Enzyme on 1.11 needs more Cache than on 1.10 ?

[yolhan83]

Hello, I encountered an issue in Julia 1.11. I hope it hasn't already been reported (I think #2214 is similar). Here is a minimal working example (MWE):

using Enzyme

function foo(x,y)
    y2 = y.^2
    return sum(x .+ y2[:])
end

x = rand(10)
y = rand(10)
dx = Enzyme.make_zero(x)
dy = Enzyme.make_zero(y)
Enzyme.autodiff(Enzyme.Reverse, foo, Enzyme.Duplicated(x,dx), Enzyme.Const(y))

This works fine on 1.10, however, on 1.11, I get

LoadError: Constant memory is stored (or returned) to a differentiable variable.
As a result, Enzyme cannot provably ensure correctness and throws this error.
This might be due to the use of a constant variable as temporary storage for active memory (https://enzyme.mit.edu/julia/stable/faq/#Runtime-Activity).
If Enzyme should be able to prove this use non-differentable, open an issue!
To work around this issue, either:
 a) rewrite this variable to not be conditionally active (fastest, but requires a code change), or
 b) set the Enzyme mode to turn on runtime activity (e.g. autodiff(set_runtime_activity(Reverse), ...) ). This will maintain correctness, but may slightly reduce performance.
Mismatched activity for:   %38 = phi {} addrspace(10)* [ %29, %L90 ], [ %573, %guard_exit125 ] const val:   %573 = load {} addrspace(10)*, {} addrspace(10)* addrspace(11)* %572, align 8, !dbg !468, !tbaa !104, !alias.scope !40, !noalias !43, !dereferenceable_or_null !221, !align !369, !enzyme_type !68, !enzymejl_source_type_Memory\7BFloat64\7D !0, !enzymejl_byref_MUT_REF !0
 value=Unknown object of type Memory{Float64}
 llvalue=  %573 = load {} addrspace(10)*, {} addrspace(10)* addrspace(11)* %572, align 8, !dbg !468, !tbaa !104, !alias.scope !40, !noalias !43, !dereferenceable_or_null !221, !align !369, !enzyme_type !68, !enzymejl_source_type_Memory\7BFloat64\7D !0, !enzymejl_byref_MUT_REF !0

Stacktrace:
  [1] ==
    @ .\promotion.jl:639
  [2] !=
    @ .\operators.jl:277
  [3] _newindexer
    @ .\broadcast.jl:604
  [4] shapeindexer
    @ .\broadcast.jl:599
  [5] newindexer
    @ .\broadcast.jl:598
  [6] extrude
    @ .\broadcast.jl:645
  [7] preprocess
    @ .\broadcast.jl:953
  [8] preprocess_args (repeats 2 times)
    @ .\broadcast.jl:955
  [9] preprocess
    @ .\broadcast.jl:952
 [10] override_bc_copyto!
    @ C:\Users\yolha\.julia\packages\Enzyme\R6sE8\src\compiler\interpreter.jl:798
 [11] copyto!
    @ .\broadcast.jl:925
 [12] copy
    @ .\broadcast.jl:897
 [13] materialize
    @ .\broadcast.jl:872
 [14] foo
    @ c:\Users\yolha\Desktop\bench_py_jl\mwe_enz.jl:4

Stacktrace:
  [1] unalias
    @ .\abstractarray.jl:1500 [inlined]
  [2] broadcast_unalias
    @ .\broadcast.jl:946 [inlined]
  [3] preprocess
    @ .\broadcast.jl:953 [inlined]
  [4] preprocess_args (repeats 2 times)
    @ .\broadcast.jl:955 [inlined]
  [5] preprocess
    @ .\broadcast.jl:952 [inlined]
  [6] override_bc_copyto!
    @ C:\Users\yolha\.julia\packages\Enzyme\R6sE8\src\compiler\interpreter.jl:798 [inlined]
  [7] copyto!
    @ .\broadcast.jl:925 [inlined]
  [8] copy
    @ .\broadcast.jl:897 [inlined]
  [9] materialize
    @ .\broadcast.jl:872 [inlined]
 [10] foo
    @ c:\Users\yolha\Desktop\bench_py_jl\mwe_enz.jl:4 [inlined]
 [11] diffejulia_foo_12936wrap
    @ c:\Users\yolha\Desktop\bench_py_jl\mwe_enz.jl:0
 [12] top-level scope
    @ c:\Users\yolha\Desktop\bench_py_jl\mwe_enz.jl:12
 [13] eval
    @ .\boot.jl:430 [inlined]
 [14] include_string(mapexpr::typeof(REPL.softscope), mod::Module, code::String, filename::String)
    @ Base .\loading.jl:2734
 [15] invokelatest(::Any, ::Any, ::Vararg{Any}; kwargs::@Kwargs{})
    @ Base .\essentials.jl:1055
 [16] invokelatest(::Any, ::Any, ::Vararg{Any})
    @ Base .\essentials.jl:1052
 [17] inlineeval(m::Module, code::String, code_line::Int64, code_column::Int64, file::String; softscope::Bool)
    @ VSCodeServer c:\Users\yolha\.vscode\extensions\julialang.language-julia-1.127.2\scripts\packages\VSCodeServer\src\eval.jl:271
 [18] (::VSCodeServer.var"#69#74"{Bool, Bool, Bool, Module, String, Int64, Int64, String, VSCodeServer.ReplRunCodeRequestParams})()
    @ VSCodeServer c:\Users\yolha\.vscode\extensions\julialang.language-julia-1.127.2\scripts\packages\VSCodeServer\src\eval.jl:181
 [19] withpath(f::VSCodeServer.var"#69#74"{Bool, Bool, Bool, Module, String, Int64, Int64, String, VSCodeServer.ReplRunCodeRequestParams}, path::String)
    @ VSCodeServer c:\Users\yolha\.vscode\extensions\julialang.language-julia-1.127.2\scripts\packages\VSCodeServer\src\repl.jl:276
 [20] (::VSCodeServer.var"#68#73"{Bool, Bool, Bool, Module, String, Int64, Int64, String, VSCodeServer.ReplRunCodeRequestParams})()
    @ VSCodeServer c:\Users\yolha\.vscode\extensions\julialang.language-julia-1.127.2\scripts\packages\VSCodeServer\src\eval.jl:179
 [21] hideprompt(f::VSCodeServer.var"#68#73"{Bool, Bool, Bool, Module, String, Int64, Int64, String, VSCodeServer.ReplRunCodeRequestParams})
    @ VSCodeServer c:\Users\yolha\.vscode\extensions\julialang.language-julia-1.127.2\scripts\packages\VSCodeServer\src\repl.jl:38
 [22] #67
    @ c:\Users\yolha\.vscode\extensions\julialang.language-julia-1.127.2\scripts\packages\VSCodeServer\src\eval.jl:150 [inlined]
 [23] with_logstate(f::VSCodeServer.var"#67#72"{Bool, Bool, Bool, Module, String, Int64, Int64, String, VSCodeServer.ReplRunCodeRequestParams}, logstate::Base.CoreLogging.LogState)
    @ Base.CoreLogging .\logging\logging.jl:522
 [24] with_logger
    @ .\logging\logging.jl:632 [inlined]
 [25] (::VSCodeServer.var"#66#71"{VSCodeServer.ReplRunCodeRequestParams})()
    @ VSCodeServer c:\Users\yolha\.vscode\extensions\julialang.language-julia-1.127.2\scripts\packages\VSCodeServer\src\eval.jl:263
 [26] #invokelatest#2
    @ .\essentials.jl:1055 [inlined]
 [27] invokelatest(::Any)
    @ Base .\essentials.jl:1052
 [28] (::VSCodeServer.var"#64#65")()
    @ VSCodeServer c:\Users\yolha\.vscode\extensions\julialang.language-julia-1.127.2\scripts\packages\VSCodeServer\src\eval.jl:34
in expression starting at c:\Users\yolha\Desktop\bench_py_jl\mwe_enz.jl:12

Note that this works if I use Duplicated(NoNeed) for the y variable, also, this is not about squaring, reshape so that too and probaply others.

version :

Julia Version 1.11.3
Commit d63adeda50 (2025-01-21 19:42 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Windows (x86_64-w64-mingw32)
  CPU: 20 × 12th Gen Intel(R) Core(TM) i7-12700H
  WORD_SIZE: 64
  LLVM: libLLVM-16.0.6 (ORCJIT, alderlake)
Threads: 20 default, 0 interactive, 10 GC (on 20 virtual cores)
Environment:
  JULIA_EDITOR = code

on Enzyme v0.13.28
related :
https://discourse.julialang.org/t/zygote-gradient-is-54000-times-slower-than-jax-gradient/125396/43

[yolhan83]

setting runtime activity fixes this btw