# HELP tensorfold:preemptions_total Requests that had to give a lane up to a later one. +# TYPE tensorfold:preemptions_total counter +tensorfold:preemptions_total 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step1024-r2-samples.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step1024-r2-samples.jsonl new file mode 100644 index 0000000000..913afa181e --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step1024-r2-samples.jsonl @@ -0,0 +1,55 @@ +{"t_s": 0.0, "VmRSS_bytes": 68374528, "VmHWM_bytes": 68374528, "Pss_bytes": 66214912, "vram_used_bytes": 187670528, "vram_total_bytes": 4294967296, "gtt_used_bytes": 31657984, "gtt_total_bytes": 193273528320} +{"t_s": 1.03, "VmRSS_bytes": 9261674496, "VmHWM_bytes": 9261674496, "Pss_bytes": 9306989568, "vram_used_bytes": 188813312, "vram_total_bytes": 4294967296, "gtt_used_bytes": 6841233408, "gtt_total_bytes": 193273528320} +{"t_s": 2.1, "VmRSS_bytes": 17067180032, "VmHWM_bytes": 17067180032, "Pss_bytes": 17101026304, "vram_used_bytes": 189366272, "vram_total_bytes": 4294967296, "gtt_used_bytes": 15055777792, "gtt_total_bytes": 193273528320} +{"t_s": 3.21, "VmRSS_bytes": 25441853440, "VmHWM_bytes": 25441853440, "Pss_bytes": 25474585600, "vram_used_bytes": 189956096, "vram_total_bytes": 4294967296, "gtt_used_bytes": 23276613632, "gtt_total_bytes": 193273528320} +{"t_s": 4.33, "VmRSS_bytes": 34553425920, "VmHWM_bytes": 34553425920, "Pss_bytes": 34551030784, "vram_used_bytes": 190509056, "vram_total_bytes": 4294967296, "gtt_used_bytes": 32332115968, "gtt_total_bytes": 193273528320} +{"t_s": 5.47, "VmRSS_bytes": 42202361856, "VmHWM_bytes": 42202361856, "Pss_bytes": 42206454784, "vram_used_bytes": 191066112, "vram_total_bytes": 4294967296, "gtt_used_bytes": 39701508096, "gtt_total_bytes": 193273528320} +{"t_s": 6.63, "VmRSS_bytes": 50775113728, "VmHWM_bytes": 50775113728, "Pss_bytes": 50772718592, "vram_used_bytes": 191602688, "vram_total_bytes": 4294967296, "gtt_used_bytes": 49398738944, "gtt_total_bytes": 193273528320} +{"t_s": 7.8, "VmRSS_bytes": 58886782976, "VmHWM_bytes": 58886782976, "Pss_bytes": 58884387840, "vram_used_bytes": 192167936, "vram_total_bytes": 4294967296, "gtt_used_bytes": 56977846272, "gtt_total_bytes": 193273528320} +{"t_s": 8.99, "VmRSS_bytes": 66948526080, "VmHWM_bytes": 66948526080, "Pss_bytes": 66953208832, "vram_used_bytes": 192741376, "vram_total_bytes": 4294967296, "gtt_used_bytes": 64343044096, "gtt_total_bytes": 193273528320} +{"t_s": 10.2, "VmRSS_bytes": 71862378496, "VmHWM_bytes": 71862378496, "Pss_bytes": 71859983360, "vram_used_bytes": 193085440, "vram_total_bytes": 4294967296, "gtt_used_bytes": 70227652608, "gtt_total_bytes": 193273528320} +{"t_s": 11.44, "VmRSS_bytes": 77724422144, "VmHWM_bytes": 77724422144, "Pss_bytes": 77767353344, "vram_used_bytes": 193536000, "vram_total_bytes": 4294967296, "gtt_used_bytes": 75845922816, "gtt_total_bytes": 193273528320} +{"t_s": 12.68, "VmRSS_bytes": 81982926848, "VmHWM_bytes": 82503352320, "Pss_bytes": 82111050752, "vram_used_bytes": 194867200, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 13.91, "VmRSS_bytes": 84898107392, "VmHWM_bytes": 84898107392, "Pss_bytes": 84835828736, "vram_used_bytes": 194867200, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 15.15, "VmRSS_bytes": 87656390656, "VmHWM_bytes": 87656390656, "Pss_bytes": 87591186432, "vram_used_bytes": 194867200, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 16.39, "VmRSS_bytes": 90429001728, "VmHWM_bytes": 90429001728, "Pss_bytes": 90422207488, "vram_used_bytes": 194867200, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 17.63, "VmRSS_bytes": 92990885888, "VmHWM_bytes": 93188132864, "Pss_bytes": 92988490752, "vram_used_bytes": 194867200, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 18.87, "VmRSS_bytes": 95765823488, "VmHWM_bytes": 95938473984, "Pss_bytes": 95763469312, "vram_used_bytes": 194867200, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 20.12, "VmRSS_bytes": 98559700992, "VmHWM_bytes": 98690416640, "Pss_bytes": 98540553216, "vram_used_bytes": 194867200, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 21.37, "VmRSS_bytes": 101596811264, "VmHWM_bytes": 101596811264, "Pss_bytes": 101544322048, "vram_used_bytes": 194867200, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 22.61, "VmRSS_bytes": 104411541504, "VmHWM_bytes": 104411541504, "Pss_bytes": 104241374208, "vram_used_bytes": 194867200, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 23.86, "VmRSS_bytes": 107097866240, "VmHWM_bytes": 107097866240, "Pss_bytes": 106990679040, "vram_used_bytes": 194867200, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 25.1, "VmRSS_bytes": 109542567936, "VmHWM_bytes": 109542567936, "Pss_bytes": 109509551104, "vram_used_bytes": 194867200, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 26.36, "VmRSS_bytes": 111520681984, "VmHWM_bytes": 111680122880, "Pss_bytes": 111504172032, "vram_used_bytes": 194867200, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 28.23, "VmRSS_bytes": 111990099968, "VmHWM_bytes": 112674865152, "Pss_bytes": 111927358464, "vram_used_bytes": 198017024, "vram_total_bytes": 4294967296, "gtt_used_bytes": 83274035200, "gtt_total_bytes": 193273528320} +{"t_s": 29.52, "VmRSS_bytes": 107098923008, "VmHWM_bytes": 112674865152, "Pss_bytes": 107096482816, "vram_used_bytes": 199417856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84028940288, "gtt_total_bytes": 193273528320} +{"t_s": 30.79, "VmRSS_bytes": 107103571968, "VmHWM_bytes": 112674865152, "Pss_bytes": 107101135872, "vram_used_bytes": 199421952, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84030046208, "gtt_total_bytes": 193273528320} +{"t_s": 32.03, "VmRSS_bytes": 107106381824, "VmHWM_bytes": 112674865152, "Pss_bytes": 107103941632, "vram_used_bytes": 199426048, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84030414848, "gtt_total_bytes": 193273528320} +{"t_s": 33.31, "VmRSS_bytes": 107109916672, "VmHWM_bytes": 112674865152, "Pss_bytes": 107107470336, "vram_used_bytes": 199417856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 34.57, "VmRSS_bytes": 107109924864, "VmHWM_bytes": 112674865152, "Pss_bytes": 107107478528, "vram_used_bytes": 199417856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 35.82, "VmRSS_bytes": 107109924864, "VmHWM_bytes": 112674865152, "Pss_bytes": 107107478528, "vram_used_bytes": 199417856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 37.09, "VmRSS_bytes": 107110268928, "VmHWM_bytes": 112674865152, "Pss_bytes": 107107822592, "vram_used_bytes": 199417856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 38.35, "VmRSS_bytes": 107110273024, "VmHWM_bytes": 112674865152, "Pss_bytes": 107107826688, "vram_used_bytes": 199417856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 39.61, "VmRSS_bytes": 107110404096, "VmHWM_bytes": 112674865152, "Pss_bytes": 107107957760, "vram_used_bytes": 199417856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 40.86, "VmRSS_bytes": 107110449152, "VmHWM_bytes": 112674865152, "Pss_bytes": 107108002816, "vram_used_bytes": 199417856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 42.12, "VmRSS_bytes": 107110449152, "VmHWM_bytes": 112674865152, "Pss_bytes": 107108002816, "vram_used_bytes": 199417856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 43.37, "VmRSS_bytes": 107110449152, "VmHWM_bytes": 112674865152, "Pss_bytes": 107108002816, "vram_used_bytes": 199417856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 44.63, "VmRSS_bytes": 107110449152, "VmHWM_bytes": 112674865152, "Pss_bytes": 107108002816, "vram_used_bytes": 199417856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 45.88, "VmRSS_bytes": 107110449152, "VmHWM_bytes": 112674865152, "Pss_bytes": 107108001792, "vram_used_bytes": 199417856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 47.14, "VmRSS_bytes": 107110449152, "VmHWM_bytes": 112674865152, "Pss_bytes": 107108002816, "vram_used_bytes": 199417856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 48.4, "VmRSS_bytes": 107110449152, "VmHWM_bytes": 112674865152, "Pss_bytes": 107108002816, "vram_used_bytes": 199417856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 49.66, "VmRSS_bytes": 107110449152, "VmHWM_bytes": 112674865152, "Pss_bytes": 107108002816, "vram_used_bytes": 199417856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 50.92, "VmRSS_bytes": 107110449152, "VmHWM_bytes": 112674865152, "Pss_bytes": 107108002816, "vram_used_bytes": 199417856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 52.18, "VmRSS_bytes": 107110449152, "VmHWM_bytes": 112674865152, "Pss_bytes": 107108002816, "vram_used_bytes": 199417856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 53.45, "VmRSS_bytes": 107110449152, "VmHWM_bytes": 112674865152, "Pss_bytes": 107108002816, "vram_used_bytes": 199417856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 54.71, "VmRSS_bytes": 107110449152, "VmHWM_bytes": 112674865152, "Pss_bytes": 107108001792, "vram_used_bytes": 199417856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 55.98, "VmRSS_bytes": 107110449152, "VmHWM_bytes": 112674865152, "Pss_bytes": 107108002816, "vram_used_bytes": 199417856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 57.25, "VmRSS_bytes": 107110449152, "VmHWM_bytes": 112674865152, "Pss_bytes": 107108002816, "vram_used_bytes": 199417856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 58.52, "VmRSS_bytes": 107110449152, "VmHWM_bytes": 112674865152, "Pss_bytes": 107108002816, "vram_used_bytes": 199417856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 59.78, "VmRSS_bytes": 107110449152, "VmHWM_bytes": 112674865152, "Pss_bytes": 107108072448, "vram_used_bytes": 199417856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 61.04, "VmRSS_bytes": 107110449152, "VmHWM_bytes": 112674865152, "Pss_bytes": 107108002816, "vram_used_bytes": 199417856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 62.29, "VmRSS_bytes": 107110449152, "VmHWM_bytes": 112674865152, "Pss_bytes": 107108002816, "vram_used_bytes": 199417856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 63.55, "VmRSS_bytes": 107110449152, "VmHWM_bytes": 112674865152, "Pss_bytes": 107108002816, "vram_used_bytes": 199417856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 64.81, "VmRSS_bytes": 107110453248, "VmHWM_bytes": 112674865152, "Pss_bytes": 107108006912, "vram_used_bytes": 199417856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 66.08, "VmRSS_bytes": 107110453248, "VmHWM_bytes": 112674865152, "Pss_bytes": 107108006912, "vram_used_bytes": 199417856, "vram_total_bytes": 4294967296, "gtt_used_bytes": 84070260736, "gtt_total_bytes": 193273528320} +{"t_s": 67.32, "VmRSS_bytes": 107031441408, "VmHWM_bytes": 112674865152, "Pss_bytes": 107029004288, "vram_used_bytes": 194789376, "vram_total_bytes": 4294967296, "gtt_used_bytes": 8003596288, "gtt_total_bytes": 193273528320} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step20480-r1-memory-endpoint.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step20480-r1-memory-endpoint.json new file mode 100644 index 0000000000..03798ef2dc --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step20480-r1-memory-endpoint.json @@ -0,0 +1 @@ +{"schema_version": 1, "context_window": 20480, "context_fitted": false, "device": {"active_bytes": 113417570964, "cache_bytes": 0, "peak_bytes": 113457088420, "peak_scope": "since_start_or_health_reset"}} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step20480-r1-metrics.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step20480-r1-metrics.txt new file mode 100644 index 0000000000..715bf0f313 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step20480-r1-metrics.txt @@ -0,0 +1,220 @@ +# HELP tensorfold:requests_running Requests in prefill or decode. +# TYPE tensorfold:requests_running gauge +tensorfold:requests_running 0 +# HELP tensorfold:requests_waiting Requests queued or held until a lane is free. +# TYPE tensorfold:requests_waiting gauge +tensorfold:requests_waiting 0 +# HELP tensorfold:generation_tokens_running Generated tokens held by live streams. +# TYPE tensorfold:generation_tokens_running gauge +tensorfold:generation_tokens_running 0 +# HELP tensorfold:prompt_tokens_total Prompt tokens of finished requests. +# TYPE tensorfold:prompt_tokens_total counter +tensorfold:prompt_tokens_total 16640 +# HELP tensorfold:generation_tokens_total Generated tokens of finished requests. +# TYPE tensorfold:generation_tokens_total counter +tensorfold:generation_tokens_total 2 +# HELP tensorfold:kv_cache_usage_ratio Tokens in a stream cache divided by that stream's context window. +# TYPE tensorfold:kv_cache_usage_ratio gauge +tensorfold:kv_cache_usage_ratio{pool="0"} 0 +# HELP tensorfold:mtp_drafted_total Draft tokens verified on finished requests. +# TYPE tensorfold:mtp_drafted_total counter +tensorfold:mtp_drafted_total 0 +# HELP tensorfold:mtp_accepted_total Draft tokens kept on finished requests. +# TYPE tensorfold:mtp_accepted_total counter +tensorfold:mtp_accepted_total 0 +# HELP tensorfold:request_latency_seconds Seconds from arrival to the reply leaving. +# TYPE tensorfold:request_latency_seconds histogram +tensorfold:request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:request_latency_seconds_bucket{le="0.5"} 1 +tensorfold:request_latency_seconds_bucket{le="1"} 1 +tensorfold:request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:request_latency_seconds_bucket{le="5"} 1 +tensorfold:request_latency_seconds_bucket{le="10"} 1 +tensorfold:request_latency_seconds_bucket{le="30"} 2 +tensorfold:request_latency_seconds_bucket{le="60"} 2 +tensorfold:request_latency_seconds_bucket{le="120"} 2 +tensorfold:request_latency_seconds_bucket{le="300"} 2 +tensorfold:request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:request_latency_seconds_sum 30.117252 +tensorfold:request_latency_seconds_count 2 +# HELP tensorfold:time_to_first_token_seconds Seconds from arrival to the first generated token. +# TYPE tensorfold:time_to_first_token_seconds histogram +tensorfold:time_to_first_token_seconds_bucket{le="0.01"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.05"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.25"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="1"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="2.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="10"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="30"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="60"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="120"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="300"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="+Inf"} 2 +tensorfold:time_to_first_token_seconds_sum 30.116545 +tensorfold:time_to_first_token_seconds_count 2 +# HELP tensorfold:request_decode_seconds Seconds a finished request spent decoding. Its sum over generation_tokens_total is the decode rate. +# TYPE tensorfold:request_decode_seconds histogram +tensorfold:request_decode_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_seconds_bucket{le="1"} 2 +tensorfold:request_decode_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_seconds_bucket{le="5"} 2 +tensorfold:request_decode_seconds_bucket{le="10"} 2 +tensorfold:request_decode_seconds_bucket{le="30"} 2 +tensorfold:request_decode_seconds_bucket{le="60"} 2 +tensorfold:request_decode_seconds_bucket{le="120"} 2 +tensorfold:request_decode_seconds_bucket{le="300"} 2 +tensorfold:request_decode_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_seconds_sum 0.000707 +tensorfold:request_decode_seconds_count 2 +# HELP tensorfold:request_time_per_output_token_seconds Seconds from the first generated token to the last, divided by the tokens less one. +# TYPE tensorfold:request_time_per_output_token_seconds histogram +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.005"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.01"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.015"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.02"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.03"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.04"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.05"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.15"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.2"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.3"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.5"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="+Inf"} 0 +tensorfold:request_time_per_output_token_seconds_sum 0 +tensorfold:request_time_per_output_token_seconds_count 0 +# HELP tensorfold:decode_rounds_total Decode rounds used by finished requests. +# TYPE tensorfold:decode_rounds_total counter +tensorfold:decode_rounds_total 0 +# HELP tensorfold:request_prefill_seconds Seconds a finished request's prompt pass took. +# TYPE tensorfold:request_prefill_seconds histogram +tensorfold:request_prefill_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="1"} 1 +tensorfold:request_prefill_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_seconds_bucket{le="30"} 2 +tensorfold:request_prefill_seconds_bucket{le="60"} 2 +tensorfold:request_prefill_seconds_bucket{le="120"} 2 +tensorfold:request_prefill_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_seconds_sum 30.115384 +tensorfold:request_prefill_seconds_count 2 +# HELP tensorfold:process_resident_bytes Current resident set (VmRSS); device memory is not in it, so it is not a physical footprint (Linux). +# TYPE tensorfold:process_resident_bytes gauge +tensorfold:process_resident_bytes 79462301696 +# HELP tensorfold:process_resident_anon_bytes Current resident anonymous memory (RssAnon): heap, stacks and private maps (Linux). +# TYPE tensorfold:process_resident_anon_bytes gauge +tensorfold:process_resident_anon_bytes 32377860096 +# HELP tensorfold:process_resident_file_bytes Current resident file-backed memory (RssFile): the binary, libraries and mapped files (Linux). +# TYPE tensorfold:process_resident_file_bytes gauge +tensorfold:process_resident_file_bytes 46950178816 +# HELP tensorfold:process_resident_shmem_bytes Current resident shared memory (RssShmem): System V shared memory, tmpfs maps and shared anonymous maps (Linux). +# TYPE tensorfold:process_resident_shmem_bytes gauge +tensorfold:process_resident_shmem_bytes 134262784 +# HELP tensorfold:process_resident_peak_bytes Kernel lifetime peak resident set (VmHWM); never reset by health (Linux). +# TYPE tensorfold:process_resident_peak_bytes gauge +tensorfold:process_resident_peak_bytes 112821686272 +# HELP tensorfold:device_memory_bytes Device memory the engine holds now: weights, caches and live streams; only where the backend counts it (CUDA). +# TYPE tensorfold:device_memory_bytes gauge +tensorfold:device_memory_bytes 113417570964 +# HELP tensorfold:device_memory_peak_bytes The most device memory the engine has held since start or the last /health?reset_peak=1. +# TYPE tensorfold:device_memory_peak_bytes gauge +tensorfold:device_memory_peak_bytes 113457088420 +# HELP tensorfold:pinned_memory_bytes Pinned host memory the engine holds now: staging buffers and windows; only where the backend counts it (CUDA). +# TYPE tensorfold:pinned_memory_bytes gauge +tensorfold:pinned_memory_bytes 0 +# HELP tensorfold:num_requests_running Requests in prefill or decode. A mirror of tensorfold:requests_running. +# TYPE tensorfold:num_requests_running gauge +tensorfold:num_requests_running 0 +# HELP tensorfold:num_requests_waiting Requests queued or held until a lane is free. A mirror of tensorfold:requests_waiting. +# TYPE tensorfold:num_requests_waiting gauge +tensorfold:num_requests_waiting 0 +# HELP tensorfold:kv_cache_usage_perc A stream's cache occupancy under vLLM's name; same streams and ratios as tensorfold:kv_cache_usage_ratio. +# TYPE tensorfold:kv_cache_usage_perc gauge +tensorfold:kv_cache_usage_perc{stream="0"} 0 +# HELP tensorfold:spec_decode_num_draft_tokens_total Draft tokens verified on finished requests, this server's single draft counter. +# TYPE tensorfold:spec_decode_num_draft_tokens_total counter +tensorfold:spec_decode_num_draft_tokens_total 0 +# HELP tensorfold:spec_decode_num_accepted_tokens_total Draft tokens kept on finished requests. +# TYPE tensorfold:spec_decode_num_accepted_tokens_total counter +tensorfold:spec_decode_num_accepted_tokens_total 0 +# HELP tensorfold:e2e_request_latency_seconds Seconds from arrival to the reply leaving, under vLLM's name. +# TYPE tensorfold:e2e_request_latency_seconds histogram +tensorfold:e2e_request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="1"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="10"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="30"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="60"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="120"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="300"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:e2e_request_latency_seconds_sum 30.117252 +tensorfold:e2e_request_latency_seconds_count 2 +# HELP tensorfold:request_decode_time_seconds Seconds a finished request spent decoding, under vLLM's name. +# TYPE tensorfold:request_decode_time_seconds histogram +tensorfold:request_decode_time_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="10"} 2 +tensorfold:request_decode_time_seconds_bucket{le="30"} 2 +tensorfold:request_decode_time_seconds_bucket{le="60"} 2 +tensorfold:request_decode_time_seconds_bucket{le="120"} 2 +tensorfold:request_decode_time_seconds_bucket{le="300"} 2 +tensorfold:request_decode_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_time_seconds_sum 0.000707 +tensorfold:request_decode_time_seconds_count 2 +# HELP tensorfold:request_prefill_time_seconds Seconds a finished request's prompt pass took, under vLLM's name. +# TYPE tensorfold:request_prefill_time_seconds histogram +tensorfold:request_prefill_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="1"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="30"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="60"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="120"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_time_seconds_sum 30.115384 +tensorfold:request_prefill_time_seconds_count 2 +# HELP tensorfold:client_disconnections_total Requests a client left before the reply left the server. +# TYPE tensorfold:client_disconnections_total counter +tensorfold:client_disconnections_total 0 +# HELP tensorfold:preemptions_total Requests that had to give a lane up to a later one. +# TYPE tensorfold:preemptions_total counter +tensorfold:preemptions_total 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step20480-r1-samples.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step20480-r1-samples.jsonl new file mode 100644 index 0000000000..e15e227d3c --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step20480-r1-samples.jsonl @@ -0,0 +1,54 @@ +{"t_s": 0.0, "VmRSS_bytes": 68964352, "VmHWM_bytes": 68964352, "Pss_bytes": 66962432, "vram_used_bytes": 187670528, "vram_total_bytes": 4294967296, "gtt_used_bytes": 31657984, "gtt_total_bytes": 193273528320} +{"t_s": 1.03, "VmRSS_bytes": 8850001920, "VmHWM_bytes": 8850001920, "Pss_bytes": 8879889408, "vram_used_bytes": 188792832, "vram_total_bytes": 4294967296, "gtt_used_bytes": 6841233408, "gtt_total_bytes": 193273528320} +{"t_s": 2.09, "VmRSS_bytes": 16759771136, "VmHWM_bytes": 16759771136, "Pss_bytes": 16757414912, "vram_used_bytes": 189325312, "vram_total_bytes": 4294967296, "gtt_used_bytes": 15055777792, "gtt_total_bytes": 193273528320} +{"t_s": 3.16, "VmRSS_bytes": 24723546112, "VmHWM_bytes": 24723546112, "Pss_bytes": 24785808384, "vram_used_bytes": 189755392, "vram_total_bytes": 4294967296, "gtt_used_bytes": 21632446464, "gtt_total_bytes": 193273528320} +{"t_s": 4.26, "VmRSS_bytes": 32242810880, "VmHWM_bytes": 32242810880, "Pss_bytes": 32271191040, "vram_used_bytes": 190308352, "vram_total_bytes": 4294967296, "gtt_used_bytes": 29849088000, "gtt_total_bytes": 193273528320} +{"t_s": 5.38, "VmRSS_bytes": 39422464000, "VmHWM_bytes": 39422464000, "Pss_bytes": 39420107776, "vram_used_bytes": 190775296, "vram_total_bytes": 4294967296, "gtt_used_bytes": 37900054528, "gtt_total_bytes": 193273528320} +{"t_s": 6.51, "VmRSS_bytes": 47423885312, "VmHWM_bytes": 47423885312, "Pss_bytes": 47421529088, "vram_used_bytes": 191287296, "vram_total_bytes": 4294967296, "gtt_used_bytes": 44629815296, "gtt_total_bytes": 193273528320} +{"t_s": 7.68, "VmRSS_bytes": 54639026176, "VmHWM_bytes": 54639026176, "Pss_bytes": 54703249408, "vram_used_bytes": 191852544, "vram_total_bytes": 4294967296, "gtt_used_bytes": 52844359680, "gtt_total_bytes": 193273528320} +{"t_s": 8.86, "VmRSS_bytes": 63799545856, "VmHWM_bytes": 63799545856, "Pss_bytes": 63797189632, "vram_used_bytes": 192491520, "vram_total_bytes": 4294967296, "gtt_used_bytes": 62703071232, "gtt_total_bytes": 193273528320} +{"t_s": 10.06, "VmRSS_bytes": 73528700928, "VmHWM_bytes": 73528700928, "Pss_bytes": 73526344704, "vram_used_bytes": 193114112, "vram_total_bytes": 4294967296, "gtt_used_bytes": 72557588480, "gtt_total_bytes": 193273528320} +{"t_s": 11.28, "VmRSS_bytes": 81029644288, "VmHWM_bytes": 82504282112, "Pss_bytes": 81027374080, "vram_used_bytes": 194338816, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 12.49, "VmRSS_bytes": 84016898048, "VmHWM_bytes": 84016898048, "Pss_bytes": 83983919104, "vram_used_bytes": 194338816, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 13.7, "VmRSS_bytes": 86923382784, "VmHWM_bytes": 86923382784, "Pss_bytes": 86772898816, "vram_used_bytes": 194338816, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 14.92, "VmRSS_bytes": 89489702912, "VmHWM_bytes": 89687805952, "Pss_bytes": 89567202304, "vram_used_bytes": 194338816, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 16.13, "VmRSS_bytes": 92244361216, "VmHWM_bytes": 92442124288, "Pss_bytes": 92338473984, "vram_used_bytes": 194338816, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 17.34, "VmRSS_bytes": 94994157568, "VmHWM_bytes": 95192444928, "Pss_bytes": 94991850496, "vram_used_bytes": 194338816, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 18.55, "VmRSS_bytes": 97922314240, "VmHWM_bytes": 97922314240, "Pss_bytes": 97778297856, "vram_used_bytes": 194338816, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 19.78, "VmRSS_bytes": 100546342912, "VmHWM_bytes": 100693946368, "Pss_bytes": 100543831040, "vram_used_bytes": 194338816, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 21.0, "VmRSS_bytes": 103649714176, "VmHWM_bytes": 103649714176, "Pss_bytes": 103495052288, "vram_used_bytes": 194338816, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 22.22, "VmRSS_bytes": 106296107008, "VmHWM_bytes": 106446397440, "Pss_bytes": 106271370240, "vram_used_bytes": 194338816, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 23.45, "VmRSS_bytes": 108972027904, "VmHWM_bytes": 109119651840, "Pss_bytes": 108969757696, "vram_used_bytes": 194338816, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 24.68, "VmRSS_bytes": 111697309696, "VmHWM_bytes": 111697309696, "Pss_bytes": 111669063680, "vram_used_bytes": 194338816, "vram_total_bytes": 4294967296, "gtt_used_bytes": 81659228160, "gtt_total_bytes": 193273528320} +{"t_s": 26.12, "VmRSS_bytes": 112203182080, "VmHWM_bytes": 112821686272, "Pss_bytes": 112178031616, "vram_used_bytes": 195751936, "vram_total_bytes": 4294967296, "gtt_used_bytes": 82407911424, "gtt_total_bytes": 193273528320} +{"t_s": 27.5, "VmRSS_bytes": 95683112960, "VmHWM_bytes": 112821686272, "Pss_bytes": 89783995392, "vram_used_bytes": 194936832, "vram_total_bytes": 4294967296, "gtt_used_bytes": 113628213248, "gtt_total_bytes": 193273528320} +{"t_s": 28.69, "VmRSS_bytes": 79438913536, "VmHWM_bytes": 112821686272, "Pss_bytes": 79436519424, "vram_used_bytes": 234577920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 114380128256, "gtt_total_bytes": 193273528320} +{"t_s": 29.91, "VmRSS_bytes": 79445200896, "VmHWM_bytes": 112821686272, "Pss_bytes": 79442806784, "vram_used_bytes": 234586112, "vram_total_bytes": 4294967296, "gtt_used_bytes": 114383855616, "gtt_total_bytes": 193273528320} +{"t_s": 31.14, "VmRSS_bytes": 79448264704, "VmHWM_bytes": 112821686272, "Pss_bytes": 79445874688, "vram_used_bytes": 234586112, "vram_total_bytes": 4294967296, "gtt_used_bytes": 114384592896, "gtt_total_bytes": 193273528320} +{"t_s": 32.35, "VmRSS_bytes": 79451578368, "VmHWM_bytes": 112821686272, "Pss_bytes": 79449187328, "vram_used_bytes": 234586112, "vram_total_bytes": 4294967296, "gtt_used_bytes": 114384592896, "gtt_total_bytes": 193273528320} +{"t_s": 33.53, "VmRSS_bytes": 79463108608, "VmHWM_bytes": 112821686272, "Pss_bytes": 79460717568, "vram_used_bytes": 234577920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 114424438784, "gtt_total_bytes": 193273528320} +{"t_s": 34.71, "VmRSS_bytes": 79463108608, "VmHWM_bytes": 112821686272, "Pss_bytes": 79460717568, "vram_used_bytes": 234577920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 114424438784, "gtt_total_bytes": 193273528320} +{"t_s": 35.9, "VmRSS_bytes": 79463108608, "VmHWM_bytes": 112821686272, "Pss_bytes": 79460717568, "vram_used_bytes": 234577920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 114424438784, "gtt_total_bytes": 193273528320} +{"t_s": 37.08, "VmRSS_bytes": 79463108608, "VmHWM_bytes": 112821686272, "Pss_bytes": 79460717568, "vram_used_bytes": 234577920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 114424438784, "gtt_total_bytes": 193273528320} +{"t_s": 38.28, "VmRSS_bytes": 79463108608, "VmHWM_bytes": 112821686272, "Pss_bytes": 79460717568, "vram_used_bytes": 234577920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 114424438784, "gtt_total_bytes": 193273528320} +{"t_s": 39.47, "VmRSS_bytes": 79463108608, "VmHWM_bytes": 112821686272, "Pss_bytes": 79460717568, "vram_used_bytes": 234577920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 114424438784, "gtt_total_bytes": 193273528320} +{"t_s": 40.67, "VmRSS_bytes": 79463108608, "VmHWM_bytes": 112821686272, "Pss_bytes": 79460717568, "vram_used_bytes": 234577920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 114424438784, "gtt_total_bytes": 193273528320} +{"t_s": 41.86, "VmRSS_bytes": 79463108608, "VmHWM_bytes": 112821686272, "Pss_bytes": 79460717568, "vram_used_bytes": 234577920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 114424438784, "gtt_total_bytes": 193273528320} +{"t_s": 43.06, "VmRSS_bytes": 79463108608, "VmHWM_bytes": 112821686272, "Pss_bytes": 79460717568, "vram_used_bytes": 234577920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 114424438784, "gtt_total_bytes": 193273528320} +{"t_s": 44.23, "VmRSS_bytes": 79463108608, "VmHWM_bytes": 112821686272, "Pss_bytes": 79460717568, "vram_used_bytes": 234577920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 114424438784, "gtt_total_bytes": 193273528320} +{"t_s": 45.44, "VmRSS_bytes": 79463108608, "VmHWM_bytes": 112821686272, "Pss_bytes": 79460717568, "vram_used_bytes": 234577920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 114424438784, "gtt_total_bytes": 193273528320} +{"t_s": 46.62, "VmRSS_bytes": 79463108608, "VmHWM_bytes": 112821686272, "Pss_bytes": 79460717568, "vram_used_bytes": 234577920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 114424438784, "gtt_total_bytes": 193273528320} +{"t_s": 47.83, "VmRSS_bytes": 79463108608, "VmHWM_bytes": 112821686272, "Pss_bytes": 79460717568, "vram_used_bytes": 234577920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 114424438784, "gtt_total_bytes": 193273528320} +{"t_s": 49.01, "VmRSS_bytes": 79463108608, "VmHWM_bytes": 112821686272, "Pss_bytes": 79460717568, "vram_used_bytes": 234577920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 114424438784, "gtt_total_bytes": 193273528320} +{"t_s": 50.22, "VmRSS_bytes": 79463108608, "VmHWM_bytes": 112821686272, "Pss_bytes": 79460717568, "vram_used_bytes": 234577920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 114424438784, "gtt_total_bytes": 193273528320} +{"t_s": 51.4, "VmRSS_bytes": 79463108608, "VmHWM_bytes": 112821686272, "Pss_bytes": 79460717568, "vram_used_bytes": 234577920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 114424438784, "gtt_total_bytes": 193273528320} +{"t_s": 52.6, "VmRSS_bytes": 79463108608, "VmHWM_bytes": 112821686272, "Pss_bytes": 79460717568, "vram_used_bytes": 234577920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 114424438784, "gtt_total_bytes": 193273528320} +{"t_s": 53.78, "VmRSS_bytes": 79463108608, "VmHWM_bytes": 112821686272, "Pss_bytes": 79460717568, "vram_used_bytes": 234577920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 114424438784, "gtt_total_bytes": 193273528320} +{"t_s": 54.99, "VmRSS_bytes": 79463108608, "VmHWM_bytes": 112821686272, "Pss_bytes": 79460717568, "vram_used_bytes": 234577920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 114424438784, "gtt_total_bytes": 193273528320} +{"t_s": 56.17, "VmRSS_bytes": 79463108608, "VmHWM_bytes": 112821686272, "Pss_bytes": 79460717568, "vram_used_bytes": 234577920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 114424438784, "gtt_total_bytes": 193273528320} +{"t_s": 57.37, "VmRSS_bytes": 79463108608, "VmHWM_bytes": 112821686272, "Pss_bytes": 79460717568, "vram_used_bytes": 234577920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 114424438784, "gtt_total_bytes": 193273528320} +{"t_s": 58.55, "VmRSS_bytes": 79463108608, "VmHWM_bytes": 112821686272, "Pss_bytes": 79460717568, "vram_used_bytes": 234577920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 114424438784, "gtt_total_bytes": 193273528320} +{"t_s": 59.75, "VmRSS_bytes": 79463108608, "VmHWM_bytes": 112821686272, "Pss_bytes": 79460717568, "vram_used_bytes": 234577920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 114424438784, "gtt_total_bytes": 193273528320} +{"t_s": 60.93, "VmRSS_bytes": 79463108608, "VmHWM_bytes": 112821686272, "Pss_bytes": 79460717568, "vram_used_bytes": 234577920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 114424438784, "gtt_total_bytes": 193273528320} +{"t_s": 62.13, "VmRSS_bytes": 79463108608, "VmHWM_bytes": 112821686272, "Pss_bytes": 79460712448, "vram_used_bytes": 234577920, "vram_total_bytes": 4294967296, "gtt_used_bytes": 114424438784, "gtt_total_bytes": 193273528320} +{"t_s": 63.31, "VmRSS_bytes": 79384121344, "VmHWM_bytes": 112821686272, "Pss_bytes": 79381732352, "vram_used_bytes": 194859008, "vram_total_bytes": 4294967296, "gtt_used_bytes": 29597970432, "gtt_total_bytes": 193273528320} diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step20480-r2-memory-endpoint.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step20480-r2-memory-endpoint.json new file mode 100644 index 0000000000..03798ef2dc --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step20480-r2-memory-endpoint.json @@ -0,0 +1 @@ +{"schema_version": 1, "context_window": 20480, "context_fitted": false, "device": {"active_bytes": 113417570964, "cache_bytes": 0, "peak_bytes": 113457088420, "peak_scope": "since_start_or_health_reset"}} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step20480-r2-metrics.txt b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step20480-r2-metrics.txt new file mode 100644 index 0000000000..0a192205aa --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step20480-r2-metrics.txt @@ -0,0 +1,220 @@ +# HELP tensorfold:requests_running Requests in prefill or decode. +# TYPE tensorfold:requests_running gauge +tensorfold:requests_running 0 +# HELP tensorfold:requests_waiting Requests queued or held until a lane is free. +# TYPE tensorfold:requests_waiting gauge +tensorfold:requests_waiting 0 +# HELP tensorfold:generation_tokens_running Generated tokens held by live streams. +# TYPE tensorfold:generation_tokens_running gauge +tensorfold:generation_tokens_running 0 +# HELP tensorfold:prompt_tokens_total Prompt tokens of finished requests. +# TYPE tensorfold:prompt_tokens_total counter +tensorfold:prompt_tokens_total 16640 +# HELP tensorfold:generation_tokens_total Generated tokens of finished requests. +# TYPE tensorfold:generation_tokens_total counter +tensorfold:generation_tokens_total 2 +# HELP tensorfold:kv_cache_usage_ratio Tokens in a stream cache divided by that stream's context window. +# TYPE tensorfold:kv_cache_usage_ratio gauge +tensorfold:kv_cache_usage_ratio{pool="0"} 0 +# HELP tensorfold:mtp_drafted_total Draft tokens verified on finished requests. +# TYPE tensorfold:mtp_drafted_total counter +tensorfold:mtp_drafted_total 0 +# HELP tensorfold:mtp_accepted_total Draft tokens kept on finished requests. +# TYPE tensorfold:mtp_accepted_total counter +tensorfold:mtp_accepted_total 0 +# HELP tensorfold:request_latency_seconds Seconds from arrival to the reply leaving. +# TYPE tensorfold:request_latency_seconds histogram +tensorfold:request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:request_latency_seconds_bucket{le="0.5"} 1 +tensorfold:request_latency_seconds_bucket{le="1"} 1 +tensorfold:request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:request_latency_seconds_bucket{le="5"} 1 +tensorfold:request_latency_seconds_bucket{le="10"} 1 +tensorfold:request_latency_seconds_bucket{le="30"} 2 +tensorfold:request_latency_seconds_bucket{le="60"} 2 +tensorfold:request_latency_seconds_bucket{le="120"} 2 +tensorfold:request_latency_seconds_bucket{le="300"} 2 +tensorfold:request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:request_latency_seconds_sum 30.263797 +tensorfold:request_latency_seconds_count 2 +# HELP tensorfold:time_to_first_token_seconds Seconds from arrival to the first generated token. +# TYPE tensorfold:time_to_first_token_seconds histogram +tensorfold:time_to_first_token_seconds_bucket{le="0.01"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.05"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.1"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.25"} 0 +tensorfold:time_to_first_token_seconds_bucket{le="0.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="1"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="2.5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="5"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="10"} 1 +tensorfold:time_to_first_token_seconds_bucket{le="30"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="60"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="120"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="300"} 2 +tensorfold:time_to_first_token_seconds_bucket{le="+Inf"} 2 +tensorfold:time_to_first_token_seconds_sum 30.263464 +tensorfold:time_to_first_token_seconds_count 2 +# HELP tensorfold:request_decode_seconds Seconds a finished request spent decoding. Its sum over generation_tokens_total is the decode rate. +# TYPE tensorfold:request_decode_seconds histogram +tensorfold:request_decode_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_seconds_bucket{le="1"} 2 +tensorfold:request_decode_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_seconds_bucket{le="5"} 2 +tensorfold:request_decode_seconds_bucket{le="10"} 2 +tensorfold:request_decode_seconds_bucket{le="30"} 2 +tensorfold:request_decode_seconds_bucket{le="60"} 2 +tensorfold:request_decode_seconds_bucket{le="120"} 2 +tensorfold:request_decode_seconds_bucket{le="300"} 2 +tensorfold:request_decode_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_seconds_sum 0.000333 +tensorfold:request_decode_seconds_count 2 +# HELP tensorfold:request_time_per_output_token_seconds Seconds from the first generated token to the last, divided by the tokens less one. +# TYPE tensorfold:request_time_per_output_token_seconds histogram +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.005"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.0075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.01"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.015"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.02"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.025"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.03"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.04"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.05"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.075"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.15"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.2"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.3"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="0.5"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="1"} 0 +tensorfold:request_time_per_output_token_seconds_bucket{le="+Inf"} 0 +tensorfold:request_time_per_output_token_seconds_sum 0 +tensorfold:request_time_per_output_token_seconds_count 0 +# HELP tensorfold:decode_rounds_total Decode rounds used by finished requests. +# TYPE tensorfold:decode_rounds_total counter +tensorfold:decode_rounds_total 0 +# HELP tensorfold:request_prefill_seconds Seconds a finished request's prompt pass took. +# TYPE tensorfold:request_prefill_seconds histogram +tensorfold:request_prefill_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_seconds_bucket{le="0.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="1"} 1 +tensorfold:request_prefill_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_seconds_bucket{le="30"} 2 +tensorfold:request_prefill_seconds_bucket{le="60"} 2 +tensorfold:request_prefill_seconds_bucket{le="120"} 2 +tensorfold:request_prefill_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_seconds_sum 30.261974 +tensorfold:request_prefill_seconds_count 2 +# HELP tensorfold:process_resident_bytes Current resident set (VmRSS); device memory is not in it, so it is not a physical footprint (Linux). +# TYPE tensorfold:process_resident_bytes gauge +tensorfold:process_resident_bytes 78190227456 +# HELP tensorfold:process_resident_anon_bytes Current resident anonymous memory (RssAnon): heap, stacks and private maps (Linux). +# TYPE tensorfold:process_resident_anon_bytes gauge +tensorfold:process_resident_anon_bytes 32381673472 +# HELP tensorfold:process_resident_file_bytes Current resident file-backed memory (RssFile): the binary, libraries and mapped files (Linux). +# TYPE tensorfold:process_resident_file_bytes gauge +tensorfold:process_resident_file_bytes 45674291200 +# HELP tensorfold:process_resident_shmem_bytes Current resident shared memory (RssShmem): System V shared memory, tmpfs maps and shared anonymous maps (Linux). +# TYPE tensorfold:process_resident_shmem_bytes gauge +tensorfold:process_resident_shmem_bytes 134262784 +# HELP tensorfold:process_resident_peak_bytes Kernel lifetime peak resident set (VmHWM); never reset by health (Linux). +# TYPE tensorfold:process_resident_peak_bytes gauge +tensorfold:process_resident_peak_bytes 112889659392 +# HELP tensorfold:device_memory_bytes Device memory the engine holds now: weights, caches and live streams; only where the backend counts it (CUDA). +# TYPE tensorfold:device_memory_bytes gauge +tensorfold:device_memory_bytes 113417570964 +# HELP tensorfold:device_memory_peak_bytes The most device memory the engine has held since start or the last /health?reset_peak=1. +# TYPE tensorfold:device_memory_peak_bytes gauge +tensorfold:device_memory_peak_bytes 113457088420 +# HELP tensorfold:pinned_memory_bytes Pinned host memory the engine holds now: staging buffers and windows; only where the backend counts it (CUDA). +# TYPE tensorfold:pinned_memory_bytes gauge +tensorfold:pinned_memory_bytes 0 +# HELP tensorfold:num_requests_running Requests in prefill or decode. A mirror of tensorfold:requests_running. +# TYPE tensorfold:num_requests_running gauge +tensorfold:num_requests_running 0 +# HELP tensorfold:num_requests_waiting Requests queued or held until a lane is free. A mirror of tensorfold:requests_waiting. +# TYPE tensorfold:num_requests_waiting gauge +tensorfold:num_requests_waiting 0 +# HELP tensorfold:kv_cache_usage_perc A stream's cache occupancy under vLLM's name; same streams and ratios as tensorfold:kv_cache_usage_ratio. +# TYPE tensorfold:kv_cache_usage_perc gauge +tensorfold:kv_cache_usage_perc{stream="0"} 0 +# HELP tensorfold:spec_decode_num_draft_tokens_total Draft tokens verified on finished requests, this server's single draft counter. +# TYPE tensorfold:spec_decode_num_draft_tokens_total counter +tensorfold:spec_decode_num_draft_tokens_total 0 +# HELP tensorfold:spec_decode_num_accepted_tokens_total Draft tokens kept on finished requests. +# TYPE tensorfold:spec_decode_num_accepted_tokens_total counter +tensorfold:spec_decode_num_accepted_tokens_total 0 +# HELP tensorfold:e2e_request_latency_seconds Seconds from arrival to the reply leaving, under vLLM's name. +# TYPE tensorfold:e2e_request_latency_seconds histogram +tensorfold:e2e_request_latency_seconds_bucket{le="0.01"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.05"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.1"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.25"} 0 +tensorfold:e2e_request_latency_seconds_bucket{le="0.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="1"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="2.5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="5"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="10"} 1 +tensorfold:e2e_request_latency_seconds_bucket{le="30"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="60"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="120"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="300"} 2 +tensorfold:e2e_request_latency_seconds_bucket{le="+Inf"} 2 +tensorfold:e2e_request_latency_seconds_sum 30.263797 +tensorfold:e2e_request_latency_seconds_count 2 +# HELP tensorfold:request_decode_time_seconds Seconds a finished request spent decoding, under vLLM's name. +# TYPE tensorfold:request_decode_time_seconds histogram +tensorfold:request_decode_time_seconds_bucket{le="0.01"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.05"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.25"} 2 +tensorfold:request_decode_time_seconds_bucket{le="0.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="1"} 2 +tensorfold:request_decode_time_seconds_bucket{le="2.5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="5"} 2 +tensorfold:request_decode_time_seconds_bucket{le="10"} 2 +tensorfold:request_decode_time_seconds_bucket{le="30"} 2 +tensorfold:request_decode_time_seconds_bucket{le="60"} 2 +tensorfold:request_decode_time_seconds_bucket{le="120"} 2 +tensorfold:request_decode_time_seconds_bucket{le="300"} 2 +tensorfold:request_decode_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_decode_time_seconds_sum 0.000333 +tensorfold:request_decode_time_seconds_count 2 +# HELP tensorfold:request_prefill_time_seconds Seconds a finished request's prompt pass took, under vLLM's name. +# TYPE tensorfold:request_prefill_time_seconds histogram +tensorfold:request_prefill_time_seconds_bucket{le="0.01"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.05"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.1"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.25"} 0 +tensorfold:request_prefill_time_seconds_bucket{le="0.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="1"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="2.5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="5"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="10"} 1 +tensorfold:request_prefill_time_seconds_bucket{le="30"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="60"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="120"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="300"} 2 +tensorfold:request_prefill_time_seconds_bucket{le="+Inf"} 2 +tensorfold:request_prefill_time_seconds_sum 30.261974 +tensorfold:request_prefill_time_seconds_count 2 +# HELP tensorfold:client_disconnections_total Requests a client left before the reply left the server. +# TYPE tensorfold:client_disconnections_total counter +tensorfold:client_disconnections_total 0 +# HELP tensorfold:preemptions_total Requests that had to give a lane up to a later one. +# TYPE tensorfold:preemptions_total counter +tensorfold:preemptions_total 0 diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step20480-r2-samples.jsonl b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step20480-r2-samples.jsonl new file mode 100644 index 0000000000..eb2a68ee29 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/memory/mem-new-step20480-r2-samples.jsonl @@ -0,0 +1,55 @@ +{"t_s": 0.0, "VmRSS_bytes": 49917952, "VmHWM_bytes": 49917952, "Pss_bytes": 50084864, 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285, 745, 25, 198, 309, 653, 51891, 5368, 1000, 381, 31233, 430, 264, 10675, 22419, 11, 321, 198, 309, 653, 1510, 723, 63, 2493, 381, 12098, 290, 13, 13891, 25, 198, 309, 638, 3708, 32331, 9, 21112, 837, 271, 262, 687, 3814, 1502, 823, 1153, 11, 2357, 1590, 198, 285, 687, 3165, 2997, 3042, 14031, 5781, 11, 343, 1590, 198, 309, 638, 5258, 21740, 5781, 8, 198, 309, 638, 3708, 18323, 11957, 198, 309, 638, 5258, 21740, 3620, 8, 271, 285, 687, 3165, 5457, 5225, 1590, 198, 309, 580, 11, 343, 283, 1455, 198, 309, 413, 580, 369, 2168, 25, 198, 388, 653, 364, 10675, 30047, 286, 5497, 303, 94231, 313, 332, 13215, 88, 1170, 220, 17, 3307, 198, 388, 653, 1436, 387, 8924, 220, 19, 19, 23, 364, 3447, 198, 388, 638, 3708, 88243, 871, 198, 388, 638, 949, 10132, 1931, 738, 2410, 4551, 1931, 738, 21704, 6277, 11, 343, 8, 198, 388, 638, 5258, 21740, 3620, 8, 198, 309, 745, 25, 198, 388, 3165, 2997, 3042, 14031, 5781, 11, 343, 8, 271, 285, 440, 638, 31919, 2277, 13575, 487, 77769, 35821, 198, 309, 638, 13734, 20852, 7, 198, 388, 12102, 25, 638, 3708, 12548, 57308, 3165, 5457, 11, 10002, 6742, 8850, 11, 2357, 10341, 8, 198, 309, 847, 271, 262, 687, 3814, 1102, 5871, 1153, 11, 2357, 1590, 198, 285, 440, 638, 31919, 2277, 10796, 7, 198, 309, 328, 12548, 198, 309, 328, 11250, 198, 309, 2343, 6742, 15385, 2491, 8, 606, 220, 15, 466, 638, 652, 10132, 1931, 738, 6742, 8, 835, 696, 4551, 1931, 738, 810, 85759, 198, 285, 16026, 198, 309, 638, 9328, 6900, 1153, 5258, 21740, 11, 2357, 15385, 2491, 8, 271, 262, 632, 445, 283, 5046, 623, 1565, 763, 49545, 487, 328, 2536, 763, 328, 1856, 487, 328, 52, 2143, 763, 6421, 487, 328, 1966, 386, 763, 6320, 8934, 198, 262, 632, 445, 10132, 1931, 738, 283, 313, 198, 285, 328, 1856, 763, 696, 4551, 1931, 738, 39082, 11, 198, 285, 49545, 763, 696, 4551, 1931, 738, 959, 6609, 842, 11, 198, 285, 6421, 763, 696, 4551, 1931, 738, 959, 6609, 842, 11, 198, 285, 6320, 763, 696, 4551, 1931, 738, 959, 6609, 842, 11, 198, 262, 333, 271, 262, 687, 3814, 39343, 640, 6903, 1153, 11, 2357, 1590, 198, 285, 5497, 283, 638, 6109, 445, 28920, 11686, 4692, 1005, 47719, 591, 548, 60, 198, 285, 5497, 10132, 1931, 738, 283, 638, 6109, 445, 10132, 1931, 738, 58, 7636, 60, 198, 285, 440, 638, 22970, 605, 532, 4268, 76382, 10132, 1931, 738, 11, 2357, 1590, 198, 309, 638, 3708, 76382, 8, 198, 309, 653, 7911, 60467, 17437, 11, 82956, 3835, 8, 12752, 914, 381, 18101, 198, 309, 653, 494, 279, 869, 781, 8900, 11, 318, 68, 1257, 25, 478, 16, 4370, 314, 478, 220, 16, 8, 198, 309, 413, 5497, 10132, 1931, 738, 369, 524, 696, 4551, 1931, 738, 959, 6609, 842, 25, 198, 388, 638, 3708, 437, 11957, 198, 309, 638, 949, 10132, 1931, 738, 76382, 10132, 1931, 738, 11, 2357, 13, 39270, 8, 198, 309, 638, 5258, 21740, 6742, 13, 39270, 8, 271, 262, 9261, 445, 283, 313, 198, 285, 328, 2143, 763, 6421, 487, 198, 285, 328, 3036, 763, 74581, 198, 285, 328, 39067, 763, 77182, 198, 285, 328, 11242, 39067, 763, 8168, 487, 198, 285, 328, 12151, 763, 62471, 198, 285, 328, 4312, 763, 5775, 487, 198, 285, 328, 43, 24054, 763, 14291, 487, 198, 285, 328, 49, 24054, 763, 328, 2372, 487, 198, 285, 328, 8085, 2126, 763, 24403, 487, 198, 285, 328, 8085, 55, 269, 763, 38591, 487, 198, 285, 328, 8085, 2939, 763, 13012, 487, 198, 285, 328, 49712, 12151, 763, 34397, 487, 198, 285, 328, 64333, 763, 65667, 487, 198, 262, 333, 271, 262, 9261, 445, 10132, 1931, 738, 283, 313, 198, 285, 6421, 763, 696, 4551, 1931, 738, 67389, 4014, 11, 198, 285, 6320, 763, 696, 4551, 1931, 738, 67389, 4014, 11, 198, 285, 15171, 763, 696, 4551, 1931, 738, 810, 37438, 11, 198, 285, 8168, 763, 696, 4551, 1931, 738, 810, 37438, 11, 198, 285, 3405, 763, 696, 4551, 1931, 738, 810, 37438, 11, 198, 285, 5775, 763, 696, 4551, 1931, 738, 810, 37438, 11, 198, 285, 14291, 763, 696, 4551, 1931, 738, 42643, 13882, 11, 198, 285, 328, 2372, 763, 696, 4551, 1931, 738, 42643, 13882, 11, 198, 285, 24403, 763, 696, 4551, 1931, 738, 1722, 842, 11, 198, 285, 38591, 763, 696, 4551, 1931, 738, 1722, 55, 842, 11, 198, 285, 13012, 763, 696, 4551, 1931, 738, 1722, 3843, 11, 198, 285, 34397, 763, 696, 4551, 1931, 738, 810, 37438, 11, 198, 285, 65667, 763, 696, 4551, 1931, 738, 1034, 19291, 11, 198, 262, 333, 271, 262, 9261, 445, 1650, 45310, 283, 12431, 17991, 294, 29860, 332, 487, 578, 198, 262, 687, 3814, 1609, 258, 6903, 1153, 11, 2357, 1590, 198, 285, 5497, 283, 638, 28434, 445, 28920, 11686, 4692, 1005, 47719, 591, 548, 60, 198, 285, 5497, 10132, 1931, 738, 283, 638, 28434, 445, 10132, 1931, 738, 58, 7636, 60, 198, 285, 440, 638, 22970, 605, 532, 4268, 76382, 10132, 1931, 738, 11, 2357, 1590, 198, 309, 413, 5497, 303, 638, 28434, 445, 1650, 45310, 25, 198, 388, 2047, 10132, 1931, 738, 283, 5497, 10132, 1931, 738, 4381, 363, 198, 388, 1245, 10132, 1931, 738, 283, 5497, 10132, 1931, 738, 198, 309, 745, 25, 198, 388, 2047, 10132, 1931, 738, 283, 5497, 10132, 1931, 738, 198, 388, 1245, 10132, 1931, 738, 283, 5497, 10132, 1931, 738, 4381, 363, 271, 309, 638, 949, 10132, 1931, 738, 17145, 10132, 1931, 738, 11, 2357, 8014, 8, 198, 309, 638, 5258, 21740, 6742, 8014, 8, 198, 309, 638, 3708, 925, 1, 313, 7636, 92, 11957, 198, 309, 638, 949, 10132, 1931, 738, 26806, 10132, 1931, 738, 11, 2357, 9236, 8, 198, 309, 638, 5258, 21740, 6742, 9236, 8, 271, 262, 25255, 3595, 283, 313, 198, 285, 328, 26429, 763, 95242, 487, 198, 285, 328, 2536, 26429, 763, 51292, 20713, 198, 285, 328, 84637, 763, 3919, 487, 198, 285, 328, 84637, 36, 763, 3919, 20713, 198, 285, 328, 38, 83, 763, 328, 20507, 198, 285, 328, 38, 83, 36, 763, 28013, 20713, 198, 285, 328, 3742, 763, 328, 284, 487, 198, 285, 328, 3742, 2536, 763, 328, 284, 524, 487, 198, 285, 328, 623, 763, 328, 258, 487, 198, 285, 328, 2536, 623, 763, 328, 1856, 303, 487, 198, 262, 333, 271, 262, 687, 3814, 16449, 3271, 1153, 11, 2357, 1590, 198, 285, 440, 638, 22970, 605, 532, 4268, 2410, 4551, 1931, 738, 707, 5602, 11, 2357, 1590, 198, 309, 638, 949, 10132, 1931, 738, 2410, 4551, 1931, 738, 707, 5602, 4381, 1453, 2357, 8014, 11, 348, 3394, 877, 1671, 2878, 8, 198, 309, 638, 5258, 21740, 6742, 8014, 8, 198, 309, 364, 296, 11, 378, 303, 10002, 6742, 45214, 11, 2357, 877, 1671, 2878, 1590, 198, 388, 638, 3708, 437, 328, 478, 638, 508, 1261, 3595, 46634, 4692, 1005, 47719, 591, 548, 60, 478, 328, 11957, 198, 388, 638, 5258, 21740, 1958, 8, 271, 262, 1744, 3595, 283, 5046, 2939, 763, 328, 429, 487, 328, 2126, 763, 328, 269, 8934, 198, 262, 1744, 445, 10132, 1931, 738, 283, 5046, 429, 763, 696, 4551, 1931, 738, 849, 7812, 11, 328, 269, 763, 696, 4551, 1931, 738, 75232, 92, 271, 262, 687, 3814, 77193, 6903, 1153, 11, 2357, 1590, 198, 285, 5497, 283, 638, 27849, 3595, 28920, 11686, 4692, 1005, 47719, 591, 548, 60, 198, 285, 5497, 10132, 1931, 738, 283, 638, 27849, 445, 10132, 1931, 738, 58, 7636, 60, 271, 285, 687, 7459, 8016, 3430, 21740, 6742, 1590, 198, 309, 2397, 2359, 5497, 10132, 1931, 738, 198, 309, 5497, 10132, 1931, 738, 283, 5497, 10132, 1931, 738, 4381, 363, 198, 309, 638, 949, 10132, 1931, 738, 76382, 10132, 1931, 738, 11, 2357, 8, 198, 309, 638, 5258, 21740, 6742, 8, 271, 285, 440, 638, 22970, 605, 532, 4268, 76382, 10132, 1931, 738, 11, 2357, 1590, 198, 309, 274, 283, 281, 1, 313, 7636, 92, 328, 198, 309, 638, 13734, 20852, 17664, 25, 638, 3708, 1104, 681, 7459, 8016, 3430, 21740, 11, 2357, 10341, 8, 271, 262, 687, 3814, 53714, 2130, 1153, 11, 2357, 1590, 198, 285, 638, 949, 10132, 1931, 738, 2410, 4551, 1931, 738, 13, 75266, 11, 2357, 2733, 8, 198, 285, 638, 5258, 21740, 6742, 2733, 8, 198, 285, 653, 9493, 1105, 25, 220, 18, 4692, 3325, 91514, 369, 264, 18890, 1412, 11, 748, 413, 2357, 2733, 198, 285, 653, 369, 449, 7308, 22419, 1179, 567, 1144, 310, 2892, 36688, 26025, 198, 285, 653, 424, 466, 884, 449, 4799, 3433, 310, 615, 220, 18, 641, 548, 3325, 548, 973, 198, 285, 413, 11074, 6742, 2733, 11, 18722, 8, 321, 11074, 6742, 2733, 2733, 11, 514, 1590, 198, 309, 638, 3708, 437, 11957, 198, 285, 638, 3708, 90609, 198, 285, 638, 3708, 6742, 12475, 8, 271, 262, 687, 3814, 73427, 1153, 11, 2357, 1590, 198, 285, 638, 949, 10132, 1931, 738, 2410, 4551, 1931, 738, 13, 75266, 11, 2357, 18859, 8, 198, 285, 638, 5258, 21740, 6742, 18859, 8, 198, 285, 440, 638, 31919, 2277, 437, 12548, 11957, 35821, 198, 309, 30644, 283, 3439, 198, 309, 364, 378, 303, 2357, 15884, 25, 198, 388, 413, 30644, 25, 198, 493, 638, 3708, 12548, 11957, 198, 388, 745, 25, 198, 493, 30644, 283, 2912, 198, 388, 638, 5258, 21740, 1958, 8, 198, 309, 364, 378, 303, 2357, 84152, 25, 198, 388, 413, 30644, 25, 198, 493, 638, 3708, 12548, 11957, 198, 388, 745, 25, 198, 493, 30644, 283, 2912, 198, 388, 638, 5258, 21740, 1958, 8, 271, 262, 687, 3814, 35158, 2208, 1153, 11, 2357, 1590, 198, 285, 687, 369, 20974, 14683, 21102, 72716, 3042, 1590, 198, 309, 460, 318, 198, 388, 11074, 72716, 3042, 11, 23846, 8, 198, 388, 321, 15511, 3042, 15385, 2491, 198, 309, 847, 271, 285, 638, 949, 10132, 1931, 738, 2410, 4551, 1931, 738, 13, 75266, 11, 2357, 2733, 8, 198, 285, 638, 5258, 21740, 6742, 2733, 8, 198, 285, 440, 638, 31919, 2277, 10618, 487, 20644, 35821, 198, 309, 413, 369, 20974, 14683, 21102, 6742, 14112, 1590, 198, 388, 653, 71458, 628, 381, 38136, 413, 279, 13992, 4290, 914, 4147, 198, 388, 638, 9328, 6900, 1153, 5258, 21740, 11, 2357, 14112, 15385, 2491, 8, 198, 309, 745, 25, 198, 388, 638, 5258, 21740, 6742, 14112, 8, 271, 262, 687, 3814, 62, 12335, 1114, 1153, 11, 2357, 1590, 198, 285, 638, 3708, 28625, 871, 198, 285, 638, 949, 10132, 1931, 738, 2410, 4551, 1931, 738, 21704, 6277, 11, 2357, 2733, 8, 198, 285, 638, 5258, 21740, 6742, 2733, 8, 271, 262, 687, 3814, 2021, 636, 45823, 1153, 11, 2357, 1590, 198, 285, 638, 3708, 437, 1076, 871, 271, 262, 687, 3814, 1063, 4601, 1153, 11, 2357, 1590, 198, 285, 413, 2357, 17534, 25, 198, 309, 638, 5258, 21740, 6742, 17534, 8, 198, 285, 638, 3708, 18323, 871, 198, 285, 413, 2357, 32550, 25, 198, 309, 638, 5258, 21740, 6742, 32550, 8, 198, 285, 413, 2357, 20807, 25, 198, 309, 638, 3708, 18323, 871, 198, 309, 638, 5258, 21740, 6742, 20807, 8, 271, 262, 687, 3814, 1203, 730, 1153, 11, 2357, 1590, 198, 285, 638, 12110, 437, 6146, 11957, 198, 285, 638, 5258, 21740, 6742, 32140, 8, 198, 285, 440, 638, 15236, 4406, 198, 309, 364, 1105, 303, 2357, 508, 2191, 25, 198, 388, 638, 5258, 21740, 57468, 8, 271, 262, 687, 3814, 5868, 1153, 11, 2357, 1590, 198, 285, 638, 3708, 6742, 20536, 8, 198, 285, 413, 2357, 4905, 25, 198, 309, 638, 3708, 18323, 11957, 198, 309, 638, 5258, 21740, 6742, 4905, 8, 271, 262, 687, 3814, 41997, 1153, 11, 2357, 1590, 198, 285, 1118, 283, 2912, 198, 285, 653, 4472, 5789, 198, 285, 660, 8125, 283, 2357, 12633, 3138, 2048, 478, 2357, 15884, 198, 285, 16184, 283, 498, 3928, 60, 348, 318, 2798, 19766, 8125, 8, 471, 2343, 6742, 42489, 578, 478, 2357, 42489, 198, 285, 364, 1857, 11, 5255, 303, 12867, 36981, 19766, 8125, 11, 16184, 681, 220, 16, 1590, 198, 309, 264, 11, 293, 283, 5255, 198, 309, 413, 1118, 25, 198, 388, 1118, 283, 3439, 198, 309, 745, 25, 198, 388, 638, 3708, 12548, 11957, 198, 309, 638, 5258, 21740, 2784, 8, 198, 309, 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493, 638, 3708, 64138, 8, 198, 493, 638, 5258, 21740, 1446, 8, 271, 285, 653, 16010, 198, 285, 413, 2357, 5037, 86, 832, 25, 198, 309, 413, 1118, 25, 198, 388, 1118, 283, 3439, 198, 309, 745, 25, 198, 388, 638, 3708, 12548, 11957, 198, 309, 638, 3708, 88243, 1, 478, 2357, 5037, 86, 832, 20536, 8, 198, 309, 413, 2357, 5037, 86, 832, 4905, 25, 198, 388, 638, 3708, 18323, 11957, 198, 388, 638, 5258, 21740, 6742, 5037, 86, 832, 4905, 8, 271, 262, 687, 3814, 44297, 1153, 11, 2357, 1590, 198, 285, 413, 2357, 20536, 369, 2168, 25, 198, 309, 638, 3708, 88243, 871, 198, 285, 745, 25, 198, 309, 638, 3708, 6742, 20536, 8, 198, 309, 638, 3708, 64138, 8, 198, 285, 638, 5258, 21740, 6742, 2733, 8, 271, 262, 687, 3814, 2275, 5520, 1153, 11, 2357, 1590, 198, 285, 440, 638, 22970, 605, 532, 4268, 2410, 4551, 1931, 738, 71003, 11, 2357, 1590, 198, 309, 638, 3708, 437, 12564, 871, 198, 309, 440, 638, 23690, 290, 363, 430, 4011, 25, 198, 388, 638, 5258, 21740, 6742, 15884, 8, 198, 309, 413, 4011, 25, 198, 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2357, 46277, 8, 271, 262, 687, 3814, 1548, 263, 2359, 1153, 11, 2357, 1590, 198, 285, 638, 12110, 437, 6082, 2359, 11957, 198, 285, 638, 13734, 20852, 17664, 25, 638, 3708, 12548, 57308, 638, 3708, 11, 2357, 46277, 8, 271, 262, 687, 3814, 1511, 11158, 1153, 11, 2357, 1590, 198, 285, 440, 638, 22970, 605, 532, 4268, 2410, 4551, 1931, 738, 849, 68620, 11, 2357, 1590, 198, 309, 638, 3708, 437, 11093, 871, 198, 309, 413, 2357, 2733, 25, 198, 388, 638, 3708, 437, 11957, 198, 388, 638, 949, 10132, 1931, 738, 2410, 4551, 1931, 738, 13, 75266, 11, 2357, 2733, 8, 198, 388, 638, 5258, 21740, 6742, 2733, 8, 271, 262, 687, 3814, 10311, 790, 1153, 11, 2357, 1590, 198, 285, 440, 638, 22970, 605, 532, 4268, 2410, 4551, 1931, 738, 7272, 10056, 11, 2357, 1590, 198, 309, 638, 3708, 437, 28726, 871, 198, 309, 413, 2357, 2733, 25, 198, 388, 638, 3708, 437, 11957, 198, 388, 638, 949, 10132, 1931, 738, 2410, 4551, 1931, 738, 13, 75266, 11, 2357, 2733, 8, 198, 388, 638, 5258, 21740, 6742, 2733, 8, 271, 262, 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6336, 8, 198, 285, 638, 3708, 437, 303, 11957, 198, 285, 638, 949, 10132, 1931, 738, 2410, 4551, 1931, 738, 71003, 4381, 1453, 2357, 18879, 11, 348, 3394, 13, 21163, 8, 198, 285, 638, 5258, 21740, 6742, 18879, 8, 198, 285, 364, 413, 55604, 303, 2357, 13, 21163, 25, 198, 309, 638, 3708, 437, 413, 11957, 198, 309, 638, 5258, 21740, 32230, 55604, 8, 271, 262, 687, 3814, 62, 2592, 7780, 1153, 11, 2357, 1590, 198, 285, 440, 638, 22970, 605, 532, 4268, 2410, 4551, 1931, 738, 71003, 11, 2357, 1590, 198, 309, 638, 949, 10132, 1931, 738, 2410, 4551, 1931, 738, 71003, 4381, 1453, 2357, 4917, 11, 2357, 5772, 8, 198, 309, 638, 5258, 21740, 6742, 4917, 8, 198, 309, 638, 3708, 437, 413, 11957, 198, 309, 638, 5258, 21740, 6742, 5772, 8, 198, 309, 638, 3708, 437, 745, 11957, 198, 309, 638, 949, 10132, 1931, 738, 2410, 4551, 1931, 738, 71003, 11, 2357, 13, 451, 84755, 8, 198, 309, 638, 5258, 21740, 6742, 13, 451, 84755, 8, 271, 262, 687, 3814, 14383, 1153, 11, 2357, 1590, 198, 285, 413, 2357, 15385, 2491, 25, 198, 309, 440, 638, 31919, 2277, 13575, 487, 77769, 35821, 198, 388, 638, 13734, 20852, 17664, 25, 638, 3708, 12548, 57308, 638, 5258, 21740, 11, 2357, 15385, 2491, 8, 198, 285, 745, 25, 198, 309, 653, 51891, 5368, 1000, 381, 31233, 430, 264, 10675, 22419, 11, 321, 198, 309, 653, 1510, 723, 63, 2493, 381, 12098, 290, 13, 13891, 25, 198, 309, 638, 3708, 32331, 9, 21112, 837, 271, 262, 687, 3814, 1502, 823, 1153, 11, 2357, 1590, 198, 285, 687, 3165, 2997, 3042, 14031, 5781, 11, 343, 1590, 198, 309, 638, 5258, 21740, 5781, 8, 198, 309, 638, 3708, 18323, 11957, 198, 309, 638, 5258, 21740, 3620, 8, 271, 285, 687, 3165, 5457, 5225, 1590, 198, 309, 580, 11, 343, 283, 1455, 198, 309, 413, 580, 369, 2168, 25, 198, 388, 653, 364, 10675, 30047, 286, 5497, 303, 94231, 313, 332, 13215, 88, 1170, 220, 17, 3307, 198, 388, 653, 1436, 387, 8924, 220, 19, 19, 23, 364, 3447, 198, 388, 638, 3708, 88243, 871, 198, 388, 638, 949, 10132, 1931, 738, 2410, 4551, 1931, 738, 21704, 6277, 11, 343, 8, 198, 388, 638, 5258, 21740, 3620, 8, 198, 309, 745, 25, 198, 388, 3165, 2997, 3042, 14031, 5781, 11, 343, 8, 271, 285, 440, 638, 31919, 2277, 13575, 487, 77769, 35821, 198, 309, 638, 13734, 20852, 7, 198, 388, 12102, 25, 638, 3708, 12548, 57308, 3165, 5457, 11, 10002, 6742, 8850, 11, 2357, 10341, 8, 198, 309, 847, 271, 262, 687, 3814, 1102, 5871, 1153, 11, 2357, 1590, 198, 285, 440, 638, 31919, 2277, 10796, 7, 198, 309, 328, 12548, 198, 309, 328, 11250, 198, 309, 2343, 6742, 15385, 2491, 8, 606, 220, 15, 466, 638, 652, 10132, 1931, 738, 6742, 8, 835, 696, 4551, 1931, 738, 810, 85759, 198, 285, 16026, 198, 309, 638, 9328, 6900, 1153, 5258, 21740, 11, 2357, 15385, 2491, 8, 271, 262, 632, 445, 283, 5046, 623, 1565, 763, 49545, 487, 328, 2536, 763, 328, 1856, 487, 328, 52, 2143, 763, 6421, 487, 328, 1966, 386, 763, 6320, 8934, 198, 262, 632, 445, 10132, 1931, 738, 283, 313, 198, 285, 328, 1856, 763, 696, 4551, 1931, 738, 39082, 11, 198, 285, 49545, 763, 696, 4551, 1931, 738, 959, 6609, 842, 11, 198, 285, 6421, 763, 696, 4551, 1931, 738, 959, 6609, 842, 11, 198, 285, 6320, 763, 696, 4551, 1931, 738, 959, 6609, 842, 11, 198, 262, 333, 271, 262, 687, 3814, 39343, 640, 6903, 1153, 11, 2357, 1590, 198, 285, 5497, 283, 638, 6109, 445, 28920, 11686, 4692, 1005, 47719, 591, 548, 60, 198, 285, 5497, 10132, 1931, 738, 283, 638, 6109, 445, 10132, 1931, 738, 58, 7636, 60, 198, 285, 440, 638, 22970, 605, 532, 4268, 76382, 10132, 1931, 738, 11, 2357, 1590, 198, 309, 638, 3708, 76382, 8, 198, 309, 653, 7911, 60467, 17437, 11, 82956, 3835, 8, 12752, 914, 381, 18101, 198, 309, 653, 494, 279, 869, 781, 8900, 11, 318, 68, 1257, 25, 478, 16, 4370, 314, 478, 220, 16, 8, 198, 309, 413, 5497, 10132, 1931, 738, 369, 524, 696, 4551, 1931, 738, 959, 6609, 842, 25, 198, 388, 638, 3708, 437, 11957, 198, 309, 638, 949, 10132, 1931, 738, 76382, 10132, 1931, 738, 11, 2357, 13, 39270, 8, 198, 309, 638, 5258, 21740, 6742, 13, 39270, 8, 271, 262, 9261, 445, 283, 313, 198, 285, 328, 2143, 763, 6421, 487, 198, 285, 328, 3036, 763, 74581, 198, 285, 328, 39067, 763, 77182, 198, 285, 328, 11242, 39067, 763, 8168, 487, 198, 285, 328, 12151, 763, 62471, 198, 285, 328, 4312, 763, 5775, 487, 198, 285, 328, 43, 24054, 763, 14291, 487, 198, 285, 328, 49, 24054, 763, 328, 2372, 487, 198, 285, 328, 8085, 2126, 763, 24403, 487, 198, 285, 328, 8085, 55, 269, 763, 38591, 487, 198, 285, 328, 8085, 2939, 763, 13012, 487, 198, 285, 328, 49712, 12151, 763, 34397, 487, 198, 285, 328, 64333, 763, 65667, 487, 198, 262, 333, 271, 262, 9261, 445, 10132, 1931, 738, 283, 313, 198, 285, 6421, 763, 696, 4551, 1931, 738, 67389, 4014, 11, 198, 285, 6320, 763, 696, 4551, 1931, 738, 67389, 4014, 11, 198, 285, 15171, 763, 696, 4551, 1931, 738, 810, 37438, 11, 198, 285, 8168, 763, 696, 4551, 1931, 738, 810, 37438, 11, 198, 285, 3405, 763, 696, 4551, 1931, 738, 810, 37438, 11, 198, 285, 5775, 763, 696, 4551, 1931, 738, 810, 37438, 11, 198, 285, 14291, 763, 696, 4551, 1931, 738, 42643, 13882, 11, 198, 285, 328, 2372, 763, 696, 4551, 1931, 738, 42643, 13882, 11, 198, 285, 24403, 763, 696, 4551, 1931, 738, 1722, 842, 11, 198, 285, 38591, 763, 696, 4551, 1931, 738, 1722, 55, 842, 11, 198, 285, 13012, 763, 696, 4551, 1931, 738, 1722, 3843, 11, 198, 285, 34397, 763, 696, 4551, 1931, 738, 810, 37438, 11, 198, 285, 65667, 763, 696, 4551, 1931, 738, 1034, 19291, 11, 198, 262, 333, 271, 262, 9261, 445, 1650, 45310, 283, 12431, 17991, 294, 29860, 332, 487, 578, 198, 262, 687, 3814, 1609, 258, 6903, 1153, 11, 2357, 1590, 198, 285, 5497, 283, 638, 28434, 445, 28920, 11686, 4692, 1005, 47719, 591, 548, 60, 198, 285, 5497, 10132, 1931, 738, 283, 638, 28434, 445, 10132, 1931, 738, 58, 7636, 60, 198, 285, 440, 638, 22970, 605, 532, 4268, 76382, 10132, 1931, 738, 11, 2357, 1590, 198, 309, 413, 5497, 303, 638, 28434, 445, 1650, 45310, 25, 198, 388, 2047, 10132, 1931, 738, 283, 5497, 10132, 1931, 738, 4381, 363, 198, 388, 1245, 10132, 1931, 738, 283, 5497, 10132, 1931, 738, 198, 309, 745, 25, 198, 388, 2047, 10132, 1931, 738, 283, 5497, 10132, 1931, 738, 198, 388, 1245, 10132, 1931, 738, 283, 5497, 10132, 1931, 738, 4381, 363, 271, 309, 638, 949, 10132, 1931, 738, 17145, 10132, 1931, 738, 11, 2357, 8014, 8, 198, 309, 638, 5258, 21740, 6742, 8014, 8, 198, 309, 638, 3708, 925, 1, 313, 7636, 92, 11957, 198, 309, 638, 949, 10132, 1931, 738, 26806, 10132, 1931, 738, 11, 2357, 9236, 8, 198, 309, 638, 5258, 21740, 6742, 9236, 8, 271, 262, 25255, 3595, 283, 313, 198, 285, 328, 26429, 763, 95242, 487, 198, 285, 328, 2536, 26429, 763, 51292, 20713, 198, 285, 328, 84637, 763, 3919, 487, 198, 285, 328, 84637, 36, 763, 3919, 20713, 198, 285, 328, 38, 83, 763, 328, 20507, 198, 285, 328, 38, 83, 36, 763, 28013, 20713, 198, 285, 328, 3742, 763, 328, 284, 487, 198, 285, 328, 3742, 2536, 763, 328, 284, 524, 487, 198, 285, 328, 623, 763, 328, 258, 487, 198, 285, 328, 2536, 623, 763, 328, 1856, 303, 487, 198, 262, 333, 271, 262, 687, 3814, 16449, 3271, 1153, 11, 2357, 1590, 198, 285, 440, 638, 22970, 605, 532, 4268, 2410, 4551, 1931, 738, 707, 5602, 11, 2357, 1590, 198, 309, 638, 949, 10132, 1931, 738, 2410, 4551, 1931, 738, 707, 5602, 4381, 1453, 2357, 8014, 11, 348, 3394, 877, 1671, 2878, 8, 198, 309, 638, 5258, 21740, 6742, 8014, 8, 198, 309, 364, 296, 11, 378, 303, 10002, 6742, 45214, 11, 2357, 877, 1671, 2878, 1590, 198, 388, 638, 3708, 437, 328, 478, 638, 508, 1261, 3595, 46634, 4692, 1005, 47719, 591, 548, 60, 478, 328, 11957, 198, 388, 638, 5258, 21740, 1958, 8, 271, 262, 1744, 3595, 283, 5046, 2939, 763, 328, 429, 487, 328, 2126, 763, 328, 269, 8934, 198, 262, 1744, 445, 10132, 1931, 738, 283, 5046, 429, 763, 696, 4551, 1931, 738, 849, 7812, 11, 328, 269, 763, 696, 4551, 1931, 738, 75232, 92, 271, 262, 687, 3814, 77193, 6903, 1153, 11, 2357, 1590, 198, 285, 5497, 283, 638, 27849, 3595, 28920, 11686, 4692, 1005, 47719, 591, 548, 60, 198, 285, 5497, 10132, 1931, 738, 283, 638, 27849, 445, 10132, 1931, 738, 58, 7636, 60, 271, 285, 687, 7459, 8016, 3430, 21740, 6742, 1590, 198, 309, 2397, 2359, 5497, 10132, 1931, 738, 198, 309, 5497, 10132, 1931, 738, 283, 5497, 10132, 1931, 738, 4381, 363, 198, 309, 638, 949, 10132, 1931, 738, 76382, 10132, 1931, 738, 11, 2357, 8, 198, 309, 638, 5258, 21740, 6742, 8, 271, 285, 440, 638, 22970, 605, 532, 4268, 76382, 10132, 1931, 738, 11, 2357, 1590, 198, 309, 274, 283, 281, 1, 313, 7636, 92, 328, 198, 309, 638, 13734, 20852, 17664, 25, 638, 3708, 1104, 681, 7459, 8016, 3430, 21740, 11, 2357, 10341, 8, 271, 262, 687, 3814, 53714, 2130, 1153, 11, 2357, 1590, 198, 285, 638, 949, 10132, 1931, 738, 2410, 4551, 1931, 738, 13, 75266, 11, 2357, 2733, 8, 198, 285, 638, 5258, 21740, 6742, 2733, 8, 198, 285, 653, 9493, 1105, 25, 220, 18, 4692, 3325, 91514, 369, 264, 18890, 1412, 11, 748, 413, 2357, 2733, 198, 285, 653, 369, 449, 7308, 22419, 1179, 567, 1144, 310, 2892, 36688, 26025, 198, 285, 653, 424, 466, 884, 449, 4799, 3433, 310, 615, 220, 18, 641, 548, 3325, 548, 973, 198, 285, 413, 11074, 6742, 2733, 11, 18722, 8, 321, 11074, 6742, 2733, 2733, 11, 514, 1590, 198, 309, 638, 3708, 437, 11957, 198, 285, 638, 3708, 90609, 198, 285, 638, 3708, 6742, 12475, 8, 271, 262, 687, 3814, 73427, 1153, 11, 2357, 1590, 198, 285, 638, 949, 10132, 1931, 738, 2410, 4551, 1931, 738, 13, 75266, 11, 2357, 18859, 8, 198, 285, 638, 5258, 21740, 6742, 18859, 8, 198, 285, 440, 638, 31919, 2277, 437, 12548, 11957, 35821, 198, 309, 30644, 283, 3439, 198, 309, 364, 378, 303, 2357, 15884, 25, 198, 388, 413, 30644, 25, 198, 493, 638, 3708, 12548, 11957, 198, 388, 745, 25, 198, 493, 30644, 283, 2912, 198, 388, 638, 5258, 21740, 1958, 8, 198, 309, 364, 378, 303, 2357, 84152, 25, 198, 388, 413, 30644, 25, 198, 493, 638, 3708, 12548, 11957, 198, 388, 745, 25, 198, 493, 30644, 283, 2912, 198, 388, 638, 5258, 21740, 1958, 8, 271, 262, 687, 3814, 35158, 2208, 1153, 11, 2357, 1590, 198, 285, 687, 369, 20974, 14683, 21102, 72716, 3042, 1590, 198, 309, 460, 318, 198, 388, 11074, 72716, 3042, 11, 23846, 8, 198, 388, 321, 15511, 3042, 15385, 2491, 198, 309, 847, 271, 285, 638, 949, 10132, 1931, 738, 2410, 4551, 1931, 738, 13, 75266, 11, 2357, 2733, 8, 198, 285, 638, 5258, 21740, 6742, 2733, 8, 198, 285, 440, 638, 31919, 2277, 10618, 487, 20644, 35821, 198, 309, 413, 369, 20974, 14683, 21102, 6742, 14112, 1590, 198, 388, 653, 71458, 628, 381, 38136, 413, 279, 13992, 4290, 914, 4147, 198, 388, 638, 9328, 6900, 1153, 5258, 21740, 11, 2357, 14112, 15385, 2491, 8, 198, 309, 745, 25, 198, 388, 638, 5258, 21740, 6742, 14112, 8, 271, 262, 687, 3814, 62, 12335, 1114, 1153, 11, 2357, 1590, 198, 285, 638, 3708, 28625, 871, 198, 285, 638, 949, 10132, 1931, 738, 2410, 4551, 1931, 738, 21704, 6277, 11, 2357, 2733, 8, 198, 285, 638, 5258, 21740, 6742, 2733, 8, 271, 262, 687, 3814, 2021, 636, 45823, 1153, 11, 2357, 1590, 198, 285, 638, 3708, 437, 1076, 871, 271, 262, 687, 3814, 1063, 4601, 1153, 11, 2357, 1590, 198, 285, 413, 2357, 17534, 25, 198, 309, 638, 5258, 21740, 6742, 17534, 8, 198, 285, 638, 3708, 18323, 871, 198, 285, 413, 2357, 32550, 25, 198, 309, 638, 5258, 21740, 6742, 32550, 8, 198, 285, 413, 2357, 20807, 25, 198, 309, 638, 3708, 18323, 871, 198, 309, 638, 5258, 21740, 6742, 20807, 8, 271, 262, 687, 3814, 1203, 730, 1153, 11, 2357, 1590, 198, 285, 638, 12110, 437, 6146, 11957, 198, 285, 638, 5258, 21740, 6742, 32140, 8, 198, 285, 440, 638, 15236, 4406, 198, 309, 364, 1105, 303, 2357, 508, 2191, 25, 198, 388, 638, 5258, 21740, 57468, 8, 271, 262, 687, 3814, 5868, 1153, 11, 2357, 1590, 198, 285, 638, 3708, 6742, 20536, 8, 198, 285, 413, 2357, 4905, 25, 198, 309, 638, 3708, 18323, 11957, 198, 309, 638, 5258, 21740, 6742, 4905, 8, 271, 262, 687, 3814, 41997, 1153, 11, 2357, 1590, 198, 285, 1118, 283, 2912, 198, 285, 653, 4472, 5789, 198, 285, 660, 8125, 283, 2357, 12633, 3138, 2048, 478, 2357, 15884, 198, 285, 16184, 283, 498, 3928, 60, 348, 318, 2798, 19766, 8125, 8, 471, 2343, 6742, 42489, 578, 478, 2357, 42489, 198, 285, 364, 1857, 11, 5255, 303, 12867, 36981, 19766, 8125, 11, 16184, 681, 220, 16, 1590, 198, 309, 264, 11, 293, 283, 5255, 198, 309, 413, 1118, 25, 198, 388, 1118, 283, 3439, 198, 309, 745, 25, 198, 388, 638, 3708, 12548, 11957, 198, 309, 638, 5258, 21740, 2784, 8, 198, 309, 413, 293, 25, 198, 388, 638, 3708, 64138, 8, 198, 388, 638, 5258, 21740, 1446, 8, 198, 309, 413, 1857, 606, 2343, 6742, 12633, 3138, 2048, 1590, 198, 388, 638, 3708, 12548, 593, 871, 271, 285, 653, 737, 2048, 11, 466, 12104, 29699, 413, 874, 737, 2048, 694, 15698, 14934, 5789, 2945, 198, 285, 413, 2357, 18932, 832, 466, 2357, 5037, 86, 3138, 2048, 25, 198, 309, 413, 1118, 25, 198, 388, 1118, 283, 3439, 198, 309, 745, 25, 198, 388, 638, 3708, 12548, 11957, 198, 309, 638, 3708, 28625, 871, 198, 309, 413, 2357, 18932, 832, 25, 198, 388, 638, 3708, 6742, 18932, 832, 20536, 8, 198, 388, 413, 2357, 18932, 832, 4905, 25, 198, 493, 638, 3708, 18323, 11957, 198, 493, 638, 5258, 21740, 6742, 18932, 832, 4905, 8, 271, 285, 653, 15698, 14934, 5789, 198, 285, 413, 2357, 5037, 86, 3138, 2048, 25, 198, 309, 364, 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a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/record_http.py b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/record_http.py new file mode 100644 index 0000000000..5e27df1daf --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/record_http.py @@ -0,0 +1,125 @@ +"""Run an unmodified upstream HTTP check and keep every exchange; usage: record_http.py SCRIPT OUT.jsonl ARGS... + +Like docs/receipts/gfx1151-qwen-833bbfcb/record-served.py (same record keys), and it also sees http.client calls and a +raw-socket request dropped before any reply (serve_cancel.py), which urlopen alone would miss. Requests and replies +reach the script unchanged. +""" +import http.client +import io +import json +import pathlib +import runpy +import socket +import sys +import threading +import time +import urllib.error +import urllib.request + +script, receipt = pathlib.Path(sys.argv[1]).resolve(), pathlib.Path(sys.argv[2]).resolve() +args = sys.argv[3:] +lock = threading.Lock() +nested = threading.local() # urlopen runs on http.client: one exchange, one record + + +def body_of(data): + try: + return json.loads(data) if data else None + except (TypeError, ValueError): + return None + + +def reply_of(raw): + try: + return json.loads(raw) + except ValueError: + return raw.decode(errors="replace") + + +def write(url, request, status, response, started, **extra): + row = {"url": url, "request": request, "status": status, "response": response, + "seconds": time.time() - started, **extra} + with lock, receipt.open("a") as f: + f.write(json.dumps(row) + "\n") + + +real_urlopen = urllib.request.urlopen + + +def urlopen(req, *a, **kw): + url = req.full_url if isinstance(req, urllib.request.Request) else str(req) + request = body_of(req.data) if isinstance(req, urllib.request.Request) else None + started = time.time() + nested.on = True + try: + r = real_urlopen(req, *a, **kw) + raw, status, headers = r.read(), r.status, r.headers + r.close() + except urllib.error.HTTPError as e: + raw = e.read() + write(url, request, e.code, reply_of(raw), started) + raise urllib.error.HTTPError(url, e.code, e.reason, e.headers, io.BytesIO(raw)) + finally: + nested.on = False + write(url, request, status, reply_of(raw), started) + out = io.BytesIO(raw) + out.status, out.headers = status, headers + return out + + +real_request, real_getresponse = http.client.HTTPConnection.request, http.client.HTTPConnection.getresponse + + +def request(self, method, url, body=None, headers={}, **kw): + self._recorded = (url, body_of(body), time.time()) + return real_request(self, method, url, body, headers, **kw) + + +def getresponse(self): + r = real_getresponse(self) + if getattr(nested, "on", False): + return r + url, sent, started = self._recorded + raw = r.read() + write(f"http://{self.host}:{self.port}{url}", sent, r.status, reply_of(raw), started) + r.read = lambda amt=None: raw + return r + + +class Dropped: + """A socket: the request it sent is recorded when the script closes it without ever reading a reply.""" + + def __init__(self, sock, address): + self.sock, self.address, self.sent, self.started, self.read = sock, address, b"", time.time(), False + + def sendall(self, data, *a): + self.sent += data + return self.sock.sendall(data, *a) + + def makefile(self, *a, **kw): + self.read = True + return self.sock.makefile(*a, **kw) + + def recv(self, *a): + self.read = True + return self.sock.recv(*a) + + def close(self): + if self.sent and not self.read: + head, _, body = self.sent.partition(b"\r\n\r\n") + path = head.split(b" ")[1].decode() + write(f"http://{self.address[0]}:{self.address[1]}{path}", body_of(body), None, None, self.started, + note="client closed the socket without reading a reply") + self.sent = b"" + return self.sock.close() + + def __getattr__(self, name): + return getattr(self.sock, name) + + +real_connect = socket.create_connection +urllib.request.urlopen = urlopen +http.client.HTTPConnection.request, http.client.HTTPConnection.getresponse = request, getresponse +socket.create_connection = lambda address, *a, **kw: Dropped(real_connect(address, *a, **kw), address) +sys.argv = [str(script), *args] +runpy.run_path(str(script), run_name="__main__") diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/runs/cold-base-131072-r1.json b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/runs/cold-base-131072-r1.json new file mode 100644 index 0000000000..fca41f6e30 --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/runs/cold-base-131072-r1.json @@ -0,0 +1,48 @@ +{ + "tag": 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[ + 86.70574188232422, + 86.68270874023438 + ] + } + ], + "decode": [ + { + "arm": "new", + "prompt": "fibonacci-raw", + "decode_tps": [ + 69.15345703661757, + 68.92013159633264 + ], + "ttft_s": 0.09908010449726135, + "spec_hit_rate": 0.7618513952706489 + }, + { + "arm": "new", + "prompt": "gpu-chat-no-think", + "decode_tps": [ + 55.4400335994644, + 56.392749687389006 + ], + "ttft_s": 0.16842073950101621, + "spec_hit_rate": 0.7618513952706489 + }, + { + "arm": "base", + "prompt": "fibonacci-raw", + "decode_tps": [ + 50.94231226334963, + 50.65589029239793 + ], + "ttft_s": 0.12370750350237358, + "spec_hit_rate": 0.7094099913867356 + }, + { + "arm": "base", + "prompt": "gpu-chat-no-think", + "decode_tps": [ + 46.230151172948915, + 44.70131133081844 + ], + "ttft_s": 0.23958044149912894, + "spec_hit_rate": 0.7094099913867356 + } + ], + "concurrent": [ + { + "arm": "new", + "prompt": "chat", + "streams": 1, + "aggregate_tps": [ + 56.2, + 58.2 + ] + }, + { + "arm": "new", + "prompt": "chat", + "streams": 4, + "aggregate_tps": [ + 100.6, + 98.9 + ] + }, + { + "arm": "new", + "prompt": "code", + "streams": 1, + "aggregate_tps": [ + 68.0, + 68.9 + ] + }, + { + "arm": "new", + "prompt": "code", + "streams": 4, + "aggregate_tps": [ + 117.7, + 117.1 + ] + }, + { + "arm": "base", + "prompt": "chat", + "streams": 1, + "aggregate_tps": [ + 45.0, + 45.6 + ] + }, + { + "arm": "base", + "prompt": "chat", + "streams": 4, + "aggregate_tps": [ + 74.5, + 71.4 + ] + }, + { + "arm": "base", + "prompt": "code", + "streams": 1, + "aggregate_tps": [ + 51.7, + 50.6 + ] + }, + { + "arm": "base", + "prompt": "code", + "streams": 4, + "aggregate_tps": [ + 89.6, + 89.7 + ] + } + ], + "coding_decode": [ + { + "mode": "drafts", + "arm": "base", + "output_tokens": 256, + "prompt_tokens": 16384.0, + "decode_tps": [ + 34.90616944594986, + 40.63882954261092, + 41.065374588925394, + 34.856905474777086, + 41.020326018930625, + 39.910888833179584 + ], + "ttft_s": [ + 46.42886849399656, + 46.460142659023404, 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"rss_peak_gib": 103.77433204650879 + }, + { + "mode": "drafts", + "arm": "new", + "output_tokens": 1024, + "prompt_tokens": 16384.0, + "decode_tps": [ + 49.43815733771798, + 49.4578287245327, + 49.223091236904075, + 48.113925325215384, + 48.02979626583727, + 48.87947047020218 + ], + "ttft_s": [ + 31.108798027999, + 30.936138116987422, + 30.93647557400982, + 30.930593572004, + 30.924267982016318, + 30.98419180099154 + ], + "wall_s": [ + 51.8015968099935, + 51.62070523199509, + 51.8011729340069, + 52.19291837300989, + 52.22384185701958, + 51.913870571996085 + ], + "cached_tokens": [ + 0 + ], + "token_sha256": [ + "35725e749acd9b19e919c31163a036d55501205fe753c51371cc6bf000ce1400" + ], + "spec_hit_rate": 0.6177004931222424, + "gpu_peak_gib": 82.72108459472656, + "rss_peak_gib": 103.77433204650879 + }, + { + "mode": "serial", + "arm": "base", + "output_tokens": 256, + "prompt_tokens": 16384.0, + "decode_tps": [ + 27.142233383057587, + 30.40630881235582, + 29.919116610877737, + 26.426750424336063, + 29.413267713707818, + 29.864084150703672 + ], + "ttft_s": [ + 46.340123449015664, + 46.38614893599879, + 46.31154512197827, + 46.47317335801199, + 46.3683642380056, + 46.69063807098428 + ], + "wall_s": [ + 55.73530402901815, + 54.772795764001785, + 54.883279664994916, + 56.12271013998543, + 55.03812672899221, + 55.34095898698433 + ], + "cached_tokens": [ + 0 + ], + "token_sha256": [ + "09172b34c45a282908548b2cb0607bf3f16a7581715252073ceb5ad22ff8f47a" + ], + "spec_hit_rate": null, + "gpu_peak_gib": 78.4827938079834, + "rss_peak_gib": 78.63330268859863 + }, + { + "mode": "serial", + "arm": "base", + "output_tokens": 1024, + "prompt_tokens": 16384.0, + "decode_tps": [ + 27.828606672701145, + 30.164434984603123, + 30.290977737527875, + 26.939153018018484, + 29.989921779500076, + 29.99056724541863 + ], + "ttft_s": [ + 46.53525917598745, + 46.42483447899576, + 46.45725613401737, + 46.685687962017255, + 46.60278144001495, + 46.56619285600027 + ], + "wall_s": [ + 83.29621841100743, + 80.33921761100646, + 80.22995671399985, + 84.66037472500466, + 80.71450602301047, + 80.67721653400804 + ], + "cached_tokens": [ + 0 + ], + "token_sha256": [ + "35725e749acd9b19e919c31163a036d55501205fe753c51371cc6bf000ce1400" + ], + "spec_hit_rate": null, + "gpu_peak_gib": 78.4827938079834, + "rss_peak_gib": 78.63330268859863 + }, + { + "mode": "serial", + "arm": "new", + "output_tokens": 256, + "prompt_tokens": 16384.0, + "decode_tps": [ + 35.71700023630829, + 35.57959941469009, + 35.530218936841834, + 35.48060872069179, + 35.44959954649033, + 35.86436435624361 + ], + "ttft_s": [ + 30.755413222010247, + 30.559503414988285, + 30.591321493004216, + 30.708914274990093, + 30.77928955500829, + 30.708091846987372 + ], + "wall_s": [ + 37.90032441401854, + 37.726740118989255, + 37.768515975010814, + 37.89613821200328, + 38.132074946013745, + 37.81840012798784 + ], + "cached_tokens": [ + 0 + ], + "token_sha256": [ + "09172b34c45a282908548b2cb0607bf3f16a7581715252073ceb5ad22ff8f47a" + ], + "spec_hit_rate": null, + "gpu_peak_gib": 82.68046951293945, + "rss_peak_gib": 104.87885475158691 + }, + { + "mode": "serial", + "arm": "new", + "output_tokens": 1024, + "prompt_tokens": 16384.0, + "decode_tps": [ + 35.75389834873005, + 35.947091337468855, + 35.662802161502036, + 35.47735828459387, + 35.77147135412561, + 35.67396196946981 + ], + "ttft_s": [ + 30.602394760004245, + 30.716184312972473, + 30.6996438470087, + 30.82310843101004, + 30.799971480999375, + 30.77806903500459 + ], + "wall_s": [ + 59.21493756902055, + 59.174972293985775, + 59.39070205501048, + 59.658711601019604, + 59.39846681599738, + 59.45472844300093 + ], + "cached_tokens": [ + 0 + ], + "token_sha256": [ + "35725e749acd9b19e919c31163a036d55501205fe753c51371cc6bf000ce1400" + ], + "spec_hit_rate": null, + "gpu_peak_gib": 82.68046951293945, + "rss_peak_gib": 104.87885475158691 + } + ] +} \ No newline at end of file diff --git a/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/summary.md b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/summary.md new file mode 100644 index 0000000000..ea414fd25d --- /dev/null +++ b/docs/receipts/gfx1151-flashnext-hip-37aed1a0/perf/summary.md @@ -0,0 +1,62 @@ +## Cold prefill (max_tokens 1, prompt cache off, fresh server per run) +| arm | prompt tokens | context | prefill tok/s (median) | per round | TTFT (s) | wall (s) | cached tokens | GTT+VRAM peak over idle (GiB) | RSS peak (GiB) | server | +|---|---|---|---|---|---|---|---|---|---|---| +| new | 2,048 | 10240 | 673.7 | 681.4, 666.0 | 3.040 | 3.041 | 0 | 82.45 | 102.9 | ready | +| base | 2,048 | 10240 | 293.2 | 290.0, 296.4 | 6.986 | 6.996 | 0 | 78.21 | 76.81 | ready | +| new | 8,192 | 16384 | 558.2 | 559.2, 557.2 | 14.68 | 14.68 | 0 | 82.62 | 105.0 | ready | +| base | 8,192 | 16384 | 261.3 | 261.3, 261.3 | 31.35 | 31.35 | 0 | 78.39 | 77.56 | ready | +| new | 32,768 | 40960 | 513.5 | 512.6, 514.5 | 63.81 | 63.81 | 0 | 83.33 | 105.0 | ready | +| base | 32,768 | 40960 | 260.4 | 260.1, 260.6 | 125.9 | 125.9 | 0 | 79.09 | 79.81 | ready | +| new | 65,536 | 73728 | 496.7 | 497.2, 496.2 | 132.0 | 132.0 | 0 | 84.27 | 104.3 | ready | +| base | 65,536 | 73728 | 259.3 | 259.3, 259.3 | 252.7 | 252.7 | 0 | 80.03 | 81.64 | ready | +| new | 131,072 | 139264 | 471.6 | 471.7, 471.5 | 277.9 | 277.9 | 0 | 86.14 | 103.8 | ready | +| base | 131,072 | 139264 | 258.0 | 258.1, 257.8 | 508.1 | 508.1 | 0 | 81.91 | 83.66 | ready | +| new | 261,888 | 262144 | 437.3 | 437.5, 437.1 | 598.8 | 598.8 | 0 | 89.68 | 103.9 | ready | +| base | 261,888 | 262144 | 244.8 | 245.1, 244.5 | 1,070 | 1,070 | 0 | 85.45 | 86.69 | ready | + +new / base, prefill tok/s +| prompt tokens | new | base | ratio | +|---|---|---|---| +| 2,048 | 673.7 | 293.2 | 2.298 | +| 8,192 | 558.2 | 261.3 | 2.136 | +| 32,768 | 513.5 | 260.4 | 1.972 | +| 65,536 | 496.7 | 259.3 | 1.915 | +| 131,072 | 471.6 | 258.0 | 1.828 | +| 261,888 | 437.3 | 244.8 | 1.786 | + +## Decode, one stream (bench_openai.py, 256 tokens, greedy, drafts on) +| arm | prompt | decode tok/s (median) | per round | TTFT (s) | wall (s, derived) | spec-decode hit rate | GTT+VRAM peak (GiB) | RSS peak (GiB) | +|---|---|---|---|---|---|---|---|---| +| new | fibonacci-raw | 69.04 | 69.15, 68.92 | 0.09908 | 3.793 | 76.2 % | 84.38 | 104.7 | +| new | gpu-chat-no-think | 55.92 | 55.44, 56.39 | 0.1684 | 4.729 | 76.2 % | 84.38 | 104.7 | +| base | fibonacci-raw | 50.80 | 50.94, 50.66 | 0.1237 | 5.143 | 70.9 % | 81.33 | 76.80 | +| base | gpu-chat-no-think | 45.47 | 46.23, 44.70 | 0.2396 | 5.848 | 70.9 % | 81.33 | 76.80 | + +## Prefill, serial decode and Default MTP decode (one public-code prompt, greedy, cache off, drafts as stated) +| arm | decode | output tokens | decode tok/s (median) | every rep | TTFT (s) | wall (s) | spec-decode hit rate | GTT+VRAM peak over idle (GiB) | RSS peak (GiB) | cached tokens | +|---|---|---|---|---|---|---|---|---|---|---| +| base | Default MTP | 256 | 40.27 | 34.91, 40.64, 41.07, 34.86, 41.02, 39.91 | 46.48 | 52.84 | 68.1 % | 78.48 | 78.67 | 0 | +| base | Default MTP | 1024 | 38.26 | 35.44, 38.42, 38.33, 34.39, 38.77, 38.19 | 46.54 | 73.32 | 68.1 % | 78.48 | 78.67 | 0 | +| new | Default MTP | 256 | 51.86 | 52.11, 51.89, 52.71, 51.83, 51.75, 50.15 | 30.91 | 35.86 | 61.8 % | 82.72 | 103.8 | 0 | +| new | Default MTP | 1024 | 49.05 | 49.44, 49.46, 49.22, 48.11, 48.03, 48.88 | 30.94 | 51.86 | 61.8 % | 82.72 | 103.8 | 0 | +| base | serial (--no-drafts) | 256 | 29.64 | 27.14, 30.41, 29.92, 26.43, 29.41, 29.86 | 46.38 | 55.19 | - | 78.48 | 78.63 | 0 | +| base | serial (--no-drafts) | 1024 | 29.99 | 27.83, 30.16, 30.29, 26.94, 29.99, 29.99 | 46.55 | 80.70 | - | 78.48 | 78.63 | 0 | +| new | serial (--no-drafts) | 256 | 35.55 | 35.72, 35.58, 35.53, 35.48, 35.45, 35.86 | 30.71 | 37.86 | - | 82.68 | 104.9 | 0 | +| new | serial (--no-drafts) | 1024 | 35.71 | 35.75, 35.95, 35.66, 35.48, 35.77, 35.67 | 30.75 | 59.39 | - | 82.68 | 104.9 | 0 | + +| arm | prefill tok/s (cold, 16K) | serial decode tok/s (256) | serial decode tok/s (1024) | Default MTP decode tok/s (256) | Default MTP decode tok/s (1024) | MTP token hash == serial's | +|---|---|---|---|---|---|---| +| new | 533.5 | 35.55 | 35.71 | 51.86 | 49.05 | yes/yes | +| base | 353.3 | 29.64 | 29.99 | 40.27 | 38.26 | yes/yes | + +## Concurrent (bench_concurrent.py --levels 1,4 --alone --serial) +| arm | prompt | streams | aggregate tok/s | per-stream tok/s | concurrent==alone (eq/ne/failed) | alone==draft:false (eq/ne/failed) | failed requests | +|---|---|---|---|---|---|---|---| +| new | chat | 1 | 57.20 | 57.20 | 6/0/0 | 2/0/0 | 0 | +| new | chat | 4 | 99.75 | 25.85 | 24/0/0 | 2/0/0 | 0 | +| new | code | 1 | 68.45 | 68.45 | 6/0/0 | 2/0/0 | 0 | +| new | code | 4 | 117.4 | 30.00 | 24/0/0 | 2/0/0 | 0 | +| base | chat | 1 | 45.30 | 45.30 | 6/0/0 | 2/0/0 | 0 | +| base | chat | 4 | 72.95 | 18.65 | 24/0/0 | 2/0/0 | 0 | +| base | code | 1 | 51.15 | 51.15 | 6/0/0 | 2/0/0 | 0 | +| base | code | 4 | 89.65 | 22.70 | 24/0/0 | 2/0/0 | 0 | diff --git a/docs/recipes/qwen3.8-flash-next.md b/docs/recipes/qwen3.8-flash-next.md index 5ab6775fd2..c6d51d0306 100644 --- a/docs/recipes/qwen3.8-flash-next.md +++ b/docs/recipes/qwen3.8-flash-next.md @@ -475,6 +475,13 @@ families refuse `--kv-dtype` before any download. `--mtp-confidence P`, from 0 to 1, sets the probability under which a chain stops before a later draft; the CUDA default is 0.70, for one stream and for concurrent rounds. Only Flash Next's CUDA engine has this rule, so the MLX path and the other families refuse it. +## HIP prompt chunk + +On HIP, Flash Next cuts prompts at 4,096 rows unless `--policy` or `TF_POLICY` names `prefill_step`. +`--policy prefill_step=20480` runs a 20K prompt in one pass. On a gfx1151 machine with 192 GiB of unified memory it +prefilled a 16K prompt about 3 % faster and held about 24 GiB more GPU memory than the default. Use it only where that +memory is free. A measurement on a larger machine is not a budget for a smaller one. + ## Draft vocabulary provenance The Flash Next dump tool accepts `--draft-vocab default` for the shipped list, diff --git a/zig/build/hip.zig b/zig/build/hip.zig index 40c02fefa7..4bb32c6b40 100644 --- a/zig/build/hip.zig +++ b/zig/build/hip.zig @@ -321,7 +321,8 @@ const headers = [_][]const u8{ "quant/mlx_tiles.hpp", "tiles/dot2.hpp", "tiles/epilogue.hpp", "tiles/gemm.hpp", "tiles/gemm_kp.hpp", "tiles/matrix_gemm.hpp", "tiles/plan.hpp", "tiles/stream.hpp", "flashnext/streams.hpp", "flashnext/ngram.hpp", "flashnext/indexer.hpp", "flashnext/sparse.hpp", - "ops/nemotron_moe.hpp", + "ops/nemotron_moe.hpp", "common/tsum.hpp", "decode/select.hpp", "tiles/moe_gemm.hpp", + "tiles/dense_gemm.hpp", "ops/qk_rope_wave.hpp", }; /// The flags of the kernels' first build: no contraction, wave32 on RDNA, C++20. diff --git a/zig/kernels/hip/common/tsum.hpp b/zig/kernels/hip/common/tsum.hpp new file mode 100644 index 0000000000..3172277732 --- /dev/null +++ b/zig/kernels/hip/common/tsum.hpp @@ -0,0 +1,54 @@ +#pragma once + +// CNT wave sums at once, each bitwise its own xor butterfly's, in fewer moves (DPP row_xmask and permlanex16). + +// Ported from Strata (src/kernels/cuda/s26_tsum.cuh@4b9e05a2); MIT License, full text in LICENSES/Strata-MIT.txt. + +#include + +namespace tf { +namespace rocm { + +// The value of lane `lane ^ O` (wave32): permlanex16 across the two rows of 16, DPP row_xmask inside a row. +template +__device__ __forceinline__ float tsum_move(float v) { + if constexpr (O == 16) { + return __int_as_float(__builtin_amdgcn_permlanex16(__float_as_int(v), __float_as_int(v), 0x76543210u, 0xfedcba98u, + false, false)); + } else { + return __int_as_float(__builtin_amdgcn_update_dpp(0, __float_as_int(v), 0x160 + O, 0xf, 0xf, false)); + } +} + +template +__device__ __forceinline__ float tsum_plain(float x) { + if constexpr (O >= 1) { + x += tsum_move(x); + return tsum_plain(x); + } else { + return x; + } +} + +// v[0..CNT), CNT a power of two up to 32: this lane's values; returns the sum of value lane >> (5 - log2 CNT). +template +__device__ __forceinline__ float tsum(float* v, int lane) { + if constexpr (CNT > 1) { + constexpr int H = CNT / 2; + const bool hi = (lane & O) != 0; +#pragma unroll + for (int j = 0; j < H; ++j) { + const float send = hi ? v[j] : v[j + H]; + const float keep = hi ? v[j + H] : v[j]; + v[j] = keep + tsum_move(send); + } + return tsum(v, lane); + } else { + return tsum_plain(v[0]); + } +} + +constexpr int tsum_log2(int p) { return p <= 1 ? 0 : 1 + tsum_log2(p / 2); } + +} // namespace rocm +} // namespace tf diff --git a/zig/kernels/hip/common/wmma.hpp b/zig/kernels/hip/common/wmma.hpp index 663cd59e2c..65f45efdc3 100644 --- a/zig/kernels/hip/common/wmma.hpp +++ b/zig/kernels/hip/common/wmma.hpp @@ -19,6 +19,15 @@ __device__ inline bf16x16 frag16(const uint32_t* p) { return __builtin_bit_cast(bf16x16, __builtin_shufflevector(lo, hi, 0, 1, 2, 3, 4, 5, 6, 7)); } +// A workgroup barrier over LDS only (lgkmcnt 0, then s_barrier): __syncthreads() also drains in-flight global loads. +__device__ __forceinline__ void lds_barrier() { +#if TF_DEVICE_WMMA_GFX11 + asm volatile("s_waitcnt lgkmcnt(0)\n\ts_barrier" ::: "memory"); +#else + __syncthreads(); +#endif +} + // The BF16 elements and sums of DotBF16, and the 16 x 16 x 16 product of two fragments added to an accumulator. struct WmmaBF16 : DotBF16 { #if TF_DEVICE_WMMA_GFX11 diff --git a/zig/kernels/hip/decode/decode.hip b/zig/kernels/hip/decode/decode.hip index 42ba9fd3da..62571f906f 100644 --- a/zig/kernels/hip/decode/decode.hip +++ b/zig/kernels/hip/decode/decode.hip @@ -29,18 +29,30 @@ constexpr int kRouterWaves = 4; constexpr int kRouterSteps = 16; // float4 loads a lane keeps in flight constexpr int kRouterRows = 16; -// logits[r, e] = x[r] . rows[e], 16 rows a block, a wave an expert; d is a multiple of 4, weight rows 16-byte aligned. -template -__device__ void router_decode(const void* x, const float* rows, float* logits, int r, int d, int e) { +// Four router weights at `at` of row `w`: fp32 rows as stored, or bf16 rows (ROWS16) widened, which is exact. +template +__device__ __forceinline__ float4 router_weights(const void* w, int at) { + if constexpr (ROWS16) { + const uint2 v = *reinterpret_cast(static_cast(w) + at); + return make_float4(bf16_up(v.x & 0xffffu), bf16_up(v.x >> 16), bf16_up(v.y & 0xffffu), bf16_up(v.y >> 16)); + } else { + return *reinterpret_cast(static_cast(w) + at); + } +} + +// logits[r, e] = x[r] . rows[e], 16 rows a block, a wave an expert; d % 4 == 0; rows 16B aligned (8B ROWS16); x staged. +template +__device__ void router_decode(const void* x, const void* rows, float* logits, int r, int d, int e, bool staged = false) { const int lane = threadIdx.x & 31; const int expert = blockIdx.x * kRouterWaves + (threadIdx.x >> 5); if (expert >= e) return; // blockIdx.y picks a block of 16 rows: a row's sums are the same whichever block it is in const int first = blockIdx.y * kRouterRows; - x = static_cast(x) + static_cast(first) * d; + if (!staged) x = static_cast(x) + static_cast(first) * d; logits += static_cast(first) * e; r = r - first < kRouterRows ? r - first : kRouterRows; - const float* w = rows + static_cast(expert) * d; + const void* w = ROWS16 ? static_cast(static_cast(rows) + static_cast(expert) * d) + : static_cast(static_cast(rows) + static_cast(expert) * d); float acc[kRouterRows]; #pragma unroll for (int k = 0; k < kRouterRows; ++k) acc[k] = 0.f; @@ -49,7 +61,7 @@ __device__ void router_decode(const void* x, const float* rows, float* logits, i #pragma unroll for (int s = 0; s < kRouterSteps; ++s) { const int at = base + (lane + 32 * s) * 4; - wv[s] = at < d ? *reinterpret_cast(w + at) : make_float4(0.f, 0.f, 0.f, 0.f); + wv[s] = at < d ? router_weights(w, at) : make_float4(0.f, 0.f, 0.f, 0.f); } #pragma unroll for (int k = 0; k < kRouterRows; ++k) { @@ -166,6 +178,9 @@ struct ConvArgs { // A round's plan (plan.count null: the launch's own rows and state): a grid row a slot, rows and state from it. PlanArgs plan; int layer; + int slots; // the launcher's grid rows (the grid says it here) + // f >= 0 here: the window starts from the last window's snapshot after its row f; null or -1: from `state` + const int* from; }; // The conv for a window's rows split into q, k, v: taps in order, then silu; q, k heads rms-normed; gate and beta last. @@ -211,9 +226,12 @@ __device__ void conv_split_body(const ConvArgs& launch) { const float* taps = c.weight + static_cast(live ? channel : 0) * c.kernel; const int kept = c.kernel - 1; float history[7]; + const int f = c.from != nullptr && c.states != nullptr ? *c.from : -1; + const float* start = f >= 0 ? c.states + static_cast(f) * kept * c.channels : c.state; if (live) { - for (int tap = 0; tap < kept; ++tap) history[tap] = c.state[static_cast(tap) * c.channels + channel]; + for (int tap = 0; tap < kept; ++tap) history[tap] = start[static_cast(tap) * c.channels + channel]; } + __atomic_signal_fence(__ATOMIC_SEQ_CST); // the start is read before any snapshot store (it may be one of them) for (int r = 0; r < c.rows; ++r) { float y = 0.f; float sample = 0.f; @@ -328,65 +346,21 @@ __device__ void } } -constexpr int kSelectThreads = 512; -constexpr int kSelectMax = 1024; +} // namespace -__device__ __forceinline__ float round_bf16_f(float v) { return round_kind(v, 2); } +#include "decode/select.hpp" -// act.hip's moe_select with picks by rank: expert i is in the top k when fewer than k beat it; `items` writes the plan. -__device__ void select_body(const float* logits, int* pick, float* wts, int* items, int* members, int capacity, - int experts, int top_k) { - __shared__ float v[kSelectMax]; - __shared__ float top_v[32]; - __shared__ int top_i[32]; - const int row = blockIdx.x; - const int slots = top_k + 1; - const float* l = logits + static_cast(row) * (experts + 1); - for (int i = threadIdx.x; i < experts; i += kSelectThreads) v[i] = l[i]; - __syncthreads(); - for (int i = threadIdx.x; i < experts; i += kSelectThreads) { - const float vi = v[i]; - int rank = 0; -#pragma unroll 16 - for (int j = 0; j < experts; ++j) { - const float vj = v[j]; - rank += (vj > vi) || (vj == vi && j < i); - } - if (rank < top_k) { - top_v[rank] = vi; - top_i[rank] = i; - } - } - __syncthreads(); - if (threadIdx.x == 0) { - const float top = top_v[0]; - float ex[32]; - float total = 0.f; - for (int k = 0; k < top_k; ++k) { - ex[k] = expf(top_v[k] - top); - total += ex[k]; - } - for (int k = 0; k < top_k; ++k) { - pick[row * slots + k] = top_i[k]; - wts[row * slots + k] = round_bf16_f(ex[k] / total); - } - const float gate = round_bf16_f(l[experts]); - pick[row * slots + top_k] = experts; - wts[row * slots + top_k] = round_bf16_f(1.f / (1.f + expf(-gate))); - } - if (items != nullptr) { - __syncthreads(); - for (int k = threadIdx.x; k < capacity; k += kSelectThreads) { - const bool real = k < slots; - items[3 * k] = real ? pick[k] : 0; - items[3 * k + 1] = real ? k : 0; - items[3 * k + 2] = real ? 1 : 0; - if (real) members[k] = k; - } - } +extern "C" __global__ void __launch_bounds__(32 * kRouterWaves) + tf_router_select_f16(const void* x, const void* rows, float* logits, int r, int d, int e, int* pick, float* wts, + int* items, int* members, int capacity, int top_k, int tile, int staged, unsigned* done) { + router_select<1>(x, rows, logits, r, d, e, pick, wts, items, members, capacity, top_k, tile, staged, done); } -} // namespace +extern "C" __global__ void __launch_bounds__(32 * kRouterWaves) + tf_router_select_bf16(const void* x, const void* rows, float* logits, int r, int d, int e, int* pick, float* wts, + int* items, int* members, int capacity, int top_k, int tile, int staged, unsigned* done) { + router_select<2>(x, rows, logits, r, d, e, pick, wts, items, members, capacity, top_k, tile, staged, done); +} extern "C" __global__ void __launch_bounds__(32 * kRouterWaves) tf_router_decode_f16(const void* x, const float* rows, float* logits, int r, int d, int e) { @@ -418,8 +392,55 @@ extern "C" __global__ void __launch_bounds__(256) gnorm_out_body(y, weight, z, out, kind, rows, width, eps, sigmoid_gate); } +// A prompt's picks (no plan), a wave a row, 4 rows a block, select_body's bytes; a NaN row: select_row's rank loop. +extern "C" __global__ void __launch_bounds__(32 * kRouterWaves) + tf_select_rows(const float* logits, int* pick, float* wts, int rows, int experts, int top_k) { + __shared__ int fallback[kRouterWaves]; + const int wave = threadIdx.x >> 5; + const int first = blockIdx.x * kRouterWaves; + const int row = first + wave; + const bool live = row < rows; + const bool bad = experts <= 16 * 32 ? select_row_lanes<16, 32>(logits, row, live, pick, wts, experts, top_k) + : select_row_lanes(logits, row, live, pick, wts, experts, top_k); + if ((threadIdx.x & 31) == 0) fallback[wave] = live && bad; + __syncthreads(); + for (int w = 0; w < kRouterWaves; ++w) + if (fallback[w]) select_row(logits, first + w, pick, wts, nullptr, nullptr, 0, experts, top_k); +} + extern "C" __global__ void __launch_bounds__(kSelectThreads) tf_select_decode(const float* logits, int* pick, float* wts, int* items, int* members, int capacity, int experts, int top_k) { select_body(logits, pick, wts, items, members, capacity, experts, top_k); } + +// Reads the live items' experts' down codes (at most cap_bytes) into the caches for the down; an asm sink keeps them. +constexpr int kPrefetchItems = 64; +extern "C" __global__ void __launch_bounds__(256) + tf_moe_prefetch(const int* items, int count, const uint4* words, long long expert_bytes, int experts, + long long cap_bytes) { + __shared__ int ids[kPrefetchItems]; + __shared__ int live; + if (threadIdx.x == 0) live = 0; + __syncthreads(); + // the live items in any order (each block its own list; the order only changes which codes are read first) + for (int k = threadIdx.x; k < count; k += blockDim.x) { + const int e = items[3 * k]; + if (items[3 * k + 2] > 0 && e >= 0 && e < experts) { + const int at = atomicAdd(&live, 1); + if (at < kPrefetchItems) ids[at] = e; + } + } + __syncthreads(); + const int n_ids = live < kPrefetchItems ? live : kPrefetchItems; + const long long per = expert_bytes / 16; + long long left = cap_bytes / 16; + unsigned acc = 0; + for (int k = 0; k < n_ids && left > 0; ++k) { + const long long n = per < left ? per : left; + const uint4* w = words + static_cast(ids[k]) * per; + for (long long j = blockIdx.x * 256ll + threadIdx.x; j < n; j += gridDim.x * 256ll) acc ^= w[j].x; + left -= n; + } + asm volatile("" ::"v"(acc)); +} diff --git a/zig/kernels/hip/decode/select.hpp b/zig/kernels/hip/decode/select.hpp new file mode 100644 index 0000000000..bb69a902b6 --- /dev/null +++ b/zig/kernels/hip/decode/select.hpp @@ -0,0 +1,363 @@ +#pragma once + +// A decode step's expert picks and the router launch that also picks; decode.hip includes it after its router. + +namespace { + +constexpr int kSelectThreads = 512; +constexpr int kSelectMax = 1024; + +__device__ __forceinline__ float round_bf16_f(float v) { return round_kind(v, 2); } + +// act.hip's moe_select with picks by rank: expert i is in the top k when fewer than k beat it; `items` writes the plan. +__device__ void select_body(const float* logits, int* pick, float* wts, int* items, int* members, int capacity, + int experts, int top_k) { + __shared__ float v[kSelectMax]; + __shared__ float top_v[32]; + __shared__ int top_i[32]; + const int row = blockIdx.x; + const int slots = top_k + 1; + const float* l = logits + static_cast(row) * (experts + 1); + for (int i = threadIdx.x; i < experts; i += kSelectThreads) v[i] = l[i]; + __syncthreads(); + for (int i = threadIdx.x; i < experts; i += kSelectThreads) { + const float vi = v[i]; + int rank = 0; +#pragma unroll 16 + for (int j = 0; j < experts; ++j) { + const float vj = v[j]; + rank += (vj > vi) || (vj == vi && j < i); + } + if (rank < top_k) { + top_v[rank] = vi; + top_i[rank] = i; + } + } + __syncthreads(); + if (threadIdx.x == 0) { + const float top = top_v[0]; + float ex[32]; + float total = 0.f; + for (int k = 0; k < top_k; ++k) { + ex[k] = expf(top_v[k] - top); + total += ex[k]; + } + for (int k = 0; k < top_k; ++k) { + pick[row * slots + k] = top_i[k]; + wts[row * slots + k] = round_bf16_f(ex[k] / total); + } + const float gate = round_bf16_f(l[experts]); + pick[row * slots + top_k] = experts; + wts[row * slots + top_k] = round_bf16_f(1.f / (1.f + expf(-gate))); + } + if (items != nullptr) { + __syncthreads(); + for (int k = threadIdx.x; k < capacity; k += kSelectThreads) { + const bool real = k < slots; + items[3 * k] = real ? pick[k] : 0; + items[3 * k + 1] = real ? k : 0; + items[3 * k + 2] = real ? 1 : 0; + if (real) members[k] = k; + } + } +} + +// select_body's pick of a row by the router's block, k argmax passes (NaN: rank loop); coherent loads: others wrote it. +__device__ void select_row(const float* logits, int row, int* pick, float* wts, int* items, int* members, int capacity, + int experts, int top_k) { + constexpr int kThreads = 32 * kRouterWaves; + __shared__ float v[kSelectMax]; + __shared__ unsigned char taken[kSelectMax]; + __shared__ float top_v[32]; + __shared__ int top_i[32]; + __shared__ float wave_v[kRouterWaves]; + __shared__ int wave_i[kRouterWaves]; + __shared__ int has_nan; + const int slots = top_k + 1; + const int lane = threadIdx.x & 31, wave = threadIdx.x >> 5; + float* l = const_cast(logits) + static_cast(row) * (experts + 1); + if (threadIdx.x == 0) has_nan = 0; + __syncthreads(); + for (int i = threadIdx.x; i < experts; i += kThreads) { + const float vi = __hip_atomic_load(l + i, __ATOMIC_RELAXED, __HIP_MEMORY_SCOPE_AGENT); + v[i] = vi; + taken[i] = 0; + if (vi != vi) has_nan = 1; + } + __syncthreads(); + if (has_nan) { + for (int i = threadIdx.x; i < experts; i += kThreads) { + const float vi = v[i]; + int rank = 0; + for (int j = 0; j < experts; ++j) { + const float vj = v[j]; + rank += (vj > vi) || (vj == vi && j < i); + } + if (rank < top_k) { + top_v[rank] = vi; + top_i[rank] = i; + } + } + } else { + for (int k = 0; k < top_k; ++k) { + float bv = 0.f; + int bi = 0x7fffffff; + for (int i = threadIdx.x; i < experts; i += kThreads) { + const float vi = v[i]; + if (!taken[i] && (bi == 0x7fffffff || vi > bv || (vi == bv && i < bi))) { + bv = vi; + bi = i; + } + } +#pragma unroll + for (int mask = 16; mask > 0; mask >>= 1) { + const float ov = __shfl_xor(bv, mask, 32); + const int oi = __shfl_xor(bi, mask, 32); + if (oi != 0x7fffffff && (bi == 0x7fffffff || ov > bv || (ov == bv && oi < bi))) { + bv = ov; + bi = oi; + } + } + if (lane == 0) { + wave_v[wave] = bv; + wave_i[wave] = bi; + } + __syncthreads(); + if (threadIdx.x == 0) { + float cv = wave_v[0]; + int ci = wave_i[0]; + for (int w = 1; w < kRouterWaves; ++w) { + const float ov = wave_v[w]; + const int oi = wave_i[w]; + if (oi != 0x7fffffff && (ci == 0x7fffffff || ov > cv || (ov == cv && oi < ci))) { + cv = ov; + ci = oi; + } + } + top_v[k] = cv; + top_i[k] = ci; + taken[ci] = 1; + } + __syncthreads(); + } + } + __syncthreads(); + if (threadIdx.x == 0) { + const float top = top_v[0]; + float ex[32]; + float total = 0.f; + for (int k = 0; k < top_k; ++k) { + ex[k] = expf(top_v[k] - top); + total += ex[k]; + } + for (int k = 0; k < top_k; ++k) { + pick[row * slots + k] = top_i[k]; + wts[row * slots + k] = round_bf16_f(ex[k] / total); + } + const float gate = round_bf16_f(__hip_atomic_load(l + experts, __ATOMIC_RELAXED, __HIP_MEMORY_SCOPE_AGENT)); + pick[row * slots + top_k] = experts; + wts[row * slots + top_k] = round_bf16_f(1.f / (1.f + expf(-gate))); + } + if (items != nullptr) { + __syncthreads(); + for (int k = threadIdx.x; k < capacity; k += kThreads) { + const bool real = k < slots; + items[3 * k] = real ? pick[k] : 0; + items[3 * k + 1] = real ? k : 0; + items[3 * k + 2] = real ? 1 : 0; + if (real) members[k] = k; + } + } + __syncthreads(); +} + +// select_row's bytes by LANES (32 or 16) lanes a row; KPER * LANES >= experts, top_k <= LANES; true: NaN, none written. +template +__device__ bool select_row_lanes(const float* logits, int row, bool live, int* pick, float* wts, int experts, int top_k) { + const int lane = threadIdx.x & 31; + const int hl = lane & (LANES - 1); + const int base = lane & ~(LANES - 1); + const unsigned group = LANES == 32 ? 0xffffffffu : ((1u << LANES) - 1u) << base; + const int slots = top_k + 1; + const float* l = logits + static_cast(live ? row : 0) * (experts + 1); + float v[KPER]; + unsigned taken = 0; + bool nan = false; +#pragma unroll + for (int j = 0; j < KPER; ++j) { + const int i = hl + LANES * j; + v[j] = i < experts ? __hip_atomic_load(l + i, __ATOMIC_RELAXED, __HIP_MEMORY_SCOPE_AGENT) : 0.f; + nan |= i < experts && v[j] != v[j]; + } + const bool bad = (static_cast(__ballot(nan)) & group) != 0u; + // the k-th pick, held by the group's lane k + float mine_v = 0.f; + int mine_i = 0; + for (int k = 0; k < top_k; ++k) { + float bv = 0.f; + int bi = 0x7fffffff; +#pragma unroll + for (int j = 0; j < KPER; ++j) { + const int i = hl + LANES * j; + if (i < experts && !((taken >> j) & 1u) && (bi == 0x7fffffff || v[j] > bv || (v[j] == bv && i < bi))) { + bv = v[j]; + bi = i; + } + } +#pragma unroll + for (int mask = LANES / 2; mask > 0; mask >>= 1) { + const float ov = __shfl_xor(bv, mask, 32); + const int oi = __shfl_xor(bi, mask, 32); + if (oi != 0x7fffffff && (bi == 0x7fffffff || ov > bv || (ov == bv && oi < bi))) { + bv = ov; + bi = oi; + } + } + if (bi % LANES == hl) taken |= 1u << (bi / LANES); + if (hl == k) { + mine_v = bv; + mine_i = bi; + } + } + // thread 0's arithmetic in its order; each exp is taken again for its weight (the same value) + const float top = __shfl(mine_v, base, 32); + float total = 0.f; + for (int k = 0; k < top_k; ++k) total += expf(__shfl(mine_v, base + k, 32) - top); + if (live && !bad) { + const int at = row * slots; + if (hl < top_k) { + pick[at + hl] = mine_i; + wts[at + hl] = round_bf16_f(expf(mine_v - top) / total); + } + if (hl == 0) { + const float gate = round_bf16_f(__hip_atomic_load(l + experts, __ATOMIC_RELAXED, __HIP_MEMORY_SCOPE_AGENT)); + pick[at + top_k] = experts; + wts[at + top_k] = round_bf16_f(1.f / (1.f + expf(-gate))); + } + } + return bad; +} + +// tf_moe_route's members and items for a few rows' pairs (at most kPlanPairs) by one block, the same plan as it makes. +constexpr int kPlanPairs = 32 * kRouterWaves; // a pair a thread: 8 rows of top 10 + the shared expert (88) +// The shared memory it takes from `pool`, in ints: 3 * experts + 2 * 32 * kRouterWaves + kPlanPairs. +__device__ void route_plan(const int* picks, int pairs, int experts, int tile, int* members, int* items, int capacity, + int* pool) { + constexpr int kThreads = 32 * kRouterWaves; + int* counts = pool; + int* starts = counts + experts; + int* ends = starts + experts; + int* scan_c = ends + experts; + int* scan_n = scan_c + kThreads; + int* pk = scan_n + kThreads; + const int t = threadIdx.x; + for (int e = t; e < experts; e += kThreads) counts[e] = 0; + if (t < pairs) pk[t] = picks[t]; + __syncthreads(); + if (t < pairs) atomicAdd(&counts[pk[t]], 1); + __syncthreads(); + const int per = (experts + kThreads - 1) / kThreads; + const int lo = min(experts, t * per), hi = min(experts, lo + per); + int own_c = 0, own_n = 0; + for (int e = lo; e < hi; ++e) { + own_c += counts[e]; + own_n += (counts[e] + tile - 1) / tile; + } + scan_c[t] = own_c; + scan_n[t] = own_n; + __syncthreads(); + for (int off = 1; off < kThreads; off <<= 1) { + const int vc = t >= off ? scan_c[t - off] : 0, vn = t >= off ? scan_n[t - off] : 0; + __syncthreads(); + scan_c[t] += vc; + scan_n[t] += vn; + __syncthreads(); + } + int start = scan_c[t] - own_c, end = scan_n[t] - own_n; + for (int e = lo; e < hi; ++e) { + starts[e] = start; + start += counts[e]; + end += (counts[e] + tile - 1) / tile; + ends[e] = end; + } + __syncthreads(); + if (t < pairs) { + const int e = pk[t]; + int before = 0; + for (int q = 0; q < t; ++q) before += pk[q] == e; + members[starts[e] + before] = t; + } + for (int slot = t; slot < capacity; slot += kThreads) { + int a = 0, b = experts; + while (a < b) { // searchsorted(ends, slot, right=True) + const int mid = (a + b) / 2; + if (ends[mid] <= slot) a = mid + 1; + else b = mid; + } + const int e = a < experts - 1 ? a : experts - 1; + const int reps = (counts[e] + tile - 1) / tile; + const int within = slot - (ends[e] - reps); + const int count = counts[e] - within * tile; + items[slot * 3] = e; + items[slot * 3 + 1] = starts[e] + within * tile; + items[slot * 3 + 2] = count < 0 ? 0 : (count > tile ? tile : count); + } +} + +// One launch: tf_router_decode's logits from bf16 rows, then the last block's picks and plan; `done` is 0 after it. +template +__device__ void router_select(const void* x, const void* rows, float* logits, int r, int d, int e, int* pick, float* wts, + int* items, int* members, int capacity, int top_k, int tile, int staged, unsigned* done) { + __shared__ bool last; + // the dynamic shared memory the host sized (none where it stages nothing and plans nothing; launches/moe.zig) + extern __shared__ __attribute__((aligned(16))) uint4 router_shared[]; + // a verify window's few rows in shared memory once a block: each wave (an expert) reads them there, not from L2 + const void* xs = router_shared; + if (staged) { + const uint4* from = static_cast(x); + for (int i = threadIdx.x; i < r * d / 8; i += 32 * kRouterWaves) router_shared[i] = from[i]; + __syncthreads(); + } + const int expert = blockIdx.x * kRouterWaves + (threadIdx.x >> 5); + if (expert < e) router_decode(staged ? xs : x, rows, logits, r, d, e, staged); + __threadfence(); + __syncthreads(); + if (threadIdx.x == 0) last = atomicAdd(done, 1u) == gridDim.x - 1; + __syncthreads(); + if (!last) return; + __threadfence(); + if (r == 1) { + select_row(logits, 0, pick, wts, items, members, capacity, e - 1, top_k); + } else if (r <= 2 * kRouterWaves && e - 1 <= kSelectMax) { + // a wave a row (half a wave past kRouterWaves rows), NaN rows by select_row; the plan reuses the staged memory + __shared__ int fallback[2 * kRouterWaves]; + int* pool = reinterpret_cast(router_shared) + 2 * 32 * kRouterWaves; + const int wave = threadIdx.x >> 5; + __syncthreads(); + const int lane = threadIdx.x & 31; + if (r > kRouterWaves && e - 1 <= 16 * 32 && top_k <= 16) { + // 5 to 8 rows: half a wave a row, rows w and w + kRouterWaves in wave w's two halves + const int row = wave + (lane >= 16 ? kRouterWaves : 0); + const bool live = row < r; + const bool bad = select_row_lanes<32, 16>(logits, row, live, pick, wts, e - 1, top_k); + if (live && (lane & 15) == 0) fallback[row] = bad; + } else { + for (int row = wave; row < r; row += kRouterWaves) { + const bool bad = e - 1 <= 16 * 32 ? select_row_lanes<16, 32>(logits, row, true, pick, wts, e - 1, top_k) + : select_row_lanes(logits, row, true, pick, wts, e - 1, top_k); + if (lane == 0) fallback[row] = bad; + } + } + __syncthreads(); + for (int row = 0; row < r; ++row) + if (fallback[row]) select_row(logits, row, pick, wts, nullptr, nullptr, 0, e - 1, top_k); + __threadfence_block(); + __syncthreads(); + if (items != nullptr) route_plan(pick, r * (top_k + 1), e, tile, members, items, capacity, pool); + } else { + for (int row = 0; row < r; ++row) select_row(logits, row, pick, wts, nullptr, nullptr, 0, e - 1, top_k); + } + if (threadIdx.x == 0) *done = 0u; +} + +} // namespace diff --git a/zig/kernels/hip/flashnext/indexer.hpp b/zig/kernels/hip/flashnext/indexer.hpp index 1c1b75d208..4233341218 100644 --- a/zig/kernels/hip/flashnext/indexer.hpp +++ b/zig/kernels/hip/flashnext/indexer.hpp @@ -1,6 +1,7 @@ #pragma once #include "streams.hpp" +#include "../ops/qk_rope_wave.hpp" // The sparse attention's indexer: pooled block keys, each row's block scores, and the blocks a row attends. @@ -9,17 +10,11 @@ namespace { constexpr int kSelectThreads = 1024; constexpr int kSelectWaves = kSelectThreads / 32; -// Block b: the mean of its ratio raw keys, RMS-normed with scale and rotated at its first position, as tf_qk_rope. -extern "C" __global__ void __launch_bounds__(kFnThreads) -tf_fn_idx_pool(const void* raw, void* pooled, const float* scale, int kind, int first, const int* pos, int dims, - int ratio, int rotary, float theta, float eps) { - __shared__ float scratch[kFnWaves]; - __shared__ float normed[kFnThreads]; - // With `pos`, launch x is a row whose completed block (if any) fills slot b; else block first + x fills slot x. - const int end = pos ? pos[blockIdx.x] + 1 : 0; - if (pos && end % ratio != 0) return; - const int b = pos ? end / ratio - 1 : first + blockIdx.x, d = threadIdx.x; - const long long slot = pos ? b : blockIdx.x; +// Block b (kFnThreads): the mean of its ratio raw keys, normed and rotated as tf_qk_rope, into slot `slot` of pooled. +__device__ __forceinline__ void fn_idx_pool_block(const void* raw, void* pooled, const float* scale, int kind, int b, + long long slot, int dims, int ratio, int rotary, float theta, float eps, + float* scratch, float* normed) { + const int d = threadIdx.x; float x = 0.f; if (d < dims) { float m = 0.f; @@ -42,6 +37,110 @@ tf_fn_idx_pool(const void* raw, void* pooled, const float* scale, int kind, int store(pooled, kind, slot * dims + d, rounded(y, kind)); } +// Block b: the mean of its ratio raw keys, RMS-normed with scale and rotated at its first position, as tf_qk_rope. +extern "C" __global__ void __launch_bounds__(kFnThreads) +tf_fn_idx_pool(const void* raw, void* pooled, const float* scale, int kind, int first, const int* pos, int dims, + int ratio, int rotary, float theta, float eps) { + __shared__ float scratch[kFnWaves]; + __shared__ float normed[kFnThreads]; + // With `pos`, launch x is a row whose completed block (if any) fills slot b; else block first + x fills slot x. + const int end = pos ? pos[blockIdx.x] + 1 : 0; + if (pos && end % ratio != 0) return; + const int b = pos ? end / ratio - 1 : first + blockIdx.x; + fn_idx_pool_block(raw, pooled, scale, kind, b, pos ? b : blockIdx.x, dims, ratio, rotary, theta, eps, scratch, normed); +} + +// A QSA layer's decode prep in one launch: q, index q and k as tf_qk_rope, v and the raw index key cached, the pools. +struct QsaRope { + const void* src; + long long s_row; + int s_head; + int heads; + int width; + const float* weight; + float* wide; // fp32 rows (heads x width a row), or null + void* cache; // the cache's heads of `total` slots of width, or null +}; +struct QsaPrep { + QsaRope q, iq, k; + const void* v; // the segment's v rows (k.heads x v_width) + void* v_cache; + int v_width; + const void* raw; // the index projection rows; the raw key at raw_offset, rows raw_stride apart + long long raw_stride; + int raw_offset; + void* raw_cache; // one head of `total` slots of raw_width + int raw_width; + void* pooled; + const float* pool_scale; + int ratio; + const int* pos; // q and index q rows' positions (rows) + const int* seg_pos; // the segment's rows' positions (n) + int rows; + int n; + int total; + int kind; + float eps; + int rotary; + float theta; +}; + +extern "C" __global__ void __launch_bounds__(kFnThreads) tf_fn_qsa_prep(QsaPrep a) { + const int tq = a.q.src ? a.rows * a.q.heads : 0; + const int tiq = a.q.src ? a.rows * a.iq.heads : 0; + const int tasks = tq + tiq + a.n * a.k.heads; + const int rope_blocks = (tasks + kFnWaves - 1) / kFnWaves; + if (static_cast(blockIdx.x) < rope_blocks) { + __shared__ float row_v[kFnWaves][512]; + const int wave = threadIdx.x >> 5; + const int g = blockIdx.x * kFnWaves + wave; + const bool live = g < tasks; + const int which = !live || g < tq ? 0 : g < tq + tiq ? 1 : 2; + const QsaRope& t = which == 0 ? a.q : which == 1 ? a.iq : a.k; + const int gi = !live ? 0 : which == 0 ? g : which == 1 ? g - tq : g - tq - tiq; + const int r = gi / t.heads, h = gi % t.heads; + qk_rope_norm(t.src, a.kind, r * t.s_row + static_cast(h) * t.s_head, t.weight, a.eps, t.width, live, + row_v[wave]); + __syncthreads(); + if (!live) return; + const int p = (which == 2 ? a.seg_pos : a.pos)[r]; + qk_rope_put(a.kind, t.width, a.rotary, a.theta, p, row_v[wave], + t.wide ? t.wide + static_cast(gi) * t.width : nullptr, t.cache, + (static_cast(h) * a.total + p) * t.width); + return; + } + // the last block: v and the raw index key into their caches (16-bit or fp32 values copied), then the pools + const int first = a.seg_pos[0]; + const long long nv = static_cast(a.n) * a.k.heads * a.v_width; + for (long long i = threadIdx.x; i < nv; i += kFnThreads) { + const int j = static_cast(i % a.v_width); + const int h = static_cast((i / a.v_width) % a.k.heads); + const int r = static_cast(i / (static_cast(a.v_width) * a.k.heads)); + const long long to = (static_cast(h) * a.total + first + r) * a.v_width + j; + if (a.kind == 0) static_cast(a.v_cache)[to] = static_cast(a.v)[i]; + else static_cast(a.v_cache)[to] = static_cast(a.v)[i]; + } + const long long nr = static_cast(a.n) * a.raw_width; + for (long long i = threadIdx.x; i < nr; i += kFnThreads) { + const long long r = i / a.raw_width; + const int c = static_cast(i % a.raw_width); + const long long from = r * a.raw_stride + a.raw_offset + c; + const long long to = (first + r) * a.raw_width + c; + if (a.kind == 0) static_cast(a.raw_cache)[to] = static_cast(a.raw)[from]; + else static_cast(a.raw_cache)[to] = static_cast(a.raw)[from]; + } + __shared__ float scratch[kFnWaves]; + __shared__ float normed[kFnThreads]; + for (int r = 0; r < a.n; ++r) { + __syncthreads(); + const int end = a.seg_pos[r] + 1; + if (end % a.ratio != 0) continue; + const int b = end / a.ratio - 1; + fn_idx_pool_block(a.raw_cache, a.pooled, a.pool_scale, a.kind, b, b, a.raw_width, a.ratio, a.rotary, a.theta, + a.eps, scratch, normed); + } +} + // Wave w of block (x, y) scores block 8 x + w for rows 8 y ..: the sum over heads of relu(q . key) / sqrt(dims). extern "C" __global__ void __launch_bounds__(kFnThreads) tf_fn_idx_scores(const float* q, const void* pooled, const int* complete, float* scores, int kind, int rows, int heads, @@ -79,6 +178,114 @@ tf_fn_idx_scores(const float* q, const void* pooled, const int* complete, float* } } +// tf_fn_idx_scores for 4 x 128 index heads at a window's rows: a wave's 8 rows' dots before the butterflies: same bits. +extern "C" __global__ void __launch_bounds__(kFnThreads) +tf_fn_idx_scores8(const float* q, const void* pooled, const int* complete, float* scores, int kind, int rows, + int blocks, long long stride, int top) { + constexpr int R = 8, H = 4, D = 128, I = D / 32; + const int lane = threadIdx.x & 31; + const int b = blockIdx.x * kFnWaves + (threadIdx.x >> 5); + const int r0 = blockIdx.y * R, r1 = min(rows, r0 + R); + bool wanted = false; // a graph launches over a bound of blocks: those no row scores read nothing + for (int r = r0; r < r1; ++r) wanted = wanted || (complete[r] > top && b < complete[r]); + if (b >= blocks || !wanted) return; + float key[I]; +#pragma unroll + for (int i = 0; i < I; ++i) key[i] = load(pooled, kind, static_cast(b) * D + lane + 32 * i); + float dot[R][H]; +#pragma unroll + for (int j = 0; j < R; ++j) { + const int r = min(r0 + j, rows - 1); +#pragma unroll + for (int h = 0; h < H; ++h) { + const float* qh = q + (static_cast(r) * H + h) * D; + float x = 0.f; +#pragma unroll + for (int i = 0; i < I; ++i) x += qh[lane + 32 * i] * key[i]; + dot[j][h] = x; + } + } +#pragma unroll + for (int mask = 16; mask > 0; mask >>= 1) +#pragma unroll + for (int j = 0; j < R; ++j) +#pragma unroll + for (int h = 0; h < H; ++h) dot[j][h] += __shfl_xor(dot[j][h], mask, 32); + const float norm = sqrtf(static_cast(D)); +#pragma unroll + for (int j = 0; j < R; ++j) { + const int r = r0 + j; + if (r >= r1 || complete[r] <= top || b >= complete[r]) continue; + float total = 0.f; +#pragma unroll + for (int h = 0; h < H; ++h) total += fmaxf(dot[j][h], 0.f); + if (lane == 0) scores[r * stride + b] = total / norm; + } +} + +// A prompt slice's scores for 4 heads of 128 dims, 4 lanes a score in tf_fn_idx_scores's sum order: the same bits. +constexpr int kQuadRows = 32, kQuadBlocks = 64, kQuadDims = 128, kQuadHeads = 4; + +__device__ __forceinline__ float fn_quad_sum(const float (&part)[8]) { + const float a0 = part[0] + part[4], a1 = part[1] + part[5], a2 = part[2] + part[6], a3 = part[3] + part[7]; + const float b0 = a0 + a2, b1 = a1 + a3; + float c = b0 + b1; + c = c + __shfl_xor(c, 2, 32); + c = c + __shfl_xor(c, 1, 32); + return c; +} + +extern "C" __global__ void __launch_bounds__(128) +tf_fn_idx_scores_quad(const float* q, const void* pooled, const int* complete, float* scores, int kind, int rows, + int blocks, long long stride, int top) { + constexpr int D = kQuadDims, H = kQuadHeads; + __shared__ __attribute__((aligned(16))) float ks[kQuadBlocks][D]; // transposed: [blk][p * 32 + m] = key[p + 4 m] + __shared__ int any; + const int lane = threadIdx.x & 31, wave = threadIdx.x >> 5, p = lane & 3; + const int r = blockIdx.y * kQuadRows + wave * 8 + (lane >> 2); + const int b0 = blockIdx.x * kQuadBlocks; + const int lim = r < rows && complete[r] > top ? complete[r] : 0; // the row scores blocks below lim + if (threadIdx.x == 0) any = 0; + __syncthreads(); + if (lim > b0 && (lane & 3) == 0) atomicOr(&any, 1); + __syncthreads(); + if (!any) return; // no row of this tile scores a block of it + for (int e = threadIdx.x; e < kQuadBlocks * D; e += 128) { + const int blk = e / D, d = e - blk * D; + ks[blk][(d & 3) * 32 + (d >> 2)] = b0 + blk < blocks ? load(pooled, kind, static_cast(b0 + blk) * D + d) : 0.f; + } + float qv[H][32]; +#pragma unroll + for (int h = 0; h < H; ++h) +#pragma unroll + for (int m = 0; m < 32; ++m) qv[h][m] = r < rows ? q[(static_cast(r) * H + h) * D + p + 4 * m] : 0.f; + __syncthreads(); + const float norm = sqrtf(static_cast(D)); + const int n = min(kQuadBlocks, blocks - b0); + for (int blk = 0; blk < n; ++blk) { + float key[32]; + const float4* k4 = reinterpret_cast(&ks[blk][p * 32]); +#pragma unroll + for (int c = 0; c < 8; ++c) { + const float4 a = k4[c]; + key[4 * c] = a.x, key[4 * c + 1] = a.y, key[4 * c + 2] = a.z, key[4 * c + 3] = a.w; + } + float total = 0.f; +#pragma unroll + for (int h = 0; h < H; ++h) { + float part[8]; +#pragma unroll + for (int j = 0; j < 8; ++j) part[j] = 0.f; +#pragma unroll + for (int i = 0; i < 4; ++i) +#pragma unroll + for (int j = 0; j < 8; ++j) part[j] = part[j] + qv[h][j + 8 * i] * key[j + 8 * i]; + total += fmaxf(fn_quad_sum(part), 0.f); + } + if (p == 0 && b0 + blk < lim) scores[r * stride + b0 + blk] = total / norm; + } +} + // An order-keeping unsigned key of a float: larger floats, larger keys. __device__ __forceinline__ unsigned fn_order(float v) { const unsigned u = __float_as_uint(v); @@ -116,6 +323,7 @@ extern "C" __global__ void __launch_bounds__(kSelectThreads) tf_fn_idx_select(const float* scores, long long stride, const int* complete, const int* ends, int* keys, long long key_stride, int* count, int* sparse, int top, int ratio) { __shared__ int hist[256]; + __shared__ int suf[256]; __shared__ int waves[kSelectWaves]; __shared__ unsigned cut_s; __shared__ int need_s; @@ -139,11 +347,32 @@ tf_fn_idx_select(const float* scores, long long stride, const int* complete, con if ((k & mask) == prefix) atomicAdd(&hist[(k >> shift) & 255u], 1); } __syncthreads(); - if (t == 0) { - int above = 0, bin = 255; - while (above + hist[bin] < need) above += hist[bin--]; - cut_s = prefix | (static_cast(bin) << shift); - need_s = need - above; + // suf[i]: the count in bins 255 - i .. 255 (8 waves of 32 bins: a wave's scan, then the waves above it) + if (t < 256) { + const int lane = t & 31; + int x = hist[255 - t]; +#pragma unroll + for (int off = 1; off < 32; off <<= 1) { + const int y = __shfl_up(x, off, 32); + if (lane >= off) x += y; + } + if (lane == 31) waves[t >> 5] = x; + suf[t] = x; + } + __syncthreads(); + if (t < 256) { + int add = 0; + for (int w = 0; w < (t >> 5); ++w) add += waves[w]; + suf[t] += add; + } + __syncthreads(); + // the cut: the one i with suf[i] >= need and the bins above it under need (the bins hold at least need) + if (t < 256) { + const int above = t > 0 ? suf[t - 1] : 0; + if (suf[t] >= need && above < need) { + cut_s = prefix | (static_cast(255 - t) << shift); + need_s = need - above; + } } __syncthreads(); prefix = cut_s; diff --git a/zig/kernels/hip/flashnext/streams.hpp b/zig/kernels/hip/flashnext/streams.hpp index 91405295b3..71a6b998a4 100644 --- a/zig/kernels/hip/flashnext/streams.hpp +++ b/zig/kernels/hip/flashnext/streams.hpp @@ -27,10 +27,11 @@ __device__ float fn_block_sum(float v, float* scratch) { return total; } -// Block (s, r): h_s += round(branch * inject[s]) (tp: `world` fp32 shares, summed in order), then x = h rinv scale. -extern "C" __global__ void __launch_bounds__(kNormThreads) -tf_fn_hc_norm(const void* h, const void* branch, const void* inject, void* h_out, void* x_out, const float* scale, - int kind, int streams, int dims, float eps, int world, long long stride) { +// Block (s, r): h_s += round(branch(r, d) * inject[s]) with a branch (rounded to `kind`), then x = h rinv scale. +template +__device__ __forceinline__ void hc_norm_body(const void* h, bool has_branch, Branch branch, const void* inject, + void* h_out, void* x_out, const float* scale, int kind, int streams, + int dims, float eps) { __shared__ float scratch[kNormThreads / 32]; const int s = blockIdx.x, r = blockIdx.y; const long long base = (static_cast(r) * streams + s) * dims; @@ -42,17 +43,8 @@ tf_fn_hc_norm(const void* h, const void* branch, const void* inject, void* h_out v[j] = 0.f; if (d >= dims) continue; float x = load(h, kind, base + d); - if (branch != nullptr) { - const long long at = static_cast(r) * dims + d; - float b; - if (world > 0) { - b = 0.f; - for (int w = 0; w < world; ++w) b += static_cast(branch)[w * stride + at]; - b = rounded(b, kind); - } else { - b = load(branch, kind, at); - } - const float add = rounded(b * load(inject, kind, static_cast(r) * streams + s), kind); + if (has_branch) { + const float add = rounded(branch(r, d) * load(inject, kind, static_cast(r) * streams + s), kind); x = rounded(x + add, kind); } v[j] = x; @@ -69,6 +61,220 @@ tf_fn_hc_norm(const void* h, const void* branch, const void* inject, void* h_out } } +// Block (s, r): h_s += round(branch * inject[s]) (tp: `world` fp32 shares, summed in order), then x = h rinv scale. +extern "C" __global__ void __launch_bounds__(kNormThreads) +tf_fn_hc_norm(const void* h, const void* branch, const void* inject, void* h_out, void* x_out, const float* scale, + int kind, int streams, int dims, float eps, int world, long long stride) { + hc_norm_body( + h, branch != nullptr, + [&](int r, int d) { + const long long at = static_cast(r) * dims + d; + if (world <= 0) return load(branch, kind, at); + float b = 0.f; + for (int w = 0; w < world; ++w) b += static_cast(branch)[w * stride + at]; + return rounded(b, kind); + }, + inject, h_out, x_out, scale, kind, streams, dims, eps); +} + +// The same with the MoE's combine as the branch, summed and rounded as moe_combine_kernel: one launch for both. +extern "C" __global__ void __launch_bounds__(kNormThreads) +tf_fn_hc_norm_moe(const void* h, const float* y, const float* wts, const void* inject, void* h_out, void* x_out, + const float* scale, int kind, int streams, int dims, float eps, int slots) { + hc_norm_body( + h, true, + [&](int r, int d) { + float acc = 0.f; + for (int k = 0; k < slots; ++k) acc += y[(static_cast(r) * slots + k) * dims + d] * wts[r * slots + k]; + return rounded(acc, kind); + }, + inject, h_out, x_out, scale, kind, streams, dims, eps); +} + +// tf_fn_hc_norm over bf16 streams of 2,560 in a 128-thread block, 16-byte accesses, the old block's sums: same bits. +constexpr int kNormVThreads = 128; +constexpr int kNormVDims = 2560; +extern "C" __global__ void __launch_bounds__(kNormVThreads) +tf_fn_hc_norm_v(const uint16_t* h, const uint16_t* branch, const uint16_t* inject, uint16_t* h_out, uint16_t* x_out, + const float* scale, int streams, float eps) { + __shared__ float scratch[kNormThreads / 32]; + const int s = blockIdx.x, r = blockIdx.y, lane = threadIdx.x; + const long long base = (static_cast(r) * streams + s) * kNormVDims; + const float inj = branch != nullptr ? bf16_to_float(inject[static_cast(r) * streams + s]) : 0.f; + float v[3][8]; + float part[8]; +#pragma unroll + for (int e = 0; e < 8; ++e) part[e] = 0.f; +#pragma unroll + for (int j = 0; j < 3; ++j) { + const int d0 = 8 * lane + j * kNormThreads; + if (d0 >= kNormVDims) break; + const uint4 hv = *reinterpret_cast(h + base + d0); + const uint32_t hw[4] = {hv.x, hv.y, hv.z, hv.w}; + uint32_t bw[4] = {0, 0, 0, 0}; + if (branch != nullptr) { + const uint4 bv = *reinterpret_cast(branch + static_cast(r) * kNormVDims + d0); + bw[0] = bv.x, bw[1] = bv.y, bw[2] = bv.z, bw[3] = bv.w; + } +#pragma unroll + for (int e = 0; e < 8; ++e) { + float x = bf16_to_float(static_cast(hw[e >> 1] >> ((e & 1) * 16))); + if (branch != nullptr) { + const float b = bf16_to_float(static_cast(bw[e >> 1] >> ((e & 1) * 16))); + const float add = rounded(b * inj, 2); + x = rounded(x + add, 2); + } + v[j][e] = x; + part[e] += x * x; + } + } + // the old wave tree: xor 16 (lane ^ 2), xor 8 (lane ^ 1), then xor 4, 2, 1 inside the lane's 8 +#pragma unroll + for (int e = 0; e < 8; ++e) part[e] = part[e] + __shfl_xor(part[e], 2, 32); +#pragma unroll + for (int e = 0; e < 8; ++e) part[e] = part[e] + __shfl_xor(part[e], 1, 32); +#pragma unroll + for (int m = 4; m > 0; m >>= 1) { + float next[8]; +#pragma unroll + for (int e = 0; e < 8; ++e) next[e] = part[e] + part[e ^ m]; +#pragma unroll + for (int e = 0; e < 8; ++e) part[e] = next[e]; + } + if ((lane & 3) == 0) scratch[lane >> 2] = part[0]; + __syncthreads(); + float total = 0.f; + for (int w = 0; w < kNormThreads / 32; ++w) total += scratch[w]; + const float rinv = rsqrtf(total / static_cast(kNormVDims) + eps); +#pragma unroll + for (int j = 0; j < 3; ++j) { + const int d0 = 8 * lane + j * kNormThreads; + if (d0 >= kNormVDims) break; + uint32_t ho[4], xo[4]; +#pragma unroll + for (int q = 0; q < 4; ++q) { + const float a0 = v[j][2 * q], a1 = v[j][2 * q + 1]; + ho[q] = static_cast(float_to_bf16(a0)) | (static_cast(float_to_bf16(a1)) << 16); + const float x0 = (a0 * rinv) * scale[s * kNormVDims + d0 + 2 * q]; + const float x1 = (a1 * rinv) * scale[s * kNormVDims + d0 + 2 * q + 1]; + xo[q] = static_cast(float_to_bf16(x0)) | (static_cast(float_to_bf16(x1)) << 16); + } + if (h_out != nullptr) *reinterpret_cast(h_out + base + d0) = uint4{ho[0], ho[1], ho[2], ho[3]}; + *reinterpret_cast(x_out + base + d0) = uint4{xo[0], xo[1], xo[2], xo[3]}; + } +} + +// tf_fn_hc_norm_v with the MoE's combine as the branch for a prompt's rows: moe_combine_kernel's then its bytes. +constexpr int kNormMoeVMost = 4; +extern "C" __global__ void __launch_bounds__(kNormMoeVMost * kNormVThreads) +tf_fn_hc_norm_moe_v(const uint16_t* h, const float* y, const float* wts, const uint16_t* inject, uint16_t* h_out, + uint16_t* x_out, const float* scale, int streams, float eps, int slots) { + __shared__ float br[kNormVDims]; + __shared__ float scratch[kNormMoeVMost][kNormThreads / 32]; + const int r = blockIdx.y, tid = threadIdx.x; + for (int d = tid; d < kNormVDims; d += streams * kNormVThreads) { + float acc = 0.f; + for (int k = 0; k < slots; ++k) acc += y[(static_cast(r) * slots + k) * kNormVDims + d] * wts[r * slots + k]; + br[d] = rounded(acc, 2); + } + __syncthreads(); + const int s = tid / kNormVThreads, lane = tid % kNormVThreads; + const long long base = (static_cast(r) * streams + s) * kNormVDims; + const float inj = bf16_to_float(inject[static_cast(r) * streams + s]); + float v[3][8]; + float part[8]; +#pragma unroll + for (int e = 0; e < 8; ++e) part[e] = 0.f; +#pragma unroll + for (int j = 0; j < 3; ++j) { + const int d0 = 8 * lane + j * kNormThreads; + if (d0 >= kNormVDims) break; + const uint4 hv = *reinterpret_cast(h + base + d0); + const uint32_t hw[4] = {hv.x, hv.y, hv.z, hv.w}; +#pragma unroll + for (int e = 0; e < 8; ++e) { + float x = bf16_to_float(static_cast(hw[e >> 1] >> ((e & 1) * 16))); + const float add = rounded(br[d0 + e] * inj, 2); + x = rounded(x + add, 2); + v[j][e] = x; + part[e] += x * x; + } + } + // tf_fn_hc_norm_v's tree: xor 16 (lane ^ 2), xor 8 (lane ^ 1), then xor 4, 2, 1 inside the lane's 8 +#pragma unroll + for (int e = 0; e < 8; ++e) part[e] = part[e] + __shfl_xor(part[e], 2, 32); +#pragma unroll + for (int e = 0; e < 8; ++e) part[e] = part[e] + __shfl_xor(part[e], 1, 32); +#pragma unroll + for (int m = 4; m > 0; m >>= 1) { + float next[8]; +#pragma unroll + for (int e = 0; e < 8; ++e) next[e] = part[e] + part[e ^ m]; +#pragma unroll + for (int e = 0; e < 8; ++e) part[e] = next[e]; + } + if ((lane & 3) == 0) scratch[s][lane >> 2] = part[0]; + __syncthreads(); + float total = 0.f; + for (int w = 0; w < kNormThreads / 32; ++w) total += scratch[s][w]; + const float rinv = rsqrtf(total / static_cast(kNormVDims) + eps); +#pragma unroll + for (int j = 0; j < 3; ++j) { + const int d0 = 8 * lane + j * kNormThreads; + if (d0 >= kNormVDims) break; + uint32_t ho[4], xo[4]; +#pragma unroll + for (int q = 0; q < 4; ++q) { + const float a0 = v[j][2 * q], a1 = v[j][2 * q + 1]; + ho[q] = static_cast(float_to_bf16(a0)) | (static_cast(float_to_bf16(a1)) << 16); + const float x0 = (a0 * rinv) * scale[s * kNormVDims + d0 + 2 * q]; + const float x1 = (a1 * rinv) * scale[s * kNormVDims + d0 + 2 * q + 1]; + xo[q] = static_cast(float_to_bf16(x0)) | (static_cast(float_to_bf16(x1)) << 16); + } + *reinterpret_cast(h_out + base + d0) = uint4{ho[0], ho[1], ho[2], ho[3]}; + *reinterpret_cast(x_out + base + d0) = uint4{xo[0], xo[1], xo[2], xo[3]}; + } +} + +// tf_fn_hc_mix over bf16 activations, 8 neighbouring outputs a thread (16-byte loads of g and x), the same bits. +extern "C" __global__ void tf_fn_hc_mix8(const void* g, int gkind, const uint16_t* x, uint16_t* mixed, int rows, + int streams, int dims) { + const long long i = gid() * 8; + if (i >= static_cast(rows) * dims) return; + const long long r = i / dims; + const int d = static_cast(i % dims); + float total[8]; +#pragma unroll + for (int e = 0; e < 8; ++e) total[e] = 0.f; + for (int s = 0; s < streams; ++s) { + const long long at = (r * streams + s) * dims + d; + float gv[8]; + if (gkind == 2) { + const uint4 u = *reinterpret_cast(static_cast(g) + at); + const uint32_t w[4] = {u.x, u.y, u.z, u.w}; +#pragma unroll + for (int e = 0; e < 8; ++e) gv[e] = bf16_to_float(static_cast(w[e >> 1] >> ((e & 1) * 16))); + } else { + const float4 a = *reinterpret_cast(static_cast(g) + at); + const float4 b = *reinterpret_cast(static_cast(g) + at + 4); + gv[0] = a.x, gv[1] = a.y, gv[2] = a.z, gv[3] = a.w, gv[4] = b.x, gv[5] = b.y, gv[6] = b.z, gv[7] = b.w; + } + const uint4 xu = *reinterpret_cast(x + at); + const uint32_t xw[4] = {xu.x, xu.y, xu.z, xu.w}; +#pragma unroll + for (int e = 0; e < 8; ++e) { + const float gate = rounded(sigmoid(rounded(gv[e], 2)), 2); + total[e] += rounded(gate * bf16_to_float(static_cast(xw[e >> 1] >> ((e & 1) * 16))), 2); + } + } + uint32_t o[4]; +#pragma unroll + for (int q = 0; q < 4; ++q) + o[q] = static_cast(float_to_bf16(total[2 * q] / static_cast(streams))) | + (static_cast(float_to_bf16(total[2 * q + 1] / static_cast(streams))) << 16); + *reinterpret_cast(mixed + i) = uint4{o[0], o[1], o[2], o[3]}; +} + // From z [rows, low (+ streams with inject)] / streams: silu for the up projection, 2 sigmoid for the inject gates. extern "C" __global__ void tf_fn_hc_gates(const float* z, void* act, void* inject, int kind, int rows, int low, int streams) { @@ -98,8 +304,8 @@ tf_fn_rms_wide(const void* x, const float* scale, void* y, int kind, int width, } // mixed[r, d] = mean over the streams (in order) of round(sigmoid(round(g)) * x): g the up projection's fp32 sums. -extern "C" __global__ void tf_fn_hc_mix(const float* g, const void* x, void* mixed, int kind, int rows, int streams, - int dims) { +extern "C" __global__ void tf_fn_hc_mix(const void* g, int gkind, const void* x, void* mixed, int kind, int rows, + int streams, int dims) { const long long i = gid(); if (i >= static_cast(rows) * dims) return; const long long r = i / dims; @@ -107,7 +313,7 @@ extern "C" __global__ void tf_fn_hc_mix(const float* g, const void* x, void* mix float total = 0.f; for (int s = 0; s < streams; ++s) { const long long at = (r * streams + s) * dims + d; - const float gate = rounded(sigmoid(rounded(g[at], kind)), kind); + const float gate = rounded(sigmoid(rounded(load(g, gkind, at), kind)), kind); total += rounded(gate * load(x, kind, at), kind); } store(mixed, kind, i, total / static_cast(streams)); diff --git a/zig/kernels/hip/ops/draw.hpp b/zig/kernels/hip/ops/draw.hpp index 196a4f61a2..909c7540cd 100644 --- a/zig/kernels/hip/ops/draw.hpp +++ b/zig/kernels/hip/ops/draw.hpp @@ -124,17 +124,32 @@ __device__ __forceinline__ uint32_t order_key(uint16_t bits) { return (bits & 0x8000) ? (~bits & 0xffffu) : (bits | 0x8000u); } -// Row r's ks[r] largest by (value desc, id asc): two histograms of the k-th key, then one ordered compaction. -extern "C" __global__ void tf_topk(const uint16_t* logits, int n, const int* ks, int stride, int* ids, uint16_t* values) { - const int r = blockIdx.x, k = ks[r]; - if (k <= 0) return; - const uint16_t* row = logits + static_cast(r) * n; - __shared__ int hist[256]; - __shared__ int pick[4]; // high byte, low byte, count above, count of the k-th key to take - __shared__ int wave_gt[kWaves], wave_eq[kWaves]; +// A row's entries for the top-k: `has(i)` for i < n, their 16-bit values and ids. +struct RowEntries { + const uint16_t* row; // the slice's first value + int base, n; // the slice's first id and length + __device__ bool has(int i) const { return i < n; } + __device__ uint16_t bits(int i) const { return row[i]; } + __device__ int id(int i) const { return base + i; } +}; + +// tf_topk_part's candidates of a row: `parts` lists of `stride` slots, an absent slot's id -1. +struct Candidates { + const int* ids; + const uint16_t* vals; + int n; + __device__ bool has(int i) const { return i < n && ids[i] >= 0; } + __device__ uint16_t bits(int i) const { return vals[i]; } + __device__ int id(int i) const { return ids[i]; } +}; + +// The k-th largest key by two 8-bit histograms: pick = {high byte, low byte, keys above it, how many of it to take}. +template +__device__ void topk_kth(const E& e, int k, int* hist, int* pick) { for (int i = threadIdx.x; i < 256; i += kThreads) hist[i] = 0; __syncthreads(); - for (int i = threadIdx.x; i < n; i += kThreads) atomicAdd(&hist[order_key(row[i]) >> 8], 1); + for (int i = threadIdx.x; i < e.n; i += kThreads) + if (e.has(i)) atomicAdd(&hist[order_key(e.bits(i)) >> 8], 1); __syncthreads(); if (threadIdx.x == 0) { int above = 0, b = 255; @@ -146,8 +161,9 @@ extern "C" __global__ void tf_topk(const uint16_t* logits, int n, const int* ks, for (int i = threadIdx.x; i < 256; i += kThreads) hist[i] = 0; __syncthreads(); const uint32_t high = pick[0]; - for (int i = threadIdx.x; i < n; i += kThreads) { - uint32_t key = order_key(row[i]); + for (int i = threadIdx.x; i < e.n; i += kThreads) { + if (!e.has(i)) continue; + uint32_t key = order_key(e.bits(i)); if ((key >> 8) == high) atomicAdd(&hist[key & 255u], 1); } __syncthreads(); @@ -155,19 +171,27 @@ extern "C" __global__ void tf_topk(const uint16_t* logits, int n, const int* ks, int above = pick[2], b = 255; for (; b > 0 && above + hist[b] < k; --b) above += hist[b]; pick[1] = b; - pick[2] = above; // the keys above the k-th - pick[3] = k - above; // how many of the k-th's to take, lowest ids first + pick[2] = above; // the keys above the k-th + pick[3] = k - above; // how many of the k-th's to take, lowest ids first } __syncthreads(); - const uint32_t kth = (high << 8) | static_cast(pick[1]); +} + +// Row r's ks[r] largest by (value desc, id asc) in one ordered compaction: keys above the k-th, then its lowest ids. +__device__ void topk_slice(const RowEntries& e, int k, int* ids, uint16_t* values) { + __shared__ int hist[256]; + __shared__ int pick[4]; + __shared__ int wave_gt[kWaves], wave_eq[kWaves]; + topk_kth(e, k, hist, pick); + const uint32_t kth = (static_cast(pick[0]) << 8) | static_cast(pick[1]); const int above = pick[2], take = pick[3]; int seen_gt = 0, seen_eq = 0; const int lane = threadIdx.x & 31, wave = threadIdx.x >> 5; - for (int base = 0; base < n; base += kThreads) { + for (int base = 0; base < e.n; base += kThreads) { int i = base + threadIdx.x; - uint16_t bits = i < n ? row[i] : 0; + uint16_t bits = i < e.n ? e.bits(i) : 0; uint32_t key = order_key(bits); - bool gt = i < n && key > kth, eq = i < n && key == kth; + bool gt = i < e.n && key > kth, eq = i < e.n && key == kth; unsigned long long mg = __ballot(gt), me = __ballot(eq); unsigned long long below = (1ull << lane) - 1; if (lane == 0) { @@ -182,14 +206,14 @@ extern "C" __global__ void tf_topk(const uint16_t* logits, int n, const int* ks, } if (gt) { int slot = gt_before + __popcll(mg & below); - ids[r * stride + slot] = i; - values[r * stride + slot] = bits; + ids[slot] = e.id(i); + values[slot] = bits; } if (eq) { int rank = eq_before + __popcll(me & below); if (rank < take) { - ids[r * stride + above + rank] = i; - values[r * stride + above + rank] = bits; + ids[above + rank] = e.id(i); + values[above + rank] = bits; } } for (int w = 0; w < kWaves; ++w) { @@ -201,4 +225,62 @@ extern "C" __global__ void tf_topk(const uint16_t* logits, int n, const int* ks, } } +extern "C" __global__ void tf_topk(const uint16_t* logits, int n, const int* ks, int stride, int* ids, uint16_t* values) { + const int r = blockIdx.x, k = ks[r]; + if (k <= 0) return; + topk_slice({logits + static_cast(r) * n, 0, n}, k, ids + r * stride, values + r * stride); +} + +// tf_topk over part blockIdx.x of row blockIdx.y: the part's own top min(ks[r], length) into `stride` slots (rest -1). +extern "C" __global__ void tf_topk_part(const uint16_t* logits, int n, const int* ks, int per, int stride, int* cand_ids, + uint16_t* cand_vals) { + const int r = blockIdx.y, p = blockIdx.x, k = ks[r]; + if (k <= 0) return; + const int base = p * per, len = max(0, min(per, n - base)), own = min(k, len); + const long long at = (static_cast(r) * gridDim.x + p) * stride; + for (int i = own + threadIdx.x; i < stride; i += kThreads) cand_ids[at + i] = -1; + if (own > 0) topk_slice({logits + static_cast(r) * n + base, base, len}, own, cand_ids + at, cand_vals + at); +} + +// Candidates a row's join holds in shared memory at most (tf_topk_parts' parts * stride). +constexpr int kJoinMost = 4096; + +// Row r's tf_topk from its parts' candidates: the same k-th key, then the same order, slots counted in shared memory. +extern "C" __global__ void tf_topk_join(const int* cand_ids, const uint16_t* cand_vals, int parts, const int* ks, int stride, + int* ids, uint16_t* values) { + const int r = blockIdx.x, k = ks[r]; + if (k <= 0) return; + const long long at = static_cast(r) * parts * stride; + const Candidates e{cand_ids + at, cand_vals + at, parts * stride}; + __shared__ int hist[256]; + __shared__ int pick[4]; + __shared__ int sid[kJoinMost]; + __shared__ uint32_t skey[kJoinMost]; + topk_kth(e, k, hist, pick); + const uint32_t kth = (static_cast(pick[0]) << 8) | static_cast(pick[1]); + const int above = pick[2], take = pick[3]; + // each candidate's id and class: 2 above the k-th, 1 the k-th's, 0 neither (or absent) + for (int i = threadIdx.x; i < e.n; i += kThreads) { + const uint32_t key = e.has(i) ? order_key(e.bits(i)) : 0u; + sid[i] = e.ids[i]; + skey[i] = !e.has(i) ? 0u : key > kth ? 2u : key == kth ? 1u : 0u; + } + __syncthreads(); + for (int i = threadIdx.x; i < e.n; i += kThreads) { + const uint32_t cls = skey[i]; + if (cls == 0) continue; + const bool gt = cls == 2; + const int id = sid[i]; + int before = 0; // the candidates of the same class with lower ids + for (int j = 0; j < e.n; ++j) before += skey[j] == cls && sid[j] < id; + if (gt) { + ids[r * stride + before] = id; + values[r * stride + before] = e.bits(i); + } else if (before < take) { + ids[r * stride + above + before] = id; + values[r * stride + above + before] = e.bits(i); + } + } +} + } // namespace diff --git a/zig/kernels/hip/ops/linear.hpp b/zig/kernels/hip/ops/linear.hpp index d133d7705e..7bcc1b6f48 100644 --- a/zig/kernels/hip/ops/linear.hpp +++ b/zig/kernels/hip/ops/linear.hpp @@ -39,6 +39,119 @@ extern "C" __global__ void tf_conv_prefill(const void* x, int kind, const float* } } +// A DeltaNet layer's prompt prework in one launch, the chain's values: conv, q/k head norms, v, new state, gate, beta. +constexpr int kPrepSeg = 16; + +__device__ __forceinline__ float prep_window(const void* x, int kind, const float* state, int kept, int channels, int c, + int t) { + if (t < kept) return state ? state[static_cast(t) * channels + c] : 0.0f; + return load(x, kind, static_cast(t - kept) * channels + c); +} + +extern "C" __global__ void __launch_bounds__(256) +tf_gdn_prompt_prep(const void* x, int kind, const float* weight, const float* state, float* new_state, float* q_out, + float* k_out, float* v_out, const float* qw, const float* kw_w, float eps, int len, int kwidth, + int vwidth, int kernel, const void* a, const void* b, const float* a_log, const float* dt_bias, + float* gate, float* beta, int heads) { + const int channels = 2 * kwidth + vwidth, kept = kernel - 1; + const int segs = (len + kPrepSeg - 1) / kPrepSeg; + const int qk_heads = 2 * kwidth / 128; + const int nA = (qk_heads * segs + 7) / 8, nB = ((vwidth + 255) / 256) * segs; + const int nC = (len * heads + 255) / 256; + int blk = blockIdx.x; + if (blk < nA) { + // q / k: a wave a head a segment + const int unit = blk * 8 + (threadIdx.x >> 5), lane = threadIdx.x & 31; + if (unit >= qk_heads * segs) return; + const int hd = unit % qk_heads, sg = unit / qk_heads; + const bool is_q = hd < qk_heads / 2; + const int r0 = sg * kPrepSeg, r1 = min(len, r0 + kPrepSeg); + float w[4][kConvTaps], win[4][kConvTaps]; +#pragma unroll + for (int j = 0; j < 4; ++j) { + const int c = hd * 128 + lane + 32 * j; + for (int tap = 0; tap < kernel; ++tap) w[j][tap] = weight[static_cast(c) * kernel + tap]; + for (int tap = 0; tap + 1 < kernel; ++tap) win[j][tap] = prep_window(x, kind, state, kept, channels, c, r0 + tap); + } + const float* nw = is_q ? qw : kw_w; + float* out = is_q ? q_out : k_out; + const int head = is_q ? hd : hd - qk_heads / 2; + for (int r = r0; r < r1; ++r) { + float v[4]; +#pragma unroll + for (int j = 0; j < 4; ++j) { + const int c = hd * 128 + lane + 32 * j; + win[j][kernel - 1] = prep_window(x, kind, state, kept, channels, c, r + kernel - 1); + float acc = 0.0f; + for (int tap = 0; tap < kernel; ++tap) { + float p = win[j][tap] * w[j][tap]; + acc = acc + p; + } + v[j] = silu(acc); + for (int tap = 0; tap + 1 < kernel; ++tap) win[j][tap] = win[j][tap + 1]; + } + float sum = 0.f; +#pragma unroll + for (int j = 0; j < 4; ++j) sum += v[j] * v[j]; +#pragma unroll + for (int mask = 16; mask > 0; mask >>= 1) sum += __shfl_xor(sum, mask, 32); + const float inv = rsqrtf(__shfl(sum, 0, 32) / 128.f + eps); + float* row = out + (static_cast(r) * (kwidth / 128) + head) * 128; +#pragma unroll + for (int j = 0; j < 4; ++j) { + const int i = lane + 32 * j; + float value = v[j] * inv; + value *= nw[i]; + row[i] = value; + } + } + return; + } + blk -= nA; + if (blk < nB) { + // v: a thread a channel a segment + const int per = (vwidth + 255) / 256; + const int vc = (blk % per) * 256 + threadIdx.x, sg = blk / per; + if (vc >= vwidth) return; + const int c = 2 * kwidth + vc; + const int r0 = sg * kPrepSeg, r1 = min(len, r0 + kPrepSeg); + float w[kConvTaps], win[kConvTaps]; + for (int tap = 0; tap < kernel; ++tap) w[tap] = weight[static_cast(c) * kernel + tap]; + for (int tap = 0; tap + 1 < kernel; ++tap) win[tap] = prep_window(x, kind, state, kept, channels, c, r0 + tap); + for (int r = r0; r < r1; ++r) { + win[kernel - 1] = prep_window(x, kind, state, kept, channels, c, r + kernel - 1); + float acc = 0.0f; + for (int tap = 0; tap < kernel; ++tap) { + float p = win[tap] * w[tap]; + acc = acc + p; + } + v_out[static_cast(r) * vwidth + vc] = silu(acc); + for (int tap = 0; tap + 1 < kernel; ++tap) win[tap] = win[tap + 1]; + } + return; + } + blk -= nB; + if (blk < nC) { + // tf_gdn_gate_prefill's gate and beta + const long long i = static_cast(blk) * 256 + threadIdx.x; + if (i >= static_cast(len) * heads) return; + const int h = static_cast(i % heads); + beta[i] = sigmoid(load(b, kind, i)); + float xa = load(a, kind, i) + dt_bias[h]; + float xb = xa * 1.0f; + float sp = xb > 20.0f ? xa : log1pf(expf(xb)) / 1.0f; + float e = -expf(a_log[h]); + gate[i] = expf(e * sp); + return; + } + blk -= nC; + // the conv's new state: the last kept inputs of every channel + const long long i = static_cast(blk) * 256 + threadIdx.x; + if (i >= static_cast(kept) * channels) return; + const int t = static_cast(i / channels), c = static_cast(i % channels); + new_state[i] = prep_window(x, kind, state, kept, channels, c, len + t); +} + // _gate_beta: beta = sigmoid(b), gate = exp(-exp(a_log) * softplus(a + dt_bias)) with torch's softplus. extern "C" __global__ void tf_gdn_gate_prefill(const void* a, const void* b, int kind, const float* a_log, const float* dt_bias, float* gate, float* beta, int count, int heads) { diff --git a/zig/kernels/hip/ops/moe.hpp b/zig/kernels/hip/ops/moe.hpp index 4971dd7027..db2519059f 100644 --- a/zig/kernels/hip/ops/moe.hpp +++ b/zig/kernels/hip/ops/moe.hpp @@ -86,6 +86,90 @@ extern "C" __global__ void tf_moe_route(const int* picks, int pairs, int experts } } +// tf_moe_route's plan of a prompt's many pairs in three launches (count, scan, scatter); `offs` is scratch. Same plan. +constexpr int kRouteSeg = 512; +constexpr int kRouteMaxExperts = 1024; + +extern "C" __global__ void __launch_bounds__(256) tf_route_count(const int* picks, int pairs, int experts, int* offs) { + __shared__ int counts[kRouteMaxExperts]; + for (int e = threadIdx.x; e < experts; e += blockDim.x) counts[e] = 0; + __syncthreads(); + const int from = blockIdx.x * kRouteSeg; + for (int p = from + threadIdx.x; p < pairs && p < from + kRouteSeg; p += blockDim.x) atomicAdd(&counts[picks[p]], 1); + __syncthreads(); + for (int e = threadIdx.x; e < experts; e += blockDim.x) offs[static_cast(blockIdx.x) * experts + e] = counts[e]; +} + +extern "C" __global__ void __launch_bounds__(1024) tf_route_scan(int* offs, int segs, int experts, int tile, int* items, + int capacity) { + __shared__ int counts[kRouteMaxExperts]; + __shared__ int starts[kRouteMaxExperts]; + __shared__ int ends[kRouteMaxExperts]; + __shared__ int scan_c[1024]; + __shared__ int scan_n[1024]; + const int t = threadIdx.x; + // an expert's segments in order: each one's place within the expert, and the expert's total + if (t < experts) { + int run = 0; + for (int g = 0; g < segs; ++g) { + int* at = offs + static_cast(g) * experts + t; + const int c = *at; + *at = run; + run += c; + } + counts[t] = run; + } + // starts: the counts' exclusive sums; ends: the tiles' inclusive sums (an expert a thread) + const int own_c = t < experts ? counts[t] : 0; + const int own_n = t < experts ? (counts[t] + tile - 1) / tile : 0; + scan_c[t] = own_c; + scan_n[t] = own_n; + __syncthreads(); + for (int off = 1; off < static_cast(blockDim.x); off <<= 1) { + const int vc = t >= off ? scan_c[t - off] : 0, vn = t >= off ? scan_n[t - off] : 0; + __syncthreads(); + scan_c[t] += vc; + scan_n[t] += vn; + __syncthreads(); + } + if (t < experts) { + starts[t] = scan_c[t] - own_c; + ends[t] = scan_n[t]; + offs[static_cast(segs) * experts + t] = starts[t]; + } + __syncthreads(); + for (int slot = t; slot < capacity; slot += blockDim.x) { + int lo = 0, hi = experts; + while (lo < hi) { // searchsorted(ends, slot, right=True) + int mid = (lo + hi) / 2; + if (ends[mid] <= slot) lo = mid + 1; + else hi = mid; + } + int e = lo < experts - 1 ? lo : experts - 1; + int reps = (counts[e] + tile - 1) / tile; + int within = slot - (ends[e] - reps); + int count = counts[e] - within * tile; + items[slot * 3] = e; + items[slot * 3 + 1] = starts[e] + within * tile; + items[slot * 3 + 2] = count < 0 ? 0 : (count > tile ? tile : count); + } +} + +extern "C" __global__ void __launch_bounds__(kRouteSeg) tf_route_scatter(const int* picks, int pairs, int segs, int experts, + const int* offs, int* members) { + __shared__ int pk[kRouteSeg]; + const int from = blockIdx.x * kRouteSeg; + const int t = threadIdx.x; + const int p = from + t; + pk[t] = p < pairs ? picks[p] : -1; + __syncthreads(); + if (p >= pairs) return; + const int e = pk[t]; + int before = 0; + for (int q = 0; q < t; ++q) before += pk[q] == e; + members[offs[static_cast(segs) * experts + e] + offs[static_cast(blockIdx.x) * experts + e] + before] = p; +} + // moe_router_kernel's logits with a wave's expert row read once for 8 token rows; each logit keeps its bits. __device__ __forceinline__ float router_sum(float x) { #pragma unroll @@ -127,52 +211,58 @@ __device__ void router_rows(const void* x, const float* rows, float* logits, int } } -// The router's logits for many rows: a 64 x 64 tile of (row, expert) a block, 4 x 4 a thread, in fp32. +// The router's logits for many rows, 128 x 64 a block, 8 x 4 a thread: one fmaf chain over k from 0, so the same bits. +constexpr int kRouterTileRows = 128; +constexpr int kRouterTileExperts = 64; + template __device__ void router_tile(const void* x, const float* rows, float* logits, int r, int d, int e) { - constexpr int kTile = 64, kStep = 32, kLd = kTile + 4; - __shared__ alignas(16) float xs[kStep][kLd]; - __shared__ alignas(16) float ws[kStep][kLd]; - const int row0 = blockIdx.y * kTile, expert0 = blockIdx.x * kTile; + constexpr int RT = 8, CT = 4, TR = 16 * RT, TC = 16 * CT, kStep = 32; + static_assert(TR == kRouterTileRows && TC == kRouterTileExperts, "the launch's tile"); + __shared__ alignas(16) float xs[kStep][TR + 4]; + __shared__ alignas(16) float ws[kStep][TC + 4]; + const int row0 = blockIdx.y * TR, expert0 = blockIdx.x * TC; const int ty = threadIdx.x / 16, tx = threadIdx.x % 16; - // the staging: activation row ar at steps ak .. ak + 7, router rows wr and wr + 32 at steps wk .. wk + 3 - const int ar = threadIdx.x / 4, ak = (threadIdx.x % 4) * 8; - const int wr = threadIdx.x / 8, wk = (threadIdx.x % 8) * 4; const uint16_t* xh = static_cast(x); - float acc[4][4] = {}; + float acc[RT][CT] = {}; for (int base = 0; base < d; base += kStep) { - uint4 xv = {0, 0, 0, 0}; - if (row0 + ar < r) xv = *reinterpret_cast(xh + static_cast(row0 + ar) * d + base + ak); - float4 w0 = {0, 0, 0, 0}, w1 = {0, 0, 0, 0}; - if (expert0 + wr < e) w0 = *reinterpret_cast(rows + static_cast(expert0 + wr) * d + base + wk); - if (expert0 + wr + 32 < e) - w1 = *reinterpret_cast(rows + static_cast(expert0 + wr + 32) * d + base + wk); __syncthreads(); - const uint16_t* h = reinterpret_cast(&xv); + // the staging: 8 activations of a row a load, 4 router weights of an expert a load + for (int q = threadIdx.x; q < TR * kStep / 8; q += 256) { + const int rr = q / (kStep / 8), kk = (q % (kStep / 8)) * 8; + uint4 v = {0, 0, 0, 0}; + if (row0 + rr < r) v = *reinterpret_cast(xh + static_cast(row0 + rr) * d + base + kk); + const uint16_t* h = reinterpret_cast(&v); #pragma unroll - for (int j = 0; j < 8; ++j) xs[ak + j][ar] = KIND == 1 ? __half2float(__ushort_as_half(h[j])) : bf16_to_float(h[j]); - const float a0[4] = {w0.x, w0.y, w0.z, w0.w}, a1[4] = {w1.x, w1.y, w1.z, w1.w}; -#pragma unroll - for (int j = 0; j < 4; ++j) ws[wk + j][wr] = a0[j], ws[wk + j][wr + 32] = a1[j]; + for (int j = 0; j < 8; ++j) xs[kk + j][rr] = KIND == 1 ? __half2float(__ushort_as_half(h[j])) : bf16_to_float(h[j]); + } + for (int q = threadIdx.x; q < TC * kStep / 4; q += 256) { + const int cc = q / (kStep / 4), kk = (q % (kStep / 4)) * 4; + float4 v = {0, 0, 0, 0}; + if (expert0 + cc < e) v = *reinterpret_cast(rows + static_cast(expert0 + cc) * d + base + kk); + ws[kk][cc] = v.x, ws[kk + 1][cc] = v.y, ws[kk + 2][cc] = v.z, ws[kk + 3][cc] = v.w; + } __syncthreads(); -#pragma unroll +#pragma unroll 4 for (int i = 0; i < kStep; ++i) { - const float4 a = *reinterpret_cast(&xs[i][4 * ty]); - const float4 b = *reinterpret_cast(&ws[i][4 * tx]); - const float av[4] = {a.x, a.y, a.z, a.w}, bv[4] = {b.x, b.y, b.z, b.w}; + float av[RT], bv[CT]; +#pragma unroll + for (int u = 0; u < RT; ++u) av[u] = xs[i][ty * RT + u]; +#pragma unroll + for (int w = 0; w < CT; ++w) bv[w] = ws[i][tx * CT + w]; #pragma unroll - for (int u = 0; u < 4; ++u) + for (int u = 0; u < RT; ++u) #pragma unroll - for (int w = 0; w < 4; ++w) acc[u][w] = fmaf(av[u], bv[w], acc[u][w]); + for (int w = 0; w < CT; ++w) acc[u][w] = fmaf(av[u], bv[w], acc[u][w]); } } #pragma unroll - for (int u = 0; u < 4; ++u) { - const int row = row0 + 4 * ty + u; + for (int u = 0; u < RT; ++u) { + const int row = row0 + ty * RT + u; if (row >= r) continue; #pragma unroll - for (int w = 0; w < 4; ++w) { - const int expert = expert0 + 4 * tx + w; + for (int w = 0; w < CT; ++w) { + const int expert = expert0 + tx * CT + w; if (expert < e) logits[static_cast(row) * e + expert] = acc[u][w]; } } diff --git a/zig/kernels/hip/ops/qk_rope_wave.hpp b/zig/kernels/hip/ops/qk_rope_wave.hpp new file mode 100644 index 0000000000..a0bc70a7d6 --- /dev/null +++ b/zig/kernels/hip/ops/qk_rope_wave.hpp @@ -0,0 +1,56 @@ +#pragma once + +#include "common.hpp" + +// tf_qk_rope's two phases for one wave's (row, head), shared with Flash Next's QSA prep: RMS norm, then the rotation. + +namespace { + +constexpr int kQkRopeMost = 512 / 32; // the widest head: 512 values + +// src[at .. at + width) RMS-normed with weight, rounded, into the wave's shared row; a dead wave norms zeros. +__device__ __forceinline__ void qk_rope_norm(const void* src, int kind, long long at, const float* weight, float eps, + int width, bool live, float* row) { + const int lane = threadIdx.x & 31; + float v[kQkRopeMost]; + float sum = 0.f; +#pragma unroll + for (int j = 0; j < kQkRopeMost; ++j) { + const int i = lane + 32 * j; + v[j] = live && i < width ? load(src, kind, at + i) : 0.f; + if (i < width) sum += v[j] * v[j]; + } +#pragma unroll + for (int mask = 16; mask > 0; mask >>= 1) sum += __shfl_xor(sum, mask, 32); + const float inv = rsqrtf(__shfl(sum, 0, 32) / static_cast(width) + eps); +#pragma unroll + for (int j = 0; j < kQkRopeMost; ++j) { + const int i = lane + 32 * j; + if (i < width) row[i] = rounded(v[j] * inv * weight[i], kind); + } +} + +// The normed row rotated at position p over its first `rotary` values, rounded, into out (fp32) and/or the cache. +__device__ __forceinline__ void qk_rope_put(int kind, int width, int rotary, float theta, int p, const float* row, + float* out, void* cache, long long slot) { + const int lane = threadIdx.x & 31; + const int half = rotary >> 1; + auto put = [&](int i, float value) { + value = rounded(value, kind); + if (out) out[i] = value; + if (cache) store(cache, kind, slot + i, value); + }; + for (int i = lane; i < half; i += 32) { + float freq = 1.f / powf(theta, static_cast(i) / static_cast(half)); + float ang = static_cast(p) * freq; + float c = cosf(ang); + float sn = sinf(ang); + float x1 = row[i]; + float x2 = row[half + i]; + put(i, x1 * c - x2 * sn); + put(half + i, x1 * sn + x2 * c); + } + for (int i = rotary + lane; i < width; i += 32) put(i, row[i]); +} + +} // namespace diff --git a/zig/kernels/hip/ops/rope.hpp b/zig/kernels/hip/ops/rope.hpp index 12b481e481..af678a0dd5 100644 --- a/zig/kernels/hip/ops/rope.hpp +++ b/zig/kernels/hip/ops/rope.hpp @@ -1,6 +1,7 @@ #pragma once #include "common.hpp" +#include "qk_rope_wave.hpp" // RoPE for a prefill and the window's fused q / k norm and rotation. @@ -36,51 +37,17 @@ extern "C" __global__ void __launch_bounds__(256) tf_qk_rope(const void* src, in const float* weight, float eps, int rows, int heads, int width, int rotary, float theta, const int* pos, float* wide, void* cache, int total) { - constexpr int kMost = 512 / 32; __shared__ float row_v[8][512]; - const int lane = threadIdx.x & 31, wave = threadIdx.x >> 5; + const int wave = threadIdx.x >> 5; const int g = blockIdx.x * 8 + wave; const bool live = g < rows * heads; const int r = live ? g / heads : 0, h = live ? g % heads : 0; - const long long at = r * s_row + static_cast(h) * s_head; - float v[kMost]; - float sum = 0.f; -#pragma unroll - for (int j = 0; j < kMost; ++j) { - const int i = lane + 32 * j; - v[j] = live && i < width ? load(src, kind, at + i) : 0.f; - if (i < width) sum += v[j] * v[j]; - } -#pragma unroll - for (int mask = 16; mask > 0; mask >>= 1) sum += __shfl_xor(sum, mask, 32); - const float inv = rsqrtf(__shfl(sum, 0, 32) / static_cast(width) + eps); -#pragma unroll - for (int j = 0; j < kMost; ++j) { - const int i = lane + 32 * j; - if (i < width) row_v[wave][i] = rounded(v[j] * inv * weight[i], kind); - } + qk_rope_norm(src, kind, r * s_row + static_cast(h) * s_head, weight, eps, width, live, row_v[wave]); __syncthreads(); if (!live) return; const int p = pos[r]; - const int half = rotary >> 1; - float* out = wide ? wide + static_cast(g) * width : nullptr; - const long long slot = (static_cast(h) * total + p) * width; - auto put = [&](int i, float value) { - value = rounded(value, kind); - if (out) out[i] = value; - if (cache) store(cache, kind, slot + i, value); - }; - for (int i = lane; i < half; i += 32) { - float freq = 1.f / powf(theta, static_cast(i) / static_cast(half)); - float ang = static_cast(p) * freq; - float c = cosf(ang); - float sn = sinf(ang); - float x1 = row_v[wave][i]; - float x2 = row_v[wave][half + i]; - put(i, x1 * c - x2 * sn); - put(half + i, x1 * sn + x2 * c); - } - for (int i = rotary + lane; i < width; i += 32) put(i, row_v[wave][i]); + qk_rope_put(kind, width, rotary, theta, p, row_v[wave], wide ? wide + static_cast(g) * width : nullptr, + cache, (static_cast(h) * total + p) * width); } } // namespace diff --git a/zig/kernels/hip/quant/mlx_tiles.hpp b/zig/kernels/hip/quant/mlx_tiles.hpp index ec4f67f515..226624139c 100644 --- a/zig/kernels/hip/quant/mlx_tiles.hpp +++ b/zig/kernels/hip/quant/mlx_tiles.hpp @@ -10,7 +10,9 @@ #include "tiles/epilogue.hpp" #include "tiles/gemm.hpp" #include "tiles/gemm_kp.hpp" +#include "tiles/dense_gemm.hpp" #include "tiles/matrix_gemm.hpp" +#include "tiles/moe_gemm.hpp" #include "tiles/stream.hpp" namespace tf { @@ -37,6 +39,42 @@ __global__ void __launch_bounds__(256) affine_wmma_gemm(Affine a) { wmma_gemm_tile, BF16Act, WmmaBF16, F32Out>(a); } +// ---- Qwen3.8-Flash-Next's routed expert products of a prompt (tiles/moe_gemm.hpp, gfx11 matrix cores) ---- + +// 64-wide K windows; each shape's ring depth is its own (MoeGateUp::kAhead, MoeDown::kAhead). + +// gate and up with silu(gate) * up as the epilogue, into a.out16 (bf16) +template +__global__ void __launch_bounds__(moe_tile::kThreads) affine_wmma_moe_gu(Affine a, float limit) { + wmma_moe_tile(a, limit); +} + +// down into a.out (fp32) +template +__global__ void __launch_bounds__(moe_tile::kThreads) affine_wmma_moe_down(Affine a) { + wmma_moe_tile(a, 0.f); +} + +// ---- a prompt's plain 4-bit group-32 products at Flash Next's K (tiles/dense_gemm.hpp, gfx11 matrix cores) ---- + +// K 2560 (the trunk's input projections), 6144 (out), 10240 (hc down), 320 (hc up); the bytes of affine_wmma_gemm +template +__global__ void __launch_bounds__(dense_tile::kThreads) affine_wmma_dense(Affine a) { + wmma_dense_tile::kAhead>(a); +} + +// hc up (K 320) with tf_fn_hc_mix in the epilogue; tf_hc_gate: its gate rnd(sigmoid(g)) for every bf16 g, filled once. +__device__ uint16_t tf_hc_gate[1 << 16]; +extern "C" __global__ void __launch_bounds__(256) tf_hc_gate_fill() { + const int h = blockIdx.x * 256 + threadIdx.x; + const float g = __uint_as_float(static_cast(h) << 16); + tf_hc_gate[h] = __builtin_bit_cast(uint16_t, narrow(1.0f / (1.0f + expf(-g)))); +} + +extern "C" __global__ void __launch_bounds__(dense_tile::kThreads) tf_affine_dense_hcmix(Affine a, HcMix mix) { + wmma_dense_tile<320, DenseTune<320>::kAhead, true>(a, mix, tf_hc_gate); +} + // ---- the decode stream tile ---- // Up to four products sharing x, K, width and group in one launch; side s owns blocks [first[s], first[s + 1]). @@ -53,6 +91,7 @@ struct StreamSides { int out_half; int pair_cols; // > 0: the (gate | up) rows of a stacked product with this many columns each, out is its activation float limit; // the activation's clamp when above 0 + int row_blocks; // > 1: the launch's row blocks are the grid's x and its column blocks its y }; // Item z of the plan (or the plain product, or a group's side) at CB columns a lane, R rows; PAIR fuses the activation. @@ -63,6 +102,21 @@ __global__ void __launch_bounds__(32 * kStreamWaves) affine_dot2_stream(Affine a stream_tile, IdentityAct, T, Epi, R, CB>(a, sides, lpc_log2, gshift); } +// The plain product on the held-codes body (stream_body's HELD): the same sums as affine_dot2_stream. +template +__global__ void __launch_bounds__(32 * kStreamWaves) affine_dot2_stream_held(Affine a, StreamSides sides, int lpc_log2, + int gshift) { + stream_tile, IdentityAct, T, StreamRound, R, CB, true>(a, sides, lpc_log2, gshift); +} + +// A routed plan of 5 to 8 rows as a work list (stream_list): grid z blocks walk `items`; 16-byte code loads, so 4-bit. +template +__global__ void __launch_bounds__(32 * kStreamWaves) affine_dot2_stream_list(Affine a, StreamSides sides, int lpc_log2, + int gshift, int items) { + using Epi = std::conditional_t, StreamRound>; + stream_list, IdentityAct, T, Epi, R, CB>(a, sides.pair_cols, sides.limit, lpc_log2, gshift, items); +} + // The plain product (or plan item) with Nemotron's relu^2 as the epilogue, into a.out16 in the activation type. template __global__ void __launch_bounds__(32 * kStreamWaves) affine_dot2_stream_relu2(Affine a, StreamSides sides, int lpc_log2, diff --git a/zig/kernels/hip/recurrence/gated_delta.hip b/zig/kernels/hip/recurrence/gated_delta.hip index 79ab274e2e..a7fe8004ec 100644 --- a/zig/kernels/hip/recurrence/gated_delta.hip +++ b/zig/kernels/hip/recurrence/gated_delta.hip @@ -7,6 +7,15 @@ namespace tf { namespace rocm { +// Where a window's scan starts: the state, or with `from` naming row f >= 0, the last window's snapshot after row f. +__device__ __forceinline__ const float* start_state(const float* state, size_t state_row, const float* states, + const int* from, int value_heads, int head, int dv, int row, int dk) { + if (from == nullptr || states == nullptr) return state + state_row; + const int f = *from; + if (f < 0) return state + state_row; + return states + ((static_cast(f) * value_heads + head) * dv + row) * dk; +} + __device__ float lane0_sum(float x) { #pragma unroll for (int mask = 16; mask > 0; mask >>= 1) x += __shfl_xor(x, mask, 32); @@ -18,7 +27,7 @@ __global__ void __launch_bounds__(32) gated_delta_kernel(const float* __restrict__ q, const float* __restrict__ k, const float* __restrict__ v, const float* __restrict__ gate, const float* __restrict__ beta, float* __restrict__ state, float* __restrict__ y, int length, int key_heads, int value_heads, int dv, - float* __restrict__ states) { + float* __restrict__ states, const int* from) { constexpr int SPAN = (DK + 31) / 32; const int lane = threadIdx.x; const int row = blockIdx.x; @@ -30,11 +39,13 @@ gated_delta_kernel(const float* __restrict__ q, const float* __restrict__ k, con float s[4] = {0.f, 0.f, 0.f, 0.f}; const size_t state_row = ((static_cast(batch) * value_heads + head) * dv + row) * DK; + const float* src = start_state(state, state_row, states, from, value_heads, head, dv, row, DK); #pragma unroll for (int i = 0; i < SPAN; ++i) { const int idx = lane + i * 32; - if (idx < DK) s[i] = state[state_row + idx]; + if (idx < DK) s[i] = src[idx]; } + __atomic_signal_fence(__ATOMIC_SEQ_CST); // the start is read before any snapshot store (it may be one of them) for (int t = 0; t < length; ++t) { const size_t step = (static_cast(batch) * length + t) * value_heads + head; @@ -98,7 +109,7 @@ __device__ __forceinline__ void gated_delta_tile_body(const float* __restrict__ q, const float* __restrict__ k, const float* __restrict__ v, const float* __restrict__ gate, const float* __restrict__ beta, float* __restrict__ state, float* __restrict__ y, int length, int key_heads, int value_heads, int dv, - float* __restrict__ states, int batch, bool write_back = true) { + float* __restrict__ states, int batch, bool write_back = true, const int* from = nullptr) { constexpr int SPAN = (DK + 31) / 32; constexpr int WIDTH = 32 * ROWS; const int lane = threadIdx.x; @@ -116,11 +127,13 @@ gated_delta_tile_body(const float* __restrict__ q, const float* __restrict__ k, float s[4] = {0.f, 0.f, 0.f, 0.f}; const size_t state_row = ((static_cast(batch) * value_heads + head) * dv + row) * DK; + const float* src = start_state(state, state_row, states, from, value_heads, head, dv, row, DK); #pragma unroll for (int i = 0; i < SPAN; ++i) { const int idx = lane + i * 32; - if (idx < DK) s[i] = state[state_row + idx]; + if (idx < DK) s[i] = src[idx]; } + __atomic_signal_fence(__ATOMIC_SEQ_CST); // the start is read before any snapshot store (it may be one of them) for (int t0 = 0; t0 < length; t0 += STEPS) { const int n = min(STEPS, length - t0); @@ -215,9 +228,33 @@ __global__ void __launch_bounds__(32 * ROWS) gated_delta_tile(const float* __restrict__ q, const float* __restrict__ k, const float* __restrict__ v, const float* __restrict__ gate, const float* __restrict__ beta, float* __restrict__ state, float* __restrict__ y, int length, int key_heads, int value_heads, int dv, - float* __restrict__ states) { + float* __restrict__ states, const int* from) { gated_delta_tile_body(q, k, v, gate, beta, state, y, length, key_heads, value_heads, dv, states, - blockIdx.z); + blockIdx.z, true, from); +} + +// A verify window that holds its state: outputs only; the keep that follows runs the state through the kept rows. +template +__device__ __forceinline__ void +gated_delta_hold(const float* __restrict__ q, const float* __restrict__ k, const float* __restrict__ v, + const float* __restrict__ gate, const float* __restrict__ beta, float* __restrict__ state, + float* __restrict__ y, int length, int key_heads, int value_heads, int dv) { + gated_delta_tile_body(q, k, v, gate, beta, state, y, length, key_heads, value_heads, dv, nullptr, + blockIdx.z, false, nullptr); +} + +// A keep: layer z's state runs through its window's first `kept` rows by the window's scan, and is stored back. +template +__device__ __forceinline__ void +gated_delta_keep(float* state, long long state_stride, const float* in, long long in_stride, int rows, int kept, + int key_heads, int value_heads, int dv) { + const long long layer = blockIdx.z; + const float* k = in + layer * in_stride; + const float* v = k + static_cast(rows) * key_heads * DK; + const float* gate = v + static_cast(rows) * value_heads * dv; + const float* beta = gate + static_cast(rows) * value_heads; + gated_delta_tile_body(nullptr, k, v, gate, beta, state + layer * state_stride, nullptr, kept, key_heads, + value_heads, dv, nullptr, 0); } // A round's windows in one launch, a grid plane a slot; rows, state and snapshots come from the plan, same scan. @@ -258,9 +295,148 @@ __device__ __forceinline__ void gated_delta_replay_body(const int* keep, int row value_heads, dv, nullptr, 0); } +// A prompt's recurrence for DK = DV = 128, 4 lanes a row and 2 rows a lane; lane0_sum's sums in its order, same bits. +constexpr int kPromptSteps = 16; + +__device__ __forceinline__ float quad_sum(const float (&part)[8]) { + // xor 16, 8, 4 of lane0_sum: virtual lanes j ^ 4, j ^ 2, j ^ 1 in registers (each pair's add commutes) + const float a0 = part[0] + part[4], a1 = part[1] + part[5], a2 = part[2] + part[6], a3 = part[3] + part[7]; + const float b0 = a0 + a2, b1 = a1 + a3; + float c = b0 + b1; + // xor 2 and 1: the other lanes of the row + c = c + __shfl_xor(c, 2, 32); + c = c + __shfl_xor(c, 1, 32); + return c; +} + +template +__device__ __forceinline__ void +gated_delta_prompt_body(const float* __restrict__ q, const float* __restrict__ k, const float* __restrict__ v, + const float* __restrict__ gate, const float* __restrict__ beta, float* __restrict__ state, + float* __restrict__ y, int length, int key_heads, int value_heads) { + constexpr int DK = 128, DV = 128, T = kPromptSteps, THREADS = 32 * WAVES, ROWS = 16 * WAVES; + const int lane = threadIdx.x, wave = threadIdx.y; + const int tid = wave * 32 + lane; + const int p = lane & 3; + const int first = blockIdx.x * ROWS; // the block's first Dv row + const int row0 = first + wave * 16 + 2 * (lane >> 2); // this lane's rows: row0, row0 + 1 + const int head = blockIdx.y, batch = blockIdx.z; + const int key_head = head / (value_heads / key_heads); + + __shared__ __attribute__((aligned(16))) float ks[T][DK]; // transposed: [t][p * 32 + m] = k[t][p + 4 m] + __shared__ __attribute__((aligned(16))) float qs[T][DK]; + __shared__ float vs[T][ROWS]; + __shared__ float gs[T]; + __shared__ float bs[T]; + + float s[2][32]; + for (int r = 0; r < 2; ++r) { + const float* at = state + ((static_cast(batch) * value_heads + head) * DV + row0 + r) * DK; +#pragma unroll + for (int m = 0; m < 32; ++m) s[r][m] = at[p + 4 * m]; + } + + for (int t0 = 0; t0 < length; t0 += T) { + const int n = min(T, length - t0); + for (int i = tid; i < n * DK; i += THREADS) { + const int step = i / DK, e = i - step * DK; + const size_t at = ((static_cast(batch) * length + (t0 + step)) * key_heads + key_head) * DK + e; + const int to = (e & 3) * 32 + (e >> 2); + ks[step][to] = k[at]; + qs[step][to] = q[at]; + } + for (int i = tid; i < n * ROWS; i += THREADS) { + const int step = i / ROWS, e = i - step * ROWS; + vs[step][e] = v[((static_cast(batch) * length + (t0 + step)) * value_heads + head) * DV + first + e]; + } + for (int i = tid; i < n; i += THREADS) { + const size_t at = (static_cast(batch) * length + (t0 + i)) * value_heads + head; + gs[i] = gate[at]; + bs[i] = beta[at]; + } + __syncthreads(); + for (int tt = 0; tt < n; ++tt) { + const float decay = gs[tt], step_beta = bs[tt]; + float kv[32], qv[32]; + const float4* k4 = reinterpret_cast(&ks[tt][p * 32]); + const float4* q4 = reinterpret_cast(&qs[tt][p * 32]); +#pragma unroll + for (int c = 0; c < 8; ++c) { + const float4 a = k4[c], b = q4[c]; + kv[4 * c] = a.x, kv[4 * c + 1] = a.y, kv[4 * c + 2] = a.z, kv[4 * c + 3] = a.w; + qv[4 * c] = b.x, qv[4 * c + 1] = b.y, qv[4 * c + 2] = b.z, qv[4 * c + 3] = b.w; + } + float out[2]; +#pragma unroll + for (int r = 0; r < 2; ++r) { + float part[8]; +#pragma unroll + for (int j = 0; j < 8; ++j) part[j] = 0.f; +#pragma unroll + for (int i = 0; i < 4; ++i) { +#pragma unroll + for (int j = 0; j < 8; ++j) { + const int m = j + 8 * i; + s[r][m] = s[r][m] * decay; + part[j] = part[j] + s[r][m] * kv[m]; + } + } + const float delta = (vs[tt][row0 - first + r] - quad_sum(part)) * step_beta; +#pragma unroll + for (int j = 0; j < 8; ++j) part[j] = 0.f; +#pragma unroll + for (int i = 0; i < 4; ++i) { +#pragma unroll + for (int j = 0; j < 8; ++j) { + const int m = j + 8 * i; + s[r][m] = s[r][m] + kv[m] * delta; + part[j] = part[j] + s[r][m] * qv[m]; + } + } + out[r] = quad_sum(part); + } + if (p == 0) { + float* yo = y + ((static_cast(batch) * length + (t0 + tt)) * value_heads + head) * DV + row0; + yo[0] = out[0]; + yo[1] = out[1]; + } + } + __syncthreads(); + } + for (int r = 0; r < 2; ++r) { + float* at = state + ((static_cast(batch) * value_heads + head) * DV + row0 + r) * DK; +#pragma unroll + for (int m = 0; m < 32; ++m) at[p + 4 * m] = s[r][m]; + } +} + } // namespace rocm } // namespace tf +extern "C" __global__ void __launch_bounds__(256) +tf_gdn_hold_128(const float* q, const float* k, const float* v, const float* gate, const float* beta, float* state, + float* y, int length, int key_heads, int value_heads, int dv) { + tf::rocm::gated_delta_hold<128, 8, 16>(q, k, v, gate, beta, state, y, length, key_heads, value_heads, dv); +} + +extern "C" __global__ void __launch_bounds__(256) +tf_gdn_hold_16(const float* q, const float* k, const float* v, const float* gate, const float* beta, float* state, + float* y, int length, int key_heads, int value_heads, int dv) { + tf::rocm::gated_delta_hold<16, 8, 16>(q, k, v, gate, beta, state, y, length, key_heads, value_heads, dv); +} + +extern "C" __global__ void __launch_bounds__(256) +tf_gdn_keep_128(float* state, long long state_stride, const float* in, long long in_stride, int rows, int kept, + int key_heads, int value_heads, int dv) { + tf::rocm::gated_delta_keep<128>(state, state_stride, in, in_stride, rows, kept, key_heads, value_heads, dv); +} + +extern "C" __global__ void __launch_bounds__(256) +tf_gdn_keep_16(float* state, long long state_stride, const float* in, long long in_stride, int rows, int kept, + int key_heads, int value_heads, int dv) { + tf::rocm::gated_delta_keep<16>(state, state_stride, in, in_stride, rows, kept, key_heads, value_heads, dv); +} + extern "C" __global__ void __launch_bounds__(256) tf_gdn_plan_128(const float* q, const float* k, const float* v, const float* gate, const float* beta, float* y, int key_heads, int value_heads, int dv, PlanArgs plan, int layer) { @@ -287,16 +463,23 @@ tf_gdn_plan_16(const float* q, const float* k, const float* v, const float* gate template __global__ void tf::rocm::gated_delta_tile<128, 8, 16>(const float* __restrict__ q, const float* __restrict__ k, const float* __restrict__ v, const float* __restrict__ gate, const float* __restrict__ beta, float* __restrict__ state, float* __restrict__ y, int length, int key_heads, - int value_heads, int dv, float* __restrict__ states); + int value_heads, int dv, float* __restrict__ states, const int* from); template __global__ void tf::rocm::gated_delta_tile<16, 8, 16>(const float* __restrict__ q, const float* __restrict__ k, const float* __restrict__ v, const float* __restrict__ gate, const float* __restrict__ beta, float* __restrict__ state, float* __restrict__ y, int length, int key_heads, int value_heads, int dv, - float* __restrict__ states); + float* __restrict__ states, const int* from); template __global__ void tf::rocm::gated_delta_kernel<128>(const float* __restrict__ q, const float* __restrict__ k, const float* __restrict__ v, const float* __restrict__ gate, const float* __restrict__ beta, float* __restrict__ state, float* __restrict__ y, int length, int key_heads, int value_heads, int dv, - float* __restrict__ states); + float* __restrict__ states, const int* from); template __global__ void tf::rocm::gated_delta_kernel<16>(const float* __restrict__ q, const float* __restrict__ k, const float* __restrict__ v, const float* __restrict__ gate, const float* __restrict__ beta, float* __restrict__ state, float* __restrict__ y, int length, int key_heads, int value_heads, int dv, - float* __restrict__ states); + float* __restrict__ states, const int* from); + +// Half a value head a block (4 waves, 64 rows; grid 2 x value heads), the fastest of the three block sizes on gfx1151. +extern "C" __global__ void __launch_bounds__(128) +tf_gdn_prompt_128(const float* q, const float* k, const float* v, const float* gate, const float* beta, float* state, + float* y, int length, int key_heads, int value_heads) { + tf::rocm::gated_delta_prompt_body<4>(q, k, v, gate, beta, state, y, length, key_heads, value_heads); +} diff --git a/zig/kernels/hip/tiles/dense_gemm.hpp b/zig/kernels/hip/tiles/dense_gemm.hpp new file mode 100644 index 0000000000..4ac294a2a8 --- /dev/null +++ b/zig/kernels/hip/tiles/dense_gemm.hpp @@ -0,0 +1,288 @@ +#pragma once + +// A prompt's plain 4-bit group-32 MLX products on the gfx11 matrix cores: affine_wmma_gemm's bytes, K a constant. + +// After Strata's kernel_bk64 (github.com/Niko1221/Strata, MIT, src/prefill/wmma_gemm.cu@4b9e05a2:396-482). + +#include + +#include "common/wmma.hpp" +#include "quant/mlx_decoder.hpp" +#include "tiles/epilogue.hpp" + +namespace tf { +namespace rocm { + +// HC_MIX (hc up, K 320): the 4 streams' columns of 32 hidden columns a block, mixed in the epilogue as tf_fn_hc_mix. +struct HcMix { + const uint16_t* x = nullptr; + uint16_t* mixed = nullptr; +}; + +namespace dense_tile { +constexpr int kBM = 128; +constexpr int kBN = 128; +constexpr int kKW = 64; // K a window: 2 groups +constexpr int kThreads = 256; +} // namespace dense_tile + +// K a multiple of 64; AHEAD windows of loads a thread holds (dividing K / 64); bf16 x and tables; row-major tiles. +template +__device__ __forceinline__ void wmma_dense_tile(const Affine& a, HcMix mix = {}, const uint16_t* gates = nullptr) { +#if TF_DEVICE_WMMA_GFX11 + using namespace dense_tile; + using Dec = MlxDecoder<4>; + using T = WmmaBF16; + constexpr int kWindows = K / kKW; + constexpr int kGroups = K / 32; + constexpr int kLdw = (kKW + 8) / 2; // a staged row: 72 bf16, so 8 lanes of 16-byte reads hit 32 banks + constexpr int kWordsRow = K / 8; + static_assert(K % kKW == 0 && kWindows % AHEAD == 0, "whole windows; a window's register slot is a constant"); + __shared__ __attribute__((aligned(16))) uint32_t xs[kBM * kLdw]; + __shared__ __attribute__((aligned(16))) uint32_t ws[kBN * kLdw]; + __shared__ float sx[2][kBM]; + __shared__ float sc[2][kBN]; + __shared__ float bi[2][kBN]; + + const int num_n = (a.n + kBN - 1) / kBN; + const int bm = blockIdx.x / num_n; + const int bn = blockIdx.x % num_n; + const int m0 = bm * kBM; + const int n0 = bn * kBN; + const int rows_left = a.m - m0; + const int tid = threadIdx.x; + const int lane = tid & 31; + const int wave = __builtin_amdgcn_readfirstlane(tid >> 5); + + // a thread's loads: group q of staged row r (column n0 + r's codes, x row m0 + r), column n0 + t % 128's terms + const int r = tid >> 1; + const int q = tid & 1; + // HC_MIX: local column c is stream c / 32's hidden column bn * 32 + c % 32 (the weights' row of that output) + const int dims = a.n / 4; + auto column = [&](int c) { return HC_MIX ? (c / 32) * dims + bn * 32 + c % 32 : n0 + c; }; + const int col = HC_MIX ? column(r) : (n0 + r < a.n ? n0 + r : a.n - 1); + const int row = r < rows_left ? m0 + r : a.m - 1; + const uint32_t* wsrc = a.words + static_cast(col) * kWordsRow + q * 4; + const u32x4* xsrc = reinterpret_cast(static_cast(a.x) + static_cast(row) * K) + q * 4; + const int trow = tid & (kBN - 1); + const bool thigh = tid >= kBN; + const int tcol = HC_MIX ? column(trow) : (n0 + trow < a.n ? n0 + trow : a.n - 1); + const uint16_t* tsrc = static_cast(thigh ? a.bias.p : a.scale.p) + static_cast(tcol) * kGroups; + + // wave (wm, wn): rows kWR wm.., columns kWC wn.. (kMT x kNT tiles); a lane: column lane % 16, rows 2 i + lane / 16 + constexpr int kWR = 64; + constexpr int kWC = kBM * kBN / 8 / kWR; + constexpr int kMT = kWR / 16; + constexpr int kNT = kWC / 16; + const int wm = wave % (kBM / kWR); + const int wn = wave / (kBM / kWR); + const int rl = lane & 15; + const int rh = lane >> 4; + const f32x8 zero = {0, 0, 0, 0, 0, 0, 0, 0}; + f32x8 acc[kMT][kNT]; +#pragma unroll + for (int mt = 0; mt < kMT; ++mt) { +#pragma unroll + for (int nt = 0; nt < kNT; ++nt) acc[mt][nt] = zero; + } + + uint4 wreg[AHEAD]; + u32x4 xreg[AHEAD][4]; + uint16_t treg[AHEAD][2]; + // Every load is unconditional (past the last window it repeats the last): a branch forces vmcnt(0) at the stash + auto load = [&](std::integral_constant, int w) { + const int wl = w < kWindows ? w : kWindows - 1; + wreg[R] = *reinterpret_cast(wsrc + wl * 8); +#pragma unroll + for (int v = 0; v < 4; ++v) xreg[R][v] = xsrc[wl * 8 + v]; + treg[R][0] = tsrc[2 * wl]; + treg[R][1] = tsrc[2 * wl + 1]; + }; + auto stash = [&](std::integral_constant) { + const uint32_t wv[4] = {wreg[R].x, wreg[R].y, wreg[R].z, wreg[R].w}; + u32x4* wdst = reinterpret_cast(ws + r * kLdw + q * 16); +#pragma unroll + for (int v = 0; v < 4; ++v) { + uint32_t p[4]; +#pragma unroll + for (int h = 0; h < 4; ++h) p[h] = __builtin_bit_cast(uint32_t, Dec::template pair(wv, v * 8 + h * 2)); + wdst[v] = u32x4{p[0], p[1], p[2], p[3]}; + } + u32x4* xdst = reinterpret_cast(xs + r * kLdw + q * 16); + float run = 0.f; +#pragma unroll + for (int v = 0; v < 4; ++v) { + xdst[v] = xreg[R][v]; + const uint32_t u[4] = {xreg[R][v].x, xreg[R][v].y, xreg[R][v].z, xreg[R][v].w}; +#pragma unroll + for (int h = 0; h < 4; ++h) { + const typename T::pair p = __builtin_bit_cast(typename T::pair, u[h]); + run += T::lo(p); + run += T::hi(p); + } + } + sx[q][r] = run; + float(*tdst)[kBN] = thigh ? bi : sc; + tdst[0][trow] = __uint_as_float(static_cast(treg[R][0]) << 16); + tdst[1][trow] = __uint_as_float(static_cast(treg[R][1]) << 16); + }; + + [&](std::integer_sequence) { + (load(std::integral_constant{}, R), ...); + }(std::make_integer_sequence{}); + stash(std::integral_constant{}); + load(std::integral_constant{}, AHEAD); + lds_barrier(); + // Window w: compute it, stash window w + 1 from its slot, refill the slot with window w + 1 + AHEAD. + auto window = [&](std::integral_constant) { + constexpr int next = (J + 1) % AHEAD; + { +#pragma unroll + for (int g = 0; g < 2; ++g) { + f32x8 d[kMT][kNT]; +#pragma unroll + for (int t = 0; t < 2; ++t) { + bf16x16 bf[kNT]; +#pragma unroll + for (int nt = 0; nt < kNT; ++nt) bf[nt] = frag16(ws + (wn * kWC + nt * 16 + rl) * kLdw + g * 16 + t * 8); +#pragma unroll + for (int mt = 0; mt < kMT; ++mt) { + const bf16x16 af = frag16(xs + (wm * kWR + mt * 16 + rl) * kLdw + g * 16 + t * 8); +#pragma unroll + for (int nt = 0; nt < kNT; ++nt) d[mt][nt] = T::mma(af, bf[nt], t == 0 ? zero : d[mt][nt]); + } + } +#pragma unroll + for (int mt = 0; mt < kMT; ++mt) { + float s_x[8]; +#pragma unroll + for (int i = 0; i < 8; ++i) s_x[i] = sx[g][wm * kWR + mt * 16 + 2 * i + rh]; +#pragma unroll + for (int nt = 0; nt < kNT; ++nt) { + const float scale = sc[g][wn * kWC + nt * 16 + rl]; + const float bias = bi[g][wn * kWC + nt * 16 + rl]; +#pragma unroll + for (int i = 0; i < 8; ++i) { + acc[mt][nt][i] = Dec::fold_scale(acc[mt][nt][i], d[mt][nt][i], scale); + acc[mt][nt][i] = Dec::fold_bias(acc[mt][nt][i], s_x[i], bias); + } + } + } + } + } + lds_barrier(); + // past the last window the stash rewrites LDS no later window reads + stash(std::integral_constant{}); + }; + for (int w0 = 0; w0 < kWindows; w0 += AHEAD) { + [&](std::integer_sequence) { + ((window(std::integral_constant{}), + load(std::integral_constant{}, w0 + J + 1 + AHEAD), lds_barrier()), + ...); + }(std::make_integer_sequence{}); + } + + // fp32 into out, or (out16 set) rounded to BF16 as tf_cast rounds the fp32 sums (nearest even, NaN 0x7fc0) + auto put = [&](auto store) { +#pragma unroll + for (int mt = 0; mt < kMT; ++mt) { +#pragma unroll + for (int i = 0; i < 8; ++i) { + const int orow = m0 + wm * kWR + mt * 16 + 2 * i + rh; + if (orow >= a.m) continue; +#pragma unroll + for (int nt = 0; nt < kNT; ++nt) { + const int ocol = n0 + wn * kWC + nt * 16 + rl; + if (ocol < a.n) store(static_cast(orow) * a.n + ocol, acc[mt][nt][i]); + } + } + } + }; + if constexpr (HC_MIX) { + // stream wn's x tile to LDS, made tf_fn_hc_mix terms in place (gates from the table), 16 d a thread summed + auto bits = [](float v) { return __builtin_bit_cast(uint16_t, narrow(v)); }; + auto wide = [](uint16_t h) { return __uint_as_float(static_cast(h) << 16); }; + auto rnd = [&](float v) { return wide(bits(v)); }; + constexpr int kRow = 4 * 32 + 8; // a row's 4 x 32 d, padded 16 bytes against bank conflicts + static_assert(kWR * kRow * 2 <= kBM * kLdw * 4, "64 rows a stash buffer"); + auto slot = [&](int lrow) { return reinterpret_cast(lrow < kWR ? xs : ws) + (lrow % kWR) * kRow; }; + constexpr int kLoads = kBM * 4 * 4 / kThreads; // 16-byte pieces a thread: 4 a (row, stream) + u32x4 xv[kLoads]; +#pragma unroll + for (int l = 0; l < kLoads; ++l) { + const int e = tid + l * kThreads, lrow = e / 16, st = (e / 4) % 4, v = e % 4; + const int orow = m0 + lrow < a.m ? m0 + lrow : a.m - 1; + xv[l] = *reinterpret_cast(mix.x + (static_cast(orow) * 4 + st) * dims + bn * 32 + v * 8); + } + __syncthreads(); +#pragma unroll + for (int l = 0; l < kLoads; ++l) { + const int e = tid + l * kThreads, lrow = e / 16, st = (e / 4) % 4, v = e % 4; + *reinterpret_cast(slot(lrow) + st * 32 + v * 8) = xv[l]; + } + __syncthreads(); + uint16_t* mine = slot(wm * kWR) + wn * 32; +#pragma unroll + for (int mt = 0; mt < kMT; ++mt) { +#pragma unroll + for (int i = 0; i < 8; ++i) { + uint16_t* at = mine + (mt * 16 + 2 * i + rh) * kRow; +#pragma unroll + for (int nt = 0; nt < kNT; ++nt) { + const int j = nt * 16 + rl; + const float gate = wide(gates[bits(acc[mt][nt][i])]); + at[j] = bits(rnd(gate * wide(at[j]))); + } + } + } + __syncthreads(); + static_assert(kBM * 2 == kThreads, "a thread: one row's 16 d"); + const int lrow = tid / 2, d0 = (tid % 2) * 16; + if (m0 + lrow < a.m) { + const uint16_t* t = slot(lrow) + d0; + uint32_t w[4][8]; +#pragma unroll + for (int st = 0; st < 4; ++st) { + const u32x4 lo = *reinterpret_cast(t + st * 32); + const u32x4 hi = *reinterpret_cast(t + st * 32 + 8); + w[st][0] = lo.x, w[st][1] = lo.y, w[st][2] = lo.z, w[st][3] = lo.w; + w[st][4] = hi.x, w[st][5] = hi.y, w[st][6] = hi.z, w[st][7] = hi.w; + } + uint32_t out[8]; +#pragma unroll + for (int k = 0; k < 8; ++k) { + uint16_t h[2]; +#pragma unroll + for (int e = 0; e < 2; ++e) { + float total = 0.f; +#pragma unroll + for (int st = 0; st < 4; ++st) total += wide(static_cast(w[st][k] >> (16 * e))); + h[e] = bits(total / 4.f); + } + out[k] = static_cast(h[0]) | (static_cast(h[1]) << 16); + } + u32x4* dst = reinterpret_cast(mix.mixed + static_cast(m0 + lrow) * dims + bn * 32 + d0); + dst[0] = u32x4{out[0], out[1], out[2], out[3]}; + dst[1] = u32x4{out[4], out[5], out[6], out[7]}; + } + } else if (a.out16 != nullptr) { + auto* out = reinterpret_cast(a.out16); + put([&](long long at, float v) { out[at] = narrow(v); }); + } else { + put([&](long long at, float v) { a.out[at] = v; }); + } +#else + (void)a; + (void)mix; + __builtin_trap(); +#endif +} + +// A K's windows of loads ahead on gfx1151: 1 at K 2560, 6144 and 320; 2 at K 10240. +template +struct DenseTune { + static constexpr int kAhead = K == 10240 ? 2 : 1; +}; + +} // namespace rocm +} // namespace tf diff --git a/zig/kernels/hip/tiles/dot2_tiles.hip b/zig/kernels/hip/tiles/dot2_tiles.hip index 8bde31cd18..8e27810f18 100644 --- a/zig/kernels/hip/tiles/dot2_tiles.hip +++ b/zig/kernels/hip/tiles/dot2_tiles.hip @@ -347,8 +347,17 @@ using Dot = DotF16; template __global__ void affine_dot2_stream(Affine, StreamSides, int, int); \ template __global__ void affine_dot2_stream_relu2(Affine, StreamSides, int, int); \ template __global__ void affine_dot2_stream_relu2_pair(Affine, Affine, int, int, int); +// one column a lane (narrow launches): the plain product only +#define TF_STREAM1(BITS, R) \ + template __global__ void affine_dot2_stream(Affine, StreamSides, int, int); #if TF_MATRIX #define TF_WMMA(BITS) template __global__ void affine_wmma_gemm(Affine); +template __global__ void affine_wmma_moe_gu<4>(Affine, float); +template __global__ void affine_wmma_moe_down<4>(Affine); +template __global__ void affine_wmma_dense<320>(Affine); +template __global__ void affine_wmma_dense<2560>(Affine); +template __global__ void affine_wmma_dense<6144>(Affine); +template __global__ void affine_wmma_dense<10240>(Affine); #else #define TF_WMMA(BITS) #endif @@ -363,11 +372,21 @@ using Dot = DotF16; template __global__ void affine_dot2_row(Affine, int); \ template __global__ void affine_dot2_row(Affine, int); \ TF_LANES(BITS, 1) TF_LANES(BITS, 2) TF_LANES(BITS, 4) TF_LANES(BITS, kLaneRows) \ + TF_STREAM1(BITS, 1) TF_STREAM1(BITS, 2) TF_STREAM1(BITS, 4) \ TF_STREAM(BITS, 1, 2) TF_STREAM(BITS, 1, 4) TF_STREAM(BITS, 1, 8) \ TF_STREAM(BITS, 2, 2) TF_STREAM(BITS, 2, 4) TF_STREAM(BITS, 2, 8) \ TF_STREAM(BITS, 4, 2) TF_STREAM(BITS, 4, 4) \ TF_WMMA(BITS) +// the 5- to 8-row routed work lists: Flash Next's gate+up (CB 2) and down (CB 4) at 4-bit +template __global__ void affine_dot2_stream_list(Affine, StreamSides, int, int, int); +template __global__ void affine_dot2_stream_list(Affine, StreamSides, int, int, int); + +// the held-codes plain tile at 4-bit: 4 rows at the waves rule's columns, 8 rows at CB 2 and 4 +#define TF_HELD(R, CB) template __global__ void affine_dot2_stream_held(Affine, StreamSides, int, int); +TF_HELD(4, 1) TF_HELD(4, 2) TF_HELD(4, 4) +TF_HELD(8, 2) TF_HELD(8, 4) + TF_TILES(2) TF_TILES(3) TF_TILES(4) diff --git a/zig/kernels/hip/tiles/moe_gemm.hpp b/zig/kernels/hip/tiles/moe_gemm.hpp new file mode 100644 index 0000000000..ccb7b12bfa --- /dev/null +++ b/zig/kernels/hip/tiles/moe_gemm.hpp @@ -0,0 +1,271 @@ +#pragma once + +// Flash Next's routed expert products of a prompt on the gfx11 matrix cores, affine_wmma_gemm's arithmetic and bytes. + +// Inspired by mlx-serve's moe_prefill_cuda.zig: gate and up rows in one tile, SwiGLU epilogue, register prefetch. + +#include + +#include +#include + +#include "common/wmma.hpp" +#include "quant/mlx_decoder.hpp" +#include "tiles/plan.hpp" + +namespace tf { +namespace rocm { + +namespace moe_tile { +constexpr int kBM = 64; // rows a pass +constexpr int kBN = 128; // staged weight rows a block +constexpr int kThreads = 256; +} // namespace moe_tile + +struct MoeGateUp { + static constexpr int kK = 2560; // hidden + static constexpr int kNI = 640; // expert width: gate rows [0, 640), up rows [640, 1280) of an expert + static constexpr int kN = 2 * kNI; + static constexpr int kTG = 8; // groups a term load covers + static constexpr bool kAct = true; + static constexpr int kBlocks = kNI / 64; + // windows of loads held in registers (4: the fastest of 2, 4 and 8 on gfx1151) + static constexpr int kAhead = 4; + // staged row `line` of block x: gate column 64 x + line, then the up column 640 + 64 x + line - 64 + __device__ static int col(int bx, int line) { return line < 64 ? 64 * bx + line : kNI + 64 * bx + line - 64; } +}; + +struct MoeDown { + static constexpr int kK = 640; // expert width + static constexpr int kN = 2560; // hidden + static constexpr int kTG = 4; // 20 groups a row: spans of 4 + static constexpr bool kAct = false; + static constexpr int kBlocks = kN / 128; + // one window of loads ahead (2 is no faster on gfx1151) + static constexpr int kAhead = 1; + __device__ static int col(int bx, int line) { return 128 * bx + line; } +}; + +// KW: K a window, 64 or 128; a staged row is KW + 8 bf16 (8 lanes' 16-byte reads hit 32 banks). AHEAD: windows ahead. +template +__device__ __forceinline__ void wmma_moe_tile(Affine a, float limit) { +#if TF_DEVICE_WMMA_GFX11 + using namespace moe_tile; + static_assert(BITS == 4, "a 32-code group is one 16-byte chunk"); + static_assert(KW == 128 || KW == 64, "4 or 2 groups a window"); + constexpr int kK = S::kK; + constexpr int kGW = KW / 32; // groups a window + constexpr int kWindows = kK / KW; + constexpr int kLdw = (KW + 8) / 2; + constexpr int kWChunks = kBN * kGW / 256; // 16-byte weight chunks a thread a window + constexpr int kXPer = KW / 8; // 16-byte x pieces a row + constexpr int kXChunks = kBM * kXPer / 256; + constexpr int kTG = S::kTG; + constexpr int kTermEvery = kTG / kGW; // windows a term load covers + constexpr int kTW = kTG / 2; // words a thread's term load + static_assert(kK % KW == 0 && (kK / 32) % kTG == 0 && kTG % kGW == 0, "whole windows and term spans"); + static_assert(kWindows % AHEAD == 0, "a window's register slot is a compile-time constant"); + using Dec = MlxDecoder; + using T = WmmaBF16; + using TermLoad = std::conditional_t; + if (!Dec::take_item(a, blockIdx.z)) return; + __shared__ __attribute__((aligned(16))) uint32_t xs[kBM * kLdw]; + __shared__ __attribute__((aligned(16))) uint32_t ws[kBN * kLdw]; + __shared__ float sx[kGW][kBM]; + __shared__ float sc[kTG][kBN]; + __shared__ float bi[kTG][kBN]; + + const int tid = threadIdx.x; + const int lane = tid & 31; + const int wave = __builtin_amdgcn_readfirstlane(tid >> 5); + const int bx = blockIdx.x; + constexpr int kWordsRow = kK * BITS / 32; + constexpr int kGroups = kK / 32; + + // weights: chunk i of thread t is row (256 i + t) / kGW, group t % kGW of the window + const int wq = tid % kGW; + const uint32_t* wsrc[kWChunks]; +#pragma unroll + for (int i = 0; i < kWChunks; ++i) wsrc[i] = a.words + static_cast(S::col(bx, (256 * i + tid) / kGW)) * kWordsRow + wq * BITS; + // terms of row t % 128, kTG groups a load: the scales (t < 128) or the biases + const int trow = tid & (kBN - 1); + const bool thigh = tid >= kBN; + const long long tcol = static_cast(S::col(bx, trow)) * kGroups; + const TermLoad* tsrc = reinterpret_cast(static_cast(thigh ? a.bias.p : a.scale.p) + tcol); + // x: chunk i of thread t is row (256 i + t) / kXPer, 16-byte piece t % kXPer (group piece / 4, quad lane t % 4) + const int xc = tid % kXPer; + + // wave (wm, wn): rows 32 wm.., staged rows 16 wn.. and 64 + 16 wn..; a lane: column lane % 16, rows 2 i + lane / 16 + const int wm = wave & 1; + const int wn = wave >> 1; + const int rl = lane & 15; + const int rh = lane >> 4; + const int lines[2] = {wn * 16 + rl, 64 + wn * 16 + rl}; + const f32x8 zero = {0, 0, 0, 0, 0, 0, 0, 0}; + + for (int h0 = 0; h0 < a.m; h0 += kBM) { + const int rows_left = a.m - h0 < kBM ? a.m - h0 : kBM; + const u32x4* xsrc[kXChunks]; +#pragma unroll + for (int i = 0; i < kXChunks; ++i) { + const int r = (256 * i + tid) / kXPer; + const int rs = h0 + (r < rows_left ? r : rows_left - 1); + xsrc[i] = reinterpret_cast(static_cast(a.x) + x_row(a, rs) * kK) + xc; + } + const bool live0 = wm * 32 < rows_left; + const bool live1 = wm * 32 + 16 < rows_left; + u32x4 wreg[AHEAD][kWChunks]; + u32x4 xreg[AHEAD][kXChunks]; + TermLoad treg[AHEAD]; + f32x8 acc[2][2]; +#pragma unroll + for (int mt = 0; mt < 2; ++mt) { +#pragma unroll + for (int j = 0; j < 2; ++j) acc[mt][j] = zero; + } + // Every load is unconditional (a branch forces vmcnt(0) at a stash); terms load with a span's first window + constexpr bool kTermsStatic = AHEAD % kTermEvery == 0; + auto load = [&](std::integral_constant, int w, std::bool_constant = {}) { + const int wl = w < kWindows ? w : kWindows - 1; +#pragma unroll + for (int i = 0; i < kWChunks; ++i) wreg[R][i] = *reinterpret_cast(wsrc[i] + wl * kGW * BITS); +#pragma unroll + for (int i = 0; i < kXChunks; ++i) xreg[R][i] = xsrc[i][wl * kXPer]; + if constexpr (TERMS) treg[R] = tsrc[wl / kTermEvery]; + }; + auto stash = [&](std::integral_constant, int w) { +#pragma unroll + for (int i = 0; i < kWChunks; ++i) { + const int row = (256 * i + tid) / kGW; + const uint32_t wv[BITS] = {wreg[R][i].x, wreg[R][i].y, wreg[R][i].z, wreg[R][i].w}; + u32x4* dst = reinterpret_cast(ws + row * kLdw + wq * 16); +#pragma unroll + for (int v = 0; v < 4; ++v) { + uint32_t q[4]; +#pragma unroll + for (int h = 0; h < 4; ++h) q[h] = __builtin_bit_cast(uint32_t, Dec::template pair(wv, v * 8 + h * 2)); + dst[v] = u32x4{q[0], q[1], q[2], q[3]}; + } + } +#pragma unroll + for (int i = 0; i < kXChunks; ++i) { + const int row = (256 * i + tid) / kXPer; + *reinterpret_cast(xs + row * kLdw + xc * 4) = xreg[R][i]; + // the group's sum in order: quad lane 0 adds its 8 values and hands the sum on, ..., lane 3 stores it + const uint32_t q[4] = {xreg[R][i].x, xreg[R][i].y, xreg[R][i].z, xreg[R][i].w}; + float run = 0.f; +#pragma unroll + for (int hop = 0; hop < 4; ++hop) { + const float in = __shfl_up(run, 1, 4); + if ((tid & 3) == hop) { + run = hop == 0 ? 0.f : in; +#pragma unroll + for (int h = 0; h < 4; ++h) { + const typename T::pair p = __builtin_bit_cast(typename T::pair, q[h]); + run += T::lo(p); + run += T::hi(p); + } + } + } + if ((tid & 3) == 3) sx[xc >> 2][row] = run; + } + if (w % kTermEvery == 0) { + const uint32_t* tv = reinterpret_cast(&treg[R]); + float(*dst)[kBN] = thigh ? bi : sc; +#pragma unroll + for (int j = 0; j < kTG; ++j) dst[j][trow] = __uint_as_float(((tv[j >> 1] >> (16 * (j & 1))) & 0xffffu) << 16); + } + }; + + lds_barrier(); + [&](std::integer_sequence) { + (load(std::integral_constant{}, R, std::bool_constant{}), ...); + }(std::make_integer_sequence{}); + stash(std::integral_constant{}, 0); + load(std::integral_constant{}, AHEAD); + lds_barrier(); + // Window w: compute it, stash window w + 1 from its slot, refill the slot with window w + 1 + AHEAD. + auto window = [&](std::integral_constant, int w) { + constexpr int next = (J + 1) % AHEAD; + if (live0) { +#pragma unroll + for (int gi = 0; gi < kGW; ++gi) { + f32x8 d[2][2]; +#pragma unroll + for (int t = 0; t < 2; ++t) { + bf16x16 bf[2]; +#pragma unroll + for (int j = 0; j < 2; ++j) bf[j] = frag16(ws + lines[j] * kLdw + gi * 16 + t * 8); +#pragma unroll + for (int mt = 0; mt < 2; ++mt) { + if (mt == 1 && !live1) continue; + const bf16x16 af = frag16(xs + (wm * 32 + mt * 16 + rl) * kLdw + gi * 16 + t * 8); +#pragma unroll + for (int j = 0; j < 2; ++j) d[mt][j] = T::mma(af, bf[j], t == 0 ? zero : d[mt][j]); + } + } + const int gt = (kGW * w + gi) % kTG; +#pragma unroll + for (int mt = 0; mt < 2; ++mt) { + if (mt == 1 && !live1) continue; + float s_x[8]; +#pragma unroll + for (int i = 0; i < 8; ++i) s_x[i] = sx[gi][wm * 32 + mt * 16 + 2 * i + rh]; +#pragma unroll + for (int j = 0; j < 2; ++j) { + const float scale = sc[gt][lines[j]]; + const float bias = bi[gt][lines[j]]; +#pragma unroll + for (int i = 0; i < 8; ++i) { + acc[mt][j][i] = Dec::fold_scale(acc[mt][j][i], d[mt][j][i], scale); + acc[mt][j][i] = Dec::fold_bias(acc[mt][j][i], s_x[i], bias); + } + } + } + } + } + lds_barrier(); + // past the last window the stash rewrites LDS no later window reads + stash(std::integral_constant{}, w + 1); + load(std::integral_constant{}, w + 1 + AHEAD, std::bool_constant{}); + lds_barrier(); + }; + for (int w0 = 0; w0 < kWindows; w0 += AHEAD) { + [&](std::integer_sequence) { + (window(std::integral_constant{}, w0 + J), ...); + }(std::make_integer_sequence{}); + } + +#pragma unroll + for (int mt = 0; mt < 2; ++mt) { +#pragma unroll + for (int i = 0; i < 8; ++i) { + const int row = wm * 32 + mt * 16 + 2 * i + rh; + if (row >= rows_left) continue; + const long long orow = out_row(a, h0 + row); + if constexpr (S::kAct) { + // moe_act_kernel on the pair's fp32 sums: clamp when limit > 0, g / (1 + exp(-g)) * u, hip_bfloat16 + float g = acc[mt][0][i]; + float u = acc[mt][1][i]; + if (limit > 0.f) { + g = fminf(g, limit); + u = fminf(fmaxf(u, -limit), limit); + } + const hip_bfloat16 v(g / (1.f + expf(-g)) * u); + reinterpret_cast(a.out16)[orow * S::kNI + 64 * bx + wn * 16 + rl] = v.data; + } else { +#pragma unroll + for (int j = 0; j < 2; ++j) a.out[orow * S::kN + S::col(bx, lines[j])] = acc[mt][j][i]; + } + } + } + } +#else + (void)a; + (void)limit; + __builtin_trap(); +#endif +} + +} // namespace rocm +} // namespace tf diff --git a/zig/kernels/hip/tiles/stream.hpp b/zig/kernels/hip/tiles/stream.hpp index e17d21ed26..5e42e8d658 100644 --- a/zig/kernels/hip/tiles/stream.hpp +++ b/zig/kernels/hip/tiles/stream.hpp @@ -6,6 +6,7 @@ #include #include "common/dot2.hpp" +#include "common/tsum.hpp" #include "common/vec.hpp" #include "tiles/plan.hpp" @@ -51,15 +52,23 @@ __device__ inline void stream_dots(const typename T::pair (&xp)[RG][16], const u ...); } -// Epi::kPair: a lane's CB columns are CB / 2 gate columns and the same up columns; out is silu(gate) * up. -template -__device__ inline void stream_body(const typename Dec::Args& a, int lpc_log2, int gshift, int bx, int pair_cols, float limit) { +// One column's chunk as its 16 code pairs, each made once (HELD: they stay while every row's x is dotted with them). +template +__device__ inline void stream_code_pairs(const uint32_t (&w)[Dec::kWords], typename T::pair (&qp)[16], + std::integer_sequence) { + ((qp[I] = Dec::template stream_pair(w)), ...); +} + +// Epi::kPair: CB / 2 gate columns and the same up columns, out silu(gate) * up; HELD: a round's code pairs made once. +template +__device__ inline void stream_body(const typename Dec::Args& a, int lpc_log2, int gshift, int bx, int by, int pair_cols, + float limit) { using pair = typename T::pair; constexpr bool PAIR = Epi::kPair; constexpr int RG = R < 4 ? R : 4; // rows a pass keeps in registers constexpr int NG = R / RG; constexpr uint32_t kOne = T::ones; - const int row0 = blockIdx.y * R; // a block's rows: more than 8 rows are 8-row blocks on the grid's y + const int row0 = by * R; // a block's rows: row block `by` of R rows const int lpc = 1 << lpc_log2; const int lane = threadIdx.x & 31; const int j = lane & (lpc - 1); @@ -103,9 +112,22 @@ __device__ inline void stream_body(const typename Dec::Args& a, int lpc_log2, in br[c] = terms.bias_raw(at); } }; - // The dots of one round. A lane past the row's last chunk read the last one: its scale and bias are zero. + // One row's x chunk of a round, loaded before the next round's codes so the dots wait for this round alone + auto xload = [&](int base, uint32_t (&xn)[16], int r) { + const int q = base + j < nch ? base + j : nch - 1; + const u32x4* src = reinterpret_cast(xr[r] + static_cast(q) * 32); +#pragma unroll + for (int v = 0; v < 4; ++v) { + const u32x4 t = src[v]; + xn[4 * v] = t.x; + xn[4 * v + 1] = t.y; + xn[4 * v + 2] = t.z; + xn[4 * v + 3] = t.w; + } + }; + // The dots of one round (a lane past the row's last chunk reads it with zero terms); x1: R = 1's x chunk auto work = [&](int base, const uint32_t (&w)[CB][Dec::kWords], const unsigned short (&sr)[CB], - const unsigned short (&br)[CB]) { + const unsigned short (&br)[CB], const uint32_t (&x1)[16]) { const bool live = base + j < nch; const int q = live ? base + j : nch - 1; float sc[CB]; @@ -115,23 +137,51 @@ __device__ inline void stream_body(const typename Dec::Args& a, int lpc_log2, in sc[c] = live ? terms.widen(sr[c]) : 0.f; bi[c] = live ? terms.widen(br[c]) : 0.f; } + if constexpr (HELD) { + pair qp[CB][16]; +#pragma unroll + for (int c = 0; c < CB; ++c) { + stream_code_pairs(w[c], qp[c], std::make_integer_sequence{}); + } +#pragma unroll + for (int r = 0; r < R; ++r) { + if (row0 + r >= a.m) break; + uint32_t xn[16]; + xload(base, xn, r); + float s = 0.f; +#pragma unroll + for (int i = 0; i < 16; ++i) { + s = T::dot(__builtin_bit_cast(pair, xn[i]), __builtin_bit_cast(pair, kOne), s); + } + pair xp[16]; + stream_x_pairs(xn, xp, std::make_integer_sequence{}); +#pragma unroll + for (int c = 0; c < CB; ++c) { + float d = 0.f; +#pragma unroll + for (int i = 0; i < 16; ++i) d = T::dot(xp[i], qp[c][i], d); + acc[r][c] = Dec::fold_scale(acc[r][c], d, sc[c]); + acc[r][c] = Dec::fold_bias(acc[r][c], s, bi[c]); + } + } + return; + } #pragma unroll for (int g = 0; g < NG; ++g) { if (row0 + g * RG >= a.m) break; + // a pass with one live row loads and dots that row only; a row's sums do not depend on the rows beside it + const bool one = RG > 1 && row0 + g * RG + 1 >= a.m; pair xp[RG][16]; float sx[RG]; #pragma unroll for (int r = 0; r < RG; ++r) { + if (one && r > 0) break; uint32_t xn[16]; - const u32x4* src = - reinterpret_cast(xr[g * RG + r] + static_cast(q) * 32); -#pragma unroll - for (int v = 0; v < 4; ++v) { - const u32x4 t = src[v]; - xn[4 * v] = t.x; - xn[4 * v + 1] = t.y; - xn[4 * v + 2] = t.z; - xn[4 * v + 3] = t.w; + if constexpr (R == 1) { +#pragma unroll + for (int i = 0; i < 16; ++i) xn[i] = x1[i]; + } else { + xload(base, xn, g * RG + r); } float s = 0.f; #pragma unroll @@ -146,6 +196,16 @@ __device__ inline void stream_body(const typename Dec::Args& a, int lpc_log2, in float d[RG]; #pragma unroll for (int r = 0; r < RG; ++r) d[r] = 0.f; + if constexpr (RG > 1) { + if (one) { + stream_dots(reinterpret_cast(xp[0]), + w[c], reinterpret_cast(d[0]), + std::make_integer_sequence{}); + acc[g * RG][c] = Dec::fold_scale(acc[g * RG][c], d[0], sc[c]); + acc[g * RG][c] = Dec::fold_bias(acc[g * RG][c], sx[0], bi[c]); + continue; + } + } stream_dots(xp, w[c], d, std::make_integer_sequence{}); #pragma unroll for (int r = 0; r < RG; ++r) { @@ -168,22 +228,53 @@ __device__ inline void stream_body(const typename Dec::Args& a, int lpc_log2, in if constexpr (R == 1) { uint32_t wb[CB][Dec::kWords]; unsigned short sbb[CB], bbb[CB]; + uint32_t xn[16]; fetch(at(0), wa, sa, ba); for (int r = 0; r < rounds; r += 2) { + xload(at(r), xn, 0); if (r + 1 < rounds) fetch(at(r + 1), wb, sbb, bbb); - work(at(r), wa, sa, ba); + work(at(r), wa, sa, ba, xn); if (r + 1 >= rounds) break; + xload(at(r + 1), xn, 0); if (r + 2 < rounds) fetch(at(r + 2), wa, sa, ba); - work(at(r + 1), wb, sbb, bbb); + work(at(r + 1), wb, sbb, bbb, xn); } } else { // several rows: the dots cover the loads' latency, and registers go to the rows' x + const uint32_t none[16] = {}; for (int r = 0; r < rounds; ++r) { fetch(at(r), wa, sa, ba); - work(at(r), wa, sa, ba); + work(at(r), wa, sa, ba, none); } } + if (lpc == 32) { + // CH sums and up sums each in a transposing butterfly; lane (c << (5 - log2 CH)) holds column c's, stores it + constexpr int L = tsum_log2(CH); + const int c = lane >> (5 - L); +#pragma unroll + for (int r = 0; r < R; ++r) { + float g[CH]; +#pragma unroll + for (int k = 0; k < CH; ++k) g[k] = acc[r][k]; + float pv[PAIR ? 2 : 1]; + pv[0] = tsum(g, lane); + if constexpr (PAIR) { + float u[CH]; +#pragma unroll + for (int k = 0; k < CH; ++k) u[k] = acc[r][k + CH]; + pv[1] = tsum(u, lane); + } + const int col = col0 + c; + if ((lane & ((32 >> L) - 1)) != 0 || row0 + r >= a.m || col >= cols) continue; + if (!__builtin_isfinite(pv[0])) pv[0] = Dec::template repair_stream(a, xr[r], col, pv[0]); + if constexpr (PAIR) { + if (!__builtin_isfinite(pv[1])) pv[1] = Dec::template repair_stream(a, xr[r], col + pair_cols, pv[1]); + } + Epi::put(a, out_row(a, row0 + r), col, pv, 0, pair_cols, limit); + } + return; + } #pragma unroll for (int r = 0; r < R; ++r) { float v[CB]; @@ -211,9 +302,12 @@ __device__ inline void stream_body(const typename Dec::Args& a, int lpc_log2, in } // Item z of the plan (or plain product, or a group's side) at CB columns a lane, R rows; chunk group is q >> gshift. -template +template __device__ inline void stream_tile(typename Dec::Args& a, const Sides& sides, int lpc_log2, int gshift) { - int bx = blockIdx.x; + // row_blocks > 1: row blocks on the grid's x, so a column block's row blocks run together, its codes in cache + const bool rows_on_x = sides.row_blocks > 1; + int bx = rows_on_x ? static_cast(blockIdx.y) : static_cast(blockIdx.x); + const int by = rows_on_x ? static_cast(blockIdx.x) : static_cast(blockIdx.y); if (sides.count > 0) { int s = 0; while (s + 1 < sides.count && bx >= sides.first[s + 1]) ++s; @@ -226,15 +320,29 @@ __device__ inline void stream_tile(typename Dec::Args& a, const Sides& sides, in a.out = static_cast(sides.out[s]); } } - if (!Dec::take_item(a, blockIdx.z) || static_cast(blockIdx.y) * R >= a.m) return; + if (!Dec::take_item(a, blockIdx.z) || by * R >= a.m) return; if constexpr (Dec::kWideBytes == 4) { - stream_body(a, lpc_log2, gshift, bx, sides.pair_cols, sides.limit); + stream_body(a, lpc_log2, gshift, bx, by, sides.pair_cols, sides.limit); } else { // every chunk is wide-aligned when the words and the row stride are if (Dec::wide_aligned(a)) { - stream_body(a, lpc_log2, gshift, bx, sides.pair_cols, sides.limit); + stream_body(a, lpc_log2, gshift, bx, by, sides.pair_cols, sides.limit); } else { - stream_body(a, lpc_log2, gshift, bx, sides.pair_cols, sides.limit); + stream_body(a, lpc_log2, gshift, bx, by, sides.pair_cols, sides.limit); + } + } +} + +// A routed plan of 5 to 8 rows as a work list: block z walks items z, z + gridDim.z, ...; a row's sums as on the grid. +template +__device__ inline void stream_list(const typename Dec::Args& a, int pair_cols, float limit, int lpc_log2, int gshift, + int items) { + const int bx = static_cast(blockIdx.x); + for (int z = static_cast(blockIdx.z); z < items; z += static_cast(gridDim.z)) { + typename Dec::Args b = a; + if (!Dec::take_item(b, z)) continue; + for (int by = 0; by * R < b.m; ++by) { + stream_body(b, lpc_log2, gshift, bx, by, pair_cols, limit); } } } diff --git a/zig/src/core/contract/hip_records.zig b/zig/src/core/contract/hip_records.zig index 6d8ee06f85..fd59d8c7ff 100644 --- a/zig/src/core/contract/hip_records.zig +++ b/zig/src/core/contract/hip_records.zig @@ -9,13 +9,14 @@ pub const Record = struct { launch: limits.HipLaunch, usage: [limits.rdna.len]U const rms_ns = "_ZN2tf4rocm10rms_kernelI"; -/// The 4-bit stream tile with the relu^2 epilogue, `rows` rows and `cb` columns a lane: DotF16 on RDNA2, else DotBF16. -fn relu2Tile(comptime rows: u32, comptime cb: u32) limits.HipLaunch { - const fmt = "_ZN2tf4rocm24affine_dot2_stream_relu2INS0_{s}ELi4ELi{d}ELi{d}EEEvNS0_6AffineENS0_11StreamSidesEii"; - const half = std.fmt.comptimePrint(fmt, .{ "6DotF16", rows, cb }); - const brain = std.fmt.comptimePrint(fmt, .{ "7DotBF16", rows, cb }); +/// The 4-bit work list of 5 to 8 rows (4-row tile): SwiGLU pair at CB 2, plain at CB 4; DotF16 on RDNA2, else DotBF16. +fn listTile(comptime pair: bool) limits.HipLaunch { + const fmt = "_ZN2tf4rocm23affine_dot2_stream_listINS0_{s}ELi4ELi4ELi{d}ELb{d}EEEvNS0_6AffineENS0_11StreamSidesEiii"; + const cb: u32 = if (pair) 2 else 4; + const half = std.fmt.comptimePrint(fmt, .{ "6DotF16", cb, @intFromBool(pair) }); + const brain = std.fmt.comptimePrint(fmt, .{ "7DotBF16", cb, @intFromBool(pair) }); return .{ - .name = std.fmt.comptimePrint("relu2 stream tile 4-bit {d}x{d}", .{ rows, cb }), + .name = std.fmt.comptimePrint("{s} stream work list 4-bit 4x{d}", .{ if (pair) "swiglu" else "plain", cb }), .symbol = brain, .image = "affine_tiles", .threads = 128, @@ -25,6 +26,24 @@ fn relu2Tile(comptime rows: u32, comptime cb: u32) limits.HipLaunch { /// HIP kernels as launched; tf-hip-kernel-contract limits DIR re-derives the usage records from the code objects. const own_records = [_]Record{ + .{ + .launch = listTile(true), + .usage = .{ + .{ .vgprs = 161, .sgprs = 102, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 163, .sgprs = 102, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 163, .sgprs = 102, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 163, .sgprs = 105, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + }, + }, + .{ + .launch = listTile(false), + .usage = .{ + .{ .vgprs = 194, .sgprs = 107, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 220, .sgprs = 107, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 220, .sgprs = 107, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 220, .sgprs = 107, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + }, + }, .{ .launch = .{ .name = "RMS norm tf_rms_rows", .symbol = "tf_rms_rows", .image = "ops", .threads = 256 }, .usage = .{ @@ -285,78 +304,7 @@ const own_records = [_]Record{ .{ .vgprs = 131, .sgprs = 52, .lds = 20544, .private = 0, .bound = 128, .wave = 32 }, }, }, - .{ - .launch = relu2Tile(1, 2), - .usage = .{ - .{ .vgprs = 63, .sgprs = 53, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 65, .sgprs = 54, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 65, .sgprs = 54, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 65, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - }, - }, - .{ - .launch = relu2Tile(1, 4), - .usage = .{ - .{ .vgprs = 101, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 102, .sgprs = 57, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 102, .sgprs = 57, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 102, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - }, - }, - .{ - .launch = relu2Tile(1, 8), - .usage = .{ - .{ .vgprs = 181, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 178, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 178, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 178, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - }, - }, - .{ - .launch = relu2Tile(2, 2), - .usage = .{ - .{ .vgprs = 75, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 68, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 68, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 68, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - }, - }, - .{ - .launch = relu2Tile(2, 4), - .usage = .{ - .{ .vgprs = 93, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 102, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 102, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 102, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - }, - }, - .{ - .launch = relu2Tile(2, 8), - .usage = .{ - .{ .vgprs = 157, .sgprs = 65, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 158, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 158, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 158, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - }, - }, - .{ - .launch = relu2Tile(4, 2), - .usage = .{ - .{ .vgprs = 113, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 114, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 114, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 114, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - }, - }, - .{ - .launch = relu2Tile(4, 4), - .usage = .{ - .{ .vgprs = 147, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 150, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 150, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 150, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - }, - }, +} ++ @import("hip_records_relu2.zig").records ++ [_]Record{ .{ .launch = .{ .name = "planned walk tf_plan_kv_write_act", @@ -424,6 +372,24 @@ const own_records = [_]Record{ .{ .vgprs = 8, .sgprs = 16, .lds = 2048, .private = 0, .bound = 256, .wave = 32 }, }, }, + .{ + .launch = .{ .name = "top-k tf_topk_part", .symbol = "tf_topk_part", .image = "ops", .threads = 1024 }, + .usage = .{ + .{ .vgprs = 33, .sgprs = 36, .lds = 1296, .private = 0, .bound = 1024, .wave = 32 }, + .{ .vgprs = 78, .sgprs = 36, .lds = 1296, .private = 0, .bound = 1024, .wave = 32 }, + .{ .vgprs = 78, .sgprs = 36, .lds = 1296, .private = 0, .bound = 1024, .wave = 32 }, + .{ .vgprs = 78, .sgprs = 36, .lds = 1296, .private = 0, .bound = 1024, .wave = 32 }, + }, + }, + .{ + .launch = .{ .name = "top-k tf_topk_join", .symbol = "tf_topk_join", .image = "ops", .threads = 1024 }, + .usage = .{ + .{ .vgprs = 16, .sgprs = 36, .lds = 33808, .private = 0, .bound = 1024, .wave = 32 }, + .{ .vgprs = 16, .sgprs = 36, .lds = 33808, .private = 0, .bound = 1024, .wave = 32 }, + .{ .vgprs = 16, .sgprs = 36, .lds = 33808, .private = 0, .bound = 1024, .wave = 32 }, + .{ .vgprs = 16, .sgprs = 37, .lds = 33808, .private = 0, .bound = 1024, .wave = 32 }, + }, + }, .{ .launch = .{ .name = "argmax tf_argmax_join", .symbol = "tf_argmax_join", .image = "ops", .threads = 256 }, .usage = .{ @@ -461,9 +427,55 @@ const own_records = [_]Record{ .{ .vgprs = 36, .sgprs = 32, .lds = 50688, .private = 0, .bound = 1024, .wave = 32 }, }, }, -} ++ @import("hip_records_pair.zig").records; + .{ + .launch = .{ .name = "MoE router (decode, fp32 rows) tf_router_decode_f16", .symbol = "tf_router_decode_f16", .image = "decode", .threads = 128 }, + .usage = .{ + .{ .vgprs = 106, .sgprs = 75, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 90, .sgprs = 75, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 90, .sgprs = 75, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 90, .sgprs = 76, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + }, + }, + .{ + .launch = .{ .name = "MoE router (decode, fp32 rows) tf_router_decode_bf16", .symbol = "tf_router_decode_bf16", .image = "decode", .threads = 128 }, + .usage = .{ + .{ .vgprs = 106, .sgprs = 75, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 91, .sgprs = 75, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 91, .sgprs = 75, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 91, .sgprs = 76, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + }, + }, + .{ + .launch = .{ .name = "MoE router and pick in one launch (decode, bf16 rows) tf_router_select_f16", .symbol = "tf_router_select_f16", .image = "decode", .threads = 128, .dynamic = 2 * 2560 * 2 }, + .usage = .{ + .{ .vgprs = 135, .sgprs = 86, .lds = 5456, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 135, .sgprs = 82, .lds = 5456, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 135, .sgprs = 82, .lds = 5456, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 135, .sgprs = 83, .lds = 5456, .private = 0, .bound = 128, .wave = 32 }, + }, + }, + .{ + .launch = .{ .name = "MoE router and pick in one launch (decode, bf16 rows) tf_router_select_bf16", .symbol = "tf_router_select_bf16", .image = "decode", .threads = 128, .dynamic = 2 * 2560 * 2 }, + .usage = .{ + .{ .vgprs = 135, .sgprs = 86, .lds = 5456, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 135, .sgprs = 82, .lds = 5456, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 135, .sgprs = 82, .lds = 5456, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 135, .sgprs = 83, .lds = 5456, .private = 0, .bound = 128, .wave = 32 }, + }, + }, + .{ + .launch = .{ .name = "MoE down codes read beside the gate and up (side stream) tf_moe_prefetch", .symbol = "tf_moe_prefetch", .image = "decode", .threads = 256 }, + .usage = .{ + .{ .vgprs = 11, .sgprs = 20, .lds = 260, .private = 0, .bound = 256, .wave = 32 }, + .{ .vgprs = 11, .sgprs = 20, .lds = 260, .private = 0, .bound = 256, .wave = 32 }, + .{ .vgprs = 11, .sgprs = 20, .lds = 260, .private = 0, .bound = 256, .wave = 32 }, + .{ .vgprs = 11, .sgprs = 18, .lds = 260, .private = 0, .bound = 256, .wave = 32 }, + }, + }, +} ++ @import("hip_records_wmma.zig").records ++ @import("hip_records_pair.zig").records; -pub const records = own_records ++ @import("hip_records_stream.zig").records; +pub const records = own_records ++ @import("hip_records_stream.zig").records ++ @import("hip_records_route.zig").records ++ + @import("hip_records_fn_attn.zig").records ++ @import("hip_records_hc.zig").records ++ @import("hip_records_gdn.zig").records; /// Gate 5's planted HIP controls: a launch past its __launch_bounds__, and 72 KiB of LDS where a workgroup has 64. pub const controls = [_]Record{ @@ -503,8 +515,13 @@ pub fn check(a: std.mem.Allocator, list: []const Record, quiet: bool) !usize { var out: std.ArrayList(u8) = .empty; defer out.deinit(a); var n: usize = 0; - for (list) |r| for (limits.rdna, r.usage) |t, u| { - if (u.vgprs == 0) { + for (list) |r| for (limits.rdna, r.usage, r.launch.served) |t, u, served| { + if (!served) { + if (u.vgprs != 0) { + try out.print(a, "{s} on {s}: usage recorded on a chip that does not launch it\n", .{ r.launch.name, t.name }); + n += 1; + } + } else if (u.vgprs == 0) { try out.print(a, "{s} on {s}: no compiled usage recorded\n", .{ r.launch.name, t.name }); n += 1; } else n += try limits.hip(r.launch, u, t, &out, a); @@ -557,3 +574,16 @@ test "a control cannot fit or lack compiled usage on any one chip" { } } } + +test "a chip a launch is not served on records no usage, and recorded usage there is a problem" { + const a = std.testing.allocator; + var r: Record = .{ .launch = .{ .name = "gfx11 tile", .symbol = "k", .image = "affine_tiles", .threads = 256, .served = limits.gfx11_only }, .usage = undefined }; + for (limits.rdna, &r.usage) |t, *u| u.* = if (std.mem.startsWith(u8, t.name, "gfx11")) .{ .vgprs = 64, .bound = 256 } else .{ .vgprs = 0 }; + try std.testing.expectEqual(@as(usize, 0), try check(a, &.{r}, true)); + r.usage[0] = .{ .vgprs = 64, .bound = 256 }; + try std.testing.expectEqual(@as(usize, 1), try check(a, &.{r}, true)); + // served everywhere: each chip without usage is a problem (gfx1030 and gfx1201 here) + r.launch.served = @splat(true); + r.usage[0] = .{ .vgprs = 0 }; + try std.testing.expectEqual(@as(usize, 2), try check(a, &.{r}, true)); +} diff --git a/zig/src/core/contract/hip_records_fn_attn.zig b/zig/src/core/contract/hip_records_fn_attn.zig new file mode 100644 index 0000000000..2e5439b73c --- /dev/null +++ b/zig/src/core/contract/hip_records_fn_attn.zig @@ -0,0 +1,23 @@ +//! Gate 5's records of Flash Next's index scores on HIP. +const Record = @import("hip_records.zig").Record; + +pub const records = [_]Record{ + .{ + .launch = .{ .name = "Flash Next index scores, 4 lanes a score", .symbol = "tf_fn_idx_scores_quad", .image = "flashnext", .threads = 128 }, + .usage = .{ + .{ .vgprs = 184, .sgprs = 22, .lds = 32772, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 184, .sgprs = 22, .lds = 32772, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 184, .sgprs = 20, .lds = 32772, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 184, .sgprs = 20, .lds = 32772, .private = 0, .bound = 128, .wave = 32 }, + }, + }, + .{ + .launch = .{ .name = "Flash Next index scores, 8 rows a wave", .symbol = "tf_fn_idx_scores8", .image = "flashnext", .threads = 256 }, + .usage = .{ + .{ .vgprs = 79, .sgprs = 26, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, + .{ .vgprs = 93, .sgprs = 26, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, + .{ .vgprs = 93, .sgprs = 26, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, + .{ .vgprs = 93, .sgprs = 44, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, + }, + }, +}; diff --git a/zig/src/core/contract/hip_records_gdn.zig b/zig/src/core/contract/hip_records_gdn.zig new file mode 100644 index 0000000000..a0cab4fa32 --- /dev/null +++ b/zig/src/core/contract/hip_records_gdn.zig @@ -0,0 +1,59 @@ +//! Gate 5's records of the DeltaNet launches (recurrence/gated_delta.hip, ops/linear.hpp). +const Record = @import("hip_records.zig").Record; + +pub const records = [_]Record{ + .{ + .launch = .{ .name = "DeltaNet tf_gdn_prompt_128", .symbol = "tf_gdn_prompt_128", .image = "gated_delta", .threads = 128 }, + .usage = .{ + .{ .vgprs = 175, .sgprs = 40, .lds = 20608, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 185, .sgprs = 39, .lds = 20608, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 185, .sgprs = 38, .lds = 20608, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 185, .sgprs = 38, .lds = 20608, .private = 0, .bound = 128, .wave = 32 }, + }, + }, + .{ + .launch = .{ .name = "DeltaNet tf_gdn_prompt_prep", .symbol = "tf_gdn_prompt_prep", .image = "ops", .threads = 256 }, + .usage = .{ + .{ .vgprs = 92, .sgprs = 59, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, + .{ .vgprs = 93, .sgprs = 59, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, + .{ .vgprs = 93, .sgprs = 59, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, + .{ .vgprs = 93, .sgprs = 60, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, + }, + }, + .{ + .launch = .{ .name = "DeltaNet tf_gdn_hold_128", .symbol = "tf_gdn_hold_128", .image = "gated_delta", .threads = 256 }, + .usage = .{ + .{ .vgprs = 38, .sgprs = 42, .lds = 17024, .private = 0, .bound = 256, .wave = 32 }, + .{ .vgprs = 38, .sgprs = 42, .lds = 17024, .private = 0, .bound = 256, .wave = 32 }, + .{ .vgprs = 38, .sgprs = 38, .lds = 17024, .private = 0, .bound = 256, .wave = 32 }, + .{ .vgprs = 38, .sgprs = 40, .lds = 17024, .private = 0, .bound = 256, .wave = 32 }, + }, + }, + .{ + .launch = .{ .name = "DeltaNet tf_gdn_hold_16", .symbol = "tf_gdn_hold_16", .image = "gated_delta", .threads = 256 }, + .usage = .{ + .{ .vgprs = 31, .sgprs = 36, .lds = 2688, .private = 0, .bound = 256, .wave = 32 }, + .{ .vgprs = 31, .sgprs = 38, .lds = 2688, .private = 0, .bound = 256, .wave = 32 }, + .{ .vgprs = 31, .sgprs = 36, .lds = 2688, .private = 0, .bound = 256, .wave = 32 }, + .{ .vgprs = 31, .sgprs = 38, .lds = 2688, .private = 0, .bound = 256, .wave = 32 }, + }, + }, + .{ + .launch = .{ .name = "DeltaNet tf_gdn_keep_128", .symbol = "tf_gdn_keep_128", .image = "gated_delta", .threads = 256 }, + .usage = .{ + .{ .vgprs = 39, .sgprs = 31, .lds = 8832, .private = 0, .bound = 256, .wave = 32 }, + .{ .vgprs = 39, .sgprs = 31, .lds = 8832, .private = 0, .bound = 256, .wave = 32 }, + .{ .vgprs = 39, .sgprs = 31, .lds = 8832, .private = 0, .bound = 256, .wave = 32 }, + .{ .vgprs = 39, .sgprs = 34, .lds = 8832, .private = 0, .bound = 256, .wave = 32 }, + }, + }, + .{ + .launch = .{ .name = "DeltaNet tf_gdn_keep_16", .symbol = "tf_gdn_keep_16", .image = "gated_delta", .threads = 256 }, + .usage = .{ + .{ .vgprs = 40, .sgprs = 29, .lds = 1664, .private = 0, .bound = 256, .wave = 32 }, + .{ .vgprs = 35, .sgprs = 28, .lds = 1664, .private = 0, .bound = 256, .wave = 32 }, + .{ .vgprs = 35, .sgprs = 28, .lds = 1664, .private = 0, .bound = 256, .wave = 32 }, + .{ .vgprs = 35, .sgprs = 31, .lds = 1664, .private = 0, .bound = 256, .wave = 32 }, + }, + }, +}; diff --git a/zig/src/core/contract/hip_records_hc.zig b/zig/src/core/contract/hip_records_hc.zig new file mode 100644 index 0000000000..0b90e4f569 --- /dev/null +++ b/zig/src/core/contract/hip_records_hc.zig @@ -0,0 +1,54 @@ +//! Gate 5's records of Flash Next's hyper-connection launches: the dense mix's gate table, the mixes and the norms. +const limits = @import("limits.zig"); +const Record = @import("hip_records.zig").Record; + +/// The chips with bf16 activations (all but RDNA2), the only ones that launch the 16-byte bf16 kernels. +const bf16_chips = [limits.rdna.len]bool{ false, true, true, true }; + +pub const records = [_]Record{ + .{ + .launch = .{ .name = "Flash Next HC gate table tf_hc_gate_fill", .symbol = "tf_hc_gate_fill", .image = "affine_tiles", .threads = 256, .served = limits.gfx11_only }, + .usage = .{ + .{ .vgprs = 0, .sgprs = 0, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, + .{ .vgprs = 7, .sgprs = 18, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, + .{ .vgprs = 7, .sgprs = 4, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, + .{ .vgprs = 0, .sgprs = 0, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, + }, + }, + .{ + .launch = .{ .name = "Flash Next HC mix tf_fn_hc_mix8", .symbol = "tf_fn_hc_mix8", .image = "flashnext", .threads = 256, .served = bf16_chips }, + .usage = .{ + .{ .vgprs = 0, .sgprs = 0, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, + .{ .vgprs = 68, .sgprs = 26, .lds = 0, .private = 0, .bound = 1024, .wave = 32 }, + .{ .vgprs = 68, .sgprs = 26, .lds = 0, .private = 0, .bound = 1024, .wave = 32 }, + .{ .vgprs = 68, .sgprs = 28, .lds = 0, .private = 0, .bound = 1024, .wave = 32 }, + }, + }, + .{ + .launch = .{ .name = "Flash Next HC norm tf_fn_hc_norm_v", .symbol = "tf_fn_hc_norm_v", .image = "flashnext", .threads = 128, .served = bf16_chips }, + .usage = .{ + .{ .vgprs = 0, .sgprs = 0, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 77, .sgprs = 22, .lds = 128, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 77, .sgprs = 22, .lds = 128, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 77, .sgprs = 23, .lds = 128, .private = 0, .bound = 128, .wave = 32 }, + }, + }, + .{ + .launch = .{ .name = "Flash Next HC norm with the MoE combine tf_fn_hc_norm_moe", .symbol = "tf_fn_hc_norm_moe", .image = "flashnext", .threads = 1024 }, + .usage = .{ + .{ .vgprs = 19, .sgprs = 40, .lds = 128, .private = 0, .bound = 1024, .wave = 32 }, + .{ .vgprs = 19, .sgprs = 40, .lds = 128, .private = 0, .bound = 1024, .wave = 32 }, + .{ .vgprs = 19, .sgprs = 40, .lds = 128, .private = 0, .bound = 1024, .wave = 32 }, + .{ .vgprs = 16, .sgprs = 42, .lds = 128, .private = 0, .bound = 1024, .wave = 32 }, + }, + }, + .{ + .launch = .{ .name = "Flash Next HC norm with the MoE combine, a block a row tf_fn_hc_norm_moe_v", .symbol = "tf_fn_hc_norm_moe_v", .image = "flashnext", .threads = 512, .served = bf16_chips }, + .usage = .{ + .{ .vgprs = 0, .sgprs = 0, .lds = 0, .private = 0, .bound = 512, .wave = 32 }, + .{ .vgprs = 51, .sgprs = 30, .lds = 10752, .private = 0, .bound = 512, .wave = 32 }, + .{ .vgprs = 59, .sgprs = 27, .lds = 10752, .private = 0, .bound = 512, .wave = 32 }, + .{ .vgprs = 59, .sgprs = 30, .lds = 10752, .private = 0, .bound = 512, .wave = 32 }, + }, + }, +}; diff --git a/zig/src/core/contract/hip_records_pair.zig b/zig/src/core/contract/hip_records_pair.zig index 117d572b5d..2460b0128d 100644 --- a/zig/src/core/contract/hip_records_pair.zig +++ b/zig/src/core/contract/hip_records_pair.zig @@ -21,73 +21,73 @@ pub const records = [_]Record{ .{ .launch = pairTile(1, 2), .usage = .{ - .{ .vgprs = 101, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 117, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 117, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 117, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 81, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 83, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 83, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 83, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = pairTile(1, 4), .usage = .{ - .{ .vgprs = 180, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 172, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 172, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 172, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 113, .sgprs = 65, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 121, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 121, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 121, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = pairTile(1, 8), .usage = .{ - .{ .vgprs = 181, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 178, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 178, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 178, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 187, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 186, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 186, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 186, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = pairTile(2, 2), .usage = .{ - .{ .vgprs = 123, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 152, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 152, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 152, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 93, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 109, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 109, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 109, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = pairTile(2, 4), .usage = .{ - .{ .vgprs = 177, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 236, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 236, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 236, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 119, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 135, .sgprs = 71, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 135, .sgprs = 71, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 135, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = pairTile(2, 8), .usage = .{ - .{ .vgprs = 157, .sgprs = 73, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 159, .sgprs = 76, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 159, .sgprs = 76, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 159, .sgprs = 76, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 164, .sgprs = 74, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 248, .sgprs = 74, .lds = 0, .private = 416, .bound = 128, .wave = 32 }, + .{ .vgprs = 248, .sgprs = 74, .lds = 0, .private = 416, .bound = 128, .wave = 32 }, + .{ .vgprs = 248, .sgprs = 74, .lds = 0, .private = 416, .bound = 128, .wave = 32 }, }, }, .{ .launch = pairTile(4, 2), .usage = .{ - .{ .vgprs = 194, .sgprs = 75, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 185, .sgprs = 76, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 185, .sgprs = 76, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 185, .sgprs = 75, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 146, .sgprs = 75, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 148, .sgprs = 76, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 148, .sgprs = 76, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 148, .sgprs = 75, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = pairTile(4, 4), .usage = .{ - .{ .vgprs = 148, .sgprs = 77, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 150, .sgprs = 78, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 150, .sgprs = 78, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 150, .sgprs = 80, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 177, .sgprs = 78, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 181, .sgprs = 79, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 181, .sgprs = 79, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 181, .sgprs = 78, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, }; diff --git a/zig/src/core/contract/hip_records_relu2.zig b/zig/src/core/contract/hip_records_relu2.zig new file mode 100644 index 0000000000..5d52561364 --- /dev/null +++ b/zig/src/core/contract/hip_records_relu2.zig @@ -0,0 +1,93 @@ +//! Gate 5's records of the relu^2 stream tiles (affine_dot2_stream_relu2). +const std = @import("std"); +const limits = @import("limits.zig"); +const Record = @import("hip_records.zig").Record; + +/// The 4-bit stream tile with the relu^2 epilogue, `rows` rows and `cb` columns a lane: DotF16 on RDNA2, else DotBF16. +fn relu2Tile(comptime rows: u32, comptime cb: u32) limits.HipLaunch { + const fmt = "_ZN2tf4rocm24affine_dot2_stream_relu2INS0_{s}ELi4ELi{d}ELi{d}EEEvNS0_6AffineENS0_11StreamSidesEii"; + const half = std.fmt.comptimePrint(fmt, .{ "6DotF16", rows, cb }); + const brain = std.fmt.comptimePrint(fmt, .{ "7DotBF16", rows, cb }); + return .{ + .name = std.fmt.comptimePrint("relu2 stream tile 4-bit {d}x{d}", .{ rows, cb }), + .symbol = brain, + .image = "affine_tiles", + .threads = 128, + .symbols = .{ half, brain, brain, brain }, + }; +} + +pub const records = [_]Record{ + .{ + .launch = relu2Tile(1, 2), + .usage = .{ + .{ .vgprs = 79, .sgprs = 54, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 83, .sgprs = 54, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 83, .sgprs = 54, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 83, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + }, + }, + .{ + .launch = relu2Tile(1, 4), + .usage = .{ + .{ .vgprs = 112, .sgprs = 57, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 121, .sgprs = 57, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 121, .sgprs = 57, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 121, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + }, + }, + .{ + .launch = relu2Tile(1, 8), + .usage = .{ + .{ .vgprs = 187, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 186, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 186, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 186, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + }, + }, + .{ + .launch = relu2Tile(2, 2), + .usage = .{ + .{ .vgprs = 93, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 110, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 110, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 110, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + }, + }, + .{ + .launch = relu2Tile(2, 4), + .usage = .{ + .{ .vgprs = 112, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 135, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 135, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 135, .sgprs = 65, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + }, + }, + .{ + .launch = relu2Tile(2, 8), + .usage = .{ + .{ .vgprs = 164, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 248, .sgprs = 90, .lds = 0, .private = 304, .bound = 128, .wave = 32 }, + .{ .vgprs = 248, .sgprs = 90, .lds = 0, .private = 304, .bound = 128, .wave = 32 }, + .{ .vgprs = 248, .sgprs = 86, .lds = 0, .private = 304, .bound = 128, .wave = 32 }, + }, + }, + .{ + .launch = relu2Tile(4, 2), + .usage = .{ + .{ .vgprs = 146, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 148, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 148, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 148, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + }, + }, + .{ + .launch = relu2Tile(4, 4), + .usage = .{ + .{ .vgprs = 176, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 181, .sgprs = 71, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 181, .sgprs = 71, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 181, .sgprs = 73, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + }, + }, +}; diff --git a/zig/src/core/contract/hip_records_route.zig b/zig/src/core/contract/hip_records_route.zig new file mode 100644 index 0000000000..cca1f213d1 --- /dev/null +++ b/zig/src/core/contract/hip_records_route.zig @@ -0,0 +1,41 @@ +//! Gate 5's records of the MoE route and pick launches: a prompt's plan in three launches and its picks. +const Record = @import("hip_records.zig").Record; + +pub const records = [_]Record{ + .{ + .launch = .{ .name = "MoE plan count tf_route_count", .symbol = "tf_route_count", .image = "ops", .threads = 256 }, + .usage = .{ + .{ .vgprs = 7, .sgprs = 13, .lds = 4096, .private = 0, .bound = 256, .wave = 32 }, + .{ .vgprs = 7, .sgprs = 18, .lds = 4096, .private = 0, .bound = 256, .wave = 32 }, + .{ .vgprs = 7, .sgprs = 13, .lds = 4096, .private = 0, .bound = 256, .wave = 32 }, + .{ .vgprs = 7, .sgprs = 12, .lds = 4096, .private = 0, .bound = 256, .wave = 32 }, + }, + }, + .{ + .launch = .{ .name = "MoE plan scan tf_route_scan", .symbol = "tf_route_scan", .image = "ops", .threads = 1024 }, + .usage = .{ + .{ .vgprs = 11, .sgprs = 15, .lds = 20480, .private = 0, .bound = 1024, .wave = 32 }, + .{ .vgprs = 11, .sgprs = 15, .lds = 20480, .private = 0, .bound = 1024, .wave = 32 }, + .{ .vgprs = 10, .sgprs = 16, .lds = 20480, .private = 0, .bound = 1024, .wave = 32 }, + .{ .vgprs = 10, .sgprs = 16, .lds = 20480, .private = 0, .bound = 1024, .wave = 32 }, + }, + }, + .{ + .launch = .{ .name = "MoE plan scatter tf_route_scatter", .symbol = "tf_route_scatter", .image = "ops", .threads = 512 }, + .usage = .{ + .{ .vgprs = 14, .sgprs = 14, .lds = 2048, .private = 0, .bound = 512, .wave = 32 }, + .{ .vgprs = 14, .sgprs = 18, .lds = 2048, .private = 0, .bound = 512, .wave = 32 }, + .{ .vgprs = 14, .sgprs = 14, .lds = 2048, .private = 0, .bound = 512, .wave = 32 }, + .{ .vgprs = 14, .sgprs = 12, .lds = 2048, .private = 0, .bound = 512, .wave = 32 }, + }, + }, + .{ + .launch = .{ .name = "MoE prompt picks a wave a row tf_select_rows", .symbol = "tf_select_rows", .image = "decode", .threads = 128 }, + .usage = .{ + .{ .vgprs = 135, .sgprs = 49, .lds = 5428, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 135, .sgprs = 46, .lds = 5428, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 135, .sgprs = 50, .lds = 5428, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 135, .sgprs = 52, .lds = 5428, .private = 0, .bound = 128, .wave = 32 }, + }, + }, +}; diff --git a/zig/src/core/contract/hip_records_stream.zig b/zig/src/core/contract/hip_records_stream.zig index ca37fb2193..4e84e6df92 100644 --- a/zig/src/core/contract/hip_records_stream.zig +++ b/zig/src/core/contract/hip_records_stream.zig @@ -18,5 +18,20 @@ pub fn tile(comptime bits: u32, comptime rows: u32, comptime cb: u32, comptime p }; } +/// The held-codes plain tile (stream_body's HELD), 4-bit only: `rows` rows, `cb` columns a lane. +pub fn held(comptime rows: u32, comptime cb: u32) limits.HipLaunch { + @setEvalBranchQuota(300_000); + const fmt = "_ZN2tf4rocm23affine_dot2_stream_heldINS0_{s}ELi4ELi{d}ELi{d}EEEvNS0_6AffineENS0_11StreamSidesEii"; + const half = std.fmt.comptimePrint(fmt, .{ "6DotF16", rows, cb }); + const brain = std.fmt.comptimePrint(fmt, .{ "7DotBF16", rows, cb }); + return .{ + .name = std.fmt.comptimePrint("held stream tile 4-bit {d}x{d}", .{ rows, cb }), + .symbol = brain, + .image = "affine_tiles", + .threads = 128, + .symbols = .{ half, brain, brain, brain }, + }; +} + pub const records = @import("hip_records_stream_plain.zig").records ++ - @import("hip_records_stream_swiglu.zig").records; + @import("hip_records_stream_swiglu.zig").records ++ @import("hip_records_stream_held.zig").records; diff --git a/zig/src/core/contract/hip_records_stream_held.zig b/zig/src/core/contract/hip_records_stream_held.zig new file mode 100644 index 0000000000..b460a21e09 --- /dev/null +++ b/zig/src/core/contract/hip_records_stream_held.zig @@ -0,0 +1,51 @@ +//! Compiler-derived launch usage of the held-codes plain stream tile on the four served RDNA targets. +const Record = @import("hip_records.zig").Record; +const held = @import("hip_records_stream.zig").held; + +pub const records = [_]Record{ + .{ + .launch = held(4, 1), + .usage = .{ + .{ .vgprs = 100, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 99, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 99, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 99, .sgprs = 75, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + }, + }, + .{ + .launch = held(4, 2), + .usage = .{ + .{ .vgprs = 126, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 128, .sgprs = 71, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 128, .sgprs = 71, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 128, .sgprs = 74, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + }, + }, + .{ + .launch = held(4, 4), + .usage = .{ + .{ .vgprs = 180, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 180, .sgprs = 73, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 180, .sgprs = 73, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 180, .sgprs = 76, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + }, + }, + .{ + .launch = held(8, 2), + .usage = .{ + .{ .vgprs = 201, .sgprs = 91, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 200, .sgprs = 90, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 200, .sgprs = 90, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 200, .sgprs = 91, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + }, + }, + .{ + .launch = held(8, 4), + .usage = .{ + .{ .vgprs = 256, .sgprs = 98, .lds = 0, .private = 68, .bound = 128, .wave = 32 }, + .{ .vgprs = 256, .sgprs = 92, .lds = 0, .private = 60, .bound = 128, .wave = 32 }, + .{ .vgprs = 256, .sgprs = 92, .lds = 0, .private = 60, .bound = 128, .wave = 32 }, + .{ .vgprs = 256, .sgprs = 94, .lds = 0, .private = 60, .bound = 128, .wave = 32 }, + }, + }, +}; diff --git a/zig/src/core/contract/hip_records_stream_plain.zig b/zig/src/core/contract/hip_records_stream_plain.zig index 795d84751a..a7f9472adc 100644 --- a/zig/src/core/contract/hip_records_stream_plain.zig +++ b/zig/src/core/contract/hip_records_stream_plain.zig @@ -3,19 +3,28 @@ const Record = @import("hip_records.zig").Record; const tile = @import("hip_records_stream.zig").tile; pub const records = [_]Record{ + .{ + .launch = tile(2, 1, 1, false), + .usage = .{ + .{ .vgprs = 57, .sgprs = 55, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 56, .sgprs = 54, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 56, .sgprs = 54, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 56, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + }, + }, .{ .launch = tile(2, 1, 2, false), .usage = .{ - .{ .vgprs = 53, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 55, .sgprs = 57, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 55, .sgprs = 57, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 55, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 59, .sgprs = 57, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 73, .sgprs = 57, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 73, .sgprs = 57, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 73, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(2, 1, 4, false), .usage = .{ - .{ .vgprs = 93, .sgprs = 57, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 94, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 94, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 94, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 94, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, @@ -24,415 +33,568 @@ pub const records = [_]Record{ .{ .launch = tile(2, 1, 8, false), .usage = .{ - .{ .vgprs = 153, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 150, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 150, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 150, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 154, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 154, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 154, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 154, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + }, + }, + .{ + .launch = tile(2, 2, 1, false), + .usage = .{ + .{ .vgprs = 74, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 69, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 69, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 69, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(2, 2, 2, false), .usage = .{ - .{ .vgprs = 62, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 64, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 64, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 64, .sgprs = 65, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 85, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 108, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 108, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 108, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(2, 2, 4, false), .usage = .{ - .{ .vgprs = 97, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 98, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 98, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 98, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 112, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 130, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 130, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 130, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(2, 2, 8, false), .usage = .{ - .{ .vgprs = 141, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 142, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 142, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 142, .sgprs = 71, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 151, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 175, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 175, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 175, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + }, + }, + .{ + .launch = tile(2, 4, 1, false), + .usage = .{ + .{ .vgprs = 128, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 119, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 119, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 119, .sgprs = 75, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(2, 4, 2, false), .usage = .{ - .{ .vgprs = 113, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 111, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 111, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 111, .sgprs = 73, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 143, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 147, .sgprs = 71, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 147, .sgprs = 71, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 147, .sgprs = 74, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(2, 4, 4, false), .usage = .{ - .{ .vgprs = 141, .sgprs = 71, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 142, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 142, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 142, .sgprs = 75, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 149, .sgprs = 71, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 173, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 173, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 173, .sgprs = 75, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + }, + }, + .{ + .launch = tile(3, 1, 1, false), + .usage = .{ + .{ .vgprs = 71, .sgprs = 51, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 58, .sgprs = 50, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 58, .sgprs = 50, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 58, .sgprs = 50, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(3, 1, 2, false), .usage = .{ - .{ .vgprs = 128, .sgprs = 50, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 113, .sgprs = 51, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 113, .sgprs = 51, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 113, .sgprs = 51, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 70, .sgprs = 53, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 77, .sgprs = 54, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 77, .sgprs = 54, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 77, .sgprs = 54, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(3, 1, 4, false), .usage = .{ - .{ .vgprs = 92, .sgprs = 52, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 93, .sgprs = 53, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 93, .sgprs = 53, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 93, .sgprs = 53, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 95, .sgprs = 55, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 97, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 97, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 97, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(3, 1, 8, false), .usage = .{ - .{ .vgprs = 170, .sgprs = 55, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 161, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 161, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 161, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 171, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 165, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 165, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 165, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + }, + }, + .{ + .launch = tile(3, 2, 1, false), + .usage = .{ + .{ .vgprs = 83, .sgprs = 57, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 96, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 96, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 96, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(3, 2, 2, false), .usage = .{ - .{ .vgprs = 102, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 122, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 122, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 122, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 76, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 109, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 109, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 109, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(3, 2, 4, false), .usage = .{ - .{ .vgprs = 96, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 90, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 90, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 90, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 95, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 133, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 133, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 133, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(3, 2, 8, false), .usage = .{ - .{ .vgprs = 137, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 138, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 138, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 138, .sgprs = 65, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 143, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 180, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 180, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 180, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + }, + }, + .{ + .launch = tile(3, 4, 1, false), + .usage = .{ + .{ .vgprs = 124, .sgprs = 65, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 132, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 132, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 132, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(3, 4, 2, false), .usage = .{ - .{ .vgprs = 89, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 107, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 107, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 107, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 108, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 146, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 146, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 146, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(3, 4, 4, false), .usage = .{ - .{ .vgprs = 131, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 134, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 134, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 134, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 142, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 174, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 174, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 174, .sgprs = 71, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + }, + }, + .{ + .launch = tile(4, 1, 1, false), + .usage = .{ + .{ .vgprs = 59, .sgprs = 55, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 60, .sgprs = 54, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 60, .sgprs = 54, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 60, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(4, 1, 2, false), .usage = .{ - .{ .vgprs = 63, .sgprs = 55, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 65, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 65, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 65, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 79, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 83, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 83, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 83, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(4, 1, 4, false), .usage = .{ - .{ .vgprs = 101, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 102, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 102, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 102, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 112, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 121, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 121, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 121, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(4, 1, 8, false), .usage = .{ - .{ .vgprs = 181, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 178, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 178, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 178, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 187, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 186, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 186, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 186, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + }, + }, + .{ + .launch = tile(4, 2, 1, false), + .usage = .{ + .{ .vgprs = 75, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 98, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 98, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 98, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(4, 2, 2, false), .usage = .{ - .{ .vgprs = 75, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 68, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 68, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 68, .sgprs = 65, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 88, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 110, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 110, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 110, .sgprs = 65, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(4, 2, 4, false), .usage = .{ - .{ .vgprs = 93, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 102, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 102, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 102, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 114, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 135, .sgprs = 65, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 135, .sgprs = 65, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 135, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(4, 2, 8, false), .usage = .{ - .{ .vgprs = 157, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 158, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 158, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 158, .sgprs = 71, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 164, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 188, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 188, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 188, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + }, + }, + .{ + .launch = tile(4, 4, 1, false), + .usage = .{ + .{ .vgprs = 126, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 134, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 134, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 134, .sgprs = 75, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(4, 4, 2, false), .usage = .{ - .{ .vgprs = 113, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 114, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 114, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 114, .sgprs = 73, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 146, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 148, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 148, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 148, .sgprs = 73, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(4, 4, 4, false), .usage = .{ - .{ .vgprs = 147, .sgprs = 71, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 150, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 150, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 150, .sgprs = 75, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 180, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 181, .sgprs = 73, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 181, .sgprs = 73, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 181, .sgprs = 76, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + }, + }, + .{ + .launch = tile(5, 1, 1, false), + .usage = .{ + .{ .vgprs = 74, .sgprs = 51, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 62, .sgprs = 50, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 62, .sgprs = 50, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 62, .sgprs = 50, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(5, 1, 2, false), .usage = .{ - .{ .vgprs = 130, .sgprs = 50, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 117, .sgprs = 51, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 117, .sgprs = 51, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 117, .sgprs = 51, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 71, .sgprs = 53, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 80, .sgprs = 54, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 80, .sgprs = 54, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 80, .sgprs = 54, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(5, 1, 4, false), .usage = .{ - .{ .vgprs = 108, .sgprs = 52, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 109, .sgprs = 53, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 109, .sgprs = 53, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 109, .sgprs = 53, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 111, .sgprs = 55, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 113, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 113, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 113, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(5, 1, 8, false), .usage = .{ - .{ .vgprs = 201, .sgprs = 55, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 193, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 193, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 193, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 202, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 197, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 197, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 197, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + }, + }, + .{ + .launch = tile(5, 2, 1, false), + .usage = .{ + .{ .vgprs = 83, .sgprs = 57, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 96, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 96, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 96, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(5, 2, 2, false), .usage = .{ - .{ .vgprs = 90, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 101, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 101, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 101, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 78, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 113, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 113, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 113, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(5, 2, 4, false), .usage = .{ - .{ .vgprs = 88, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 98, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 98, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 98, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 106, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 141, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 141, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 141, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(5, 2, 8, false), .usage = .{ - .{ .vgprs = 153, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 162, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 162, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 162, .sgprs = 65, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 157, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 194, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 194, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 194, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + }, + }, + .{ + .launch = tile(5, 4, 1, false), + .usage = .{ + .{ .vgprs = 124, .sgprs = 65, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 132, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 132, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 132, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(5, 4, 2, false), .usage = .{ - .{ .vgprs = 92, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 107, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 107, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 107, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 115, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 149, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 149, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 149, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(5, 4, 4, false), .usage = .{ - .{ .vgprs = 153, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 142, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 142, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 142, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 147, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 180, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 180, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 181, .sgprs = 71, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + }, + }, + .{ + .launch = tile(6, 1, 1, false), + .usage = .{ + .{ .vgprs = 64, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 64, .sgprs = 57, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 64, .sgprs = 57, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 64, .sgprs = 57, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(6, 1, 2, false), .usage = .{ - .{ .vgprs = 79, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 69, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 69, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 69, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 74, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 85, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 85, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 85, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(6, 1, 4, false), .usage = .{ - .{ .vgprs = 116, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 117, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 117, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 117, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 127, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 121, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 121, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 121, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(6, 1, 8, false), .usage = .{ - .{ .vgprs = 220, .sgprs = 65, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 209, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 209, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 209, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 219, .sgprs = 65, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 213, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 213, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 213, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + }, + }, + .{ + .launch = tile(6, 2, 1, false), + .usage = .{ + .{ .vgprs = 86, .sgprs = 65, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 98, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 98, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 98, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(6, 2, 2, false), .usage = .{ - .{ .vgprs = 71, .sgprs = 65, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 72, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 72, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 72, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 107, .sgprs = 65, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 113, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 113, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 113, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(6, 2, 4, false), .usage = .{ - .{ .vgprs = 101, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 102, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 102, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 102, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 133, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 143, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 143, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 143, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(6, 2, 8, false), .usage = .{ - .{ .vgprs = 173, .sgprs = 71, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 162, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 162, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 162, .sgprs = 74, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 193, .sgprs = 71, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 200, .sgprs = 73, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 200, .sgprs = 73, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 200, .sgprs = 74, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + }, + }, + .{ + .launch = tile(6, 4, 1, false), + .usage = .{ + .{ .vgprs = 123, .sgprs = 73, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 134, .sgprs = 76, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 134, .sgprs = 76, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 134, .sgprs = 77, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(6, 4, 2, false), .usage = .{ - .{ .vgprs = 106, .sgprs = 73, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 112, .sgprs = 74, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 112, .sgprs = 74, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 112, .sgprs = 76, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 141, .sgprs = 73, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 148, .sgprs = 75, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 148, .sgprs = 75, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 148, .sgprs = 76, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(6, 4, 4, false), .usage = .{ - .{ .vgprs = 162, .sgprs = 75, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 170, .sgprs = 76, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 170, .sgprs = 76, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 170, .sgprs = 78, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 175, .sgprs = 75, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 182, .sgprs = 77, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 182, .sgprs = 77, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 182, .sgprs = 78, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + }, + }, + .{ + .launch = tile(8, 1, 1, false), + .usage = .{ + .{ .vgprs = 64, .sgprs = 55, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 68, .sgprs = 54, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 68, .sgprs = 54, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 68, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(8, 1, 2, false), .usage = .{ - .{ .vgprs = 78, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 77, .sgprs = 57, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 77, .sgprs = 57, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 77, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 78, .sgprs = 57, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 95, .sgprs = 57, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 95, .sgprs = 57, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 95, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(8, 1, 4, false), .usage = .{ - .{ .vgprs = 133, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 134, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 134, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 134, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 136, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 137, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 137, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 137, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(8, 1, 8, false), .usage = .{ - .{ .vgprs = 226, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 256, .sgprs = 62, .lds = 0, .private = 124, .bound = 128, .wave = 32 }, - .{ .vgprs = 256, .sgprs = 62, .lds = 0, .private = 124, .bound = 128, .wave = 32 }, - .{ .vgprs = 256, .sgprs = 64, .lds = 0, .private = 124, .bound = 128, .wave = 32 }, + .{ .vgprs = 250, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 256, .sgprs = 62, .lds = 0, .private = 132, .bound = 128, .wave = 32 }, + .{ .vgprs = 256, .sgprs = 62, .lds = 0, .private = 132, .bound = 128, .wave = 32 }, + .{ .vgprs = 256, .sgprs = 64, .lds = 0, .private = 132, .bound = 128, .wave = 32 }, + }, + }, + .{ + .launch = tile(8, 2, 1, false), + .usage = .{ + .{ .vgprs = 78, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 96, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 96, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 96, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(8, 2, 2, false), .usage = .{ - .{ .vgprs = 83, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 75, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 75, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 75, .sgprs = 65, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 98, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 105, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 105, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 105, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(8, 2, 4, false), .usage = .{ - .{ .vgprs = 113, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 114, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 114, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 114, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 134, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 141, .sgprs = 65, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 141, .sgprs = 65, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 141, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(8, 2, 8, false), .usage = .{ - .{ .vgprs = 189, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 190, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 190, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 190, .sgprs = 71, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 195, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 205, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 205, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 205, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + }, + }, + .{ + .launch = tile(8, 4, 1, false), + .usage = .{ + .{ .vgprs = 114, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 132, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 132, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 132, .sgprs = 75, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(8, 4, 2, false), .usage = .{ - .{ .vgprs = 128, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 125, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 125, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 125, .sgprs = 73, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 131, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 155, .sgprs = 71, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 155, .sgprs = 71, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 155, .sgprs = 74, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(8, 4, 4, false), .usage = .{ - .{ .vgprs = 163, .sgprs = 71, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 164, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 164, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 164, .sgprs = 75, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 193, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 195, .sgprs = 73, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 195, .sgprs = 73, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 195, .sgprs = 76, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, }; diff --git a/zig/src/core/contract/hip_records_stream_swiglu.zig b/zig/src/core/contract/hip_records_stream_swiglu.zig index 44da49994d..6b0e1e91e4 100644 --- a/zig/src/core/contract/hip_records_stream_swiglu.zig +++ b/zig/src/core/contract/hip_records_stream_swiglu.zig @@ -6,433 +6,433 @@ pub const records = [_]Record{ .{ .launch = tile(2, 1, 2, true), .usage = .{ - .{ .vgprs = 52, .sgprs = 55, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 54, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 54, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 54, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 59, .sgprs = 55, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 72, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 72, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 72, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(2, 1, 4, true), .usage = .{ .{ .vgprs = 96, .sgprs = 57, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 88, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 88, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 88, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 91, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 91, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 91, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(2, 1, 8, true), .usage = .{ - .{ .vgprs = 157, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 154, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 154, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 154, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 158, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 158, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 158, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 158, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(2, 2, 2, true), .usage = .{ - .{ .vgprs = 62, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 64, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 64, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 64, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 82, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 105, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 105, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 105, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(2, 2, 4, true), .usage = .{ - .{ .vgprs = 96, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 92, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 92, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 92, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 110, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 128, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 128, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 128, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(2, 2, 8, true), .usage = .{ - .{ .vgprs = 137, .sgprs = 65, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 138, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 138, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 138, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 147, .sgprs = 65, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 171, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 171, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 171, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(2, 4, 2, true), .usage = .{ - .{ .vgprs = 112, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 111, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 111, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 111, .sgprs = 74, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 140, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 144, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 144, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 144, .sgprs = 74, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(2, 4, 4, true), .usage = .{ - .{ .vgprs = 137, .sgprs = 71, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 140, .sgprs = 74, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 140, .sgprs = 74, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 140, .sgprs = 76, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 147, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 171, .sgprs = 71, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 171, .sgprs = 71, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 171, .sgprs = 75, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(3, 1, 2, true), .usage = .{ - .{ .vgprs = 127, .sgprs = 49, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 112, .sgprs = 50, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 112, .sgprs = 50, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 112, .sgprs = 50, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 67, .sgprs = 52, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 74, .sgprs = 53, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 74, .sgprs = 53, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 74, .sgprs = 53, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(3, 1, 4, true), .usage = .{ - .{ .vgprs = 90, .sgprs = 50, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 91, .sgprs = 51, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 91, .sgprs = 51, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 91, .sgprs = 51, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 95, .sgprs = 53, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 96, .sgprs = 53, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 96, .sgprs = 53, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 96, .sgprs = 53, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(3, 1, 8, true), .usage = .{ - .{ .vgprs = 174, .sgprs = 52, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 165, .sgprs = 53, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 165, .sgprs = 53, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 165, .sgprs = 53, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 175, .sgprs = 55, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 169, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 169, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 169, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(3, 2, 2, true), .usage = .{ - .{ .vgprs = 102, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 122, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 122, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 122, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 73, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 109, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 109, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 109, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(3, 2, 4, true), .usage = .{ - .{ .vgprs = 94, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 88, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 88, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 88, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 93, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 94, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 94, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 94, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(3, 2, 8, true), .usage = .{ - .{ .vgprs = 133, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 134, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 134, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 134, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 142, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 176, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 176, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 176, .sgprs = 65, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(3, 4, 2, true), .usage = .{ - .{ .vgprs = 89, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 107, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 107, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 107, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 111, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 144, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 144, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 144, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(3, 4, 4, true), .usage = .{ - .{ .vgprs = 110, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 132, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 132, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 132, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 140, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 138, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 138, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 138, .sgprs = 71, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(4, 1, 2, true), .usage = .{ - .{ .vgprs = 58, .sgprs = 55, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 60, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 60, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 60, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 59, .sgprs = 55, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 75, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 75, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 75, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(4, 1, 4, true), .usage = .{ - .{ .vgprs = 99, .sgprs = 57, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 100, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 100, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 100, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 112, .sgprs = 57, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 119, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 119, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 119, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(4, 1, 8, true), .usage = .{ - .{ .vgprs = 185, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 182, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 182, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 182, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 191, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 190, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 190, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 190, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(4, 2, 2, true), .usage = .{ - .{ .vgprs = 91, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 68, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 68, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 68, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 83, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 106, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 106, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 106, .sgprs = 65, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(4, 2, 4, true), .usage = .{ - .{ .vgprs = 91, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 100, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 100, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 100, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 116, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 134, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 134, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 134, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(4, 2, 8, true), .usage = .{ - .{ .vgprs = 153, .sgprs = 65, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 154, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 154, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 154, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 163, .sgprs = 65, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 184, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 184, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 184, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(4, 4, 2, true), .usage = .{ - .{ .vgprs = 112, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 113, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 113, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 113, .sgprs = 74, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 143, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 145, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 145, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 145, .sgprs = 73, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(4, 4, 4, true), .usage = .{ - .{ .vgprs = 145, .sgprs = 71, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 148, .sgprs = 74, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 148, .sgprs = 74, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 148, .sgprs = 76, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 174, .sgprs = 71, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 179, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 179, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 179, .sgprs = 76, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(5, 1, 2, true), .usage = .{ - .{ .vgprs = 129, .sgprs = 49, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 116, .sgprs = 50, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 116, .sgprs = 50, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 116, .sgprs = 50, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 64, .sgprs = 52, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 76, .sgprs = 53, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 76, .sgprs = 53, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 76, .sgprs = 53, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(5, 1, 4, true), .usage = .{ - .{ .vgprs = 106, .sgprs = 50, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 107, .sgprs = 51, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 107, .sgprs = 51, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 107, .sgprs = 51, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 111, .sgprs = 53, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 112, .sgprs = 53, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 112, .sgprs = 53, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 112, .sgprs = 53, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(5, 1, 8, true), .usage = .{ - .{ .vgprs = 206, .sgprs = 52, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 197, .sgprs = 53, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 197, .sgprs = 53, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 197, .sgprs = 53, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 206, .sgprs = 55, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 201, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 201, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 201, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(5, 2, 2, true), .usage = .{ - .{ .vgprs = 90, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 101, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 101, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 101, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 75, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 75, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 75, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 75, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(5, 2, 4, true), .usage = .{ - .{ .vgprs = 86, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 96, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 96, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 96, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 104, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 104, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 104, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 104, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(5, 2, 8, true), .usage = .{ - .{ .vgprs = 149, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 158, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, .{ .vgprs = 158, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 158, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 190, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 190, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 190, .sgprs = 65, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(5, 4, 2, true), .usage = .{ - .{ .vgprs = 92, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 107, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 107, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 107, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 109, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 113, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 113, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 113, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(5, 4, 4, true), .usage = .{ - .{ .vgprs = 151, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 140, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 140, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 140, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 142, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 143, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 143, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 143, .sgprs = 71, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(6, 1, 2, true), .usage = .{ - .{ .vgprs = 78, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 68, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 68, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 68, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 71, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 82, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 82, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 82, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(6, 1, 4, true), .usage = .{ - .{ .vgprs = 114, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 115, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 115, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 115, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 127, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 121, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 121, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 121, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(6, 1, 8, true), .usage = .{ - .{ .vgprs = 224, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 213, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 213, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 213, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 223, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 217, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 217, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 217, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(6, 2, 2, true), .usage = .{ - .{ .vgprs = 71, .sgprs = 65, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 72, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 72, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 72, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 100, .sgprs = 65, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 108, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 108, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 108, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(6, 2, 4, true), .usage = .{ - .{ .vgprs = 99, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 100, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 100, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 100, .sgprs = 71, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 133, .sgprs = 67, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 141, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 141, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 141, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(6, 2, 8, true), .usage = .{ - .{ .vgprs = 157, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 170, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 170, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 170, .sgprs = 73, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 189, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 196, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 196, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 196, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(6, 4, 2, true), .usage = .{ - .{ .vgprs = 105, .sgprs = 73, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 111, .sgprs = 76, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 111, .sgprs = 76, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 111, .sgprs = 77, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 138, .sgprs = 73, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 145, .sgprs = 74, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 145, .sgprs = 74, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 145, .sgprs = 76, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(6, 4, 4, true), .usage = .{ - .{ .vgprs = 150, .sgprs = 75, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 164, .sgprs = 78, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 164, .sgprs = 78, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 164, .sgprs = 79, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 173, .sgprs = 75, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 180, .sgprs = 76, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 180, .sgprs = 76, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 180, .sgprs = 78, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(8, 1, 2, true), .usage = .{ - .{ .vgprs = 77, .sgprs = 55, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 76, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 76, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 76, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 75, .sgprs = 55, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 94, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 94, .sgprs = 56, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 94, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(8, 1, 4, true), .usage = .{ - .{ .vgprs = 131, .sgprs = 57, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 132, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 132, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 132, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 136, .sgprs = 57, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 137, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 137, .sgprs = 58, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 137, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(8, 1, 8, true), .usage = .{ - .{ .vgprs = 230, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 231, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 231, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 231, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 254, .sgprs = 59, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 235, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 235, .sgprs = 60, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 235, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(8, 2, 2, true), .usage = .{ - .{ .vgprs = 90, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 75, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 75, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 75, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 95, .sgprs = 61, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 102, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 102, .sgprs = 62, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 102, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(8, 2, 4, true), .usage = .{ - .{ .vgprs = 111, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 112, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 112, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 112, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 132, .sgprs = 63, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 139, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 139, .sgprs = 64, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 139, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(8, 2, 8, true), .usage = .{ - .{ .vgprs = 207, .sgprs = 65, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 186, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 186, .sgprs = 68, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 186, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 191, .sgprs = 65, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 201, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 201, .sgprs = 66, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 201, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(8, 4, 2, true), .usage = .{ .{ .vgprs = 128, .sgprs = 69, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 124, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 124, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 124, .sgprs = 74, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 152, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 152, .sgprs = 70, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 152, .sgprs = 74, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, .{ .launch = tile(8, 4, 4, true), .usage = .{ - .{ .vgprs = 161, .sgprs = 71, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 162, .sgprs = 74, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 162, .sgprs = 74, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, - .{ .vgprs = 162, .sgprs = 76, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 191, .sgprs = 71, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 193, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 193, .sgprs = 72, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, + .{ .vgprs = 193, .sgprs = 76, .lds = 0, .private = 0, .bound = 128, .wave = 32 }, }, }, }; diff --git a/zig/src/core/contract/hip_records_wmma.zig b/zig/src/core/contract/hip_records_wmma.zig new file mode 100644 index 0000000000..20b9599804 --- /dev/null +++ b/zig/src/core/contract/hip_records_wmma.zig @@ -0,0 +1,78 @@ +//! Gate 5's records of the gfx11 matrix-core prompt tiles and Flash Next's attention launches. +const limits = @import("limits.zig"); +const Record = @import("hip_records.zig").Record; + +pub const records = [_]Record{ + .{ + .launch = .{ .name = "prompt expert gate+up tile 4-bit", .symbol = "_ZN2tf4rocm18affine_wmma_moe_guILi4EEEvNS0_6AffineEf", .image = "affine_tiles", .threads = 256, .served = limits.gfx11_only }, + .usage = .{ + .{ .vgprs = 0, .sgprs = 0, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, + .{ .vgprs = 226, .sgprs = 34, .lds = 36352, .private = 0, .bound = 256, .wave = 32 }, + .{ .vgprs = 225, .sgprs = 36, .lds = 36352, .private = 0, .bound = 256, .wave = 32 }, + .{ .vgprs = 0, .sgprs = 0, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, + }, + }, + .{ + .launch = .{ .name = "prompt expert down tile 4-bit", .symbol = "_ZN2tf4rocm20affine_wmma_moe_downILi4EEEvNS0_6AffineE", .image = "affine_tiles", .threads = 256, .served = limits.gfx11_only }, + .usage = .{ + .{ .vgprs = 0, .sgprs = 0, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, + .{ .vgprs = 189, .sgprs = 33, .lds = 32256, .private = 0, .bound = 256, .wave = 32 }, + .{ .vgprs = 189, .sgprs = 34, .lds = 32256, .private = 0, .bound = 256, .wave = 32 }, + .{ .vgprs = 0, .sgprs = 0, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, + }, + }, + .{ + .launch = .{ .name = "prompt dense tile 4-bit K 320", .symbol = "_ZN2tf4rocm17affine_wmma_denseILi320EEEvNS0_6AffineE", .image = "affine_tiles", .threads = 256, .served = limits.gfx11_only }, + .usage = .{ + .{ .vgprs = 0, .sgprs = 0, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, + .{ .vgprs = 208, .sgprs = 22, .lds = 39936, .private = 0, .bound = 256, .wave = 32 }, + .{ .vgprs = 208, .sgprs = 22, .lds = 39936, .private = 0, .bound = 256, .wave = 32 }, + .{ .vgprs = 0, .sgprs = 0, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, + }, + }, + .{ + .launch = .{ .name = "prompt dense tile 4-bit K 320 with the HC mix", .symbol = "tf_affine_dense_hcmix", .image = "affine_tiles", .threads = 256, .served = limits.gfx11_only }, + .usage = .{ + .{ .vgprs = 0, .sgprs = 0, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, + .{ .vgprs = 215, .sgprs = 23, .lds = 39936, .private = 0, .bound = 256, .wave = 32 }, + .{ .vgprs = 215, .sgprs = 23, .lds = 39936, .private = 0, .bound = 256, .wave = 32 }, + .{ .vgprs = 0, .sgprs = 0, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, + }, + }, + .{ + .launch = .{ .name = "prompt dense tile 4-bit K 2560", .symbol = "_ZN2tf4rocm17affine_wmma_denseILi2560EEEvNS0_6AffineE", .image = "affine_tiles", .threads = 256, .served = limits.gfx11_only }, + .usage = .{ + .{ .vgprs = 0, .sgprs = 0, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, + .{ .vgprs = 208, .sgprs = 22, .lds = 39936, .private = 0, .bound = 256, .wave = 32 }, + .{ .vgprs = 208, .sgprs = 22, .lds = 39936, .private = 0, .bound = 256, .wave = 32 }, + .{ .vgprs = 0, .sgprs = 0, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, + }, + }, + .{ + .launch = .{ .name = "prompt dense tile 4-bit K 6144", .symbol = "_ZN2tf4rocm17affine_wmma_denseILi6144EEEvNS0_6AffineE", .image = "affine_tiles", .threads = 256, .served = limits.gfx11_only }, + .usage = .{ + .{ .vgprs = 0, .sgprs = 0, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, + .{ .vgprs = 208, .sgprs = 22, .lds = 39936, .private = 0, .bound = 256, .wave = 32 }, + .{ .vgprs = 208, .sgprs = 22, .lds = 39936, .private = 0, .bound = 256, .wave = 32 }, + .{ .vgprs = 0, .sgprs = 0, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, + }, + }, + .{ + .launch = .{ .name = "prompt dense tile 4-bit K 10240", .symbol = "_ZN2tf4rocm17affine_wmma_denseILi10240EEEvNS0_6AffineE", .image = "affine_tiles", .threads = 256, .served = limits.gfx11_only }, + .usage = .{ + .{ .vgprs = 0, .sgprs = 0, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, + .{ .vgprs = 246, .sgprs = 22, .lds = 39936, .private = 0, .bound = 256, .wave = 32 }, + .{ .vgprs = 246, .sgprs = 22, .lds = 39936, .private = 0, .bound = 256, .wave = 32 }, + .{ .vgprs = 0, .sgprs = 0, .lds = 0, .private = 0, .bound = 256, .wave = 32 }, + }, + }, + .{ + .launch = .{ .name = "Flash Next QSA decode prep", .symbol = "tf_fn_qsa_prep", .image = "flashnext", .threads = 256 }, + .usage = .{ + .{ .vgprs = 36, .sgprs = 50, .lds = 17440, .private = 0, .bound = 256, .wave = 32 }, + .{ .vgprs = 43, .sgprs = 50, .lds = 17440, .private = 0, .bound = 256, .wave = 32 }, + .{ .vgprs = 34, .sgprs = 52, .lds = 17440, .private = 0, .bound = 256, .wave = 32 }, + .{ .vgprs = 34, .sgprs = 51, .lds = 17440, .private = 0, .bound = 256, .wave = 32 }, + }, + }, +}; diff --git a/zig/src/core/contract/limits.zig b/zig/src/core/contract/limits.zig index 3089d01d31..7149de7cc1 100644 --- a/zig/src/core/contract/limits.zig +++ b/zig/src/core/contract/limits.zig @@ -181,6 +181,13 @@ pub const rdna = [_]Rdna{ .{ .name = "gfx1201", .vgprs_simd = 1536, .granule = 24 }, }; +/// `HipLaunch.served` of a tile only the gfx11 matrix cores run (RDNA3 and RDNA3.5, not RDNA2 or RDNA4). +pub const gfx11_only: [rdna.len]bool = blk: { + var on: [rdna.len]bool = undefined; + for (rdna, &on) |t, *o| o.* = std.mem.startsWith(u8, t.name, "gfx11"); + break :blk on; +}; + /// A HIP kernel as launched: its symbol, its code object, most threads a workgroup and dynamic LDS bytes. pub const HipLaunch = struct { name: []const u8, @@ -190,6 +197,8 @@ pub const HipLaunch = struct { dynamic: u32 = 0, /// The symbol on each chip (rdna's order) where it differs, as a stream tile's dot2 type does. symbols: ?[rdna.len][]const u8 = null, + /// The chips (rdna's order) that launch it: a gfx11 matrix-core tile records no usage elsewhere (`gfx11_only`). + served: [rdna.len]bool = @splat(true), /// The symbol the launch resolves on chip `i` of `rdna`. pub fn symbolOn(l: HipLaunch, i: usize) []const u8 { diff --git a/zig/src/core/lanes/config.zig b/zig/src/core/lanes/config.zig index 67561ea93b..a0db8fd594 100644 --- a/zig/src/core/lanes/config.zig +++ b/zig/src/core/lanes/config.zig @@ -27,6 +27,7 @@ pub const Model = struct { depth_rate: f64 = 0, // the newest round's weight in a depth's acceptance estimate (0: the core's) plain_guard: bool = false, // plain rounds compete with drafted depths draft_confidence: ?f64 = null, + pinned_depth: bool = false, // every round asks the head for the most drafts and verifies what it holds (its own gate stops it) drafts: u32 = 1, // head drafts a round at most window_costs: []const Cost = &.{}, // forward ms by exact window width (timed at load) mtp_step_ms: f64 = 0.0, // one chained head step (timed at load) @@ -64,6 +65,7 @@ pub const Config = struct { plain_guard: bool, most_drafts: u32, draft_confidence: ?f64 = null, + pinned_depth: bool = false, family_streams: bool, batch_rows: u32, batch_streams: u32, @@ -148,6 +150,7 @@ pub const Config = struct { .plain_guard = m.plain_guard, .most_drafts = @min(m.drafts, @min(width - 1, max_draft)), .draft_confidence = m.draft_confidence, + .pinned_depth = m.pinned_depth, .family_streams = streams, .batch_rows = batch_rows, .batch_streams = if (streams) (if (m.max_streams != 0) m.max_streams else 32) else 1, diff --git a/zig/src/core/lanes/depth.zig b/zig/src/core/lanes/depth.zig index 06a0c71c1e..ddce3168b6 100644 --- a/zig/src/core/lanes/depth.zig +++ b/zig/src/core/lanes/depth.zig @@ -60,6 +60,7 @@ pub const Rule = struct { plain_guard: bool, node_probabilities: bool, confidence_floor: ?f64 = null, + pinned: bool = false, // the most drafts every round: the head's own gate ends its chain (Model.pinned_depth) batch_rows: u32, batched_heads: bool = false, // one batch drafts every stream of a shared round (its steps: the deepest stream's) round_ms: Table = .{}, // a round's wall time by drafts, every stream's: what sampled streams price by @@ -144,7 +145,7 @@ pub const Rule = struct { pub fn depth(r: *Rule, who: Who) !i64 { const most = @min(@as(i64, r.most_drafts), @max(1, who.draft_room - 1)); if (most <= 0) return 0; - if (r.confidence_floor != null and !who.sampled) return most; + if ((r.confidence_floor != null and !who.sampled) or r.pinned) return most; const p = try r.rates(who); if (r.family_costs.empty()) { const want: i64 = if (p[0] < 0.8) 1 else if (p[0] < 0.9) 2 else 3; @@ -205,7 +206,7 @@ pub const Rule = struct { /// Head drafts for the streams of a shared round, sized by allocation over their chain chances. pub fn budgets(r: *Rule, whos: []Who, probe: Probe, sampled: bool, out: []i64) !void { - if (r.confidence_floor != null) { + if (r.confidence_floor != null or r.pinned) { for (whos, out) |*w, *o| o.* = try r.headDepth(w, null, probe); return; } @@ -373,6 +374,23 @@ test "under a confidence floor a greedy stream drafts the most, and a sampled on try std.testing.expectEqual(@as(i64, 1), try rule.headDepth(&sampled, null, probe)); // a first rate under 0.8: one draft } +test "a pinned depth asks for the most drafts every round, where the rule would draft one" { + const gpa = std.testing.allocator; + var fc: Table = .{}; + defer fc.deinit(gpa); + // rows past the first cost 20 ms each: the rule drafts one at a 0.5 estimate + for (1..9) |w| try fc.put(gpa, @intCast(w), 10.0 + 20.0 * @as(f64, @floatFromInt(w - 1))); + const shared: Table = .{}; + for ([_]bool{ false, true }, [_]i64{ 1, 7 }) |pinned, want| { + var rule: Rule = .{ .gpa = gpa, .prior = &.{ 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5 }, .most_drafts = 7, .family_costs = &fc, .shared_costs = &shared, .mtp_step_ms = 0.5, .plain_guard = false, .node_probabilities = false, .pinned = pinned, .batch_rows = 8 }; + defer rule.deinit(); + var st: ?State = null; + defer if (st) |*s| s.deinit(gpa); + const who: Who = .{ .state = &st, .draft_room = 100, .finished = false, .forced = false }; + for (0..7) |_| try std.testing.expectEqual(want, try rule.depth(who)); // before the 8th round's probe + } +} + test "a shared round's drafts come out the same whichever depths its overhead was measured at" { const gpa = std.testing.allocator; var shared: Table = .{}; diff --git a/zig/src/core/lanes/engine.zig b/zig/src/core/lanes/engine.zig index 231e453d26..ddcceb9d8a 100644 --- a/zig/src/core/lanes/engine.zig +++ b/zig/src/core/lanes/engine.zig @@ -72,6 +72,7 @@ pub const Engine = struct { .plain_guard = cfg.plain_guard, .node_probabilities = cfg.node_probabilities, .confidence_floor = cfg.draft_confidence, + .pinned = cfg.pinned_depth, .batch_rows = cfg.batch_rows, .batched_heads = cfg.draft_streams, }, diff --git a/zig/src/core/lanes/lone_costs.zig b/zig/src/core/lanes/lone_costs.zig index 5b6cd608e1..6080ada056 100644 --- a/zig/src/core/lanes/lone_costs.zig +++ b/zig/src/core/lanes/lone_costs.zig @@ -14,7 +14,7 @@ fn observed(s: anytype) Table { pub fn enabled(e: anytype, p: anytype) bool { return e.alone and e.cfg.lone_cost_tile > 0 and e.cfg.timed and e.cfg.plain_guard and - e.cfg.draft_confidence == null and p.kind == .head and p.lanes == null; + e.cfg.draft_confidence == null and !e.cfg.pinned_depth and p.kind == .head and p.lanes == null; } /// Measured full-round time at this width; otherwise the nearest sample plus the startup forward-time difference. diff --git a/zig/src/core/lanes/windows.zig b/zig/src/core/lanes/windows.zig index cae79f607c..c48b2bd0e9 100644 --- a/zig/src/core/lanes/windows.zig +++ b/zig/src/core/lanes/windows.zig @@ -241,6 +241,13 @@ pub fn anySampled(plans: []const Plan) bool { /// Trim draft prefixes by landing probability to the shared width with the most expected tokens a ms. pub fn allocate(e: *Engine, plans: []Plan) !void { + if (e.cfg.pinned_depth) { + // a pinned depth verifies every draft the head holds: its own confidence gate already ended the chain + for (plans) |p| { + if (p.kind == .head) p.stream.granted = @intCast(p.count()); + } + return; + } if (e.trim) |t| return trimmed(e, plans, t); const a = e.arena.allocator(); const fixed = try a.alloc(u32, plans.len); diff --git a/zig/src/families/flashnext/hip/cache.zig b/zig/src/families/flashnext/hip/cache.zig index 8717704472..5457ca6594 100644 --- a/zig/src/families/flashnext/hip/cache.zig +++ b/zig/src/families/flashnext/hip/cache.zig @@ -1,12 +1,12 @@ -//! A stream's state on a rank: sparse layers' keys, DeltaNet states, the n-gram tail; a window's per-row snapshots. +//! A stream's state on a rank: sparse keys, DeltaNet states, n-gram tail, a window's conv snapshots and DeltaNet inputs const std = @import("std"); const hip = @import("hip"); const model = @import("model.zig"); const Dims = model.Dims; -/// Most rows a verified window holds: the pending token and up to three drafts. -pub const max_window = 4; +/// Most rows a verified window holds: the pending token and up to seven drafts. +pub const max_window = 8; /// Where the bytes of one sparse layer's caches start, and their strides. pub const SparseView = struct { k: u64, v: u64, raw: u64, pooled: u64 }; @@ -14,6 +14,9 @@ pub const SparseView = struct { k: u64, v: u64, raw: u64, pooled: u64 }; /// Where one DeltaNet layer's conv tail (fp32 (taps - 1, channels)) and recurrent state (fp32) live. pub const LinearView = struct { conv: u64, state: u64 }; +/// One DeltaNet layer's window inputs, as the window's conv and split wrote them and its keep reads them. +pub const WindowInputs = struct { k: u64, v: u64, gate: u64, beta: u64 }; + pub const Layout = struct { sparse: usize, linear: usize, @@ -26,6 +29,12 @@ pub const Layout = struct { state_bytes: usize, tail_rows: usize, tail_bytes: usize, + /// fp32 values of one window row's DeltaNet inputs: k (key heads x Dk), v (value heads x Dv), gate and beta. + in_row: usize, + key_heads: usize, + key_dim: usize, + value_heads: usize, + value_dim: usize, kv_heads: usize, head_dim: usize, index_dim: usize, @@ -48,6 +57,11 @@ pub const Layout = struct { .state_bytes = d.value_heads * d.key_dim * d.value_dim * 4, .tail_rows = d.ngram * (d.ple_taps - 1), .tail_bytes = d.ngram * (d.ple_taps - 1) * d.wide() * a, + .in_row = d.key_heads * d.key_dim + d.value_heads * d.value_dim + 2 * d.value_heads, + .key_heads = d.key_heads, + .key_dim = d.key_dim, + .value_heads = d.value_heads, + .value_dim = d.value_dim, .kv_heads = d.kv_heads, .head_dim = d.head_dim, .index_dim = d.index_dim, @@ -75,9 +89,14 @@ pub const Layout = struct { return l.sparse * sparse_rows + l.linear * l.linearBytes() + l.tail_bytes; } - /// Device bytes of a window's snapshots: every DeltaNet layer's conv tail and state after each row. + /// Device bytes of one DeltaNet layer's window inputs: max_window rows of k, then of v, then of gate, then of beta. + pub fn inBytes(l: Layout) usize { + return max_window * l.in_row * 4; + } + + /// Device bytes of a window's keep material: every DeltaNet layer's conv tail after each row, then its inputs. pub fn windowBytes(l: Layout) usize { - return max_window * l.linear * l.linearBytes(); + return max_window * l.linear * l.conv_bytes + l.linear * l.inBytes(); } /// Device bytes of the n-gram conv's input over a window: the tail, then the window's rows. @@ -92,10 +111,12 @@ pub const Caches = struct { slot: []usize, linear: []bool, mem: hip.DeviceBuffer, - /// Snapshots of the last window: every linear layer's conv tails (a row each), then their states (a row each). + /// The last window's keep material: every linear layer's conv tails (a row each), then its DeltaNet inputs. window: hip.DeviceBuffer, /// The n-gram conv's input over the last window (the tail, then its rows): a keep takes its new tail from it. cin: hip.DeviceBuffer, + /// The snapshot row the conv tails are at (null: their places), as `start()` says: a dropping keep names it. + pending: ?usize = null, /// Positions kept, and complete blocks pooled in every sparse layer. len: usize = 0, pooled: usize = 0, @@ -126,7 +147,8 @@ pub const Caches = struct { var mem = try hip.DeviceBuffer.alloc(d, layout.bytes()); errdefer mem.free(); try mem.fill8(0); - var window = try hip.DeviceBuffer.alloc(d, @max(layout.windowBytes(), 4)); + // the snapshots, then the i32 naming the row a window starts from (`start`) + var window = try hip.DeviceBuffer.alloc(d, layout.windowBytes() + 16); errdefer window.free(); var cin = try hip.DeviceBuffer.alloc(d, layout.cinBytes()); errdefer cin.free(); @@ -144,6 +166,10 @@ pub const Caches = struct { /// The state of fresh caches again, the memory kept: zeros, no positions, eos before any row. pub fn reset(c: *Caches, eos: i64) !void { try c.mem.fill8(0); + // the start word -1 (no snapshot row): bytes 0xff by the same blocking fill as the memory's + try hip.runtime.check(c.window.r.api.hipMemset(@ptrFromInt(c.start()), 0xff, 4)); + try hip.runtime.check(c.window.r.api.hipStreamSynchronize(null)); + c.pending = null; c.len = 0; c.pooled = 0; c.history = .{ eos, eos }; @@ -175,18 +201,73 @@ pub const Caches = struct { return .{ .conv = at, .state = at + l.conv_bytes }; } + /// The device i32 the window kernels read: the snapshot row their conv tails start from, -1 for their places. + pub fn start(c: *const Caches) u64 { + return c.window.base() + c.layout.windowBytes(); + } + + /// The window starts from snapshot row `row` (null: the states' own places), after the work on `s` so far. + pub fn startAt(c: *Caches, row: ?usize, s: hip.Stream) !void { + const same = if (row) |r| (if (c.pending) |q| q == r else false) else c.pending == null; + if (same) return; + const word: c_int = if (row) |r| @intCast(r) else -1; + try hip.runtime.check(c.window.r.api.hipMemsetD32Async(@ptrFromInt(c.start()), word, 1, s.handle)); + c.pending = row; + } + + /// The conv tails copied back from the snapshot row a keep named, for readers other than a window's kernels. + pub fn settle(c: *Caches, s: hip.Stream) !void { + const row = c.pending orelse return; + const l = c.layout; + for (c.linear, 0..) |linear, i| { + if (!linear) continue; + try hip.runtime.check(c.window.r.api.hipMemcpyDtoDAsync(@ptrFromInt(c.linearAt(i).conv), @ptrFromInt(c.snapshot(i, row)), l.conv_bytes, s.handle)); + } + try c.startAt(null, s); + } + + /// Every DeltaNet state run through the last window's first `kept` rows in one launch (the window's own scan). + pub fn keepStates(c: *const Caches, l: *const hip.Launcher, kept: usize, s: hip.Stream) !void { + const lay = c.layout; + if (lay.linear == 0) return; + const first = for (c.linear, 0..) |linear, i| { + if (linear and c.slot[i] == 0) break i; + } else return error.NoLinearLayer; + try l.tf_gdn_keep( + @ptrFromInt(c.linearAt(first).state), + @intCast(lay.linearBytes() / 4), + @ptrFromInt(c.inputs(first).k), + @intCast(lay.inBytes() / 4), + max_window, + @intCast(kept), + @intCast(lay.linear), + @intCast(lay.key_heads), + @intCast(lay.value_heads), + @intCast(lay.key_dim), + @intCast(lay.value_dim), + s.handle, + ); + } + /// The n-gram conv's tail rows (act dtype, (tail_rows, W)). pub fn tail(c: *const Caches) u64 { const l = c.layout; return c.mem.base() + l.sparse * l.sparseBytes() + l.linear * l.linearBytes(); } - /// Row `row` of the window's snapshots of linear layer `layer`; a layer's rows consecutive, as the kernels write. - pub fn snapshot(c: *const Caches, layer: usize, row: usize) LinearView { - const l = c.layout; + /// Row `row` of linear layer `layer`'s window conv-tail snapshots, a layer's rows consecutive (the kernels' order). + pub fn snapshot(c: *const Caches, layer: usize, row: usize) u64 { const n = c.slot[layer] * max_window + row; - const states = c.window.base() + l.linear * max_window * l.conv_bytes; - return .{ .conv = c.window.base() + n * l.conv_bytes, .state = states + n * l.state_bytes }; + return c.window.base() + n * c.layout.conv_bytes; + } + + /// Where linear layer `layer`'s window inputs live: max_window rows of k, of v, of gate and of beta (fp32). + pub fn inputs(c: *const Caches, layer: usize) WindowInputs { + const l = c.layout; + const k = c.window.base() + l.linear * max_window * l.conv_bytes + c.slot[layer] * l.inBytes(); + const v = k + max_window * l.key_heads * l.key_dim * 4; + const gate = v + max_window * l.value_heads * l.value_dim * 4; + return .{ .k = k, .v = v, .gate = gate, .beta = gate + max_window * l.value_heads * 4 }; } }; diff --git a/zig/src/families/flashnext/hip/engine.zig b/zig/src/families/flashnext/hip/engine.zig index ce3b74fd5e..e7c6136d0b 100644 --- a/zig/src/families/flashnext/hip/engine.zig +++ b/zig/src/families/flashnext/hip/engine.zig @@ -52,6 +52,9 @@ pub const Engine = struct { ctx: hip.Context, lib: hip.Launcher, stream: hip.Stream, + /// A stream beside `stream` and the events its forks and joins take. + side: hip.Stream, + ring: hip.side.Ring, o: Options, cfg: config.Config, ck: core.checkpoint.Checkpoint, @@ -108,6 +111,10 @@ pub const Engine = struct { e.act = if (caps.act == .f16) .f16 else .bf16; e.stream = try hip.Stream.init(&e.driver); errdefer e.stream.deinit(); + e.side = try hip.Stream.init(&e.driver); + errdefer e.side.deinit(); + e.ring = try hip.side.Ring.init(&e.driver); + errdefer e.ring.deinit(); e.comm = null; // RCCL's init waits for every rank: none enters it unless every rank got this far _ = try steps.done(.{ 0, 0 }, .first); @@ -126,6 +133,8 @@ pub const Engine = struct { e.weights.model.tp = e.comm; const spelling = try spellingOf(e.keep.allocator(), io, dir); e.tables = try tables.Tables.init(e.keep.allocator(), &e.ck, &e.cfg, e.weights.model.ple.layer, spelling); + // one rank: the n-gram rows in anonymous memory (ranks of a group share the mapping's page cache instead) + if (o.world == 1 and o.policy.rows == .resident) try e.tables.keepResident(e.keep.allocator(), &e.ck); const c = mixers.qkConstants(e.cfg.key_dim); var w: [2]hip.DeviceBuffer = undefined; for (&w, [_]f32{ c.q, c.k }) |*b, v| { @@ -188,6 +197,9 @@ pub const Engine = struct { e.ck.close(); e.cfg.deinit(); if (e.comm) |c| c.close(); + e.side.synchronize() catch {}; + e.ring.deinit(); + e.side.deinit(); e.stream.deinit(); e.lib.unload(); e.ctx.deinit(); @@ -200,7 +212,7 @@ pub const Engine = struct { } pub fn ops(e: *Engine, arena: *hip.Arena) hip.ops.Ops { - return .{ .l = &e.lib, .bf16 = e.act == .bf16, .stream = e.stream.handle, .arena = arena }; + return .{ .l = &e.lib, .bf16 = e.act == .bf16, .stream = e.stream.handle, .arena = arena, .side = .{ .stream = e.side.handle, .ring = &e.ring } }; } /// The layer kinds as the caches lay them out: true for a DeltaNet layer. @@ -259,28 +271,14 @@ pub const Engine = struct { return .{ .ptr = out, .kind = y.kind }; } - /// The first `kept` rows of a window from `c.len` become the stream's: DeltaNet states, n-gram tail and history. + /// A window's first `kept` rows become the stream's: states run through them, a dropped row's conv tail named. pub fn keepWindow(e: *Engine, c: *cache.Caches, tokens: []const u32, kept: usize) !void { if (kept == 0 or kept > tokens.len) return error.BadKeep; const l = c.layout; const s = e.stream.handle; - if (kept < tokens.len) for (c.linear, 0..) |linear, i| { - if (!linear) continue; - const from = c.snapshot(i, kept - 1); - const to = c.linearAt(i); - try hip.runtime.check(e.driver.api.hipMemcpyDtoDAsync( - @ptrFromInt(to.conv), - @ptrFromInt(from.conv), - l.conv_bytes, - s, - )); - try hip.runtime.check(e.driver.api.hipMemcpyDtoDAsync( - @ptrFromInt(to.state), - @ptrFromInt(from.state), - l.state_bytes, - s, - )); - }; + // a window of one row stored its states (mixers.recur): nothing to run + if (tokens.len > 1) try c.keepStates(&e.lib, kept, e.stream); + try c.startAt(if (kept < tokens.len) kept - 1 else null, e.stream); const row = l.tail_bytes / l.tail_rows; try hip.runtime.check(e.driver.api.hipMemcpyDtoDAsync( @ptrFromInt(c.tail()), @@ -300,6 +298,7 @@ pub const Engine = struct { try e.stream.synchronize(); e.host.used = 0; e.arena.reset(); + try c.settle(e.stream); const segs = [_]forward.Seg{.{ .c = c, .tokens = tokens, .pos = c.len }}; const staged = try forward.stage(&e.weights.model, &e.host, &segs, false); const out = try forward.run(e.ops(&e.arena), &e.weights.model, &e.host, &segs, false, staged); diff --git a/zig/src/families/flashnext/hip/forward.zig b/zig/src/families/flashnext/hip/forward.zig index 9af288e27f..e9ad18a044 100644 --- a/zig/src/families/flashnext/hip/forward.zig +++ b/zig/src/families/flashnext/hip/forward.zig @@ -72,10 +72,14 @@ pub fn hcPre(o: Ops, m: *const model.Model, hc: model.Hc, x: Tensor, rows: usize @intCast(d.streams), o.stream, ); - const g = try o.project(act, hc.up, rows, true); + // a prompt's up product with the mix in the dense tile's epilogue (no g in memory): the same bytes + if (try o.hcUpMix(act, hc.up, x, rows)) |mixed| return mixed; + // g in the activation kind: the mix rounds it there first (the dense prompt tile writes it so, without a cast) + const g = try o.project(act, hc.up, rows, false); const mixed = try take(o, m.act, rows * d.hidden); try o.l.fn_hc_mix( @ptrFromInt(g.ptr), + @intCast(@backingInt(g.kind)), @ptrFromInt(x.ptr), @ptrFromInt(mixed.ptr), kind, @@ -382,15 +386,28 @@ pub fn run(ops: Ops, m: *const model.Model, host: *Host, segs: []const Seg, wind }; try hcBranch(o, m, h, branch, inject, x, layer.mhc.scale, rows); const mixed2 = try hcPre(o, m, layer.mhc, x, rows, inject); - const y = try hip.moe.run(o, m.act, layer.moe, mixed2, rows, !window); const next = if (i + 1 < m.layers.len) m.layers[i + 1].ahc.scale else m.mix.scale; - try hcBranch(o, m, h, y, inject, x, next, rows); + if (window and m.tp == null) { + // a window's MoE combine inside the next HC norm: the experts' rows and weights, one launch for both + const p = try hip.moe.parts(o, m.act, layer.moe, mixed2, rows); + try o.l.fn_hc_norm_moe(@ptrFromInt(h.ptr), @ptrFromInt(p.y), @ptrFromInt(p.wts), @ptrFromInt(inject.ptr), @ptrFromInt(h.ptr), @ptrFromInt(x.ptr), @ptrFromInt(next), @backingInt(m.act), @intCast(rows), @intCast(d.streams), @intCast(d.hidden), d.eps, @intCast(p.slots), o.stream); + } else if (m.tp == null and m.act == .bf16 and d.hidden == 2560 and d.streams <= 4) { + // a prompt's MoE combine inside the next HC norm, a block a row: the combined rows never written + const p = try hip.moe.parts(o, m.act, layer.moe, mixed2, rows); + try o.l.fn_hc_norm_moe_v(@ptrFromInt(h.ptr), @ptrFromInt(p.y), @ptrFromInt(p.wts), @ptrFromInt(inject.ptr), @ptrFromInt(h.ptr), @ptrFromInt(x.ptr), @ptrFromInt(next), @intCast(rows), @intCast(d.streams), d.eps, @intCast(p.slots), o.stream); + } else { + const y = try hip.moe.run(o, m.act, layer.moe, mixed2, rows, !window); + try hcBranch(o, m, h, y, inject, x, next, rows); + } } // a window's count moves in `Engine.round`, which a replay runs too: the launches change nothing on the host if (!window) for (segs) |g| { g.c.pooled = (g.pos + g.tokens.len) / d.index_ratio; }; - return .{ .mixed = try hcPre(o, m, m.mix, x, rows, null), .streams = h }; + const out: Out = .{ .mixed = try hcPre(o, m, m.mix, x, rows, null), .streams = h }; + // hip.moe.parts' side-stream prefetches (windows of <= prefetch_rows rows) rejoin the stream after the last layer + if (window and m.tp == null and rows <= hip.moe.prefetch_rows) try o.join(); + return out; } /// Streams a forward takes at once at most. diff --git a/zig/src/families/flashnext/hip/head.zig b/zig/src/families/flashnext/hip/head.zig index 8bf83c97d5..632ace62de 100644 --- a/zig/src/families/flashnext/hip/head.zig +++ b/zig/src/families/flashnext/hip/head.zig @@ -5,6 +5,8 @@ const model = @import("model.zig"); const cache = @import("cache.zig"); const forward = @import("forward.zig"); const mixers = @import("mixers.zig"); +const lanes = @import("lanes"); +const serve = @import("hip_serve"); const Ops = hip.ops.Ops; const Tensor = hip.ops.Tensor; @@ -24,22 +26,25 @@ pub fn caches( return cache.Caches.init(gpa, d, h.dims, &.{false}, cap, act, eos); } -/// `tokens` (each the token after its row) over residual `streams` from `pos`; `ones` a one a stream a row. -pub fn run( +/// The head's layer input: token embeddings and residual `streams` normed, projected, mixed; the first HC read. +const Entry = struct { o: Ops, h: Tensor, x: Tensor, inject: Tensor, mixed: Tensor, dev_pos: u64 }; + +fn entry( ops: Ops, m: *const model.Model, host: *forward.Host, - c: *cache.Caches, streams: Tensor, tokens: []const u32, pos: usize, ones: hip.DeviceBuffer, -) !Out { +) !Entry { + const rows = tokens.len; + // a window's rows (absorbs, chain steps) on the decode tiles; a prompt chunk's on the prefill tiles, as the trunk's var o = ops; - o.window = true; + o.window = rows <= cache.max_window; + o.prefill = !o.window; const w = &m.mtp.?; const d = w.dims; - const rows = tokens.len; if (rows * d.streams * m.act.size() > ones.len) return error.HeadRowsPastOnes; const ids = try host.gpa.alloc(i32, rows); defer host.gpa.free(ids); @@ -74,15 +79,54 @@ pub fn run( try forward.hcNorm(o, m, h, e, .{ .ptr = ones.base(), .kind = m.act }, x, l.ahc.scale, rows); const inject = try take(o, m.act, rows * d.streams); const mixed = try forward.hcPre(o, m, l.ahc, x, rows, inject); + return .{ .o = o, .h = h, .x = x, .inject = inject, .mixed = mixed, .dev_pos = dev_pos }; +} + +/// `tokens` (each the token after its row) over residual `streams` from `pos`; `ones` a one a stream a row. +pub fn run( + ops: Ops, + m: *const model.Model, + host: *forward.Host, + c: *cache.Caches, + streams: Tensor, + tokens: []const u32, + pos: usize, + ones: hip.DeviceBuffer, +) !Out { + const rows = tokens.len; + const w = &m.mtp.?; + const d = w.dims; + const l = w.layer; + const in = try entry(ops, m, host, streams, tokens, pos, ones); + const o = in.o; const seg = [_]forward.Seg{.{ .c = c, .tokens = tokens, .pos = pos }}; c.pooled = @min(c.pooled, pos / d.index_ratio); - const branch = try mixers.sparse(o, m, d, l.mixer.sparse, &seg, 0, mixed, rows, dev_pos, host, null); - try forward.hcNorm(o, m, h, branch, inject, x, l.mhc.scale, rows); - const mixed2 = try forward.hcPre(o, m, l.mhc, x, rows, inject); + const branch = try mixers.sparse(o, m, d, l.mixer.sparse, &seg, 0, in.mixed, rows, in.dev_pos, host, null); + try forward.hcNorm(o, m, in.h, branch, in.inject, in.x, l.mhc.scale, rows); + const mixed2 = try forward.hcPre(o, m, l.mhc, in.x, rows, in.inject); const y = try hip.moe.run(o, m.act, l.moe, mixed2, rows, false); - try forward.hcNorm(o, m, h, y, inject, x, w.mix.scale, rows); + try forward.hcNorm(o, m, in.h, y, in.inject, in.x, w.mix.scale, rows); c.pooled = (pos + rows) / d.index_ratio; - return .{ .mixed = try forward.hcPre(o, m, w.mix, x, rows, null), .streams = h }; + return .{ .mixed = try forward.hcPre(o, m, w.mix, in.x, rows, null), .streams = in.h }; +} + +/// The head's caches over prompt rows whose outputs nothing reads: run's key writes, no attention, HC reads or MoE. +pub fn keys( + ops: Ops, + m: *const model.Model, + host: *forward.Host, + c: *cache.Caches, + streams: Tensor, + tokens: []const u32, + pos: usize, + ones: hip.DeviceBuffer, +) !void { + const w = &m.mtp.?; + const d = w.dims; + const in = try entry(ops, m, host, streams, tokens, pos, ones); + c.pooled = @min(c.pooled, pos / d.index_ratio); + try mixers.sparseKeys(in.o, m, d, w.layer.mixer.sparse, .{ .c = c, .tokens = tokens, .pos = pos }, 0, in.mixed, in.dev_pos); + c.pooled = (pos + tokens.len) / d.index_ratio; } /// The draft head's greedy token for each of `rows` mixed rows (argmax over the draft vocabulary) and its probability. @@ -112,3 +156,50 @@ pub fn draws( p.* = @bitCast(f); } } + +/// Candidates a keyed draft downloads at most (top_k + MARGIN); a request asking for more drafts its argmax. +pub const max_keyed = 64; + +/// A sampled stream's draft: the target's keyed Gumbel-max over the head's survivors; null if greedy or past max_keyed. +pub fn keyed( + o: Ops, + m: *const model.Model, + host: *forward.Host, + s: hip.Stream, + mixed: Tensor, + ids: []const u32, + sampling: lanes.Sampling, + position: u64, + prob: ?*f32, +) !?u32 { + if (sampling.temperature <= 0 or sampling.top_k == 0) return null; + const w = &m.mtp.?; + const n = w.draft.n; + const stride: usize = @min(n, @as(usize, sampling.top_k) + serve.sample.MARGIN); + if (stride > max_keyed) return null; + const logits = try o.project(mixed, w.draft, 1, false); + const k: i32 = @intCast(stride); + const ks = try host.put(o, std.mem.asBytes(&k)); + // argmax, its probability, then the candidates' ids and values: one download + const dev = try o.arena.take(8 + stride * 6); + if (prob != null) { + try o.argmaxRows(logits, 1, n, dev); + try o.tokenProb(logits, 1, n, dev, dev + 4); + } + try o.topkRows(logits, 1, n, ks, stride, dev + 8, dev + 8 + stride * 4); + const at = std.mem.alignForward(usize, host.used, 16); + const bytes = host.staging.bytes[at..][0 .. 8 + stride * 6]; + try hip.runtime.check(host.d.api.hipMemcpyDtoHAsync(bytes.ptr, @ptrFromInt(dev), bytes.len, s.handle)); + try s.synchronize(); + const words = std.mem.bytesAsSlice(u32, @as([]align(4) u8, @alignCast(bytes[0 .. 8 + stride * 4]))); + if (prob) |q| q.* = @bitCast(words[1]); + const vals = std.mem.bytesAsSlice(u16, @as([]align(2) u8, @alignCast(bytes[8 + stride * 4 ..]))); + var values: [max_keyed]f64 = undefined; + var tokens: [max_keyed]u64 = undefined; + const dtype: serve.sample.Dtype = if (m.act == .f16) .f16 else .bf16; + for (0..stride) |j| { + values[j] = serve.sample.widen(vals, dtype, j); + tokens[j] = ids[words[2 + j]]; + } + return @intCast(try lanes.sampling.choose(host.gpa, values[0..stride], tokens[0..stride], position, sampling)); +} diff --git a/zig/src/families/flashnext/hip/lanes.zig b/zig/src/families/flashnext/hip/lanes.zig index 0f346ba986..5e3878eda4 100644 --- a/zig/src/families/flashnext/hip/lanes.zig +++ b/zig/src/families/flashnext/hip/lanes.zig @@ -16,7 +16,7 @@ const be = lanes.backend; const draw = serve.draw; /// Drawn tokens a handle names, newest last. -const ring = 1024; +pub const ring = 1024; /// Drafts the head holds for a stream at most. pub const max_depth = cache.max_window - 1; @@ -63,6 +63,8 @@ pub const Fx = struct { ones: hip.DeviceBuffer, draft_ids: []u32, drafts: u32, + /// The window forwards and a head step timed at load (measure): the depth rule's costs; none untimed. + costs: serve.costs.Costs = .{}, /// The kept prompt states (null: no reuse), and the slot the next one takes on every rank. store: ?pc.Store = null, next_slot: u32 = 0, @@ -134,6 +136,7 @@ pub const Fx = struct { fn snapSave(ptr: *anyopaque, owner: ?*anyopaque, at: u32) anyerror!pc.Saved { const f = of(ptr); const lane: *Lane = @ptrCast(@alignCast(owner orelse return error.NoOwner)); + try lane.caches.settle(f.e.stream); const saved = try snapshot.save( f.gpa, &f.e.driver, @@ -182,7 +185,7 @@ pub const Fx = struct { snapshot.drop(f.gpa, s); } - fn send(f: *Fx, words: []const u32) !void { + pub fn send(f: *Fx, words: []const u32) !void { if (f.e.stopped) return error.GroupStopped; if (f.link) |l| try l.send(words); } @@ -204,8 +207,80 @@ pub const Fx = struct { } }; } + /// One stream's window forwards (1 row to the cap's window) and a head step, timed at load: the depth rule's costs. + pub fn measure(f: *Fx) !void { + const e = f.e; + var rig: Rig = .{ .f = f, .c = try e.lease(0) }; + defer e.unlease(rig.c); + try serve.costs.forwards(&rig, @min(cache.max_window, f.drafts + 1), 1, cache.max_window, &f.costs); + if (e.weights.model.mtp != null) f.costs.step_ms = try rig.step(); + } + + const Rig = struct { + f: *Fx, + c: cache.Caches, + tokens: [cache.max_window]u32 = @splat(1), + + /// One verify's work for one stream of `widths[0]` rows: the round and the greedy draw of every row. + pub fn time(r: *Rig, widths: []const usize) !f64 { + if (widths.len != 1) return error.OneStreamTimed; + return serve.costs.mean(Window{ .r = r, .w = widths[0] }, Window.go); + } + + const Window = struct { + r: *Rig, + w: usize, + + fn go(x: Window) anyerror!void { + const e = x.r.f.e; + // each round from an empty stream: nothing is kept + x.r.c.len = 0; + const segs = [_]forward.Seg{.{ .c = &x.r.c, .tokens = x.r.tokens[0..x.w], .pos = 0 }}; + const done = try e.round(&segs, try e.choose(&segs)); + var reqs: [cache.max_window]draw.Request = undefined; + var out: [cache.max_window]u32 = undefined; + for (reqs[0..x.w], 0..) |*q, i| q.* = .{ .sampling = null, .position = 1 + i }; + try e.drawer.draw(e.ops(&e.arena), e.stream, done.logits, reqs[0..x.w], out[0..x.w], false); + } + }; + + /// One chained head step: the head's forward over one row and its draft's draw. + fn step(r: *Rig) !f64 { + const f = r.f; + const e = f.e; + const m = &e.weights.model; + var hc = try head_mod.caches(f.gpa, &e.driver, &m.mtp.?, 64, e.act, e.eos); + defer hc.deinit(f.gpa); + var streams = try hip.DeviceBuffer.alloc(&e.driver, m.dims.wide() * m.act.size()); + defer streams.free(); + return serve.costs.mean(Head{ .r = r, .hc = &hc, .streams = streams }, Head.go); + } + + const Head = struct { + r: *Rig, + hc: *cache.Caches, + streams: hip.DeviceBuffer, + + fn go(x: Head) anyerror!void { + const f = x.r.f; + const e = f.e; + const m = &e.weights.model; + try e.stream.synchronize(); + e.host.used = 0; + e.arena.reset(); + const o = e.ops(&e.arena); + const out = try head_mod.run(o, m, &e.host, x.hc, .{ .ptr = x.streams.base(), .kind = m.act }, x.r.tokens[0..1], 0, f.ones); + var tok: [1]u32 = undefined; + var prob: [1]f32 = undefined; + try head_mod.draws(o, m, &e.host, e.stream, out.mixed, 1, f.draft_ids, &tok, &prob); + } + }; + }; + pub fn facts(f: *const Fx) lanes.Model { const drafting = f.e.weights.model.mtp != null and f.drafts > 0; + // plain rounds compete with drafted ones once the forwards are timed + const timed = drafting and f.costs.windows > 0; return .{ .exact_width = cache.max_window, .gpu_tokens = false, @@ -217,6 +292,12 @@ pub const Fx = struct { .batch_rows = @intCast(cache.max_window * f.streams), .max_streams = @intCast(f.streams), .draft_streams = false, + .plain_guard = timed, + // gated: the most drafts every round, the head's per-step confidence (--mtp-confidence) ends the chain + .pinned_depth = drafting and f.e.o.policy.mtp_depth == .gated, + .window_costs = f.costs.window[0..f.costs.windows], + .shared_costs = f.costs.shared[0..f.costs.shareds], + .mtp_step_ms = f.costs.step_ms, }; } @@ -229,7 +310,7 @@ pub const Fx = struct { f.gpa.destroy(l); } - fn of(ptr: *anyopaque) *Fx { + pub fn of(ptr: *anyopaque) *Fx { const f: *Fx = @ptrCast(@alignCast(ptr)); if (bound != f.e) { f.e.ctx.makeCurrent() catch |err| std.log.err("hipSetDevice on the lane thread: {s}", .{@errorName(err)}); @@ -245,12 +326,12 @@ pub const Fx = struct { return at; } - fn sampling(s: *const lanes.Stream) ?lanes.Sampling { + pub fn sampling(s: *const lanes.Stream) ?lanes.Sampling { return s.sampling; } /// The pending window's first `rows` rows kept; the other ranks keep the same. - fn mark(f: *Fx, lane: *Lane, rows: usize) !void { + pub fn mark(f: *Fx, lane: *Lane, rows: usize) !void { const p = lane.pending orelse return; if (f.link != null) try f.send(&.{ @backingInt(worker.Op.keep), lane.id, @intCast(rows), @intCast(p.rows) }); try f.e.keepWindow(&lane.caches, p.tokens[0..p.rows], rows); @@ -288,7 +369,9 @@ pub const Fx = struct { while (f.slotBusy(slot, gop.key_ptr.*)) slot += 1; const caches = try e.lease(slot); errdefer e.unlease(caches); - var head: ?cache.Caches = if (m.mtp) |*h| try head_mod.caches( + // the head's caches only for a stream that drafts (not --no-drafts, "draft": false or --mtp-drafts 0) + const drafts = s.drafts and f.drafts > 0; + var head: ?cache.Caches = if (m.mtp) |*h| if (!drafts) null else try head_mod.caches( f.gpa, &e.driver, h, @@ -352,9 +435,9 @@ pub const Fx = struct { const rows = to - at; const row_bytes = m.dims.wide() * m.act.size(); if (lane.head) |*hc| { - // the head's keys for every prompt row with a next token (the last waits for the first draw) + // the head's keys for every prompt row with a next token (the last waits for the first draw), caches only const n = if (last) rows - 1 else rows; - if (n > 0) _ = try head_mod.run( + if (n > 0) try head_mod.keys( e.ops(&e.arena), m, &e.host, @@ -426,157 +509,10 @@ pub const Fx = struct { return f.drawn[handle % ring]; } - /// Every window in one forward, each from its stream's kept length; every row drawn at its position. - fn verifyFn(ptr: *anyopaque, windows: []const be.Window, out: []be.Verified) anyerror!void { - const f = of(ptr); - const e = f.e; - const m = &e.weights.model; - if (windows.len > forward.max_segs) return error.WindowTooWide; - var tokens: [forward.max_segs][cache.max_window]u32 = undefined; - var segs: [forward.max_segs]forward.Seg = undefined; - var total: usize = 0; - if (f.link != null) { - f.msg.clearRetainingCapacity(); - try f.msg.appendSlice(f.gpa, &.{ @backingInt(worker.Op.verify), @intCast(windows.len), 0 }); - } - for (windows, 0..) |w, i| { - if (w.parents != null) return error.TreesNotBuilt; - const lane = f.lanes.get(w.stream) orelse return error.UnknownStream; - if (lane.pending) |p| try f.mark(lane, p.rows); - const n = w.rows(); - if (n > cache.max_window) return error.WindowTooWide; - if (w.held > lane.held_n or (w.held > 0 and w.tokens.len > 0)) return error.NoHeldDrafts; - tokens[i][0] = w.pending; - if (w.held > 0) @memcpy(tokens[i][1..n], lane.held[0..w.held]) else @memcpy(tokens[i][1..n], w.tokens); - const len = lane.caches.len; - for (w.positions, 0..) |p, r| if (p != len + 1 + r) return error.PositionMismatch; - segs[i] = .{ .c = &lane.caches, .tokens = tokens[i][0..n], .pos = len }; - total += n; - if (f.link != null) { - try f.msg.appendSlice(f.gpa, &.{ lane.id, @intCast(n) }); - try f.msg.appendSlice(f.gpa, tokens[i][0..n]); - } - } - const pick = try e.choose(segs[0..windows.len]); - if (f.link != null) { - f.msg.items[2] = @backingInt(pick); - try f.send(f.msg.items); - } - const done = try e.round(segs[0..windows.len], pick); - const fw = done.out; - const row_bytes = m.dims.wide() * m.act.size(); - var off: usize = 0; - for (windows) |w| { - const lane = f.lanes.get(w.stream).?; - try hip.raw.copy(lane.streams, 0, fw.streams.ptr + off * row_bytes, w.rows() * row_bytes, e.stream.handle); - off += w.rows(); - } - const o = e.ops(&e.arena); - const logits = done.logits; - var reqs: [forward.max_segs * cache.max_window]draw.Request = undefined; - var drawn: [forward.max_segs * cache.max_window]u32 = undefined; - off = 0; - for (windows) |w| { - const n = w.rows(); - const words = if (w.masks.len > 0) w.masks.len / n else 0; - for (w.positions, 0..) |p, r| reqs[off + r] = .{ - .sampling = sampling(w.stream), - .position = p, - .mask = w.masks[r * words ..][0..words], - }; - off += n; - } - if (total > e.drawer.rows) return error.WindowTooWide; - try e.drawer.draw(o, e.stream, logits, reqs[0..total], drawn[0..total], false); - off = 0; - for (windows, out, 0..) |w, *v, i| { - const n = w.rows(); - const lane = f.lanes.get(w.stream).?; - @memcpy(v.sampled[0..n], drawn[off..][0..n]); - @memcpy(v.drafts, if (w.held > 0) lane.held[0..w.held] else w.tokens); - lane.held_n = 0; - lane.pending = .{ .tokens = tokens[i], .rows = n }; - off += n; - } - } - - fn keepFn(ptr: *anyopaque, windows: []const be.Window, paths: []const []const u32) anyerror!void { - const f = of(ptr); - for (windows, paths) |w, path| { - const lane = f.lanes.get(w.stream) orelse return error.UnknownStream; - for (path, 0..) |r, j| if (r != j) return error.TreesNotBuilt; - if (lane.pending != null) try f.mark(lane, path.len); - } - } - - /// The head absorbs each stream's kept rows (residual streams and the token after each), then chains its drafts. - fn draftFn(ptr: *anyopaque, requests: []const be.DraftRequest) anyerror!void { - const f = of(ptr); - const e = f.e; - const m = &e.weights.model; - const row_bytes = m.dims.wide() * m.act.size(); - for (requests) |r| { - const lane = f.lanes.get(r.stream) orelse return error.UnknownStream; - if (lane.pending) |p| try f.mark(lane, if (r.rows) |kept| kept.len else p.rows); - lane.held_n = 0; - if (r.position != lane.caches.len + 1) return error.PositionMismatch; - const hc = if (lane.head) |*h| h else continue; - const token: u32 = if (r.rows != null) - r.follow[r.follow.len - 1] - else switch (r.first orelse return error.NoFirstToken) { - .handle => |at| f.drawn[at % ring], - .value => |v| v, - }; - var follow_buf: [cache.max_window]u32 = undefined; - const follow: []const u32 = if (r.rows != null) r.follow else blk: { - follow_buf[0] = token; - break :blk follow_buf[0..1]; - }; - const start = lane.caches.len - follow.len; - try e.stream.synchronize(); - e.host.used = 0; - e.arena.reset(); - const o = e.ops(&e.arena); - var out = try head_mod.run( - o, - m, - &e.host, - hc, - .{ .ptr = lane.streams.base(), .kind = m.act }, - follow, - start, - f.ones, - ); - var mixed = forward.at(out.mixed, (follow.len - 1) * m.dims.hidden); - var streams = out.streams.ptr + (follow.len - 1) * row_bytes; - const depth = @min(r.depth, max_depth); - // a chain past the first round ends after a draft the head gives under the confidence (--mtp-confidence) - const stop_under: f32 = if (r.rows != null) @floatCast(e.o.policy.mtp.confidence) else 0.0; - var d: usize = 0; - var chained: usize = 0; - while (d < depth) : (d += 1) { - var tok: [1]u32 = undefined; - var prob: [1]f32 = undefined; - try head_mod.draws(o, m, &e.host, e.stream, mixed, 1, f.draft_ids, &tok, &prob); - lane.held[d] = tok[0]; - chained = d + 1; - if (d + 1 == depth or prob[0] < stop_under) break; - out = try head_mod.run( - o, - m, - &e.host, - hc, - .{ .ptr = streams, .kind = m.act }, - &tok, - lane.caches.len + d, - f.ones, - ); - mixed = out.mixed; - streams = out.streams.ptr; - } - lane.held_n = chained; - } - } + const lanes_round = @import("lanes_round.zig"); + const verifyFn = lanes_round.verifyFn; + const keepFn = lanes_round.keepFn; + const draftFn = lanes_round.draftFn; fn heldFn(ptr: *anyopaque, s: *lanes.Stream, _: std.mem.Allocator) anyerror!?lanes.stream.Held { const lane = of(ptr).lanes.get(s) orelse return error.UnknownStream; diff --git a/zig/src/families/flashnext/hip/lanes_round.zig b/zig/src/families/flashnext/hip/lanes_round.zig new file mode 100644 index 0000000000..796e149247 --- /dev/null +++ b/zig/src/families/flashnext/hip/lanes_round.zig @@ -0,0 +1,175 @@ +//! A lane round on Flash Next's HIP backend: every window verified in one forward, kept, then the head's drafts. +const hip = @import("hip"); +const lanes = @import("lanes"); +const serve = @import("hip_serve"); +const hip_lanes = @import("lanes.zig"); +const cache = @import("cache.zig"); +const forward = @import("forward.zig"); +const head_mod = @import("head.zig"); +const worker = @import("worker.zig"); + +const Fx = hip_lanes.Fx; +const be = lanes.backend; +const draw = serve.draw; +const ring = hip_lanes.ring; +const max_depth = hip_lanes.max_depth; +const of = Fx.of; +const sampling = Fx.sampling; + +/// Every window in one forward, each from its stream's kept length; every row drawn at its position. +pub fn verifyFn(ptr: *anyopaque, windows: []const be.Window, out: []be.Verified) anyerror!void { + const f = of(ptr); + const e = f.e; + const m = &e.weights.model; + if (windows.len > forward.max_segs) return error.WindowTooWide; + var tokens: [forward.max_segs][cache.max_window]u32 = undefined; + var segs: [forward.max_segs]forward.Seg = undefined; + var total: usize = 0; + if (f.link != null) { + f.msg.clearRetainingCapacity(); + try f.msg.appendSlice(f.gpa, &.{ @backingInt(worker.Op.verify), @intCast(windows.len), 0 }); + } + for (windows, 0..) |w, i| { + if (w.parents != null) return error.TreesNotBuilt; + const lane = f.lanes.get(w.stream) orelse return error.UnknownStream; + if (lane.pending) |p| try f.mark(lane, p.rows); + const n = w.rows(); + if (n > cache.max_window) return error.WindowTooWide; + if (w.held > lane.held_n or (w.held > 0 and w.tokens.len > 0)) return error.NoHeldDrafts; + tokens[i][0] = w.pending; + if (w.held > 0) @memcpy(tokens[i][1..n], lane.held[0..w.held]) else @memcpy(tokens[i][1..n], w.tokens); + const len = lane.caches.len; + for (w.positions, 0..) |p, r| if (p != len + 1 + r) return error.PositionMismatch; + segs[i] = .{ .c = &lane.caches, .tokens = tokens[i][0..n], .pos = len }; + total += n; + if (f.link != null) { + try f.msg.appendSlice(f.gpa, &.{ lane.id, @intCast(n) }); + try f.msg.appendSlice(f.gpa, tokens[i][0..n]); + } + } + const pick = try e.choose(segs[0..windows.len]); + if (f.link != null) { + f.msg.items[2] = @backingInt(pick); + try f.send(f.msg.items); + } + const done = try e.round(segs[0..windows.len], pick); + const fw = done.out; + const row_bytes = m.dims.wide() * m.act.size(); + var off: usize = 0; + for (windows) |w| { + const lane = f.lanes.get(w.stream).?; + try hip.raw.copy(lane.streams, 0, fw.streams.ptr + off * row_bytes, w.rows() * row_bytes, e.stream.handle); + off += w.rows(); + } + const o = e.ops(&e.arena); + const logits = done.logits; + var reqs: [forward.max_segs * cache.max_window]draw.Request = undefined; + var drawn: [forward.max_segs * cache.max_window]u32 = undefined; + off = 0; + for (windows) |w| { + const n = w.rows(); + const words = if (w.masks.len > 0) w.masks.len / n else 0; + for (w.positions, 0..) |p, r| reqs[off + r] = .{ + .sampling = sampling(w.stream), + .position = p, + .mask = w.masks[r * words ..][0..words], + }; + off += n; + } + if (total > e.drawer.rows) return error.WindowTooWide; + try e.drawer.draw(o, e.stream, logits, reqs[0..total], drawn[0..total], false); + off = 0; + for (windows, out, 0..) |w, *v, i| { + const n = w.rows(); + const lane = f.lanes.get(w.stream).?; + @memcpy(v.sampled[0..n], drawn[off..][0..n]); + @memcpy(v.drafts, if (w.held > 0) lane.held[0..w.held] else w.tokens); + lane.held_n = 0; + lane.pending = .{ .tokens = tokens[i], .rows = n }; + off += n; + } +} + +pub fn keepFn(ptr: *anyopaque, windows: []const be.Window, paths: []const []const u32) anyerror!void { + const f = of(ptr); + for (windows, paths) |w, path| { + const lane = f.lanes.get(w.stream) orelse return error.UnknownStream; + for (path, 0..) |r, j| if (r != j) return error.TreesNotBuilt; + if (lane.pending != null) try f.mark(lane, path.len); + } +} + +/// The head absorbs each stream's kept rows (residual streams and the token after each), then chains its drafts. +pub fn draftFn(ptr: *anyopaque, requests: []const be.DraftRequest) anyerror!void { + const f = of(ptr); + const e = f.e; + const m = &e.weights.model; + const row_bytes = m.dims.wide() * m.act.size(); + for (requests) |r| { + const lane = f.lanes.get(r.stream) orelse return error.UnknownStream; + if (lane.pending) |p| try f.mark(lane, if (r.rows) |kept| kept.len else p.rows); + lane.held_n = 0; + if (r.position != lane.caches.len + 1) return error.PositionMismatch; + const hc = if (lane.head) |*h| h else continue; + const token: u32 = if (r.rows != null) + r.follow[r.follow.len - 1] + else switch (r.first orelse return error.NoFirstToken) { + .handle => |at| f.drawn[at % ring], + .value => |v| v, + }; + var follow_buf: [cache.max_window]u32 = undefined; + const follow: []const u32 = if (r.rows != null) r.follow else blk: { + follow_buf[0] = token; + break :blk follow_buf[0..1]; + }; + const start = lane.caches.len - follow.len; + try e.stream.synchronize(); + e.host.used = 0; + e.arena.reset(); + const o = e.ops(&e.arena); + var out = try head_mod.run( + o, + m, + &e.host, + hc, + .{ .ptr = lane.streams.base(), .kind = m.act }, + follow, + start, + f.ones, + ); + var mixed = forward.at(out.mixed, (follow.len - 1) * m.dims.hidden); + var streams = out.streams.ptr + (follow.len - 1) * row_bytes; + const depth = @min(r.depth, max_depth); + // a chain ends after a draft under --mtp-confidence: past the first round, or always under mtp_depth=gated + const gate = r.rows != null or e.o.policy.mtp_depth == .gated; + const stop_under: f32 = if (gate) @floatCast(e.o.policy.mtp.confidence) else 0.0; + var d: usize = 0; + var chained: usize = 0; + while (d < depth) : (d += 1) { + var tok: [1]u32 = undefined; + var prob: [1]f32 = .{1.0}; + // a sampled stream drafts the target's keyed choice (head.keyed), its probability only for the gate + const keyed = if (sampling(r.stream)) |sm| + try head_mod.keyed(o, m, &e.host, e.stream, mixed, f.draft_ids, sm, r.position + d, if (stop_under > 0) &prob[0] else null) + else + null; + if (keyed) |t| tok[0] = t else try head_mod.draws(o, m, &e.host, e.stream, mixed, 1, f.draft_ids, &tok, &prob); + lane.held[d] = tok[0]; + chained = d + 1; + if (d + 1 == depth or prob[0] < stop_under) break; + out = try head_mod.run( + o, + m, + &e.host, + hc, + .{ .ptr = streams, .kind = m.act }, + &tok, + lane.caches.len + d, + f.ones, + ); + mixed = out.mixed; + streams = out.streams.ptr; + } + lane.held_n = chained; + } +} diff --git a/zig/src/families/flashnext/hip/load.zig b/zig/src/families/flashnext/hip/load.zig index 91923df52e..eae011abbb 100644 --- a/zig/src/families/flashnext/hip/load.zig +++ b/zig/src/families/flashnext/hip/load.zig @@ -186,6 +186,9 @@ const Loader = struct { .rows = r.router.shape[0], .remap = if (r.remap) |t| (try u.tensor(t)).ptr else 0, .exact = true, + // a decode step's router and pick in one launch read the bf16 rows (the same values as rows32) + .rows16 = (try u.tensor(r.router)).ptr, + .done = (try u.tensor(.{ .dtype = .u32, .rank = 1, .shape = .{ 1, 1, 1, 1, 1 }, .bytes = &[_]u8{ 0, 0, 0, 0 } })).ptr, .experts = .{ .fused = try quant.view(try quant.upload(u, r.experts.fused), true), .down = try quant.view(try quant.upload(u, r.experts.down), true), diff --git a/zig/src/families/flashnext/hip/mixers.zig b/zig/src/families/flashnext/hip/mixers.zig index 6c25d79412..7f9676e1e2 100644 --- a/zig/src/families/flashnext/hip/mixers.zig +++ b/zig/src/families/flashnext/hip/mixers.zig @@ -8,6 +8,8 @@ const forward = @import("forward.zig"); const Ops = hip.ops.Ops; const Tensor = hip.ops.Tensor; const take = forward.take; +const mixers_attend = @import("mixers_attend.zig"); +const attend = mixers_attend.attend; /// normalize_qk's constants: q and k scaled by rsqrt(sum + 1e-6) (q also by dk^-0.5) as an RMS norm with a weight. pub fn qkConstants(key_dim: usize) struct { q: f32, k: f32, eps: f32 } { @@ -41,20 +43,22 @@ pub fn linear( const gate = try o.arena.of(f32, rows * d.value_heads); const beta = try o.arena.of(f32, rows * d.value_heads); if (window) { - // a window's conv, split, q and k norms and gates in one launch a stream, each row's conv state kept aside + // a window's conv, split, norms and gates in one launch a stream; k, v, gate and beta into its window inputs var at_row: usize = 0; for (segs) |g| { const n = g.tokens.len; const nh = n * d.value_heads; + const in = g.c.inputs(index); try o.l.tf_conv_split(.{ .x = forward.at(qkv, at_row * ch).ptr, .kind = @backingInt(m.act), .weight = l.conv, .state = g.c.linearAt(index).conv, - .states = g.c.snapshot(index, 0).conv, + .states = g.c.snapshot(index, 0), + .from = g.c.start(), .qn = q + at_row * kw * 4, - .kn = k + at_row * kw * 4, - .v = v + at_row * vw * 4, + .kn = in.k, + .v = in.v, .channels = @intCast(ch), .kernel = @intCast(d.conv), .rows = @intCast(n), @@ -68,8 +72,8 @@ pub fn linear( .gb = forward.at(b, at_row * d.value_heads).ptr, .a_log = l.a_log, .dt_bias = l.dt_bias, - .gate = gate + at_row * d.value_heads * 4, - .beta = beta + at_row * d.value_heads * 4, + .gate = in.gate, + .beta = in.beta, .gcount = @intCast(nh), .heads = @intCast(d.value_heads), }, o.stream); @@ -77,6 +81,44 @@ pub fn linear( } return recur(o, m, l, segs, index, q, k, v, gate, beta, z, rows, true); } + if (o.fused() and d.key_dim == 128 and d.conv <= 8) { + // a stream's conv, split, q and k norms and gates in one launch (tf_gdn_prompt_prep: the chain's values) + var at_row: usize = 0; + for (segs) |g| { + const n = g.tokens.len; + const st = g.c.linearAt(index); + const conv_bytes = (d.conv - 1) * ch * 4; + const next = try o.arena.take(conv_bytes); + try o.l.tf_gdn_prompt_prep( + @ptrFromInt(forward.at(qkv, at_row * ch).ptr), + @backingInt(m.act), + @ptrFromInt(l.conv), + @ptrFromInt(st.conv), + @ptrFromInt(next), + @ptrFromInt(q + at_row * kw * 4), + @ptrFromInt(k + at_row * kw * 4), + @ptrFromInt(v + at_row * vw * 4), + @ptrFromInt(m.qk.q), + @ptrFromInt(m.qk.k), + m.qk.eps, + @intCast(n), + @intCast(kw), + @intCast(vw), + @intCast(d.conv), + @ptrFromInt(forward.at(a, at_row * d.value_heads).ptr), + @ptrFromInt(forward.at(b, at_row * d.value_heads).ptr), + @ptrFromInt(l.a_log), + @ptrFromInt(l.dt_bias), + @ptrFromInt(gate + at_row * d.value_heads * 4), + @ptrFromInt(beta + at_row * d.value_heads * 4), + @intCast(d.value_heads), + o.stream, + ); + if (o.stream != hip.counting) try hip.runtime.check(o.l.r.api.hipMemcpyDtoDAsync(@ptrFromInt(st.conv), @ptrFromInt(next), conv_bytes, o.stream)); + at_row += n; + } + return recur(o, m, l, segs, index, q, k, v, gate, beta, z, rows, false); + } const mixed = try o.arena.of(f32, rows * ch); var off: usize = 0; for (segs) |g| { @@ -143,13 +185,25 @@ fn recur( var off: usize = 0; for (segs) |g| { const n = g.tokens.len; - const snaps: ?u64 = if (window) g.c.snapshot(index, 0).state else null; + // a window's k, v, gate and beta are in the stream's window inputs (linear's conv and split wrote them there) + const in: cache.WindowInputs = if (window) g.c.inputs(index) else .{ + .k = k + off * kw * 4, + .v = v + off * vw * 4, + .gate = gate + off * d.value_heads * 4, + .beta = beta + off * d.value_heads * 4, + }; + if (window and n > 1) { + // the window holds the state (its keep runs it); a one-row window takes the plain scan, which stores it + try o.gatedDeltaHold(q + off * kw * 4, in.k, in.v, in.gate, in.beta, g.c.linearAt(index).state, y + off * vw * 4, n, d.key_heads, d.value_heads, d.key_dim, d.value_dim); + off += n; + continue; + } try o.gatedDelta( q + off * kw * 4, - k + off * kw * 4, - v + off * vw * 4, - gate + off * d.value_heads * 4, - beta + off * d.value_heads * 4, + in.k, + in.v, + in.gate, + in.beta, g.c.linearAt(index).state, y + off * vw * 4, n, @@ -157,7 +211,8 @@ fn recur( d.value_heads, d.key_dim, d.value_dim, - snaps, + null, + 0, ); off += n; } @@ -166,9 +221,79 @@ fn recur( return o.project(out, l.out, rows, l.out.partial); } -/// Rows of a prompt's attention a slice: the indexer's scores and the attention's parts stay bounded. -const slice_rows = 64; -const parts = 16; +/// A segment's keys, values, index keys and pools into its sparse caches: `sparse`'s eager writes (not tf_fn_qsa_prep). +fn writeKeys( + o: Ops, + m: *const model.Model, + d: model.Dims, + s: model.Sparse, + g: forward.Seg, + layer: usize, + keys: Tensor, + values: Tensor, + idx: Tensor, + off: usize, + at_pos: u64, +) !void { + const hd = d.head_dim; + const di = d.index_dim; + const width = (d.index_heads + 1) * di; + const n = g.tokens.len; + const kv = g.c.sparse(layer); + const cap = g.c.layout.cap; + const pos = g.pos; + try o.qkRope( + forward.at(keys, off * d.kv_heads * hd), + d.kv_heads * hd, + hd, + s.k_norm, + d.eps, + n, + d.kv_heads, + hd, + d.rotary, + d.theta, + at_pos, + null, + kv.k, + cap, + ); + try o.kvWrite(forward.at(values, off * d.kv_heads * hd), kv.v, n, d.kv_heads, hd, cap, pos); + try o.copyCols( + forward.at(idx, off * width), + width, + d.index_heads * di, + kv.raw + pos * di * m.act.size(), + n, + di, + ); + const blocks = (pos + n) / d.index_ratio; + const pooled = g.c.pooled; + if (blocks > pooled) try o.l.fn_idx_pool( + @ptrFromInt(kv.raw), + @ptrFromInt(kv.pooled + pooled * di * m.act.size()), + @ptrFromInt(s.ik_norm), + @backingInt(m.act), + @intCast(pooled), + @intCast(blocks - pooled), + @intCast(di), + @intCast(d.index_ratio), + @intCast(d.rotary), + d.theta, + d.eps, + o.stream, + ); +} + +/// A prompt's rows into a sparse layer's caches only (sparse()'s bytes, no attention): the MTP head's prompt rows. +pub fn sparseKeys(o: Ops, m: *const model.Model, d: model.Dims, s: model.Sparse, g: forward.Seg, layer: usize, x: Tensor, dev_pos: u64) !void { + const rows = g.tokens.len; + var outs: [4]Tensor = undefined; + if (!try o.projectGroup(x, &.{ s.q, s.k, s.v, s.index }, rows, &outs)) { + for (&outs, [_]model.Projection{ s.q, s.k, s.v, s.index }) |*t, p| t.* = try o.project(x, p, rows, false); + } + try writeKeys(o, m, d, s, g, layer, outs[1], outs[2], outs[3], 0, dev_pos); +} /// The rows' ends and complete blocks on the device, and the blocks a window's scores walk (see forward.Staged). pub const Rows = struct { ends: u64, complete: u64, bound: usize }; @@ -197,7 +322,11 @@ pub fn sparse( } const qg, const keys, const values, const idx = outs; const q32 = try o.arena.of(f32, rows * d.heads * hd); - try o.qkRope( + const iq = try o.arena.of(f32, rows * d.index_heads * di); + const graphed = o.window and staged != null; + const prep = prepWrites(graphed, rows, segs.len, segs[0].c.pooled, segs[0].pos, d.index_ratio, m.act); + // at device positions the first segment's prep launch also takes q and the index q (tf_fn_qsa_prep) + if (!prep) try o.qkRope( qg, d.heads * 2 * hd, 2 * hd, @@ -213,10 +342,8 @@ pub fn sparse( null, 0, ); - const iq = try o.arena.of(f32, rows * d.index_heads * di); - try o.qkRope(idx, width, di, s.iq_norm, d.eps, rows, d.index_heads, di, d.rotary, d.theta, dev_pos, iq, null, 0); const att = try o.arena.of(f32, rows * d.heads * hd); - const graphed = o.window and staged != null; + if (!prep) try o.qkRope(idx, width, di, s.iq_norm, d.eps, rows, d.index_heads, di, d.rotary, d.theta, dev_pos, iq, null, 0); var off: usize = 0; for (segs) |g| { const n = g.tokens.len; @@ -224,68 +351,36 @@ pub fn sparse( const cap = g.c.layout.cap; const pos = g.pos; const at_pos = dev_pos + off * 4; - try o.qkRope( - forward.at(keys, off * d.kv_heads * hd), - d.kv_heads * hd, - hd, - s.k_norm, - d.eps, - n, - d.kv_heads, - hd, - d.rotary, - d.theta, - at_pos, - null, - kv.k, - cap, - ); - if (graphed) { - try o.kvWriteAt(forward.at(values, off * d.kv_heads * hd), kv.v, n, d.kv_heads, hd, cap, at_pos); - const raw = try take(o, m.act, n * di); - try o.copyCols(forward.at(idx, off * width), width, d.index_heads * di, raw.ptr, n, di); - try o.kvWriteAt(raw, kv.raw, n, 1, di, cap, at_pos); - try o.l.fn_idx_pool_at( - @ptrFromInt(kv.raw), - @ptrFromInt(kv.pooled), - @ptrFromInt(s.ik_norm), - kind, - @ptrFromInt(at_pos), - @intCast(n), - @intCast(di), - @intCast(d.index_ratio), - @intCast(d.rotary), - d.theta, - d.eps, - o.stream, - ); - } else { - try o.kvWrite(forward.at(values, off * d.kv_heads * hd), kv.v, n, d.kv_heads, hd, cap, pos); - try o.copyCols( - forward.at(idx, off * width), - width, - d.index_heads * di, - kv.raw + pos * di * m.act.size(), - n, - di, - ); - const blocks = (pos + n) / d.index_ratio; - const pooled = g.c.pooled; - if (blocks > pooled) try o.l.fn_idx_pool( - @ptrFromInt(kv.raw), - @ptrFromInt(kv.pooled + pooled * di * m.act.size()), - @ptrFromInt(s.ik_norm), - kind, - @intCast(pooled), - @intCast(blocks - pooled), - @intCast(di), - @intCast(d.index_ratio), - @intCast(d.rotary), - d.theta, - d.eps, - o.stream, - ); - } + if (prep) { + // q and the index q (the first segment's launch), k, v, the raw index key and the pools in one launch + const first = off == 0; + const rope = hip.launches.flashnext.QsaRope; + try o.l.fn_qsa_prep(.{ + .q = if (first) rope{ .src = qg.ptr, .s_row = @intCast(d.heads * 2 * hd), .s_head = @intCast(2 * hd), .heads = @intCast(d.heads), .width = @intCast(hd), .weight = s.q_norm, .wide = q32 } else .{}, + .iq = if (first) rope{ .src = idx.ptr, .s_row = @intCast(width), .s_head = @intCast(di), .heads = @intCast(d.index_heads), .width = @intCast(di), .weight = s.iq_norm, .wide = iq } else .{}, + .k = .{ .src = forward.at(keys, off * d.kv_heads * hd).ptr, .s_row = @intCast(d.kv_heads * hd), .s_head = @intCast(hd), .heads = @intCast(d.kv_heads), .width = @intCast(hd), .weight = s.k_norm, .cache = kv.k }, + .v = forward.at(values, off * d.kv_heads * hd).ptr, + .v_cache = kv.v, + .v_width = @intCast(hd), + .raw = forward.at(idx, off * width).ptr, + .raw_stride = @intCast(width), + .raw_offset = @intCast(d.index_heads * di), + .raw_cache = kv.raw, + .raw_width = @intCast(di), + .pooled = kv.pooled, + .pool_scale = s.ik_norm, + .ratio = @intCast(d.index_ratio), + .pos = dev_pos, + .seg_pos = at_pos, + .rows = @intCast(rows), + .n = @intCast(n), + .total = @intCast(cap), + .kind = kind, + .eps = d.eps, + .rotary = @intCast(d.rotary), + .theta = d.theta, + }, o.stream); + } else try writeKeys(o, m, d, s, g, layer, keys, values, idx, off, at_pos); const r: ?Rows = if (staged) |st| .{ .ends = st.ends + off * 4, .complete = st.complete + off * 4, @@ -313,108 +408,25 @@ pub fn sparse( return o.project(gated, s.o, rows, s.o.partial); } -/// One stream's `rows` rows from `pos` in slices; `graphed`: every row scored and selected over `staged.bound` blocks. -fn attend( - o: Ops, - m: *const model.Model, - d: model.Dims, - kv: cache.SparseView, - cap: usize, - q32: u64, - iq: u64, - att: u64, - rows: usize, - pos: usize, - host: *forward.Host, - staged: ?Rows, - graphed: bool, -) !void { - const hd = d.head_dim; - const di = d.index_dim; - const kind = @backingInt(m.act); - const key_stride = d.index_top * d.index_ratio + d.index_ratio; - var r0: usize = 0; - while (r0 < rows) : (r0 += slice_rows) { - const n = @min(slice_rows, rows - r0); - const mark = o.arena.mark(); - defer o.arena.release(mark); - var complete: [slice_rows]i32 = undefined; - var ends: [slice_rows]i32 = undefined; - var sparse_rows = graphed; - for (0..n) |r| { - ends[r] = @intCast(pos + r0 + r + 1); - complete[r] = @divFloor(ends[r], @as(i32, @intCast(d.index_ratio))); - sparse_rows = sparse_rows or complete[r] > d.index_top; - } - const dev_complete = if (staged) |st| st.complete + r0 * 4 else try host.put( - o, - std.mem.sliceAsBytes(complete[0..n]), - ); - const dev_ends = if (staged) |st| st.ends + r0 * 4 else try host.put(o, std.mem.sliceAsBytes(ends[0..n])); - var ids: ?u64 = null; - var sparse_flags: ?u64 = null; - var count = dev_ends; - if (sparse_rows) { - const nb: usize = if (graphed) staged.?.bound else @intCast(complete[n - 1]); - const scores = try o.arena.of(f32, n * nb); - try o.l.fn_idx_scores( - @ptrFromInt(iq + r0 * d.index_heads * di * 4), - @ptrFromInt(kv.pooled), - @ptrFromInt(dev_complete), - @ptrFromInt(scores), - kind, - @intCast(n), - @intCast(d.index_heads), - @intCast(di), - @intCast(nb), - @intCast(nb), - @intCast(d.index_top), - o.stream, - ); - const list = try o.arena.of(i32, n * key_stride); - const counts = try o.arena.of(i32, n); - const flags = try o.arena.of(i32, n); - try o.l.fn_idx_select( - @ptrFromInt(scores), - @intCast(nb), - @ptrFromInt(dev_complete), - @ptrFromInt(dev_ends), - @ptrFromInt(list), - @intCast(key_stride), - @ptrFromInt(counts), - @ptrFromInt(flags), - @intCast(n), - @intCast(d.index_top), - @intCast(d.index_ratio), - o.stream, - ); - ids = list; - sparse_flags = flags; - count = counts; - } - const po = try o.arena.of(f32, n * d.heads * parts * hd); - const pm = try o.arena.of(f32, n * d.heads * parts * 2); - const scale: f32 = @floatCast(1.0 / std.math.sqrt(@as(f64, @floatFromInt(hd)))); - try o.l.fn_sparse_attention( - @ptrFromInt(q32 + r0 * d.heads * hd * 4), - @ptrFromInt(kv.k), - @ptrFromInt(kv.v), - @backingInt(m.act), - if (ids) |i| @ptrFromInt(i) else null, - @intCast(key_stride), - @ptrFromInt(count), - if (sparse_flags) |f| @ptrFromInt(f) else null, - @ptrFromInt(po), - @ptrFromInt(pm), - @ptrFromInt(att + r0 * d.heads * hd * 4), - @intCast(n), - @intCast(d.heads), - @intCast(d.kv_heads), - @intCast(hd), - @intCast(cap), - scale, - parts, - o.stream, - ); - } +/// Rows from which a call's attention takes the prompt kernel: below, the tile runs in parts for a wider grid. +const prompt_rows = 16; + +/// Whether tf_fn_qsa_prep takes the writes: a graphed window, or one 16-bit segment < prompt_rows with pools current. +pub fn prepWrites(graphed: bool, rows: usize, segs: usize, pooled: usize, pos: usize, ratio: usize, act: model.Kind) bool { + if (graphed) return true; + if (act == .f32 or rows == 0 or rows >= prompt_rows or segs != 1) return false; + return pooled == pos / ratio; +} + +test "QSA writes: a graphed window always takes the prep launch; an eager call only when its pools are all its rows'" { + // graphed: always (its caches are pooled through every window's prep) + try std.testing.expect(prepWrites(true, 8, 1, 0, 4000, 4, .bf16)); + // the MTP head's step: one row, its cache pooled to its first row (pos 4001: 1,000 blocks) + try std.testing.expect(prepWrites(false, 1, 1, 1000, 4001, 4, .bf16)); + try std.testing.expect(prepWrites(false, 1, 1, 1000, 4003, 4, .bf16)); + // a cache behind its row's blocks (writeKeys pools 999 too), a prompt's rows, two segments, fp32 rows: eager + try std.testing.expect(!prepWrites(false, 1, 1, 999, 4001, 4, .bf16)); + try std.testing.expect(!prepWrites(false, 16, 1, 1000, 4001, 4, .bf16)); + try std.testing.expect(!prepWrites(false, 2, 2, 1000, 4001, 4, .bf16)); + try std.testing.expect(!prepWrites(false, 1, 1, 1000, 4001, 4, .f32)); } diff --git a/zig/src/families/flashnext/hip/mixers_attend.zig b/zig/src/families/flashnext/hip/mixers_attend.zig new file mode 100644 index 0000000000..99c7a58412 --- /dev/null +++ b/zig/src/families/flashnext/hip/mixers_attend.zig @@ -0,0 +1,119 @@ +//! Flash Next's sparse attention a stream at a time on a HIP rank: the indexer's scores and picks, then the attention. +const std = @import("std"); +const hip = @import("hip"); +const model = @import("model.zig"); +const cache = @import("cache.zig"); +const forward = @import("forward.zig"); +const Rows = @import("mixers.zig").Rows; + +const Ops = hip.ops.Ops; + +/// Rows of a prompt's attention a slice: the indexer's scores and the attention's parts stay bounded. +const slice_rows = 64; +const parts = 16; + +/// One stream's `rows` rows from `pos` in slices; `graphed`: every row scored and selected over `staged.bound` blocks. +pub fn attend( + o: Ops, + m: *const model.Model, + d: model.Dims, + kv: cache.SparseView, + cap: usize, + q32: u64, + iq: u64, + att: u64, + rows: usize, + pos: usize, + host: *forward.Host, + staged: ?Rows, + graphed: bool, +) !void { + const hd = d.head_dim; + const di = d.index_dim; + const kind = @backingInt(m.act); + const key_stride = d.index_top * d.index_ratio + d.index_ratio; + var r0: usize = 0; + while (r0 < rows) : (r0 += slice_rows) { + const n = @min(slice_rows, rows - r0); + const mark = o.arena.mark(); + defer o.arena.release(mark); + var complete: [slice_rows]i32 = undefined; + var ends: [slice_rows]i32 = undefined; + var sparse_rows = graphed; + for (0..n) |r| { + ends[r] = @intCast(pos + r0 + r + 1); + complete[r] = @divFloor(ends[r], @as(i32, @intCast(d.index_ratio))); + sparse_rows = sparse_rows or complete[r] > d.index_top; + } + const dev_complete = if (staged) |st| st.complete + r0 * 4 else try host.put( + o, + std.mem.sliceAsBytes(complete[0..n]), + ); + const dev_ends = if (staged) |st| st.ends + r0 * 4 else try host.put(o, std.mem.sliceAsBytes(ends[0..n])); + var ids: ?u64 = null; + var sparse_flags: ?u64 = null; + var count = dev_ends; + if (sparse_rows) { + const nb: usize = if (graphed) staged.?.bound else @intCast(complete[n - 1]); + const scores = try o.arena.of(f32, n * nb); + try o.l.fn_idx_scores( + @ptrFromInt(iq + r0 * d.index_heads * di * 4), + @ptrFromInt(kv.pooled), + @ptrFromInt(dev_complete), + @ptrFromInt(scores), + kind, + @intCast(n), + @intCast(d.index_heads), + @intCast(di), + @intCast(nb), + @intCast(nb), + @intCast(d.index_top), + o.stream, + ); + const list = try o.arena.of(i32, n * key_stride); + const counts = try o.arena.of(i32, n); + const flags = try o.arena.of(i32, n); + try o.l.fn_idx_select( + @ptrFromInt(scores), + @intCast(nb), + @ptrFromInt(dev_complete), + @ptrFromInt(dev_ends), + @ptrFromInt(list), + @intCast(key_stride), + @ptrFromInt(counts), + @ptrFromInt(flags), + @intCast(n), + @intCast(d.index_top), + @intCast(d.index_ratio), + o.stream, + ); + ids = list; + sparse_flags = flags; + count = counts; + } + const po = try o.arena.of(f32, n * d.heads * parts * hd); + const pm = try o.arena.of(f32, n * d.heads * parts * 2); + const scale: f32 = @floatCast(1.0 / std.math.sqrt(@as(f64, @floatFromInt(hd)))); + try o.l.fn_sparse_attention( + @ptrFromInt(q32 + r0 * d.heads * hd * 4), + @ptrFromInt(kv.k), + @ptrFromInt(kv.v), + @backingInt(m.act), + if (ids) |i| @ptrFromInt(i) else null, + @intCast(key_stride), + @ptrFromInt(count), + if (sparse_flags) |f| @ptrFromInt(f) else null, + @ptrFromInt(po), + @ptrFromInt(pm), + @ptrFromInt(att + r0 * d.heads * hd * 4), + @intCast(n), + @intCast(d.heads), + @intCast(d.kv_heads), + @intCast(hd), + @intCast(cap), + scale, + parts, + o.stream, + ); + } +} diff --git a/zig/src/families/flashnext/hip/native.zig b/zig/src/families/flashnext/hip/native.zig index 867a5e34a3..4981dfbfb2 100644 --- a/zig/src/families/flashnext/hip/native.zig +++ b/zig/src/families/flashnext/hip/native.zig @@ -18,6 +18,12 @@ pub const formats: []const []const u8 = &.{ "mlx-q3g32", "mlx-q4g32", "mlx-q6g32 pub const default_context: i64 = 32768; /// The engine cuts prompts itself. pub const prefill_step: u32 = 0; +/// Flash Next's HIP prompt chunk where the policy names none; prefill_step=20480 trades about 24 GiB for about 3 %. +pub const policy_prefill_step: u32 = 4096; +/// Drafts a verify window holds at most past its pending token (`--mtp-drafts` above it is refused before the load). +pub const max_drafts: u32 = lanes_mod.max_depth; +/// Flash Next's HIP MTP policy where no flag or mtp_depth key names one: a chain gated to 7 drafts, under 0.9 the last. +pub const policy_mtp: struct { drafts: u8, confidence: f64, depth: hip.policy.MtpDepth } = .{ .drafts = 7, .confidence = 0.9, .depth = .gated }; /// Device bytes a rank keeps for the forward's scratch until the engine counts its own. pub const scratch_bytes: u64 = 2 << 30; @@ -214,6 +220,15 @@ fn lanesOf(gpa: std.mem.Allocator, dev: hip.Device, o: anytype, p: Prepared, str errdefer fx.deinit(); // kept prompt states live in host memory: --prompt-cache-gib, else 16 GiB fx.keepPrompts(@intFromFloat((o.cache_gib orelse 16.0) * (1 << 30))); + // one rank: the depth rule's costs timed now (a group's ranks would have to run the timing rounds together) + if (o.world == 1 and fx.facts().mtp) { + fx.measure() catch |err| std.log.warn("lane costs not timed: {t}", .{err}); + const c = &fx.costs; + var line: [512]u8 = undefined; + var w: std.Io.Writer = .fixed(&line); + for (c.window[0..c.windows]) |x| w.print(" {d}:{d:.2}", .{ x.width, x.ms }) catch {}; + std.log.info("lane costs ms by window rows{s}; head step {d:.3}", .{ w.buffered(), c.step_ms }); + } const startup = try std.fmt.allocPrint( gpa, "HIP {s} device {d}, rank {d} of {d}: Flash Next, {d:.2} GiB on the device, " ++ @@ -277,7 +292,7 @@ pub fn open( }; } -/// Device bytes a stream takes at `cap` positions: its caches, window snapshots, the head's caches and its rows. +/// Device bytes of a stream at `cap` positions: caches, window conv snapshots and DeltaNet inputs, head caches, rows. fn streamBytes(e: *const Engine, cap: usize) usize { var buf: [config.max_layers]bool = undefined; const kinds = e.kinds(&buf) catch return std.math.maxInt(usize); diff --git a/zig/src/families/flashnext/hip/snapshot.zig b/zig/src/families/flashnext/hip/snapshot.zig index 7ca80f10e3..d3d0fbf2b5 100644 --- a/zig/src/families/flashnext/hip/snapshot.zig +++ b/zig/src/families/flashnext/hip/snapshot.zig @@ -94,6 +94,8 @@ pub fn save( ) !*Saved { try s.synchronize(); if (c.len != at) return error.SnapshotNotAtMark; + // a keep that named a snapshot row left the conv tails out of their places: the caller settles first + if (c.pending != null) return error.SnapshotUnsettled; const out = try gpa.create(Saved); errdefer gpa.destroy(out); const main = try copyOut(d, c, at, ratio, gpa); @@ -115,6 +117,8 @@ fn restore( ) !void { try s.synchronize(); if (saved.at + 1 > c.layout.cap) return error.SnapshotTooLong; + // the copy fills the places: a window after it starts from them, not from a snapshot row an earlier keep named + try c.startAt(null, s); try copyIn(d, c, saved.at, ratio, saved.main, gpa); if (head) |h| try copyIn(d, h, saved.at, ratio, saved.head, gpa); c.len = saved.at; diff --git a/zig/src/families/flashnext/hip/state_test.zig b/zig/src/families/flashnext/hip/state_test.zig index 2d907ee485..d9ba72fadc 100644 --- a/zig/src/families/flashnext/hip/state_test.zig +++ b/zig/src/families/flashnext/hip/state_test.zig @@ -34,6 +34,14 @@ const Host = struct { @memset(@as([*]u8, @ptrCast(dst.?))[0..n], @intCast(value)); return 0; } + fn set32(dst: abi.DevicePtr, value: c_int, n: usize, _: abi.Stream) callconv(.c) abi.Result { + @memset(@as([*]c_int, @ptrCast(@alignCast(dst.?)))[0..n], value); + return 0; + } + fn dtod(dst: abi.DevicePtr, src: abi.DevicePtr, n: usize, _: abi.Stream) callconv(.c) abi.Result { + @memcpy(@as([*]u8, @ptrCast(dst.?))[0..n], @as([*]const u8, @ptrCast(src.?))[0..n]); + return 0; + } fn sync(_: abi.Stream) callconv(.c) abi.Result { return @intFromBool(fail_sync); } @@ -52,6 +60,8 @@ const Host = struct { r.api.hipMemcpyHtoD = htod; r.api.hipMemcpyDtoH = dtoh; r.api.hipMemset = set; + r.api.hipMemsetD32Async = set32; + r.api.hipMemcpyDtoDAsync = dtod; r.api.hipStreamSynchronize = sync; r.api.hipMalloc = malloc; r.api.hipFree = free; @@ -131,9 +141,12 @@ const Saved = struct { } }; -/// Caches are a new stream's: every byte zero, no positions, eos before any row. +/// Caches are a new stream's: every byte zero, no positions, eos before any row, the start word -1 (no snapshot row). fn expectFresh(c: *const cache.Caches) !void { for (bytes(c)) |b| try std.testing.expectEqual(@as(u8, 0), b); + const word = @as([*]const u8, @ptrCast(c.window.ptr.?))[c.layout.windowBytes()..][0..4]; + try std.testing.expectEqualSlices(u8, &.{ 0xff, 0xff, 0xff, 0xff }, word); + try std.testing.expectEqual(@as(?usize, null), c.pending); try std.testing.expectEqual(@as(usize, 0), c.len); try std.testing.expectEqual(@as(usize, 0), c.pooled); try std.testing.expectEqual([2]i64{ eos, eos }, c.history); @@ -196,6 +209,45 @@ test "a lone rank's restore that fails at any copy or allocation leaves fresh ca try std.testing.expect(k > 1); } +test "a state saved without the head (a stream that cannot draft) never resumes a drafting stream; the head's goes unread" { + var r = Host.runtime(); + const s: hip.Stream = .{ .r = &r, .handle = null }; + // saved by a lane without head caches: no head bytes + var main = try caches(&r); + defer main.deinit(std.testing.allocator); + for (bytes(&main), 0..) |*b, i| b.* = @truncate(i *% 7 +% 9); + main.len = at; + main.pooled = at / ratio; + main.history = .{ 5, 6 }; + const bare = try snapshot.save(std.testing.allocator, &r, s, &main, null, at, ratio); + defer snapshot.drop(std.testing.allocator, bare); + try std.testing.expectEqual(@as(usize, 0), bare.head.len); + { + // a drafting lane: its head would have no state for the prompt, so the restore is refused and both start over + var to = try caches(&r); + defer to.deinit(std.testing.allocator); + var head = try caches(&r); + defer head.deinit(std.testing.allocator); + try std.testing.expectError(error.RestoreRefused, snapshot.restoreAgreed(std.testing.allocator, &r, s, bare, &to, &head, ratio, eos, null)); + try expectFresh(&to); + try expectFresh(&head); + } + { + // a lane without a head resumes it + var to = try caches(&r); + defer to.deinit(std.testing.allocator); + try snapshot.restoreAgreed(std.testing.allocator, &r, s, bare, &to, null, ratio, eos, null); + try expectRestored(&to, &main); + } + // a state saved with the head resumes a lane without one: its main state alone + var src = try Saved.init(&r, 4); + defer src.deinit(); + var to = try caches(&r); + defer to.deinit(std.testing.allocator); + try snapshot.restoreAgreed(std.testing.allocator, &r, s, src.copy, &to, null, ratio, eos, null); + try expectRestored(&to, &src.main); +} + test "a lone rank whose caches cannot be made fresh after a failed restore stops" { var r = Host.runtime(); const s: hip.Stream = .{ .r = &r, .handle = null }; @@ -340,3 +392,66 @@ test "a round's graph is chosen for the pool's caches only: caches made elsewher try std.testing.expectEqual(engine.Pick.capture, try e.choose(&.{.{ .c = &c, .tokens = &step, .pos = 0 }})); e.pool.unlease(c); } + +/// The device word at `start()`: the snapshot row a window's conv tails start from, -1 for their places. +fn startWord(c: *const cache.Caches) i32 { + return std.mem.readInt(i32, @as([*]const u8, @ptrCast(c.window.ptr.?))[c.layout.windowBytes()..][0..4], .little); +} + +test "a keep that names a snapshot row: a save refuses until the conv tails settle, then saves the row's tails" { + var r = Host.runtime(); + const s: hip.Stream = .{ .r = &r, .handle = null }; + var c = try caches(&r); + defer c.deinit(std.testing.allocator); + c.len = at; + c.pooled = at / ratio; + // a window of four rows kept two: its conv tails wait in snapshot row 1, the word names it + const linear = 1; + const row = 1; + const snap: [*]u8 = @ptrFromInt(c.snapshot(linear, row)); + for (snap[0..c.layout.conv_bytes], 0..) |*b, i| b.* = @truncate(i *% 3 +% 1); + try c.startAt(row, s); + try std.testing.expectEqual(@as(i32, row), startWord(&c)); + try std.testing.expectError(error.SnapshotUnsettled, snapshot.save(std.testing.allocator, &r, s, &c, null, at, ratio)); + try c.settle(s); + try std.testing.expectEqual(@as(?usize, null), c.pending); + try std.testing.expectEqual(@as(i32, -1), startWord(&c)); + const conv: [*]const u8 = @ptrFromInt(c.linearAt(linear).conv); + try std.testing.expectEqualSlices(u8, snap[0..c.layout.conv_bytes], conv[0..c.layout.conv_bytes]); + const copy = try snapshot.save(std.testing.allocator, &r, s, &c, null, at, ratio); + snapshot.drop(std.testing.allocator, copy); +} + +test "a restore over caches whose last keep named a snapshot row resumes from the copy's own places" { + var r = Host.runtime(); + const s: hip.Stream = .{ .r = &r, .handle = null }; + var src = try Saved.init(&r, 11); + defer src.deinit(); + var c = try caches(&r); + defer c.deinit(std.testing.allocator); + try c.startAt(3, s); + try snapshot.restoreAgreed(std.testing.allocator, &r, s, src.copy, &c, null, ratio, eos, null); + try expectRestored(&c, &src.main); + try std.testing.expectEqual(@as(?usize, null), c.pending); + try std.testing.expectEqual(@as(i32, -1), startWord(&c)); +} + +test "a stream cancelled or ended inside a window: its slot leased again starts fresh, no snapshot row named" { + var r = Host.runtime(); + const s: hip.Stream = .{ .r = &r, .handle = null }; + var pool: cache.Pool = .{}; + defer pool.deinit(std.testing.allocator); + var maker: Maker = .{ .r = &r }; + for ([_]?usize{ null, 0, 6 }) |row| { + var c = try pool.lease(std.testing.allocator, 0, s, eos, cap, &maker); + for (bytes(&c), 0..) |*b, i| b.* = @truncate(i *% 13 +% 5); + c.len = 17; + // the window's last keep (kept all, one, or seven of eight rows), then the stream goes + try c.startAt(row, s); + pool.unlease(c); + c = try pool.lease(std.testing.allocator, 0, s, eos, cap, &maker); + try expectFresh(&c); + pool.unlease(c); + } + try std.testing.expectEqual(@as(usize, 1), maker.made); +} diff --git a/zig/src/families/flashnext/hip/tables.zig b/zig/src/families/flashnext/hip/tables.zig index 1bf51c0c4e..bb58728a82 100644 --- a/zig/src/families/flashnext/hip/tables.zig +++ b/zig/src/families/flashnext/hip/tables.zig @@ -71,6 +71,41 @@ pub const Tables = struct { }; } + /// The rows copied once into anonymous memory from `a` (hip.Policy.rows): a round's gather then never faults. + pub fn keepResident(t: *Tables, a: std.mem.Allocator, ck: *const core.checkpoint.Checkpoint) !void { + for (t.shards) |*s| { + inline for (.{ "words", "scales", "biases" }) |f| { + const from = @field(s, f); + advise(from, std.os.linux.MADV.SEQUENTIAL); + const copy = try a.alloc(u8, from.len); + @memcpy(copy, from); + advise(from, std.os.linux.MADV.DONTNEED); + dropCached(ck, from); + @field(s, f) = copy; + } + } + } + + fn advise(b: []const u8, advice: u32) void { + if (@import("builtin").os.tag != .linux) return; + const page = std.heap.pageSize(); + const from = std.mem.alignBackward(usize, @intFromPtr(b.ptr), page); + const to = std.mem.alignForward(usize, @intFromPtr(b.ptr) + b.len, page); + _ = std.os.linux.madvise(@ptrFromInt(from), to - from, advice); + } + + /// The page cache's copy of `b`'s file range dropped (safetensors.File.release does it for a whole file). + fn dropCached(ck: *const core.checkpoint.Checkpoint, b: []const u8) void { + if (@import("builtin").os.tag != .linux) return; + for (ck.files.items) |*f| { + const m = f.map.memory; + if (@intFromPtr(b.ptr) < @intFromPtr(m.ptr) or @intFromPtr(b.ptr) + b.len > @intFromPtr(m.ptr) + m.len) continue; + const off = @intFromPtr(b.ptr) - @intFromPtr(m.ptr); + _ = std.os.linux.fadvise(f.file.handle, @intCast(off), @intCast(b.len), std.os.linux.POSIX_FADV.DONTNEED); + return; + } + } + /// Each id's packed words, scales and biases copied into the three staging slices, in id order. pub fn gather(t: *const Tables, ids: []const u32, words: []u8, scales: []u8, biases: []u8) !void { const wb = t.wordBytes(); diff --git a/zig/src/families/flashnext/hip/worker.zig b/zig/src/families/flashnext/hip/worker.zig index f7721eacec..ce74d624dd 100644 --- a/zig/src/families/flashnext/hip/worker.zig +++ b/zig/src/families/flashnext/hip/worker.zig @@ -85,6 +85,7 @@ pub fn follow(gpa: std.mem.Allocator, e: *Engine, link: hip.collective.Link) !vo .snap => { const lane = lanes.get(w[1]) orelse return error.UnknownStream; // a copy this rank cannot keep is a restore it refuses later, which every rank then hears + lane.caches.settle(e.stream) catch continue; const x = snapshot.save(gpa, &e.driver, e.stream, &lane.caches, null, w[3], ratio) catch continue; saved.put(gpa, w[2], x) catch snapshot.drop(gpa, x); }, diff --git a/zig/src/families/qwen3_5/backend/hip/forward/forward.zig b/zig/src/families/qwen3_5/backend/hip/forward/forward.zig index 9926861d78..c7edf6bca3 100644 --- a/zig/src/families/qwen3_5/backend/hip/forward/forward.zig +++ b/zig/src/families/qwen3_5/backend/hip/forward/forward.zig @@ -134,7 +134,7 @@ fn linear(o: Ops, m: *const view.Model, l: view.Linear, caches: *state.Caches, i const beta = try o.arena.of(f32, rows * s.value_heads); try o.gdnGatePrefill(a, b, l.a_log, l.dt_bias, gate, beta, rows, s.value_heads); const y = try o.arena.of(f32, rows * s.valueWidth()); - try o.gatedDelta(q, k, v, gate, beta, cache.state.base(), y, rows, s.key_heads, s.value_heads, s.key_dim, s.value_dim, null); + try o.gatedDelta(q, k, v, gate, beta, cache.state.base(), y, rows, s.key_heads, s.value_heads, s.key_dim, s.value_dim, null, 0); return gatedOut(o, m, l, y, z, rows); } diff --git a/zig/src/hip/kernel_tests/chain.zig b/zig/src/hip/kernel_tests/chain.zig index 1d93126038..8043f69f48 100644 --- a/zig/src/hip/kernel_tests/chain.zig +++ b/zig/src/hip/kernel_tests/chain.zig @@ -168,6 +168,87 @@ fn conv(t: *Rig, rng: *rig.Rng, rows: usize) !void { if (rows > 1) try same(bufs[0][3], bufs[1][3]); } +/// A prompt's conv chain against tf_gdn_prompt_prep: q, k, v, gate, beta and conv state, byte for byte. +fn promptPrep(t: *Rig, rng: *rig.Rng, rows: usize, with_state: bool) !void { + const kw: usize = 2048; + const vw: usize = 6144; + const ch = 2 * kw + vw; + const kernel: usize = 4; + const eps: f32 = 1e-6; + const vheads: usize = 48; + const hx = try gpa.alloc(u16, rows * ch); + defer gpa.free(hx); + for (hx) |*v| v.* = t.bits(rng.unit() * 2.0); + const hw = try gpa.alloc(f32, ch * kernel); + defer gpa.free(hw); + for (hw) |*v| v.* = rng.unit() / 2.0; + const hs = try gpa.alloc(f32, (kernel - 1) * ch); + defer gpa.free(hs); + for (hs) |*v| v.* = rng.unit(); + const hn = try gpa.alloc(f32, 128 * 2); + defer gpa.free(hn); + for (hn) |*v| v.* = 1.0 + rng.unit() / 4.0; + const ha = try gpa.alloc(u16, rows * vheads); + defer gpa.free(ha); + for (ha) |*v| v.* = t.bits(rng.unit() * 3.0); + const hb = try gpa.alloc(u16, rows * vheads); + defer gpa.free(hb); + for (hb) |*v| v.* = t.bits(rng.unit() * 3.0); + const hlog = try gpa.alloc(f32, vheads * 2); + defer gpa.free(hlog); + for (hlog) |*v| v.* = rng.unit(); + var x = try t.upload(hx); + defer x.free(); + var weight = try t.upload(hw); + defer weight.free(); + var state = try t.upload(hs); + defer state.free(); + var norm = try t.upload(hn); + defer norm.free(); + var dev_a = try t.upload(ha); + defer dev_a.free(); + var dev_b = try t.upload(hb); + defer dev_b.free(); + var dev_log = try t.upload(hlog); + defer dev_log.free(); + var mixed = try t.alloc(rows * ch * 4); + defer mixed.free(); + var qc = try t.alloc(rows * kw * 4); + defer qc.free(); + var kc = try t.alloc(rows * kw * 4); + defer kc.free(); + var bufs: [2][6]DeviceBuffer = undefined; // q, k, v, gate, beta, new state + for (0..2) |v| bufs[v] = .{ try t.alloc(rows * kw * 4), try t.alloc(rows * kw * 4), try t.alloc(rows * vw * 4), try t.alloc(rows * vheads * 4), try t.alloc(rows * vheads * 4), try t.alloc((kernel - 1) * ch * 4) }; + defer for (&bufs) |*set| for (set) |*b| b.free(); + const s = t.stream.handle; + const l = &t.on; + const kind = t.kind(); + const st: ?*anyopaque = if (with_state) ptr(at(state)) else null; + { + const b = bufs[0]; + try l.tf_conv_prefill(ptr(at(x)), kind, @ptrFromInt(at(weight)), @ptrCast(@alignCast(st)), @ptrFromInt(at(mixed)), @ptrFromInt(at(b[5])), @intCast(rows), @intCast(ch), @intCast(kernel), s); + try l.tf_copy_cols(ptr(at(mixed)), @intCast(ch), 0, ptr(at(qc)), 0, @intCast(rows), @intCast(kw), s); + try l.tf_copy_cols(ptr(at(mixed)), @intCast(ch), @intCast(kw), ptr(at(kc)), 0, @intCast(rows), @intCast(kw), s); + try l.tf_copy_cols(ptr(at(mixed)), @intCast(ch), @intCast(2 * kw), ptr(at(b[2])), 0, @intCast(rows), @intCast(vw), s); + try l.tf_rms(ptr(at(qc)), @ptrFromInt(at(norm)), ptr(at(b[0])), 0, @intCast(rows * (kw / 128)), 128, eps, s); + try l.tf_rms(ptr(at(kc)), @ptrFromInt(at(norm) + 512), ptr(at(b[1])), 0, @intCast(rows * (kw / 128)), 128, eps, s); + try l.tf_gdn_gate_prefill(ptr(at(dev_a)), ptr(at(dev_b)), kind, @ptrFromInt(at(dev_log)), @ptrFromInt(at(dev_log) + vheads * 4), @ptrFromInt(at(b[3])), @ptrFromInt(at(b[4])), @intCast(rows), @intCast(vheads), s); + } + { + const b = bufs[1]; + try l.tf_gdn_prompt_prep(ptr(at(x)), kind, @ptrFromInt(at(weight)), @ptrCast(@alignCast(st)), @ptrFromInt(at(b[5])), @ptrFromInt(at(b[0])), @ptrFromInt(at(b[1])), @ptrFromInt(at(b[2])), @ptrFromInt(at(norm)), @ptrFromInt(at(norm) + 512), eps, @intCast(rows), @intCast(kw), @intCast(vw), @intCast(kernel), ptr(at(dev_a)), ptr(at(dev_b)), @ptrFromInt(at(dev_log)), @ptrFromInt(at(dev_log) + vheads * 4), @ptrFromInt(at(b[3])), @ptrFromInt(at(b[4])), @intCast(vheads), s); + } + try t.stream.synchronize(); + for (0..6) |i| try same(bufs[0][i], bufs[1][i]); +} + +test "the prompt's merged conv, split, norms and gates write the chain's q, k, v, gate, beta and conv state" { + const t = try Rig.open(1 << 20); + defer t.close(); + var rng: rig.Rng = .{ .state = 0x6D3 }; + for ([_]usize{ 1, 15, 16, 40, 300 }) |rows| for ([_]bool{ true, false }) |with_state| try promptPrep(t, &rng, rows, with_state); +} + /// The linear attention's gated norm: rms then gnorm_silu against one launch; the sigmoid gate against the host's too. fn gnorm(t: *Rig, rng: *rig.Rng, rows: usize, sigmoid: c_int) !void { const n = rows * 32 * 128; diff --git a/zig/src/hip/kernel_tests/decode.zig b/zig/src/hip/kernel_tests/decode.zig index 5c85b799ca..fdebe2de10 100644 --- a/zig/src/hip/kernel_tests/decode.zig +++ b/zig/src/hip/kernel_tests/decode.zig @@ -6,7 +6,7 @@ const gpa = rig.gpa; const at = rig.at; const Launcher = @import("../launches.zig").Launcher; -fn p(b: anytype) ?*anyopaque { +pub fn p(b: anytype) ?*anyopaque { return @ptrFromInt(at(b)); } @@ -138,7 +138,7 @@ const affine = @import("../launches/affine.zig"); const ref = @import("affine/reference.zig"); /// A random packed product on the host and the device: (n, k) at `bits` and `group`, bf16 tables, `experts` stacked. -const Matrix = struct { +pub const Matrix = struct { n: usize, k: usize, bits: usize, @@ -148,7 +148,7 @@ const Matrix = struct { bias: []u16, dev: [3]@import("../memory.zig").DeviceBuffer, - fn init(t: *Rig, rng: *rig.Rng, n: usize, k: usize, bits: usize, group_size: usize, experts: usize) !Matrix { + pub fn init(t: *Rig, rng: *rig.Rng, n: usize, k: usize, bits: usize, group_size: usize, experts: usize) !Matrix { var m: Matrix = .{ .n = n, .k = k, .bits = bits, .group = group_size, .words = undefined, .scale = undefined, .bias = undefined, .dev = undefined }; m.words = try gpa.alloc(u32, experts * n * k * bits / 32); m.scale = try gpa.alloc(u16, experts * n * k / group_size); @@ -160,18 +160,18 @@ const Matrix = struct { return m; } - fn deinit(m: *Matrix) void { + pub fn deinit(m: *Matrix) void { gpa.free(m.words); gpa.free(m.scale); gpa.free(m.bias); for (&m.dev) |*b| b.free(); } - fn problem(m: Matrix, t: *const Rig, x: []const u16) ref.Problem { + pub fn problem(m: Matrix, t: *const Rig, x: []const u16) ref.Problem { return .{ .fp16 = !t.bf16, .n = m.n, .k = m.k, .bits = m.bits, .group = m.group, .x = x, .words = m.words, .scale = m.scale, .bias = m.bias }; } - fn arg(m: Matrix, t: *const Rig, x: u64, rows: usize, out: u64) affine.Arg { + pub fn arg(m: Matrix, t: *const Rig, x: u64, rows: usize, out: u64) affine.Arg { return .{ .x = x, .words = at(m.dev[0]), @@ -301,3 +301,8 @@ test "the routed gate and up with its activation in one launch is no further fro try pair(t, &rng, 1, 768, 2048, 6, 64); try pair(t, &rng, 1, 512, 2048, 4, 128); } + +test { + _ = @import("decode_route.zig"); + _ = @import("decode_products.zig"); +} diff --git a/zig/src/hip/kernel_tests/decode_products.zig b/zig/src/hip/kernel_tests/decode_products.zig new file mode 100644 index 0000000000..2a2b78cc4e --- /dev/null +++ b/zig/src/hip/kernel_tests/decode_products.zig @@ -0,0 +1,319 @@ +//! Routed, plain and prompt products against the launcher's pick and the matrix tile: the same bytes. +const std = @import("std"); +const rig = @import("rig.zig"); +const Rig = rig.Rig; +const gpa = rig.gpa; +const at = rig.at; +const affine = @import("../launches/affine.zig"); +const ref = @import("affine/reference.zig"); +const Matrix = @import("decode.zig").Matrix; + +/// A verify window's routed gate+up or down at every columns-a-lane count, and as single-pair items: the same bytes. +fn windowBytes(t: *Rig, rng: *rig.Rng, down: bool, rows: usize, unique_in: ?usize) !void { + const n: usize = if (down) 2560 else 2 * 640; + const k: usize = if (down) 640 else 2560; + const experts = 64; + const slots = 11; + var m = try Matrix.init(t, rng, n, k, 4, 32, experts); + defer m.deinit(); + const kernels = &t.on.affine; + defer kernels.stream_cb_force = 0; + const pairs = rows * slots; + const unique = unique_in orelse slots + (slots * (rows - 1)) / 2; + const x_rows = if (down) pairs else rows; + const hx = try gpa.alloc(u16, x_rows * k); + defer gpa.free(hx); + for (hx) |*v| v.* = t.bits(rng.unit()); + var x = try t.upload(hx); + defer x.free(); + const dead = 9; + const items = try gpa.alloc(i32, (unique + dead) * 3); + defer gpa.free(items); + const members = try gpa.alloc(i32, pairs); + defer gpa.free(members); + // the same pairs, every one its own item (members in the same order), then the dead items + const single = try gpa.alloc(i32, (pairs + dead) * 3); + defer gpa.free(single); + var first: usize = 0; + var most: usize = 0; + for (0..unique) |i| { + var count: usize = 0; + var j = i; + while (j < pairs) : (j += unique) { + members[first + count] = @intCast(j); + single[3 * (first + count) ..][0..3].* = .{ @intCast((i * 7) % experts), @intCast(first + count), 1 }; + count += 1; + } + items[3 * i ..][0..3].* = .{ @intCast((i * 7) % experts), @intCast(first), @intCast(count) }; + first += count; + most = @max(most, count); + } + for (0..dead) |d| { + items[3 * (unique + d) ..][0..3].* = .{ experts - 1, @intCast(pairs), 0 }; + single[3 * (pairs + d) ..][0..3].* = .{ experts - 1, @intCast(pairs), 0 }; + } + var dev_items = try t.upload(items); + defer dev_items.free(); + var dev_single = try t.upload(single); + defer dev_single.free(); + var dev_members = try t.upload(members); + defer dev_members.free(); + const out_bytes = if (down) pairs * n * 4 else pairs * (n / 2) * 2; + var want: ?[]u8 = null; + defer if (want) |w| gpa.free(w); + // each CB on the grouped plan, the rule's CB on single items (a.m 1), the grouped plan at a.m = rows as the engine + for ([_]c_int{ 0, 1, 2, 4, 8, -1, -2 }) |cb| { + var out = try t.alloc(out_bytes); + defer out.free(); + const split = cb == -1; + var a = m.arg(t, at(x), if (split) 1 else if (cb == -2) rows else most, if (down) at(out) else 0); + if (!down) a.out16 = at(out); + a.route = .{ .items = at(if (split) dev_single else dev_items), .members = at(dev_members), .x_div = if (down) 1 else slots }; + const n_items: c_int = @intCast(if (split) pairs + dead else unique + dead); + kernels.stream_cb_force = @max(cb, 0); + if (down) try kernels.routed(&t.r, a, n_items, t.stream.handle) else try std.testing.expect(try kernels.pairRun(&t.r, a, 0, n_items, t.stream.handle)); + try t.stream.synchronize(); + const got = try rig.download(u8, out); + if (want) |w| { + defer gpa.free(got); + try std.testing.expectEqualSlices(u8, w, got); + } else want = got; + } +} + +test "the routed gate+up and down write the same bytes at every columns a lane and as single-pair items (Flash Next, 1 to 8 rows)" { + const t = try Rig.open(1 << 20); + defer t.close(); + var rng: rig.Rng = .{ .state = 0x9E3779B97F4A7C15 }; + for ([_]bool{ false, true }) |down| { + for ([_]usize{ 1, 2, 4, 5, 8 }) |rows| try windowBytes(t, &rng, down, rows, null); + // 4 rows an expert: the 4-row tile + try windowBytes(t, &rng, down, 4, 11); + try windowBytes(t, &rng, down, 8, 22); + } +} + +/// A plain product (one matrix, fp32 out) at every columns-a-lane count against the launcher's pick: the same bytes. +fn plainBytes(t: *Rig, rng: *rig.Rng, n: usize, k: usize, rows: usize) !void { + var m = try Matrix.init(t, rng, n, k, 4, 32, 1); + defer m.deinit(); + const kernels = &t.on.affine; + defer kernels.stream_cb_force = 0; + const hx = try gpa.alloc(u16, rows * k); + defer gpa.free(hx); + for (hx) |*v| v.* = t.bits(rng.unit()); + var x = try t.upload(hx); + defer x.free(); + var want: ?[]u8 = null; + defer if (want) |w| gpa.free(w); + for ([_]c_int{ 0, 1, 2, 4, 8 }) |cb| { + var out = try t.alloc(rows * n * 4); + defer out.free(); + const a = m.arg(t, at(x), rows, at(out)); + kernels.stream_cb_force = cb; + try kernels.streamGo(&t.r, a, .{}, a.n, 1, t.stream.handle); + try t.stream.synchronize(); + const got = try rig.download(u8, out); + if (want) |w| { + defer gpa.free(got); + try std.testing.expectEqualSlices(u8, w, got); + } else want = got; + } +} + +test "a plain product writes the same bytes at every columns a lane (Flash Next's in-proj K, out-proj, a ragged N; 1 to 4 rows)" { + const t = try Rig.open(1 << 20); + defer t.close(); + var rng: rig.Rng = .{ .state = 0x9E3779B97F4A7C15 }; + for ([_]usize{ 1, 2, 4 }) |rows| { + try plainBytes(t, &rng, 4096, 2560, rows); + try plainBytes(t, &rng, 2560, 6144, rows); + try plainBytes(t, &rng, 4099, 2560, rows); + } +} + +/// Flash Next's prompt expert tiles against the 128-row matrix tile: the same bytes. +fn promptExperts(t: *Rig, rng: *rig.Rng, down: bool, rows: usize, experts: usize, skew: bool, limit: f32) !void { + const kernels = &t.on.affine; + const sh = if (down) affine.Kernels.moe_down_shape else affine.Kernels.moe_gu_shape; + const n: usize = @intCast(sh.n); + const k: usize = @intCast(sh.k); + const slots = 11; + const pairs = rows * slots; + const width = if (down) n else n / 2; + var m = try Matrix.init(t, rng, n, k, @intCast(sh.bits), @intCast(sh.group), experts); + defer m.deinit(); + const x_rows = if (down) pairs else rows; + const hx = try gpa.alloc(u16, x_rows * k); + defer gpa.free(hx); + for (hx) |*v| v.* = t.bits(rng.unit()); + var x = try t.upload(hx); + defer x.free(); + // each pair draws an expert; sorted by expert (stable) into items of at most 128 pairs, as moe_route plans a prompt + const pick = try gpa.alloc(u32, pairs); + defer gpa.free(pick); + for (pick) |*e| { + const r = rng.next(); + e.* = @intCast(if (skew and r % 4 != 0) r % 3 else r % experts); + } + const members = try gpa.alloc(i32, pairs); + defer gpa.free(members); + var n_members: usize = 0; + const items = try gpa.alloc(i32, 3 * (pairs + experts + 8)); + defer gpa.free(items); + @memset(items, 0); + var n_items: usize = 0; + for (0..experts) |e| { + var run: usize = 0; + for (0..pairs) |pi| { + if (pick[pi] != e) continue; + if (run == 0) { + items[3 * n_items ..][0..3].* = .{ @intCast(e), @intCast(n_members), 0 }; + n_items += 1; + } + members[n_members] = @intCast(pi); + n_members += 1; + items[3 * (n_items - 1) + 2] += 1; + run = if (run + 1 == 128) 0 else run + 1; + } + } + // a plan's capacity holds empty items past the used ones + const count = n_items + 8; + var dev_items = try t.upload(items[0 .. 3 * count]); + defer dev_items.free(); + var dev_members = try t.upload(members); + defer dev_members.free(); + var sums = [2]@import("../memory.zig").DeviceBuffer{ try t.alloc(pairs * n * 4), try t.alloc(pairs * n * 4) }; + defer for (&sums) |*b| b.free(); + var acts: [2]@import("../memory.zig").DeviceBuffer = .{ try t.alloc(pairs * width * 2), try t.alloc(pairs * width * 2) }; + defer for (&acts) |*b| b.free(); + try sums[1].fill8(0xA5); + var a = m.arg(t, at(x), 128, at(sums[0])); + a.route = .{ .items = at(dev_items), .members = at(dev_members), .x_div = if (down) 1 else slots }; + try kernels.blockGo(&t.r, a, t.stream.handle, @intCast(count), .matrix); + if (down) { + a.out = at(sums[1]); + try std.testing.expect(try kernels.moeDown(&t.r, a, @intCast(count), t.stream.handle)); + } else { + try t.off.tf_moe_act(@ptrFromInt(at(sums[0])), @ptrFromInt(at(acts[0])), t.kind(), @intCast(pairs), @intCast(width), limit, t.stream.handle); + a.out = 0; + a.out16 = at(acts[1]); + try std.testing.expect(try kernels.moeGateUp(&t.r, a, @intCast(count), limit, t.stream.handle)); + } + try t.stream.synchronize(); + const cmp = if (down) sums else acts; + const want = try rig.download(u8, cmp[0]); + defer gpa.free(want); + const got = try rig.download(u8, cmp[1]); + defer gpa.free(got); + const size: usize = if (down) 4 else 2; + var differ: usize = 0; + for (0..want.len / size) |e| if (!std.mem.eql(u8, want[e * size ..][0..size], got[e * size ..][0..size])) { + if (differ < 4) std.debug.print(" prompt experts down {} rows {d} skew {}: pair {d} column {d} differs\n", .{ down, rows, skew, e / width, e % width }); + differ += 1; + }; + try std.testing.expectEqual(@as(usize, 0), differ); + // and the matrix tile's sums are float64's within its bound + const prob = m.problem(t, hx); + const ref_sums = try rig.download(f32, sums[0]); + defer gpa.free(ref_sums); + for (0..8) |s| { + const pi = s * (pairs - 1) / 7; + const col = (s * 97) % width; + const r = ref.reference(prob, if (down) pi else pi / slots, pick[pi], col); + try std.testing.expect(@abs(@as(f64, ref_sums[pi * n + col]) - r.y) <= 1e-5 * r.norm + 1e-7); + } +} + +test "Flash Next's prompt gate and up with its activation in one launch writes the bytes of the matrix tile and moe_act" { + const t = try Rig.open(1 << 20); + defer t.close(); + if (t.on.affine.moe_gu == null) return error.SkipZigTest; + var rng: rig.Rng = .{ .state = 0x9E3779B97F4A7C15 }; + try promptExperts(t, &rng, false, 300, 24, false, 0); + try promptExperts(t, &rng, false, 2048, 24, true, 0); + try promptExperts(t, &rng, false, 64, 24, false, 0); + try promptExperts(t, &rng, false, 512, 24, false, 7.0); +} + +test "Flash Next's prompt expert down writes the bytes of the matrix tile" { + const t = try Rig.open(1 << 20); + defer t.close(); + if (t.on.affine.moe_down == null) return error.SkipZigTest; + var rng: rig.Rng = .{ .state = 0x2545F4914F6CDD1D }; + try promptExperts(t, &rng, true, 300, 24, false, 0); + try promptExperts(t, &rng, true, 2048, 24, true, 0); + try promptExperts(t, &rng, true, 64, 24, false, 0); +} + +/// A prompt's product on its K's dense tile against the matrix tile: the same fp32 bytes, and tf_cast's bf16 bytes. +fn promptDense(t: *Rig, rng: *rig.Rng, rows: usize, n: usize, k: usize) !void { + const kernels = &t.on.affine; + var m = try Matrix.init(t, rng, n, k, 4, 32, 1); + defer m.deinit(); + const hx = try gpa.alloc(u16, rows * k); + defer gpa.free(hx); + for (hx) |*v| v.* = t.bits(rng.unit()); + var x = try t.upload(hx); + defer x.free(); + var outs = [2]@import("../memory.zig").DeviceBuffer{ try t.alloc(rows * n * 4), try t.alloc(rows * n * 4) }; + defer for (&outs) |*b| b.free(); + try outs[1].fill8(0xA5); + var a = m.arg(t, at(x), rows, at(outs[0])); + try kernels.blockGo(&t.r, a, t.stream.handle, 1, .matrix); + a.out = at(outs[1]); + const e = kernels.choose(.project, .prefill, affine.Kernels.shapeOf(a, 1)) orelse return error.TestUnexpectedResult; + try std.testing.expectEqualStrings("mlx.project.prefill.dense", e.id); + try kernels.prefillLaunch(&t.r, a, t.stream.handle, 1, 0); + try t.stream.synchronize(); + const want = try rig.download(u8, outs[0]); + defer gpa.free(want); + const got = try rig.download(u8, outs[1]); + defer gpa.free(got); + var differ: usize = 0; + for (0..want.len / 4) |i| if (!std.mem.eql(u8, want[i * 4 ..][0..4], got[i * 4 ..][0..4])) { + if (differ < 4) std.debug.print(" prompt dense {d}x{d} rows {d}: row {d} column {d} differs\n", .{ n, k, rows, i / n, i % n }); + differ += 1; + }; + try std.testing.expectEqual(@as(usize, 0), differ); + // the BF16 output: the cast of the fp32 sums + var halves = [2]@import("../memory.zig").DeviceBuffer{ try t.alloc(rows * n * 2), try t.alloc(rows * n * 2) }; + defer for (&halves) |*b| b.free(); + try halves[1].fill8(0xA5); + try t.on.tf_cast(@ptrFromInt(at(outs[0])), 0, @ptrFromInt(at(halves[0])), t.kind(), @intCast(rows * n), t.stream.handle); + a.out = 0; + a.out16 = at(halves[1]); + try kernels.prefillLaunch(&t.r, a, t.stream.handle, 1, 0); + try t.stream.synchronize(); + const want16 = try rig.download(u8, halves[0]); + defer gpa.free(want16); + const got16 = try rig.download(u8, halves[1]); + defer gpa.free(got16); + for (0..want16.len / 2) |i| if (!std.mem.eql(u8, want16[i * 2 ..][0..2], got16[i * 2 ..][0..2])) { + if (differ < 4) std.debug.print(" prompt dense bf16 {d}x{d} rows {d}: row {d} column {d} differs\n", .{ n, k, rows, i / n, i % n }); + differ += 1; + }; + try std.testing.expectEqual(@as(usize, 0), differ); + const prob = m.problem(t, hx); + const sums = try rig.download(f32, outs[1]); + defer gpa.free(sums); + for (0..8) |s| { + const r = s * (rows - 1) / 7; + const col = (s * 97) % n; + const y = ref.reference(prob, r, 0, col); + try std.testing.expect(@abs(@as(f64, sums[r * n + col]) - y.y) <= 1e-5 * y.norm + 1e-7); + } +} + +test "a prompt's dense products at Flash Next's K write the bytes of the matrix tile, and of tf_cast's rounding in bf16" { + const t = try Rig.open(1 << 20); + defer t.close(); + if (t.on.affine.dense[0] == null) return error.SkipZigTest; + var rng: rig.Rng = .{ .state = 0x6A09E667F3BCC908 }; + try promptDense(t, &rng, 300, 640, 2560); + try promptDense(t, &rng, 130, 200, 2560); + try promptDense(t, &rng, 257, 2560, 6144); + try promptDense(t, &rng, 200, 324, 10240); + try promptDense(t, &rng, 383, 10240, 320); + try promptDense(t, &rng, 1024, 1024, 2560); +} diff --git a/zig/src/hip/kernel_tests/decode_route.zig b/zig/src/hip/kernel_tests/decode_route.zig new file mode 100644 index 0000000000..35182ed2f9 --- /dev/null +++ b/zig/src/hip/kernel_tests/decode_route.zig @@ -0,0 +1,279 @@ +//! The merged router, pick and plan launches against the launches they replace and against served plans. +const std = @import("std"); +const rig = @import("rig.zig"); +const Rig = rig.Rig; +const gpa = rig.gpa; +const at = rig.at; +const p = @import("decode.zig").p; + +/// Router and pick in one launch vs tf_moe_router, tf_select_decode and (2 to 8 rows, tile 8) tf_moe_route: same bytes. +fn routerSelect(t: *Rig, rng: *rig.Rng, rows: usize, d: usize, e: usize, top_k: usize, ties: bool) !void { + const slots = top_k + 1; + const cap: usize = 16 * slots + 16 * slots / 8; + const hx = try gpa.alloc(u16, rows * d); + defer gpa.free(hx); + for (hx) |*v| v.* = t.bits(rng.unit()); + const h16 = try gpa.alloc(u16, e * d); + defer gpa.free(h16); + for (h16) |*v| v.* = rig.bf16Bits(rng.unit() / 8.0); + if (ties) for ([_]usize{ 3, 9, 100, 511 }) |dst| @memcpy(h16[dst * d ..][0..d], h16[0..d]); + const h32 = try gpa.alloc(f32, e * d); + defer gpa.free(h32); + for (h16, h32) |b, *v| v.* = @bitCast(@as(u32, b) << 16); + var x = try t.upload(hx); + defer x.free(); + var w16 = try t.upload(h16); + defer w16.free(); + var w32 = try t.upload(h32); + defer w32.free(); + var done = try t.upload(@as([]const u32, &.{0})); + defer done.free(); + const sizes = [_]usize{ rows * e * 4, rows * slots * 4, rows * slots * 4, cap * 12, rows * slots * 4 }; + var got: [3][5][]u8 = undefined; + // 0: the two launches; 1 and 2: the one launch twice (its block counter is zero again after each) + for (0..3) |v| { + var bufs: [5]@import("../memory.zig").DeviceBuffer = undefined; + for (&bufs, sizes) |*b, n| { + b.* = try t.alloc(n); + const zero = try gpa.alloc(u8, n); + defer gpa.free(zero); + @memset(zero, 0); + try b.upload(0, zero); + } + defer for (&bufs) |*b| b.free(); + const s = t.stream.handle; + const planned = rows <= 8; + const tile: usize = if (rows == 1) 0 else 8; + const items: ?[*]i32 = if (planned) @ptrFromInt(at(bufs[3])) else null; + const members: ?[*]i32 = if (planned) @ptrFromInt(at(bufs[4])) else null; + if (v == 0) { + try t.on.tf_moe_router(p(x), t.kind(), @ptrFromInt(at(w32)), @ptrFromInt(at(bufs[0])), @intCast(rows), @intCast(d), @intCast(e), s); + const one = rows == 1; + try t.on.tf_moe_select(@ptrFromInt(at(bufs[0])), @ptrFromInt(at(bufs[1])), @ptrFromInt(at(bufs[2])), if (one) items else null, if (one) members else null, @intCast(cap), @intCast(rows), @intCast(e - 1), @intCast(top_k), s); + if (planned and !one) try t.on.tf_moe_route(@ptrFromInt(at(bufs[1])), @intCast(rows * slots), @intCast(e), @intCast(tile), members, items, @intCast(cap), s); + } else { + try std.testing.expect(try t.on.routerSelect(p(x), t.kind(), p(w16), @ptrFromInt(at(bufs[0])), @ptrFromInt(at(bufs[1])), @ptrFromInt(at(bufs[2])), items, members, @intCast(cap), @intCast(rows), @intCast(d), @intCast(e), @intCast(top_k), @intCast(tile), at(done), s)); + } + try t.stream.synchronize(); + for (&got[v], bufs) |*g, b| g.* = try rig.download(u8, b); + } + defer for (&got) |*g| for (g) |b| gpa.free(b); + for (1..3) |v| for (0..5) |k| { + if (!std.mem.eql(u8, got[0][k], got[v][k])) { + std.debug.print("router+pick rows={d} ties={} run {d}: buffer {d} differs\n", .{ rows, ties, v, k }); + return error.TestUnexpectedResult; + } + }; +} + +/// tf_moe_route's prompt plan puts every live item before planItems(pairs, experts, 128); `bound` routings fill it. +fn routeLive(t: *Rig, rng: *rig.Rng, rows: usize, bound: bool) !void { + const moe = @import("../moe.zig"); + const experts = 513; + const tile = 128; + const pairs = rows * 11; + const cap = moe.capacity(pairs, experts); + const pick = try gpa.alloc(i32, pairs); + defer gpa.free(pick); + if (bound) { + // 128 k + 1 pairs an expert, the pairs past them in whole tiles and one partial spare, in a shuffled order + const per = (pairs - experts) / experts / tile; + var n: usize = 0; + for (0..experts) |e| for (0..tile * per + 1) |_| { + pick[n] = @intCast(e); + n += 1; + }; + var e: usize = 0; + while (pairs - n >= tile) : (e += 1) { + for (0..tile) |_| { + pick[n] = @intCast(e); + n += 1; + } + } + while (n < pairs) : (n += 1) pick[n] = experts - 1; + var i: usize = pairs; + while (i > 1) : (i -= 1) std.mem.swap(i32, &pick[i - 1], &pick[rng.next() % i]); + } else for (pick) |*e| { + const r = rng.next(); + e.* = @intCast(if (r % 2 == 0) r % 8 else r % experts); + } + var dev_pick = try t.upload(pick); + defer dev_pick.free(); + var members = try t.alloc(pairs * 4); + defer members.free(); + var items = try t.alloc(cap * 12); + defer items.free(); + try items.fill8(0xFF); + try t.on.tf_moe_route(@ptrFromInt(at(dev_pick)), @intCast(pairs), experts, tile, @ptrFromInt(at(members)), @ptrFromInt(at(items)), @intCast(cap), t.stream.handle); + try t.stream.synchronize(); + const host = try rig.download(i32, items); + defer gpa.free(host); + const z = moe.planItems(pairs, experts, tile); + var live: usize = 0; + var past: usize = 0; + var covered: usize = 0; + for (0..cap) |slot| if (host[3 * slot + 2] > 0) { + live += 1; + covered += @intCast(host[3 * slot + 2]); + if (slot >= z) past += 1; + }; + std.debug.print(" prompt plan rows {d}{s}: {d} live items, z {d} (capacity {d})\n", .{ rows, if (bound) " at the bound" else "", live, z, cap }); + try std.testing.expectEqual(@as(usize, 0), past); + try std.testing.expectEqual(pairs, covered); + if (bound) try std.testing.expectEqual(z, live); +} + +test "a prompt plan's live items come before planItems(pairs, experts, 128), which they fill at 128 k + 1 pairs an expert" { + const t = try Rig.open(1 << 20); + defer t.close(); + var rng: rig.Rng = .{ .state = 0x2545F4914F6CDD1D }; + for ([_]usize{ 8192, 17715, 20480 }) |rows| for ([_]bool{ true, false }) |bound| try routeLive(t, &rng, rows, bound); +} + +test "the router and the pick in one launch give the two launches' bytes (Qwen3.8 Flash Next: 513 x 2560, top 10)" { + const t = try Rig.open(1 << 20); + defer t.close(); + var rng: rig.Rng = .{ .state = 0x9E3779B97F4A7C15 }; + for ([_]usize{ 1, 2, 3, 4, 5, 6, 7, 8, 16 }) |rows| for ([_]bool{ false, true }) |ties| try routerSelect(t, &rng, rows, 2560, 513, 10, ties); +} + +/// Served plans, 3 MoE layers a width of 1-8 rows: i32 layer, rows, slots, cap; picks (rows x slots); items (cap x 3). +const served_plans = @embedFile("served_plans.bin"); + +/// One launch on a served plan (one-hot x, served picks the top weights): the served bytes, as the launches replaced. +fn servedPlan(t: *Rig, rng: *rig.Rng, rows: usize, slots: usize, cap: usize, picks: []const i32, items: []const i32) !void { + const d: usize = 2560; + const e: usize = 513; + const top_k = slots - 1; + const hx = try gpa.alloc(u16, rows * d); + defer gpa.free(hx); + @memset(hx, t.bits(0)); + for (0..rows) |r| hx[r * d + r] = t.bits(1); + const h16 = try gpa.alloc(u16, e * d); + defer gpa.free(h16); + @memset(h16, 0); + for (0..rows) |r| { + for (0..e) |ex| h16[ex * d + r] = rig.bf16Bits(rng.unit() / 8.0); + for (0..top_k) |k| h16[@as(usize, @intCast(picks[r * slots + k])) * d + r] = rig.bf16Bits(4.0 - 0.25 * @as(f32, @floatFromInt(k))); + } + const h32 = try gpa.alloc(f32, e * d); + defer gpa.free(h32); + for (h16, h32) |b, *v| v.* = @bitCast(@as(u32, b) << 16); + var x = try t.upload(hx); + defer x.free(); + var w16 = try t.upload(h16); + defer w16.free(); + var w32 = try t.upload(h32); + defer w32.free(); + var done = try t.upload(@as([]const u32, &.{0})); + defer done.free(); + const sizes = [_]usize{ rows * e * 4, rows * slots * 4, rows * slots * 4, cap * 12, rows * slots * 4 }; + var got: [2][5][]u8 = undefined; + const tile: usize = if (rows == 1) 0 else 8; + for (0..2) |v| { + var bufs: [5]@import("../memory.zig").DeviceBuffer = undefined; + for (&bufs, sizes) |*b, n| { + b.* = try t.alloc(n); + const zero = try gpa.alloc(u8, n); + defer gpa.free(zero); + @memset(zero, 0); + try b.upload(0, zero); + } + defer for (&bufs) |*b| b.free(); + const s = t.stream.handle; + const it: [*]i32 = @ptrFromInt(at(bufs[3])); + const mem: [*]i32 = @ptrFromInt(at(bufs[4])); + if (v == 0) { + try t.on.tf_moe_router(p(x), t.kind(), @ptrFromInt(at(w32)), @ptrFromInt(at(bufs[0])), @intCast(rows), @intCast(d), @intCast(e), s); + const one = rows == 1; + try t.on.tf_moe_select(@ptrFromInt(at(bufs[0])), @ptrFromInt(at(bufs[1])), @ptrFromInt(at(bufs[2])), if (one) it else null, if (one) mem else null, @intCast(cap), @intCast(rows), @intCast(e - 1), @intCast(top_k), s); + if (!one) try t.on.tf_moe_route(@ptrFromInt(at(bufs[1])), @intCast(rows * slots), @intCast(e), @intCast(tile), mem, it, @intCast(cap), s); + } else { + try std.testing.expect(try t.on.routerSelect(p(x), t.kind(), p(w16), @ptrFromInt(at(bufs[0])), @ptrFromInt(at(bufs[1])), @ptrFromInt(at(bufs[2])), it, mem, @intCast(cap), @intCast(rows), @intCast(d), @intCast(e), @intCast(top_k), @intCast(tile), at(done), s)); + } + try t.stream.synchronize(); + for (&got[v], bufs) |*g, b| g.* = try rig.download(u8, b); + } + defer for (&got) |*g| for (g) |b| gpa.free(b); + for (0..2) |v| { + if (!std.mem.eql(u8, got[v][1], std.mem.sliceAsBytes(picks)) or !std.mem.eql(u8, got[v][3], std.mem.sliceAsBytes(items))) { + std.debug.print("served plan rows={d} run {d}: picks or items differ from the served bytes\n", .{ rows, v }); + return error.TestUnexpectedResult; + } + } + for (0..5) |k| if (!std.mem.eql(u8, got[0][k], got[1][k])) { + std.debug.print("served plan rows={d}: buffer {d} differs between the launches\n", .{ rows, k }); + return error.TestUnexpectedResult; + }; +} + +test "the router and the pick in one launch give a served plan's picks and items, byte for byte (rows 1 to 8)" { + const t = try Rig.open(1 << 20); + defer t.close(); + var rng: rig.Rng = .{ .state = 0x2545F4914F6CDD1D }; + var at_byte: usize = 0; + var seen: [9]usize = @splat(0); + while (at_byte + 16 <= served_plans.len) { + const head = std.mem.bytesAsSlice(i32, served_plans[at_byte..][0..16]); + const rows: usize = @intCast(head[1]); + const slots: usize = @intCast(head[2]); + const cap: usize = @intCast(head[3]); + at_byte += 16; + const picks = try gpa.alloc(i32, rows * slots); + defer gpa.free(picks); + @memcpy(std.mem.sliceAsBytes(picks), served_plans[at_byte..][0 .. rows * slots * 4]); + at_byte += rows * slots * 4; + const items = try gpa.alloc(i32, cap * 3); + defer gpa.free(items); + @memcpy(std.mem.sliceAsBytes(items), served_plans[at_byte..][0 .. cap * 12]); + at_byte += cap * 12; + try servedPlan(t, &rng, rows, slots, cap, picks, items); + seen[rows] += 1; + } + for (seen[1..]) |n| try std.testing.expect(n == 3); +} + +test "a prompt's picks a wave a row (tf_select_rows) are select_body's bytes, ties included" { + const t = try Rig.open(1 << 20); + defer t.close(); + var rng: rig.Rng = .{ .state = 0x5E1EC7 }; + const top_k: usize = 10; + const slots = top_k + 1; + for ([_][2]usize{ .{ 4099, 512 }, .{ 37, 512 }, .{ 1029, 1024 }, .{ 6, 64 } }) |shape| { + const rows = shape[0]; + const experts = shape[1]; + const h = try gpa.alloc(f32, rows * (experts + 1)); + defer gpa.free(h); + for (h) |*v| v.* = rng.unit() * 4.0; + // ties: three experts copy expert 0's logit in every row, and in odd rows expert 5 copies expert 1's + for (0..rows) |r| { + const row = h[r * (experts + 1) ..][0 .. experts + 1]; + for ([_]usize{ 3, 9, experts / 2 }) |c| row[c] = row[0]; + if (r % 2 == 1) row[5] = row[1]; + } + var logits = try t.upload(h); + defer logits.free(); + var got: [2][2][]u8 = undefined; + for (0..2) |v| { + var pick = try t.alloc(rows * slots * 4); + defer pick.free(); + var wts = try t.alloc(rows * slots * 4); + defer wts.free(); + var items = try t.alloc(slots * 12); + defer items.free(); + var members = try t.alloc(slots * 4); + defer members.free(); + // 0: select_body (tf_select_decode, taken where a plan is asked for); 1: tf_select_rows + const it: ?[*]i32 = if (v == 0) @ptrFromInt(at(items)) else null; + const mem: ?[*]i32 = if (v == 0) @ptrFromInt(at(members)) else null; + try t.on.tf_moe_select(@ptrFromInt(at(logits)), @ptrFromInt(at(pick)), @ptrFromInt(at(wts)), it, mem, @intCast(slots), @intCast(rows), @intCast(experts), @intCast(top_k), t.stream.handle); + try t.stream.synchronize(); + got[v] = .{ try rig.download(u8, pick), try rig.download(u8, wts) }; + } + defer for (&got) |*g| for (g) |b| gpa.free(b); + for (0..2) |k| if (!std.mem.eql(u8, got[0][k], got[1][k])) { + std.debug.print("select rows={d} experts={d}: {s} differ\n", .{ rows, experts, if (k == 0) "picks" else "weights" }); + return error.TestUnexpectedResult; + }; + } +} diff --git a/zig/src/hip/kernel_tests/flashnext.zig b/zig/src/hip/kernel_tests/flashnext.zig index 3681738184..99796c4f0a 100644 --- a/zig/src/hip/kernel_tests/flashnext.zig +++ b/zig/src/hip/kernel_tests/flashnext.zig @@ -127,7 +127,8 @@ test "hyper-connection norm, gates and mix: the reference's roundings, each row defer mixed.free(); try t.on.fn_hc_gates(ptr(?[*]const f32, z), ptr(?*anyopaque, act), ptr(?*anyopaque, inj), k, rows, low, s, st); try t.on.fn_hc_mix( - ptr(?[*]const f32, g), + ptr(?*const anyopaque, g), + 0, ptr(?*const anyopaque, x_out), ptr(?*anyopaque, mixed), k, @@ -508,3 +509,7 @@ test "n-gram rows: every head's hash of the window, segments cut at eos, exact" }; } } + +test { + _ = @import("flashnext_hc.zig"); +} diff --git a/zig/src/hip/kernel_tests/flashnext_attn.zig b/zig/src/hip/kernel_tests/flashnext_attn.zig index 9523dd1d6e..86d726cecb 100644 --- a/zig/src/hip/kernel_tests/flashnext_attn.zig +++ b/zig/src/hip/kernel_tests/flashnext_attn.zig @@ -168,6 +168,118 @@ fn selectRef(scores: []const f32, nb: usize, end: usize, top: usize, ratio: usiz for (nb * ratio..end) |k| try out.append(gpa, @intCast(k)); } +test "a prompt slice's block scores at 4 lanes a score are a wave a block's, bit for bit (Flash Next: 4 x 128)" { + const t = try Rig.open(1 << 24); + defer t.close(); + var rng: rig.Rng = .{ .state = 0x9A4D }; + const heads = 4; + const dims = 128; + const top = 32; + const blocks = 1100; + const rows = 64; + var complete: [rows]i32 = undefined; + // rows past the budget at varied depths, some under it (no scores), one at the last block + for (&complete, 0..) |*c, r| c.* = if (r % 9 == 4) 20 else @intCast(@min(blocks, 40 + r * 17)); + complete[rows - 1] = blocks; + const hq = try gpa.alloc(f32, rows * heads * dims); + defer gpa.free(hq); + for (hq) |*x| x.* = rng.unit(); + const hp = try fx.acts(t, &rng, blocks * dims, 1.0); + defer gpa.free(hp); + var q = try t.upload(hq); + defer q.free(); + var pooled = try t.upload(hp); + defer pooled.free(); + var dc = try t.upload(&complete); + defer dc.free(); + var got: [2][]u8 = undefined; + for (0..2) |v| { + var scores = try t.alloc(rows * blocks * 4); + defer scores.free(); + try scores.fill8(0x7f); + const st = t.stream.handle; + if (v == 0) { + // 8-row calls (under the quad's rows: tf_fn_idx_scores8, whose scores the 1-row kernel's test below pins) + var r0: usize = 0; + while (r0 < rows) : (r0 += 8) try t.on.fn_idx_scores( + @ptrFromInt(at(q) + r0 * heads * dims * 4), + ptr(?*const anyopaque, pooled), + @ptrFromInt(at(dc) + r0 * 4), + @ptrFromInt(at(scores) + r0 * blocks * 4), + t.kind(), + 8, + heads, + dims, + blocks, + blocks, + top, + st, + ); + } else try t.on.fn_idx_scores(ptr(?[*]const f32, q), ptr(?*const anyopaque, pooled), ptr(?[*]const i32, dc), ptr(?[*]f32, scores), t.kind(), rows, heads, dims, blocks, blocks, top, st); + try t.stream.synchronize(); + got[v] = try rig.download(u8, scores); + } + defer for (got) |g| gpa.free(g); + try std.testing.expectEqualSlices(u8, got[0], got[1]); +} + +test "a verify window's block scores at 5-15 rows (8 rows' dots a wave at once) are one row's at a time, bit for bit" { + const t = try Rig.open(1 << 24); + defer t.close(); + var rng: rig.Rng = .{ .state = 0x9A4F }; + const heads = 4; + const dims = 128; + const top = 32; + const blocks = 1100; + const most = 15; + const hq = try gpa.alloc(f32, most * heads * dims); + defer gpa.free(hq); + for (hq) |*x| x.* = rng.unit(); + const hp = try fx.acts(t, &rng, blocks * dims, 1.0); + defer gpa.free(hp); + var q = try t.upload(hq); + defer q.free(); + var pooled = try t.upload(hp); + defer pooled.free(); + for ([_]usize{ 5, 8, 11, 15 }) |rows| { + // a window's rows one block apart, one under the budget (no scores), the last at the bound + var complete: [most]i32 = @splat(0); + for (0..rows) |r| complete[r] = @intCast(@min(blocks, 1000 + r * 7)); + complete[1] = 20; + complete[rows - 1] = blocks; + var dc = try t.upload(&complete); + defer dc.free(); + var got: [2][]u8 = undefined; + for (0..2) |v| { + var scores = try t.alloc(rows * blocks * 4); + defer scores.free(); + try scores.fill8(0x7f); + const st = t.stream.handle; + if (v == 0) { + // one row a call: tf_fn_idx_scores + for (0..rows) |r| try t.on.fn_idx_scores( + @ptrFromInt(at(q) + r * heads * dims * 4), + ptr(?*const anyopaque, pooled), + @ptrFromInt(at(dc) + r * 4), + @ptrFromInt(at(scores) + r * blocks * 4), + t.kind(), + 1, + heads, + dims, + blocks, + blocks, + top, + st, + ); + } else try t.on.fn_idx_scores(ptr(?[*]const f32, q), ptr(?*const anyopaque, pooled), ptr(?[*]const i32, dc), ptr(?[*]f32, scores), t.kind(), @intCast(rows), heads, dims, blocks, blocks, top, st); + try t.stream.synchronize(); + got[v] = try rig.download(u8, scores); + } + defer for (got) |g| gpa.free(g); + try std.testing.expectEqualSlices(u8, got[0], got[1]); + } +} + test "block scores and selection: relu-summed heads, the best blocks with ties to the lower id, dense rows untouched" { const t = try Rig.open(1 << 22); defer t.close(); @@ -415,3 +527,7 @@ fn sparseCase(t: *Rig, comptime heads: usize, comptime kv_heads: usize) !void { } }; } + +test { + _ = @import("flashnext_attn_tiles.zig"); +} diff --git a/zig/src/hip/kernel_tests/flashnext_attn_tiles.zig b/zig/src/hip/kernel_tests/flashnext_attn_tiles.zig new file mode 100644 index 0000000000..0ff756c610 --- /dev/null +++ b/zig/src/hip/kernel_tests/flashnext_attn_tiles.zig @@ -0,0 +1,131 @@ +//! Flash Next's QSA decode prep against the launches it replaces. +const std = @import("std"); +const rig = @import("rig.zig"); +const fx = @import("flashnext.zig"); +const Rig = rig.Rig; +const gpa = rig.gpa; +const at = rig.at; +const ptr = fx.ptr; +const rnd = fx.rnd; + +/// tf_fn_qsa_prep against the launches it replaces: the same q, caches and pooled keys; `n` rows at `first`. +fn qsaPrep(t: *Rig, rng: *rig.Rng, n: usize, first: i32, with_q: bool) !void { + const heads = 24; + const kv_heads = 2; + const hd = 256; + const ih = 4; + const di = 128; + const width = (ih + 1) * di; + const ratio = 4; + const rotary = 64; + const theta: f32 = 10_000_000; + const eps: f32 = 1e-6; + const cap = 64; + const s = t.stream.handle; + const hq = try fx.acts(t, rng, n * heads * 2 * hd, 2.0); + defer gpa.free(hq); + const hk = try fx.acts(t, rng, n * kv_heads * hd, 2.0); + defer gpa.free(hk); + const hv = try fx.acts(t, rng, n * kv_heads * hd, 2.0); + defer gpa.free(hv); + const hi = try fx.acts(t, rng, n * width, 2.0); + defer gpa.free(hi); + // the earlier rows of each block already in the raw cache + const hraw0 = try fx.acts(t, rng, cap * di, 2.0); + defer gpa.free(hraw0); + var norms: [4][hd]f32 = undefined; + for (&norms) |*w| for (w) |*x| { + x.* = 1.0 + rng.unit() * 0.5; + }; + var q = try t.upload(hq); + defer q.free(); + var k = try t.upload(hk); + defer k.free(); + var v = try t.upload(hv); + defer v.free(); + var idx = try t.upload(hi); + defer idx.free(); + var w = [4]@import("../memory.zig").DeviceBuffer{ try t.upload(&norms[0]), try t.upload(&norms[1]), try t.upload(&norms[2]), try t.upload(&norms[3]) }; + defer for (&w) |*b| b.free(); + var hpos: [4]i32 = undefined; + for (0..n) |r| hpos[r] = first + @as(i32, @intCast(r)); + var pos = try t.upload(hpos[0..n]); + defer pos.free(); + // [0]: the separate launches, [1]: the one launch; each has q, index q, K, V, raw and pooled buffers + var outs: [2][6]@import("../memory.zig").DeviceBuffer = undefined; + const sizes = [6]usize{ n * heads * hd * 4, n * ih * di * 4, kv_heads * cap * hd * 2, kv_heads * cap * hd * 2, cap * di * 2, (cap / ratio) * di * 2 }; + for (&outs) |*set| for (set, sizes) |*b, size| { + b.* = try t.alloc(size); + try b.fill8(0xA5); + }; + defer for (&outs) |*set| for (set) |*b| b.free(); + for (&outs) |*set| try set[4].upload(0, std.mem.sliceAsBytes(hraw0)); + const kind = t.kind(); + { + const o = &outs[0]; + if (with_q) { + try t.on.tf_qk_rope(ptr(?*const anyopaque, q), kind, 2 * heads * hd, 2 * hd, ptr(?[*]const f32, w[0]), eps, @intCast(n), heads, hd, rotary, theta, ptr(?[*]const i32, pos), ptr(?[*]f32, o[0]), null, 0, s); + try t.on.tf_qk_rope(ptr(?*const anyopaque, idx), kind, width, di, ptr(?[*]const f32, w[1]), eps, @intCast(n), ih, di, rotary, theta, ptr(?[*]const i32, pos), ptr(?[*]f32, o[1]), null, 0, s); + } + try t.on.tf_qk_rope(ptr(?*const anyopaque, k), kind, kv_heads * hd, hd, ptr(?[*]const f32, w[2]), eps, @intCast(n), kv_heads, hd, rotary, theta, ptr(?[*]const i32, pos), null, ptr(?*anyopaque, o[2]), cap, s); + try t.on.tf_kv_write_at(ptr(?*const anyopaque, v), ptr(?*anyopaque, o[3]), kind, @intCast(n), kv_heads, hd, cap, ptr(?[*]const i32, pos), s); + var raw = try t.alloc(n * di * 2); + defer raw.free(); + try t.on.tf_copy_cols(ptr(?*const anyopaque, idx), width, ih * di, ptr(?*anyopaque, raw), kind, @intCast(n), di, s); + try t.on.tf_kv_write_at(ptr(?*const anyopaque, raw), ptr(?*anyopaque, o[4]), kind, @intCast(n), 1, di, cap, ptr(?[*]const i32, pos), s); + try t.on.fn_idx_pool_at(ptr(?*const anyopaque, o[4]), ptr(?*anyopaque, o[5]), ptr(?[*]const f32, w[3]), kind, ptr(?[*]const i32, pos), @intCast(n), di, ratio, rotary, theta, eps, s); + try t.stream.synchronize(); + } + { + const o = &outs[1]; + try t.on.fn_qsa_prep(.{ + .q = if (with_q) .{ .src = at(q), .s_row = 2 * heads * hd, .s_head = 2 * hd, .heads = heads, .width = hd, .weight = at(w[0]), .wide = at(o[0]) } else .{}, + .iq = if (with_q) .{ .src = at(idx), .s_row = width, .s_head = di, .heads = ih, .width = di, .weight = at(w[1]), .wide = at(o[1]) } else .{}, + .k = .{ .src = at(k), .s_row = kv_heads * hd, .s_head = hd, .heads = kv_heads, .width = hd, .weight = at(w[2]), .cache = at(o[2]) }, + .v = at(v), + .v_cache = at(o[3]), + .v_width = hd, + .raw = at(idx), + .raw_stride = width, + .raw_offset = ih * di, + .raw_cache = at(o[4]), + .raw_width = di, + .pooled = at(o[5]), + .pool_scale = at(w[3]), + .ratio = ratio, + .pos = at(pos), + .seg_pos = at(pos), + .rows = @intCast(n), + .n = @intCast(n), + .total = cap, + .kind = kind, + .eps = eps, + .rotary = rotary, + .theta = theta, + }, s); + try t.stream.synchronize(); + } + const names = [6][]const u8{ "q", "index q", "K cache", "V cache", "raw cache", "pooled" }; + for (0..6) |b| { + const want = try rig.download(u8, outs[0][b]); + defer gpa.free(want); + const got = try rig.download(u8, outs[1][b]); + defer gpa.free(got); + if (!std.mem.eql(u8, want, got)) { + std.debug.print("qsa prep n={d} first={d} q={}: {s} differs\n", .{ n, first, with_q, names[b] }); + return error.TestUnexpectedResult; + } + } +} + +test "the QSA decode prep in one launch writes the bytes of the seven launches it replaces (Flash Next, 1 to 4 rows)" { + const t = try Rig.open(1 << 20); + defer t.close(); + var rng: rig.Rng = .{ .state = 0x51A9 }; + // a row completing a block at its end (15), inside the window (10 .. 13 completes 11), none (12, 13 .. 14) + try qsaPrep(t, &rng, 1, 15, true); + try qsaPrep(t, &rng, 1, 13, true); + try qsaPrep(t, &rng, 4, 10, true); + try qsaPrep(t, &rng, 2, 12, true); + try qsaPrep(t, &rng, 3, 20, false); +} diff --git a/zig/src/hip/kernel_tests/flashnext_hc.zig b/zig/src/hip/kernel_tests/flashnext_hc.zig new file mode 100644 index 0000000000..d6c1418d5c --- /dev/null +++ b/zig/src/hip/kernel_tests/flashnext_hc.zig @@ -0,0 +1,264 @@ +//! Flash Next's merged hyper-connection and MoE-combine launches against the launches they replace, byte for byte. +const std = @import("std"); +const rig = @import("rig.zig"); +const fx = @import("flashnext.zig"); +const Rig = rig.Rig; +const gpa = rig.gpa; +const at = rig.at; +const DeviceBuffer = @import("../memory.zig").DeviceBuffer; +const ptr = fx.ptr; +const acts = fx.acts; +const value = fx.value; + +/// A random MLX 4-bit g32 matrix (n, k) with bf16 tables, on the device. +const Packed = struct { + dev: [3]DeviceBuffer, + + fn init(t: *Rig, rng: *rig.Rng, n: usize, k: usize) !Packed { + const words = try gpa.alloc(u32, n * k / 8); + defer gpa.free(words); + const scale = try gpa.alloc(u16, n * k / 32); + defer gpa.free(scale); + const bias = try gpa.alloc(u16, scale.len); + defer gpa.free(bias); + for (words) |*w| w.* = @truncate(rng.next() >> 16); + for (scale) |*v| v.* = rig.bf16Bits((rng.unit() + 1.0) / 64.0); + for (bias) |*v| v.* = rig.bf16Bits(-rng.unit() / 8.0); + return .{ .dev = .{ try t.upload(words), try t.upload(scale), try t.upload(bias) } }; + } + + fn deinit(p: *Packed) void { + for (&p.dev) |*b| b.free(); + } + + fn affine(p: Packed, n: usize, k: usize) @import("../ops/types.zig").Affine { + return .{ .words = at(p.dev[0]), .scale = at(p.dev[1]), .bias = at(p.dev[2]), .tables = .bf16, .n = @intCast(n), .k = @intCast(k), .bits = 4, .group = 32 }; + } +}; + +test "the MoE combine inside the HC norm: moe_combine_kernel's then tf_fn_hc_norm's bytes, 1 to 8 rows" { + const t = try Rig.open(64 << 20); + defer t.close(); + var rng: rig.Rng = .{ .state = 0x4C7 }; + const s = 4; + const d = 2560; + const slots = 11; // Flash Next: 10 routed experts and the shared one + const k = t.kind(); + const st = t.stream.handle; + for ([_]usize{ 1, 3, 4, 8 }) |rows| { + const yh = try gpa.alloc(f32, rows * slots * d); + defer gpa.free(yh); + for (yh) |*v| v.* = rng.unit() * 2.0; + const wh = try gpa.alloc(f32, rows * slots); + defer gpa.free(wh); + for (wh) |*v| v.* = rng.unit() * 0.5; + const hh = try acts(t, &rng, rows * s * d, 3.0); + defer gpa.free(hh); + const ih = try acts(t, &rng, rows * s, 2.0); + defer gpa.free(ih); + const sh = try gpa.alloc(f32, s * d); + defer gpa.free(sh); + for (sh) |*v| v.* = 1.0 + rng.unit() * 0.25; + var y = try t.upload(yh); + defer y.free(); + var w = try t.upload(wh); + defer w.free(); + var inject = try t.upload(ih); + defer inject.free(); + var scale = try t.upload(sh); + defer scale.free(); + var h = [_]DeviceBuffer{ try t.upload(hh), try t.upload(hh) }; + defer for (&h) |*b| b.free(); + var x = [_]DeviceBuffer{ try t.alloc(rows * s * d * 2), try t.alloc(rows * s * d * 2) }; + defer for (&x) |*b| b.free(); + var branch = try t.alloc(rows * d * 2); + defer branch.free(); + // the chain: the combine into the activation kind, then the norm with it as the branch + try t.ops(&t.on).moeCombine(at(y), at(w), .{ .ptr = at(branch), .kind = if (k == 2) .bf16 else .f16 }, rows, slots, d); + try t.on.fn_hc_norm(@ptrFromInt(at(h[0])), @ptrFromInt(at(branch)), @ptrFromInt(at(inject)), @ptrFromInt(at(h[0])), @ptrFromInt(at(x[0])), @ptrFromInt(at(scale)), k, @intCast(rows), s, d, 1e-6, st); + try t.on.fn_hc_norm_moe(@ptrFromInt(at(h[1])), @ptrFromInt(at(y)), @ptrFromInt(at(w)), @ptrFromInt(at(inject)), @ptrFromInt(at(h[1])), @ptrFromInt(at(x[1])), @ptrFromInt(at(scale)), k, @intCast(rows), s, d, 1e-6, slots, st); + try t.stream.synchronize(); + for ([_][2]DeviceBuffer{ h, x }) |pair| { + const a = try rig.download(u16, pair[0]); + defer gpa.free(a); + const b = try rig.download(u16, pair[1]); + defer gpa.free(b); + try std.testing.expectEqualSlices(u16, a, b); + } + } +} + +test "a prompt's MoE combine inside the HC norm, a block a row: moe_combine_kernel's then tf_fn_hc_norm_v's bytes" { + const t = try Rig.open(256 << 20); + defer t.close(); + if (!t.bf16) return; // the 16-byte kernels are bf16 only + var rng: rig.Rng = .{ .state = 0x4D1 }; + const s = 4; + const d = 2560; + const slots = 11; // Flash Next: 10 routed experts and the shared one + const st = t.stream.handle; + for ([_]usize{ 1, 7, 64, 513 }) |rows| { + const yh = try gpa.alloc(f32, rows * slots * d); + defer gpa.free(yh); + for (yh) |*v| v.* = rng.unit() * 2.0; + // a few slot values huge, tiny or zero: the sums' rounding and the norm's range, not only the middle + for (0..rows) |r| yh[(r * slots + r % slots) * d + r % d] = if (r % 3 == 0) 3.0e4 else if (r % 3 == 1) 1.0e-30 else 0.0; + const wh = try gpa.alloc(f32, rows * slots); + defer gpa.free(wh); + for (wh) |*v| v.* = rng.unit() * 0.5; + const hh = try acts(t, &rng, rows * s * d, 3.0); + defer gpa.free(hh); + const ih = try acts(t, &rng, rows * s, 2.0); + defer gpa.free(ih); + const sh = try gpa.alloc(f32, s * d); + defer gpa.free(sh); + for (sh) |*v| v.* = 1.0 + rng.unit() * 0.25; + var y = try t.upload(yh); + defer y.free(); + var w = try t.upload(wh); + defer w.free(); + var inject = try t.upload(ih); + defer inject.free(); + var scale = try t.upload(sh); + defer scale.free(); + var h = [_]DeviceBuffer{ try t.upload(hh), try t.upload(hh) }; + defer for (&h) |*b| b.free(); + var x = [_]DeviceBuffer{ try t.alloc(rows * s * d * 2), try t.alloc(rows * s * d * 2) }; + defer for (&x) |*b| b.free(); + var branch = try t.alloc(rows * d * 2); + defer branch.free(); + // the chain: the combine into bf16, then the norm (tf_fn_hc_norm_v at bf16 2,560) with it as the branch + try t.ops(&t.on).moeCombine(at(y), at(w), .{ .ptr = at(branch), .kind = .bf16 }, rows, slots, d); + try t.on.fn_hc_norm(@ptrFromInt(at(h[0])), @ptrFromInt(at(branch)), @ptrFromInt(at(inject)), @ptrFromInt(at(h[0])), @ptrFromInt(at(x[0])), @ptrFromInt(at(scale)), 2, @intCast(rows), s, d, 1e-6, st); + try t.on.fn_hc_norm_moe_v(@ptrFromInt(at(h[1])), @ptrFromInt(at(y)), @ptrFromInt(at(w)), @ptrFromInt(at(inject)), @ptrFromInt(at(h[1])), @ptrFromInt(at(x[1])), @ptrFromInt(at(scale)), @intCast(rows), s, 1e-6, slots, st); + try t.stream.synchronize(); + for ([_][2]DeviceBuffer{ h, x }) |pair| { + const a = try rig.download(u16, pair[0]); + defer gpa.free(a); + const b = try rig.download(u16, pair[1]); + defer gpa.free(b); + try std.testing.expectEqualSlices(u16, a, b); + } + } +} + +test "hyper-connection norm and mix, 16-byte kernels: the per-element kernels' bytes at 1 to 300 rows" { + const t = try Rig.open(64 << 20); + defer t.close(); + if (!t.bf16) return; // the 16-byte kernels are bf16 only + var rng: rig.Rng = .{ .state = 0x4CA }; + const s = 4; + const d = 2560; + const w = s * d; + const k = t.kind(); + const st = t.stream.handle; + const scale = try gpa.alloc(f32, w); + defer gpa.free(scale); + for (scale) |*x| x.* = 1.0 + rng.unit() * 0.5; + var sc = try t.upload(scale); + defer sc.free(); + for ([_]usize{ 1, 3, 4, 8, 300 }) |rows| { + const hh = try acts(t, &rng, rows * w, 2.0); + defer gpa.free(hh); + const hb = try acts(t, &rng, rows * d, 1.0); + defer gpa.free(hb); + const hi = try acts(t, &rng, rows * s, 1.0); + defer gpa.free(hi); + // the branch as one fp32 share holds the same values: the shares path is the 1,024-thread kernel + const fb = try gpa.alloc(f32, rows * d); + defer gpa.free(fb); + for (fb, hb) |*f, b| f.* = value(t, b); + var h = try t.upload(hh); + defer h.free(); + var branch = try t.upload(hb); + defer branch.free(); + var share = try t.upload(fb); + defer share.free(); + var inject = try t.upload(hi); + defer inject.free(); + for ([_]bool{ true, false }) |with_branch| { + var outs = [_]DeviceBuffer{ try t.alloc(rows * w * 2), try t.alloc(rows * w * 2), try t.alloc(rows * w * 2), try t.alloc(rows * w * 2) }; + defer for (&outs) |*b| b.free(); + try t.on.fn_hc_norm(ptr(?*const anyopaque, h), if (with_branch) ptr(?*const anyopaque, branch) else null, ptr(?*const anyopaque, inject), ptr(?*anyopaque, outs[0]), ptr(?*anyopaque, outs[1]), ptr(?[*]const f32, sc), k, @intCast(rows), s, d, 1e-6, st); + try t.on.fn_hc_norm_shares(ptr(?*const anyopaque, h), if (with_branch) ptr(?*const anyopaque, share) else null, ptr(?*const anyopaque, inject), ptr(?*anyopaque, outs[2]), ptr(?*anyopaque, outs[3]), ptr(?[*]const f32, sc), k, @intCast(rows), s, d, 1e-6, 1, 0, st); + try t.stream.synchronize(); + for ([_][2]usize{ .{ 0, 2 }, .{ 1, 3 } }) |pair| { + const a = try rig.download(u16, outs[pair[0]]); + defer gpa.free(a); + const b = try rig.download(u16, outs[pair[1]]); + defer gpa.free(b); + try std.testing.expectEqualSlices(u16, b, a); + } + } + // the mix over fp32 and bf16 g against the per-element kernel + const gh = try gpa.alloc(f32, rows * w); + defer gpa.free(gh); + for (gh) |*x| x.* = rng.unit() * 6.0; + const g16 = try acts(t, &rng, rows * w, 6.0); + defer gpa.free(g16); + var g32 = try t.upload(gh); + defer g32.free(); + var gb = try t.upload(g16); + defer gb.free(); + var x = try t.upload(hh); + defer x.free(); + for ([_]c_int{ 0, k }) |gkind| { + var mixed = [_]DeviceBuffer{ try t.alloc(rows * d * 2), try t.alloc(rows * d * 2) }; + defer for (&mixed) |*b| b.free(); + const gp = if (gkind == 0) ptr(?*const anyopaque, g32) else ptr(?*const anyopaque, gb); + try t.on.fn_hc_mix(gp, gkind, ptr(?*const anyopaque, x), ptr(?*anyopaque, mixed[0]), k, @intCast(rows), s, d, st); + try t.on.fn_hc_mix_scalar(gp, gkind, ptr(?*const anyopaque, x), ptr(?*anyopaque, mixed[1]), k, @intCast(rows), s, d, st); + try t.stream.synchronize(); + const a = try rig.download(u16, mixed[0]); + defer gpa.free(a); + const b = try rig.download(u16, mixed[1]); + defer gpa.free(b); + try std.testing.expectEqualSlices(u16, b, a); + } + } +} + +test "hc up with the HC mix in the dense tile's epilogue: the dense product's bf16 g then tf_fn_hc_mix, byte for byte" { + const t = try Rig.open(64 << 20); + defer t.close(); + if (!t.bf16) return; + var o = t.ops(&t.on); + o.prefill = true; + var rng: rig.Rng = .{ .state = 0x4CB }; + const s = 4; + const d = 2560; + const w = s * d; + const low = 320; + var up = try Packed.init(t, &rng, w, low); + defer up.deinit(); + var ran: usize = 0; + for ([_]usize{ 129, 300, 1000 }) |rows| { + t.arena.reset(); + const ah = try acts(t, &rng, rows * low, 1.0); + defer gpa.free(ah); + const xh = try acts(t, &rng, rows * w, 2.0); + defer gpa.free(xh); + var act = try t.upload(ah); + defer act.free(); + var x = try t.upload(xh); + defer x.free(); + const at_act: @import("../ops/types.zig").Tensor = .{ .ptr = at(act), .kind = .bf16 }; + const at_x: @import("../ops/types.zig").Tensor = .{ .ptr = at(x), .kind = .bf16 }; + // null: the registry does not take the dense tile at this row count + const fused = (try o.hcUpMixAffine(at_act, up.affine(w, low), at_x, rows)) orelse continue; + ran += 1; + const g = try o.affine(at_act, up.affine(w, low), rows, false); + try std.testing.expectEqual(@import("../ops/types.zig").Kind.bf16, g.kind); + var want = try t.alloc(rows * d * 2); + defer want.free(); + try t.on.fn_hc_mix(@ptrFromInt(g.ptr), 2, ptr(?*const anyopaque, x), ptr(?*anyopaque, want), t.kind(), @intCast(rows), s, d, t.stream.handle); + try t.stream.synchronize(); + const a = try rig.download(u16, want); + defer gpa.free(a); + const b = try gpa.alloc(u16, rows * d); + defer gpa.free(b); + try @import("../runtime.zig").check(t.r.api.hipMemcpyDtoH(std.mem.sliceAsBytes(b).ptr, @ptrFromInt(fused.ptr), b.len * 2)); + try std.testing.expectEqualSlices(u16, a, b); + } + try std.testing.expect(ran > 0); +} diff --git a/zig/src/hip/kernel_tests/gdn.zig b/zig/src/hip/kernel_tests/gdn.zig index 531d7785d9..4134a64c84 100644 --- a/zig/src/hip/kernel_tests/gdn.zig +++ b/zig/src/hip/kernel_tests/gdn.zig @@ -137,6 +137,7 @@ fn run( d, d, null, + 0, ); } @@ -221,3 +222,239 @@ test "a prompt cut on either side of 64 rows gives the same rows and state as on try std.testing.expectEqualSlices(u32, @ptrCast(ws), @ptrCast(gs)); } } + +/// A `length`-row window from `at`, states into `snaps`; `from` (device i32, 0 none): -1 the state, f row f's snapshot. +fn window(t: *Rig, sh: Shape, in: [5]DeviceBuffer, state: DeviceBuffer, y: DeviceBuffer, snaps: DeviceBuffer, from: u64, at: usize, length: usize) !void { + const q, const k, const v, const gate, const beta = in; + const qk = at * sh.key_heads * d * 4; + const vy = at * sh.value_heads * d * 4; + const gb = at * sh.value_heads * 4; + try t.ops(&t.on).gatedDelta(rig.at(q) + qk, rig.at(k) + qk, rig.at(v) + vy, rig.at(gate) + gb, rig.at(beta) + gb, rig.at(state), rig.at(y) + vy, length, sh.key_heads, sh.value_heads, d, d, rig.at(snaps), from); +} + +test "a window started from the last window's snapshot row gives the bits of that snapshot copied back" { + const t = try Rig.open(1 << 30); + defer t.close(); + const sh: Shape = .{ .length = 8, .key_heads = 2, .value_heads = 4 }; + const rows = 4; + const in = try Inputs.make(sh, 0x5747e); + defer in.free(); + var bufs: [5]DeviceBuffer = undefined; + for (&bufs, [_][]f32{ in.q, in.k, in.v, in.gate, in.beta }) |*b, a| b.* = try t.upload(a); + defer for (&bufs) |*b| b.free(); + const state_bytes = sh.value_heads * d * d * 4; + var y = try t.alloc(sh.length * sh.value_heads * d * 4); + defer y.free(); + for ([_]i32{ -1, 0, 1, 2, 3 }) |f| { + // the first window: rows 0-3 from the input state, each row's state into `snaps` + var state = try t.upload(in.state); + defer state.free(); + var snaps = try t.alloc(rows * state_bytes); + defer snaps.free(); + var none = try t.upload(&[_]i32{-1}); + defer none.free(); + try window(t, sh, bufs, state, y, snaps, rig.at(none), 0, rows); + try t.stream.synchronize(); + // the copy: the start's bytes in a state of their own, then rows 4-7 from it + const first = try rig.download(u8, snaps); + defer gpa.free(first); + const after = try rig.download(u8, state); + defer gpa.free(after); + const start = if (f < 0) after else first[@as(usize, @intCast(f)) * state_bytes ..][0..state_bytes]; + var copied = try t.upload(start); + defer copied.free(); + var copied_snaps = try t.alloc(rows * state_bytes); + defer copied_snaps.free(); + try y.fill8(0); + try window(t, sh, bufs, copied, y, copied_snaps, rig.at(none), rows, rows); + try t.stream.synchronize(); + const want_y = try rig.download(u8, y); + defer gpa.free(want_y); + // the start row: rows 4-7 from the state the first window left, `from` naming row f of its snapshots in place + var word = try t.upload(&[_]i32{f}); + defer word.free(); + try y.fill8(0); + try window(t, sh, bufs, state, y, snaps, rig.at(word), rows, rows); + try t.stream.synchronize(); + const got_y = try rig.download(u8, y); + defer gpa.free(got_y); + try std.testing.expectEqualSlices(u8, want_y, got_y); + for ([_][2]DeviceBuffer{ .{ copied, state }, .{ copied_snaps, snaps } }) |pair| { + const want = try rig.download(u8, pair[0]); + defer gpa.free(want); + const got = try rig.download(u8, pair[1]); + defer gpa.free(got); + try std.testing.expectEqualSlices(u8, want, got); + } + } +} + +test "a prompt's recurrence a block a value head gives the bits of a wave a row (Flash Next: 16 key, 48 value heads)" { + const t = try Rig.open(1 << 30); + defer t.close(); + for ([_]Shape{ + .{ .length = 64, .key_heads = 2, .value_heads = 4 }, + .{ .length = 333, .key_heads = 2, .value_heads = 4 }, + .{ .length = 300, .key_heads = 16, .value_heads = 48 }, + }) |sh| { + const in = try Inputs.make(sh, 0xB10C + sh.length); + defer in.free(); + var bufs: [5]DeviceBuffer = undefined; + for (&bufs, [_][]f32{ in.q, in.k, in.v, in.gate, in.beta }) |*b, a| b.* = try t.upload(a); + defer for (&bufs) |*b| b.free(); + const state_bytes = sh.value_heads * d * d * 4; + var got: [2][2][]u8 = undefined; + for (0..2) |w| { + var state = try t.upload(in.state); + defer state.free(); + var y = try t.alloc(sh.length * sh.value_heads * d * 4); + defer y.free(); + try y.fill8(0xff); + // a wave a row: the same launch with snapshots asked for; a block a value head: none + var snaps = try t.alloc(if (w == 0) sh.length * state_bytes else 4); + defer snaps.free(); + const F = ?[*]f32; + try t.on.tf_gated_delta(@ptrFromInt(rig.at(bufs[0])), @ptrFromInt(rig.at(bufs[1])), @ptrFromInt(rig.at(bufs[2])), @ptrFromInt(rig.at(bufs[3])), @ptrFromInt(rig.at(bufs[4])), @ptrFromInt(rig.at(state)), @ptrFromInt(rig.at(y)), 1, @intCast(sh.length), @intCast(sh.key_heads), @intCast(sh.value_heads), d, d, t.stream.handle, if (w == 0) @as(F, @ptrFromInt(rig.at(snaps))) else null, 0); + try t.stream.synchronize(); + got[w][0] = try rig.download(u8, y); + got[w][1] = try rig.download(u8, state); + } + defer for (&got) |*g| for (g) |b| gpa.free(b); + for (0..2) |k| if (!std.mem.eql(u8, got[0][k], got[1][k])) { + std.debug.print("gdn prompt length={d} heads={d}: buffer {d} differs\n", .{ sh.length, sh.value_heads, k }); + return error.TestUnexpectedResult; + }; + } +} + +/// Rows a keep's inputs hold a layer (Flash Next's cache.max_window): a keep's row stride. +const keep_rows = 8; + +/// Layer `z`'s keep inputs as Flash Next's window writes them (k, v, gate, beta); rows past `rows` NaN, to show a read. +fn keepInputs(sh: Shape, in: Inputs, rows: usize, out: []f32) void { + @memset(out, std.math.nan(f32)); + const kr = sh.key_heads * d; + const vr = sh.value_heads * d; + const gr = sh.value_heads; + const v_at = keep_rows * kr; + const g_at = v_at + keep_rows * vr; + const b_at = g_at + keep_rows * gr; + @memcpy(out[0 .. rows * kr], in.k[0 .. rows * kr]); + @memcpy(out[v_at..][0 .. rows * vr], in.v[0 .. rows * vr]); + @memcpy(out[g_at..][0 .. rows * gr], in.gate[0 .. rows * gr]); + @memcpy(out[b_at..][0 .. rows * gr], in.beta[0 .. rows * gr]); +} + +test "a held window and its keep give the bits of today's window: its outputs, and the snapshot after row kept - 1" { + const t = try Rig.open(1 << 30); + defer t.close(); + // Flash Next's heads; two layers in one keep, each its own inputs and state, the states apart by a stride + const sh: Shape = .{ .length = keep_rows, .key_heads = 16, .value_heads = 48 }; + const layers = 2; + var ins: [layers]Inputs = undefined; + for (&ins, 0..) |*in, z| in.* = try Inputs.make(sh, 0xD25 + z); + defer for (ins) |in| in.free(); + const state_floats = sh.value_heads * d * d; + const state_bytes = state_floats * 4; + const state_stride = state_floats + 64; + const in_row = sh.key_heads * d + sh.value_heads * d + 2 * sh.value_heads; + const in_stride = keep_rows * in_row; + const vy_bytes = sh.length * sh.value_heads * d * 4; + const F = ?[*]f32; + const CF = ?[*]const f32; + for (1..keep_rows + 1) |rows| { + // today: each layer's window of `rows` rows writes its outputs, a snapshot after each row and the last state + var want_y: [layers][]u8 = undefined; + var want_snaps: [layers][]u8 = undefined; + for (0..layers) |z| { + const in = ins[z]; + var bufs: [5]DeviceBuffer = undefined; + for (&bufs, [_][]f32{ in.q, in.k, in.v, in.gate, in.beta }) |*b, a| b.* = try t.upload(a); + defer for (&bufs) |*b| b.free(); + var state = try t.upload(in.state); + defer state.free(); + var y = try t.alloc(vy_bytes); + defer y.free(); + try y.fill8(0); + var snaps = try t.alloc(rows * state_bytes); + defer snaps.free(); + try window(t, sh, bufs, state, y, snaps, 0, 0, rows); + try t.stream.synchronize(); + want_y[z] = try rig.download(u8, y); + want_snaps[z] = try rig.download(u8, snaps); + } + defer for (want_y, want_snaps) |a, b| { + gpa.free(a); + gpa.free(b); + }; + // the held window: the same outputs, the state untouched + for (0..layers) |z| { + const in = ins[z]; + var bufs: [5]DeviceBuffer = undefined; + for (&bufs, [_][]f32{ in.q, in.k, in.v, in.gate, in.beta }) |*b, a| b.* = try t.upload(a); + defer for (&bufs) |*b| b.free(); + var state = try t.upload(in.state); + defer state.free(); + var y = try t.alloc(vy_bytes); + defer y.free(); + try y.fill8(0); + try t.on.tf_gdn_hold(@ptrFromInt(rig.at(bufs[0])), @ptrFromInt(rig.at(bufs[1])), @ptrFromInt(rig.at(bufs[2])), @ptrFromInt(rig.at(bufs[3])), @ptrFromInt(rig.at(bufs[4])), @ptrFromInt(rig.at(state)), @ptrFromInt(rig.at(y)), @intCast(rows), @intCast(sh.key_heads), @intCast(sh.value_heads), d, d, t.stream.handle); + try t.stream.synchronize(); + const got_y = try rig.download(u8, y); + defer gpa.free(got_y); + try std.testing.expectEqualSlices(u8, want_y[z], got_y); + const held = try rig.download(f32, state); + defer gpa.free(held); + try std.testing.expectEqualSlices(u32, @ptrCast(in.state), @ptrCast(held)); + } + // a window of one row takes the plain scan, which stores its state: the snapshot's bits and the same outputs + if (rows == 1) for (0..layers) |z| { + const in = ins[z]; + var bufs: [5]DeviceBuffer = undefined; + for (&bufs, [_][]f32{ in.q, in.k, in.v, in.gate, in.beta }) |*b, a| b.* = try t.upload(a); + defer for (&bufs) |*b| b.free(); + var state = try t.upload(in.state); + defer state.free(); + var y = try t.alloc(vy_bytes); + defer y.free(); + try y.fill8(0); + try run(t, sh, bufs[0], bufs[1], bufs[2], bufs[3], bufs[4], state, y, 0, 1); + try t.stream.synchronize(); + const got_y = try rig.download(u8, y); + defer gpa.free(got_y); + try std.testing.expectEqualSlices(u8, want_y[z], got_y); + const stored = try rig.download(u8, state); + defer gpa.free(stored); + try std.testing.expectEqualSlices(u8, want_snaps[z][0..state_bytes], stored); + }; + // the keep of every count a window of `rows` can keep: kept 1 is a full reject (the pending token alone) + const packed_in = try gpa.alloc(f32, layers * in_stride); + defer gpa.free(packed_in); + for (0..layers) |z| keepInputs(sh, ins[z], rows, packed_in[z * in_stride ..][0..in_stride]); + var inputs = try t.upload(packed_in); + defer inputs.free(); + const states = try gpa.alloc(f32, layers * state_stride); + defer gpa.free(states); + for (1..rows + 1) |kept| { + @memset(states, std.math.nan(f32)); + for (0..layers) |z| @memcpy(states[z * state_stride ..][0..state_floats], ins[z].state); + var state = try t.upload(states); + defer state.free(); + try t.on.tf_gdn_keep(@as(F, @ptrFromInt(rig.at(state))), @intCast(state_stride), @as(CF, @ptrFromInt(rig.at(inputs))), @intCast(in_stride), keep_rows, @intCast(kept), layers, @intCast(sh.key_heads), @intCast(sh.value_heads), d, d, t.stream.handle); + try t.stream.synchronize(); + const got = try rig.download(u8, state); + defer gpa.free(got); + for (0..layers) |z| { + const want = want_snaps[z][(kept - 1) * state_bytes ..][0..state_bytes]; + std.testing.expectEqualSlices(u8, want, got[z * state_stride * 4 ..][0..state_bytes]) catch |err| { + std.debug.print("gdn keep rows={d} kept={d} layer={d}: state differs from the snapshot\n", .{ rows, kept, z }); + return err; + }; + // the stride's gap stays as it was: the keep stores the states alone + const gap = (z * state_stride + state_floats) * 4; + const gap_bytes = (state_stride - state_floats) * 4; + try std.testing.expectEqualSlices(u8, std.mem.sliceAsBytes(states)[gap..][0..gap_bytes], got[gap..][0..gap_bytes]); + } + } + } +} diff --git a/zig/src/hip/kernel_tests/ops.zig b/zig/src/hip/kernel_tests/ops.zig index 1c427945f3..c8c0edb578 100644 --- a/zig/src/hip/kernel_tests/ops.zig +++ b/zig/src/hip/kernel_tests/ops.zig @@ -8,7 +8,7 @@ const ops = @import("../ops/ops.zig"); const Tensor = ops.Tensor; const Kind = ops.Kind; -fn act(t: *const Rig) Kind { +pub fn act(t: *const Rig) Kind { return if (t.bf16) .bf16 else .f16; } @@ -21,7 +21,7 @@ fn round(t: *const Rig, v: f64) u16 { return @intCast((u + 0x7fff + ((u >> 16) & 1)) >> 16); } -fn tensor(b: anytype, kind: Kind) Tensor { +pub fn tensor(b: anytype, kind: Kind) Tensor { return .{ .ptr = at(b), .kind = kind }; } @@ -176,7 +176,7 @@ test "argmax and top-k follow torch's order: the larger value, then the lower in try std.testing.expectEqual(@as(i32, -1), gi[2 * stride]); } -test "the MoE route sorts pairs by expert, stably, into items of at most a tile" { +test "the MoE route sorts pairs by expert, stably, into items of at most a tile (one block, or three launches for a prompt)" { const t = try Rig.open(1 << 20); defer t.close(); const o = t.ops(&t.on); @@ -187,6 +187,11 @@ test "the MoE route sorts pairs by expert, stably, into items of at most a tile" .{ 64, 1000, 64 }, .{ 513, 11, 8 }, .{ 513, 2816, 8 }, + // a prompt's pairs: tf_moe_route_wide's three launches (2,048 pairs and more) + .{ 513, 2048, 128 }, + .{ 513, 45089, 128 }, + .{ 513, 90112, 128 }, + .{ 1024, 20000, 16 }, }) |shape| { const experts = shape[0]; const pairs = shape[1]; @@ -517,3 +522,7 @@ test "the linear attention's prompt conv and DeltaNet gates sit within 1e-5 of f try std.testing.expect(@abs(gb[i] - sigmoid(t.value(hb[i]))) < 1e-6); } } + +test { + _ = @import("ops_flashnext.zig"); +} diff --git a/zig/src/hip/kernel_tests/ops_flashnext.zig b/zig/src/hip/kernel_tests/ops_flashnext.zig new file mode 100644 index 0000000000..c063740104 --- /dev/null +++ b/zig/src/hip/kernel_tests/ops_flashnext.zig @@ -0,0 +1,103 @@ +//! Flash Next's top-k in parts and prompt router tile against tf_topk and the host's fma chain, byte for byte. +const std = @import("std"); +const rig = @import("rig.zig"); +const Rig = rig.Rig; +const gpa = rig.gpa; +const at = rig.at; +const kt = @import("ops.zig"); +const act = kt.act; +const tensor = kt.tensor; + +test "top-k in parts gives tf_topk's ids, values and order byte for byte (Flash Next draft and full vocabularies)" { + const t = try Rig.open(1 << 20); + defer t.close(); + const o = t.ops(&t.on); + var rng: rig.Rng = .{ .state = 0x7095 }; + const stride = 64; + for ([_]usize{ 8192, 79591, 248320 }) |n| for ([_]u8{ 0, 1, 2, 3 }) |shape| { + const rows = 4; + const hl = try gpa.alloc(u16, rows * n); + defer gpa.free(hl); + for (hl) |*x| x.* = t.bits(rng.unit() * 8.0); + switch (shape) { + // a few distinct values: ties at the k-th across every part + 1 => for (hl, 0..) |*x, j| { + x.* = t.bits(@floatFromInt((j * 7919) % 5)); + }, + // NaN, infinities and both zeros among the largest + 2 => for (0..rows) |r| { + hl[r * n + 3] = 0x7fc0; + hl[r * n + n - 1] = 0x7f80; + hl[r * n + n / 2] = 0xff80; + hl[r * n + 11] = 0x8000; + hl[r * n + 12] = 0; + }, + // one value everywhere: every entry ties + 3 => @memset(hl, t.bits(1.5)), + else => {}, + } + var logits = try t.upload(hl); + defer logits.free(); + const ks = [_]i32{ 28, 1, 0, 64 }; + var dev_ks = try t.upload(&ks); + defer dev_ks.free(); + var got: [2][2][]u8 = undefined; + for (0..2) |v| { + var ids = try t.alloc(rows * stride * 4); + defer ids.free(); + var vals = try t.alloc(rows * stride * 2); + defer vals.free(); + try ids.fill8(0xff); + try vals.fill8(0xff); + if (v == 0) { + try t.on.tf_topk_rows(@ptrFromInt(at(logits)), rows, @intCast(n), @ptrFromInt(at(dev_ks)), stride, @ptrFromInt(at(ids)), @ptrFromInt(at(vals)), t.stream.handle); + } else try o.topkRows(tensor(logits, act(t)), rows, n, at(dev_ks), stride, at(ids), at(vals)); + try t.stream.synchronize(); + got[v][0] = try rig.download(u8, ids); + got[v][1] = try rig.download(u8, vals); + } + defer for (&got) |*g| for (g) |b| gpa.free(b); + for (0..2) |k| if (!std.mem.eql(u8, got[0][k], got[1][k])) { + std.debug.print("top-k parts n={d} shape={d}: buffer {d} differs\n", .{ n, shape, k }); + return error.TestUnexpectedResult; + }; + }; +} + +test "the prompt router tile: every logit one fp32 fma chain over k in order, the bytes of the host's chain" { + const t = try Rig.open(1 << 20); + defer t.close(); + var o = t.ops(&t.on); + o.prefill = true; + var rng: rig.Rng = .{ .state = 0x7071E }; + const d: usize = 2560; + const e: usize = 513; + // the rows: two tiles and a part, and one row past a full tile of 128 + for ([_]usize{ 300, 129 }) |rows| { + const hx = try gpa.alloc(u16, rows * d); + defer gpa.free(hx); + for (hx) |*v| v.* = t.bits(rng.unit() * 2.0); + const hw = try gpa.alloc(f32, e * d); + defer gpa.free(hw); + for (hw) |*v| v.* = @bitCast(@as(u32, rig.bf16Bits(rng.unit() / 8.0)) << 16); + var x = try t.upload(hx); + defer x.free(); + var w = try t.upload(hw); + defer w.free(); + var out = try t.alloc(rows * e * 4); + defer out.free(); + try o.moeRouter(tensor(x, act(t)), at(w), at(out), rows, d, e); + try t.stream.synchronize(); + const got = try rig.download(f32, out); + defer gpa.free(got); + // every expert of a sample of rows (each tile's first and last, every 37th, the last three): the host is slow + for (0..rows) |r| if (r % 37 == 0 or r % 128 == 0 or r % 128 == 127 or r + 3 >= rows) for (0..e) |c| { + var acc: f32 = 0; + for (0..d) |k| acc = @mulAdd(f32, @floatCast(t.value(hx[r * d + k])), hw[c * d + k], acc); + if (@as(u32, @bitCast(acc)) != @as(u32, @bitCast(got[r * e + c]))) { + std.debug.print("router tile rows={d}: logit ({d}, {d}) {e} where the chain gives {e}\n", .{ rows, r, c, got[r * e + c], acc }); + return error.TestUnexpectedResult; + } + }; + } +} diff --git a/zig/src/hip/kernel_tests/served_plans.bin b/zig/src/hip/kernel_tests/served_plans.bin new file mode 100644 index 0000000000..1a78a5114f Binary files /dev/null and b/zig/src/hip/kernel_tests/served_plans.bin differ diff --git a/zig/src/hip/launches.zig b/zig/src/hip/launches.zig index ace7c08e7c..c029c28961 100644 --- a/zig/src/hip/launches.zig +++ b/zig/src/hip/launches.zig @@ -8,7 +8,7 @@ const Module = @import("module.zig").Module; const Function = @import("module.zig").Function; const Stream = @import("stream.zig").Stream; const caps = @import("caps.zig"); -const affine = @import("launches/affine.zig"); +pub const affine = @import("launches/affine.zig"); const util = @import("launches/util.zig"); @@ -38,7 +38,7 @@ const plan = @import("launches/plan.zig"); const elementwise = @import("launches/elementwise.zig"); const draw = @import("launches/draw.zig"); const tp = @import("launches/tp.zig"); -const flashnext = @import("launches/flashnext.zig"); +pub const flashnext = @import("launches/flashnext.zig"); const mamba = @import("launches/mamba.zig"); const nemotron_moe = @import("launches/nemotron_moe.zig"); @@ -63,6 +63,9 @@ pub const Launcher = struct { gdn_gate: Triple, gated_delta_tile: [2]Function, // dk 128, 16 gated_delta_wave: [2]Function, + gdn_hold: [2]Function, // dk 128, 16: a verify window that holds its state (no snapshot, no store) + gdn_keep: [2]Function, // dk 128, 16: a keep's run of every DeltaNet layer's state through its kept rows + gdn_prompt: Function, // dk = dv = 128, a prompt's rows, half a value head a block score_keys: Triple, // by cache kind apply_values: Triple, causal: Triple, @@ -107,11 +110,15 @@ pub const Launcher = struct { const Decode = struct { router: [2]Function, // fp16, bf16 + router_select: [2]Function, // fp16, bf16 x; bf16 rows tail: Function, conv_split: Function, rms2: Function, gnorm_out: Function, select: Function, + select_rows: Function, + /// A MoE call's live experts' down codes read beside its gate and up (tf_moe_prefetch). + prefetch: Function, }; const Ops = struct { @@ -130,10 +137,16 @@ pub const Launcher = struct { argmax_part: Function, argmax_join: Function, topk: Function, + topk_part: Function, + topk_join: Function, conv_prefill: Function, + gdn_prompt_prep: Function, gdn_gate_prefill: Function, dense_rows: Function, moe_route: Function, + route_count: Function, + route_scan: Function, + route_scatter: Function, router_rows: [2]Function, // fp16, bf16 router_tile: [2]Function, router_small: [2]Function, @@ -168,7 +181,7 @@ pub const Launcher = struct { const pl = l.mods[@backingInt(kernels.Group.plan)]; l.fuse = choices.fuse; l.wide = choices.wide; - l.dec = .{ .router = .{ try dec.function("tf_router_decode_f16"), try dec.function("tf_router_decode_bf16") }, .tail = try dec.function("tf_tail"), .conv_split = try dec.function("tf_conv_split"), .rms2 = try dec.function("tf_rms2"), .gnorm_out = try dec.function("tf_gnorm_out"), .select = try dec.function("tf_select_decode") }; + l.dec = .{ .router = .{ try dec.function("tf_router_decode_f16"), try dec.function("tf_router_decode_bf16") }, .router_select = .{ try dec.function("tf_router_select_f16"), try dec.function("tf_router_select_bf16") }, .tail = try dec.function("tf_tail"), .conv_split = try dec.function("tf_conv_split"), .rms2 = try dec.function("tf_rms2"), .gnorm_out = try dec.function("tf_gnorm_out"), .select = try dec.function("tf_select_decode"), .select_rows = try dec.function("tf_select_rows"), .prefetch = try dec.function("tf_moe_prefetch") }; l.plan = .{ .kv_write = try pl.function("tf_plan_kv_write"), .kv_write_act = try pl.function("tf_plan_kv_write_act"), @@ -202,10 +215,16 @@ pub const Launcher = struct { .argmax_part = try ops.function("tf_argmax_part"), .argmax_join = try ops.function("tf_argmax_join"), .topk = try ops.function("tf_topk"), + .topk_part = try ops.function("tf_topk_part"), + .topk_join = try ops.function("tf_topk_join"), .conv_prefill = try ops.function("tf_conv_prefill"), + .gdn_prompt_prep = try ops.function("tf_gdn_prompt_prep"), .gdn_gate_prefill = try ops.function("tf_gdn_gate_prefill"), .dense_rows = try ops.function("tf_dense_rows"), .moe_route = try ops.function("tf_moe_route"), + .route_count = try ops.function("tf_route_count"), + .route_scan = try ops.function("tf_route_scan"), + .route_scatter = try ops.function("tf_route_scatter"), .router_rows = .{ try ops.function("tf_router_rows_f16"), try ops.function("tf_router_rows_bf16") }, .router_tile = .{ try ops.function("tf_router_tile_f16"), try ops.function("tf_router_tile_bf16") }, .router_small = .{ try ops.function("tf_router_small_f16"), try ops.function("tf_router_small_bf16") }, @@ -247,12 +266,15 @@ pub const Launcher = struct { try act.function(ns ++ "15gdn_gate_kernelI12hip_bfloat16EEvPKT_S5_PKfS7_PfS8_ii"), }; l.gated_delta_tile = .{ - try gd.function(ns ++ "16gated_delta_tileILi128ELi8ELi16EEEvPKfS3_S3_S3_S3_PfS4_iiiiS4_"), - try gd.function(ns ++ "16gated_delta_tileILi16ELi8ELi16EEEvPKfS3_S3_S3_S3_PfS4_iiiiS4_"), + try gd.function(ns ++ "16gated_delta_tileILi128ELi8ELi16EEEvPKfS3_S3_S3_S3_PfS4_iiiiS4_PKi"), + try gd.function(ns ++ "16gated_delta_tileILi16ELi8ELi16EEEvPKfS3_S3_S3_S3_PfS4_iiiiS4_PKi"), }; + l.gdn_hold = .{ try gd.function("tf_gdn_hold_128"), try gd.function("tf_gdn_hold_16") }; + l.gdn_keep = .{ try gd.function("tf_gdn_keep_128"), try gd.function("tf_gdn_keep_16") }; + l.gdn_prompt = try gd.function("tf_gdn_prompt_128"); l.gated_delta_wave = .{ - try gd.function(ns ++ "18gated_delta_kernelILi128EEEvPKfS3_S3_S3_S3_PfS4_iiiiS4_"), - try gd.function(ns ++ "18gated_delta_kernelILi16EEEvPKfS3_S3_S3_S3_PfS4_iiiiS4_"), + try gd.function(ns ++ "18gated_delta_kernelILi128EEEvPKfS3_S3_S3_S3_PfS4_iiiiS4_PKi"), + try gd.function(ns ++ "18gated_delta_kernelILi16EEEvPKfS3_S3_S3_S3_PfS4_iiiiS4_PKi"), }; l.score_keys = .{ try att.function("_Z10score_keysI6__halfEvPKfPKT_PfiiiifixxxPKi"), @@ -282,6 +304,7 @@ pub const Launcher = struct { const dot2 = l.mods[@backingInt(kernels.Group.affine_dot2)]; l.affine = try affine.Kernels.load(tiles, dot2, caps.Caps.of(kernels.arch) orelse return error.Invalid, choices.products); try l.affine.fillByteLut(r, dot2); + try l.affine.fillHcGate(r); l.fnx = try flashnext.Fns.load(l.mods[@backingInt(kernels.Group.flashnext)]); return l; } @@ -299,6 +322,7 @@ pub const Launcher = struct { pub const tf_conv_rows = conv.tf_conv_rows; pub const tf_conv_split = conv.tf_conv_split; pub const tf_conv_prefill = conv.tf_conv_prefill; + pub const tf_gdn_prompt_prep = conv.tf_gdn_prompt_prep; pub const tf_qk_rope = rope.tf_qk_rope; pub const tf_rope_decode = rope.tf_rope_decode; pub const tf_rope_prefill = rope.tf_rope_prefill; @@ -306,10 +330,15 @@ pub const Launcher = struct { pub const routerWith = moe.routerWith; pub const routerWindow = moe.routerWindow; pub const tf_moe_router = moe.tf_moe_router; + pub const routerSelect = moe.routerSelect; pub const tf_moe_select = moe.tf_moe_select; pub const tf_moe_act = moe.tf_moe_act; + pub const tf_moe_prefetch = moe.tf_moe_prefetch; pub const tf_moe_combine = moe.tf_moe_combine; pub const tf_moe_route = moe.tf_moe_route; + pub const tf_moe_route_wide = moe.tf_moe_route_wide; + pub const routeScratch = moe.routeScratch; + pub const route_seg = moe.route_seg; pub const tf_causal = attention.tf_causal; pub const tf_attn_gate = attention.tf_attn_gate; pub const tf_kv_write = attention.tf_kv_write; @@ -317,6 +346,7 @@ pub const Launcher = struct { pub const tf_argmax_rows = draw.tf_argmax_rows; pub const tf_argmax_parts = draw.tf_argmax_parts; pub const tf_topk_rows = draw.tf_topk_rows; + pub const tf_topk_parts = draw.tf_topk_parts; pub const tf_add_wide = tp.tf_add_wide; pub const tf_moe_localize = tp.tf_moe_localize; pub const tf_moe_foreign_items = tp.tf_moe_foreign_items; @@ -325,6 +355,8 @@ pub const Launcher = struct { pub const pagedCausal = attention.pagedCausal; pub const tf_gdn_gate = recurrence.tf_gdn_gate; pub const tf_gated_delta = recurrence.tf_gated_delta; + pub const tf_gdn_hold = recurrence.tf_gdn_hold; + pub const tf_gdn_keep = recurrence.tf_gdn_keep; pub const planKvWrite = plan.planKvWrite; pub const planCausal = plan.planCausal; pub const planCausalAs = plan.planCausalAs; @@ -347,14 +379,18 @@ pub const Launcher = struct { pub const tf_dense_rows = elementwise.tf_dense_rows; pub const fn_hc_norm = flashnext.hcNorm; pub const fn_hc_norm_shares = flashnext.hcNormShares; + pub const fn_hc_norm_moe = flashnext.hcNormMoe; + pub const fn_hc_norm_moe_v = flashnext.hcNormMoeV; pub const fn_hc_gates = flashnext.hcGates; pub const fn_hc_mix = flashnext.hcMix; + pub const fn_hc_mix_scalar = flashnext.hcMixScalar; pub const fn_rms_wide = flashnext.rmsWide; pub const fn_ple_gate = flashnext.pleGate; pub const fn_ple_conv = flashnext.pleConv; pub const fn_ngram_ids = flashnext.ngramIds; pub const fn_idx_pool = flashnext.idxPool; pub const fn_idx_pool_at = flashnext.idxPoolAt; + pub const fn_qsa_prep = flashnext.qsaPrep; pub const fn_idx_scores = flashnext.idxScores; pub const fn_idx_select = flashnext.idxSelect; pub const fn_sparse_attention = flashnext.sparseAttention; diff --git a/zig/src/hip/launches/affine.zig b/zig/src/hip/launches/affine.zig index 4378596dc7..076da6bc1f 100644 --- a/zig/src/hip/launches/affine.zig +++ b/zig/src/hip/launches/affine.zig @@ -14,6 +14,9 @@ const registry = @import("core").registry; const quant = @import("core").quant; const tuning = @import("../tuning/tuning.zig"); const mlx_entries = @import("mlx_entries.zig"); +const affine_stream = @import("affine_stream.zig"); +const affine_load = @import("affine_load.zig"); +const affine_matrix = @import("affine_matrix.zig"); const Error = runtime.Error; @@ -54,6 +57,8 @@ pub const StreamSides = extern struct { out_half: c_int = 0, pair_cols: c_int = 0, limit: f32 = 0, + /// > 1: the launch's row blocks are the grid's x and its column blocks its y (stream.hpp stream_tile) + row_blocks: c_int = 0, }; /// One side of a group: its matrix and where its (rows, n) output goes. @@ -82,17 +87,26 @@ pub const Registry = registry.Registry(Launch); pub const Entry = Registry.E; pub const bit_widths = [_]c_int{ 2, 3, 4, 5, 6, 8 }; -const row_counts = [_]u8{ 1, 2, 4, 8 }; -const piece_counts = [_]u8{ 1, 2, 4 }; +pub const row_counts = [_]u8{ 1, 2, 4, 8 }; +pub const piece_counts = [_]u8{ 1, 2, 4 }; pub const lane_rows = 8; // kLaneRows pub const lane_group_max = 128; const fast_n = 256; -pub const stream_cbs = [_]c_int{ 2, 4, 8 }; // columns a lane carries in the stream tile +pub const stream_cbs = [_]c_int{ 1, 2, 4, 8 }; // columns a lane carries in the stream tile (1: plain products only) pub const stream_rows = [_]u8{ 1, 2, 4 }; // its row counts: columns * rows <= 16 pub const stream_waves = 4; // kStreamWaves pub const streams_wanted = 3000; // kStreamWavesWanted pub const stream_code_words = 32; // kStreamCodeWords +pub const stream_pair_code_words = affine_stream.stream_pair_code_words; +pub const stream_routed_cb_top = affine_stream.stream_routed_cb_top; +pub const stream_list_blocks = affine_stream.stream_list_blocks; +pub const stream_one_col_n = affine_stream.stream_one_col_n; +pub const HeldPick = affine_stream.HeldPick; +pub const held_wide_n = affine_stream.held_wide_n; +pub const held_narrow_lo = affine_stream.held_narrow_lo; +pub const held_narrow_hi = affine_stream.held_narrow_hi; +pub const heldPick = affine_stream.heldPick; /// The K-parallel tiles of a short prompt: cb columns a lane set, r rows a pass over up to rb row blocks. pub const KpTile = struct { cb: c_int, r: c_int, waves: c_int, rb: c_int, loop: bool = true }; @@ -132,11 +146,27 @@ pub const Kernels = struct { /// The same tile with Nemotron's relu^2 as its epilogue, and with two such products in one launch. relu2: [bit_widths.len][stream_rows.len][stream_cbs.len]?Function, relu2_pair: [bit_widths.len][stream_rows.len][stream_cbs.len]?Function, + /// The 5- to 8-row routed 4-bit work lists (stream.hpp stream_list), 4-row tile: [0] pair CB 2, [1] plain CB 4. + stream_list: [2]Function, /// Off keeps the decode tiles before the stream tile (the policy's reference switch). stream_on: bool, + /// A test's forced columns a lane (a stream_cbs value; 0: the rule), where the shape takes it. + stream_cb_force: c_int, + /// The held-codes 4-bit plain tile (stream.hpp HELD) by rows (4, 8) and columns a lane; `heldPick` picks it. + held: [2][stream_cbs.len]?Function, block: [bit_widths.len]Function, gemm: [bit_widths.len]Function, wmma_gemm: [bit_widths.len]Function, + /// Qwen3.8-Flash-Next's routed gate and up of a prompt with the activation as epilogue (tiles/moe_gemm.hpp); gfx11. + moe_gu: ?Function, + /// The same tile's routed down of a prompt, fp32 out. + moe_down: ?Function, + /// A prompt's plain 4-bit group-32 products at each of dense_ks (tiles/dense_gemm.hpp); gfx11. + dense: [dense_ks.len]?Function, + /// hc up (K 320) on the dense tile with tf_fn_hc_mix in its epilogue (tf_affine_dense_hcmix); gfx11. + dense_hcmix: ?Function, + /// Fills the tile's gate table (rnd(sigmoid(g)) for every bf16 g) once a device; gfx11. + hc_gate_fill: ?Function, kp: [bit_widths.len][kp_tiles.len]Function, span: [2]Function, fold: Function, @@ -146,96 +176,22 @@ pub const Kernels = struct { fill: Function, reg: Registry, - /// `tiles` holds dot2_tiles.hip's kernels, `dot2` dot2.hip's; bf16 on the WMMA build, fp16 on RDNA2. - pub fn load(tiles_obj: Module, dot2_obj: Module, caps: Caps, choices: Choices) Error!Kernels { - var k: Kernels = undefined; - const wmma = caps.act == .bf16; - k.caps = caps; - k.wmma = wmma; - k.matrix = wmma and caps.matrix == .wmma11; - k.mode = choices.matrix; - k.tile = if (choices.gemm) .gemm else .block; - k.stream_on = choices.stream; - k.reg = Registry.init(tableFor(caps), &mlx_entries.all); - k.reg.verify(k.env(), .mlx) catch return error.Invalid; - // the GEMM tile's rows of x a lane keeps (tiles/gemm.hpp GemmShape): 8 for BF16, 16 for FP16 - if (wmma) try k.resolve("7DotBF16", "Li8E", tiles_obj) else try k.resolve("6DotF16", "Li16E", tiles_obj); - const r = "_ZN2tf4rocm"; - k.span = .{ try dot2_obj.function(r ++ "16affine_dot2_spanILi1EEEvNS0_6AffineEPfi"), try dot2_obj.function(r ++ "16affine_dot2_spanILi8EEEvNS0_6AffineEPfi") }; - k.fold = try dot2_obj.function(r ++ "16affine_dot2_foldEPKfNS0_10GroupTableES3_Pfiii"); - k.wide = try dot2_obj.function(r ++ "16affine_dot2_wideENS0_6AffineE"); - k.tiled = try dot2_obj.function(r ++ "17affine_dot2_tiledENS0_6AffineE"); - k.reference = try dot2_obj.function(r ++ "18affine_dot2_kernelENS0_6AffineE"); - k.fill = try dot2_obj.function(r ++ "13fill_byte_lutEP6__half"); - return k; - } - - fn resolve(k: *Kernels, comptime dot: []const u8, comptime shape: []const u8, m: Module) Error!void { - @setEvalBranchQuota(300_000); - inline for (bit_widths, 0..) |bits, b| { - k.block[b] = try m.function(std.fmt.comptimePrint("_ZN2tf4rocm17affine_dot2_blockINS0_{s}ELi{d}EEEvNS0_6AffineE", .{ dot, bits })); - if (k.matrix) k.wmma_gemm[b] = try m.function(std.fmt.comptimePrint("_ZN2tf4rocm16affine_wmma_gemmILi{d}EEEvNS0_6AffineE", .{bits})); - k.gemm[b] = try m.function(std.fmt.comptimePrint("_ZN2tf4rocm17affine_gemm_blockINS0_{s}ELi{d}E{s}EEvNS0_6AffineE", .{ dot, bits, shape })); - inline for (kp_tiles, 0..) |t, i| { - k.kp[b][i] = try m.function(std.fmt.comptimePrint("_ZN2tf4rocm14affine_gemm_kpINS0_{s}ELi{d}ELi{d}ELi{d}ELi{d}ELi{d}ELb{d}EEEvNS0_6AffineE", .{ dot, bits, t.cb, t.r, t.waves, t.rb, @intFromBool(t.loop) })); - } - inline for (piece_counts, 0..) |pieces, p| { - k.row[b][p] = try m.function(std.fmt.comptimePrint("_ZN2tf4rocm15affine_dot2_rowINS0_{s}ELi{d}ELi{d}EEEvNS0_6AffineEi", .{ dot, bits, pieces })); - inline for (row_counts, 0..) |rows, r| { - k.lanes[b][r][p] = try m.function(std.fmt.comptimePrint("_ZN2tf4rocm17affine_dot2_lanesINS0_{s}ELi{d}ELi{d}ELi{d}EEEvNS0_6AffineE", .{ dot, bits, rows, pieces })); - } - } - inline for (stream_rows, 0..) |rows, r| { - inline for (stream_cbs, 0..) |cb, c| { - k.stream[b][r][c] = if (cb * rows <= 16) - try m.function(std.fmt.comptimePrint("_ZN2tf4rocm18affine_dot2_streamINS0_{s}ELi{d}ELi{d}ELi{d}ELb0EEEvNS0_6AffineENS0_11StreamSidesEii", .{ dot, bits, rows, cb })) - else - null; - k.pairs[b][r][c] = if (cb * rows <= 16) - try m.function(std.fmt.comptimePrint("_ZN2tf4rocm18affine_dot2_streamINS0_{s}ELi{d}ELi{d}ELi{d}ELb1EEEvNS0_6AffineENS0_11StreamSidesEii", .{ dot, bits, rows, cb })) - else - null; - k.relu2[b][r][c] = if (cb * rows <= 16) - try m.function( - std.fmt.comptimePrint("_ZN2tf4rocm24affine_dot2_stream_relu2INS0_{s}" ++ - "ELi{d}ELi{d}ELi{d}EEEvNS0_6AffineENS0_11StreamSidesEii", .{ dot, bits, rows, cb }), - ) - else - null; - k.relu2_pair[b][r][c] = if (cb * rows <= 16) - try m.function( - std.fmt.comptimePrint("_ZN2tf4rocm29affine_dot2_stream_relu2_pairINS0_{s}" ++ - "ELi{d}ELi{d}ELi{d}EEEvNS0_6AffineES3_iii", .{ dot, bits, rows, cb }), - ) - else - null; - } - } - } - } - - /// fp16(bf16(code)) for every byte into the module's constant table: the RDNA2 fp16 tiles read it. Once a device. - pub fn fillByteLut(k: *const Kernels, r: *const runtime.Runtime, dot2_obj: Module) Error!void { - if (k.wmma) return; - const lut = try dot2_obj.global("_ZN2tf4rocm8kByteF16E"); - var args: hl.Args = .{}; - try args.add(lut.address); - try hl.launch(k.fill, .{ .grid = .{ .x = 1 }, .block = .{ .x = 256 } }, .{ .r = r, .handle = null }, &args); - try runtime.check(r.api.hipStreamSynchronize(null)); - } + pub const load = affine_load.load; + pub const fillByteLut = affine_load.fillByteLut; + pub const fillHcGate = affine_load.fillHcGate; /// Launches on `s`; the counting stream runs nothing. - fn go(r: *const runtime.Runtime, f: Function, grid: hl.Dim3, block: hl.Dim3, s: abi.Stream, args: *hl.Args) Error!void { + pub fn go(r: *const runtime.Runtime, f: Function, grid: hl.Dim3, block: hl.Dim3, s: abi.Stream, args: *hl.Args) Error!void { if (s == util.counting) return; try hl.launch(f, .{ .grid = grid, .block = block }, .{ .r = r, .handle = s }, args); } - fn refuse(what: []const u8) Error { + pub fn refuse(what: []const u8) Error { std.log.err("affine: {s}", .{what}); return error.Invalid; } - fn bitIndex(bits: c_int) ?usize { + pub fn bitIndex(bits: c_int) ?usize { return std.mem.indexOfScalar(c_int, &bit_widths, bits); } @@ -247,7 +203,7 @@ pub const Kernels = struct { }; } - fn cdiv(n: c_int, by: c_int) c_uint { + pub fn cdiv(n: c_int, by: c_int) c_uint { return @intCast(@divTrunc(n + by - 1, by)); } @@ -320,64 +276,13 @@ pub const Kernels = struct { /// The stream tile on `total_n` columns (a group's sum); `sides` counts them off block by block when it has any. pub fn streamGo(k: *const Kernels, r: *const runtime.Runtime, a: Arg, sides_in: StreamSides, total_n: c_int, items: c_int, s: abi.Stream) Error!void { - return k.streamWith(r, a, sides_in, total_n, items, s, false); + return affine_stream.streamWith(k, r, a, sides_in, total_n, items, s, false); } /// `streamGo` with Nemotron's relu^2 as the epilogue: `a.out16` takes relu(round(sum))^2 in the activation type. pub fn relu2Go(k: *const Kernels, r: *const runtime.Runtime, a: Arg, items: c_int, s: abi.Stream) Error!void { if (a.out16 == 0 or a.out != 0) return refuse("relu2 output"); - return k.streamWith(r, a, .{}, a.n, items, s, true); - } - - fn streamWith( - k: *const Kernels, - r: *const runtime.Runtime, - a: Arg, - sides_in: StreamSides, - total_n: c_int, - items: c_int, - s: abi.Stream, - relu2: bool, - ) Error!void { - const b = bitIndex(a.bits).?; - var sides = sides_in; - // a pair's lane carries half as many output columns: a gate column and its up column make one - const pair_div: c_int = if (sides.pair_cols > 0) 2 else 1; - var lpc_log2: u5 = 0; - while ((@as(c_int, 1) << lpc_log2) < (a.k >> 5) and lpc_log2 < 5) lpc_log2 += 1; - const ri: usize = if (a.m == 1) 0 else if (a.m == 2) 1 else 2; - // the widest column count that still fills the card with waves, within the registers the lane's code words take - var pick: usize = 0; - var c: usize = stream_cbs.len; - while (c > 0) { - c -= 1; - if (stream_cbs[c] * stream_rows[ri] > 16 or stream_cbs[c] * a.bits > stream_code_words) continue; - pick = c; - const per_block: c_int = stream_waves * (@as(c_int, 32) >> lpc_log2) * @divExact(stream_cbs[c], pair_div); - if (@as(u64, cdiv(total_n, per_block)) * stream_waves * @as(u64, @intCast(items)) * cdiv(a.m, stream_rows[ri]) >= streams_wanted) break; - } - const per_block: c_int = stream_waves * (@as(c_int, 32) >> lpc_log2) * @divExact(stream_cbs[pick], pair_div); - var blocks: c_uint = cdiv(total_n, per_block); - if (sides.count > 0) { - blocks = 0; - for (0..@intCast(sides.count)) |i| { - sides.first[i] = @intCast(blocks); - blocks += cdiv(sides.n[i], per_block); - } - sides.first[@intCast(sides.count)] = @intCast(blocks); - } - var args: hl.Args = .{}; - try args.add(a); - try args.add(sides); - try args.add(@as(c_int, lpc_log2)); - try args.add(@as(c_int, switch (a.group) { - 32 => 0, - 64 => 1, - else => 2, - })); - const table = if (sides.pair_cols > 0) &k.pairs else if (relu2) &k.relu2 else &k.stream; - const f = table[b][ri][pick].?; - try go(r, f, .{ .x = blocks, .y = cdiv(a.m, stream_rows[ri]), .z = @intCast(items) }, .{ .x = 32 * stream_waves }, s, &args); + return affine_stream.streamWith(k, r, a, .{}, a.n, items, s, true); } /// One row on the row tile: a lane owns a group, a wave reads a column's row in one run. @@ -451,6 +356,18 @@ pub const Kernels = struct { try go(r, f, .{ .x = cdiv(a.n, 128), .y = cdiv(a.m, 128), .z = @intCast(items) }, .{ .x = 256 }, s, &args); } + pub const MoeShape = affine_matrix.MoeShape; + pub const moe_gu_shape = affine_matrix.moe_gu_shape; + pub const moe_down_shape = affine_matrix.moe_down_shape; + pub const moeGateUpTakes = affine_matrix.moeGateUpTakes; + pub const moeDownTakes = affine_matrix.moeDownTakes; + pub const moeGateUp = affine_matrix.moeGateUp; + pub const moeDown = affine_matrix.moeDown; + pub const dense_ks = affine_matrix.dense_ks; + pub const denseIndex = affine_matrix.denseIndex; + pub const denseGo = affine_matrix.denseGo; + pub const denseHcMixGo = affine_matrix.denseHcMixGo; + /// K-parallel tile `tier` (an index of kp_tiles) of a short prompt. pub fn kpGo(k: *const Kernels, r: *const runtime.Runtime, a: Arg, s: abi.Stream, items: c_int, tier: usize) Error!void { const b = bitIndex(a.bits) orelse return refuse("bits"); @@ -596,4 +513,7 @@ test "the lane groups of a row tile" { test { _ = mlx_entries; + _ = affine_stream; + _ = affine_load; + _ = affine_matrix; } diff --git a/zig/src/hip/launches/affine_load.zig b/zig/src/hip/launches/affine_load.zig new file mode 100644 index 0000000000..680f204096 --- /dev/null +++ b/zig/src/hip/launches/affine_load.zig @@ -0,0 +1,128 @@ +//! Resolving the affine kernels from the tile and dot2 code objects, and their once-a-device tables. + +const std = @import("std"); +const runtime = @import("../runtime.zig"); +const hl = @import("../launch.zig"); +const Module = @import("../module.zig").Module; +const Caps = @import("../caps.zig").Caps; +const mlx_entries = @import("mlx_entries.zig"); +const affine = @import("affine.zig"); + +const Error = runtime.Error; +const Kernels = affine.Kernels; +const Choices = affine.Choices; +const Registry = affine.Registry; +const tableFor = Kernels.tableFor; +const bit_widths = affine.bit_widths; +const row_counts = affine.row_counts; +const piece_counts = affine.piece_counts; +const stream_cbs = affine.stream_cbs; +const stream_rows = affine.stream_rows; +const kp_tiles = affine.kp_tiles; +const dense_ks = Kernels.dense_ks; + +/// `tiles` holds dot2_tiles.hip's kernels, `dot2` dot2.hip's; bf16 on the WMMA build, fp16 on RDNA2. +pub fn load(tiles_obj: Module, dot2_obj: Module, caps: Caps, choices: Choices) Error!Kernels { + var k: Kernels = undefined; + const wmma = caps.act == .bf16; + k.caps = caps; + k.wmma = wmma; + k.matrix = wmma and caps.matrix == .wmma11; + k.mode = choices.matrix; + k.tile = if (choices.gemm) .gemm else .block; + k.stream_on = choices.stream; + k.stream_cb_force = 0; + k.reg = Registry.init(tableFor(caps), &mlx_entries.all); + k.reg.verify(k.env(), .mlx) catch return error.Invalid; + // the GEMM tile's rows of x a lane keeps (tiles/gemm.hpp GemmShape): 8 for BF16, 16 for FP16 + if (wmma) try resolve(&k, "7DotBF16", "Li8E", tiles_obj) else try resolve(&k, "6DotF16", "Li16E", tiles_obj); + const r = "_ZN2tf4rocm"; + k.span = .{ try dot2_obj.function(r ++ "16affine_dot2_spanILi1EEEvNS0_6AffineEPfi"), try dot2_obj.function(r ++ "16affine_dot2_spanILi8EEEvNS0_6AffineEPfi") }; + k.fold = try dot2_obj.function(r ++ "16affine_dot2_foldEPKfNS0_10GroupTableES3_Pfiii"); + k.wide = try dot2_obj.function(r ++ "16affine_dot2_wideENS0_6AffineE"); + k.tiled = try dot2_obj.function(r ++ "17affine_dot2_tiledENS0_6AffineE"); + k.reference = try dot2_obj.function(r ++ "18affine_dot2_kernelENS0_6AffineE"); + k.fill = try dot2_obj.function(r ++ "13fill_byte_lutEP6__half"); + k.moe_gu = if (k.matrix) try tiles_obj.function(r ++ "18affine_wmma_moe_guILi4EEEvNS0_6AffineEf") else null; + k.moe_down = if (k.matrix) try tiles_obj.function(r ++ "20affine_wmma_moe_downILi4EEEvNS0_6AffineE") else null; + k.dense_hcmix = if (k.matrix) try tiles_obj.function("tf_affine_dense_hcmix") else null; + k.hc_gate_fill = if (k.matrix) try tiles_obj.function("tf_hc_gate_fill") else null; + inline for (dense_ks, 0..) |dk, i| { + k.dense[i] = if (k.matrix) try tiles_obj.function(std.fmt.comptimePrint(r ++ "17affine_wmma_denseILi{d}EEEvNS0_6AffineE", .{dk})) else null; + } + return k; +} + +fn resolve(k: *Kernels, comptime dot: []const u8, comptime shape: []const u8, m: Module) Error!void { + @setEvalBranchQuota(400_000); + inline for (.{ 4, 8 }, 0..) |rows, r| { + inline for (stream_cbs, 0..) |cb, c| { + k.held[r][c] = if ((rows == 4 and cb <= 4) or (rows == 8 and (cb == 2 or cb == 4))) + try m.function(std.fmt.comptimePrint("_ZN2tf4rocm23affine_dot2_stream_heldINS0_{s}ELi4ELi{d}ELi{d}EEEvNS0_6AffineENS0_11StreamSidesEii", .{ dot, rows, cb })) + else + null; + } + } + k.stream_list = .{ + try m.function(std.fmt.comptimePrint("_ZN2tf4rocm23affine_dot2_stream_listINS0_{s}ELi4ELi4ELi2ELb1EEEvNS0_6AffineENS0_11StreamSidesEiii", .{dot})), + try m.function(std.fmt.comptimePrint("_ZN2tf4rocm23affine_dot2_stream_listINS0_{s}ELi4ELi4ELi4ELb0EEEvNS0_6AffineENS0_11StreamSidesEiii", .{dot})), + }; + inline for (bit_widths, 0..) |bits, b| { + k.block[b] = try m.function(std.fmt.comptimePrint("_ZN2tf4rocm17affine_dot2_blockINS0_{s}ELi{d}EEEvNS0_6AffineE", .{ dot, bits })); + if (k.matrix) k.wmma_gemm[b] = try m.function(std.fmt.comptimePrint("_ZN2tf4rocm16affine_wmma_gemmILi{d}EEEvNS0_6AffineE", .{bits})); + k.gemm[b] = try m.function(std.fmt.comptimePrint("_ZN2tf4rocm17affine_gemm_blockINS0_{s}ELi{d}E{s}EEvNS0_6AffineE", .{ dot, bits, shape })); + inline for (kp_tiles, 0..) |t, i| { + k.kp[b][i] = try m.function(std.fmt.comptimePrint("_ZN2tf4rocm14affine_gemm_kpINS0_{s}ELi{d}ELi{d}ELi{d}ELi{d}ELi{d}ELb{d}EEEvNS0_6AffineE", .{ dot, bits, t.cb, t.r, t.waves, t.rb, @intFromBool(t.loop) })); + } + inline for (piece_counts, 0..) |pieces, p| { + k.row[b][p] = try m.function(std.fmt.comptimePrint("_ZN2tf4rocm15affine_dot2_rowINS0_{s}ELi{d}ELi{d}EEEvNS0_6AffineEi", .{ dot, bits, pieces })); + inline for (row_counts, 0..) |rows, r| { + k.lanes[b][r][p] = try m.function(std.fmt.comptimePrint("_ZN2tf4rocm17affine_dot2_lanesINS0_{s}ELi{d}ELi{d}ELi{d}EEEvNS0_6AffineE", .{ dot, bits, rows, pieces })); + } + } + inline for (stream_rows, 0..) |rows, r| { + inline for (stream_cbs, 0..) |cb, c| { + k.stream[b][r][c] = if (cb * rows <= 16) + try m.function(std.fmt.comptimePrint("_ZN2tf4rocm18affine_dot2_streamINS0_{s}ELi{d}ELi{d}ELi{d}ELb0EEEvNS0_6AffineENS0_11StreamSidesEii", .{ dot, bits, rows, cb })) + else + null; + k.pairs[b][r][c] = if (cb * rows <= 16 and cb >= 2) + try m.function(std.fmt.comptimePrint("_ZN2tf4rocm18affine_dot2_streamINS0_{s}ELi{d}ELi{d}ELi{d}ELb1EEEvNS0_6AffineENS0_11StreamSidesEii", .{ dot, bits, rows, cb })) + else + null; + k.relu2[b][r][c] = if (cb * rows <= 16 and cb >= 2) + try m.function( + std.fmt.comptimePrint("_ZN2tf4rocm24affine_dot2_stream_relu2INS0_{s}" ++ + "ELi{d}ELi{d}ELi{d}EEEvNS0_6AffineENS0_11StreamSidesEii", .{ dot, bits, rows, cb }), + ) + else + null; + k.relu2_pair[b][r][c] = if (cb * rows <= 16 and cb >= 2) + try m.function( + std.fmt.comptimePrint("_ZN2tf4rocm29affine_dot2_stream_relu2_pairINS0_{s}" ++ + "ELi{d}ELi{d}ELi{d}EEEvNS0_6AffineES3_iii", .{ dot, bits, rows, cb }), + ) + else + null; + } + } + } +} + +/// fp16(bf16(code)) for every byte into the module's constant table: the RDNA2 fp16 tiles read it. Once a device. +pub fn fillByteLut(k: *const Kernels, r: *const runtime.Runtime, dot2_obj: Module) Error!void { + if (k.wmma) return; + const lut = try dot2_obj.global("_ZN2tf4rocm8kByteF16E"); + var args: hl.Args = .{}; + try args.add(lut.address); + try hl.launch(k.fill, .{ .grid = .{ .x = 1 }, .block = .{ .x = 256 } }, .{ .r = r, .handle = null }, &args); + try runtime.check(r.api.hipStreamSynchronize(null)); +} + +/// tf_affine_dense_hcmix's gate table into the tiles module: 65,536 gates, once a device. +pub fn fillHcGate(k: *const Kernels, r: *const runtime.Runtime) Error!void { + const f = k.hc_gate_fill orelse return; + var args: hl.Args = .{}; + try hl.launch(f, .{ .grid = .{ .x = 256 }, .block = .{ .x = 256 } }, .{ .r = r, .handle = null }, &args); + try runtime.check(r.api.hipStreamSynchronize(null)); +} diff --git a/zig/src/hip/launches/affine_matrix.zig b/zig/src/hip/launches/affine_matrix.zig new file mode 100644 index 0000000000..d5188cf60a --- /dev/null +++ b/zig/src/hip/launches/affine_matrix.zig @@ -0,0 +1,82 @@ +//! The gfx11 matrix-core tiles of a prompt: the routed MoE banks and the dense trunk products. + +const abi = @import("../abi.zig"); +const runtime = @import("../runtime.zig"); +const hl = @import("../launch.zig"); +const affine = @import("affine.zig"); + +const Error = runtime.Error; +const Kernels = affine.Kernels; +const Arg = affine.Arg; +const go = Kernels.go; +const cdiv = Kernels.cdiv; +const refuse = Kernels.refuse; + +/// The shapes tiles/moe_gemm.hpp compiles (MoeGateUp, MoeDown): Flash Next's expert banks, 4-bit group 32, bf16 x. +pub const MoeShape = struct { n: c_int, k: c_int, bits: c_int = 4, group: c_int = 32, blocks: c_uint }; +pub const moe_gu_shape: MoeShape = .{ .n = 1280, .k = 2560, .blocks = 10 }; +pub const moe_down_shape: MoeShape = .{ .n = 2560, .k = 640, .blocks = 20 }; + +/// Whether moeGateUp takes the plan `a` of `items` items (its output aside). +pub fn moeGateUpTakes(k: *const Kernels, a: Arg, items: c_int) bool { + return k.moe_gu != null and moeTakes(k, a, items, moe_gu_shape); +} + +/// Whether moeDown takes the plan `a` of `items` items (its output aside). +pub fn moeDownTakes(k: *const Kernels, a: Arg, items: c_int) bool { + return k.moe_down != null and moeTakes(k, a, items, moe_down_shape); +} + +fn moeTakes(k: *const Kernels, a: Arg, items: c_int, sh: MoeShape) bool { + if (k.mode == .off or k.tile != .gemm) return false; + if (a.fp16 != 0 or a.n != sh.n or a.k != sh.k or a.bits != sh.bits or a.group != sh.group) return false; + // the tile reads 8 groups' bf16 scales (and biases) of a row in one 16-byte load: the bf16 planes only + if (a.route.items == 0 or a.route.members == 0 or items < 1 or a.scale.kind != 1 or a.bias.kind != 1) return false; + return a.x % 16 == 0 and a.words % 16 == 0; +} + +/// A prompt's routed gate and up of that shape as silu(gate) * up into bf16 `a.out16`; false, nothing launched, else. +pub fn moeGateUp(k: *const Kernels, r: *const runtime.Runtime, a: Arg, items: c_int, limit: f32, s: abi.Stream) Error!bool { + if (!k.moeGateUpTakes(a, items) or a.out16 == 0) return false; + var args: hl.Args = .{}; + try args.add(a); + try args.add(limit); + try go(r, k.moe_gu.?, .{ .x = moe_gu_shape.blocks, .z = @intCast(items) }, .{ .x = 256 }, s, &args); + return true; +} + +/// A prompt's routed down of that shape into fp32 `a.out`: the matrix tile's bits; false, nothing launched, otherwise. +pub fn moeDown(k: *const Kernels, r: *const runtime.Runtime, a: Arg, items: c_int, s: abi.Stream) Error!bool { + if (!k.moeDownTakes(a, items) or a.out == 0 or a.out16 != 0) return false; + var args: hl.Args = .{}; + try args.add(a); + try go(r, k.moe_down.?, .{ .x = moe_down_shape.blocks, .z = @intCast(items) }, .{ .x = 256 }, s, &args); + return true; +} + +/// The K tiles/dense_gemm.hpp compiles (affine_wmma_dense): Flash Next's trunk, 4-bit group 32, bf16 x and tables. +pub const dense_ks = [_]c_int{ 320, 2560, 6144, 10240 }; + +pub fn denseIndex(k: c_int) ?usize { + for (dense_ks, 0..) |d, i| if (d == k) return i; + return null; +} + +/// A prompt's plain product on the dense tile of its K: the bytes of the matrix tile. +pub fn denseGo(k: *const Kernels, r: *const runtime.Runtime, a: Arg, s: abi.Stream) Error!void { + const f = k.dense[denseIndex(a.k) orelse return refuse("dense K")] orelse return refuse("dense tile"); + var args: hl.Args = .{}; + try args.add(a); + try go(r, f, .{ .x = cdiv(a.n, 128) * cdiv(a.m, 128) }, .{ .x = 256 }, s, &args); +} + +/// hc up's product (K 320) on the dense tile with tf_fn_hc_mix's mix as its epilogue: `x` [m, n], `mixed` [m, n / 4]. +pub fn denseHcMixGo(k: *const Kernels, r: *const runtime.Runtime, a: Arg, x: u64, mixed: u64, s: abi.Stream) Error!void { + const f = k.dense_hcmix orelse return refuse("hc mix tile"); + if (a.k != 320 or @rem(a.n, 4 * 32) != 0 or a.fp16 != 0) return refuse("hc mix shape"); + var args: hl.Args = .{}; + try args.add(a); + try args.add(x); + try args.add(mixed); + try go(r, f, .{ .x = cdiv(a.n, 128) * cdiv(a.m, 128) }, .{ .x = 256 }, s, &args); +} diff --git a/zig/src/hip/launches/affine_pair.zig b/zig/src/hip/launches/affine_pair.zig index b7749d9954..a642499d7f 100644 --- a/zig/src/hip/launches/affine_pair.zig +++ b/zig/src/hip/launches/affine_pair.zig @@ -39,7 +39,7 @@ pub fn relu2PairGo(k: *const Kernels, r: *const runtime.Runtime, a: Arg, b: Arg, while (c > 0) { c -= 1; const cb = affine.stream_cbs[c]; - if (cb * affine.stream_rows[ri] > 16 or cb * a.bits > affine.stream_code_words) continue; + if (cb < 2 or cb * affine.stream_rows[ri] > 16 or cb * a.bits > affine.stream_code_words) continue; pick = c; const per: c_int = affine.stream_waves * (@as(c_int, 32) >> lpc_log2) * cb; const waves = @as(u64, cdiv(a.n, per)) * affine.stream_waves * @as(u64, @intCast(items)); diff --git a/zig/src/hip/launches/affine_stream.zig b/zig/src/hip/launches/affine_stream.zig new file mode 100644 index 0000000000..624578f935 --- /dev/null +++ b/zig/src/hip/launches/affine_stream.zig @@ -0,0 +1,172 @@ +//! The stream tile's launch: the column rule, the held-codes tile and the routed work lists (tiles/stream.hpp). + +const std = @import("std"); +const abi = @import("../abi.zig"); +const runtime = @import("../runtime.zig"); +const hl = @import("../launch.zig"); +const Function = @import("../module.zig").Function; +const affine = @import("affine.zig"); + +const Error = runtime.Error; +const Kernels = affine.Kernels; +const Arg = affine.Arg; +const StreamSides = affine.StreamSides; +const go = Kernels.go; +const cdiv = Kernels.cdiv; +const bitIndex = Kernels.bitIndex; +const stream_cbs = affine.stream_cbs; +const stream_rows = affine.stream_rows; +const stream_waves = affine.stream_waves; +const streams_wanted = affine.streams_wanted; +const stream_code_words = affine.stream_code_words; + +/// A SwiGLU pair's lane carries at most this many code words (at least 2 columns): more waves in flight, same sums. +pub const stream_pair_code_words = 8; +/// The widest columns a lane of a routed plain product (the experts' down) takes, by row tile (stream_rows). +pub const stream_routed_cb_top = [stream_rows.len]c_int{ 8, 4, 4 }; +/// The blocks on z of a routed work list (stream_list): each walks about live items / 16 of the plan's items +pub const stream_list_blocks = 16; +/// The columns below which one row of a plain product takes one column a lane; wider heads keep the waves rule. +pub const stream_one_col_n = 20_000; + +/// Where an unrouted 4-bit plain product takes the held-codes tile: 3-4 rows on the rule's columns, 5-8 rows by width. +pub const HeldPick = struct { r: usize, c: usize, rows: c_int }; +pub const held_wide_n = 16_000; +pub const held_narrow_lo = 1_000; +pub const held_narrow_hi = 4_096; +pub fn heldPick(bits: c_int, m: c_int, total_n: c_int, cb: c_int) ?HeldPick { + if (bits != 4 or m < 3 or m > 8) return null; + const ci = std.mem.indexOfScalar(c_int, &stream_cbs, cb) orelse return null; + if (m <= 4) return if (cb <= 4) .{ .r = 0, .c = ci, .rows = 4 } else null; + if (total_n >= held_wide_n) return .{ .r = 1, .c = 2, .rows = 8 }; + if (total_n > held_narrow_lo and total_n <= held_narrow_hi) return .{ .r = 1, .c = 1, .rows = 8 }; + return null; +} + +test "heldPick: the held tile at 3 and 4 rows on the rule's columns, at 5 to 8 rows by width" { + try std.testing.expectEqual(@as(?HeldPick, null), heldPick(4, 1, 16480, 1)); + try std.testing.expectEqual(@as(?HeldPick, null), heldPick(4, 2, 248320, 8)); + try std.testing.expectEqual(@as(?HeldPick, .{ .r = 0, .c = 0, .rows = 4 }), heldPick(4, 3, 2560, 1)); + try std.testing.expectEqual(@as(?HeldPick, .{ .r = 0, .c = 2, .rows = 4 }), heldPick(4, 4, 16480, 4)); + try std.testing.expectEqual(@as(?HeldPick, .{ .r = 1, .c = 2, .rows = 8 }), heldPick(4, 6, 16480, 4)); + try std.testing.expectEqual(@as(?HeldPick, .{ .r = 1, .c = 1, .rows = 8 }), heldPick(4, 8, 2560, 1)); + try std.testing.expectEqual(@as(?HeldPick, null), heldPick(4, 5, 13952, 4)); + try std.testing.expectEqual(@as(?HeldPick, null), heldPick(4, 7, 324, 1)); + try std.testing.expectEqual(@as(?HeldPick, null), heldPick(8, 3, 2560, 1)); +} + +pub fn streamWith( + k: *const Kernels, + r: *const runtime.Runtime, + a: Arg, + sides_in: StreamSides, + total_n: c_int, + items: c_int, + s: abi.Stream, + relu2: bool, +) Error!void { + const b = bitIndex(a.bits).?; + var sides = sides_in; + // a pair's lane carries half as many output columns: a gate column and its up column make one + const pair_div: c_int = if (sides.pair_cols > 0) 2 else 1; + var lpc_log2: u5 = 0; + while ((@as(c_int, 1) << lpc_log2) < (a.k >> 5) and lpc_log2 < 5) lpc_log2 += 1; + const ri: usize = if (a.m == 1) 0 else if (a.m == 2) 1 else 2; + // the widest column count that still fills the card with waves, within the registers the lane's code words take + var pick: usize = 0; + var c: usize = stream_cbs.len; + while (c > 0) { + c -= 1; + // one column a lane is the plain product's only (a pair's gate and up need two; relu^2 keeps its tiles) + if (stream_cbs[c] * stream_rows[ri] > 16 or stream_cbs[c] * a.bits > stream_code_words or (stream_cbs[c] < 2 and (pair_div == 2 or relu2))) continue; + if (pair_div == 2 and stream_cbs[c] > 2 and stream_cbs[c] * a.bits > stream_pair_code_words) continue; + if (a.route.items != 0 and pair_div == 1 and !relu2 and stream_cbs[c] > stream_routed_cb_top[ri]) continue; + // one row of an unrouted plain product under stream_one_col_n columns: one column a lane; wider keeps the rule + if (ri == 0 and a.route.items == 0 and pair_div == 1 and !relu2 and total_n < stream_one_col_n and stream_cbs[c] > 1) continue; + pick = c; + const per_block: c_int = stream_waves * (@as(c_int, 32) >> lpc_log2) * @divExact(stream_cbs[c], pair_div); + if (@as(u64, cdiv(total_n, per_block)) * stream_waves * @as(u64, @intCast(items)) * cdiv(a.m, stream_rows[ri]) >= streams_wanted) break; + } + for (stream_cbs, 0..) |cb, i| { + if (cb != k.stream_cb_force or cb * stream_rows[ri] > 16 or cb * a.bits > stream_code_words or (cb < 2 and (pair_div == 2 or relu2))) continue; + pick = i; + } + if (a.route.items == 0 and pair_div == 1 and !relu2) { + if (heldPick(a.bits, a.m, total_n, stream_cbs[pick])) |hp| { + if (k.held[hp.r][hp.c]) |f| return heldGo(r, f, a, sides_in, total_n, items, s, lpc_log2, hp.rows, stream_cbs[hp.c]); + } + } + const per_block: c_int = stream_waves * (@as(c_int, 32) >> lpc_log2) * @divExact(stream_cbs[pick], pair_div); + var blocks: c_uint = cdiv(total_n, per_block); + if (sides.count > 0) { + blocks = 0; + for (0..@intCast(sides.count)) |i| { + sides.first[i] = @intCast(blocks); + blocks += cdiv(sides.n[i], per_block); + } + sides.first[@intCast(sides.count)] = @intCast(blocks); + } + // rows past the tile's: row blocks on x, column blocks on y (at most 65,535), so a column block reads codes once + const row_blocks = cdiv(a.m, stream_rows[ri]); + sides.row_blocks = if (row_blocks > 1 and blocks <= 65535) @intCast(row_blocks) else 0; + // 5 to 8 rows of a routed 4-bit plan on the 4-row tile: the work list, no block for a dead item or a dead row block + const list_cb: c_int = if (pair_div == 2) 2 else 4; + if (a.route.items != 0 and !relu2 and sides.count == 0 and a.m > 4 and a.bits == 4 and ri == 2 and + stream_cbs[pick] == list_cb and ((a.words | @as(u64, @intCast(@divExact(a.k * a.bits, 8)))) & 15) == 0) + { + var la: hl.Args = .{}; + try la.add(a); + try la.add(sides); + try la.add(@as(c_int, lpc_log2)); + try la.add(@as(c_int, switch (a.group) { + 32 => 0, + 64 => 1, + else => 2, + })); + try la.add(items); + const lf = k.stream_list[if (pair_div == 2) 0 else 1]; + return go(r, lf, .{ .x = blocks, .y = 1, .z = @intCast(@min(items, stream_list_blocks)) }, .{ .x = 32 * stream_waves }, s, &la); + } + var args: hl.Args = .{}; + try args.add(a); + try args.add(sides); + try args.add(@as(c_int, lpc_log2)); + try args.add(@as(c_int, switch (a.group) { + 32 => 0, + 64 => 1, + else => 2, + })); + const table = if (sides.pair_cols > 0) &k.pairs else if (relu2) &k.relu2 else &k.stream; + const f = table[b][ri][pick].?; + const grid: hl.Dim3 = if (sides.row_blocks > 1) + .{ .x = row_blocks, .y = blocks, .z = @intCast(items) } + else + .{ .x = blocks, .y = row_blocks, .z = @intCast(items) }; + try go(r, f, grid, .{ .x = 32 * stream_waves }, s, &args); +} + +/// A plain product on the held-codes tile: `rows` rows a block (every row of the launch in one row block at 5-8). +fn heldGo(r: *const runtime.Runtime, f: Function, a: Arg, sides_in: StreamSides, total_n: c_int, items: c_int, s: abi.Stream, lpc_log2: u5, rows: c_int, cb: c_int) Error!void { + const per_block: c_int = stream_waves * (@as(c_int, 32) >> lpc_log2) * cb; + var sides = sides_in; + var blocks: c_uint = cdiv(total_n, per_block); + if (sides.count > 0) { + blocks = 0; + for (0..@intCast(sides.count)) |i| { + sides.first[i] = @intCast(blocks); + blocks += cdiv(sides.n[i], per_block); + } + sides.first[@intCast(sides.count)] = @intCast(blocks); + } + sides.row_blocks = 0; + var args: hl.Args = .{}; + try args.add(a); + try args.add(sides); + try args.add(@as(c_int, lpc_log2)); + try args.add(@as(c_int, switch (a.group) { + 32 => 0, + 64 => 1, + else => 2, + })); + try go(r, f, .{ .x = blocks, .y = cdiv(a.m, rows), .z = @intCast(items) }, .{ .x = 32 * stream_waves }, s, &args); +} diff --git a/zig/src/hip/launches/conv.zig b/zig/src/hip/launches/conv.zig index 59f2cb0af4..2848cac0be 100644 --- a/zig/src/hip/launches/conv.zig +++ b/zig/src/hip/launches/conv.zig @@ -45,6 +45,8 @@ pub const ConvArgs = extern struct { plan: PlanArgs = .{}, layer: c_int = 0, slots: c_int = 1, + /// A device i32: with row f >= 0, a window's start is the last window's snapshot after row f (states must be set). + from: u64 = 0, }; pub fn tf_conv_decode(l: *const Launcher, x: CF, weight: CF, state: F, y: F, batch: c_int, channels: c_int, kernel: c_int, s: S) Error!void { @@ -95,3 +97,20 @@ pub fn tf_conv_prefill(l: *const Launcher, x: C, kind: c_int, weight: CF, state: if (kernel > 8) return invalid("conv_prefill"); try l.go(l.op.conv_prefill, dim(cdiv(channels, 256), @max(1, cdiv(len, 16)), 1), dim(256, 1, 1), 0, s, &a); } + +/// A DeltaNet layer's prompt prework in one launch: conv, q/k RMS norm, v, new conv state, gate and beta (linear.hpp). +pub fn tf_gdn_prompt_prep(l: *const Launcher, x: C, kind: c_int, weight: CF, state: CF, new_state: F, q: F, k: F, v: F, qw: CF, kw_w: CF, eps: f32, len: c_int, kwidth: c_int, vwidth: c_int, kernel: c_int, a: C, b: C, a_log: CF, dt_bias: CF, gate: F, beta: F, heads: c_int, s: S) Error!void { + if (kernel < 1 or kernel > 8 or @rem(kwidth, 128) != 0 or len < 1) return invalid("gdn prompt prep"); + var args: Args = .{}; + inline for (.{ ad(x), kind, ad(weight), ad(state), ad(new_state), ad(q), ad(k), ad(v), ad(qw), ad(kw_w), eps, len, kwidth, vwidth, kernel, ad(a), ad(b), ad(a_log), ad(dt_bias), ad(gate), ad(beta), heads }) |val| try args.add(val); + const n: usize = @intCast(len); + const kwu: usize = @intCast(kwidth); + const vwu: usize = @intCast(vwidth); + const segs = (n + 15) / 16; + const qk_heads = 2 * kwu / 128; + const per_v = (vwu + 255) / 256; + const states = @as(usize, @intCast(kernel - 1)) * (2 * kwu + vwu); + const total = (qk_heads * segs + 7) / 8 + per_v * segs + (n * @as(usize, @intCast(heads)) + 255) / 256 + (states + 255) / 256; + const blocks: c_int = @intCast(total); + try l.go(l.op.gdn_prompt_prep, dim(blocks, 1, 1), dim(256, 1, 1), 0, s, &args); +} diff --git a/zig/src/hip/launches/draw.zig b/zig/src/hip/launches/draw.zig index 475b1e7bd7..d905d70263 100644 --- a/zig/src/hip/launches/draw.zig +++ b/zig/src/hip/launches/draw.zig @@ -67,3 +67,27 @@ pub fn tf_topk_rows(l: *const Launcher, logits: C, rows: c_int, n: c_int, ks: CI try a.add(ad(values)); try l.go(l.op.topk, dim(rows, 1, 1), dim(1024, 1, 1), 0, s, &a); } + +/// tf_topk_rows in two launches: each of `parts` parts of `per` values its top ks[r] into candidates, then join a row. +pub fn tf_topk_parts(l: *const Launcher, logits: C, rows: c_int, n: c_int, ks: CI, stride: c_int, per: c_int, parts: c_int, cand_ids: I, cand_vals: P, ids: I, values: P, s: S) Error!void { + if (rows == 0) return; + if (per < 1 or parts < 1 or @as(i64, per) * parts < n) return util.invalid("topk parts"); + var a: Args = .{}; + try a.add(ad(logits)); + try a.add(n); + try a.add(ad(ks)); + try a.add(per); + try a.add(stride); + try a.add(ad(cand_ids)); + try a.add(ad(cand_vals)); + try l.go(l.op.topk_part, dim(parts, rows, 1), dim(1024, 1, 1), 0, s, &a); + var b: Args = .{}; + try b.add(ad(cand_ids)); + try b.add(ad(cand_vals)); + try b.add(parts); + try b.add(ad(ks)); + try b.add(stride); + try b.add(ad(ids)); + try b.add(ad(values)); + try l.go(l.op.topk_join, dim(rows, 1, 1), dim(1024, 1, 1), 0, s, &b); +} diff --git a/zig/src/hip/launches/flashnext.zig b/zig/src/hip/launches/flashnext.zig index dd272698dc..be41e69efa 100644 --- a/zig/src/hip/launches/flashnext.zig +++ b/zig/src/hip/launches/flashnext.zig @@ -1,5 +1,6 @@ //! Flash Next's launches: stream norms, gates and mixes, the n-gram gate, conv and hashes, indexer, sparse attention. +const std = @import("std"); const Launcher = @import("../launches.zig").Launcher; const Module = @import("../module.zig").Module; const Function = @import("../module.zig").Function; @@ -19,14 +20,21 @@ const cdiv = util.cdiv; pub const Fns = struct { hc_norm: Function, + hc_norm_moe: Function, + hc_norm_v: Function, // bf16 streams of 2,560, one rank: 128 threads a block, 16-byte accesses, the same bits + hc_norm_moe_v: Function, // hc_norm_v with the MoE combine as the branch, a block a row (a prompt's rows) hc_gates: Function, rms_wide: Function, hc_mix: Function, + hc_mix8: Function, // bf16 activations, g bf16 or fp32: 8 outputs a thread, the same bits ple_gate: Function, ple_conv: Function, ngram_ids: Function, idx_pool: Function, + qsa_prep: Function, idx_scores: Function, + idx_scores_quad: Function, + idx_scores8: Function, // a verify window's 5-15 rows: 8 rows' dots a wave at once, the same scores idx_select: Function, sparse_parts: [2]Function, // groups of up to 6 and up to 12 query heads sparse_merge: Function, @@ -34,14 +42,21 @@ pub const Fns = struct { pub fn load(m: Module) Error!Fns { return .{ .hc_norm = try m.function("tf_fn_hc_norm"), + .hc_norm_moe = try m.function("tf_fn_hc_norm_moe"), + .hc_norm_v = try m.function("tf_fn_hc_norm_v"), + .hc_norm_moe_v = try m.function("tf_fn_hc_norm_moe_v"), .hc_gates = try m.function("tf_fn_hc_gates"), .rms_wide = try m.function("tf_fn_rms_wide"), .hc_mix = try m.function("tf_fn_hc_mix"), + .hc_mix8 = try m.function("tf_fn_hc_mix8"), .ple_gate = try m.function("tf_fn_ple_gate"), .ple_conv = try m.function("tf_fn_ple_conv"), .ngram_ids = try m.function("tf_fn_ngram_ids"), .idx_pool = try m.function("tf_fn_idx_pool"), + .qsa_prep = try m.function("tf_fn_qsa_prep"), .idx_scores = try m.function("tf_fn_idx_scores"), + .idx_scores_quad = try m.function("tf_fn_idx_scores_quad"), + .idx_scores8 = try m.function("tf_fn_idx_scores8"), .idx_select = try m.function("tf_fn_idx_select"), .sparse_parts = .{ try m.function("tf_fn_sparse_parts6"), try m.function("tf_fn_sparse_parts12") }, .sparse_merge = try m.function("tf_fn_sparse_merge"), @@ -72,6 +87,52 @@ pub fn hcNorm( return hcNormShares(l, h, branch, inject, h_out, x_out, scale, kind, rows, streams, dims, eps, 0, 0, s); } +/// hcNorm with the MoE's combine of fp32 expert rows `y` [rows, slots, dims] by `wts` [rows, slots] as the branch. +pub fn hcNormMoe( + l: *const Launcher, + h: C, + y: CF, + wts: CF, + inject: C, + h_out: P, + x_out: P, + scale: CF, + kind: c_int, + rows: c_int, + streams: c_int, + dims: c_int, + eps: f32, + slots: c_int, + s: S, +) Error!void { + if (dims > most_dims or slots < 1) return util.invalid("hcNormMoe"); + var a: Args = .{}; + inline for (.{ ad(h), ad(y), ad(wts), ad(inject), ad(h_out), ad(x_out), ad(scale), kind, streams, dims, eps, slots }) |v| try a.add(v); + try l.go(l.fnx.hc_norm_moe, dim(streams, rows, 1), dim(1024, 1, 1), 0, s, &a); +} + +/// hcNormMoe for a prompt's bf16 streams of 2,560 on one rank, a block a row, same bits; the caller checks the shape. +pub fn hcNormMoeV( + l: *const Launcher, + h: C, + y: CF, + wts: CF, + inject: C, + h_out: P, + x_out: P, + scale: CF, + rows: c_int, + streams: c_int, + eps: f32, + slots: c_int, + s: S, +) Error!void { + if (streams < 1 or streams > 4 or slots < 1) return util.invalid("hcNormMoeV"); + var a: Args = .{}; + inline for (.{ ad(h), ad(y), ad(wts), ad(inject), ad(h_out), ad(x_out), ad(scale), streams, eps, slots }) |v| try a.add(v); + try l.go(l.fnx.hc_norm_moe_v, dim(1, rows, 1), dim(128 * streams, 1, 1), 0, s, &a); +} + /// hcNorm with the branch as `world` fp32 shares `stride` values apart (a tensor-parallel gather), summed in order. pub fn hcNormShares( l: *const Launcher, @@ -91,6 +152,11 @@ pub fn hcNormShares( s: S, ) Error!void { if (dims > most_dims) return util.invalid("hcNorm"); + if (world == 0 and kind == 2 and dims == 2560) { + var v: Args = .{}; + inline for (.{ ad(h), ad(branch), ad(inject), ad(h_out), ad(x_out), ad(scale), streams, eps }) |x| try v.add(x); + return l.go(l.fnx.hc_norm_v, dim(streams, rows, 1), dim(128, 1, 1), 0, s, &v); + } var a: Args = .{}; inline for (.{ ad(h), @@ -147,7 +213,8 @@ pub fn rmsWide( /// The block input: the mean over the streams of sigmoid(g) times the normed stream. pub fn hcMix( l: *const Launcher, - g: CF, + g: C, + gkind: c_int, x: C, mixed: P, kind: c_int, @@ -156,8 +223,18 @@ pub fn hcMix( dims: c_int, s: S, ) Error!void { + if (kind == 2 and (gkind == 0 or gkind == 2) and @rem(dims, 8) == 0) { + var v: Args = .{}; + inline for (.{ ad(g), gkind, ad(x), ad(mixed), rows, streams, dims }) |w| try v.add(w); + return l.flat(l.fnx.hc_mix8, @divExact(@as(i64, rows) * dims, 8), s, &v); + } + return hcMixScalar(l, g, gkind, x, mixed, kind, rows, streams, dims, s); +} + +/// hcMix on the per-element kernel (any kinds): the reference the bf16 path's bytes are tested against. +pub fn hcMixScalar(l: *const Launcher, g: C, gkind: c_int, x: C, mixed: P, kind: c_int, rows: c_int, streams: c_int, dims: c_int, s: S) Error!void { var a: Args = .{}; - inline for (.{ ad(g), ad(x), ad(mixed), kind, rows, streams, dims }) |v| try a.add(v); + inline for (.{ ad(g), gkind, ad(x), ad(mixed), kind, rows, streams, dims }) |v| try a.add(v); try l.flat(l.fnx.hc_mix, @as(i64, rows) * dims, s, &a); } @@ -314,6 +391,53 @@ pub fn idxPoolAt( try l.go(l.fnx.idx_pool, dim(rows, 1, 1), dim(threads, 1, 1), 0, s, &a); } +/// flashnext/indexer.hpp's QsaRope and QsaPrep: a QSA layer's decode prep at device positions in one launch. +pub const QsaRope = extern struct { src: u64 = 0, s_row: c_longlong = 0, s_head: c_int = 0, heads: c_int = 0, width: c_int = 0, weight: u64 = 0, wide: u64 = 0, cache: u64 = 0 }; +pub const QsaPrep = extern struct { + q: QsaRope = .{}, + iq: QsaRope = .{}, + k: QsaRope, + v: u64, + v_cache: u64, + v_width: c_int, + raw: u64, + raw_stride: c_longlong, + raw_offset: c_int, + raw_cache: u64, + raw_width: c_int, + pooled: u64, + pool_scale: u64, + ratio: c_int, + pos: u64, + seg_pos: u64, + rows: c_int, + n: c_int, + total: c_int, + kind: c_int, + eps: f32, + rotary: c_int, + theta: f32, +}; + +comptime { + std.debug.assert(@sizeOf(QsaRope) == 56 and @sizeOf(QsaPrep) == 304); +} + +/// tf_fn_qsa_prep: a QSA layer's q/k rope, v and raw index key cache writes and completed-block pools in one launch. +pub fn qsaPrep(l: *const Launcher, a: QsaPrep, s: S) Error!void { + if (a.n < 1 or a.k.width > 512 or a.q.width > 512 or a.iq.width > 512 or a.raw_width > threads or a.kind == 0) return util.invalid("qsaPrep"); + const qt: c_int = if (a.q.src != 0) a.rows * (a.q.heads + a.iq.heads) else 0; + const tasks: c_int = qt + a.n * a.k.heads; + var args: Args = .{}; + try args.add(a); + try l.go(l.fnx.qsa_prep, dim(cdiv(tasks, threads / 32) + 1, 1, 1), dim(threads, 1, 1), 0, s, &args); +} + +/// Rows from which the block scores take tf_fn_idx_scores_quad (fewer: a verify window's, a wave a block). +pub const quad_rows = 16; +/// Rows from which (to quad_rows) the block scores take tf_fn_idx_scores8; fewer rows keep the plain kernel. +pub const scores8_rows = 5; + /// Every row's score of each of `blocks` pooled blocks it has complete, for rows past `top` complete blocks. pub fn idxScores( l: *const Launcher, @@ -332,6 +456,18 @@ pub fn idxScores( ) Error!void { if (blocks == 0) return; if (dims > threads) return util.invalid("idxScores"); + // a prompt slice of Flash Next's 4 x 128 index heads: 4 lanes a score, the same sums (indexer.hpp) + if (rows >= quad_rows and heads == 4 and dims == 128) { + var b: Args = .{}; + inline for (.{ ad(q), ad(pooled), ad(complete), ad(scores), kind, rows, blocks, stride, top }) |v| try b.add(v); + return l.go(l.fnx.idx_scores_quad, dim(cdiv(blocks, 64), cdiv(rows, 32), 1), dim(128, 1, 1), 0, s, &b); + } + // a verify window's rows of the same heads: a wave's 8 rows' dots at once, the same sums (indexer.hpp) + if (rows >= scores8_rows and heads == 4 and dims == 128) { + var c: Args = .{}; + inline for (.{ ad(q), ad(pooled), ad(complete), ad(scores), kind, rows, blocks, stride, top }) |v| try c.add(v); + return l.go(l.fnx.idx_scores8, dim(cdiv(blocks, threads / 32), cdiv(rows, 8), 1), dim(threads, 1, 1), 0, s, &c); + } var a: Args = .{}; inline for (.{ ad(q), @@ -381,53 +517,5 @@ pub fn idxSelect( try l.go(l.fnx.idx_select, dim(rows, 1, 1), dim(1024, 1, 1), 0, s, &a); } -/// Attention of each row's heads over its listed keys (or its first count[r] keys) in `parts` parts, then merged. -pub fn sparseAttention( - l: *const Launcher, - q: CF, - k: C, - v: C, - cache_kind: c_int, - ids: CI, - id_stride: i64, - count: CI, - sparse: CI, - parts_o: F, - parts_ms: F, - out: F, - rows: c_int, - heads: c_int, - kv_heads: c_int, - dims: c_int, - cap: i64, - scale: f32, - parts: c_int, - s: S, -) Error!void { - if (dims > 256 or @rem(heads, kv_heads) != 0 or @divExact(heads, kv_heads) > 12) - return util.invalid("sparseAttention"); - var a: Args = .{}; - inline for (.{ - ad(q), - ad(k), - ad(v), - cache_kind, - ad(ids), - id_stride, - ad(count), - ad(sparse), - ad(parts_o), - ad(parts_ms), - heads, - kv_heads, - dims, - cap, - scale, - parts, - }) |x| try a.add(x); - const wide: usize = if (@divExact(heads, kv_heads) <= 6) 0 else 1; - try l.go(l.fnx.sparse_parts[wide], dim(kv_heads, rows, parts), dim(256, 1, 1), 0, s, &a); - var b: Args = .{}; - inline for (.{ ad(parts_o), ad(parts_ms), ad(out), heads, dims, parts }) |x| try b.add(x); - try l.go(l.fnx.sparse_merge, dim(heads, rows, 1), dim(256, 1, 1), 0, s, &b); -} +const sparse_attn = @import("flashnext_sparse.zig"); +pub const sparseAttention = sparse_attn.sparseAttention; diff --git a/zig/src/hip/launches/flashnext_sparse.zig b/zig/src/hip/launches/flashnext_sparse.zig new file mode 100644 index 0000000000..7298d20877 --- /dev/null +++ b/zig/src/hip/launches/flashnext_sparse.zig @@ -0,0 +1,65 @@ +//! Flash Next's sparse attention: the parts tile and merge. + +const Launcher = @import("../launches.zig").Launcher; +const util = @import("util.zig"); +const S = util.S; +const P = util.P; +const C = util.C; +const F = util.F; +const CF = util.CF; +const CI = util.CI; +const Args = util.Args; +const Error = util.Error; +const ad = util.ad; +const dim = util.dim; + +/// Attention of each row's heads over its listed keys (or its first count[r] keys) in `parts` parts, then merged. +pub fn sparseAttention( + l: *const Launcher, + q: CF, + k: C, + v: C, + cache_kind: c_int, + ids: CI, + id_stride: i64, + count: CI, + sparse: CI, + parts_o: F, + parts_ms: F, + out: F, + rows: c_int, + heads: c_int, + kv_heads: c_int, + dims: c_int, + cap: i64, + scale: f32, + parts: c_int, + s: S, +) Error!void { + if (dims > 256 or @rem(heads, kv_heads) != 0 or @divExact(heads, kv_heads) > 12) + return util.invalid("sparseAttention"); + var a: Args = .{}; + inline for (.{ + ad(q), + ad(k), + ad(v), + cache_kind, + ad(ids), + id_stride, + ad(count), + ad(sparse), + ad(parts_o), + ad(parts_ms), + heads, + kv_heads, + dims, + cap, + scale, + parts, + }) |x| try a.add(x); + const wide: usize = if (@divExact(heads, kv_heads) <= 6) 0 else 1; + try l.go(l.fnx.sparse_parts[wide], dim(kv_heads, rows, parts), dim(256, 1, 1), 0, s, &a); + var b: Args = .{}; + inline for (.{ ad(parts_o), ad(parts_ms), ad(out), heads, dims, parts }) |x| try b.add(x); + try l.go(l.fnx.sparse_merge, dim(heads, rows, 1), dim(256, 1, 1), 0, s, &b); +} diff --git a/zig/src/hip/launches/mlx_entries.zig b/zig/src/hip/launches/mlx_entries.zig index 9d71533476..10cc9b39cf 100644 --- a/zig/src/hip/launches/mlx_entries.zig +++ b/zig/src/hip/launches/mlx_entries.zig @@ -185,6 +185,12 @@ fn fitsPrefillMatrix(s: Shape) bool { return prefillOk(s) and !s.fp16 and gemmFits(s); } +/// The dense tile: plain 4-bit group-32 products, bf16 x and tables, a K it compiles, at least one full column tile. +fn fitsPrefillDense(s: Shape) bool { + return fitsPrefillMatrix(s) and s.items == 0 and s.bits == 4 and s.group == 32 and s.tables == .bf16 and s.x_aligned and + s.n >= 128 and Kernels.denseIndex(@intCast(s.k)) != null; +} + fn fitsPrefillGemm(s: Shape) bool { return prefillOk(s) and gemmFits(s); } @@ -239,6 +245,10 @@ fn launchBlock(comptime kind: affine.BlockKind) Launch { }.f; } +fn launchDense(k: *const Kernels, c: Call) Error!void { + try k.denseGo(c.r, c.arg, c.s); +} + fn launchKp(comptime tier: usize) Launch { return struct { fn f(k: *const Kernels, c: Call) Error!void { @@ -315,7 +325,11 @@ fn prefill(comptime op: Op) [7]Entry { }; } -pub const all = project_decode ++ routed_decode ++ other_decode ++ prefill(.project) ++ prefill(.routed); +const project_prefill = [_]Entry{ + entry(.project, .prefill, "dense", .{ .family = .gemm, .fits = &fitsPrefillDense, .launch = &launchDense, .caps = &matrixCores, .policy = &matrixOn, .rounds = .always }), +}; + +pub const all = project_decode ++ routed_decode ++ other_decode ++ project_prefill ++ prefill(.project) ++ prefill(.routed); // ---- the choices on the GPUs' tables @@ -456,3 +470,33 @@ test "gfx1201 takes the K-parallel tile for short routed prompts, up to its item try std.testing.expect(std.mem.endsWith(u8, r.select(env, .mlx, .routed, .prefill, shape).?.id, w[5])); } } + +test "a prompt's plain 4-bit group-32 products at Flash Next's K take the dense tile past the K-parallel tiles" { + const r = kernelsOn("gfx1151"); + const env = envOn("gfx1151", true, true, true); + var shape: Shape = .{ .m = 8192, .n = 10240, .k = 2560, .bits = 4, .group = 32, .fp16 = false }; + for ([_]u32{ 320, 2560, 6144, 10240 }) |k| { + shape.k = k; + try std.testing.expect(std.mem.endsWith(u8, r.select(env, .mlx, .project, .prefill, shape).?.id, "dense")); + } + shape.m = 32; + try std.testing.expect(std.mem.endsWith(u8, r.select(env, .mlx, .project, .prefill, shape).?.id, "kp2")); + shape.m = 33; + try std.testing.expect(std.mem.endsWith(u8, r.select(env, .mlx, .project, .prefill, shape).?.id, "dense")); + // the matrix tile keeps every other product: another K, width, group or table kind, a narrow one, a plan + const others = [_]Shape{ + .{ .m = 8192, .n = 10240, .k = 4096, .bits = 4, .group = 32, .fp16 = false }, + .{ .m = 8192, .n = 10240, .k = 2560, .bits = 8, .group = 32, .fp16 = false }, + .{ .m = 8192, .n = 10240, .k = 2560, .bits = 4, .group = 64, .fp16 = false }, + .{ .m = 8192, .n = 10240, .k = 2560, .bits = 4, .group = 32, .fp16 = false, .tables = .f32 }, + .{ .m = 8192, .n = 48, .k = 2560, .bits = 4, .group = 32, .fp16 = false }, + }; + for (others) |s| try std.testing.expect(std.mem.endsWith(u8, r.select(env, .mlx, .project, .prefill, s).?.id, "matrix")); + shape.m = 8192; + shape.items = 301; + try std.testing.expect(std.mem.endsWith(u8, r.select(env, .mlx, .routed, .prefill, shape).?.id, "matrix")); + // with the matrix cores off, and on gfx1201, the dot2 GEMM tile + shape.items = 0; + try std.testing.expect(std.mem.endsWith(u8, r.select(envOn("gfx1151", true, true, false), .mlx, .project, .prefill, shape).?.id, "gemm")); + try std.testing.expect(std.mem.endsWith(u8, r.select(envOn("gfx1201", true, true, true), .mlx, .project, .prefill, shape).?.id, "gemm")); +} diff --git a/zig/src/hip/launches/moe.zig b/zig/src/hip/launches/moe.zig index 2cccb06e86..fb3c4a8558 100644 --- a/zig/src/hip/launches/moe.zig +++ b/zig/src/hip/launches/moe.zig @@ -36,7 +36,7 @@ pub fn routerWith(l: *const Launcher, x: C, kind: c_int, rows: CF, logits: F, r: try a.add(e); const k: usize = if (kind == 1) 0 else 1; if (small) return l.go(l.op.router_small[k], dim(cdiv(e, 8), cdiv(r, 32), 1), dim(256, 1, 1), 0, s, &a); - try l.go(l.op.router_tile[k], dim(cdiv(e, 64), cdiv(r, 64), 1), dim(256, 1, 1), 0, s, &a); + try l.go(l.op.router_tile[k], dim(cdiv(e, 64), cdiv(r, 128), 1), dim(256, 1, 1), 0, s, &a); } /// A lane round's router at any row count; false (nothing launched) where the shape keeps the other kernels. @@ -53,6 +53,49 @@ pub fn routerWindow(l: *const Launcher, x: C, kind: c_int, rows: CF, logits: F, return true; } +/// Decode router logits, row picks and (with `items`) plan in one launch; false where the shape keeps them apart. +pub fn routerSelect(l: *const Launcher, x: C, kind: c_int, rows16: C, logits: F, pick: I, wts: F, items: I, members: I, capacity: c_int, r: c_int, d: c_int, e: c_int, top_k: c_int, tile: c_int, done: u64, s: S) Error!bool { + if (!l.fuse or done == 0 or r < 1 or r > 16 or @rem(d, 4) != 0 or ad(rows16) % 8 != 0 or ad(x) % 8 != 0) return false; + if (e - 1 > 1024 or top_k < 1 or top_k > 31) return false; + // the plan in the launch: one row, or 2 to 8 rows of at most plan_pairs pairs (route_plan's pair a thread) + if (items != null and r != 1 and (r > 8 or r * (top_k + 1) > plan_pairs or tile < 1)) return false; + var a: Args = .{}; + try a.add(ad(x)); + try a.add(ad(rows16)); + try a.add(ad(logits)); + try a.add(r); + try a.add(d); + try a.add(e); + try a.add(ad(pick)); + try a.add(ad(wts)); + try a.add(ad(items)); + try a.add(ad(members)); + try a.add(capacity); + try a.add(top_k); + try a.add(tile); + const sh = routerShared(ad(x), r, d, e, items != null); + try a.add(@as(c_int, @intFromBool(sh.staged))); + try a.add(done); + try l.go(l.dec.router_select[if (kind == 1) 0 else 1], dim(cdiv(e, 4), 1, 1), dim(128, 1, 1), sh.bytes, s, &a); + return true; +} + +/// The most bytes of x tf_router_select stages: 2 rows of 2560 bf16; more rows cost blocks a WGP than they save in L2. +const STAGED = 2 * 2560 * 2; + +/// decode/select.hpp's kPlanPairs: the pairs route_plan takes in the router launch, a thread each (32 * kRouterWaves). +const plan_pairs = 128; + +/// tf_router_select's dynamic shared memory: max of staged rows and (2 to 8 rows) top lists plus plan pool; 1 row: 0. +fn routerShared(x: usize, r: c_int, d: c_int, e: c_int, plan: bool) struct { bytes: u32, staged: bool } { + if (r < 2 or r > 8) return .{ .bytes = 0, .staged = false }; + const staged = @rem(d, 8) == 0 and x % 16 == 0 and r * d * 2 <= STAGED; + const rows: c_int = if (staged) r * d * 2 else 0; + // the waves' top values and indices (32 each a wave), then route_plan's counts, starts and ends, scans and pairs + const ints: c_int = if (e - 1 <= 1024) 2 * 32 * 4 + (if (plan) 3 * e + 2 * 128 + plan_pairs else 0) else 0; + return .{ .bytes = @intCast(@max(rows, ints * 4)), .staged = staged }; +} + pub fn tf_moe_router(l: *const Launcher, x: C, kind: c_int, rows: CF, logits: F, r: c_int, d: c_int, e: c_int, s: S) Error!void { // a prompt's rows take the 64 x 64 tiles, a round's few rows a wave an expert; each logit's sum is the same var a: Args = .{}; @@ -66,7 +109,7 @@ pub fn tf_moe_router(l: *const Launcher, x: C, kind: c_int, rows: CF, logits: F, if (l.fuse and r <= 16 and @rem(d, 4) == 0 and ad(rows) % 16 == 0 and ad(x) % 8 == 0) { return l.go(l.dec.router[k], dim(cdiv(e, 4), 1, 1), dim(128, 1, 1), 0, s, &a); } - if (r >= 64 and @rem(d, 32) == 0) return l.go(l.op.router_tile[k], dim(cdiv(e, 64), cdiv(r, 64), 1), dim(256, 1, 1), 0, s, &a); + if (r >= 64 and @rem(d, 32) == 0) return l.go(l.op.router_tile[k], dim(cdiv(e, 64), cdiv(r, 128), 1), dim(256, 1, 1), 0, s, &a); try l.go(l.op.router_rows[k], dim(cdiv(e, 8), cdiv(r, 8), 1), dim(256, 1, 1), 0, s, &a); } @@ -81,6 +124,17 @@ pub fn tf_moe_select(l: *const Launcher, logits: CF, pick: I, wts: F, items: I, try a.add(capacity); try a.add(experts); try a.add(top_k); + // a prompt's rows (no plan): a wave a row, 4 rows a block, select_body's bytes (tf_select_rows) + if (l.fuse and items == null) { + var b: Args = .{}; + try b.add(ad(logits)); + try b.add(ad(pick)); + try b.add(ad(wts)); + try b.add(r); + try b.add(experts); + try b.add(top_k); + return l.go(l.dec.select_rows, dim(cdiv(r, 4), 1, 1), dim(128, 1, 1), 0, s, &b); + } if (l.fuse) return l.go(l.dec.select, dim(r, 1, 1), dim(512, 1, 1), 0, s, &a); try l.go(l.moe_select, dim(r, 1, 1), dim(32, 1, 1), 0, s, &a); } @@ -96,6 +150,22 @@ pub fn tf_moe_act(l: *const Launcher, both: CF, out: P, kind: c_int, pairs: c_in try l.go(l.moe_act[if (kind == 1) 0 else 1], dim(cdiv(total, 256), 1, 1), dim(256, 1, 1), 0, s, &a); } +/// The prefetch's blocks: 16 of 256 threads finish a one-row call's down codes about when its down starts. +pub const prefetch_blocks = 16; + +/// tf_moe_prefetch on side stream `s`: reads the live items' experts' down codes, at most `cap_bytes`; writes nothing. +pub fn tf_moe_prefetch(l: *const Launcher, items: CI, count: c_int, words: u64, expert_bytes: i64, experts: c_int, cap_bytes: i64, s: S) Error!void { + if (count <= 0 or expert_bytes <= 0 or @rem(expert_bytes, 16) != 0) return invalid("moe prefetch"); + var a: Args = .{}; + try a.add(ad(items)); + try a.add(count); + try a.add(words); + try a.add(expert_bytes); + try a.add(experts); + try a.add(cap_bytes); + try l.go(l.dec.prefetch, dim(prefetch_blocks, 1, 1), dim(256, 1, 1), 0, s, &a); +} + pub fn tf_moe_combine(l: *const Launcher, y: CF, wts: CF, out: P, kind: c_int, r: c_int, slots: c_int, d: c_int, s: S) Error!void { var a: Args = .{}; try a.add(ad(y)); @@ -106,6 +176,42 @@ pub fn tf_moe_combine(l: *const Launcher, y: CF, wts: CF, out: P, kind: c_int, r try l.go(l.moe_combine[tri(kind)], dim(cdiv(d, 256), r, 1), dim(256, 1, 1), 0, s, &a); } +/// decode.hip / moe.hpp kRouteSeg: the pairs a block of tf_route_count and tf_route_scatter takes. +pub const route_seg = 512; + +/// The bytes of tf_moe_route_wide's scratch for `pairs` pairs over `experts` experts. +pub fn routeScratch(pairs: usize, experts: usize) usize { + return (std.math.divCeil(usize, pairs, route_seg) catch unreachable) * experts * 4 + experts * 4; +} + +/// tf_moe_route's members and items in three launches over 512-pair segments; a few pairs keep tf_moe_route. +pub fn tf_moe_route_wide(l: *const Launcher, picks: CI, pairs: c_int, experts: c_int, tile: c_int, members: I, items: I, capacity: c_int, scratch: u64, s: S) Error!void { + if (pairs < 4 * route_seg or experts > 1024 or scratch == 0) return tf_moe_route(l, picks, pairs, experts, tile, members, items, capacity, s); + const segs: c_int = @intCast(cdiv(pairs, route_seg)); + var a: Args = .{}; + try a.add(ad(picks)); + try a.add(pairs); + try a.add(experts); + try a.add(scratch); + try l.go(l.op.route_count, dim(segs, 1, 1), dim(256, 1, 1), 0, s, &a); + var b: Args = .{}; + try b.add(scratch); + try b.add(segs); + try b.add(experts); + try b.add(tile); + try b.add(ad(items)); + try b.add(capacity); + try l.go(l.op.route_scan, dim(1, 1, 1), dim(1024, 1, 1), 0, s, &b); + var c: Args = .{}; + try c.add(ad(picks)); + try c.add(pairs); + try c.add(segs); + try c.add(experts); + try c.add(scratch); + try c.add(ad(members)); + try l.go(l.op.route_scatter, dim(segs, 1, 1), dim(route_seg, 1, 1), 0, s, &c); +} + pub fn tf_moe_route(l: *const Launcher, picks: CI, pairs: c_int, experts: c_int, tile: c_int, members: I, items: I, capacity: c_int, s: S) Error!void { var a: Args = .{}; try a.add(ad(picks)); diff --git a/zig/src/hip/launches/recurrence.zig b/zig/src/hip/launches/recurrence.zig index 441999032c..fcbe9d2931 100644 --- a/zig/src/hip/launches/recurrence.zig +++ b/zig/src/hip/launches/recurrence.zig @@ -28,7 +28,11 @@ pub fn tf_gdn_gate(l: *const Launcher, av: C, bv: C, kind: c_int, a_log: CF, dt_ try l.go(l.gdn_gate[tri(kind)], dim(cdiv(count, 256), 1, 1), dim(256, 1, 1), 0, s, &a); } -pub fn tf_gated_delta(l: *const Launcher, q: CF, k: CF, v: CF, gate: CF, beta: CF, state: F, y: F, batch: c_int, length: c_int, key_heads: c_int, value_heads: c_int, dk: c_int, dv: c_int, s: S, states: F) Error!void { +/// Rows from which a prompt's recurrence takes tf_gdn_prompt_128 (fewer: a wave a row reads the state faster). +pub const prompt_rows = 64; + +/// `from`: device i32 snapshot row of `states` a lone stream's window starts from, -1 for `state`; 0: none. +pub fn tf_gated_delta(l: *const Launcher, q: CF, k: CF, v: CF, gate: CF, beta: CF, state: F, y: F, batch: c_int, length: c_int, key_heads: c_int, value_heads: c_int, dk: c_int, dv: c_int, s: S, states: F, from: u64) Error!void { if ((dk != 16 and dk != 128) or dv < 1 or key_heads < 1 or @rem(value_heads, key_heads) != 0 or batch < 1 or length < 1) { return invalid("gated delta"); } @@ -45,6 +49,23 @@ pub fn tf_gated_delta(l: *const Launcher, q: CF, k: CF, v: CF, gate: CF, beta: C try a.add(value_heads); try a.add(dv); try a.add(ad(states)); + if (from != 0 and batch != 1) return invalid("gated delta start row"); + try a.add(from); + // a prompt's rows (no snapshots): half a value head a block, 4 lanes a row, the same sums (gated_delta.hip) + if (dk == 128 and dv == 128 and states == null and length >= prompt_rows) { + var b: Args = .{}; + try b.add(ad(q)); + try b.add(ad(k)); + try b.add(ad(v)); + try b.add(ad(gate)); + try b.add(ad(beta)); + try b.add(ad(state)); + try b.add(ad(y)); + try b.add(length); + try b.add(key_heads); + try b.add(value_heads); + return l.go(l.gdn_prompt, dim(2, value_heads, batch), dim(32, 4, 1), 0, s, &b); + } const wide: usize = if (dk == 128) 0 else 1; // Eight rows share one k/q tile; a short dv stays on the one-row wave, which is the same scan. if (@rem(dv, 8) == 0) { @@ -54,6 +75,42 @@ pub fn tf_gated_delta(l: *const Launcher, q: CF, k: CF, v: CF, gate: CF, beta: C } } +/// A verify window's recurrence that holds the state: outputs only; tf_gdn_keep then runs the kept rows. dv % 8 == 0. +pub fn tf_gdn_hold(l: *const Launcher, q: CF, k: CF, v: CF, gate: CF, beta: CF, state: F, y: F, length: c_int, key_heads: c_int, value_heads: c_int, dk: c_int, dv: c_int, s: S) Error!void { + if ((dk != 16 and dk != 128) or @rem(dv, 8) != 0 or key_heads < 1 or @rem(value_heads, key_heads) != 0 or length < 1 or length > 16) { + return invalid("gated delta hold"); + } + var a: Args = .{}; + try a.add(ad(q)); + try a.add(ad(k)); + try a.add(ad(v)); + try a.add(ad(gate)); + try a.add(ad(beta)); + try a.add(ad(state)); + try a.add(ad(y)); + try a.add(length); + try a.add(key_heads); + try a.add(value_heads); + try a.add(dv); + try l.go(l.gdn_hold[if (dk == 128) 0 else 1], dim(@divExact(dv, 8), value_heads, 1), dim(32, 8, 1), 0, s, &a); +} + +/// A keep: each of `layers` DeltaNet states (strided) runs through the first `kept` of its window's `rows` input rows. +pub fn tf_gdn_keep(l: *const Launcher, state: F, state_stride: i64, in: CF, in_stride: i64, rows: c_int, kept: c_int, layers: c_int, key_heads: c_int, value_heads: c_int, dk: c_int, dv: c_int, s: S) Error!void { + if ((dk != 16 and dk != 128) or @rem(dv, 8) != 0 or kept < 1 or kept > rows or layers < 1) return invalid("gated delta keep"); + var a: Args = .{}; + try a.add(ad(state)); + try a.add(state_stride); + try a.add(ad(in)); + try a.add(in_stride); + try a.add(rows); + try a.add(kept); + try a.add(key_heads); + try a.add(value_heads); + try a.add(dv); + try l.go(l.gdn_keep[if (dk == 128) 0 else 1], dim(@divExact(dv, 8), value_heads, layers), dim(32, 8, 1), 0, s, &a); +} + pub fn tf_gdn_gate_prefill(l: *const Launcher, av: C, bv: C, kind: c_int, a_log: CF, dt_bias: CF, gate: F, beta: F, count: c_int, heads: c_int, s: S) Error!void { var a: Args = .{}; try a.add(ad(av)); diff --git a/zig/src/hip/moe.zig b/zig/src/hip/moe.zig index 0ddd802a9a..9a8556e19a 100644 --- a/zig/src/hip/moe.zig +++ b/zig/src/hip/moe.zig @@ -29,6 +29,10 @@ pub const Routed = struct { remap: u64 = 0, /// Plan the rows' own pairs, not a power-of-two bucket's (no graph replays the launches at other row counts). exact: bool = false, + /// The router's rows in bf16 (E + 1, D), as `rows32`: one router-and-pick launch reads them (0: two over `rows32`). + rows16: u64 = 0, + /// A u32, zero between launches, that the one-launch router and pick counts its finished blocks in. + done: u64 = 0, /// Routed experts, the shared one not counted. pub fn count(r: Routed) usize { @@ -36,6 +40,9 @@ pub const Routed = struct { } }; +/// Most rows a call has to read its live experts' down codes on the side stream beside its gate and up (more: no gain). +pub const prefetch_rows = 1; + /// experts.py: the decode tile's most rows, the GEMM tile's rows and where it starts, items' pair cap. const LANE_ROWS = 8; const BLOCK_ROWS = 128; @@ -53,6 +60,12 @@ pub fn capacity(pairs: usize, experts: usize) usize { return @min(pairs, experts) + pairs / @min(TILE, LANE_ROWS); } +/// The most live items a prompt plan has at `tile` pairs an item (tf_moe_route puts them first): its launches' z. +pub fn planItems(pairs: usize, experts: usize, tile: usize) usize { + const a = @min(pairs, experts); + return a + (pairs - a) / tile; +} + /// tile_for: the decode tile below BLOCK_FROM rows, the GEMM tile from there; a lane round's rows keep the decode tile. pub fn tileFor(o: Ops, rows: usize) usize { return tileOf(rows, o.window); @@ -76,10 +89,10 @@ pub fn run(o: Ops, kind: Kind, r: Routed, x: Tensor, rows: usize, prefill: bool) const wts = try o.arena.of(f32, size * slots); const items = try o.arena.of(i32, cap * 3); const members = try o.arena.of(i32, size * slots); - try o.moeRouter(x, r.rows32, logits, rows, ex.dims, r.rows); const count: usize = cap; var tile: usize = undefined; if (r.remap != 0) { + try o.moeRouter(x, r.rows32, logits, rows, ex.dims, r.rows); // every rank picks the same pairs, runs the ones it holds (the others group under an id past its experts) try o.moeSelect(logits, pick, wts, null, 0, rows, r.count(), r.top_k); const local = try o.arena.of(i32, size * slots); @@ -97,13 +110,13 @@ pub fn run(o: Ops, kind: Kind, r: Routed, x: Tensor, rows: usize, prefill: bool) try o.moeCombine(y, wts, .{ .ptr = share, .kind = .f32 }, rows, slots, ex.dims); return .{ .ptr = share, .kind = .f32 }; } - const p = try expertParts(o, kind, r, x, rows, logits, pick, wts, items, members, cap); + const p = try expertParts(o, kind, r, x, rows, logits, pick, wts, items, members, cap, false); const out = try o.arena.take(rows * ex.dims * kind.size()); try o.moeCombine(p.y, wts, .{ .ptr = out, .kind = kind }, rows, slots, ex.dims); return .{ .ptr = out, .kind = kind }; } -/// The routed slots a row (fp32) and their weights before the sum: a single rank only. +/// The routed slots a row (fp32) and their weights before the sum, single rank: join the side stream before reading y. pub const Parts = struct { y: u64, wts: u64, slots: usize }; pub fn parts(o: Ops, kind: Kind, r: Routed, x: Tensor, rows: usize) ops.Error!Parts { @@ -115,27 +128,47 @@ pub fn parts(o: Ops, kind: Kind, r: Routed, x: Tensor, rows: usize) ops.Error!Pa const wts = try o.arena.of(f32, size * slots); const items = try o.arena.of(i32, cap * 3); const members = try o.arena.of(i32, size * slots); - try o.moeRouter(x, r.rows32, logits, rows, r.experts.dims, r.rows); - const p = try expertParts(o, kind, r, x, rows, logits, pick, wts, items, members, cap); + const p = try expertParts(o, kind, r, x, rows, logits, pick, wts, items, members, cap, true); return .{ .y = p.y, .wts = wts, .slots = slots }; } /// Select, plan, gate and up, the activation and down: the rows' slots before the combine. -fn expertParts(o: Ops, kind: Kind, r: Routed, x: Tensor, rows: usize, logits: u64, pick: u64, wts: u64, items: u64, members: u64, cap: usize) ops.Error!struct { y: u64 } { +fn expertParts(o: Ops, kind: Kind, r: Routed, x: Tensor, rows: usize, logits: u64, pick: u64, wts: u64, items: u64, members: u64, cap: usize, prefetch: bool) ops.Error!struct { y: u64 } { const ex = r.experts; const slots = r.top_k + 1; const pairs = rows * slots; var count: usize = cap; var tile: usize = undefined; if (rows == 1) { - try o.moeSelect(logits, pick, wts, .{ .items = items, .members = members }, cap, 1, r.count(), r.top_k); + // the router and the pick (and the plan) in one launch where the decode kernels take it + if (!try o.moeRouterSelect(x, r.rows16, r.done, logits, pick, wts, .{ .items = items, .members = members }, cap, 1, ex.dims, r.rows, r.top_k, 0)) { + try o.moeRouter(x, r.rows32, logits, rows, ex.dims, r.rows); + try o.moeSelect(logits, pick, wts, .{ .items = items, .members = members }, cap, 1, r.count(), r.top_k); + } tile = 1; count = slots; } else { - try o.moeSelect(logits, pick, wts, null, 0, rows, r.count(), r.top_k); tile = tileFor(o, rows); - try o.moeRoute(pick, pairs, r.rows, tile, members, items, cap); + // a verify window's 2 to 8 rows: the router, the pick and tf_moe_route's plan in one launch + const planned = rows <= 8 and try o.moeRouterSelect(x, r.rows16, r.done, logits, pick, wts, .{ .items = items, .members = members }, cap, rows, ex.dims, r.rows, r.top_k, tile); + if (!planned) { + if (!try o.moeRouterSelect(x, r.rows16, r.done, logits, pick, wts, null, 0, rows, ex.dims, r.rows, r.top_k, 0)) { + try o.moeRouter(x, r.rows32, logits, rows, ex.dims, r.rows); + try o.moeSelect(logits, pick, wts, null, 0, rows, r.count(), r.top_k); + } + try o.moeRoute(pick, pairs, r.rows, tile, members, items, cap); + // a prompt plan's launches cover its live items only (the slots past them are dead) + if (tile == BLOCK_ROWS) count = @min(cap, planItems(pairs, r.rows, tile)); + } } + // the live experts' down codes into the caches on the side stream while the gate and up run + if (prefetch and rows <= prefetch_rows and !o.prefill) switch (ex.down.handle) { + .mlx => |h| { + const expert_bytes = @as(usize, ex.down.n) * @as(usize, ex.down.k) * @as(usize, h.bits) / 8; + try o.moePrefetch(items, count, h.words, expert_bytes, r.rows, count * expert_bytes); + }, + .dense => {}, + }; // the gate and up's activation is the launch's epilogue when the tile takes the shape const act_t: Tensor = if (try o.projectRoutedAct(x, ex.fused, items, count, members, pairs, slots, @min(tile, rows), ex.limit)) |t| t else blk: { const both = try o.projectRouted(x, ex.fused, items, count, members, pairs, slots, @min(tile, rows)); @@ -156,6 +189,44 @@ test "buffer sizes follow moe.run and max_items" { try std.testing.expectEqual(@as(usize, 129 + 16 * 9 / 8), capacity(16 * 9, 129)); } +test "a prompt plan's live items are at most planItems, equal with every expert at 128 k + 1 pairs" { + const items = struct { + fn of(counts: []const usize, tile: usize) usize { + var n: usize = 0; + for (counts) |c| n += (c + tile - 1) / tile; + return n; + } + }; + var prng = std.Random.DefaultPrng.init(0x5851F42D4C957F2D); + const rnd = prng.random(); + var counts: [513]usize = undefined; + // the coding prompt in 8,192-row chunks and in one chunk, 11 slots a row + for ([_]usize{ 8192 * 11, 17715 * 11, 20480 * 11 }) |pairs| { + // the bound's case: 128 k + 1 pairs an expert, the pairs past them on one expert (fewer than a tile) + const per = (pairs - counts.len) / counts.len / BLOCK_ROWS; + var used: usize = 0; + for (&counts) |*c| { + c.* = BLOCK_ROWS * per + 1; + used += c.*; + } + var spare = pairs - used; + var e: usize = 0; + while (spare >= BLOCK_ROWS) : (e += 1) { + counts[e] += BLOCK_ROWS; + spare -= BLOCK_ROWS; + } + counts[counts.len - 1] += spare; + try std.testing.expectEqual(planItems(pairs, counts.len, BLOCK_ROWS), items.of(&counts, BLOCK_ROWS)); + // skewed and sparse routings stay under it + for (0..20) |_| { + @memset(&counts, 0); + for (0..pairs) |_| counts[if (rnd.boolean()) rnd.uintLessThan(usize, 8) else rnd.uintLessThan(usize, counts.len)] += 1; + try std.testing.expect(items.of(&counts, BLOCK_ROWS) <= planItems(pairs, counts.len, BLOCK_ROWS)); + } + try std.testing.expect(planItems(pairs, counts.len, BLOCK_ROWS) <= capacity(pairs, counts.len)); + } +} + test "the routed products take the decode tile below 64 rows and in a lane round, the GEMM tile from 64 rows" { const o: Ops = .{ .l = undefined, .bf16 = true, .stream = undefined, .arena = undefined }; var round = o; diff --git a/zig/src/hip/ops/draw.zig b/zig/src/hip/ops/draw.zig index 43d4ecdbcd..45486cc387 100644 --- a/zig/src/hip/ops/draw.zig +++ b/zig/src/hip/ops/draw.zig @@ -36,6 +36,12 @@ pub fn argmaxRows(o: Ops, logits: Tensor, rows: usize, n: usize, out: u64) Error /// Values a part of a wide row's argmax takes. const part_values = 1024; +/// Values a part of a wide row's top-k takes at least, and the most parts a row takes (the join reads parts * stride). +const part_topk = 4096; +const max_topk_parts = 64; +/// Candidates tf_topk_join holds a row (draw.hpp kJoinMost). +const join_most = 4096; + /// softmax(row r)[ids[r]] of `rows` logits rows (fp16 or bf16) into fp32 `out`; of the row's largest when `ids` is 0. pub fn tokenProb(o: Ops, logits: Tensor, rows: usize, n: usize, ids: u64, out: u64) Error!void { if (logits.kind == .f32) return error.BadShape; @@ -45,5 +51,13 @@ pub fn tokenProb(o: Ops, logits: Tensor, rows: usize, n: usize, ids: u64, out: u /// Each row's `ks[r]` largest by (value desc, id asc): ids (i32) and the values' 16-bit patterns, `stride` apart. pub fn topkRows(o: Ops, logits: Tensor, rows: usize, n: usize, ks: u64, stride: usize, ids: u64, values: u64) Error!void { if (logits.kind == .f32) return error.BadShape; + // a wide row in parts over the card, then each row's from the parts' own: the same ids, values and order + const parts = @min(max_topk_parts, (n + part_topk - 1) / part_topk); + if (o.fused() and n >= 2 * part_topk and parts * stride <= join_most) { + const per = (n + parts - 1) / parts; + const cand_ids = try o.arena.of(i32, rows * parts * stride); + const cand_vals = try o.arena.of(u16, rows * parts * stride); + return o.l.tf_topk_parts(p(logits.ptr), int(rows), int(n), i(ks), int(stride), int(per), int(parts), i(cand_ids), p(cand_vals), i(ids), p(values), o.stream); + } try o.l.tf_topk_rows(p(logits.ptr), int(rows), int(n), i(ks), int(stride), i(ids), p(values), o.stream); } diff --git a/zig/src/hip/ops/moe.zig b/zig/src/hip/ops/moe.zig index effaebbe81..059a565928 100644 --- a/zig/src/hip/ops/moe.zig +++ b/zig/src/hip/ops/moe.zig @@ -2,6 +2,8 @@ const t = @import("types.zig"); const Ops = @import("ops.zig").Ops; +const Launcher = @import("../launches.zig").Launcher; +const util = @import("../launches/util.zig"); const Error = t.Error; const Tensor = t.Tensor; const p = t.p; @@ -24,13 +26,21 @@ pub fn moeRouter(o: Ops, x: Tensor, rows32: u64, logits: u64, r: usize, d: usize try o.l.tf_moe_router(p(x.ptr), @backingInt(x.kind), f(rows32), f(logits), int(r), int(d), int(e), o.stream); } +/// Decode router logits (bf16 rows), pick and `plan` (`tile` pairs an item, 0: one row) in one launch; false if not. +pub fn moeRouterSelect(o: Ops, x: Tensor, rows16: u64, done: u64, logits: u64, pick: u64, wts: u64, plan: ?struct { items: u64, members: u64 }, capacity: usize, r: usize, d: usize, e: usize, top_k: usize, tile: usize) Error!bool { + if (o.prefill or rows16 == 0) return false; + return o.l.routerSelect(p(x.ptr), @backingInt(x.kind), @ptrFromInt(rows16), f(logits), i(pick), f(wts), if (plan) |pl| i(pl.items) else null, if (plan) |pl| i(pl.members) else null, int(capacity), int(r), int(d), int(e), int(top_k), int(tile), done, o.stream); +} + /// The pick rule per row; with `plan` (one row) it also writes the plan's items and members. pub fn moeSelect(o: Ops, logits: u64, pick: u64, wts: u64, plan: ?struct { items: u64, members: u64 }, capacity: usize, r: usize, experts: usize, top_k: usize) Error!void { try o.l.tf_moe_select(f(logits), i(pick), f(wts), if (plan) |pl| i(pl.items) else null, if (plan) |pl| i(pl.members) else null, int(capacity), int(r), int(experts), int(top_k), o.stream); } +/// The plan: tf_moe_route's members and items; a prompt's many pairs in three launches over arena scratch. pub fn moeRoute(o: Ops, picks: u64, pairs: usize, experts: usize, tile: usize, members: u64, items: u64, capacity: usize) Error!void { - try o.l.tf_moe_route(@ptrFromInt(picks), int(pairs), int(experts), int(tile), i(members), i(items), int(capacity), o.stream); + const scratch: u64 = if (pairs >= 4 * Launcher.route_seg) try o.arena.take(Launcher.routeScratch(pairs, experts)) else 0; + try o.l.tf_moe_route_wide(@ptrFromInt(picks), int(pairs), int(experts), int(tile), i(members), i(items), int(capacity), scratch, o.stream); } pub fn moeAct(o: Ops, both: u64, out: Tensor, pairs: usize, width: usize, limit: f32) Error!void { @@ -40,3 +50,10 @@ pub fn moeAct(o: Ops, both: u64, out: Tensor, pairs: usize, width: usize, limit: pub fn moeCombine(o: Ops, y: u64, wts: u64, out: Tensor, r: usize, slots: usize, d: usize) Error!void { try o.l.tf_moe_combine(f(y), f(wts), p(out.ptr), @backingInt(out.kind), int(r), int(slots), int(d), o.stream); } + +/// After a fork, read the live `items`' experts' down codes into the caches on the side stream, at most `cap` bytes. +pub fn moePrefetch(o: Ops, items: u64, count: usize, words: u64, expert_bytes: usize, experts: usize, cap: usize) Error!void { + if (o.side.stream == null or o.side.ring == null or o.stream == util.counting) return; + try o.fork(); + try o.l.tf_moe_prefetch(@ptrFromInt(items), int(count), words, @intCast(expert_bytes), int(experts), @intCast(cap), o.side.stream); +} diff --git a/zig/src/hip/ops/ops.zig b/zig/src/hip/ops/ops.zig index 04a17e8410..1459ef8bf3 100644 --- a/zig/src/hip/ops/ops.zig +++ b/zig/src/hip/ops/ops.zig @@ -13,6 +13,7 @@ const elementwise = @import("elementwise.zig"); const moe = @import("moe.zig"); const draw = @import("draw.zig"); const tp = @import("tp.zig"); +const side_stream = @import("../side.zig"); pub const mamba = @import("mamba.zig"); pub const Kind = types.Kind; @@ -33,9 +34,23 @@ pub const Ops = struct { prefill: bool = false, /// A lane round's forward: decode tiles at any row count, so a row's bits ignore the rows it shares a round with. window: bool = false, + /// A stream beside `stream` and its events (none: `fork` and `join` do nothing). + side: side_stream.Side = .{}, + + /// Later work on `side` starts after this stream's work so far. + pub fn fork(o: Ops) Error!void { + return o.side.fork(o.stream); + } + + /// Later work on this stream starts after `side`'s work so far. + pub fn join(o: Ops) Error!void { + return o.side.join(o.stream); + } pub const project = products.project; pub const projectGroup = products.projectGroup; + pub const hcUpMix = products.hcUpMix; + pub const hcUpMixAffine = products.hcUpMixAffine; pub const projectRoutedAct = products.projectRoutedAct; pub const projectRouted = products.projectRouted; pub const projectRelu2 = products.projectRelu2; @@ -72,6 +87,7 @@ pub const Ops = struct { pub const gdnGatePrefill = recurrence.gdnGatePrefill; pub const gdnGate = recurrence.gdnGate; pub const gatedDelta = recurrence.gatedDelta; + pub const gatedDeltaHold = recurrence.gatedDeltaHold; pub const rms = norms.rms; pub const rms2 = norms.rms2; pub const gnormOut = norms.gnormOut; @@ -87,9 +103,11 @@ pub const Ops = struct { pub const moeTail = moe.moeTail; pub const moeRouter = moe.moeRouter; pub const moeSelect = moe.moeSelect; + pub const moeRouterSelect = moe.moeRouterSelect; pub const moeRoute = moe.moeRoute; pub const moeAct = moe.moeAct; pub const moeCombine = moe.moeCombine; + pub const moePrefetch = moe.moePrefetch; pub const argmaxRows = draw.argmaxRows; pub const topkRows = draw.topkRows; pub const tokenProb = draw.tokenProb; diff --git a/zig/src/hip/ops/project.zig b/zig/src/hip/ops/project.zig index 1333f090a4..da17df6a5d 100644 --- a/zig/src/hip/ops/project.zig +++ b/zig/src/hip/ops/project.zig @@ -1,5 +1,6 @@ //! The products on a projection of any format, dispatched on its tag; `affine*` are the MLX affine path behind them. +const std = @import("std"); const t = @import("types.zig"); const quant = @import("core").quant; const launches = @import("../launches.zig"); @@ -236,7 +237,8 @@ pub fn affine(o: Ops, x: Tensor, w: Affine, m: usize, f32_out: bool) Error!Tenso const z = o.l; const shape = shapeOf(o, x, w, m); const tile = z.affine.choose(.project, if (o.prefill) .prefill else .decode, shape) orelse return error.BadShape; - half = !f32_out and !o.prefill and tile.roundsAct(shape); + // a prompt's tiles write fp32 and o.cast rounds it, except the dense tile, which rounds as the cast does + half = !f32_out and tile.roundsAct(shape); const out = try o.arena.take(m * n * @as(usize, if (half) 2 else 4)); { const arg: affine_launch.Arg = .{ @@ -262,6 +264,41 @@ pub fn affine(o: Ops, x: Tensor, w: Affine, m: usize, f32_out: bool) Error!Tenso return .{ .ptr = narrow, .kind = x.kind }; } +/// A prompt's hc up product with the HC mix in the dense tile's epilogue (same bytes); null where that tile won't run. +pub fn hcUpMix(o: Ops, act: Tensor, proj: Projection, x: Tensor, m: usize) Error!?Tensor { + const w = switch (proj.handle) { + .mlx => |h| affineOf(proj, h), + .dense => return null, + }; + return hcUpMixAffine(o, act, w, x, m); +} + +/// hcUpMix over the MLX affine weights `w` (hc up's). +pub fn hcUpMixAffine(o: Ops, act: Tensor, w: Affine, x: Tensor, m: usize) Error!?Tensor { + try w.check(); + if (!o.prefill or m == 0 or act.kind != .bf16 or x.kind != .bf16 or w.k != 320 or w.n % 128 != 0) return null; + const z = o.l; + const tile = z.affine.choose(.project, .prefill, shapeOf(o, act, w, m)) orelse return null; + if (!std.mem.eql(u8, tile.id, "mlx.project.prefill.dense")) return null; + const mixed = try o.arena.take(m * (w.n / 4) * 2); + const kind = w.tables.table(); + const arg: affine_launch.Arg = .{ + .x = act.ptr, + .words = w.words, + .scale = .{ .p = w.scale, .kind = kind }, + .bias = .{ .p = w.bias, .kind = kind }, + .out = 0, + .m = int(m), + .n = int(w.n), + .k = int(w.k), + .bits = w.bits, + .group = w.group, + .fp16 = 0, + }; + try z.affine.denseHcMixGo(z.r, arg, x.ptr, mixed, o.stream); + return .{ .ptr = mixed, .kind = .bf16 }; +} + /// Up to four products of the same rows in one stream-tile launch, rounded to x's kind; false if unsupported. pub fn affineGroup(o: Ops, x: Tensor, ws: []const Affine, m: usize, outs: []Tensor) Error!bool { const z = o.l; @@ -301,9 +338,30 @@ pub fn affineGroup(o: Ops, x: Tensor, ws: []const Affine, m: usize, outs: []Tens /// Routed gate and up in one launch, silu(gate) * up as epilogue into x's kind; null when the tile cannot. pub fn affineRoutedAct(o: Ops, x: Tensor, w: Affine, items: u64, count: usize, members: u64, pairs: usize, x_div: usize, rows: usize, limit: f32) Error!?Tensor { const z = o.l; - if (o.prefill or !o.fused() or x.kind == .f32 or w.n % 2 != 0) return null; + if (!o.fused() or x.kind == .f32 or w.n % 2 != 0) return null; try w.check(); const kind = w.tables.table(); + if (o.prefill) { + // Flash Next's shape on the matrix cores (tiles/moe_gemm.hpp); any other prompt keeps the GEMM and moe_act + var arg: affine_launch.Arg = .{ + .x = x.ptr, + .words = w.words, + .scale = .{ .p = w.scale, .kind = kind }, + .bias = .{ .p = w.bias, .kind = kind }, + .out = 0, + .m = int(rows), + .n = int(w.n), + .k = int(w.k), + .bits = int(w.bits), + .group = int(w.group), + .fp16 = @intFromBool(x.kind == .f16), + .route = .{ .items = items, .members = members, .x_div = int(x_div) }, + }; + if (!z.affine.moeGateUpTakes(arg, int(count))) return null; + arg.out16 = try o.arena.take(pairs * (w.n / 2) * 2); + if (!try z.affine.moeGateUp(z.r, arg, int(count), limit, o.stream)) return error.BadShape; + return .{ .ptr = arg.out16, .kind = x.kind }; + } var shape = shapeOf(o, x, w, rows); shape.pairs = true; if (z.affine.choose(.routed_act, .decode, shape) == null) return null; @@ -334,7 +392,10 @@ pub fn affineRouted(o: Ops, x: Tensor, w: Affine, items: u64, count: usize, memb if (o.prefill) { const z = o.l; const kind = w.tables.table(); - try z.affine.prefillLaunch(z.r, .{ .x = x.ptr, .words = w.words, .scale = .{ .p = w.scale, .kind = kind }, .bias = .{ .p = w.bias, .kind = kind }, .out = out, .m = int(rows), .n = int(w.n), .k = int(w.k), .bits = int(w.bits), .group = int(w.group), .fp16 = @intFromBool(x.kind == .f16), .route = .{ .items = items, .members = members, .x_div = int(x_div) } }, o.stream, int(count), int(pairs)); + const arg: affine_launch.Arg = .{ .x = x.ptr, .words = w.words, .scale = .{ .p = w.scale, .kind = kind }, .bias = .{ .p = w.bias, .kind = kind }, .out = out, .m = int(rows), .n = int(w.n), .k = int(w.k), .bits = int(w.bits), .group = int(w.group), .fp16 = @intFromBool(x.kind == .f16), .route = .{ .items = items, .members = members, .x_div = int(x_div) } }; + // Flash Next's expert down on the matrix cores (tiles/moe_gemm.hpp); any other plan takes the registry's tile + if (try z.affine.moeDown(z.r, arg, int(count), o.stream)) return out; + try z.affine.prefillLaunch(z.r, arg, o.stream, int(count), int(pairs)); return out; } try o.l.tf_affine_routed(p(x.ptr), p(w.words), p(w.scale), p(w.bias), w.tables.table(), p(out), i(items), int(count), i(members), int(x_div), int(rows), int(w.n), int(w.k), w.bits, w.group, @intFromBool(x.kind == .f16), o.stream); diff --git a/zig/src/hip/ops/recurrence.zig b/zig/src/hip/ops/recurrence.zig index cf2b5f8be5..871f1e48f5 100644 --- a/zig/src/hip/ops/recurrence.zig +++ b/zig/src/hip/ops/recurrence.zig @@ -30,7 +30,12 @@ pub fn gdnGate(o: Ops, a: Tensor, b: Tensor, a_log: u64, dt_bias: u64, gate: u64 try o.l.tf_gdn_gate(p(a.ptr), p(b.ptr), @backingInt(a.kind), f(a_log), f(dt_bias), f(gate), f(beta), int(elements), int(heads), o.stream); } -/// The DeltaNet recurrence in fp32, state in place, the same walk at every length. -pub fn gatedDelta(o: Ops, q: u64, k: u64, v: u64, gate: u64, beta: u64, state: u64, y: u64, length: usize, key_heads: usize, value_heads: usize, dk: usize, dv: usize, states: ?u64) Error!void { - try o.l.tf_gated_delta(f(q), f(k), f(v), f(gate), f(beta), f(state), f(y), 1, int(length), int(key_heads), int(value_heads), int(dk), int(dv), o.stream, if (states) |s| f(s) else null); +/// The DeltaNet recurrence in fp32, state in place, same walk at every length; `from`: 0 or a device i32 start row. +pub fn gatedDelta(o: Ops, q: u64, k: u64, v: u64, gate: u64, beta: u64, state: u64, y: u64, length: usize, key_heads: usize, value_heads: usize, dk: usize, dv: usize, states: ?u64, from: u64) Error!void { + try o.l.tf_gated_delta(f(q), f(k), f(v), f(gate), f(beta), f(state), f(y), 1, int(length), int(key_heads), int(value_heads), int(dk), int(dv), o.stream, if (states) |s| f(s) else null, from); +} + +/// A verify window's recurrence that holds the state (outputs `y` only); the keep then runs it through the kept rows. +pub fn gatedDeltaHold(o: Ops, q: u64, k: u64, v: u64, gate: u64, beta: u64, state: u64, y: u64, length: usize, key_heads: usize, value_heads: usize, dk: usize, dv: usize) Error!void { + try o.l.tf_gdn_hold(f(q), f(k), f(v), f(gate), f(beta), f(state), f(y), int(length), int(key_heads), int(value_heads), int(dk), int(dv), o.stream); } diff --git a/zig/src/hip/policy.zig b/zig/src/hip/policy.zig index 827e99720a..62e728d2bd 100644 --- a/zig/src/hip/policy.zig +++ b/zig/src/hip/policy.zig @@ -10,9 +10,15 @@ pub const Attention = enum { auto, f32 }; /// One kernel family switched to its reference, apart from `kernels=reference` that switches them all. pub const Pick = enum { auto, reference }; +/// Where one rank reads host-held row tables (n-gram rows): a resident copy made at load (no faults), or the mapping. +pub const Rows = enum { resident, mapped }; + /// MTP drafting: `--mtp-drafts` and `--mtp-confidence`. pub const Mtp = struct { drafts: u8 = 3, confidence: f64 = 0.3 }; +/// MTP depth: `rule` prices each depth (lanes/depth.zig); `gated` drafts to the cap until a draft under the confidence. +pub const MtpDepth = enum { rule, gated }; + /// A path a rank reads locally (it never travels with the policy). pub const Path = struct { buf: [160]u8 = @splat(0), @@ -38,6 +44,8 @@ pub const Policy = struct { stream: Pick = .auto, gemm: Pick = .auto, fuse: Pick = .auto, + rows: Rows = .resident, + mtp_depth: MtpDepth = .rule, prefill_step: u32 = 1024, /// Prompt rows a chunk while other streams decode: a multiple of 64 dividing 1024 (the idle chunk). fill_rows: u32 = 512, @@ -107,7 +115,7 @@ pub const Policy = struct { fn set(p: *Policy, key: []const u8, value: []const u8) Error!void { const eql = std.mem.eql; - if (eql(u8, key, "matrix")) p.matrix = try parseEnum(Choice, value) else if (eql(u8, key, "attention")) p.attention = try parseEnum(Attention, value) else if (eql(u8, key, "kernels")) p.kernels = try parseEnum(Pick, value) else if (eql(u8, key, "graphs")) p.graphs = try parseEnum(Choice, value) else if (eql(u8, key, "stream")) p.stream = try parseEnum(Pick, value) else if (eql(u8, key, "gemm")) p.gemm = try parseEnum(Pick, value) else if (eql(u8, key, "fuse")) p.fuse = try parseEnum(Pick, value) else if (eql(u8, key, "prefill_step")) { + if (eql(u8, key, "matrix")) p.matrix = try parseEnum(Choice, value) else if (eql(u8, key, "attention")) p.attention = try parseEnum(Attention, value) else if (eql(u8, key, "kernels")) p.kernels = try parseEnum(Pick, value) else if (eql(u8, key, "graphs")) p.graphs = try parseEnum(Choice, value) else if (eql(u8, key, "stream")) p.stream = try parseEnum(Pick, value) else if (eql(u8, key, "gemm")) p.gemm = try parseEnum(Pick, value) else if (eql(u8, key, "fuse")) p.fuse = try parseEnum(Pick, value) else if (eql(u8, key, "rows")) p.rows = try parseEnum(Rows, value) else if (eql(u8, key, "mtp_depth")) p.mtp_depth = try parseEnum(MtpDepth, value) else if (eql(u8, key, "prefill_step")) { p.prefill_step = std.fmt.parseInt(u32, value, 10) catch return error.BadValue; } else if (eql(u8, key, "fill_rows")) { p.fill_rows = std.fmt.parseInt(u32, value, 10) catch return error.BadValue; @@ -126,6 +134,8 @@ pub const Policy = struct { if (p.stream != .auto) try w.print(",stream={t}", .{p.stream}); if (p.gemm != .auto) try w.print(",gemm={t}", .{p.gemm}); if (p.fuse != .auto) try w.print(",fuse={t}", .{p.fuse}); + if (p.rows != .resident) try w.print(",rows={t}", .{p.rows}); + if (p.mtp_depth != .rule) try w.print(",mtp_depth={t}", .{p.mtp_depth}); if (p.graph_fail >= 0) try w.print(",graph_fail={d}", .{p.graph_fail}); if (p.rccl_lib.slice()) |path| try w.print(",rccl_lib={s}", .{path}); try w.print("; mtp drafts {d} under {d}, {d} snapshots", .{ p.mtp.drafts, p.mtp.confidence, p.slots }); @@ -137,8 +147,9 @@ pub const Policy = struct { pub fn words(p: Policy) [word_count]u32 { const conf: u64 = @bitCast(p.mtp.confidence); const pack = [_]u32{ - @backingInt(p.matrix), @backingInt(p.attention), @backingInt(p.kernels), @backingInt(p.graphs), - @backingInt(p.stream), @backingInt(p.gemm), @backingInt(p.fuse), + @backingInt(p.matrix), @backingInt(p.attention), @backingInt(p.kernels), @backingInt(p.graphs), + @backingInt(p.stream), @backingInt(p.gemm), @backingInt(p.fuse), @backingInt(p.rows), + @backingInt(p.mtp_depth), }; var nibbles: [2]u32 = .{ 0, 0 }; for (pack, 0..) |v, i| nibbles[i / 8] |= v << @intCast(4 * (i % 8)); @@ -148,7 +159,7 @@ pub const Policy = struct { /// `local` with every field rank 0 sent; a rank keeps its own graph fault and library path. pub fn fromWords(w: [word_count]u32, local: Policy) Policy { var p = local; - var vals: [7]u32 = undefined; + var vals: [9]u32 = undefined; for (&vals, 0..) |*v, i| v.* = (w[i / 8] >> @intCast(4 * (i % 8))) & 0xf; p.matrix = @fromBackingInt(@intCast(vals[0])); p.attention = @fromBackingInt(@intCast(vals[1])); @@ -157,6 +168,8 @@ pub const Policy = struct { p.stream = @fromBackingInt(@intCast(vals[4])); p.gemm = @fromBackingInt(@intCast(vals[5])); p.fuse = @fromBackingInt(@intCast(vals[6])); + p.rows = @fromBackingInt(@intCast(vals[7])); + p.mtp_depth = @fromBackingInt(@intCast(vals[8])); p.mtp = .{ .drafts = @truncate(w[1] >> 24), .confidence = @bitCast(@as(u64, w[3]) | @as(u64, w[4]) << 32) }; p.prefill_step = w[2]; p.slots = w[5]; @@ -195,6 +208,21 @@ pub const Policy = struct { } }; + /// Whether `flags` (`--policy`) or TF_POLICY names `key`: a family's own default applies only where neither does. + pub fn names(flags: []const u8, env: Env, key: []const u8) bool { + if (namesIn(flags, key)) return true; + return if (env.get("TF_POLICY")) |text| namesIn(text, key) else false; + } + + fn namesIn(text: []const u8, key: []const u8) bool { + var it = std.mem.tokenizeAny(u8, text, ", "); + while (it.next()) |pair| { + const eq = std.mem.indexOfScalar(u8, pair, '=') orelse continue; + if (std.mem.eql(u8, pair[0..eq], key)) return true; + } + return false; + } + /// The policy: defaults, then `flags` (`--policy`), then TF_POLICY; `notes` says when TF_POLICY acted. pub fn resolve(flags: []const u8, env: Env, notes: *Notes) Error!Policy { var p: Policy = .{}; @@ -223,9 +251,17 @@ test "apply sets fields and refuses what it does not know" { try std.testing.expectEqual(@as(u32, 256), p.fill_rows); } +test "names sees a key in the flags or in TF_POLICY, and only as a key" { + try std.testing.expect(Policy.names("matrix=on,prefill_step=1024", .none, "prefill_step")); + try std.testing.expect(!Policy.names("matrix=on", .none, "prefill_step")); + try std.testing.expect(!Policy.names("graphs=off", .none, "prefill")); + try std.testing.expect(Policy.names("", .{ .vars = &.{.{ "TF_POLICY", "prefill_step=4096" }} }, "prefill_step")); + try std.testing.expect(!Policy.names("", .{ .vars = &.{.{ "TF_POLICY", "fill_rows=256" }} }, "prefill_step")); +} + test "a policy survives its words" { var p: Policy = .{ .mtp = .{ .drafts = 2, .confidence = 0.25 }, .slots = 4, .graph_fail = 1 }; - try p.apply("matrix=on,attention=f32,graphs=off,fuse=reference,fill_rows=128"); + try p.apply("matrix=on,attention=f32,graphs=off,fuse=reference,fill_rows=128,rows=mapped,mtp_depth=gated"); const back = Policy.fromWords(p.words(), .{ .graph_fail = 1 }); try std.testing.expectEqualDeep(p, back); } diff --git a/zig/src/hip/root.zig b/zig/src/hip/root.zig index f7aae9d257..02b654f10a 100644 --- a/zig/src/hip/root.zig +++ b/zig/src/hip/root.zig @@ -11,6 +11,8 @@ pub const HostBuffer = memory.HostBuffer; pub const usage = memory.usage; pub const Usage = memory.Usage; pub const Stream = @import("stream.zig").Stream; +/// A second stream beside a step's own, with the events its forks and joins take. +pub const side = @import("side.zig"); pub const Module = @import("module.zig").Module; pub const Function = @import("module.zig").Function; pub const launch = @import("launch.zig"); @@ -53,6 +55,7 @@ pub const loopback = @import("comm/loopback.zig"); test { _ = policy; + _ = side; _ = admission; _ = Device; _ = collective; diff --git a/zig/src/hip/side.zig b/zig/src/hip/side.zig new file mode 100644 index 0000000000..701b948c7b --- /dev/null +++ b/zig/src/hip/side.zig @@ -0,0 +1,140 @@ +//! A second HIP stream beside a step's own: `fork` gives it the step's work so far, `join` gives its work back. +const std = @import("std"); +const abi = @import("abi.zig"); +const runtime = @import("runtime.zig"); +const util = @import("launches/util.zig"); + +/// Ordering events forks and joins take in turn: 256 gives each record of one captured forward its own event. +pub const ring_len = 256; + +/// A slot is recorded and waited on in one call and a wait takes the record queued before it, so the ring may wrap. +pub const Ring = struct { + r: *const runtime.Runtime, + events: [ring_len]abi.Event = @splat(null), + next: usize = 0, + + pub fn init(r: *const runtime.Runtime) runtime.Error!Ring { + var ring: Ring = .{ .r = r }; + errdefer ring.deinit(); + for (&ring.events) |*e| { + try runtime.check(r.api.hipEventCreateWithFlags(e, abi.event_disable_timing)); + if (e.* == null) return error.Invalid; + } + return ring; + } + + pub fn deinit(ring: *Ring) void { + for (ring.events) |e| if (e != null) { + _ = ring.r.api.hipEventDestroy(e); + }; + ring.* = undefined; + } + + fn take(ring: *Ring) abi.Event { + const e = ring.events[ring.next]; + ring.next = (ring.next + 1) % ring_len; + return e; + } +}; + +/// The side stream and its events, as `Ops` carries them (both null: no side stream, `fork` and `join` do nothing). +pub const Side = struct { + stream: abi.Stream = null, + ring: ?*Ring = null, + + fn on(s: Side, main: abi.Stream) bool { + return s.stream != null and s.ring != null and main != util.counting; + } + + /// Later work on the side stream starts after `main`'s work so far. + pub fn fork(s: Side, main: abi.Stream) runtime.Error!void { + if (!s.on(main)) return; + const ring = s.ring.?; + const e = ring.take(); + try runtime.check(ring.r.api.hipEventRecord(e, main)); + try runtime.check(ring.r.api.hipStreamWaitEvent(s.stream, e, 0)); + } + + /// Later work on `main` starts after the side stream's work so far. + pub fn join(s: Side, main: abi.Stream) runtime.Error!void { + if (!s.on(main)) return; + const ring = s.ring.?; + const e = ring.take(); + try runtime.check(ring.r.api.hipEventRecord(e, s.stream)); + try runtime.check(ring.r.api.hipStreamWaitEvent(main, e, 0)); + } +}; + +test "fork records on the main stream and the side waits; join the other way; off without a side or when counting" { + const Mock = struct { + var log: [8]struct { what: u8, stream: usize, event: usize } = undefined; + var n: usize = 0; + fn record(e: abi.Event, s: abi.Stream) callconv(.c) c_int { + log[n] = .{ .what = 'r', .stream = @intFromPtr(s), .event = @intFromPtr(e) }; + n += 1; + return 0; + } + fn wait(s: abi.Stream, e: abi.Event, _: c_uint) callconv(.c) c_int { + log[n] = .{ .what = 'w', .stream = @intFromPtr(s), .event = @intFromPtr(e) }; + n += 1; + return 0; + } + }; + var r: runtime.Runtime = undefined; + r.api.hipEventRecord = Mock.record; + r.api.hipStreamWaitEvent = Mock.wait; + var ring: Ring = .{ .r = &r }; + for (&ring.events, 0..) |*e, i| e.* = @ptrFromInt(0x1000 + i); + const main: abi.Stream = @ptrFromInt(0x10); + const side: Side = .{ .stream = @ptrFromInt(0x20), .ring = &ring }; + try side.fork(main); + try side.join(main); + try std.testing.expectEqual(@as(usize, 4), Mock.n); + try std.testing.expectEqual(@as(u8, 'r'), Mock.log[0].what); + try std.testing.expectEqual(@as(usize, 0x10), Mock.log[0].stream); + try std.testing.expectEqual(@as(usize, 0x20), Mock.log[1].stream); + try std.testing.expectEqual(Mock.log[0].event, Mock.log[1].event); + try std.testing.expectEqual(@as(usize, 0x20), Mock.log[2].stream); + try std.testing.expectEqual(@as(usize, 0x10), Mock.log[3].stream); + try std.testing.expect(Mock.log[2].event != Mock.log[0].event); + try (Side{}).fork(main); + try side.join(util.counting); + try std.testing.expectEqual(@as(usize, 4), Mock.n); +} + +test "more forks than the ring before one join: each wait follows its own record at once, the slots wrap in order" { + const Mock = struct { + var last_record: usize = 0; + var records: usize = 0; + var waits: usize = 0; + var paired: bool = true; + var first: [3]usize = .{ 0, 0, 0 }; + fn record(e: abi.Event, _: abi.Stream) callconv(.c) c_int { + if (records == waits + 1) paired = false; // a record while another one's wait is outstanding + last_record = @intFromPtr(e); + if (records < 3) first[records] = last_record; + records += 1; + return 0; + } + fn wait(_: abi.Stream, e: abi.Event, _: c_uint) callconv(.c) c_int { + if (@intFromPtr(e) != last_record or waits + 1 != records) paired = false; + waits += 1; + return 0; + } + }; + var r: runtime.Runtime = undefined; + r.api.hipEventRecord = Mock.record; + r.api.hipStreamWaitEvent = Mock.wait; + var ring: Ring = .{ .r = &r }; + for (&ring.events, 0..) |*e, i| e.* = @ptrFromInt(0x1000 + i); + const side: Side = .{ .stream = @ptrFromInt(0x20), .ring = &ring }; + const forks = 2 * ring_len + 3; + for (0..forks) |_| try side.fork(@ptrFromInt(0x10)); + try side.join(@ptrFromInt(0x10)); + try std.testing.expect(Mock.paired); + try std.testing.expectEqual(@as(usize, forks + 1), Mock.records); + try std.testing.expectEqual(@as(usize, forks + 1), Mock.waits); + // the join took slot (forks mod ring_len): the ring wrapped twice in order + try std.testing.expectEqual(@as(usize, 0x1000 + forks % ring_len), Mock.last_record); + try std.testing.expectEqual(@as(usize, 0x1001), Mock.first[1]); +} diff --git a/zig/src/hip/tuning/gfx1100.zon b/zig/src/hip/tuning/gfx1100.zon index 462330a8b1..42d0c0f5d9 100644 --- a/zig/src/hip/tuning/gfx1100.zon +++ b/zig/src/hip/tuning/gfx1100.zon @@ -32,6 +32,7 @@ .{ .id = "mlx.project.prefill.kp3", .cost = 2, .items = 300, .plain = false }, .{ .id = "mlx.project.prefill.kp1", .cost = 3, .rows = 4, .items = 300 }, .{ .id = "mlx.project.prefill.kp2", .cost = 4, .rows = 32, .routed = false }, + .{ .id = "mlx.project.prefill.dense", .cost = 9 }, .{ .id = "mlx.project.prefill.matrix", .cost = 10 }, .{ .id = "mlx.project.prefill.gemm", .cost = 11 }, .{ .id = "mlx.project.prefill.block", .cost = 12 }, diff --git a/zig/src/native/draft_sources_hip_test.zig b/zig/src/native/draft_sources_hip_test.zig index 475b23d0c5..56fb594ead 100644 --- a/zig/src/native/draft_sources_hip_test.zig +++ b/zig/src/native/draft_sources_hip_test.zig @@ -40,6 +40,7 @@ test "draft sources: HIP Flash Next checkpoint head and explicit zero" { var e: f.engine.Engine = undefined; var b: f.lanes.Fx = undefined; b.e = &e; + b.costs = .{}; b.streams = 4; b.drafts = 3; e.weights.model.mtp = null; diff --git a/zig/src/native/hip.zig b/zig/src/native/hip.zig index 77f7a29d3c..775c6fdcfe 100644 --- a/zig/src/native/hip.zig +++ b/zig/src/native/hip.zig @@ -50,6 +50,26 @@ fn matrixRefused(policy: hip.Policy, caps: hip.Caps) ?[]const u8 { }; } +/// Drafts family `F` verifies at most: its own `max_drafts` (Flash Next 7), else 3 (the other HIP heads' `max_depth`). +fn draftCap(comptime F: type) u32 { + return if (@hasDecl(F, "max_drafts")) F.max_drafts else 3; +} + +/// A family's own MTP policy (`policy_mtp`) where no --mtp-drafts, no --mtp-confidence and no mtp_depth key names one. +fn familyMtp(comptime F: type, o: api.Open, env: hip.Policy.Env, policy: *hip.Policy) void { + if (!@hasDecl(F, "policy_mtp") or o.mtp_drafts != null or o.mtp_confidence != null) return; + if (hip.Policy.names(o.policy, env, "mtp_depth")) return; + policy.mtp = .{ .drafts = F.policy_mtp.drafts, .confidence = F.policy_mtp.confidence }; + policy.mtp_depth = F.policy_mtp.depth; +} + +/// The widest draft cap of any HIP family: what every rank refuses past before it knows the family. +const most_drafts: u32 = blk: { + var most: u32 = 0; + for (registry) |F| most = @max(most, draftCap(F)); + break :blk most; +}; + /// The tensor-parallel flags as the Python ROCm server checks them, and the flags this engine cannot take. fn checkGroup(a: Allocator, o: api.Open, problem: *[]const u8) Refused!void { if (o.drafter != null) return refuse(a, problem, "--drafter: the HIP engine runs no DFlash2 drafter yet; serve without --drafter", .{}); @@ -60,7 +80,7 @@ fn checkGroup(a: Allocator, o: api.Open, problem: *[]const u8) Refused!void { if (o.tp == 1 and o.rank != 0) return refuse(a, problem, "--rank must be 0 when --tp 1", .{}); if (o.rank >= o.tp) return refuse(a, problem, "--rank {d} not in [0, --tp {d})", .{ o.rank, o.tp }); if (o.keep) |n| if (n < 0) return refuse(a, problem, "--checkpoint-slots must be 0 or more", .{}); - if (o.mtp_drafts) |n| if (n > 3) return refuse(a, problem, "--mtp-drafts {d}: the HIP engine drafts at most 3", .{n}); + if (o.mtp_drafts) |n| if (n > most_drafts) return refuse(a, problem, "--mtp-drafts {d}: the HIP engine drafts at most {d}", .{ n, most_drafts }); if (o.mtp_confidence) |c| if (c < 0 or c > 1) return refuse(a, problem, "--mtp-confidence must be from 0 to 1", .{}); if (o.prompt_cache_gib) |g| if (g < 0) return refuse(a, problem, "--prompt-cache-gib must be 0 or more", .{}); } @@ -92,6 +112,7 @@ fn cacheRefused(o: api.Open) ?[]const u8 { /// Resolves the policy on rank 0 (defaults, flags, old variables, TF_POLICY), joins the group, sends it to the others. fn ready(comptime F: type, a: Allocator, gpa: Allocator, io: std.Io, o: api.Open, problem: *[]const u8) (Refused || Allocator.Error)!Ready { try checkGroup(a, o, problem); + if (o.mtp_drafts) |n| if (n > draftCap(F)) return refuse(a, problem, "--mtp-drafts {d}: {s} drafts at most {d} on HIP", .{ n, F.model_type, draftCap(F) }); if (cacheRefused(o)) |why| return refuse(a, problem, "{s}", .{why}); const native = modelContext(a, io, o.dir); const window = admission.contextWindow(o.context, native, F.default_context) catch |err| return switch (err) { @@ -103,8 +124,11 @@ fn ready(comptime F: type, a: Allocator, gpa: Allocator, io: std.Io, o: api.Open const caps = hip.Device.capsOf(index) orelse return refuse(a, problem, "HIP device {d} is not a GPU this engine supports", .{index}); var notes: hip.Policy.Notes = .{}; var policy = hip.Policy.resolve(o.policy, .current, ¬es) catch |err| return refuse(a, problem, "the policy \"{s}\" is refused ({s})", .{ o.policy, @errorName(err) }); + familyMtp(F, o, .current, &policy); if (o.mtp_drafts) |n| policy.mtp.drafts = @intCast(n); if (o.mtp_confidence) |c| policy.mtp.confidence = c; + // a family's own prompt chunk where neither --policy nor TF_POLICY names one; rank 0's policy reaches every rank + if (@hasDecl(F, "policy_prefill_step") and !hip.Policy.names(o.policy, .current, "prefill_step")) policy.prefill_step = F.policy_prefill_step; if (o.keep) |n| policy.slots = @intCast(@min(n, 1 << 16)); if (matrixRefused(policy, caps)) |why| return refuse(a, problem, "matrix=on: {s}; matrix=auto runs the dot2 tiles", .{why}); const group: ?hip.collective.Group = if (o.tp > 1) try join(a, gpa, io, o, caps, &policy, problem) else null; @@ -363,6 +387,40 @@ test "the group flags: one rank source, a supported world, a master past one ran try std.testing.expectError(error.Refused, checkGroup(a, outside, &problem)); } +test "--mtp-drafts: Flash Next verifies up to 7 drafts on HIP, the other families 3; past 7 every rank refuses" { + try std.testing.expectEqual(@as(u32, 7), draftCap(flashnext.native)); + try std.testing.expectEqual(@as(u32, 3), draftCap(qwen35.native)); + try std.testing.expectEqual(@as(u32, 3), draftCap(nemotron.native)); + try std.testing.expectEqual(@as(u32, 7), most_drafts); + var arena: std.heap.ArenaAllocator = .init(std.testing.allocator); + defer arena.deinit(); + const a = arena.allocator(); + var problem: []const u8 = ""; + try checkGroup(a, .{ .dir = "d", .model_type = "qwen4_exp", .mtp_drafts = 7 }, &problem); + try std.testing.expectError(error.Refused, checkGroup(a, .{ .dir = "d", .model_type = "qwen4_exp", .mtp_drafts = 8 }, &problem)); + try std.testing.expectStringStartsWith(problem, "--mtp-drafts 8: the HIP engine drafts at most 7"); +} + +test "Flash Next's own MTP policy (gated, 7 drafts under 0.9) where no flag or key names one; the others keep the HIP default" { + const base: api.Open = .{ .dir = "d", .model_type = "qwen4_exp" }; + var p: hip.Policy = .{}; + familyMtp(flashnext.native, base, .none, &p); + try std.testing.expectEqual(@as(u8, 7), p.mtp.drafts); + try std.testing.expectEqual(@as(f64, 0.9), p.mtp.confidence); + try std.testing.expectEqual(hip.policy.MtpDepth.gated, p.mtp_depth); + for ([_]api.Open{ .{ .dir = "d", .model_type = "qwen4_exp", .mtp_drafts = 3 }, .{ .dir = "d", .model_type = "qwen4_exp", .mtp_confidence = 0 }, .{ .dir = "d", .model_type = "qwen4_exp", .policy = "mtp_depth=rule" } }) |named| { + var q: hip.Policy = .{}; + familyMtp(flashnext.native, named, .none, &q); + try std.testing.expectEqualDeep(hip.Policy{}, q); + } + var env_named: hip.Policy = .{}; + familyMtp(flashnext.native, base, .{ .vars = &.{.{ "TF_POLICY", "mtp_depth=rule" }} }, &env_named); + try std.testing.expectEqualDeep(hip.Policy{}, env_named); + var other: hip.Policy = .{}; + familyMtp(qwen35.native, .{ .dir = "d", .model_type = "qwen3_5" }, .none, &other); + try std.testing.expectEqualDeep(hip.Policy{}, other); +} + test "--drafter is refused before any load, on every rank, until the HIP engine runs DFlash2" { var arena: std.heap.ArenaAllocator = .init(std.testing.allocator); defer arena.deinit(); diff --git a/zig/tests/flashnext_hip/main.zig b/zig/tests/flashnext_hip/main.zig index ddfe9e40d9..d96a2da62e 100644 --- a/zig/tests/flashnext_hip/main.zig +++ b/zig/tests/flashnext_hip/main.zig @@ -7,7 +7,7 @@ const tokenizer = @import("tokenizer"); /// No per-thread alternate signal stack: its thread-local leaves RCCL's and HIP's threads too little stack to start. pub const std_options: std.Options = .{ .signal_stack_size = null }; -const usage = "usage: tf-flashnext-hip-test generate [--tp N --rank R --master H --port P --policy P] [--text T] [--chat] [--max N] [--capacity N] [--repeat N] [--chunk N] [--hash]\n"; +const usage = "usage: tf-flashnext-hip-test generate [--tp N --rank R --master H --port P --policy P] [--text T] [--chat] [--max N] [--capacity N] [--repeat N] [--chunk N] [--hash] [--margins N]\n"; const Args = struct { dir: []const u8 = "", @@ -24,6 +24,8 @@ const Args = struct { chunk: usize = 512, /// Print a hash of every step's whole logits row, to compare builds and policies bit for bit. hash: bool = false, + /// Print the first N steps' two best tokens and their logits (a near-tie shows as a small gap). + margins: usize = 0, }; fn parse(args: []const [:0]const u8) !Args { @@ -58,6 +60,8 @@ fn parse(args: []const [:0]const u8) !Args { a.repeat = try std.fmt.parseInt(usize, v, 10) else if (std.mem.eql(u8, name, "--chunk")) a.chunk = try std.fmt.parseInt(usize, v, 10) + else if (std.mem.eql(u8, name, "--margins")) + a.margins = try std.fmt.parseInt(usize, v, 10) else return error.UnknownOption; } @@ -124,16 +128,18 @@ fn generate(gpa: std.mem.Allocator, io: std.Io, a: Args) !void { var digest = std.hash.Fnv1a_64.init(); const first = try e.logits(o, last, 1); if (a.hash) try mix(e, &digest, first); + if (a.margins > 0 and loud) try margin(e, first, 0); try e.drawer.draw(o, e.stream, first, &.{.{ .sampling = null, .position = prompt.len }}, &next, false); const p1 = nowNs(io); var reply: std.ArrayList(u32) = .empty; try reply.append(arena.allocator(), next[0]); - for (1..a.max) |_| { + for (1..a.max) |n_step| { const step = [1]u32{next[0]}; const seg = [_]fx.forward.Seg{.{ .c = &c, .tokens = &step, .pos = c.len }}; const y = (try e.round(&seg, try e.choose(&seg))).logits; o = e.ops(&e.arena); if (a.hash) try mix(e, &digest, y); + if (n_step < a.margins and loud) try margin(e, y, n_step); try e.drawer.draw(o, e.stream, y, &.{.{ .sampling = null, .position = c.len + 1 }}, &next, false); try e.keepWindow(&c, &step, 1); try reply.append(arena.allocator(), next[0]); @@ -160,6 +166,23 @@ fn generate(gpa: std.mem.Allocator, io: std.Io, a: Args) !void { } } +/// Step `n`'s two best tokens and their logits (bf16 or fp16 rows), read back after the stream's work. +fn margin(e: *fx.engine.Engine, y: hip.ops.Tensor, n: usize) !void { + const row = try e.gpa.alloc(u16, e.cfg.vocab); + defer e.gpa.free(row); + try e.stream.synchronize(); + try hip.runtime.check(e.driver.api.hipMemcpyDtoH(@ptrCast(row.ptr), @ptrFromInt(y.ptr), row.len * 2)); + var best: [2]struct { id: usize, v: f32 } = .{ .{ .id = 0, .v = -std.math.inf(f32) }, .{ .id = 0, .v = -std.math.inf(f32) } }; + for (row, 0..) |b, i| { + const v: f32 = if (y.kind == .f16) @floatCast(@as(f16, @bitCast(b))) else @bitCast(@as(u32, b) << 16); + if (v > best[0].v) { + best[1] = best[0]; + best[0] = .{ .id = i, .v = v }; + } else if (v > best[1].v) best[1] = .{ .id = i, .v = v }; + } + std.debug.print("margin step {d}: {d} {d:.4}, {d} {d:.4}, gap {d:.4}\n", .{ n, best[0].id, best[0].v, best[1].id, best[1].v, best[0].v - best[1].v }); +} + /// One logits row folded into `digest`, read back after the stream's work. fn mix(e: *fx.engine.Engine, digest: *std.hash.Fnv1a_64, y: hip.ops.Tensor) !void { const bytes = try e.gpa.alloc(u8, e.cfg.vocab * y.kind.size()); diff --git a/zig/tests/hip/contract_fn_qsa.zig b/zig/tests/hip/contract_fn_qsa.zig new file mode 100644 index 0000000000..4969618e31 --- /dev/null +++ b/zig/tests/hip/contract_fn_qsa.zig @@ -0,0 +1,366 @@ +//! Flash Next's QSA decode prep under the contract on HIP: one launch, bit-equal to the seven launches it replaces. +const std = @import("std"); +const hip = @import("hip"); +const core = @import("core"); +const rig_ = @import("contract_rig.zig"); +const kit = @import("contract_kit.zig"); + +const contract = core.contract; +const c = contract.spec; +const g = contract.gates; +const rows = contract.rows; + +/// Flash Next's QSA layer: 24 query heads and 2 kv heads of 256, 4 index heads of 128 and the raw index key after them. +const heads = 24; +const kv_heads = 2; +const hd = 256; +const ih = 4; +const di = 128; +const width = (ih + 1) * di; +const ratio = 4; +const rotary = 64; +const theta: f32 = 10_000_000; +const eps: f32 = 1e-6; +/// The first row's position: rows from it complete blocks at 1023, 1027 and on, each block's first rows cached before. +const first = 1021; +const cap = 1088; +const slots = cap / ratio; + +/// The launch's fp32 q and index q rows, or the caches it writes (keys, values, raw index keys, pooled keys). +pub const Part = enum { wide, caches }; + +/// A lane's 16 squares of a 512-wide head and the wave's xor tree; a pool's block tree is no deeper. +fn normDepth(_: c.Shape) usize { + return 1 + 512 / 32 + 5; +} + +const why = "the outputs pass two roundings to the activation kind: a bf16 sum of squares misses by a few of " ++ + "their ulps (fp16's overflows)"; + +const names = [2][2][]const u8{ + .{ "hip flashnext tf_fn_qsa_prep (q and index q rows, fp16)", "hip flashnext tf_fn_qsa_prep (q and index q rows, bf16)" }, + .{ "hip flashnext tf_fn_qsa_prep (caches and pools, fp16)", "hip flashnext tf_fn_qsa_prep (caches and pools, bf16)" }, +}; + +/// A decode row, a draft window, a verify window under the prompt path's 16 rows. +const served = [_]c.Shape{ + .{ .rows = 1, .n = heads, .k = hd }, + .{ .rows = 4, .n = heads, .k = hd }, + .{ .rows = 15, .n = heads, .k = hd }, +}; + +pub fn spec(p: Part, k: kit.Kind) c.Spec { + return .{ + .name = names[@backingInt(p)][@intFromBool(k == .bf16)], + .accum = .f32, + .depth = normDepth, + .ops = 8, + .mids = 1, + .out = if (p == .wide) .f32 else kit.elem(k), + .replaces = "tf_qk_rope (q, index q, k), tf_kv_write_at (v, raw key), tf_copy_cols and tf_fn_idx_pool_at", + // the rows' block ends: 4 positions a pooled block + .tiles = .{ .{ .size = ratio }, .{}, .{} }, + .served = &served, + .sums = .{ .bf16 = 0, .why = why }, + }; +} + +/// shape.rows rows at positions first ..: their projections of the kind, the caches' earlier contents prepared. +pub const Qsa = struct { + rig: rig_.Rig, + l: *const hip.Launcher, + k: kit.Kind, + part: Part, + arena: std.heap.ArenaAllocator, + shape: c.Shape = undefined, + qg: []f64 = &.{}, // [rows][24][512]: q, then the gate + kr: []f64 = &.{}, // [rows][2][256] + vr: []f64 = &.{}, + idx: []f64 = &.{}, // [rows][640]: the index q heads, then the raw key + w: [4][]f64 = undefined, // q, index q, k and pool norms + before: [4][]f64 = undefined, // K [2][cap][256], V, raw [cap][128], pooled [slots][128] before the launch + before_bytes: [4][]u8 = undefined, + tol: []f64 = &.{}, + dev: [9]u64 = @splat(0), // qg, k, v, idx, the four norms, positions + outs: [6]u64 = @splat(0), // q rows, index q rows, K, V, raw, pooled + base: [7]u64 = @splat(0), // the same for the replaced launches, and the copied raw keys + + pub fn init(a: std.mem.Allocator, rt: *const hip.Runtime, s: hip.Stream, l: *const hip.Launcher, p: Part) Qsa { + return .{ .rig = .{ .a = a, .r = rt, .s = s }, .l = l, .k = kit.act(), .part = p, .arena = .init(a) }; + } + + pub fn deinit(self: *Qsa) void { + self.arena.deinit(); + self.rig.deinit(); + } + + pub fn kernel(self: *Qsa) g.Kernel { + return .{ .spec = spec(self.part, self.k), .ctx = self, .vt = &vt }; + } + + const vt = g.hooks(Qsa); + + fn lens(self: *const Qsa) [6]usize { + const n = self.shape.rows; + return .{ n * heads * hd, n * ih * di, kv_heads * cap * hd, kv_heads * cap * hd, cap * di, slots * di }; + } + + fn values(self: *Qsa, rng: std.Random, n: usize, stress: bool) ![]f64 { + const v = try self.arena.allocator().alloc(f64, n); + for (v) |*x| x.* = if (stress) + @floatFromInt(@as(i32, @intCast(rng.uintLessThan(u32, 129))) - 64) + else + kit.round(self.k, rng.float(f64) * 4 - 2); + return v; + } + + /// Projections in [-2, 2) of the kind, norms in [1, 1.5); gate 4: integers in [-64, 64] and unit norms. + pub fn prepare(self: *Qsa, shape: c.Shape, fill: g.Fill, seed: u64) !bool { + if (shape.rows == 0 or shape.rows > cap - first or shape.n != heads or shape.k != hd) return false; + self.rig.reset(); + _ = self.arena.reset(.retain_capacity); + self.shape = shape; + const a = self.arena.allocator(); + var prng = std.Random.DefaultPrng.init(seed); + const rng = prng.random(); + const n = shape.rows; + const stress = fill == .stress; + self.qg = try self.values(rng, n * heads * 2 * hd, stress); + self.kr = try self.values(rng, n * kv_heads * hd, stress); + self.vr = try self.values(rng, n * kv_heads * hd, stress); + self.idx = try self.values(rng, n * width, stress); + const l = self.lens(); + for (&self.before, l[2..]) |*x, len| x.* = try self.values(rng, len, stress); + for (&self.w, [4]usize{ hd, di, hd, di }) |*x, len| { + x.* = try a.alloc(f64, len); + for (x.*) |*v| v.* = if (stress) 1 else @as(f32, @floatCast(1 + rng.float(f64) * 0.5)); + } + if (fill == .nonfinite) self.plant(); + const kb = kit.size(self.k); + const ins = [4][]f64{ self.qg, self.kr, self.vr, self.idx }; + for (ins, self.dev[0..4]) |vals, *at| at.* = try self.rig.input(try self.kindBytes(vals)); + for (self.w, self.dev[4..8]) |vals, *at| at.* = try self.rig.input(try kit.f32Bytes(a, vals)); + const pos = try a.alloc(i32, n); + for (pos, 0..) |*p, r| p.* = @intCast(first + r); + self.dev[8] = try self.rig.input(std.mem.sliceAsBytes(pos)); + for (&self.before_bytes, self.before) |*b, vals| b.* = try self.kindBytes(vals); + const sizes = [6]usize{ l[0] * 4, l[1] * 4, l[2] * kb, l[3] * kb, l[4] * kb, l[5] * kb }; + for (&self.outs, sizes, 0..) |*at, len, i| { + const mine = (i < 2) == (self.part == .wide); + at.* = if (mine) try self.rig.output(len) else try self.rig.scratch(len); + } + for (self.base[0..6], sizes) |*at, len| at.* = try self.rig.scratch(len); + self.base[6] = try self.rig.scratch(n * di * kb); + return true; + } + + fn kindBytes(self: *Qsa, vals: []const f64) ![]u8 { + const b = try self.arena.allocator().alloc(u8, vals.len * kit.size(self.k)); + for (vals, 0..) |v, i| kit.put(self.k, b, i, v); + return b; + } + + /// q row 0 a NaN; k row 1 a +Inf; row 2's raw index key both infinities (its block completes); v row 0 a -Inf. + fn plant(self: *Qsa) void { + const inf = std.math.inf(f64); + self.qg[3] = std.math.nan(f64); + self.vr[hd + 2] = -inf; + if (self.shape.rows > 1) self.kr[kv_heads * hd + 5] = inf; + if (self.shape.rows > 2) { + self.idx[2 * width + ih * di + 1] = inf; + self.idx[2 * width + ih * di + 2] = -inf; + } + } + + /// The caches back to their prepared contents. + fn restore(self: *Qsa, at: []const u64) !void { + for (at, self.before_bytes) |p, b| try self.rig.put(p, b); + } + + pub fn run(self: *Qsa) !void { + try self.restore(self.outs[2..6]); + const d = self.dev; + const o = self.outs; + const n: c_int = @intCast(self.shape.rows); + const Rope = hip.launches.flashnext.QsaRope; + try self.l.fn_qsa_prep(.{ + .q = Rope{ .src = d[0], .s_row = 2 * heads * hd, .s_head = 2 * hd, .heads = heads, .width = hd, .weight = d[4], .wide = o[0] }, + .iq = Rope{ .src = d[3], .s_row = width, .s_head = di, .heads = ih, .width = di, .weight = d[5], .wide = o[1] }, + .k = .{ .src = d[1], .s_row = kv_heads * hd, .s_head = hd, .heads = kv_heads, .width = hd, .weight = d[6], .cache = o[2] }, + .v = d[2], + .v_cache = o[3], + .v_width = hd, + .raw = d[3], + .raw_stride = width, + .raw_offset = ih * di, + .raw_cache = o[4], + .raw_width = di, + .pooled = o[5], + .pool_scale = d[7], + .ratio = ratio, + .pos = d[8], + .seg_pos = d[8], + .rows = n, + .n = n, + .total = cap, + .kind = @backingInt(self.k), + .eps = eps, + .rotary = rotary, + .theta = theta, + }, self.rig.s.handle); + try self.rig.s.synchronize(); + } + + /// tf_qk_rope for q, index q and k, v and the raw index key written at their positions, then the pools. + pub fn replaced(self: *Qsa) ![]const u8 { + try self.restore(self.base[2..6]); + const d = self.dev; + const b = self.base; + const n: c_int = @intCast(self.shape.rows); + const kind = @backingInt(self.k); + const st = self.rig.s.handle; + const C = ?*const anyopaque; + const P = ?*anyopaque; + const CF = ?[*]const f32; + const CI = ?[*]const i32; + const F = ?[*]f32; + const pos = kit.ptr(CI, d[8]); + const l = self.l; + try l.tf_qk_rope(kit.ptr(C, d[0]), kind, 2 * heads * hd, 2 * hd, kit.ptr(CF, d[4]), eps, n, heads, hd, rotary, theta, pos, kit.ptr(F, b[0]), null, 0, st); + try l.tf_qk_rope(kit.ptr(C, d[3]), kind, width, di, kit.ptr(CF, d[5]), eps, n, ih, di, rotary, theta, pos, kit.ptr(F, b[1]), null, 0, st); + try l.tf_qk_rope(kit.ptr(C, d[1]), kind, kv_heads * hd, hd, kit.ptr(CF, d[6]), eps, n, kv_heads, hd, rotary, theta, pos, null, kit.ptr(P, b[2]), cap, st); + try l.tf_kv_write_at(kit.ptr(C, d[2]), kit.ptr(P, b[3]), kind, n, kv_heads, hd, cap, pos, st); + try l.tf_copy_cols(kit.ptr(C, d[3]), width, ih * di, kit.ptr(P, b[6]), kind, n, di, st); + try l.tf_kv_write_at(kit.ptr(C, b[6]), kit.ptr(P, b[4]), kind, n, 1, di, cap, pos, st); + try l.fn_idx_pool_at(kit.ptr(C, b[4]), kit.ptr(P, b[5]), kit.ptr(CF, d[7]), kind, pos, n, di, ratio, rotary, theta, eps, st); + const sizes = self.byteLens(); + const a = self.arena.allocator(); + var all: std.ArrayList(u8) = .empty; + const lo: usize = if (self.part == .wide) 0 else 2; + const hi: usize = if (self.part == .wide) 2 else 6; + for (b[lo..hi], sizes[lo..hi]) |at, len| try all.appendSlice(a, try self.rig.bytes(at, len)); + return all.items; + } + + fn byteLens(self: *const Qsa) [6]usize { + const l = self.lens(); + const kb = kit.size(self.k); + return .{ l[0] * 4, l[1] * 4, l[2] * kb, l[3] * kb, l[4] * kb, l[5] * kb }; + } + + pub fn count(self: *Qsa) usize { + const l = self.lens(); + return if (self.part == .wide) l[0] + l[1] else l[2] + l[3] + l[4] + l[5]; + } + + /// Gate 4's accumulator and order of every sum (null: float64). + const How = struct { c.Accum, g.Order }; + + fn sum(sim: ?How, t: []const f64) f64 { + return if (sim) |how| rows.sumIn(how[0], how[1], t) else rows.sumIn(.none, .sequential, t); + } + + /// The kind's unit roundoff: half its ulp at 1. + fn unit(self: *const Qsa) f64 { + return if (self.k == .bf16) 0x1p-8 else 0x1p-11; + } + + /// RMS norm with weight, then the rotation at position p over the first 64 values (tf_qk_rope's formula). + fn rope(self: *const Qsa, x: []const f64, w: []const f64, p: f64, sim: ?How, out: []f64, tol: ?[]f64, extra: f64) void { + var sq: [512]f64 = undefined; + for (sq[0..x.len], x) |*s, v| s.* = v * v; + const inv = 1 / @sqrt(sum(sim, sq[0..x.len]) / @as(f64, @floatFromInt(x.len)) + eps); + var nrm: [512]f64 = undefined; + for (nrm[0..x.len], x, w) |*y, v, s| y.* = v * inv * s; + const half = rotary / 2; + const u = self.unit(); + for (0..x.len) |i| { + if (i >= rotary) { + out[i] = nrm[i]; + if (tol) |t| t[i] = u * 2 * @abs(nrm[i]) * (1 + 0x1p-6) + (0x1p-20 + extra) * @abs(nrm[i]) + 0x1p-120; + continue; + } + const f = i % half; + const ang = p / std.math.pow(f64, theta, @as(f64, @floatFromInt(f)) / half); + const cs = @cos(ang); + const sn = @sin(ang); + const x1 = nrm[f]; + const x2 = nrm[f + half]; + out[i] = if (i < half) x1 * cs - x2 * sn else x1 * sn + x2 * cs; + const m = if (i < half) @abs(x1 * cs) + @abs(x2 * sn) else @abs(x1 * sn) + @abs(x2 * cs); + const amp = @abs(x1) + @abs(x2); + // the normed values' and the output's roundings; fp32's angle (powf, p freq), cos, sin and products + if (tol) |t| t[i] = u * (m + @abs(out[i])) * (1 + 0x1p-6) + (p * 0x1p-21 + 0x1p-20 + extra) * amp + 0x1p-120; + } + } + + /// Every output of the launch in float64, the part's slice into `out`; tol the gate-4 allowance of each. + fn outputs(self: *Qsa, out: []f64, tol: ?[]f64, sim: ?How) !void { + const a = self.arena.allocator(); + const l = self.lens(); + var total: usize = 0; + for (l) |x| total += x; + const all = try a.alloc(f64, total); + const tl = try a.alloc(f64, total); + @memset(tl, 0x1p-120); + var at: [6]usize = undefined; + var off: usize = 0; + for (&at, l) |*x, len| { + x.* = off; + off += len; + } + for (self.before, at[2..]) |vals, o| @memcpy(all[o..][0..vals.len], vals); + const n = self.shape.rows; + const t = if (tol != null) tl else null; + for (0..n) |r| { + const p: f64 = @floatFromInt(first + r); + for (0..heads) |h| { + const o = at[0] + (r * heads + h) * hd; + self.rope(self.qg[(r * heads + h) * 2 * hd ..][0..hd], self.w[0], p, sim, all[o..][0..hd], if (t) |x| x[o..][0..hd] else null, 0); + } + for (0..ih) |h| { + const o = at[1] + (r * ih + h) * di; + self.rope(self.idx[r * width + h * di ..][0..di], self.w[1], p, sim, all[o..][0..di], if (t) |x| x[o..][0..di] else null, 0); + } + for (0..kv_heads) |h| { + const o = at[2] + (h * cap + first + r) * hd; + self.rope(self.kr[(r * kv_heads + h) * hd ..][0..hd], self.w[2], p, sim, all[o..][0..hd], if (t) |x| x[o..][0..hd] else null, 0); + @memcpy(all[at[3] + (h * cap + first + r) * hd ..][0..hd], self.vr[(r * kv_heads + h) * hd ..][0..hd]); + } + @memcpy(all[at[4] + (first + r) * di ..][0..di], self.idx[r * width + ih * di ..][0..di]); + } + // the blocks the rows complete: the mean of their 4 raw keys (rounded to the kind), then pooled as a row + var mean: [di]f64 = undefined; + var four: [ratio]f64 = undefined; + for (0..n) |r| { + const end = first + r + 1; + if (end % ratio != 0) continue; + const b = end / ratio - 1; + for (&mean, 0..) |*m, d| { + for (&four, 0..) |*v, j| v.* = all[at[4] + (b * ratio + j) * di + d]; + m.* = sum(sim, &four) / ratio; + } + const o = at[5] + b * di; + const p: f64 = @floatFromInt(b * ratio); + self.rope(&mean, self.w[3], p, sim, all[o..][0..di], if (t) |x| x[o..][0..di] else null, 2 * self.unit()); + } + const lo = if (self.part == .wide) 0 else at[2]; + @memcpy(out, all[lo..][0..out.len]); + if (tol) |x| @memcpy(x, tl[lo..][0..out.len]); + } + + pub fn reference(self: *Qsa, want: []f64, mag: []f64) !void { + self.tol = try self.arena.allocator().alloc(f64, want.len); + try self.outputs(want, self.tol, null); + for (mag, want) |*m, w| m.* = if (std.math.isFinite(w)) @abs(w) else 0; + } + + /// Two roundings to the kind, fp32's norm, angle and rotation, and for a pool its mean's rounding. + pub fn bounds(self: *Qsa, _: []const f64, _: []const f64, allow: []f64) !void { + @memcpy(allow, self.tol); + } + + pub fn simulate(self: *Qsa, acc: c.Accum, order: g.Order, out: []f64) !void { + return self.outputs(out, null, .{ acc, order }); + } +}; diff --git a/zig/tests/hip/contract_fn_scores.zig b/zig/tests/hip/contract_fn_scores.zig new file mode 100644 index 0000000000..d757afab6e --- /dev/null +++ b/zig/tests/hip/contract_fn_scores.zig @@ -0,0 +1,244 @@ +//! Flash Next's index block scores under the contract on HIP: the quad and window forms. +const std = @import("std"); +const hip = @import("hip"); +const core = @import("core"); +const rig_ = @import("contract_rig.zig"); +const kit = @import("contract_kit.zig"); + +const contract = core.contract; +const c = contract.spec; +const g = contract.gates; +const rows = contract.rows; + +/// Flash Next's index heads: 4 of 128 a row. +const heads = 4; +const dims = 128; +/// Rows past `top` complete blocks score them; every row here completes every block, so every score is written. +const top = 0; + +pub const Which = enum { quad, eight }; + +const relu_nan = "relu is fmaxf(x, 0): a NaN head dot scores 0 where float64 keeps the NaN"; + +/// A lane's 4 products and their chain, the wave's xor tree, then the heads' relus summed. +fn laneDepth(_: c.Shape) usize { + return 1 + dims / 32 + 5 + heads; +} + +const names = [2][2][]const u8{ + .{ "hip flashnext tf_fn_idx_scores_quad (fp16 keys)", "hip flashnext tf_fn_idx_scores_quad (bf16 keys)" }, + .{ "hip flashnext tf_fn_idx_scores8 (fp16 keys)", "hip flashnext tf_fn_idx_scores8 (bf16 keys)" }, +}; + +/// A prompt slice's rows (16 and up) and a verify window's (5 to 15). +const quad_served = [_]c.Shape{ + .{ .rows = 32, .n = 1100, .k = dims }, + .{ .rows = 64, .n = 300, .k = dims }, + .{ .rows = 16, .n = 2048, .k = dims }, +}; +const eight_served = [_]c.Shape{ + .{ .rows = 5, .n = 1100, .k = dims }, + .{ .rows = 8, .n = 2048, .k = dims }, + .{ .rows = 15, .n = 300, .k = dims }, +}; + +/// rows x blocks scores of shape.k = 128 dims; the quad and window forms must equal tf_fn_idx_scores bit for bit. +pub fn spec(w: Which, k: kit.Kind) c.Spec { + var s: c.Spec = .{ + .name = names[@backingInt(w)][@intFromBool(k == .bf16)], + .accum = .f32, + .depth = laneDepth, + .ops = 2, + .out = .f32, + .served = &quad_served, + .known = .{ .gate = .nonfinite, .finding = relu_nan }, + }; + switch (w) { + .quad => { + s.replaces = "tf_fn_idx_scores"; + s.tiles = .{ .{ .size = 32 }, .{ .size = 64 }, .{} }; + }, + .eight => { + s.replaces = "tf_fn_idx_scores"; + s.tiles = .{ .{ .size = 8 }, .{ .size = 8 }, .{} }; + s.served = &eight_served; + }, + } + return s; +} + +/// q [rows][4][128] fp32 and pooled keys [blocks][128] of the activation kind. +pub const Scores = struct { + rig: rig_.Rig, + l: *const hip.Launcher, + k: kit.Kind, + which: Which, + arena: std.heap.ArenaAllocator, + shape: c.Shape = undefined, + q: []f64 = &.{}, + keys: []f64 = &.{}, + dq: u64 = 0, + dk: u64 = 0, + dc: u64 = 0, + out: u64 = 0, + base: u64 = 0, + + pub fn init(a: std.mem.Allocator, rt: *const hip.Runtime, s: hip.Stream, l: *const hip.Launcher, w: Which) Scores { + return .{ .rig = .{ .a = a, .r = rt, .s = s }, .l = l, .k = kit.act(), .which = w, .arena = .init(a) }; + } + + pub fn deinit(self: *Scores) void { + self.arena.deinit(); + self.rig.deinit(); + } + + pub fn kernel(self: *Scores) g.Kernel { + return .{ .spec = spec(self.which, self.k), .ctx = self, .vt = &vt }; + } + + const vt = g.hooks(Scores); + + /// q in [-1, 1) fp32, keys in [-1, 1) of the kind; every row all blocks. + pub fn prepare(self: *Scores, shape: c.Shape, fill: g.Fill, seed: u64) !bool { + if (shape.rows == 0 or shape.n == 0 or shape.k != dims) return false; + self.rig.reset(); + _ = self.arena.reset(.retain_capacity); + self.shape = shape; + const a = self.arena.allocator(); + var prng = std.Random.DefaultPrng.init(seed); + const rng = prng.random(); + self.q = try a.alloc(f64, shape.rows * heads * dims); + self.keys = try a.alloc(f64, shape.n * dims); + for (self.q) |*v| v.* = @as(f32, @floatCast(rng.float(f64) * 2 - 1)); + for (self.keys) |*v| v.* = kit.round(self.k, rng.float(f64) * 2 - 1); + if (fill == .stress) self.stress(rng); + if (fill == .nonfinite) self.plant(); + const kb = try a.alloc(u8, self.keys.len * kit.size(self.k)); + for (self.keys, 0..) |v, i| kit.put(self.k, kb, i, v); + const complete = try a.alloc(i32, shape.rows); + @memset(complete, @intCast(shape.n)); + self.dq = try self.rig.input(try kit.f32Bytes(a, self.q)); + self.dk = try self.rig.input(kb); + self.dc = try self.rig.input(std.mem.sliceAsBytes(complete)); + self.out = try self.rig.output(shape.rows * shape.n * 4); + self.base = try self.rig.scratch(shape.rows * shape.n * 4); + return true; + } + + /// Row 0 a NaN, row 1 a +Inf, row 2 both infinities (one head), a block's key -Inf. + fn plant(self: *Scores) void { + const s = self.shape; + const inf = std.math.inf(f64); + self.q[3] = std.math.nan(f64); + if (s.rows > 1) self.q[(1 * heads + 1) * dims + 7] = inf; + if (s.rows > 2) { + self.q[(2 * heads + 2) * dims + 4] = inf; + self.q[(2 * heads + 2) * dims + 5] = -inf; + } + self.keys[(s.n / 2) * dims + 9] = -inf; + } + + /// Gate 4: integers exact in every kind and in bf16; q's second half undoes its first, keys one less for 8 dims. + fn stress(self: *Scores, rng: std.Random) void { + const h = dims / 2; + for (0..self.shape.n) |b| for (0..h) |d| { + const v: f64 = @floatFromInt(2 + rng.uintLessThan(u32, 127)); + self.keys[b * dims + d] = v; + self.keys[b * dims + h + d] = v - @as(f64, if (d < 8) 1 else 0); + }; + for (0..self.shape.rows * heads) |rh| for (0..h) |d| { + const v: f64 = @floatFromInt(1 + rng.uintLessThan(u32, 128)); + self.q[rh * dims + d] = v; + self.q[rh * dims + h + d] = -v; + }; + } + + pub fn run(self: *Scores) !void { + try self.launch(self.which, self.out); + try self.rig.s.synchronize(); + } + + /// One launch as idxScores makes it, the form chosen here rather than by the row count. + fn launch(self: *Scores, w: ?Which, out: u64) !void { + const s = self.shape; + const n: c_int = @intCast(s.rows); + const blocks: c_int = @intCast(s.n); + const stride: i64 = @intCast(s.n); + const kind = @backingInt(self.k); + const t: c_int = top; + const st = self.rig.s; + const f = self.l.fnx; + var a: hip.launch.Args = .{}; + const bx = (s.n + 63) / 64; + const which = w orelse { + // tf_fn_idx_scores: a wave a block, 8 rows a block + inline for (.{ self.dq, self.dk, self.dc, out, kind, n, @as(c_int, heads), @as(c_int, dims), blocks, stride, t }) |v| + try a.add(v); + const grid: hip.launch.Dim3 = .{ .x = @intCast((s.n + 7) / 8), .y = @intCast((s.rows + 7) / 8) }; + return hip.launch.launch(f.idx_scores, .{ .grid = grid, .block = .{ .x = 256 } }, st, &a); + }; + switch (which) { + .quad => { + inline for (.{ self.dq, self.dk, self.dc, out, kind, n, blocks, stride, t }) |v| try a.add(v); + const grid: hip.launch.Dim3 = .{ .x = @intCast(bx), .y = @intCast((s.rows + 31) / 32) }; + try hip.launch.launch(f.idx_scores_quad, .{ .grid = grid, .block = .{ .x = 128 } }, st, &a); + }, + .eight => { + inline for (.{ self.dq, self.dk, self.dc, out, kind, n, blocks, stride, t }) |v| try a.add(v); + const grid: hip.launch.Dim3 = .{ .x = @intCast((s.n + 7) / 8), .y = @intCast((s.rows + 7) / 8) }; + try hip.launch.launch(f.idx_scores8, .{ .grid = grid, .block = .{ .x = 256 } }, st, &a); + }, + } + } + + /// tf_fn_idx_scores on the same inputs. + pub fn replaced(self: *Scores) ![]const u8 { + try self.launch(null, self.base); + return self.rig.bytes(self.base, self.shape.rows * self.shape.n * 4); + } + + pub fn count(self: *Scores) usize { + return self.shape.rows * self.shape.n; + } + + fn reluNan(x: f64) f64 { + return if (std.math.isNan(x)) x else @max(x, 0); + } + + /// Row r's score of block b: the heads' relu(q . key) summed over sqrt(128), in float64; mag its terms' sum. + pub fn reference(self: *Scores, want: []f64, mag: []f64) !void { + const s = self.shape; + const norm = @sqrt(@as(f64, dims)); + for (0..s.rows) |r| for (0..s.n) |b| { + var total: f64 = 0; + var abs: f64 = 0; + for (0..heads) |h| { + var dot: f64 = 0; + for (0..dims) |d| { + const qv = self.q[(r * heads + h) * dims + d]; + const kv = self.keys[b * dims + d]; + dot += qv * kv; + abs += @abs(qv * kv); + } + total += reluNan(dot); + } + want[r * s.n + b] = total / norm; + mag[r * s.n + b] = abs / norm; + }; + } + + /// Gate 4's scores: each head's dot in the accumulator and order, its relu, the heads' sum, over sqrt(128). + pub fn simulate(self: *Scores, acc: c.Accum, order: g.Order, out: []f64) !void { + const s = self.shape; + const norm = @sqrt(@as(f64, dims)); + var t: [dims]f64 = undefined; + var per: [heads]f64 = undefined; + for (0..s.rows) |r| for (0..s.n) |b| { + for (&per, 0..) |*p, h| { + for (&t, 0..) |*x, d| x.* = self.q[(r * heads + h) * dims + d] * self.keys[b * dims + d]; + p.* = reluNan(rows.sumIn(acc, order, &t)); + } + out[r * s.n + b] = rows.sumIn(acc, .sequential, &per) / norm; + }; + } +}; diff --git a/zig/tests/hip/contract_gdn.zig b/zig/tests/hip/contract_gdn.zig new file mode 100644 index 0000000000..5186a1e311 --- /dev/null +++ b/zig/tests/hip/contract_gdn.zig @@ -0,0 +1,314 @@ +//! The DeltaNet recurrence under the contract on HIP: its float64 rows, and the prompt kernel at half a head a block. +const std = @import("std"); +const hip = @import("hip"); +const core = @import("core"); +const rig_ = @import("contract_rig.zig"); +const kit = @import("contract_kit.zig"); + +const contract = core.contract; +const c = contract.spec; +const g = contract.gates; +const rows = contract.rows; + +/// Value heads a key head: Flash Next's 48 value heads over 16 key heads. +pub const group = 3; + +/// A gate 4 replay's accumulator and order. +pub const Sim = struct { c.Accum, g.Order }; + +/// Gate 4's inputs: the exact scans' (both sums), or the matrix-core form's (k = 0, beta = 0: the readout alone). +pub const Mode = enum { exact, wy }; + +/// The longest chain a state element passes a row: decay, k product, the 32-lane sum, delta's two, the update's two. +pub fn depth(s: c.Shape) usize { + return 15 * s.rows + 10; +} + +/// One stream's float64 inputs: t tokens, h value heads, dk = dv = d; every value an fp32 one. +pub const Problem = struct { + t: usize, + h: usize, + d: usize, + q: []f64, // [t][h / group][d] + k: []f64, // [t][h / group][d] + v: []f64, // [t][h][d] + gate: []f64, // [t][h] + beta: []f64, // [t][h] + state: []f64, // [h][d value rows][d] + + pub fn kh(p: *const Problem) usize { + return p.h / group; + } + + pub fn make(a: std.mem.Allocator, t: usize, h: usize, d: usize, fill: g.Fill, seed: u64, mode: Mode) !Problem { + const n = h / group; + var p: Problem = .{ + .t = t, + .h = h, + .d = d, + .q = try a.alloc(f64, t * n * d), + .k = try a.alloc(f64, t * n * d), + .v = try a.alloc(f64, t * h * d), + .gate = try a.alloc(f64, t * h), + .beta = try a.alloc(f64, t * h), + .state = try a.alloc(f64, h * d * d), + }; + var prng = std.Random.DefaultPrng.init(seed); + const rng = prng.random(); + if (fill == .stress) { + p.stress(rng, mode); + return p; + } + p.random(rng); + if (fill == .nonfinite and t > 2 and h > 2) p.plant(); + return p; + } + + /// L2-normalized q and k rows, normal v, a state of 0.1 scale, gates exp(-A softplus(x)), beta = sigmoid. + fn random(p: *Problem, rng: std.Random) void { + const d = p.d; + for ([_][]f64{ p.q, p.k }) |x| for (0..x.len / d) |row| { + const at = x[row * d ..][0..d]; + var ss: f64 = 0; + for (at) |*e| { + e.* = rng.floatNorm(f64); + ss += e.* * e.*; + } + for (at) |*e| e.* = fp32(e.* / @sqrt(ss)); + }; + for (p.v) |*e| e.* = fp32(rng.floatNorm(f64)); + for (p.state) |*e| e.* = fp32(0.1 * rng.floatNorm(f64)); + const heads: f64 = @floatFromInt(p.h); + for (p.gate, p.beta, 0..) |*gv, *bv, i| { + const scale = 0.5 + 7.5 * @as(f64, @floatFromInt(i % p.h)) / heads; + gv.* = fp32(@exp(-scale * std.math.log1p(@exp(rng.floatNorm(f64) - 2)))); + bv.* = fp32(1 / (1 + @exp(-rng.floatNorm(f64)))); + } + } + + /// NaN in q (token 0, key head 0) and a gate (token 2, head 0), +Inf in v (token 1, head 1), -Inf in a state + fn plant(p: *Problem) void { + p.q[0] = std.math.nan(f64); + p.gate[2 * p.h] = std.math.nan(f64); + p.v[(p.h + 1) * p.d] = std.math.inf(f64); + p.state[(2 * p.d + 3) * p.d] = -std.math.inf(f64); + } + + /// Gate 4: decay 1; the state's halves cancel to e_0 against mirrored k and q, so every sum is a small integer. + fn stress(p: *Problem, rng: std.Random, mode: Mode) void { + const d = p.d; + @memset(p.gate, 1); + @memset(p.beta, if (mode == .wy) 0 else 1); + for (0..p.state.len / d) |row| mirror(rng, p.state[row * d ..][0..d], -1); + for (0..p.q.len / d) |row| { + mirror(rng, p.q[row * d ..][0..d], 1); + mirror(rng, p.k[row * d ..][0..d], 1); + if (mode == .wy) @memset(p.k[row * d ..][0..d], 0); + } + // v is k's element 0, the remembered sum: delta is 0 and the state stays as it was + for (0..p.t) |t| for (0..p.h) |h| { + @memset(p.v[(t * p.h + h) * d ..][0..d], p.k[(t * p.kh() + h / group) * d]); + }; + } + + /// y [t][h][d] and the state after `upto` tokens in float64 (sums in `sim`'s accumulator and order when given). + pub fn walk(p: *const Problem, a: std.mem.Allocator, upto: usize, y: []f64, ymag: []f64, st: []f64, smag: []f64, sim: ?Sim) !void { + const d = p.d; + const terms = try a.alloc(f64, d); + defer a.free(terms); + @memcpy(st, p.state); + for (smag, p.state) |*m, v| m.* = @abs(v); + for (0..p.h) |h| for (0..d) |r| { + const s = st[(h * d + r) * d ..][0..d]; + const m = smag[(h * d + r) * d ..][0..d]; + for (0..upto) |t| { + const at = t * p.h + h; + const decay = p.gate[at]; + const beta = p.beta[at]; + const key = p.k[(t * p.kh() + h / group) * d ..][0..d]; + const query = p.q[(t * p.kh() + h / group) * d ..][0..d]; + const value = p.v[at * d + r]; + var mrem: f64 = 0; + for (s, m, key, terms) |*sv, *mv, kv, *o| { + sv.* *= decay; + mv.* *= decay; + o.* = sv.* * kv; + mrem += mv.* * @abs(kv); + } + const delta = (value - sum(terms, sim)) * beta; + const mdelta = (@abs(value) + mrem) * @abs(beta); + var my: f64 = 0; + for (s, m, key, query, terms) |*sv, *mv, kv, qv, *o| { + sv.* += kv * delta; + mv.* += @abs(kv) * mdelta; + o.* = sv.* * qv; + my += mv.* * @abs(qv); + } + y[at * d + r] = sum(terms, sim); + ymag[at * d + r] = my; + } + }; + } +}; + +fn fp32(x: f64) f64 { + return @as(f32, @floatCast(x)); +} + +/// Integers in [1, 128] in the first half; the second half `sign` times the first, plus 1 at element 0 when negated. +fn mirror(rng: std.Random, x: []f64, sign: f64) void { + const half = x.len / 2; + for (x[0..half], x[half..], 0..) |*lo, *hi, i| { + lo.* = @floatFromInt(1 + rng.uintLessThan(u32, 128)); + hi.* = sign * lo.* + @as(f64, if (sign < 0 and i == 0) 1 else 0); + } +} + +fn sum(t: []const f64, sim: ?Sim) f64 { + if (sim) |how| return rows.sumIn(how[0], how[1], t); + var x: f64 = 0; + for (t) |v| x += v; + return x; +} + +/// q, k, v, gate and beta as fp32 inputs of `r`. +pub fn upload(r: *rig_.Rig, a: std.mem.Allocator, p: *const Problem) ![5]u64 { + var at: [5]u64 = undefined; + for (&at, [_][]const f64{ p.q, p.k, p.v, p.gate, p.beta }) |*x, v| x.* = try r.input(try kit.f32Bytes(a, v)); + return at; +} + +/// The plain window scan (gated_delta_tile, no snapshots) over `length` tokens: the kernels below must give its bits. +pub fn plain(l: *const hip.Launcher, r: *rig_.Rig, in: [5]u64, state: u64, y: u64, p: *const Problem, length: usize) !void { + var a: hip.launch.Args = .{}; + for ([_]u64{ in[0], in[1], in[2], in[3], in[4], state, y }) |x| try a.add(x); + for ([_]usize{ length, p.kh(), p.h, p.d }) |x| try a.add(@as(c_int, @intCast(x))); + try a.add(@as(u64, 0)); // no snapshots + try a.add(@as(u64, 0)); // no start row + const f = l.gated_delta_tile[if (p.d == 128) 0 else 1]; + const grid: hip.launch.Dim3 = .{ .x = @intCast(p.d / 8), .y = @intCast(p.h) }; + try hip.launch.launch(f, .{ .grid = grid, .block = .{ .x = 32, .y = 8 } }, r.s, &a); +} + +/// A launch's two outputs, each registered on its own: y, and the state after the tokens. +pub const Part = enum { y, state }; + +/// Flash Next's 48 value heads at the shortest prompt that takes the kernel and a longer one; two key heads, 97 tokens. +const prompt_served = [_]c.Shape{ + .{ .rows = 64, .n = 48, .k = 128 }, + .{ .rows = 300, .n = 48, .k = 128 }, + .{ .rows = 97, .n = 6, .k = 128 }, +}; + +pub fn promptSpec(part: Part) c.Spec { + return .{ + .name = if (part == .y) "hip DeltaNet tf_gdn_prompt_128 (y)" else "hip DeltaNet tf_gdn_prompt_128 (the state)", + .accum = .f32, + .depth = depth, + .out = .f32, + .replaces = "gated_delta_tile<128, 8, 16>", + .tiles = .{ .{ .size = 16 }, .{}, .{} }, + .served = &prompt_served, + }; +} + +/// tf_gdn_prompt_128: shape.rows tokens over shape.n value heads, dk = dv = 128, the state updated in place. +pub const Prompt = struct { + rig: rig_.Rig, + l: *const hip.Launcher, + part: Part, + arena: std.heap.ArenaAllocator, + shape: c.Shape = undefined, + p: Problem = undefined, + in: [5]u64 = @splat(0), + y: u64 = 0, + st: u64 = 0, + st_bytes: []u8 = &.{}, + base: [2]u64 = @splat(0), // the plain scan's y and state + + pub fn init(a: std.mem.Allocator, rt: *const hip.Runtime, s: hip.Stream, l: *const hip.Launcher, part: Part) Prompt { + return .{ .rig = .{ .a = a, .r = rt, .s = s }, .l = l, .part = part, .arena = .init(a) }; + } + + pub fn deinit(self: *Prompt) void { + self.arena.deinit(); + self.rig.deinit(); + } + + pub fn kernel(self: *Prompt) g.Kernel { + return .{ .spec = promptSpec(self.part), .ctx = self, .vt = &vt }; + } + + const vt = g.hooks(Prompt); + + pub fn prepare(self: *Prompt, shape: c.Shape, fill: g.Fill, seed: u64) !bool { + if (shape.k != 128 or shape.rows == 0 or shape.n == 0 or shape.n % group != 0) return false; + self.rig.reset(); + _ = self.arena.reset(.retain_capacity); + const a = self.arena.allocator(); + self.shape = shape; + self.p = try Problem.make(a, shape.rows, shape.n, 128, fill, seed, .exact); + self.in = try upload(&self.rig, a, &self.p); + self.st_bytes = try kit.f32Bytes(a, self.p.state); + const yb = shape.rows * shape.n * 128 * 4; + const sb = self.st_bytes.len; + // the other part's output is scratch: the gates read one part's bytes + self.y = if (self.part == .y) try self.rig.output(yb) else try self.rig.scratch(yb); + self.st = if (self.part == .state) try self.rig.output(sb) else try self.rig.scratch(sb); + self.base = .{ try self.rig.scratch(yb), try self.rig.scratch(sb) }; + return true; + } + + /// The state back to the prepared one, then one launch: half a value head a block, 4 waves. + pub fn run(self: *Prompt) !void { + try self.rig.put(self.st, self.st_bytes); + var a: hip.launch.Args = .{}; + for ([_]u64{ self.in[0], self.in[1], self.in[2], self.in[3], self.in[4], self.st, self.y }) |x| try a.add(x); + for ([_]usize{ self.shape.rows, self.p.kh(), self.shape.n }) |x| try a.add(@as(c_int, @intCast(x))); + const grid: hip.launch.Dim3 = .{ .x = 2, .y = @intCast(self.shape.n) }; + try hip.launch.launch(self.l.gdn_prompt, .{ .grid = grid, .block = .{ .x = 32, .y = 4 } }, self.rig.s, &a); + try self.rig.s.synchronize(); + } + + /// The plain scan from the prepared state over the same tokens. + pub fn replaced(self: *Prompt) ![]const u8 { + try self.rig.put(self.base[1], self.st_bytes); + try plain(self.l, &self.rig, self.in, self.base[1], self.base[0], &self.p, self.shape.rows); + if (self.part == .y) return self.rig.bytes(self.base[0], self.count() * 4); + return self.rig.bytes(self.base[1], self.st_bytes.len); + } + + pub fn count(self: *Prompt) usize { + return if (self.part == .y) self.shape.rows * self.shape.n * 128 else self.p.state.len; + } + + pub fn reference(self: *Prompt, want: []f64, mag: []f64) !void { + return self.outputs(want, mag, null); + } + + pub fn simulate(self: *Prompt, acc: c.Accum, order: g.Order, out: []f64) !void { + const mag = try self.rig.a.alloc(f64, out.len); + defer self.rig.a.free(mag); + return self.outputs(out, mag, .{ acc, order }); + } + + fn outputs(self: *Prompt, want: []f64, mag: []f64, sim: ?Sim) !void { + return partOf(self.rig.a, &self.p, self.shape.rows, self.part, want, mag, sim); + } +}; + +/// One part's float64 outputs and magnitudes after `upto` tokens, the other part's in scratch. +pub fn partOf(a: std.mem.Allocator, p: *const Problem, upto: usize, part: Part, want: []f64, mag: []f64, sim: ?Sim) !void { + const ny = p.t * p.h * p.d; + const ns = p.state.len; + const buf = try a.alloc(f64, 2 * (ny + ns)); + defer a.free(buf); + const y = buf[0..ny]; + const ymag = buf[ny..][0..ny]; + const st = buf[2 * ny ..][0..ns]; + const smag = buf[2 * ny + ns ..][0..ns]; + try p.walk(a, upto, y, ymag, st, smag, sim); + const n = upto * p.h * p.d; + @memcpy(want, if (part == .y) y[0..n] else st); + @memcpy(mag, if (part == .y) ymag[0..n] else smag); +} diff --git a/zig/tests/hip/contract_gdn_hold.zig b/zig/tests/hip/contract_gdn_hold.zig new file mode 100644 index 0000000000..509548f6e7 --- /dev/null +++ b/zig/tests/hip/contract_gdn_hold.zig @@ -0,0 +1,181 @@ +//! A verify window that holds its DeltaNet state, and the keep that replays it, under the contract on HIP. +const std = @import("std"); +const hip = @import("hip"); +const core = @import("core"); +const rig_ = @import("contract_rig.zig"); +const kit = @import("contract_kit.zig"); +const gdn = @import("contract_gdn.zig"); + +const contract = core.contract; +const c = contract.spec; +const g = contract.gates; + +/// tf_gdn_hold_*: a window's y, the state left as it was; tf_gdn_keep_*: each layer's state after its kept rows. +pub const Which = enum { hold, keep }; + +/// Rows a keep's inputs hold a layer: Flash Next's cache.max_window. +const window = 8; +/// DeltaNet layers in one keep launch, each with its own inputs and state, the states one after another. +const layers = 2; + +/// Windows of 2, 4 and 8 rows over Flash Next's 48 value heads (16 key heads). +fn holdServed(comptime dk: usize) [3]c.Shape { + return .{ .{ .rows = 2, .n = 48, .k = dk }, .{ .rows = 4, .n = 48, .k = dk }, .{ .rows = 8, .n = 48, .k = dk } }; +} + +/// A keep of 4 rows, a full reject (the pending row alone) and a full accept of 8. +fn keepServed(comptime dk: usize) [3]c.Shape { + return .{ .{ .rows = 4, .n = 48, .k = dk }, .{ .rows = 1, .n = 48, .k = dk }, .{ .rows = 8, .n = 48, .k = dk } }; +} + +const hold_128 = holdServed(128); +const hold_16 = holdServed(16); +const keep_128 = keepServed(128); +const keep_16 = keepServed(16); + +pub fn spec(which: Which, dk: usize) c.Spec { + const wide = dk == 128; + const names = [2][2][]const u8{ + .{ "hip DeltaNet tf_gdn_hold_16 (y)", "hip DeltaNet tf_gdn_hold_128 (y)" }, + .{ "hip DeltaNet tf_gdn_keep_16 (the states)", "hip DeltaNet tf_gdn_keep_128 (the states)" }, + }; + return .{ + .name = names[@intFromBool(which == .keep)][@intFromBool(wide)], + .accum = .f32, + .depth = gdn.depth, + .out = .f32, + .replaces = if (wide) "gated_delta_tile<128, 8, 16>" else "gated_delta_tile<16, 8, 16>", + // the scan stages 16 rows of k and q at a time + .tiles = .{ .{ .size = 16 }, .{}, .{} }, + .served = switch (which) { + .hold => if (wide) &hold_128 else &hold_16, + .keep => if (wide) &keep_128 else &keep_16, + }, + }; +} + +/// shape.rows window rows (hold) or kept rows (keep) over shape.n value heads, dk = dv = shape.k. +pub const Window = struct { + rig: rig_.Rig, + l: *const hip.Launcher, + which: Which, + dk: usize, + arena: std.heap.ArenaAllocator, + shape: c.Shape = undefined, + p: [layers]gdn.Problem = undefined, + ins: [layers][5]u64 = undefined, + sets: usize = 1, + in: u64 = 0, // a keep's inputs: each layer's k, v, gate and beta for `window` rows + st: u64 = 0, + st_bytes: []u8 = &.{}, + y: u64 = 0, + base: [2]u64 = @splat(0), // the plain scan's states and y + + pub fn init(a: std.mem.Allocator, rt: *const hip.Runtime, s: hip.Stream, l: *const hip.Launcher, which: Which, dk: usize) Window { + return .{ .rig = .{ .a = a, .r = rt, .s = s }, .l = l, .which = which, .dk = dk, .arena = .init(a) }; + } + + pub fn deinit(self: *Window) void { + self.arena.deinit(); + self.rig.deinit(); + } + + pub fn kernel(self: *Window) g.Kernel { + return .{ .spec = spec(self.which, self.dk), .ctx = self, .vt = &vt }; + } + + const vt = g.hooks(Window); + + fn one(self: *const Window) usize { + return self.shape.n * self.dk * self.dk; + } + + pub fn prepare(self: *Window, shape: c.Shape, fill: g.Fill, seed: u64) !bool { + const most: usize = if (self.which == .hold) 16 else window; + if (shape.k != self.dk or shape.rows == 0 or shape.rows > most or shape.n == 0 or shape.n % gdn.group != 0) return false; + self.rig.reset(); + _ = self.arena.reset(.retain_capacity); + const a = self.arena.allocator(); + self.shape = shape; + self.sets = if (self.which == .hold) 1 else layers; + const tokens = if (self.which == .hold) shape.rows else window; + var states: std.ArrayList(f64) = .empty; + for (0..self.sets) |z| { + self.p[z] = try gdn.Problem.make(a, tokens, shape.n, self.dk, fill, seed + z, .exact); + self.ins[z] = try gdn.upload(&self.rig, a, &self.p[z]); + try states.appendSlice(a, self.p[z].state); + } + self.st_bytes = try kit.f32Bytes(a, states.items); + const yb = tokens * shape.n * self.dk * 4; + if (self.which == .hold) { + // the hold reads the state and must leave it: an input, which gate 2 checks unchanged + self.st = try self.rig.input(self.st_bytes); + self.y = try self.rig.output(yb); + } else { + var packed_in: std.ArrayList(f64) = .empty; + for (self.p[0..self.sets]) |p| for ([_][]const f64{ p.k, p.v, p.gate, p.beta }) |x| try packed_in.appendSlice(a, x); + self.in = try self.rig.input(try kit.f32Bytes(a, packed_in.items)); + self.st = try self.rig.output(self.st_bytes.len); + self.y = 0; + } + self.base = .{ try self.rig.scratch(self.st_bytes.len), try self.rig.scratch(yb) }; + return true; + } + + /// One launch: the hold over the window, or the keep of both layers (their states back to the prepared ones). + pub fn run(self: *Window) !void { + const CF = ?[*]const f32; + const F = ?[*]f32; + const n: c_int = @intCast(self.shape.n); + const kh: c_int = @divExact(n, gdn.group); + const d: c_int = @intCast(self.dk); + const s = self.rig.s.handle; + if (self.which == .hold) { + const in = self.ins[0]; + try self.l.tf_gdn_hold(kit.ptr(CF, in[0]), kit.ptr(CF, in[1]), kit.ptr(CF, in[2]), kit.ptr(CF, in[3]), kit.ptr(CF, in[4]), kit.ptr(F, self.st), kit.ptr(F, self.y), @intCast(self.shape.rows), kh, n, d, d, s); + } else { + try self.rig.put(self.st, self.st_bytes); + const p = &self.p[0]; + const in_stride = p.k.len + p.v.len + p.gate.len + p.beta.len; + try self.l.tf_gdn_keep(kit.ptr(F, self.st), @intCast(self.one()), kit.ptr(CF, self.in), @intCast(in_stride), window, @intCast(self.shape.rows), layers, kh, n, d, d, s); + } + try self.rig.s.synchronize(); + } + + /// The plain scan over the window's rows from the prepared state (y), or each layer's over its kept rows (states). + pub fn replaced(self: *Window) ![]const u8 { + const each = self.one() * 4; + for (0..self.sets) |z| { + const st = self.base[0] + z * each; + try self.rig.put(st, self.st_bytes[z * each ..][0..each]); + try gdn.plain(self.l, &self.rig, self.ins[z], st, self.base[1], &self.p[z], self.shape.rows); + } + if (self.which == .hold) return self.rig.bytes(self.base[1], self.count() * 4); + return self.rig.bytes(self.base[0], self.st_bytes.len); + } + + pub fn count(self: *Window) usize { + return if (self.which == .hold) self.shape.rows * self.shape.n * self.dk else self.sets * self.one(); + } + + pub fn reference(self: *Window, want: []f64, mag: []f64) !void { + return self.outputs(want, mag, null); + } + + pub fn simulate(self: *Window, acc: c.Accum, order: g.Order, out: []f64) !void { + const mag = try self.rig.a.alloc(f64, out.len); + defer self.rig.a.free(mag); + return self.outputs(out, mag, .{ acc, order }); + } + + /// The hold's y over its rows; the keep's states after the kept rows, layer by layer. + fn outputs(self: *Window, want: []f64, mag: []f64, sim: ?gdn.Sim) !void { + const a = self.rig.a; + const rows = self.shape.rows; + if (self.which == .hold) return gdn.partOf(a, &self.p[0], rows, .y, want, mag, sim); + const each = self.one(); + for (0..self.sets) |z| { + try gdn.partOf(a, &self.p[z], rows, .state, want[z * each ..][0..each], mag[z * each ..][0..each], sim); + } + } +}; diff --git a/zig/tests/hip/contract_gdn_prep.zig b/zig/tests/hip/contract_gdn_prep.zig new file mode 100644 index 0000000000..926fd2ba80 --- /dev/null +++ b/zig/tests/hip/contract_gdn_prep.zig @@ -0,0 +1,341 @@ +//! A DeltaNet prompt's prework in one launch under the contract on HIP: tf_gdn_prompt_prep, the chain's bytes. +const std = @import("std"); +const hip = @import("hip"); +const core = @import("core"); +const rig_ = @import("contract_rig.zig"); +const kit = @import("contract_kit.zig"); +const gdn = @import("contract_gdn.zig"); + +const contract = core.contract; +const c = contract.spec; +const g = contract.gates; +const rows = contract.rows; + +const taps = 4; // the conv's kernel (Flash Next's) +const eps: f32 = 1e-6; + +/// A q or k output: the conv's four adds, then a head's 128 squares, four a lane, and the wave's xor tree. +fn depth(_: c.Shape) usize { + return 4 + 4 + 5; +} + +/// Flash Next's 48 value heads (16 key heads): a prompt of 40 tokens, one token, and 300. +const served = [_]c.Shape{ + .{ .rows = 40, .n = 48, .k = 128 }, + .{ .rows = 1, .n = 48, .k = 128 }, + .{ .rows = 300, .n = 48, .k = 128 }, +}; + +pub fn spec(k: kit.Kind) c.Spec { + return .{ + .name = if (k == .bf16) "hip DeltaNet tf_gdn_prompt_prep (bf16 in)" else "hip DeltaNet tf_gdn_prompt_prep (fp16 in)", + .accum = .f32, + .depth = depth, + // silu, the mean's eps, rsqrt and two products; the gate's add, softplus and two exps + .ops = 16, + .out = .f32, + .replaces = "tf_conv_prefill, tf_copy_cols, tf_rms and tf_gdn_gate_prefill", + .tiles = .{ .{ .size = 16 }, .{}, .{} }, + .served = &served, + }; +} + +/// shape.rows tokens of a layer's conv input over shape.n value heads: q, k, v, gate, beta and the new conv state. +pub const Prep = struct { + rig: rig_.Rig, + l: *const hip.Launcher, + k: kit.Kind, + arena: std.heap.ArenaAllocator, + shape: c.Shape = undefined, + kw: usize = 0, // key heads x 128 + vw: usize = 0, // value heads x 128 + ch: usize = 0, // the conv's channels: q, k, v + x: []f64 = &.{}, // [rows][ch], of the kind + w: []f64 = &.{}, // [ch][taps] + st: []f64 = &.{}, // [taps - 1][ch] + qw: []f64 = &.{}, + kn: []f64 = &.{}, + av: []f64 = &.{}, // [rows][heads], of the kind + bv: []f64 = &.{}, // [rows][heads], of the kind + a_log: []f64 = &.{}, + dt: []f64 = &.{}, + in: [9]u64 = @splat(0), // x, w, state, q and k norm weights, a, b, a_log, dt_bias + out: [6]u64 = @splat(0), // q, k, v, gate, beta, new state + base: [9]u64 = @splat(0), // the chain's six, then its mixed rows and its q and k columns + + pub fn init(a: std.mem.Allocator, rt: *const hip.Runtime, s: hip.Stream, l: *const hip.Launcher) Prep { + return .{ .rig = .{ .a = a, .r = rt, .s = s }, .l = l, .k = kit.act(), .arena = .init(a) }; + } + + pub fn deinit(self: *Prep) void { + self.arena.deinit(); + self.rig.deinit(); + } + + pub fn kernel(self: *Prep) g.Kernel { + return .{ .spec = spec(self.k), .ctx = self, .vt = &vt }; + } + + const vt = g.hooks(Prep); + + /// Each output's elements, in the order the outputs are bound: q, k, v, gate, beta, new state. + fn lens(self: *const Prep) [6]usize { + const n = self.shape.rows; + const heads = self.shape.n; + return .{ n * self.kw, n * self.kw, n * self.vw, n * heads, n * heads, (taps - 1) * self.ch }; + } + + pub fn prepare(self: *Prep, shape: c.Shape, fill: g.Fill, seed: u64) !bool { + if (shape.k != 128 or shape.rows == 0 or shape.n == 0 or shape.n % gdn.group != 0) return false; + self.rig.reset(); + _ = self.arena.reset(.retain_capacity); + const a = self.arena.allocator(); + self.shape = shape; + const n = shape.rows; + const heads = shape.n; + self.kw = heads / gdn.group * 128; + self.vw = heads * 128; + self.ch = 2 * self.kw + self.vw; + self.x = try a.alloc(f64, n * self.ch); + self.w = try a.alloc(f64, self.ch * taps); + self.st = try a.alloc(f64, (taps - 1) * self.ch); + self.qw = try a.alloc(f64, 128); + self.kn = try a.alloc(f64, 128); + self.av = try a.alloc(f64, n * heads); + self.bv = try a.alloc(f64, n * heads); + self.a_log = try a.alloc(f64, heads); + self.dt = try a.alloc(f64, heads); + var prng = std.Random.DefaultPrng.init(seed); + const rng = prng.random(); + if (fill == .stress) self.stress() else self.random(rng); + if (fill == .nonfinite) self.plant(); + const kinds = [_][]const f64{ self.x, self.av, self.bv }; + var kb: [3][]u8 = undefined; + for (&kb, kinds) |*b, v| { + b.* = try a.alloc(u8, v.len * kit.size(self.k)); + for (v, 0..) |e, i| kit.put(self.k, b.*, i, e); + } + const ins = [_][]const u8{ + kb[0], + try kit.f32Bytes(a, self.w), + try kit.f32Bytes(a, self.st), + try kit.f32Bytes(a, self.qw), + try kit.f32Bytes(a, self.kn), + kb[1], + kb[2], + try kit.f32Bytes(a, self.a_log), + try kit.f32Bytes(a, self.dt), + }; + for (ins, &self.in) |b, *at| at.* = try self.rig.input(b); + for (self.lens(), &self.out) |len, *at| at.* = try self.rig.output(len * 4); + for (self.lens(), self.base[0..6]) |len, *at| at.* = try self.rig.scratch(len * 4); + self.base[6] = try self.rig.scratch(n * self.ch * 4); + self.base[7] = try self.rig.scratch(n * self.kw * 4); + self.base[8] = try self.rig.scratch(n * self.kw * 4); + return true; + } + + fn random(self: *Prep, rng: std.Random) void { + put(rng, self.k, self.x, -2, 2); + put(rng, self.k, self.av, -3, 3); + put(rng, self.k, self.bv, -3, 3); + put(rng, .f32, self.w, -0.5, 0.5); + put(rng, .f32, self.st, -1, 1); + put(rng, .f32, self.qw, 1, 1.25); + put(rng, .f32, self.kn, 1, 1.25); + put(rng, .f32, self.a_log, 0, 1); + put(rng, .f32, self.dt, -1, 1); + } + + /// Gate 4: taps alternate every row, so weights A, B, -A, 1 - B leave the second tap, an integer in [40, 63]. + fn stress(self: *Prep) void { + const n = self.shape.rows; + for (0..n + taps - 1) |t| for (0..self.ch) |ch| { + const v: f64 = @floatFromInt(40 + (ch + t % 2) % 24); + if (t < taps - 1) self.st[t * self.ch + ch] = v else self.x[(t - (taps - 1)) * self.ch + ch] = v; + }; + for (0..self.ch) |ch| { + const w = self.w[ch * taps ..][0..taps]; + w[0] = @floatFromInt(2000 + ch % 40); + w[1] = @floatFromInt(1990 + ch % 50); + w[2] = -w[0]; + w[3] = 1 - w[1]; + } + // silu of an integer past 17 is itself in fp32: the norms sum integer squares below 2^19 + @memset(self.qw, 1); + @memset(self.kn, 1); + @memset(self.av, 0); + @memset(self.bv, 0); + @memset(self.a_log, 0); + @memset(self.dt, 0); + } + + /// NaN, +Inf and -Inf in a q, a k and a v channel; NaN in the conv state; NaN, -Inf in a and +Inf in b. + fn plant(self: *Prep) void { + const heads = self.shape.n; + if (self.shape.rows < 3 or heads < 4) return; + self.x[0] = std.math.nan(f64); + self.x[self.ch + self.kw + 5] = std.math.inf(f64); + self.x[2 * self.ch + 2 * self.kw + 7] = -std.math.inf(f64); + self.st[self.ch + 2 * self.kw + 9] = std.math.nan(f64); + self.av[1] = std.math.nan(f64); + self.bv[heads + 2] = std.math.inf(f64); + self.av[2 * heads + 3] = -std.math.inf(f64); + } + + pub fn run(self: *Prep) !void { + const C = ?*const anyopaque; + const CF = ?[*]const f32; + const F = ?[*]f32; + const in = self.in; + const out = self.out; + try self.l.tf_gdn_prompt_prep( + kit.ptr(C, in[0]), + @backingInt(self.k), + kit.ptr(CF, in[1]), + kit.ptr(CF, in[2]), + kit.ptr(F, out[5]), + kit.ptr(F, out[0]), + kit.ptr(F, out[1]), + kit.ptr(F, out[2]), + kit.ptr(CF, in[3]), + kit.ptr(CF, in[4]), + eps, + @intCast(self.shape.rows), + @intCast(self.kw), + @intCast(self.vw), + taps, + kit.ptr(C, in[5]), + kit.ptr(C, in[6]), + kit.ptr(CF, in[7]), + kit.ptr(CF, in[8]), + kit.ptr(F, out[3]), + kit.ptr(F, out[4]), + @intCast(self.shape.n), + self.rig.s.handle, + ); + try self.rig.s.synchronize(); + } + + /// The chain the launch replaces: conv, three column copies, the q and k norms, the gates. + pub fn replaced(self: *Prep) ![]const u8 { + const l = self.l; + const P = ?*anyopaque; + const C = ?*const anyopaque; + const CF = ?[*]const f32; + const F = ?[*]f32; + const s = self.rig.s.handle; + const in = self.in; + const b = self.base; + const n: c_int = @intCast(self.shape.rows); + const ch: c_longlong = @intCast(self.ch); + const kw: c_int = @intCast(self.kw); + const kind = @backingInt(self.k); + try l.tf_conv_prefill(kit.ptr(C, in[0]), kind, kit.ptr(CF, in[1]), kit.ptr(CF, in[2]), kit.ptr(F, b[6]), kit.ptr(F, b[5]), n, @intCast(self.ch), taps, s); + try l.tf_copy_cols(kit.ptr(C, b[6]), ch, 0, kit.ptr(P, b[7]), 0, n, kw, s); + try l.tf_copy_cols(kit.ptr(C, b[6]), ch, kw, kit.ptr(P, b[8]), 0, n, kw, s); + try l.tf_copy_cols(kit.ptr(C, b[6]), ch, 2 * kw, kit.ptr(P, b[2]), 0, n, @intCast(self.vw), s); + const heads: c_int = n * @divExact(kw, 128); + try l.tf_rms(kit.ptr(C, b[7]), kit.ptr(CF, in[3]), kit.ptr(P, b[0]), 0, heads, 128, eps, s); + try l.tf_rms(kit.ptr(C, b[8]), kit.ptr(CF, in[4]), kit.ptr(P, b[1]), 0, heads, 128, eps, s); + try l.tf_gdn_gate_prefill(kit.ptr(C, in[5]), kit.ptr(C, in[6]), kind, kit.ptr(CF, in[7]), kit.ptr(CF, in[8]), kit.ptr(F, b[3]), kit.ptr(F, b[4]), n, @intCast(self.shape.n), s); + const a = self.arena.allocator(); + var all: std.ArrayList(u8) = .empty; + for (self.lens(), b[0..6]) |len, at| try all.appendSlice(a, try self.rig.bytes(at, len * 4)); + return all.items; + } + + pub fn count(self: *Prep) usize { + var n: usize = 0; + for (self.lens()) |len| n += len; + return n; + } + + /// Conv tap t of channel ch: the state's rows, then x's. + fn window(self: *const Prep, t: usize, ch: usize) f64 { + return if (t < taps - 1) self.st[t * self.ch + ch] else self.x[(t - (taps - 1)) * self.ch + ch]; + } + + /// The conv's sum at row r of channel ch (in `sim`'s accumulator and order when given) and its terms' magnitude. + fn conv(self: *const Prep, r: usize, ch: usize, sim: ?gdn.Sim) struct { f64, f64 } { + var t: [taps]f64 = undefined; + var abs: f64 = 0; + for (&t, 0..) |*o, j| { + o.* = self.window(r + j, ch) * self.w[ch * taps + j]; + abs += @abs(o.*); + } + if (sim) |how| return .{ rows.sumIn(how[0], how[1], &t), abs }; + return .{ t[0] + t[1] + t[2] + t[3], abs }; + } + + fn outputs(self: *Prep, want: []f64, mag: []f64, sim: ?gdn.Sim) !void { + const n = self.shape.rows; + const heads = self.shape.n; + const kh = self.kw / 128; + const len = self.lens(); + var at: [6]usize = undefined; + var off: usize = 0; + for (&at, len) |*o, l| { + o.* = off; + off += l; + } + @memset(mag, 0); + var vals: [128]f64 = undefined; + var sq: [128]f64 = undefined; + for (0..n) |r| { + // q heads then k heads: silu of the conv, then the head's RMS norm times its weight + for (0..2 * kh) |hd| { + for (&vals, &sq, 0..) |*v, *q, i| { + v.* = kit.silu(self.conv(r, hd * 128 + i, sim)[0]); + q.* = v.* * v.*; + } + const ss = if (sim) |how| rows.sumIn(how[0], how[1], &sq) else blk: { + var x: f64 = 0; + for (sq) |e| x += e; + break :blk x; + }; + const inv = 1 / @sqrt(ss / 128 + @as(f64, eps)); + const is_q = hd < kh; + const nw = if (is_q) self.qw else self.kn; + const base = (if (is_q) at[0] else at[1]) + (r * kh + hd % kh) * 128; + for (vals, nw, 0..) |v, wv, i| { + want[base + i] = v * inv * wv; + mag[base + i] = @abs(want[base + i]); + } + } + for (0..self.vw) |i| { + const sum, const abs = self.conv(r, 2 * self.kw + i, sim); + want[at[2] + r * self.vw + i] = kit.silu(sum); + mag[at[2] + r * self.vw + i] = abs * kit.siluSlope(sum); + } + for (0..heads) |h| { + const i = r * heads + h; + const xa = self.av[i] + self.dt[h]; + const sp = if (xa > 20) xa else std.math.log1p(@exp(xa)); + want[at[3] + i] = @exp(-@exp(self.a_log[h]) * sp); + want[at[4] + i] = 1 / (1 + @exp(-self.bv[i])); + } + } + for (0..taps - 1) |t| for (0..self.ch) |ch| { + want[at[5] + t * self.ch + ch] = self.window(n + t, ch); + }; + } + + pub fn reference(self: *Prep, want: []f64, mag: []f64) !void { + return self.outputs(want, mag, null); + } + + pub fn simulate(self: *Prep, acc: c.Accum, order: g.Order, out: []f64) !void { + const mag = try self.rig.a.alloc(f64, out.len); + defer self.rig.a.free(mag); + return self.outputs(out, mag, .{ acc, order }); + } +}; + +/// Values uniform in [lo, hi), exact in the kind (fp16 normals only, as bf16 values are). +fn put(rng: std.Random, k: kit.Kind, v: []f64, lo: f64, hi: f64) void { + for (v) |*x| { + x.* = kit.round(k, lo + rng.float(f64) * (hi - lo)); + if (k == .f16 and @abs(x.*) < 0x1p-14) x.* = 0; + } +} diff --git a/zig/tests/hip/contract_hc_mix.zig b/zig/tests/hip/contract_hc_mix.zig new file mode 100644 index 0000000000..cfa2f7ed8c --- /dev/null +++ b/zig/tests/hip/contract_hc_mix.zig @@ -0,0 +1,437 @@ +//! Flash Next's HC mix under the contract on HIP: its float64 model, the dense tile's HC mix epilogue, its gate table. +const std = @import("std"); +const hip = @import("hip"); +const core = @import("core"); +const rig_ = @import("contract_rig.zig"); +const kit = @import("contract_kit.zig"); + +const contract = core.contract; +const c = contract.spec; +const g = contract.gates; +const rows = contract.rows; + +const Kernels = @FieldType(hip.Launcher, "affine"); +/// launches/affine.zig's Arg, as denseGo and denseHcMixGo take it. +const Arg = @typeInfo(@TypeOf(Kernels.denseGo)).@"fn".param_types[2].?; +const C = ?*const anyopaque; +const P = ?*anyopaque; + +/// sigmoid and silu as the kernels compute them, within this of float64's: expf within 3 ulps, then two roundings. +pub const fn_err = 0x1p-20; +const nan = std.math.nan(f64); +const inf = std.math.inf(f64); + +pub fn bf(v: f64) f64 { + return kit.round(.bf16, v); +} + +/// 1 / (1 + e^-v) in float64: NaN for NaN, 1 for +Inf, 0 for -Inf. +pub fn sigmoid(v: f64) f64 { + return 1 / (1 + @exp(-v)); +} + +/// tf_fn_hc_mix's gate of a g: g rounded to bf16, its sigmoid rounded to bf16. +pub fn gate(v: f64) f64 { + return bf(sigmoid(bf(v))); +} + +/// The gates the kernels can give for a g in [lo, hi]: the sigmoid within fn_err, or 2^-126 below fp32's normals. +pub fn gates(lo: f64, hi: f64) [2]f64 { + const a = sigmoid(bf(lo)) * (1 - fn_err) - 0x1p-126; + const b = sigmoid(bf(hi)) * (1 + fn_err) + 0x1p-126; + return .{ bf(@max(a, 0)), bf(b) }; +} + +/// The mix's output before its last rounding, its streams' terms summed in `acc` in `order` (float64 for none). +pub fn mixed(gs: []const f64, xs: []const f64, acc: c.Accum, order: rows.Order) f64 { + var t: [8]f64 = undefined; + for (gs, xs, t[0..gs.len]) |v, x, *o| o.* = bf(gate(v) * x); + return rows.sumIn(acc, order, t[0..gs.len]) / @as(f64, @floatFromInt(gs.len)); +} + +/// One output: float64's value at the kernel's rounding points, the range the device's can take, its allowance. +pub const Range = struct { want: f64, lo: f64, hi: f64, allow: f64 }; + +/// The largest power of two a nonzero bf16 value is a whole multiple of. +fn unitOf(v: f64) f64 { + var p = std.math.ldexp(@as(f64, 1), std.math.frexp(v).exponent - 8); + while (@mod(v, 2 * p) == 0) p *= 2; + return p; +} + +/// fp32 adds of these bf16 terms are exact in any order: every partial a whole count of their least unit below 2^24. +fn exactAdds(t: []const f64) bool { + var unit: f64 = inf; + var abs: f64 = 0; + for (t) |v| if (v != 0) { + unit = @min(unit, unitOf(v)); + abs += @abs(v); + }; + return abs == 0 or abs / unit < 0x1p24; +} + +/// Output (r, d) of the mix from each stream's g (the device's within `err` of it) and x, the terms' adds in fp32. +pub fn range(gs: []const f64, err: []const f64, xs: []const f64) Range { + var want: f64 = 0; + var lo: f64 = 0; + var hi: f64 = 0; + var abs: f64 = 0; + var t: [8]f64 = undefined; + var fixed = true; + for (gs, err, xs, t[0..gs.len]) |v, e, x, *o| { + o.* = bf(gate(v) * x); + want += o.*; + const span = gates(v - e, v + e); + const ends = [2]f64{ bf(span[0] * x), bf(span[1] * x) }; + fixed = fixed and ends[0] == ends[1]; + lo += @min(ends[0], ends[1]); + hi += @max(ends[0], ends[1]); + abs += @max(@abs(ends[0]), @abs(ends[1])); + } + const n: f64 = @floatFromInt(gs.len); + // n - 1 fp32 adds and the division by n, each within 2^-24 of the terms' magnitude over n + const slack = if (fixed and exactAdds(t[0..gs.len])) 0 else 0x1p-24 * abs; + const pre = [2]f64{ lo / n - slack, hi / n + slack }; + const out = [2]f64{ bf(pre[0]), bf(pre[1]) }; + want /= n; + const allow = @max(@max(pre[1], out[1]) - want, want - @min(pre[0], out[0])); + return .{ .want = want, .lo = out[0], .hi = out[1], .allow = allow + 0x1p-133 }; +} + +pub fn rangeBounds(ranges: []const Range, allow: []f64) void { + for (allow, ranges) |*l, r| l.* = r.allow; +} + +pub fn rangeIntervals(ranges: []const Range, lo: []f64, hi: []f64) void { + for (lo, hi, ranges) |*a, *b, r| { + a.* = r.lo; + b.* = r.hi; + } +} + +/// x's plants in row `r` of [rows][ways][width]: NaN, +Inf, -Inf, and both infinities in one output's streams. +pub fn plantX(x: []f64, ways: usize, width: usize, r: usize) void { + const at = [_][2]usize{ .{ 1, 5 }, .{ 2, 9 }, .{ 3, 11 }, .{ 0, 13 }, .{ 1, 13 } }; + const put = [_]f64{ nan, inf, -inf, inf, -inf }; + for (at, put) |p, v| x[(r * ways + p[0] % ways) * width + p[1] % width] = v; +} + +/// float64 values as bf16 bytes. +pub fn bf16Bytes(a: std.mem.Allocator, v: []const f64) ![]u8 { + const b = try a.alloc(u8, v.len * 2); + for (v, 0..) |x, i| kit.put(.bf16, b, i, x); + return b; +} + +/// Gate 1 of a replacement: its bytes are the replaced launches', and every output's class is float64's. +pub fn classes(e: c.Elem, out: []const u8, base: []const u8, want: []const f64) ?[]const u8 { + if (!std.mem.eql(u8, out, base)) return "non-finite output differs from the replaced launches' bytes"; + var planted: usize = 0; + for (want, 0..) |w, i| { + if (c.classOf(w) != .finite) planted += 1; + if (c.classOf(c.read(e, out, i)) != c.classOf(w)) return "non-finite output class differs from float64"; + } + if (planted == 0 or planted == want.len) return "the plants make no output, or every output, non-finite"; + return null; +} + +const streams = 4; +const low = 320; // hc up's K +const bits = 4; +const group = 32; + +/// A group's two WMMAs as 16 dot2 steps, two roundings each (gfx11's fp32 accumulate drops bits), then its two folds. +fn denseDepth(s: c.Shape) usize { + return 2 * 16 + 2 * (s.k / group); +} + +const both = "the separate launches' bytes and every float64 output class"; + +pub fn denseSpec() c.Spec { + return .{ + .name = "hip tf_affine_dense_hcmix (hc up, 4-bit, K 320, the HC mix as its epilogue)", + .accum = .f32, + .depth = denseDepth, + .out = .bf16, + .replaces = "the dense K 320 tile's bf16 product then tf_fn_hc_mix", + .nan = .{ .stated = both }, + .tiles = .{ .{ .size = 128 }, .{ .size = 128, .step = 128, .min = 128 }, .{} }, + // prompt rows the registry gives the dense tile, four streams of 2,560 + .served = &.{ + .{ .rows = 129, .n = streams * 2560, .k = low }, + .{ .rows = 300, .n = streams * 2560, .k = low }, + .{ .rows = 1000, .n = streams * 2560, .k = low }, + }, + .sums = .{ .exact = false }, + }; +} + +/// act [rows][320] times hc up's MLX 4-bit matrix [n][320], then mixed with x [rows][4][n / 4]: [rows][n / 4] bf16. +pub const Dense = struct { + rig: rig_.Rig, + l: *const hip.Launcher, + arena: std.heap.ArenaAllocator, + shape: c.Shape = undefined, + f: ?contract.affine.Affine = null, + x: []f64 = &.{}, + ranges: []Range = &.{}, + arg: Arg = undefined, + xs: u64 = 0, + out: u64 = 0, + g16: u64 = 0, + base: u64 = 0, + + pub fn init(a: std.mem.Allocator, rt: *const hip.Runtime, s: hip.Stream, l: *const hip.Launcher) Dense { + return .{ .rig = .{ .a = a, .r = rt, .s = s }, .l = l, .arena = .init(a) }; + } + + pub fn deinit(self: *Dense) void { + self.arena.deinit(); + self.rig.deinit(); + } + + pub fn kernel(self: *Dense) g.Kernel { + return .{ .spec = denseSpec(), .ctx = self, .vt = &dense_vt }; + } + + const dense_vt = g.hooks(Dense); + + fn dims(self: *const Dense) usize { + return self.shape.n / streams; + } + + /// The affine family's act and weights (gate 4: its integer sums, g in [-56, -8]); x in [-2, 2), 1 at gate 4. + pub fn prepare(self: *Dense, shape: c.Shape, fill: g.Fill, seed: u64) !bool { + if (shape.rows == 0 or shape.k != low or shape.n == 0 or shape.n % 128 != 0) return false; + self.rig.reset(); + _ = self.arena.reset(.retain_capacity); + self.shape = shape; + const a = self.arena.allocator(); + const f = try contract.affine.Affine.init(a, shape, bits, group); + try f.fill(fill, seed); + self.f = f; + var prng = std.Random.DefaultPrng.init(seed ^ 0x6863); + self.x = (try kit.values(a, prng.random(), .bf16, shape.rows * shape.n, -2, 2))[0]; + // the terms are then the gates: positive, so their fp32 adds stay within 2^-24 of the sum + if (fill == .stress) @memset(self.x, 1); + if (fill == .nonfinite and shape.rows > 4) plantX(self.x, streams, self.dims(), 4); + const w = try a.alloc(u32, shape.n * shape.k * bits / 32); + f.words(w); + self.arg = .{ + .x = try self.rig.input(std.mem.sliceAsBytes(f.x)), + .words = try self.rig.input(std.mem.sliceAsBytes(w)), + .scale = .{ .p = try self.rig.input(std.mem.sliceAsBytes(f.scales)), .kind = 1 }, // bf16 tables + .bias = .{ .p = try self.rig.input(std.mem.sliceAsBytes(f.biases)), .kind = 1 }, + .out = 0, + .m = @intCast(shape.rows), + .n = @intCast(shape.n), + .k = @intCast(shape.k), + .bits = bits, + .group = group, + .fp16 = 0, + }; + self.xs = try self.rig.input(try bf16Bytes(a, self.x)); + self.out = try self.rig.output(self.count() * 2); + self.g16 = try self.rig.scratch(shape.rows * shape.n * 2); + self.base = try self.rig.scratch(self.count() * 2); + return true; + } + + pub fn run(self: *Dense) !void { + try self.l.affine.denseHcMixGo(self.l.r, self.arg, self.xs, self.out, self.rig.s.handle); + try self.rig.s.synchronize(); + } + + /// The dense K 320 tile's product rounded to bf16, then tf_fn_hc_mix over it. + pub fn replaced(self: *Dense) ![]const u8 { + var plain = self.arg; + plain.out16 = self.g16; + const st = self.rig.s.handle; + try self.l.affine.denseGo(self.l.r, plain, st); + const m: c_int = @intCast(self.shape.rows); + const d: c_int = @intCast(self.dims()); + try self.l.fn_hc_mix_scalar(kit.ptr(C, self.g16), 2, kit.ptr(C, self.xs), kit.ptr(P, self.base), 2, m, streams, d, st); + return self.rig.bytes(self.base, self.count() * 2); + } + + pub fn check(self: *Dense, at: c.Gate) !?[]const u8 { + if (at != .nonfinite) return null; + const a = self.arena.allocator(); + const out = try a.dupe(u8, try self.rig.outputBytes()); + const want = try a.alloc(f64, self.count()); + const mag = try a.alloc(f64, self.count()); + try self.reference(want, mag); + return classes(.bf16, out, try self.replaced(), want); + } + + pub fn count(self: *Dense) usize { + return self.shape.rows * self.dims(); + } + + fn mixRows(self: *Dense, gv: []const f64, want: []f64, mag: []f64, err: []const f64) void { + const d = self.dims(); + for (0..self.shape.rows) |r| for (0..d) |j| { + var gs: [streams]f64 = undefined; + var es: [streams]f64 = undefined; + var xs: [streams]f64 = undefined; + for (0..streams) |s| { + gs[s] = gv[r * self.shape.n + s * d + j]; + es[s] = err[r * self.shape.n + s * d + j]; + xs[s] = self.x[(r * streams + s) * d + j]; + } + const i = r * d + j; + want[i] = mixed(&gs, &xs, .none, .sequential); + mag[i] = @abs(want[i]); + self.ranges[i] = range(&gs, &es, &xs); + }; + } + + /// The float64 product at MLX's factored formula, then the mix at its bf16 points; g within gamma(depth) of it. + pub fn reference(self: *Dense, want: []f64, mag: []f64) !void { + const f = self.f.?; + const a = self.arena.allocator(); + const gv = try a.alloc(f64, f.outputs()); + const err = try a.alloc(f64, f.outputs()); + const gam = c.gamma(@floatFromInt(denseDepth(self.shape)), c.unit(.f32)); + for (0..self.shape.rows) |r| for (0..self.shape.n) |j| { + const o = f.one(r, j); + gv[r * self.shape.n + j] = o[0]; + err[r * self.shape.n + j] = gam * o[1]; + }; + self.ranges = try a.alloc(Range, self.count()); + self.mixRows(gv, want, mag, err); + } + + pub fn bounds(self: *Dense, _: []const f64, _: []const f64, allow: []f64) !void { + rangeBounds(self.ranges, allow); + } + + pub fn intervals(self: *Dense, lo: []f64, hi: []f64) !void { + rangeIntervals(self.ranges, lo, hi); + } + + pub fn simulate(self: *Dense, acc: c.Accum, order: g.Order, out: []f64) !void { + const f = self.f.?; + const a = self.arena.allocator(); + const gv = try a.alloc(f64, f.outputs()); + try f.simulate(acc, order, gv); + const d = self.dims(); + for (0..self.shape.rows) |r| for (0..d) |j| { + var gs: [streams]f64 = undefined; + var xs: [streams]f64 = undefined; + for (0..streams) |s| { + gs[s] = gv[r * self.shape.n + s * d + j]; + xs[s] = self.x[(r * streams + s) * d + j]; + } + out[r * d + j] = mixed(&gs, &xs, acc, order); + }; + } +}; + +/// tf_hc_gate_fill's table in the tiles' code object: rnd(sigmoid(g)) for every bf16 g, as tf_affine_dense_hcmix reads. +const table_symbol = "_ZN2tf4rocm10tf_hc_gateE"; +const entries = 1 << 16; +const table_rule = "every bf16 g: NaN for NaN, else float64's 1 / (1 + e^-g) rounded to bf16 within expf's 2^-20 " ++ + "(2^-126 below fp32's normals); and tf_fn_hc_mix's gate of g, bit for bit"; + +fn none(_: c.Shape) usize { + return 0; +} + +pub fn tableSpec() c.Spec { + return .{ + .name = "hip tf_hc_gate_fill (tf_affine_dense_hcmix's 65,536 gates)", + .accum = .none, + .depth = none, + .out = .raw, + .nan = .{ .stated = table_rule }, + .served = &.{.{ .rows = 1, .n = entries, .k = 0 }}, + }; +} + +/// The table filled as the launcher fills it, each entry NaN before, copied out of the code object's global. +pub const Table = struct { + rig: rig_.Rig, + l: *const hip.Launcher, + arena: std.heap.ArenaAllocator, + global: u64 = 0, + gs: u64 = 0, + ones: u64 = 0, + out: u64 = 0, + base: u64 = 0, + msg: [160]u8 = undefined, + + pub fn init(a: std.mem.Allocator, rt: *const hip.Runtime, s: hip.Stream, l: *const hip.Launcher) Table { + return .{ .rig = .{ .a = a, .r = rt, .s = s }, .l = l, .arena = .init(a) }; + } + + pub fn deinit(self: *Table) void { + self.arena.deinit(); + self.rig.deinit(); + } + + pub fn kernel(self: *Table) g.Kernel { + return .{ .spec = tableSpec(), .ctx = self, .vt = &table_vt }; + } + + const table_vt = g.hooks(Table); + + /// Every gate's input is its own index; no fill changes them. Also every bf16 g and x = 1 for tf_fn_hc_mix. + pub fn prepare(self: *Table, _: c.Shape, _: g.Fill, _: u64) !bool { + self.rig.reset(); + _ = self.arena.reset(.retain_capacity); + const a = self.arena.allocator(); + const t = try self.l.mods[@backingInt(hip.kernels.Group.affine_tiles)].global(table_symbol); + if (t.len != entries * 2) return error.Invalid; + self.global = t.address; + const ids = try a.alloc(u16, entries); + for (ids, 0..) |*v, i| v.* = @intCast(i); + const ones = try a.alloc(u16, entries); + @memset(ones, 0x3f80); + self.gs = try self.rig.input(std.mem.sliceAsBytes(ids)); + self.ones = try self.rig.input(std.mem.sliceAsBytes(ones)); + self.out = try self.rig.output(entries * 2); + self.base = try self.rig.scratch(entries * 2); + return true; + } + + pub fn run(self: *Table) !void { + const api = self.rig.r.api; + try self.rig.s.synchronize(); + // every entry NaN first: an entry the fill skips cannot pass as the value the load left there + try hip.runtime.check(api.hipMemset(@ptrFromInt(self.global), 0xff, entries * 2)); + try self.l.affine.fillHcGate(self.l.r); + const st = self.rig.s.handle; + try hip.runtime.check(api.hipMemcpyDtoDAsync(@ptrFromInt(self.out), @ptrFromInt(self.global), entries * 2, st)); + try self.rig.s.synchronize(); + } + + pub fn count(_: *Table) usize { + return entries * 2; + } + + pub fn reference(_: *Table, want: []f64, mag: []f64) !void { + @memset(want, 0); + @memset(mag, 0); + } + + /// Each entry by the stated rule, and against tf_fn_hc_mix's gate (one stream, x = 1: its output is the gate). + pub fn check(self: *Table, _: c.Gate) !?[]const u8 { + const a = self.arena.allocator(); + const got = try a.dupe(u8, try self.rig.bytes(self.out, entries * 2)); + const st = self.rig.s.handle; + try self.l.fn_hc_mix_scalar(kit.ptr(C, self.gs), 2, kit.ptr(C, self.ones), kit.ptr(P, self.base), 2, 1, 1, entries, st); + const mix = try self.rig.bytes(self.base, entries * 2); + for (0..entries) |h| { + const v: f64 = c.fromBf16(@intCast(h)); + const out = c.read(.bf16, got, h); + const span = gates(v, v); + const ok = if (std.math.isNan(v)) std.math.isNan(out) else out >= span[0] and out <= span[1]; + if (!ok) return try std.fmt.bufPrint(&self.msg, "g {e} holds {e}, the rule gives [{e}, {e}]", .{ v, out, span[0], span[1] }); + if (!std.mem.eql(u8, got[2 * h ..][0..2], mix[2 * h ..][0..2])) { + return try std.fmt.bufPrint(&self.msg, "g {e} holds {e}, tf_fn_hc_mix's gate is {e}", .{ v, out, c.read(.bf16, mix, h) }); + } + } + return null; + } +}; diff --git a/zig/tests/hip/contract_hc_mix8.zig b/zig/tests/hip/contract_hc_mix8.zig new file mode 100644 index 0000000000..ee831b3d0a --- /dev/null +++ b/zig/tests/hip/contract_hc_mix8.zig @@ -0,0 +1,205 @@ +//! tf_fn_hc_mix8 under the contract on HIP: Flash Next's HC mix, 8 bf16 outputs a thread, bit-equal to tf_fn_hc_mix. +const std = @import("std"); +const hip = @import("hip"); +const core = @import("core"); +const rig_ = @import("contract_rig.zig"); +const kit = @import("contract_kit.zig"); +const mix = @import("contract_hc_mix.zig"); + +const contract = core.contract; +const c = contract.spec; +const g = contract.gates; + +const C = ?*const anyopaque; +const P = ?*anyopaque; +const nan = std.math.nan(f64); +const inf = std.math.inf(f64); + +/// The kind of g: the up product's fp32 sums, or its bf16 rows. +pub const Gkind = enum(c_int) { f32 = 0, bf16 = 2 }; + +/// The streams' terms added in order, then the division by their count. +fn depth(s: c.Shape) usize { + return s.k + 1; +} + +const both = "the per-element kernel's bytes and every float64 output class"; + +pub fn spec(gk: Gkind) c.Spec { + return .{ + .name = if (gk == .f32) "hip tf_fn_hc_mix8 (g fp32, bf16 x)" else "hip tf_fn_hc_mix8 (g bf16, bf16 x)", + .accum = .f32, + .depth = depth, + .ops = 1, + .out = .bf16, + .replaces = "tf_fn_hc_mix", + .nan = .{ .stated = both }, + // a block's 2,048 outputs in steps of a thread's 8, over the rows' streams of 2,560 + .tiles = .{ .{}, .{ .size = 2048, .step = 8, .min = 8 }, .{} }, + // a decode row, a verify window's 16 and a prompt's rows; four streams + .served = &.{ + .{ .rows = 1, .n = 2560, .k = 4 }, + .{ .rows = 16, .n = 2560, .k = 4 }, + .{ .rows = 300, .n = 2560, .k = 4 }, + }, + }; +} + +/// g and x [rows][streams][dims] (shape rows, dims as n, streams as k): mixed [rows][dims] bf16. +pub const Mix8 = struct { + rig: rig_.Rig, + l: *const hip.Launcher, + gk: Gkind, + arena: std.heap.ArenaAllocator, + shape: c.Shape = undefined, + gv: []f64 = &.{}, + x: []f64 = &.{}, + ranges: []mix.Range = &.{}, + gs: u64 = 0, + xs: u64 = 0, + out: u64 = 0, + base: u64 = 0, + + pub fn init(a: std.mem.Allocator, rt: *const hip.Runtime, s: hip.Stream, l: *const hip.Launcher, gk: Gkind) Mix8 { + return .{ .rig = .{ .a = a, .r = rt, .s = s }, .l = l, .gk = gk, .arena = .init(a) }; + } + + pub fn deinit(self: *Mix8) void { + self.arena.deinit(); + self.rig.deinit(); + } + + pub fn kernel(self: *Mix8) g.Kernel { + return .{ .spec = spec(self.gk), .ctx = self, .vt = &vt }; + } + + const vt = g.hooks(Mix8); + + fn at(self: *const Mix8, r: usize, s: usize, d: usize) usize { + return (r * self.shape.k + s) * self.shape.n + d; + } + + /// g in [-6, 6), x in [-2, 2); gate 4: g 16 (gate 1), x 2^20, v, -2^20 and 0 a column, so only fp32 keeps v. + pub fn prepare(self: *Mix8, shape: c.Shape, fill: g.Fill, seed: u64) !bool { + // the launcher takes tf_fn_hc_mix8 for bf16 activations at widths a multiple of 8 + if (shape.rows == 0 or shape.n == 0 or shape.n % 8 != 0 or shape.k == 0 or shape.k > 8) return false; + self.rig.reset(); + _ = self.arena.reset(.retain_capacity); + self.shape = shape; + const a = self.arena.allocator(); + var prng = std.Random.DefaultPrng.init(seed); + const rng = prng.random(); + const n = shape.rows * shape.k * shape.n; + self.gv = try kit.floats(a, rng, n, -6, 6); + if (self.gk == .bf16) for (self.gv) |*v| { + v.* = mix.bf(v.*); + }; + self.x = (try kit.values(a, rng, .bf16, n, -2, 2))[0]; + if (fill == .stress) self.stress(rng); + if (fill == .nonfinite) self.plant(); + const gb = if (self.gk == .f32) try kit.f32Bytes(a, self.gv) else try mix.bf16Bytes(a, self.gv); + self.gs = try self.rig.input(gb); + self.xs = try self.rig.input(try mix.bf16Bytes(a, self.x)); + self.out = try self.rig.output(self.count() * 2); + self.base = try self.rig.scratch(self.count() * 2); + return true; + } + + fn stress(self: *Mix8, rng: std.Random) void { + @memset(self.gv, 16); + @memset(self.x, 0); + for (0..self.shape.rows) |r| for (0..self.shape.n) |d| { + const v: f64 = @floatFromInt(1 + rng.uintLessThan(u32, 64)); + const put = [_]f64{ 0x1p20, v, -0x1p20 }; + for (put, 0..) |p, s| if (s < self.shape.k) { + self.x[self.at(r, s, d)] = p; + }; + }; + } + + /// g: NaN, +Inf, -Inf (a gate of 0) and -Inf times an infinite x in rows 0-3; x's plants in row 4. + fn plant(self: *Mix8) void { + const s = self.shape; + const k = s.k; + const gat = [_][3]usize{ .{ 0, 0, 7 }, .{ 1, 2, 3 }, .{ 1, 1, 4 }, .{ 2, 3, 6 }, .{ 3, 0, 8 } }; + const gput = [_]f64{ nan, inf, -inf, -inf, inf }; + for (gat, gput) |p, v| if (p[0] < s.rows) { + self.gv[self.at(p[0], p[1] % k, p[2] % s.n)] = v; + }; + if (s.rows > 1) self.x[self.at(1, 1 % k, 4 % s.n)] = inf; + if (s.rows > 3) self.x[self.at(3, 0, 8 % s.n)] = -inf; + if (s.rows > 4) mix.plantX(self.x, k, s.n, 4); + } + + pub fn run(self: *Mix8) !void { + const s = self.shape; + const gk = @backingInt(self.gk); + const st = self.rig.s.handle; + try self.l.fn_hc_mix(kit.ptr(C, self.gs), gk, kit.ptr(C, self.xs), kit.ptr(P, self.out), 2, @intCast(s.rows), @intCast(s.k), @intCast(s.n), st); + try self.rig.s.synchronize(); + } + + /// tf_fn_hc_mix, one output a thread, on the same g and x. + pub fn replaced(self: *Mix8) ![]const u8 { + const s = self.shape; + const gk = @backingInt(self.gk); + const st = self.rig.s.handle; + try self.l.fn_hc_mix_scalar(kit.ptr(C, self.gs), gk, kit.ptr(C, self.xs), kit.ptr(P, self.base), 2, @intCast(s.rows), @intCast(s.k), @intCast(s.n), st); + return self.rig.bytes(self.base, self.count() * 2); + } + + pub fn check(self: *Mix8, at_: c.Gate) !?[]const u8 { + if (at_ != .nonfinite) return null; + const a = self.arena.allocator(); + const out = try a.dupe(u8, try self.rig.outputBytes()); + const want = try a.alloc(f64, self.count()); + const mag = try a.alloc(f64, self.count()); + try self.reference(want, mag); + return mix.classes(.bf16, out, try self.replaced(), want); + } + + pub fn count(self: *Mix8) usize { + return self.shape.rows * self.shape.n; + } + + fn column(self: *const Mix8, r: usize, d: usize, gs: []f64, xs: []f64) void { + for (gs, xs, 0..) |*gv, *x, s| { + gv.* = self.gv[self.at(r, s, d)]; + x.* = self.x[self.at(r, s, d)]; + } + } + + /// The mix at its bf16 points in float64; g is an input, so it carries no error. + pub fn reference(self: *Mix8, want: []f64, mag: []f64) !void { + const s = self.shape; + self.ranges = try self.arena.allocator().alloc(mix.Range, self.count()); + const zero: [8]f64 = @splat(0); + var gs: [8]f64 = undefined; + var xs: [8]f64 = undefined; + for (0..s.rows) |r| for (0..s.n) |d| { + self.column(r, d, gs[0..s.k], xs[0..s.k]); + const i = r * s.n + d; + want[i] = mix.mixed(gs[0..s.k], xs[0..s.k], .none, .sequential); + mag[i] = @abs(want[i]); + self.ranges[i] = mix.range(gs[0..s.k], zero[0..s.k], xs[0..s.k]); + }; + } + + pub fn bounds(self: *Mix8, _: []const f64, _: []const f64, allow: []f64) !void { + mix.rangeBounds(self.ranges, allow); + } + + pub fn intervals(self: *Mix8, lo: []f64, hi: []f64) !void { + mix.rangeIntervals(self.ranges, lo, hi); + } + + pub fn simulate(self: *Mix8, acc: c.Accum, order: g.Order, out: []f64) !void { + const s = self.shape; + var gs: [8]f64 = undefined; + var xs: [8]f64 = undefined; + for (0..s.rows) |r| for (0..s.n) |d| { + self.column(r, d, gs[0..s.k], xs[0..s.k]); + out[r * s.n + d] = mix.mixed(gs[0..s.k], xs[0..s.k], acc, order); + }; + } +}; diff --git a/zig/tests/hip/contract_hc_norm.zig b/zig/tests/hip/contract_hc_norm.zig new file mode 100644 index 0000000000..655481a08a --- /dev/null +++ b/zig/tests/hip/contract_hc_norm.zig @@ -0,0 +1,302 @@ +//! Flash Next's HC norms under the contract on HIP: the 16-byte norm and the MoE combine in it, bit-equal to chains. +const std = @import("std"); +const hip = @import("hip"); +const core = @import("core"); +const rig_ = @import("contract_rig.zig"); +const kit = @import("contract_kit.zig"); +const mix = @import("contract_hc_mix.zig"); + +const contract = core.contract; +const c = contract.spec; +const g = contract.gates; +const rows = contract.rows; + +const C = ?*const anyopaque; +const P = ?*anyopaque; +const CF = ?[*]const f32; +const nan = std.math.nan(f64); +const inf = std.math.inf(f64); + +/// tf_fn_hc_norm_v with a branch added to h in place, or without (x only); tf_fn_hc_norm_moe and its 16-byte form. +pub const Mode = enum { v_branch, v_plain, moe, moe_v }; + +const dims = 2560; // Flash Next's stream width, the one the 16-byte kernels take +const slots = 11; // Flash Next's 10 routed experts and the shared one +const eps: f32 = 1e-6; + +/// The old norm's sum of squares: up to 4 a thread, the wave's xor tree, the block's 32 waves; the combine's slots. +fn depth(s: c.Shape) usize { + return (s.k + 1023) / 1024 + 5 + 32 + slots; +} + +const why = "a 16-bit output follows the sum of squares as ss^-1/2: a bf16 sum's error is a few output ulps"; +const rule = "the chain's bytes and every float64 output class"; + +pub fn spec(m: Mode, k: kit.Kind) c.Spec { + var s = c.Spec{ + .name = switch (m) { + .v_branch => "hip tf_fn_hc_norm_v (bf16, a branch added in place)", + .v_plain => "hip tf_fn_hc_norm_v (bf16, no branch)", + .moe => if (k == .bf16) "hip tf_fn_hc_norm_moe (bf16)" else "hip tf_fn_hc_norm_moe (fp16)", + .moe_v => "hip tf_fn_hc_norm_moe_v (bf16, a prompt's rows)", + }, + .accum = .f32, + .depth = depth, + // rsqrt, the mean and eps, two products + .ops = 8, + .out = kit.elem(k), + .replaces = if (m == .moe or m == .moe_v) "tf_moe_combine then tf_fn_hc_norm" else "tf_fn_hc_norm", + .nan = .{ .stated = rule }, + // one to four streams, Flash Next's four the widest + .tiles = .{ .{}, .{ .size = 4 }, .{} }, + .served = switch (m) { + .v_branch, .v_plain => &.{ + .{ .rows = 1, .n = 4, .k = dims }, + .{ .rows = 16, .n = 4, .k = dims }, + .{ .rows = 300, .n = 4, .k = dims }, + }, + .moe => &.{ + .{ .rows = 1, .n = 4, .k = dims }, + .{ .rows = 8, .n = 4, .k = dims }, + .{ .rows = 16, .n = 4, .k = dims }, + }, + .moe_v => &.{ + .{ .rows = 1, .n = 4, .k = dims }, + .{ .rows = 64, .n = 4, .k = dims }, + .{ .rows = 300, .n = 4, .k = dims }, + }, + }, + .sums = .{ .bf16 = 0, .why = why }, + }; + // the 1,024-thread block's edges in the width it takes, up to 4,096 + if (m == .moe) s.tiles[2] = .{ .size = 1024 }; + return s; +} + +/// h [rows][streams][k] of the kind, x [rows][streams][k]: h += round(branch * inject) (a branch), x = h rinv scale. +pub const Norm = struct { + rig: rig_.Rig, + l: *const hip.Launcher, + mode: Mode, + k: kit.Kind, + arena: std.heap.ArenaAllocator, + shape: c.Shape = undefined, + h: []f64 = &.{}, + br: []f64 = &.{}, // [rows][k], the v modes' branch + y: []f64 = &.{}, // [rows][slots][k], the MoE's expert rows + wts: []f64 = &.{}, + inj: []f64 = &.{}, + scale: []f64 = &.{}, + h_bytes: []u8 = &.{}, + in: [5]u64 = @splat(0), // branch or y, wts, inject, scale, h when not in place + out: [2]u64 = @splat(0), // h in place, x + base: [3]u64 = @splat(0), // the chain's h, x and combined branch + + pub fn init(a: std.mem.Allocator, rt: *const hip.Runtime, s: hip.Stream, l: *const hip.Launcher, m: Mode) Norm { + const k: kit.Kind = if (m == .moe) kit.act() else .bf16; + return .{ .rig = .{ .a = a, .r = rt, .s = s }, .l = l, .mode = m, .k = k, .arena = .init(a) }; + } + + pub fn deinit(self: *Norm) void { + self.arena.deinit(); + self.rig.deinit(); + } + + pub fn kernel(self: *Norm) g.Kernel { + return .{ .spec = spec(self.mode, self.k), .ctx = self, .vt = &vt }; + } + + const vt = g.hooks(Norm); + + fn moe(self: *const Norm) bool { + return self.mode == .moe or self.mode == .moe_v; + } + + fn inPlace(self: *const Norm) bool { + return self.mode != .v_plain; + } + + fn at(self: *const Norm, r: usize, s: usize, d: usize) usize { + return (r * self.shape.n + s) * self.shape.k + d; + } + + /// h in [-3, 3), branch in [-1, 1), inject in [-2, 2), y in [-2, 2) by weights in [0, 0.5), scale in [1, 1.25). + pub fn prepare(self: *Norm, shape: c.Shape, fill: g.Fill, seed: u64) !bool { + if (shape.rows == 0 or shape.n == 0 or shape.n > 4 or shape.k == 0) return false; + if (if (self.mode == .moe) shape.k > 4096 else shape.k != dims) return false; + self.rig.reset(); + _ = self.arena.reset(.retain_capacity); + self.shape = shape; + const a = self.arena.allocator(); + var prng = std.Random.DefaultPrng.init(seed); + const rng = prng.random(); + const k = self.k; + const n = shape.rows * shape.n * shape.k; + self.h = (try kit.values(a, rng, k, n, -3, 3))[0]; + self.br = (try kit.values(a, rng, k, shape.rows * shape.k, -1, 1))[0]; + self.inj = (try kit.values(a, rng, k, shape.rows * shape.n, -2, 2))[0]; + self.y = if (self.moe()) try kit.floats(a, rng, shape.rows * slots * shape.k, -2, 2) else &.{}; + self.wts = try kit.floats(a, rng, shape.rows * slots, 0, 0.5); + self.scale = try kit.floats(a, rng, shape.n * shape.k, 1, 1.25); + if (fill == .stress) try self.stress(seed); + if (fill == .nonfinite) self.plant(); + self.h_bytes = try a.alloc(u8, n * kit.size(k)); + for (self.h, 0..) |v, i| kit.put(k, self.h_bytes, i, v); + const branch = if (self.moe()) try kit.f32Bytes(a, self.y) else blk: { + const b = try a.alloc(u8, self.br.len * kit.size(k)); + for (self.br, 0..) |v, i| kit.put(k, b, i, v); + break :blk b; + }; + const ib = try a.alloc(u8, self.inj.len * kit.size(k)); + for (self.inj, 0..) |v, i| kit.put(k, ib, i, v); + const ins = [_][]const u8{ branch, try kit.f32Bytes(a, self.wts), ib, try kit.f32Bytes(a, self.scale) }; + for (ins, self.in[0..4]) |b, *p| p.* = try self.rig.input(b); + if (self.inPlace()) self.out[0] = try self.rig.output(self.h_bytes.len) else self.in[4] = try self.rig.input(self.h_bytes); + self.out[1] = try self.rig.output(self.h_bytes.len); + self.base = .{ try self.rig.scratch(self.h_bytes.len), try self.rig.scratch(self.h_bytes.len), try self.rig.scratch(shape.rows * shape.k * kit.size(k)) }; + return true; + } + + /// Gate 4: the norm's rows of integers (rows.zig's) and nothing added, so its sums are exact in fp32. + fn stress(self: *Norm, seed: u64) !void { + const s = self.shape; + const r = try rows.Rows.init(self.arena.allocator(), .rms, .{ .rows = s.rows * s.n, .n = s.k, .k = s.k }); + r.fill(.stress, seed); + for (self.h, r.x) |*v, b| v.* = c.fromBf16(b); + @memset(self.br, 0); + @memset(self.y, 0); + } + + /// h: NaN, +Inf, -Inf, both infinities in one stream (rows 0-3); the branch +Inf and an inject NaN in row 4. + fn plant(self: *Norm) void { + const s = self.shape; + const at_ = [_][3]usize{ .{ 0, 0, s.k / 3 }, .{ 1, 1, s.k / 2 }, .{ 2, 2, s.k - 1 }, .{ 3, 3, 0 }, .{ 3, 3, s.k - 1 } }; + const put = [_]f64{ nan, inf, -inf, inf, -inf }; + for (at_, put) |p, v| if (p[0] < s.rows) { + self.h[self.at(p[0], p[1] % s.n, p[2])] = v; + }; + if (s.rows < 5) return; + if (self.moe()) self.y[(4 * slots + 3) * s.k + 7 % s.k] = inf else self.br[4 * s.k + 7 % s.k] = inf; + self.inj[4 * s.n + s.n - 1] = nan; + } + + fn ptr(at_: u64) ?*anyopaque { + return @ptrFromInt(at_); + } + + /// h back to the prepared rows (in place), then the launch. + pub fn run(self: *Norm) !void { + const s = self.shape; + const st = self.rig.s.handle; + const rn: c_int = @intCast(s.rows); + const sn: c_int = @intCast(s.n); + if (self.inPlace()) try self.rig.put(self.out[0], self.h_bytes); + const h = self.out[0]; + const x = ptr(self.out[1]); + const sc = kit.ptr(CF, self.in[3]); + const y = kit.ptr(CF, self.in[0]); + const w = kit.ptr(CF, self.in[1]); + const inj = kit.ptr(C, self.in[2]); + switch (self.mode) { + // the launcher takes tf_fn_hc_norm_v for one rank's bf16 streams of 2,560 + .v_branch => try self.l.fn_hc_norm(kit.ptr(C, h), kit.ptr(C, self.in[0]), inj, ptr(h), x, sc, 2, rn, sn, dims, eps, st), + .v_plain => try self.l.fn_hc_norm(kit.ptr(C, self.in[4]), null, null, null, x, sc, 2, rn, sn, dims, eps, st), + .moe => try self.l.fn_hc_norm_moe(kit.ptr(C, h), y, w, inj, ptr(h), x, sc, @backingInt(self.k), rn, sn, @intCast(s.k), eps, slots, st), + .moe_v => try self.l.fn_hc_norm_moe_v(kit.ptr(C, h), y, w, inj, ptr(h), x, sc, rn, sn, eps, slots, st), + } + try self.rig.s.synchronize(); + } + + /// tf_moe_combine into the kind (the MoE modes), then tf_fn_hc_norm's 1,024-thread blocks on the same rows. + pub fn replaced(self: *Norm) ![]const u8 { + const s = self.shape; + const st = self.rig.s.handle; + const kind = @backingInt(self.k); + var branch = self.in[0]; + if (self.moe()) { + const y = kit.ptr(CF, self.in[0]); + try self.l.tf_moe_combine(y, kit.ptr(CF, self.in[1]), ptr(self.base[2]), kind, @intCast(s.rows), slots, @intCast(s.k), st); + branch = self.base[2]; + } + if (self.inPlace()) try self.rig.put(self.base[0], self.h_bytes); + const h = if (self.inPlace()) self.base[0] else self.in[4]; + const add = self.mode != .v_plain; + var a: hip.launch.Args = .{}; + const ptrs = [_]u64{ h, if (add) branch else 0, if (add) self.in[2] else 0, if (add) h else 0, self.base[1], self.in[3] }; + for (ptrs) |v| try a.add(v); + for ([_]c_int{ kind, @intCast(s.n), @intCast(s.k) }) |v| try a.add(v); + try a.add(eps); + try a.add(@as(c_int, 0)); // no tensor-parallel shares + try a.add(@as(c_longlong, 0)); + const cfg: hip.launch.Config = .{ .grid = .{ .x = @intCast(s.n), .y = @intCast(s.rows) }, .block = .{ .x = 1024 } }; + try hip.launch.launch(self.l.fnx.hc_norm, cfg, self.rig.s, &a); + const len = self.h_bytes.len; + const x = try self.arena.allocator().dupe(u8, try self.rig.bytes(self.base[1], len)); + if (!self.inPlace()) return x; + return std.mem.concat(self.arena.allocator(), u8, &.{ try self.rig.bytes(self.base[0], len), x }); + } + + pub fn check(self: *Norm, at_: c.Gate) !?[]const u8 { + if (at_ != .nonfinite) return null; + const a = self.arena.allocator(); + const out = try a.dupe(u8, try self.rig.outputBytes()); + const want = try a.alloc(f64, self.count()); + const mag = try a.alloc(f64, self.count()); + try self.reference(want, mag); + return mix.classes(kit.elem(self.k), out, try self.replaced(), want); + } + + pub fn count(self: *Norm) usize { + return (if (self.inPlace()) @as(usize, 2) else 1) * self.h.len; + } + + /// The branch at (r, d) in the kind: the v modes' row, or the experts' rows combined in float64 and rounded. + fn branchAt(self: *const Norm, r: usize, d: usize) f64 { + const k = self.shape.k; + if (!self.moe()) return self.br[r * k + d]; + var acc: f64 = 0; + for (0..slots) |j| acc += self.y[(r * slots + j) * k + d] * self.wts[r * slots + j]; + return kit.round(self.k, acc); + } + + /// h after the branch, rounded where the kernels round: h + round(branch * inject), rounded to the kind. + fn residual(self: *const Norm, r: usize, s: usize, d: usize) f64 { + const v = self.h[self.at(r, s, d)]; + if (self.mode == .v_plain) return v; + const add = kit.round(self.k, self.branchAt(r, d) * self.inj[r * self.shape.n + s]); + return kit.round(self.k, v + add); + } + + fn norms(self: *Norm, acc: c.Accum, order: g.Order, want: []f64, mag: ?[]f64) !void { + const s = self.shape; + const t = try self.arena.allocator().alloc(f64, 2 * s.k); + const off = if (self.inPlace()) self.h.len else 0; + for (0..s.rows) |r| for (0..s.n) |si| { + const v = t[0..s.k]; + for (v, t[s.k..], 0..) |*o, *sq, d| { + o.* = self.residual(r, si, d); + sq.* = o.* * o.*; + } + const ss = rows.sumIn(acc, order, t[s.k..]); + const inv = 1 / @sqrt(ss / @as(f64, @floatFromInt(s.k)) + eps); + for (v, 0..) |o, d| { + const i = self.at(r, si, d); + if (self.inPlace()) want[i] = o; + want[off + i] = o * inv * self.scale[si * s.k + d]; + if (mag) |m| { + if (self.inPlace()) m[i] = 0; + m[off + i] = @abs(want[off + i]) / 2; // x ~ ss^-1/2 + } + } + }; + } + + /// h at its rounding points, then rms(h) * scale in float64 (the h rows first when written in place). + pub fn reference(self: *Norm, want: []f64, mag: []f64) !void { + return self.norms(.none, .sequential, want, mag); + } + + pub fn simulate(self: *Norm, acc: c.Accum, order: g.Order, out: []f64) !void { + return self.norms(acc, order, out, null); + } +}; diff --git a/zig/tests/hip/contract_limits.zig b/zig/tests/hip/contract_limits.zig index 23e11b25ee..9ba6ac7c35 100644 --- a/zig/tests/hip/contract_limits.zig +++ b/zig/tests/hip/contract_limits.zig @@ -72,6 +72,10 @@ pub fn live(a: std.mem.Allocator, r: *const hip.Runtime, ctx: hip.Context, arch: std.debug.print(say, .{ word, arch, d[0], got, d[2] }); } for (all) |rec| { + if (!rec.launch.served[at]) { + std.debug.print("N/A limits live {s}: not launched on {s}\n", .{ rec.launch.name, arch }); + continue; + } const bytes = try image(rec.launch.image); const listed = try hsaco.kernels(a, bytes); defer a.free(listed); @@ -108,6 +112,14 @@ pub fn objects(a: std.mem.Allocator, io: std.Io, dir: []const u8) !usize { var line: std.ArrayList(u8) = .empty; defer line.deinit(a); for (limits.rdna, 0..) |t, i| { + if (!rec.launch.served[i]) { + // not launched on this chip: nothing to record, and a recorded usage is stale + const none = rec.usage[i].vgprs == 0; + if (!none) n += 1; + std.debug.print("{s} limits {s} {s}: not launched on this chip\n", .{ if (none) "N/A " else "FAIL", t.name, rec.launch.name }); + try line.print(a, ".{{ .vgprs = 0, .sgprs = 0, .lds = 0, .private = 0, .bound = {d}, .wave = {d} }}, ", .{ rec.launch.threads, t.wave }); + continue; + } const path = try file(a, dir, t.name, rec.launch.image); defer a.free(path); const bytes = std.Io.Dir.cwd().readFileAlloc(io, path, a, .limited(1 << 28)) catch |err| { diff --git a/zig/tests/hip/contract_main.zig b/zig/tests/hip/contract_main.zig index 5b07bfefb3..fd9a3a99c2 100644 --- a/zig/tests/hip/contract_main.zig +++ b/zig/tests/hip/contract_main.zig @@ -16,6 +16,14 @@ const relu2_k = @import("contract_relu2.zig"); const kv_k = @import("contract_kv_write.zig"); const argmax_k = @import("contract_argmax.zig"); const pair_k = @import("contract_relu2_pair.zig"); +const wmma_dense_k = @import("contract_wmma_dense.zig"); +const wmma_moe_k = @import("contract_wmma_moe.zig"); +const route_k = @import("contract_route.zig"); +const select_k = @import("contract_select.zig"); +const topk_k = @import("contract_topk.zig"); +const prefetch_k = @import("contract_prefetch.zig"); +const fn_scores_k = @import("contract_fn_scores.zig"); +const fn_qsa_k = @import("contract_fn_qsa.zig"); const g = core.contract.gates; @@ -136,6 +144,66 @@ fn run(a: std.mem.Allocator, io: std.Io) !usize { var pair = pair_k.Pair.init(a, &r, s, &l); defer pair.deinit(); try kernels.append(a, pair.kernel()); + var wmma_dense: [wmma_dense_k.cases.len]wmma_dense_k.Dense = undefined; + for (&wmma_dense, 0..) |*x, i| x.* = .init(a, &r, s, &l, i); + defer for (&wmma_dense) |*x| x.deinit(); + for (&wmma_dense) |*x| if (x.ready()) try kernels.append(a, x.kernel()); + var wmma_moe: [2]wmma_moe_k.Moe = undefined; + for (&wmma_moe, std.enums.values(wmma_moe_k.Part)) |*x, p| x.* = .init(a, &r, s, &l, p); + defer for (&wmma_moe) |*x| x.deinit(); + for (&wmma_moe) |*x| if (x.ready()) try kernels.append(a, x.kernel()); + var route = route_k.Route.init(a, &r, s, &l); + defer route.deinit(); + try kernels.append(a, route.kernel()); + var selects: [2]select_k.Select = undefined; + for (&selects, std.enums.values(select_k.Which)) |*m, w| m.* = .init(a, &r, s, &l, w); + defer for (&selects) |*m| m.deinit(); + for (&selects) |*m| try kernels.append(a, m.kernel()); + var topk = topk_k.Topk.init(a, &r, s, &l); + defer topk.deinit(); + try kernels.append(a, topk.kernel()); + var prefetch = prefetch_k.Prefetch.init(a, &r, s, &l); + defer prefetch.deinit(); + try kernels.append(a, prefetch.kernel()); + var fn_scores: [2]fn_scores_k.Scores = undefined; + for (&fn_scores, std.enums.values(fn_scores_k.Which)) |*x, w| x.* = .init(a, &r, s, &l, w); + defer for (&fn_scores) |*x| x.deinit(); + for (&fn_scores) |*x| try kernels.append(a, x.kernel()); + var fn_qsa: [2]fn_qsa_k.Qsa = undefined; + for (&fn_qsa, std.enums.values(fn_qsa_k.Part)) |*x, p| x.* = .init(a, &r, s, &l, p); + defer for (&fn_qsa) |*x| x.deinit(); + for (&fn_qsa) |*x| try kernels.append(a, x.kernel()); + // Flash Next's hyper-connection kernels: the dense tile's HC mix and its gate table on the gfx11 matrix cores + const hc_mix_k = @import("contract_hc_mix.zig"); + var hc_dense = hc_mix_k.Dense.init(a, &r, s, &l); + defer hc_dense.deinit(); + var hc_table = hc_mix_k.Table.init(a, &r, s, &l); + defer hc_table.deinit(); + if (l.affine.matrix) try kernels.appendSlice(a, &.{ hc_dense.kernel(), hc_table.kernel() }); + const hc_bf16 = @import("contract_kit.zig").act() == .bf16; + const hc_mix8_k = @import("contract_hc_mix8.zig"); + var hc_mix8: [2]hc_mix8_k.Mix8 = undefined; + for (&hc_mix8, std.enums.values(hc_mix8_k.Gkind)) |*m, gk| m.* = .init(a, &r, s, &l, gk); + defer for (&hc_mix8) |*m| m.deinit(); + if (hc_bf16) for (&hc_mix8) |*m| try kernels.append(a, m.kernel()); + const hc_norm_k = @import("contract_hc_norm.zig"); + var hc_norms: [4]hc_norm_k.Norm = undefined; + for (&hc_norms, std.enums.values(hc_norm_k.Mode)) |*m, w| m.* = .init(a, &r, s, &l, w); + defer for (&hc_norms) |*m| m.deinit(); + for (&hc_norms) |*m| if (hc_bf16 or m.mode == .moe) try kernels.append(a, m.kernel()); + const gdn_k = @import("contract_gdn.zig"); + var gdn_prompts: [2]gdn_k.Prompt = undefined; + for (&gdn_prompts, std.enums.values(gdn_k.Part)) |*m, p| m.* = .init(a, &r, s, &l, p); + defer for (&gdn_prompts) |*m| m.deinit(); + for (&gdn_prompts) |*m| try kernels.append(a, m.kernel()); + var gdn_prep = @import("contract_gdn_prep.zig").Prep.init(a, &r, s, &l); + defer gdn_prep.deinit(); + try kernels.append(a, gdn_prep.kernel()); + const hold_k = @import("contract_gdn_hold.zig"); + var gdn_windows: [4]hold_k.Window = undefined; + for (&gdn_windows, 0..) |*m, i| m.* = .init(a, &r, s, &l, if (i < 2) .hold else .keep, if (i % 2 == 0) 128 else 16); + defer for (&gdn_windows) |*m| m.deinit(); + for (&gdn_windows) |*m| try kernels.append(a, m.kernel()); var t: g.Tally = .{}; const t0 = ms(io); try g.runAll(a, kernels.items, 0x6b63, &t); diff --git a/zig/tests/hip/contract_prefetch.zig b/zig/tests/hip/contract_prefetch.zig new file mode 100644 index 0000000000..3513bd6a36 --- /dev/null +++ b/zig/tests/hip/contract_prefetch.zig @@ -0,0 +1,101 @@ +//! The MoE down codes' prefetch under the contract on HIP: it reads the live items' experts and writes nothing. +const std = @import("std"); +const hip = @import("hip"); +const core = @import("core"); +const rig_ = @import("contract_rig.zig"); + +const contract = core.contract; +const c = contract.spec; +const g = contract.gates; + +const held = 16; // the experts the codes buffer holds; every live id is below it + +fn none(_: c.Shape) usize { + return 0; +} + +const rule = "no output: every buffer as prepared and every guard intact after each run; with no output it has no " ++ + "float class or bound, so gates 1 and 3 check this, and no sums, so gate 4 has none"; + +/// rows: items; n: experts an id may name; k: 16-byte words of one expert's codes. +pub fn spec() c.Spec { + return .{ + .name = "hip tf_moe_prefetch", + .accum = .none, + .depth = none, + .out = .raw, + .nan = .{ .stated = rule }, + // a decode row's 11 items over Flash Next's 513 experts, each a 4-bit 2560 x 640 down of 51,200 words + .served = &.{.{ .rows = 11, .n = 513, .k = 51200 }}, + }; +} + +/// shape.rows items naming experts below 16 (a dead item and an id past shape.n among them), and their codes. +pub const Prefetch = struct { + rig: rig_.Rig, + l: *const hip.Launcher, + arena: std.heap.ArenaAllocator, + shape: c.Shape = undefined, + in: [2]u64 = @splat(0), + before: []const u8 = &.{}, + msg: [120]u8 = undefined, + + pub fn init(a: std.mem.Allocator, rt: *const hip.Runtime, s: hip.Stream, l: *const hip.Launcher) Prefetch { + return .{ .rig = .{ .a = a, .r = rt, .s = s }, .l = l, .arena = .init(a) }; + } + + pub fn deinit(self: *Prefetch) void { + self.arena.deinit(); + self.rig.deinit(); + } + + pub fn kernel(self: *Prefetch) g.Kernel { + return .{ .spec = spec(), .ctx = self, .vt = &vt }; + } + + const vt = g.hooks(Prefetch); + + pub fn prepare(self: *Prefetch, shape: c.Shape, _: g.Fill, seed: u64) !bool { + if (shape.rows == 0 or shape.n == 0 or shape.k == 0) return false; + self.rig.reset(); + _ = self.arena.reset(.retain_capacity); + self.shape = shape; + const a = self.arena.allocator(); + var prng = std.Random.DefaultPrng.init(seed); + const rng = prng.random(); + const items = try a.alloc(i32, shape.rows * 3); + for (0..shape.rows) |i| { + const id: i32 = @intCast(if (i == 2) shape.n else rng.uintLessThan(usize, @min(held, shape.n))); + items[3 * i ..][0..3].* = .{ id, @intCast(i), @intFromBool(i % 5 != 4) }; + } + const words = try a.alloc(u8, @min(held, shape.n) * shape.k * 16); + rng.bytes(words); + self.in = .{ try self.rig.input(std.mem.sliceAsBytes(items)), try self.rig.input(words) }; + self.before = try a.dupe(u8, try self.rig.inputBytes()); + return true; + } + + /// The engine's cap: every item's expert in full. + pub fn run(self: *Prefetch) !void { + const s = self.shape; + const bytes: i64 = @intCast(s.k * 16); + const items: c_int = @intCast(s.rows); + try self.l.tf_moe_prefetch(@ptrFromInt(self.in[0]), items, self.in[1], bytes, @intCast(s.n), @as(i64, items) * bytes, self.rig.s.handle); + try self.rig.s.synchronize(); + } + + pub fn count(_: *Prefetch) usize { + return 0; + } + + pub fn reference(_: *Prefetch, _: []f64, _: []f64) !void {} + + /// Every input byte as prepared and every guard intact. + pub fn check(self: *Prefetch, _: g.Gate) !?[]const u8 { + const now = try self.rig.inputBytes(); + if (std.mem.indexOfDiff(u8, self.before, now)) |at| + return try std.fmt.bufPrint(&self.msg, "input byte {d} changed", .{at}); + if (!try self.rig.intact()) return "a run wrote outside its buffers"; + return null; + } +}; diff --git a/zig/tests/hip/contract_relu2_pair.zig b/zig/tests/hip/contract_relu2_pair.zig index a17e1aa942..f666a5ee49 100644 --- a/zig/tests/hip/contract_relu2_pair.zig +++ b/zig/tests/hip/contract_relu2_pair.zig @@ -16,12 +16,13 @@ const group = 64; const experts = 8; // the experts the plan's items pick from (a layer has 128; the kernel reads the picked ones) const top_k = 6; /// launches/affine.zig's stream tile constants: columns a lane, row counts, waves a block, waves wanted, code words. -const stream_cbs = [_]c_int{ 2, 4, 8 }; -const stream_rows = [_]u8{ 1, 2, 4 }; -const stream_waves = 4; -const streams_wanted = 3000; -const stream_code_words = 32; -const bit_index = 2; // 4 in launches/affine.zig's bit_widths +const tiles = hip.launches.affine; +const stream_cbs = tiles.stream_cbs; +const stream_rows = tiles.stream_rows; +const stream_waves = tiles.stream_waves; +const streams_wanted = tiles.streams_wanted; +const stream_code_words = tiles.stream_code_words; +const bit_index = std.mem.indexOfScalar(c_int, &tiles.bit_widths, bits).?; fn depth(s: c.Shape) usize { return s.k / 2 + s.k / group + 8; @@ -160,7 +161,7 @@ pub const Pair = struct { while (cbi > 0) { cbi -= 1; const cb = stream_cbs[cbi]; - if (cb * stream_rows[ri] > 16 or cb * a.bits > stream_code_words) continue; + if (cb < 2 or cb * stream_rows[ri] > 16 or cb * a.bits > stream_code_words) continue; pick = cbi; const per: c_int = stream_waves * (@as(c_int, 32) >> lpc_log2) * cb; const waves = @as(u64, cdiv(a.n, per)) * stream_waves * top_k; diff --git a/zig/tests/hip/contract_route.zig b/zig/tests/hip/contract_route.zig new file mode 100644 index 0000000000..f84236f5ef --- /dev/null +++ b/zig/tests/hip/contract_route.zig @@ -0,0 +1,225 @@ +//! A prompt's MoE plan in three launches under the contract on HIP: tf_moe_route's members and items. +const std = @import("std"); +const hip = @import("hip"); +const core = @import("core"); +const rig_ = @import("contract_rig.zig"); + +const contract = core.contract; +const c = contract.spec; +const g = contract.gates; + +const seg = 512; // moe.hpp kRouteSeg: the pairs a block of tf_route_count and tf_route_scatter takes + +fn none(_: c.Shape) usize { + return 0; +} + +const rule = "members: the pairs stably sorted by expert; items: each expert's pairs in tiles, experts in order, " ++ + "then dead items, as tf_moe_route cuts them"; + +/// rows: token rows; n: the plan's experts, the shared one last; k: slots a row. +pub fn spec() c.Spec { + return .{ + .name = "hip tf_route_count, tf_route_scan and tf_route_scatter", + .accum = .none, + .depth = none, + .out = .raw, + .replaces = "tf_moe_route", + .nan = .{ .stated = rule }, + // the rows where the plan's tile goes from 8 pairs to 128 + .tiles = .{ .{ .size = 64 }, .{}, .{} }, + // Flash Next's 512 experts and shared one, top 10: prompt chunks, and the fewest rows the launcher plans here + .served = &.{ + .{ .rows = 2048, .n = 513, .k = 11 }, + .{ .rows = 8192, .n = 513, .k = 11 }, + .{ .rows = 187, .n = 513, .k = 11 }, + }, + }; +} + +/// tf_moe_route's plan of `picks` (each below `experts`) at `tile` pairs an item: members [pairs], items [cap][3]. +pub fn plan(a: std.mem.Allocator, picks: []const i32, experts: usize, tile: usize, cap: usize) !struct { []i32, []i32 } { + const counts = try a.alloc(usize, 3 * experts); + defer a.free(counts); + const starts = counts[experts..][0..experts]; + const ends = counts[2 * experts ..][0..experts]; + @memset(counts[0..experts], 0); + for (picks) |p| counts[@intCast(p)] += 1; + var start: usize = 0; + var end: usize = 0; + for (counts[0..experts], starts, ends) |n, *s, *e| { + s.* = start; + start += n; + end += (n + tile - 1) / tile; + e.* = end; + } + const members = try a.alloc(i32, picks.len); + const placed = try a.alloc(usize, experts); + defer a.free(placed); + @memset(placed, 0); + for (picks, 0..) |p, i| { + const e: usize = @intCast(p); + members[starts[e] + placed[e]] = @intCast(i); + placed[e] += 1; + } + const items = try a.alloc(i32, cap * 3); + const t: i64 = @intCast(tile); + for (0..cap) |slot| { + // searchsorted(ends, slot, right=True); the slots past the live items take the last expert + var lo: usize = 0; + var hi: usize = experts; + while (lo < hi) { + const mid = (lo + hi) / 2; + if (ends[mid] <= slot) lo = mid + 1 else hi = mid; + } + const e = @min(lo, experts - 1); + const reps = (counts[e] + tile - 1) / tile; + const within = @as(i64, @intCast(slot)) - @as(i64, @intCast(ends[e] - reps)); + const left = @as(i64, @intCast(counts[e])) - within * t; + items[3 * slot] = @intCast(e); + items[3 * slot + 1] = @intCast(@as(i64, @intCast(starts[e])) + within * t); + items[3 * slot + 2] = @intCast(std.math.clamp(left, 0, t)); + } + return .{ members, items }; +} + +/// shape.rows rows of shape.k picks over shape.n experts: the plan's members and items in three launches. +pub const Route = struct { + rig: rig_.Rig, + l: *const hip.Launcher, + arena: std.heap.ArenaAllocator, + shape: c.Shape = undefined, + picks: []i32 = &.{}, + tile: usize = 0, + cap: usize = 0, + segs: usize = 0, + in: u64 = 0, + offs: u64 = 0, + out: [2]u64 = @splat(0), + base: [2]u64 = @splat(0), + msg: [160]u8 = undefined, + + pub fn init(a: std.mem.Allocator, rt: *const hip.Runtime, s: hip.Stream, l: *const hip.Launcher) Route { + return .{ .rig = .{ .a = a, .r = rt, .s = s }, .l = l, .arena = .init(a) }; + } + + pub fn deinit(self: *Route) void { + self.arena.deinit(); + self.rig.deinit(); + } + + pub fn kernel(self: *Route) g.Kernel { + return .{ .spec = spec(), .ctx = self, .vt = &vt }; + } + + const vt = g.hooks(Route); + + fn pairs(self: *const Route) usize { + return self.shape.rows * self.shape.k; + } + + /// Routed picks half from 8 hot experts, then the shared expert; the nonfinite gate's from 3, so tiles fill. + pub fn prepare(self: *Route, shape: c.Shape, fill: g.Fill, seed: u64) !bool { + if (shape.rows == 0 or shape.k == 0 or shape.n < 2 or shape.n > 1024) return false; + self.rig.reset(); + _ = self.arena.reset(.retain_capacity); + self.shape = shape; + const a = self.arena.allocator(); + var prng = std.Random.DefaultPrng.init(seed); + const rng = prng.random(); + const experts = shape.n; + const n = self.pairs(); + // moe.zig tileOf: the decode tile below 64 rows, the GEMM tile from there; capacity at the call's pairs + self.tile = if (shape.rows < 64) 8 else 128; + self.cap = @min(n, experts) + n / 8; + self.segs = (n + seg - 1) / seg; + self.picks = try a.alloc(i32, n); + const hot = @min(if (fill == .nonfinite) @as(usize, 3) else 8, experts - 1); + for (self.picks, 0..) |*p, i| { + const from = if (fill == .nonfinite or rng.boolean()) hot else experts - 1; + p.* = @intCast(if (i % shape.k == shape.k - 1) experts - 1 else rng.uintLessThan(usize, from)); + } + self.in = try self.rig.input(std.mem.sliceAsBytes(self.picks)); + self.offs = try self.rig.scratch((self.segs + 1) * experts * 4); + const lens = [2]usize{ n * 4, self.cap * 12 }; + for (&self.out, &self.base, lens) |*o, *b, len| { + o.* = try self.rig.output(len); + b.* = try self.rig.scratch(len); + const poison = try a.alloc(u8, len); + @memset(poison, 0xff); // as the outputs start + try self.rig.put(b.*, poison); + } + return true; + } + + pub fn run(self: *Route) !void { + const op = &self.l.op; + const experts: c_int = @intCast(self.shape.n); + const segs: c_int = @intCast(self.segs); + const n: c_int = @intCast(self.pairs()); + const blocks: hip.launch.Dim3 = .{ .x = @intCast(self.segs) }; + var a: hip.launch.Args = .{}; + try a.add(self.in); + for ([_]c_int{ n, experts }) |v| try a.add(v); + try a.add(self.offs); + try hip.launch.launch(op.route_count, .{ .grid = blocks, .block = .{ .x = 256 } }, self.rig.s, &a); + var b: hip.launch.Args = .{}; + try b.add(self.offs); + for ([_]c_int{ segs, experts, @intCast(self.tile) }) |v| try b.add(v); + try b.add(self.out[1]); + try b.add(@as(c_int, @intCast(self.cap))); + try hip.launch.launch(op.route_scan, .{ .grid = .{ .x = 1 }, .block = .{ .x = 1024 } }, self.rig.s, &b); + var d: hip.launch.Args = .{}; + try d.add(self.in); + for ([_]c_int{ n, segs, experts }) |v| try d.add(v); + try d.add(self.offs); + try d.add(self.out[0]); + try hip.launch.launch(op.route_scatter, .{ .grid = blocks, .block = .{ .x = seg } }, self.rig.s, &d); + try self.rig.s.synchronize(); + } + + /// Members then items at two device addresses, on the host. + fn both(self: *Route, at: [2]u64) ![]const u8 { + const a = self.arena.allocator(); + const members = try a.dupe(u8, try self.rig.bytes(at[0], self.pairs() * 4)); + return std.mem.concat(a, u8, &.{ members, try self.rig.bytes(at[1], self.cap * 12) }); + } + + /// tf_moe_route's one block on the same picks. + pub fn replaced(self: *Route) ![]const u8 { + const s = self.shape; + try self.l.tf_moe_route( + @ptrFromInt(self.in), + @intCast(self.pairs()), + @intCast(s.n), + @intCast(self.tile), + @ptrFromInt(self.base[0]), + @ptrFromInt(self.base[1]), + @intCast(self.cap), + self.rig.s.handle, + ); + return self.both(self.base); + } + + pub fn count(self: *Route) usize { + return self.pairs() * 4 + self.cap * 12; + } + + pub fn reference(_: *Route, want: []f64, mag: []f64) !void { + @memset(want, 0); + @memset(mag, 0); + } + + /// The members and items against the rule's plan of the same picks, byte for byte. + pub fn check(self: *Route, _: g.Gate) !?[]const u8 { + const a = self.arena.allocator(); + const members, const items = try plan(a, self.picks, self.shape.n, self.tile, self.cap); + const want = try std.mem.concat(a, u8, &.{ std.mem.sliceAsBytes(members), std.mem.sliceAsBytes(items) }); + const got = try self.both(self.out); + const at = std.mem.indexOfDiff(u8, got, want) orelse return null; + const m = members.len * 4; + const what = if (at < m) "member" else "item field"; + const i = if (at < m) at / 4 else (at - m) / 4; + return try std.fmt.bufPrint(&self.msg, "{s} {d} differs from the rule's plan", .{ what, i }); + } +}; diff --git a/zig/tests/hip/contract_select.zig b/zig/tests/hip/contract_select.zig new file mode 100644 index 0000000000..d4602a7970 --- /dev/null +++ b/zig/tests/hip/contract_select.zig @@ -0,0 +1,444 @@ +//! The MoE pick under the contract on HIP: a prompt's picks a wave a row, and the router, pick and plan in one launch. +const std = @import("std"); +const hip = @import("hip"); +const core = @import("core"); +const rig_ = @import("contract_rig.zig"); +const kit = @import("contract_kit.zig"); +const route = @import("contract_route.zig"); + +const contract = core.contract; +const c = contract.spec; +const g = contract.gates; +const rows_ = contract.rows; + +pub const Which = enum { rows, router }; + +const top_k = 10; // Flash Next's routed picks a row; its shared expert takes the slot after them +const slots = top_k + 1; +const tile = 8; // moe.zig tileOf: a verify window's plan tile +const waves = 4; // decode.hip kRouterWaves: rows a block of tf_select_rows + +fn none(_: c.Shape) usize { + return 0; +} + +/// A lane's fma chain over a d / 32 slice of the dot, then the wave's 5 shuffle adds. +fn chain(s: c.Shape) usize { + return s.k / 32 + 5; +} + +/// moe.zig capacity(bucket(rows) * slots, e): a decode call's items, 16 rows' worth. +fn capacity(e: usize) usize { + return @min(16 * slots, e) + 16 * slots / 8; +} + +const pick_rule = "every slot of every row written: the top k logits, larger first, equal ones to the lower id, a NaN " ++ + "below every number; weights the softmax of the picks (NaN where a NaN or inf - inf enters) within bf16's half " ++ + "ulp and 2 (k + 8) fp32 ulps of float64; the shared slot sigmoid(bf16(gate))"; +const select_known = "select_body (upstream): a NaN shares rank 0 with the top number (slot 0 races) and a row with " ++ + "fewer than k numbers leaves slots unwritten; bytes kept equal to upstream's"; +const router_rule = "logits in float64's classes; picks and weights by tf_select_rows' rule; the plan tf_moe_route's " ++ + "of the picks (one row: an item a slot)"; +const router_names = [2][]const u8{ "hip tf_router_select_f16", "hip tf_router_select_bf16" }; + +pub fn spec(which: Which, k: kit.Kind) c.Spec { + return switch (which) { + .rows => .{ + .name = "hip tf_select_rows", + .accum = .none, + .depth = none, + .out = .raw, + .replaces = "tf_select_decode (select_body)", + .nan = .{ .stated = pick_rule }, + .known = .{ .gate = .nonfinite, .finding = select_known }, + // a block's 4 rows; select_row_lanes' 16 logits a lane to 512 experts + .tiles = .{ .{ .size = waves }, .{ .size = 512, .min = 16 }, .{} }, + // Flash Next's 512 experts, top 10: a one-row prompt and a prompt chunk + .served = &.{ + .{ .rows = 1, .n = 512, .k = top_k }, + .{ .rows = 2048, .n = 512, .k = top_k }, + }, + }, + .router => .{ + .name = router_names[@intFromBool(k == .bf16)], + .accum = .f32, + .depth = chain, + // the logits, its first output: gate 4 reads them; gate 3 compares every output's bytes + .out = .f32, + .replaces = "tf_router_decode, tf_select_decode or tf_select_rows, then tf_moe_route", + .nan = .{ .stated = router_rule }, + .known = .{ .gate = .nonfinite, .finding = select_known }, + .tiles = .{ .{ .size = waves }, .{}, .{} }, + // Flash Next's 512 experts and shared gate over 2560 wide rows: a decode row, a verify window, 16 rows + .served = &.{ + .{ .rows = 1, .n = 513, .k = 2560 }, + .{ .rows = 8, .n = 513, .k = 2560 }, + .{ .rows = 16, .n = 513, .k = 2560 }, + }, + }, + }; +} + +fn say(msg: []u8, comptime fmt: []const u8, args: anytype) !?[]const u8 { + return try std.fmt.bufPrint(msg, fmt, args); +} + +fn word(b: []const u8, i: usize) i32 { + return std.mem.readInt(i32, b[4 * i ..][0..4], .little); +} + +/// A weight within bf16's half ulp of a value within 2 (k + 8) fp32 ulps of float64; classes equal. +fn close(got: f64, want: f64, k: usize) bool { + if (std.math.isNan(got) or std.math.isNan(want)) return std.math.isNan(got) and std.math.isNan(want); + if (got == want) return true; + const tol = (0x1p-8 + 2 * @as(f64, @floatFromInt(k + 8)) * 0x1p-23) * @abs(want) + 0x1p-120; + return @abs(got - want) <= tol; +} + +/// The pick rule over one call's logits [rows][experts + 1] (the gate's last): null when every row keeps it. +fn pickRule(msg: []u8, a: std.mem.Allocator, logits: []const f64, rows: usize, experts: usize, k: usize, ids: []const u8, wts: []const u8) !?[]const u8 { + const order = try a.alloc(usize, experts); + const want = try a.alloc(f64, k); + const By = struct { + fn ahead(v: []const f64, x: usize, y: usize) bool { + const nx = std.math.isNan(v[x]); + const ny = std.math.isNan(v[y]); + if (nx or ny) return if (nx and ny) x < y else ny; + return v[x] > v[y] or (v[x] == v[y] and x < y); + } + }; + for (0..rows) |r| { + const row = logits[r * (experts + 1) ..][0 .. experts + 1]; + for (order, 0..) |*v, i| v.* = i; + std.sort.pdq(usize, order, row, By.ahead); + const at = r * (k + 1); + for (0..k) |j| { + const id = word(ids, at + j); + if (id != @as(i32, @intCast(order[j]))) + return say(msg, "row {d} slot {d} holds expert {d}, the rule gives {d}", .{ r, j, id, order[j] }); + } + if (word(ids, at + k) != @as(i32, @intCast(experts))) + return say(msg, "row {d}: the shared slot is not expert {d}", .{ r, experts }); + var total: f64 = 0; + for (want, order[0..k]) |*w, i| { + w.* = @exp(row[i] - row[order[0]]); + total += w.*; + } + for (want, 0..) |w, j| { + const got = c.read(.f32, wts, at + j); + if (!close(got, w / total, k)) + return say(msg, "row {d} slot {d}: weight {e:.6}, float64 {e:.6}", .{ r, j, got, w / total }); + } + const gate = kit.round(.bf16, row[experts]); + const shared = c.read(.f32, wts, at + k); + if (!close(shared, 1 / (1 + @exp(-gate)), 1)) + return say(msg, "row {d}: shared weight {e:.6} for gate {e:.6}", .{ r, shared, gate }); + } + return null; +} + +/// NaN, both infinities and tied +Inf among a call's logits [rows][experts + 1], and a row of fewer than k numbers. +fn plantLogits(x: []f64, rows: usize, experts: usize, k: usize) void { + const nan = std.math.nan(f64); + const inf = std.math.inf(f64); + const at = [_][2]usize{ .{ 0, 7 }, .{ 1, 5 }, .{ 1, 6 }, .{ 2, 3 }, .{ 3, 1 }, .{ 3, 2 }, .{ 3, 9 }, .{ 4, experts }, .{ 4, 0 }, .{ 4, 11 } }; + const put = [_]f64{ nan, inf, inf, -inf, inf, -inf, nan, nan, nan, nan }; + for (at, put) |p, v| if (p[0] < rows) { + x[p[0] * (experts + 1) + p[1]] = v; + }; + if (rows > 4) for (x[4 * (experts + 1) + k / 2 ..][0 .. experts - k / 2]) |*v| { + v.* = nan; + }; +} + +/// Infinities in router rows, x's sign or 0 there by row: NaN logits, both infinities, a row of 5 numbers. +fn plantRouter(x: []f64, w: []f64, rows: usize, e: usize, d: usize) void { + const inf = std.math.inf(f64); + w[d] = inf; + w[2 * d] = -inf; + w[3 * d] = inf; + w[3 * d + 4] = -inf; + w[(e - 1) * d + 4] = inf; + for (8..e - 1) |j| w[j * d + 8] = inf; + const signs = [5][2]f64{ .{ 0.5, 0.5 }, .{ -0.5, 0.5 }, .{ 0.5, -0.5 }, .{ 0, 0.5 }, .{ 0.5, 0 } }; + for (0..rows) |r| { + x[r * d] = signs[r % 5][0]; + x[r * d + 4] = signs[r % 5][1]; + x[r * d + 8] = if (r % 5 == 3) 0 else 0.5; + } +} + +/// tf_select_rows on fp32 logits, or tf_router_select on x of the kind and bf16 router rows; both check the rule. +pub const Select = struct { + rig: rig_.Rig, + which: Which, + l: *const hip.Launcher, + k: kit.Kind, + arena: std.heap.ArenaAllocator, + shape: c.Shape = undefined, + x: []f64 = &.{}, // the logits [rows][experts + 1], or x [rows][d] + w: []f64 = &.{}, // the router's rows [e][d] + in: [3]u64 = @splat(0), + out: [5]u64 = @splat(0), + base: [5]u64 = @splat(0), + lens: [5]usize = @splat(0), + outs: usize = 0, + done: u64 = 0, + msg: [200]u8 = undefined, + + pub fn init(a: std.mem.Allocator, rt: *const hip.Runtime, s: hip.Stream, l: *const hip.Launcher, w: Which) Select { + return .{ .rig = .{ .a = a, .r = rt, .s = s }, .which = w, .l = l, .k = kit.act(), .arena = .init(a) }; + } + + pub fn deinit(self: *Select) void { + self.arena.deinit(); + self.rig.deinit(); + } + + pub fn kernel(self: *Select) g.Kernel { + return .{ .spec = spec(self.which, self.k), .ctx = self, .vt = &vt }; + } + + const vt = g.hooks(Select); + + pub fn prepare(self: *Select, shape: c.Shape, fill: g.Fill, seed: u64) !bool { + const s = shape; + if (s.rows == 0) return false; + switch (self.which) { + .rows => if (s.n < 12 or s.n > 1024 or s.k == 0 or s.k > 31 or s.k > s.n) return false, + .router => if (s.rows > 16 or s.n < top_k + 2 or s.n > 1025 or s.k < 16 or s.k % 4 != 0) return false, + } + self.rig.reset(); + _ = self.arena.reset(.retain_capacity); + self.shape = s; + var prng = std.Random.DefaultPrng.init(seed); + const rng = prng.random(); + switch (self.which) { + .rows => try self.prepareRows(rng, fill), + .router => try self.prepareRouter(rng, fill), + } + const a = self.arena.allocator(); + for (self.out[0..self.outs], self.base[0..self.outs], self.lens[0..self.outs]) |*o, *b, len| { + o.* = try self.rig.output(len); + b.* = try self.rig.scratch(len); + const poison = try a.alloc(u8, len); + @memset(poison, 0xff); // as the outputs start + try self.rig.put(b.*, poison); + } + return true; + } + + /// Logits in sixteenths, so equal logits are common; the gate's logit last in each row. + fn prepareRows(self: *Select, rng: std.Random, fill: g.Fill) !void { + const a = self.arena.allocator(); + const s = self.shape; + self.x = try a.alloc(f64, s.rows * (s.n + 1)); + for (self.x) |*v| v.* = @as(f64, @floatFromInt(rng.uintLessThan(u32, 64))) / 16 - 2; + if (fill == .nonfinite) plantLogits(self.x, s.rows, s.n, s.k); + self.in[0] = try self.rig.input(try kit.f32Bytes(a, self.x)); + const picks = s.rows * (s.k + 1) * 4; + self.lens = .{ picks, picks, 0, 0, 0 }; + self.outs = 2; + } + + /// x in [-1, 1) and router rows in [-1/8, 1/8), three rows equal to expert 0's; gate 4: mirrored integers. + fn prepareRouter(self: *Select, rng: std.Random, fill: g.Fill) !void { + const a = self.arena.allocator(); + const s = self.shape; + const e = s.n; + const d = s.k; + self.x = try a.alloc(f64, s.rows * d); + self.w = try a.alloc(f64, e * d); + if (fill == .stress) { + // the second half undoes the first, but for one: every fp32 partial sum exact, each logit small + const h = d / 2; + for (0..s.rows) |r| for (0..h) |i| { + const v: f64 = @floatFromInt(1 + rng.uintLessThan(u32, 57)); + self.x[r * d + i] = v; + self.x[r * d + h + i] = v; + }; + for (0..e) |j| { + for (0..h) |i| { + const v: f64 = @floatFromInt(1 + rng.uintLessThan(u32, 57)); + self.w[j * d + i] = v; + self.w[j * d + h + i] = -v; + } + self.w[j * d + h] += 1; + } + } else { + for (self.x) |*v| { + v.* = kit.round(self.k, rng.float(f64) * 2 - 1); + if (self.k == .f16 and @abs(v.*) < 0x1p-14) v.* = 0; // fp16 normals only, as kit.values gives + } + for (self.w) |*v| v.* = kit.round(.bf16, rng.float(f64) / 4 - 0.125); + for ([_]usize{ 3, 9, e / 2 }) |j| if (j < e - 1) @memcpy(self.w[j * d ..][0..d], self.w[0..d]); + if (fill == .nonfinite) plantRouter(self.x, self.w, s.rows, e, d); + } + const xb = try a.alloc(u8, self.x.len * 2); + for (self.x, 0..) |v, i| kit.put(self.k, xb, i, v); + const w16 = try a.alloc(u8, self.w.len * 2); + for (self.w, 0..) |v, i| kit.put(.bf16, w16, i, v); + self.in = .{ try self.rig.input(xb), try self.rig.input(w16), try self.rig.input(try kit.f32Bytes(a, self.w)) }; + self.done = try self.rig.scratch(4); + const picks = s.rows * slots * 4; + self.lens = .{ s.rows * e * 4, picks, picks, capacity(e) * 12, picks }; + self.outs = if (s.rows <= 8) 5 else 3; + } + + /// tf_select_rows (4 rows a block), or with `body` select_body's block a row with no plan (tf_select_decode). + fn launchPick(self: *Select, body: bool, out: [5]u64) !void { + const s = self.shape; + var a: hip.launch.Args = .{}; + for ([_]u64{ self.in[0], out[0], out[1] }) |v| try a.add(v); + const n: c_int = @intCast(s.n); + const k: c_int = @intCast(s.k); + const rows: u32 = @intCast(s.rows); + if (body) { + for ([_]u64{ 0, 0 }) |v| try a.add(v); + for ([_]c_int{ 0, n, k }) |v| try a.add(v); + const cfg: hip.launch.Config = .{ .grid = .{ .x = rows }, .block = .{ .x = 512 } }; + return hip.launch.launch(self.l.dec.select, cfg, self.rig.s, &a); + } + for ([_]c_int{ @intCast(s.rows), n, k }) |v| try a.add(v); + const cfg: hip.launch.Config = .{ .grid = .{ .x = (rows + waves - 1) / waves }, .block = .{ .x = 32 * waves } }; + try hip.launch.launch(self.l.dec.select_rows, cfg, self.rig.s, &a); + } + + pub fn run(self: *Select) !void { + const s = self.shape; + switch (self.which) { + .rows => try self.launchPick(false, self.out), + .router => { + const planned = self.outs == 5; + const items: ?[*]i32 = if (planned) @ptrFromInt(self.out[3]) else null; + const members: ?[*]i32 = if (planned) @ptrFromInt(self.out[4]) else null; + const ran = try self.l.routerSelect( + @ptrFromInt(self.in[0]), + @backingInt(self.k), + @ptrFromInt(self.in[1]), + @ptrFromInt(self.out[0]), + @ptrFromInt(self.out[1]), + @ptrFromInt(self.out[2]), + items, + members, + @intCast(capacity(s.n)), + @intCast(s.rows), + @intCast(s.k), + @intCast(s.n), + top_k, + @as(c_int, if (s.rows == 1) 0 else tile), + self.done, + self.rig.s.handle, + ); + if (!ran) return error.RouterSelectRefused; + }, + } + try self.rig.s.synchronize(); + } + + /// tf_router_decode on the rows widened to fp32, the pick (one row: select_body with its plan), then tf_moe_route. + fn routerBaseline(self: *Select) !void { + const s = self.shape; + const b = self.base; + const h = self.rig.s.handle; + const one = s.rows == 1; + const cap: c_int = @intCast(capacity(s.n)); + const items: ?[*]i32 = if (one) @ptrFromInt(b[3]) else null; + const members: ?[*]i32 = if (one) @ptrFromInt(b[4]) else null; + const r: c_int = @intCast(s.rows); + const e: c_int = @intCast(s.n); + try self.l.tf_moe_router(@ptrFromInt(self.in[0]), @backingInt(self.k), @ptrFromInt(self.in[2]), @ptrFromInt(b[0]), r, @intCast(s.k), e, h); + try self.l.tf_moe_select(@ptrFromInt(b[0]), @ptrFromInt(b[1]), @ptrFromInt(b[2]), items, members, cap, r, e - 1, top_k, h); + if (self.outs == 5 and !one) try self.l.tf_moe_route(@ptrFromInt(b[1]), r * slots, e, tile, @ptrFromInt(b[4]), @ptrFromInt(b[3]), cap, h); + } + + /// The launches it replaces on the same inputs, every output's bytes in order. + pub fn replaced(self: *Select) ![]const u8 { + switch (self.which) { + .rows => try self.launchPick(true, self.base), + .router => try self.routerBaseline(), + } + const a = self.arena.allocator(); + var all: std.ArrayList(u8) = .empty; + for (self.base[0..self.outs], self.lens[0..self.outs]) |at, len| try all.appendSlice(a, try self.rig.bytes(at, len)); + return all.items; + } + + pub fn count(self: *Select) usize { + const s = self.shape; + return if (self.which == .router) s.rows * s.n else self.lens[0] + self.lens[1]; + } + + pub fn reference(self: *Select, want: []f64, mag: []f64) !void { + @memset(want, 0); + @memset(mag, 0); + if (self.which == .rows) return; + const s = self.shape; + for (0..s.rows) |r| for (0..s.n) |j| { + const at = r * s.n + j; + for (self.x[r * s.k ..][0..s.k], self.w[j * s.k ..][0..s.k]) |x, w| { + want[at] += x * w; + mag[at] += @abs(x * w); + } + }; + } + + /// The router's dots in an accumulator and order (gate 4). + pub fn simulate(self: *Select, acc: c.Accum, order: g.Order, out: []f64) !void { + const s = self.shape; + const t = try self.arena.allocator().alloc(f64, s.k); + for (0..s.rows) |r| for (0..s.n) |j| { + for (t, self.x[r * s.k ..][0..s.k], self.w[j * s.k ..][0..s.k]) |*v, x, w| v.* = x * w; + out[r * s.n + j] = rows_.sumIn(acc, order, t); + }; + } + + /// The pick rule on the logits it read, or wrote (the router: classes against float64), then the plan. + pub fn check(self: *Select, _: g.Gate) !?[]const u8 { + const a = self.arena.allocator(); + const s = self.shape; + const first: usize = if (self.which == .rows) 0 else 1; // the router's logits come first + const ids = try a.dupe(u8, try self.rig.bytes(self.out[first], self.lens[1])); + const wts = try a.dupe(u8, try self.rig.bytes(self.out[first + 1], self.lens[1])); + if (self.which == .rows) return pickRule(&self.msg, a, self.x, s.rows, s.n, s.k, ids, wts); + const n = s.rows * s.n; + const want = try a.alloc(f64, 2 * n); + try self.reference(want[0..n], want[n..]); + const raw = try self.rig.bytes(self.out[0], n * 4); + const logits = try a.alloc(f64, n); + for (logits, want[0..n], 0..) |*v, f, i| { + v.* = c.read(.f32, raw, i); + if (c.classOf(v.*) != c.classOf(f)) + return say(&self.msg, "logit {d} is {t} where float64 gives {t}", .{ i, c.classOf(v.*), c.classOf(f) }); + } + if (try pickRule(&self.msg, a, logits, s.rows, s.n - 1, top_k, ids, wts)) |why| return why; + return if (self.outs == 5) self.checkPlan(ids) else null; + } + + /// One row: an item a slot (expert, slot, 1) and dead items after; more: tf_moe_route's plan of the picks. + fn checkPlan(self: *Select, ids: []const u8) !?[]const u8 { + const a = self.arena.allocator(); + const s = self.shape; + const cap = capacity(s.n); + const picks = try a.alloc(i32, s.rows * slots); + for (picks, 0..) |*p, i| p.* = word(ids, i); + var members: []i32 = undefined; + var items: []i32 = undefined; + if (s.rows == 1) { + items = try a.alloc(i32, cap * 3); + @memset(items, 0); + members = try a.alloc(i32, slots); + for (0..slots) |k| { + items[3 * k ..][0..3].* = .{ picks[k], @intCast(k), 1 }; + members[k] = @intCast(k); + } + } else { + members, items = try route.plan(a, picks, s.n, tile, cap); + } + if (!std.mem.eql(u8, try self.rig.bytes(self.out[3], cap * 12), std.mem.sliceAsBytes(items))) + return say(&self.msg, "the plan's items differ from the rule's ({d} rows)", .{s.rows}); + if (!std.mem.eql(u8, try self.rig.bytes(self.out[4], picks.len * 4), std.mem.sliceAsBytes(members))) + return say(&self.msg, "the plan's members differ from the rule's ({d} rows)", .{s.rows}); + return null; + } +}; diff --git a/zig/tests/hip/contract_topk.zig b/zig/tests/hip/contract_topk.zig new file mode 100644 index 0000000000..c72b416ee1 --- /dev/null +++ b/zig/tests/hip/contract_topk.zig @@ -0,0 +1,223 @@ +//! The top-k of a wide logits row in parts under the contract on HIP: tf_topk's ids, values and order. +const std = @import("std"); +const hip = @import("hip"); +const core = @import("core"); +const rig_ = @import("contract_rig.zig"); +const kit = @import("contract_kit.zig"); + +const contract = core.contract; +const c = contract.spec; +const g = contract.gates; + +const part_least = 4096; // ops/draw.zig part_topk: the values a part takes at least +const most_parts = 64; // ops/draw.zig max_topk_parts +const join_most = 4096; // draw.hpp kJoinMost: the candidates a row's join holds + +fn none(_: c.Shape) usize { + return 0; +} + +const names = [2][]const u8{ + "hip tf_topk_part and tf_topk_join (fp16)", + "hip tf_topk_part and tf_topk_join (bf16)", +}; +const rule = "each row's ks[r] largest by a 16-bit key of the value's bits (-0 equal to +0, a positive NaN above " ++ + "+Inf, a negative NaN below -Inf), ties to the lower id, as ids and the values' bits; no slot past ks[r] written"; + +/// rows: logits rows; n: values a row; k: the stride, the most any row takes. +pub fn spec(k: kit.Kind) c.Spec { + return .{ + .name = names[@intFromBool(k == .bf16)], + .accum = .none, + .depth = none, + .out = .raw, + .replaces = "tf_topk", + .nan = .{ .stated = rule }, + // the narrowest row ops.topkRows takes in parts + .tiles = .{ .{}, .{ .size = 2 * part_least, .min = 2 * part_least }, .{} }, + // a row and a window of rows over Flash Next's 248,320 logits, and the narrowest row the parts take + .served = &.{ + .{ .rows = 1, .n = 248320, .k = 64 }, + .{ .rows = 4, .n = 248320, .k = 64 }, + .{ .rows = 4, .n = 2 * part_least, .k = 64 }, + }, + }; +} + +/// draw.hpp order_key: monotone in the value, -0 and +0 one key, NaNs past the infinities by their sign. +fn key(bits: u16) u32 { + const b: u32 = if (bits == 0x8000) 0 else bits; + return if (b & 0x8000 != 0) ~b & 0xffff else b | 0x8000; +} + +/// shape.rows rows of shape.n 16-bit logits: each row's ks[r] largest as ids and values, shape.k slots apart. +pub const Topk = struct { + rig: rig_.Rig, + l: *const hip.Launcher, + k: kit.Kind, + arena: std.heap.ArenaAllocator, + shape: c.Shape = undefined, + bits: []u16 = &.{}, + ks: []i32 = &.{}, + parts: usize = 0, + per: usize = 0, + in: [2]u64 = @splat(0), + cand: [2]u64 = @splat(0), + out: [2]u64 = @splat(0), + base: [2]u64 = @splat(0), + msg: [160]u8 = undefined, + + pub fn init(a: std.mem.Allocator, rt: *const hip.Runtime, s: hip.Stream, l: *const hip.Launcher) Topk { + return .{ .rig = .{ .a = a, .r = rt, .s = s }, .l = l, .k = kit.act(), .arena = .init(a) }; + } + + pub fn deinit(self: *Topk) void { + self.arena.deinit(); + self.rig.deinit(); + } + + pub fn kernel(self: *Topk) g.Kernel { + return .{ .spec = spec(self.k), .ctx = self, .vt = &vt }; + } + + const vt = g.hooks(Topk); + + /// Values in eighths, so ties are common; ks cycle 28, 1, 0 and the stride; non-finite: NaNs, infinities, zeros. + pub fn prepare(self: *Topk, shape: c.Shape, fill: g.Fill, seed: u64) !bool { + if (shape.rows == 0 or shape.n < 16 or shape.k == 0) return false; + // ops.topkRows' parts of a row + const parts = @min(most_parts, (shape.n + part_least - 1) / part_least); + if (parts * shape.k > join_most) return false; + self.rig.reset(); + _ = self.arena.reset(.retain_capacity); + self.shape = shape; + self.parts = parts; + self.per = (shape.n + parts - 1) / parts; + const a = self.arena.allocator(); + var prng = std.Random.DefaultPrng.init(seed); + const rng = prng.random(); + const n = shape.rows * shape.n; + const b = try a.alloc(u8, n * 2); + for (0..n) |i| kit.put(self.k, b, i, @as(f64, @floatFromInt(rng.uintLessThan(u32, 256))) / 8 - 16); + self.bits = try a.alloc(u16, n); + for (self.bits, 0..) |*v, i| v.* = std.mem.readInt(u16, b[2 * i ..][0..2], .little); + if (fill == .nonfinite) { + const nan: u16 = if (self.k == .bf16) 0x7fc0 else 0x7e00; + const inf: u16 = if (self.k == .bf16) 0x7f80 else 0x7c00; + const at = [_][2]usize{ + .{ 0, shape.n / 3 }, .{ 0, shape.n - 1 }, .{ 1, shape.n / 2 }, .{ 1, 5 }, .{ 2, 0 }, + .{ 2, 9 }, .{ 2, 10 }, .{ 3, 7 }, .{ 3, 8 }, .{ 4, 1 }, + .{ 4, 2 }, + }; + const put = [_]u16{ nan, nan, inf, nan | 0x8000, inf | 0x8000, 0x8000, 0, inf, inf, nan | 0x8000, nan }; + for (at, put) |p, v| if (p[0] < shape.rows) { + self.bits[p[0] * shape.n + p[1]] = v; + }; + } + self.ks = try a.alloc(i32, shape.rows); + const cycle = [_]usize{ 28, 1, 0, shape.k }; + for (self.ks, 0..) |*v, r| v.* = @intCast(@min(cycle[r % 4], shape.k, shape.n)); + self.in = .{ + try self.rig.input(std.mem.sliceAsBytes(self.bits)), + try self.rig.input(std.mem.sliceAsBytes(self.ks)), + }; + const cands = shape.rows * parts * shape.k; + self.cand = .{ try self.rig.scratch(cands * 4), try self.rig.scratch(cands * 2) }; + const lens = [2]usize{ shape.rows * shape.k * 4, shape.rows * shape.k * 2 }; + for (&self.out, &self.base, lens) |*o, *base, len| { + o.* = try self.rig.output(len); + base.* = try self.rig.scratch(len); + const poison = try a.alloc(u8, len); + @memset(poison, 0xff); // as the outputs start, so a slot neither writes compares equal + try self.rig.put(base.*, poison); + } + return true; + } + + pub fn run(self: *Topk) !void { + const s = self.shape; + try self.l.tf_topk_parts( + @ptrFromInt(self.in[0]), + @intCast(s.rows), + @intCast(s.n), + @ptrFromInt(self.in[1]), + @intCast(s.k), + @intCast(self.per), + @intCast(self.parts), + @ptrFromInt(self.cand[0]), + @ptrFromInt(self.cand[1]), + @ptrFromInt(self.out[0]), + @ptrFromInt(self.out[1]), + self.rig.s.handle, + ); + try self.rig.s.synchronize(); + } + + /// Ids then values at two device addresses, on the host. + fn both(self: *Topk, at: [2]u64) ![]const u8 { + const a = self.arena.allocator(); + const s = self.shape; + const ids = try a.dupe(u8, try self.rig.bytes(at[0], s.rows * s.k * 4)); + return std.mem.concat(a, u8, &.{ ids, try self.rig.bytes(at[1], s.rows * s.k * 2) }); + } + + /// tf_topk's one block a row on the same rows. + pub fn replaced(self: *Topk) ![]const u8 { + const s = self.shape; + try self.l.tf_topk_rows( + @ptrFromInt(self.in[0]), + @intCast(s.rows), + @intCast(s.n), + @ptrFromInt(self.in[1]), + @intCast(s.k), + @ptrFromInt(self.base[0]), + @ptrFromInt(self.base[1]), + self.rig.s.handle, + ); + return self.both(self.base); + } + + pub fn count(self: *Topk) usize { + return self.shape.rows * self.shape.k * 6; + } + + pub fn reference(_: *Topk, want: []f64, mag: []f64) !void { + @memset(want, 0); + @memset(mag, 0); + } + + /// Each row's slots against the rule over the row's bits; the slots past ks[r] keep their poison. + pub fn check(self: *Topk, _: g.Gate) !?[]const u8 { + const a = self.arena.allocator(); + const s = self.shape; + const got = try self.both(self.out); + const vals = got[s.rows * s.k * 4 ..]; + const order = try a.alloc(u32, s.n); + const By = struct { + fn ahead(row: []const u16, x: u32, y: u32) bool { + const kx = key(row[x]); + const ky = key(row[y]); + return kx > ky or (kx == ky and x < y); + } + }; + for (0..s.rows) |r| { + const row: []const u16 = self.bits[r * s.n ..][0..s.n]; + for (order, 0..) |*v, i| v.* = @intCast(i); + std.sort.pdq(u32, order, row, By.ahead); + const k: usize = @intCast(self.ks[r]); + for (0..s.k) |j| { + const at = r * s.k + j; + const id = std.mem.readInt(i32, got[4 * at ..][0..4], .little); + const v = std.mem.readInt(u16, vals[2 * at ..][0..2], .little); + const want_id: i32 = if (j < k) @intCast(order[j]) else -1; + const want_v: u16 = if (j < k) row[order[j]] else 0xffff; + if (id != want_id or v != want_v) return try std.fmt.bufPrint( + &self.msg, + "row {d} slot {d} holds {d} (0x{x:0>4}), the rule gives {d} (0x{x:0>4})", + .{ r, j, id, v, want_id, want_v }, + ); + } + } + return null; + } +}; diff --git a/zig/tests/hip/contract_wmma_dense.zig b/zig/tests/hip/contract_wmma_dense.zig new file mode 100644 index 0000000000..3284b17bc2 --- /dev/null +++ b/zig/tests/hip/contract_wmma_dense.zig @@ -0,0 +1,167 @@ +//! The gfx11 matrix-core dense tile of a prompt under the contract on HIP: affine_wmma_gemm's bytes at each K. +const std = @import("std"); +const hip = @import("hip"); +const core = @import("core"); +const rig_ = @import("contract_rig.zig"); +const kit = @import("contract_kit.zig"); + +const contract = core.contract; +const c = contract.spec; +const g = contract.gates; +const Affine = contract.affine.Affine; +const tiles = hip.launches.affine; +pub const Arg = tiles.Arg; + +/// Flash Next's trunk products: 4-bit codes in groups of 32, bf16 x and tables. +pub const bits = 4; +pub const group = 32; + +/// A K the tile compiles, its output (bf16 at out16 as tf_cast rounds, else fp32) and the engine's (rows, n) at it. +pub const Case = struct { k: usize, half: bool, name: []const u8, served: []const c.Shape }; + +const ks = [_]struct { usize, []const c.Shape }{ + // hc up: the 4 streams' 2,560 columns from 320 + .{ 320, &.{.{ .rows = 383, .n = 10240, .k = 320 }} }, + .{ 2560, &.{.{ .rows = 300, .n = 640, .k = 2560 }} }, + .{ 6144, &.{.{ .rows = 257, .n = 2560, .k = 6144 }} }, + // hc down: 320 columns, and 324 with the 4 stream injections + .{ 10240, &.{ .{ .rows = 200, .n = 324, .k = 10240 }, .{ .rows = 200, .n = 320, .k = 10240 } } }, +}; + +pub const cases = blk: { + var out: [2 * ks.len]Case = undefined; + for (ks, 0..) |e, i| { + for ([_]bool{ false, true }, 0..) |half, h| { + const say = "hip affine_wmma_dense<{d}> (4-bit, group 32, {s} out)"; + out[2 * i + h] = .{ .k = e[0], .half = half, .served = e[1], .name = std.fmt.comptimePrint(say, .{ e[0], if (half) "bf16" else "fp32" }) }; + } + } + break :blk out; +}; + +/// A group's 16 dot2 steps from zero (2 u each: an ulp of the step's largest addend), then its scale and bias fmas. +fn depth(s: c.Shape) usize { + return 2 * 16 + 2 * (s.k / group) + 8; +} + +pub fn spec(cfg: Case) c.Spec { + return .{ + .name = cfg.name, + .accum = .f32, + .depth = depth, + .out = if (cfg.half) .bf16 else .f32, + .replaces = if (cfg.half) "affine_wmma_gemm then tf_cast" else "affine_wmma_gemm", + // the registry takes it from 33 rows (the K-parallel tiles below) and one full column tile + .tiles = .{ .{ .size = 128, .min = 33 }, .{ .size = 128, .min = 128 }, .{} }, + .served = cfg.served, + }; +} + +/// x, the packed codes and the bf16 tables of `f` uploaded as the tiles read them; the caller binds the output. +pub fn upload(r: *rig_.Rig, a: std.mem.Allocator, f: Affine) !Arg { + const w = try a.alloc(u32, f.shape.n * f.shape.k * bits / 32); + f.words(w); + return .{ + .x = try r.input(std.mem.sliceAsBytes(f.x)), + .words = try r.input(std.mem.sliceAsBytes(w)), + .scale = .{ .p = try r.input(std.mem.sliceAsBytes(f.scales)), .kind = 1 }, + .bias = .{ .p = try r.input(std.mem.sliceAsBytes(f.biases)), .kind = 1 }, + .out = 0, + .m = @intCast(f.shape.rows), + .n = @intCast(f.shape.n), + .k = @intCast(f.shape.k), + .bits = bits, + .group = group, + .fp16 = 0, + }; +} + +/// Gate 1's table plants beside the x plants: a NaN scale, an infinite bias and a -inf scale, each in its own column. +pub fn plantTables(f: Affine) void { + const groups = f.shape.k / f.group; + f.scales[3 * groups] = c.toBf16(std.math.nan(f32)); + f.biases[5 * groups + 1] = c.toBf16(std.math.inf(f32)); + f.scales[7 * groups + 2] = c.toBf16(-std.math.inf(f32)); +} + +/// x [rows][K] bf16 times the MLX 4-bit matrix [n][K]: y [rows][n], fp32 or bf16. +pub const Dense = struct { + rig: rig_.Rig, + l: *const hip.Launcher, + arena: std.heap.ArenaAllocator, + index: usize, + f: ?Affine = null, + arg: Arg = undefined, + sum: u64 = 0, + base: u64 = 0, + + pub fn init(a: std.mem.Allocator, rt: *const hip.Runtime, s: hip.Stream, l: *const hip.Launcher, i: usize) Dense { + return .{ .rig = .{ .a = a, .r = rt, .s = s }, .l = l, .arena = .init(a), .index = i }; + } + + pub fn deinit(self: *Dense) void { + self.arena.deinit(); + self.rig.deinit(); + } + + /// The chip has the tile: gfx11's matrix cores. + pub fn ready(self: *const Dense) bool { + return self.l.affine.dense[tiles.Kernels.denseIndex(@intCast(cases[self.index].k)).?] != null; + } + + pub fn kernel(self: *Dense) g.Kernel { + return .{ .spec = spec(cases[self.index]), .ctx = self, .vt = &vt }; + } + + const vt = g.hooks(Dense); + + pub fn prepare(self: *Dense, shape: c.Shape, fill: g.Fill, seed: u64) !bool { + const cfg = cases[self.index]; + if (shape.rows == 0 or shape.n < 8 or shape.k != cfg.k) return false; + self.rig.reset(); + _ = self.arena.reset(.retain_capacity); + const a = self.arena.allocator(); + const f = try Affine.init(a, shape, bits, group); + try f.fill(fill, seed); + if (fill == .nonfinite) plantTables(f); + self.f = f; + self.arg = try upload(&self.rig, a, f); + const n = f.outputs(); + if (cfg.half) self.arg.out16 = try self.rig.output(n * 2) else self.arg.out = try self.rig.output(n * 4); + self.sum = try self.rig.scratch(n * 4); + self.base = if (cfg.half) try self.rig.scratch(n * 2) else 0; + return true; + } + + pub fn run(self: *Dense) !void { + try self.l.affine.denseGo(self.l.r, self.arg, self.rig.s.handle); + try self.rig.s.synchronize(); + } + + /// The matrix tile the registry took before (fp32 sums), then tf_cast's rounding for a bf16 output. + pub fn replaced(self: *Dense) ![]const u8 { + var m = self.arg; + m.out = self.sum; + m.out16 = 0; + const st = self.rig.s.handle; + try self.l.affine.blockGo(self.l.r, m, st, 1, .matrix); + const n = self.f.?.outputs(); + if (!cases[self.index].half) return self.rig.bytes(self.sum, n * 4); + const src = kit.ptr(?*const anyopaque, self.sum); + try self.l.tf_cast(src, @backingInt(kit.Kind.f32), kit.ptr(?*anyopaque, self.base), @backingInt(kit.Kind.bf16), @intCast(n), st); + return self.rig.bytes(self.base, n * 2); + } + + pub fn count(self: *Dense) usize { + return self.f.?.outputs(); + } + + /// MLX's factored formula in float64: per group s * sum(q x) + b * sum(x). + pub fn reference(self: *Dense, want: []f64, mag: []f64) !void { + try self.f.?.reference(want, mag); + } + + pub fn simulate(self: *Dense, acc: c.Accum, order: g.Order, out: []f64) !void { + try self.f.?.simulate(acc, order, out); + } +}; diff --git a/zig/tests/hip/contract_wmma_moe.zig b/zig/tests/hip/contract_wmma_moe.zig new file mode 100644 index 0000000000..2a475787e5 --- /dev/null +++ b/zig/tests/hip/contract_wmma_moe.zig @@ -0,0 +1,225 @@ +//! Flash Next's routed prompt expert tiles under the contract on HIP (gfx11 matrix cores): the matrix tile's bytes. +const std = @import("std"); +const hip = @import("hip"); +const core = @import("core"); +const rig_ = @import("contract_rig.zig"); +const kit = @import("contract_kit.zig"); +const dense_k = @import("contract_wmma_dense.zig"); + +const contract = core.contract; +const c = contract.spec; +const g = contract.gates; +const Affine = contract.affine.Affine; +const tiles = hip.launches.affine; +const Arg = dense_k.Arg; + +/// gate+up: silu(gate) * up of each pair in bf16; down: each pair's fp32 sums. +pub const Part = enum { gu, down }; + +/// The experts stacked in a test's bank and the pairs a row: every expert takes each row once. +pub const experts = 2; +pub const slots = 2; +/// The most pairs an item of a prompt's plan holds (moe_route's tile). +pub const item_pairs = 128; +/// The largest |silu'(x)|: 1.0998 at x = 2.3994. +const slope_max = 1.1; + +pub fn shapeOf(part: Part) tiles.Kernels.MoeShape { + return if (part == .gu) tiles.Kernels.moe_gu_shape else tiles.Kernels.moe_down_shape; +} + +/// Outputs a pair: the expert width for gate+up (its rows hold gate then up), the hidden width for down. +pub fn width(part: Part) usize { + const n: usize = @intCast(shapeOf(part).n); + return if (part == .gu) n / 2 else n; +} + +/// Row r's slot s picks expert (r + s) % experts. +pub fn pick(p: usize) usize { + return (p / slots + p % slots) % experts; +} + +/// A prompt's plan as moe_route writes it: each expert's pairs in order, items of at most 128, two empty items past. +pub const Plan = struct { items: []i32, members: []i32, count: usize }; + +pub fn plan(a: std.mem.Allocator, pairs: usize) !Plan { + const members = try a.alloc(i32, pairs); + const items = try a.alloc(i32, 3 * (pairs + experts + 2)); + @memset(items, 0); + var used: usize = 0; + var at: usize = 0; + for (0..experts) |e| { + var run: usize = 0; + for (0..pairs) |p| { + if (pick(p) != e) continue; + if (run == 0) { + items[3 * used ..][0..3].* = .{ @intCast(e), @intCast(at), 0 }; + used += 1; + } + members[at] = @intCast(p); + at += 1; + items[3 * (used - 1) + 2] += 1; + run = if (run + 1 == item_pairs) 0 else run + 1; + } + } + return .{ .items = items[0 .. 3 * (used + 2)], .members = members, .count = used + 2 }; +} + +/// A bank of `experts` stacked expert matrices, the plan over `rows` rows' pairs, and the call's argument. +pub const Bank = struct { + f: Affine, + plan: Plan, + arg: Arg, + pairs: usize, + + /// x is the rows (gate+up) or the pairs (down); null where the shape is not the tile's. + pub fn load(r: *rig_.Rig, a: std.mem.Allocator, part: Part, shape: c.Shape, fill: g.Fill, seed: u64) !?Bank { + const sh = shapeOf(part); + if (shape.rows == 0 or shape.n != width(part) or shape.k != @as(usize, @intCast(sh.k))) return null; + const pairs = shape.rows * slots; + const n: usize = @intCast(sh.n); + const f = try Affine.init(a, .{ .rows = if (part == .gu) shape.rows else pairs, .n = experts * n, .k = shape.k }, dense_k.bits, dense_k.group); + try f.fill(fill, seed); + const pl = try plan(a, pairs); + var arg = try dense_k.upload(r, a, f); + const out = try r.output(pairs * shape.n * @as(usize, if (part == .gu) 2 else 4)); + if (part == .gu) arg.out16 = out else arg.out = out; + arg.m = item_pairs; + arg.n = sh.n; + arg.route = .{ + .items = try r.input(std.mem.sliceAsBytes(pl.items)), + .members = try r.input(std.mem.sliceAsBytes(pl.members)), + .x_div = if (part == .gu) slots else 1, + }; + return .{ .f = f, .plan = pl, .arg = arg, .pairs = pairs }; + } + + /// Each pair's outputs from the bank's columns y [x rows][experts n] (and their term magnitudes `ym`). + pub fn gather(b: Bank, part: Part, y: []const f64, ym: ?[]const f64, want: []f64, mag: ?[]f64) void { + const n = width(part); + const per: usize = @intCast(shapeOf(part).n); + for (0..b.pairs) |p| { + const row = if (part == .gu) p / slots else p; + const at = row * b.f.shape.n + pick(p) * per; + for (0..n) |col| { + const o = p * n + col; + if (part == .down) { + want[o] = y[at + col]; + if (mag) |m| m[o] = ym.?[at + col]; + continue; + } + const gate = y[at + col]; + const up = y[at + n + col]; + want[o] = kit.silu(gate) * up; + // an error e in gate moves silu(gate) * up by at most 1.1 e (|up| + up's error) + if (mag) |m| m[o] = slope_max * ym.?[at + col] * (@abs(up) + ym.?[at + n + col]) + @abs(kit.silu(gate)) * ym.?[at + n + col]; + } + } + } +}; + +/// A group's 16 dot2 steps from zero (2 u each: an ulp of the step's largest addend), then its scale and bias fmas. +fn depth(s: c.Shape) usize { + return 2 * 16 + 2 * (s.k / dense_k.group) + 8; +} + +pub fn spec(part: Part) c.Spec { + return .{ + .name = if (part == .gu) "hip affine_wmma_moe_gu<4> (Flash Next's expert gate and up, silu(g) u, bf16 out)" else "hip affine_wmma_moe_down<4> (Flash Next's expert down, fp32 out)", + .accum = .f32, + .depth = depth, + // gate+up's epilogue: expf within 2 ulps, then the add, the quotient and the product + .ops = if (part == .gu) 7 else 0, + .out = if (part == .gu) .bf16 else .f32, + .replaces = if (part == .gu) "affine_wmma_gemm over the plan, then tf_moe_act" else "affine_wmma_gemm over the plan", + // a 64-row pass of an item; 300 rows make three items an expert, the last short + .tiles = .{ .{ .size = 64 }, .{}, .{} }, + .served = if (part == .gu) &.{.{ .rows = 300, .n = 640, .k = 2560 }} else &.{.{ .rows = 300, .n = 2560, .k = 640 }}, + }; +} + +/// The plan's pairs through one expert bank: gate+up (bf16 activations) or down (fp32). +pub const Moe = struct { + rig: rig_.Rig, + l: *const hip.Launcher, + arena: std.heap.ArenaAllocator, + part: Part, + bank: ?Bank = null, + sum: u64 = 0, + base: u64 = 0, + + pub fn init(a: std.mem.Allocator, rt: *const hip.Runtime, s: hip.Stream, l: *const hip.Launcher, part: Part) Moe { + return .{ .rig = .{ .a = a, .r = rt, .s = s }, .l = l, .arena = .init(a), .part = part }; + } + + pub fn deinit(self: *Moe) void { + self.arena.deinit(); + self.rig.deinit(); + } + + pub fn ready(self: *const Moe) bool { + return (if (self.part == .gu) self.l.affine.moe_gu else self.l.affine.moe_down) != null; + } + + pub fn kernel(self: *Moe) g.Kernel { + return .{ .spec = spec(self.part), .ctx = self, .vt = &vt }; + } + + const vt = g.hooks(Moe); + + pub fn prepare(self: *Moe, shape: c.Shape, fill: g.Fill, seed: u64) !bool { + self.rig.reset(); + _ = self.arena.reset(.retain_capacity); + const b = try Bank.load(&self.rig, self.arena.allocator(), self.part, shape, fill, seed) orelse return false; + self.bank = b; + self.sum = try self.rig.scratch(b.pairs * @as(usize, @intCast(shapeOf(self.part).n)) * 4); + self.base = if (self.part == .gu) try self.rig.scratch(b.pairs * width(.gu) * 2) else 0; + return true; + } + + pub fn run(self: *Moe) !void { + const b = self.bank.?; + const k = &self.l.affine; + const items: c_int = @intCast(b.plan.count); + const st = self.rig.s.handle; + const took = if (self.part == .gu) try k.moeGateUp(self.l.r, b.arg, items, 0, st) else try k.moeDown(self.l.r, b.arg, items, st); + if (!took) return error.TileRefused; + try self.rig.s.synchronize(); + } + + /// The routed matrix tile the registry took before (fp32 sums), then moe_act for gate+up (no clamp, as served). + pub fn replaced(self: *Moe) ![]const u8 { + const b = self.bank.?; + var m = b.arg; + m.out = self.sum; + m.out16 = 0; + const st = self.rig.s.handle; + try self.l.affine.blockGo(self.l.r, m, st, @intCast(b.plan.count), .matrix); + const n = width(self.part); + if (self.part == .down) return self.rig.bytes(self.sum, b.pairs * n * 4); + const both = kit.ptr(?[*]const f32, self.sum); + try self.l.tf_moe_act(both, kit.ptr(?*anyopaque, self.base), @backingInt(kit.Kind.bf16), @intCast(b.pairs), @intCast(n), 0, st); + return self.rig.bytes(self.base, b.pairs * n * 2); + } + + pub fn count(self: *Moe) usize { + return self.bank.?.pairs * width(self.part); + } + + /// MLX's factored formula in float64 for each pair's expert, then silu(gate) * up for gate+up. + pub fn reference(self: *Moe, want: []f64, mag: []f64) !void { + const b = self.bank.?; + const a = self.arena.allocator(); + const y = try a.alloc(f64, 2 * b.f.outputs()); + try b.f.reference(y[0..b.f.outputs()], y[b.f.outputs()..]); + b.gather(self.part, y[0..b.f.outputs()], y[b.f.outputs()..], want, mag); + } + + pub fn simulate(self: *Moe, acc: c.Accum, order: g.Order, out: []f64) !void { + const b = self.bank.?; + const y = try self.rig.a.alloc(f64, b.f.outputs()); + defer self.rig.a.free(y); + try b.f.simulate(acc, order, y); + b.gather(self.part, y, null, out, null); + } +};