forked from ndd314/cuda_examples
-
Notifications
You must be signed in to change notification settings - Fork 0
Expand file tree
/
Copy pathDocumentation.html
More file actions
665 lines (639 loc) · 30.9 KB
/
Copy pathDocumentation.html
File metadata and controls
665 lines (639 loc) · 30.9 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
<html xmlns:comem3="xalan://com.em3" xmlns:em3="http://www.em3.com/2002/widget">
<head>
<META http-equiv="Content-Type" content="text/html; charset=UTF-8">
<title>NVIDIA CUDA Documentation</title>
<link type="image/x-icon" href="images/NVSphere.ico" rel="shortcut icon">
<script type="text/javascript">
<!--
function openScreenshot(url)
{
var dlgWidth = 556;
var dlgHeight = 634;
var dlgLeft = (screen.width - dlgWidth) / 2;
var dlgTop = (screen.height - dlgHeight) / 2;
var specs = 'toolbar=no,scrollbars=no,location=no,status=no,menubar=no,resizable=no,width=550,height=610,left=' + dlgLeft + ',top=' + dlgTop;
newwin = window.open(url, 'ScreenshotWindow', specs);
newwin.focus();
}
function pageSelectorGoTo()
{
window.location = document.forms[1].pageSelector.value
}
-->
</script>
<style type="text/css">
body {
margin-left:0px;
margin-top:0px;
font-family:Verdana, Geneva, Arial, Helvetica, Sans Serif;
font-size: 11px;
}
td, div {
font-family:Verdana, Geneva, Arial, Helvetica, Sans Serif;
font-size: 11px;
}
#devTable {
position:absolute;
top:0px;
}
.devGradient {
vertical-align:top;
padding:10px;
}
A {
text-decoration:none;
/* color: #008000; */
/* green color: #76b900; */
/*font-weight:bold; */
color: #5B8C00;
}
A:hover {
text-decoration:underline;
color: #000000;
}
A:visited {
color: #5B8C00;
}
.bucketText {
font-size: 10px;
}
A.bucketHeader {
font-weight:bold;
color: #009900;
text-decoration:none;
}
A.bucketHeader:hover {
text-decoration:underline;
}
A.bucketHeader:visited {
color: #005000;
}
H1 {
font-size:15px;
color: #000000;
font-weight:bold;
}
H2 {
font-size:14px;
color: #000000;
font-weight:bold;
}
H3 {
font-size:14px;
color: #000080;
font-weight:bold;
}
H4 {
font-size:12px;
color: #000000;
font-weight:bold;
}
H5 {
font-size:12px;
color: #000080;
font-weight:bold;
}
H6 {
font-size:10px;
color: #000000;
font-weight:bold;
}
H6 {
font-size:10px;
color: #000080;
font-weight:bold;
}
.search {
font-size:7pt;
color: #FFFFFF;
}
.searchResultsHeader {
font-size:10pt;
font-weight:bold;
color: #000080;
}
.smallText {
font-size: 11px;
}
.legal{
font-size:7pt;
color: #000000;
}
A.legal{
text-decoration:none
color: #000000;
}
A.legal:hover{
text-decoration:underline
color: #000000;
}
A.legal:visited{
color: #000000;
}
#mytable
{
BORDER-COLLAPSE: collapse;
borderColor: #dfdfe7;
cellSpacing: 0;
cellPadding: 6;
borderColorLight: #e9eaed;
border: 1;
}
#mytable td {
FONT-SIZE: 10px;
FONT-FAMILY: Verdana, Geneva, Arial, Helvetica, 'Sans Serif';
borderColor: #dfdfe7;
background-color: #F4F4F7;
border-right: 1px solid #dfdfe7;
border-bottom: 1px solid #dfdfe7;
padding: 6px 6px 6px 12px;
}
#mytable th {
padding: 6px 6px 6px 12px;
FONT-FAMILY: Verdana, Geneva, Arial, Helvetica, 'Sans Serif';
FONT-WEIGHT: 400;
FONT-SIZE: 10px;
borderColor: #c0c0c0;
bgColor: #dfdfe7
}
.itemName
{
float: left;
font-size: 12px;
font-weight: bold;
}
td.verticalBder
{
padding-top: 0px;
padding-left: 0px;
padding-right: 0px;
padding-bottom: 0px;
border-right: 1px solid #aca899
}
.anchorImage
{
border: none;
}
.itemMinspec
{
border: none;
}
td.itemMinspec
{
padding-top: 0px;
padding-left: 5px;
padding-bottom: 1px;
vertical-align: middle;
}
td.screenshot
{
width: 134px;
height: 134px;
padding-top: 0px;
padding-bottom: 3px;
padding-left: 0px;
}
td.colInfo
{
padding-top: 1px;
padding-left: 5px;
}
.featuredMonth
{
padding-bottom: 5px;
padding-top: 5px;
padding-left: 5px;
background-color: #dfdfe7;
color: black;
border: solid 1px #d3dae4;
font-weight: bold;
font-size: 14px;
}
.itemGroup
{
font-weight: bold;
}
.itemImage
{
border: 2px solid #008000;
}
.itemImageNoLink
{
border: 2px solid white;
}
.description
{
font-size: 10px;
}
.links
{
font-size: 10px;
}
.changeNotification
{
font-size: 9px;
}
</style>
</head>
<body>
<table style="background-color:#ffffff;border-color:#cccccc;border-style:solid;border-top-width:1px;border-left-width:1px;border-right-width:1px;border-bottom-width:1px;" cellspacing="0" cellpadding="0" border="0" width="591" align="center">
<tr>
<td valign="top">
<div style="position:relative;left:13px;top:8px;padding-bottom:20px;width:565px;">
<!--
******************
MAIN
******************
-->
<h2>NVIDIA CUDA Documentation</h2>
<p>The CUDA Toolkit includes 100+ code samples, utilities, whitepapers, and additional documentation to help you get started developing, porting, and optimizing your applications for the CUDA architecture. You can get quick access to many of the toolkit resources on this page, or <a href="http://developer.nvidia.com/getcuda">download the complete toolkit.</a><br/>
<br/>Please note that you may need to install the latest <a href="http://www.nvidia.com/drivers">NVIDIA drivers</a> and <a href="http://www.nvidia.com/getcuda">CUDA Toolkit</a> to compile and run the code samples.<br/></p>
<table width="575" border="0">
<!-- generated html start -->
<tr>
<td colspan="3" class="separator"><a id="$Anchor"><hr /></a></td>
</tr>
<tr>
<td width="71%" rowspan ="1" align="left" valign="top" class="title"><a name="CUDAGettingStartedGuide(MicrosoftWindows)"></a><span class="itemName" name="path"><strong>CUDA Getting Started Guide (Microsoft Windows) </strong></span><br/>
<br/>
<span class="description">This guide will show you how to install and check the correct operation of the CUDA development tools in Windows.</span></td>
<td rowspan ="1" width="5" align="left" valign="top" class="verticalBder"> </td>
<td rowspan ="1" align="right" valign="top" class="itemMinspec">
<p><span class="links">
<a href="doc/CUDA_Getting_Started_Windows.pdf" name="path">Open</a><br />
</p>
</td>
</tr> <tr>
<td colspan="3" class="separator"><a id="$Anchor"><hr /></a></td>
</tr>
<tr>
<td width="71%" rowspan ="1" align="left" valign="top" class="title"><a name="CUDAGettingStartedGuide(Linux)"></a><span class="itemName" name="path"><strong>CUDA Getting Started Guide (Linux) </strong></span><br/>
<br/>
<span class="description">This guide will show you how to install and check the correct operation of the CUDA development tools in Linux.</span></td>
<td rowspan ="1" width="5" align="left" valign="top" class="verticalBder"> </td>
<td rowspan ="1" align="right" valign="top" class="itemMinspec">
<p><span class="links">
<a href="doc/CUDA_Getting_Started_Linux.pdf" name="path">Open</a><br />
</p>
</td>
</tr> <tr>
<td colspan="3" class="separator"><a id="$Anchor"><hr /></a></td>
</tr>
<tr>
<td width="71%" rowspan ="1" align="left" valign="top" class="title"><a name="CUDAGettingStartedGuide(MacOSX)"></a><span class="itemName" name="path"><strong>CUDA Getting Started Guide (Mac OS X) </strong></span><br/>
<br/>
<span class="description">This guide will show you how to install and check the correct operation of the CUDA development tools in Mac OS X.</span></td>
<td rowspan ="1" width="5" align="left" valign="top" class="verticalBder"> </td>
<td rowspan ="1" align="right" valign="top" class="itemMinspec">
<p><span class="links">
<a href="doc/CUDA_Getting_Started_Mac.pdf" name="path">Open</a><br />
</p>
</td>
</tr> <tr>
<td colspan="3" class="separator"><a id="$Anchor"><hr /></a></td>
</tr>
<tr>
<td width="71%" rowspan ="1" align="left" valign="top" class="title"><a name="CUDACProgrammingGuide"></a><span class="itemName" name="path"><strong>CUDA C Programming Guide </strong></span><br/>
<br/>
<span class="description">This is a detailed programming guide for CUDA C developers.</span></td>
<td rowspan ="1" width="5" align="left" valign="top" class="verticalBder"> </td>
<td rowspan ="1" align="right" valign="top" class="itemMinspec">
<p><span class="links">
<a href="doc/CUDA_C_Programming_Guide.pdf" name="path">Open</a><br />
</p>
</td>
</tr> <tr>
<td colspan="3" class="separator"><a id="$Anchor"><hr /></a></td>
</tr>
<tr>
<td width="71%" rowspan ="1" align="left" valign="top" class="title"><a name="CUDACBestPracticesGuide"></a><span class="itemName" name="path"><strong>CUDA C Best Practices Guide </strong></span><br/>
<br/>
<span class="description">This is a manual to help developers obtain the best performance from the NVIDIA CUDA Architecture. It presents established optimization techniques and explains coding metaphors and idioms that can greatly simplify progarmming for the CUDA architecture.</span></td>
<td rowspan ="1" width="5" align="left" valign="top" class="verticalBder"> </td>
<td rowspan ="1" align="right" valign="top" class="itemMinspec">
<p><span class="links">
<a href="doc/CUDA_C_Best_Practices_Guide.pdf" name="path">Open</a><br />
</p>
</td>
</tr> <tr>
<td colspan="3" class="separator"><a id="$Anchor"><hr /></a></td>
</tr>
<tr>
<td width="71%" rowspan ="1" align="left" valign="top" class="title"><a name="CUDAOccupancyCalculator"></a><span class="itemName" name="path"><strong>CUDA Occupancy Calculator </strong></span><br/>
<br/>
<span class="description">The CUDA Occupancy Calculator allows you to compute the multiprocessor occupancy of a GPU by a given CUDA kernel. This tool provides guidance for optimizing the best kernel launch configuration for the best possible occupancy for the GPU.</span></td>
<td rowspan ="1" width="5" align="left" valign="top" class="verticalBder"> </td>
<td rowspan ="1" align="right" valign="top" class="itemMinspec">
<p><span class="links">
<a href="tools/CUDA_Occupancy_Calculator.xls" name="path">Open</a><br />
</p>
</td>
</tr> <tr>
<td colspan="3" class="separator"><a id="$Anchor"><hr /></a></td>
</tr>
<tr>
<td width="71%" rowspan ="1" align="left" valign="top" class="title"><a name="CUDADeveloperGuideforOptimusPlatforms"></a><span class="itemName" name="path"><strong>CUDA Developer Guide for Optimus Platforms </strong></span><br/>
<br/>
<span class="description">This document provides guidance to CUDA developers and explains how NVIDIA CUDA APIs can be used to query for GPU capabilities in Optimus systems. It is strongly recommended to follow these guidelines to ensure CUDA applications are compatible with all notebooks featuring Optimus.</span></td>
<td rowspan ="1" width="5" align="left" valign="top" class="verticalBder"> </td>
<td rowspan ="1" align="right" valign="top" class="itemMinspec">
<p><span class="links">
<a href="doc/Optimus_Developer_Guide.pdf" name="path">Open</a><br />
</p>
</td>
</tr> <tr>
<td colspan="3" class="separator"><a id="$Anchor"><hr /></a></td>
</tr>
<tr>
<td width="71%" rowspan ="1" align="left" valign="top" class="title"><a name="CUDARuntimeAPIReferenceManual(PDF)"></a><span class="itemName" name="path"><strong>CUDA Runtime API Reference Manual (PDF) </strong></span><br/>
<br/>
<span class="description">This is the CUDA Runtime API reference manual in PDF format.</span></td>
<td rowspan ="1" width="5" align="left" valign="top" class="verticalBder"> </td>
<td rowspan ="1" align="right" valign="top" class="itemMinspec">
<p><span class="links">
<a href="doc/CUDA_Runtime_API.pdf" name="path">Open</a><br />
</p>
</td>
</tr> <tr>
<td colspan="3" class="separator"><a id="$Anchor"><hr /></a></td>
</tr>
<tr>
<td width="71%" rowspan ="1" align="left" valign="top" class="title"><a name="CUDADriverAPIReferenceManual(PDF)"></a><span class="itemName" name="path"><strong>CUDA Driver API Reference Manual (PDF) </strong></span><br/>
<br/>
<span class="description">This is the CUDA Driver API reference manual in PDF format.</span></td>
<td rowspan ="1" width="5" align="left" valign="top" class="verticalBder"> </td>
<td rowspan ="1" align="right" valign="top" class="itemMinspec">
<p><span class="links">
<a href="doc/CUDA_Driver_API.pdf" name="path">Open</a><br />
</p>
</td>
</tr> <tr>
<td colspan="3" class="separator"><a id="$Anchor"><hr /></a></td>
</tr>
<tr>
<td width="71%" rowspan ="1" align="left" valign="top" class="title"><a name="FloatingPointandIEEE754ComplianceforNVIDIAGPUs"></a><span class="itemName" name="path"><strong>Floating Point and IEEE 754 Compliance for NVIDIA GPUs </strong></span><br/>
<br/>
<span class="description">A number of issues related to floating point accuracy and compliance are a frequent source of confusion on both CPUs and GPUs. The purpose of this white pa- per is to discuss the most common issues related to NVIDIA GPUs and to supplement the documentation in the CUDA C Programming Guide.</span></td>
<td rowspan ="1" width="5" align="left" valign="top" class="verticalBder"> </td>
<td rowspan ="1" align="right" valign="top" class="itemMinspec">
<p><span class="links">
<a href="doc/Floating_Point_on_NVIDIA_GPU.pdf" name="path">Open</a><br />
</p>
</td>
</tr> <tr>
<td colspan="3" class="separator"><a id="$Anchor"><hr /></a></td>
</tr>
<tr>
<td width="71%" rowspan ="1" align="left" valign="top" class="title"><a name="Incomplete-LUandCholeskyPreconditionedIterativeMethodsUsingCUSPARSEandCUBLAS"></a><span class="itemName" name="path"><strong>Incomplete-LU and Cholesky Preconditioned Iterative Methods Using CUSPARSE and CUBLAS </strong></span><br/>
<br/>
<span class="description">In this white paper we show how to use the CUSPARSE and CUBLAS libraries to achieve a 2× speedup over CPU in the incomplete-LU and Cholesky preconditioned iterative methods. We focus on the Bi-Conjugate Gradient Stabilized and Conjugate Gradient iterative methods, that can be used to solve large sparse nonsymmetric and symmetric positive defi- nite linear systems, respectively. Also, we comment on the parallel sparse triangular solve, which is an essential building block in these algorithms.</span></td>
<td rowspan ="1" width="5" align="left" valign="top" class="verticalBder"> </td>
<td rowspan ="1" align="right" valign="top" class="itemMinspec">
<p><span class="links">
<a href="doc/Incomplete_LU_Cholesky.pdf" name="path">Open</a><br />
</p>
</td>
</tr> <tr>
<td colspan="3" class="separator"><a id="$Anchor"><hr /></a></td>
</tr>
<tr>
<td width="71%" rowspan ="1" align="left" valign="top" class="title"><a name="TheCUDACompilerDriver(NVCC)"></a><span class="itemName" name="path"><strong>The CUDA Compiler Driver (NVCC) </strong></span><br/>
<br/>
<span class="description">This CUDA compiler driver allows one to compile each CUDA source file, and several of these steps are subtly different for different modes of CUDA compilation (such as generation of device code repositories). It is the purpose of the CUDA compiler driver nvcc to hide the intricate details of CUDA compilation from developers."</span></td>
<td rowspan ="1" width="5" align="left" valign="top" class="verticalBder"> </td>
<td rowspan ="1" align="right" valign="top" class="itemMinspec">
<p><span class="links">
<a href="doc/CUDA_Compiler_Driver_NVCC.pdf" name="path">Open</a><br />
</p>
</td>
</tr> <tr>
<td colspan="3" class="separator"><a id="$Anchor"><hr /></a></td>
</tr>
<tr>
<td width="71%" rowspan ="1" align="left" valign="top" class="title"><a name="PTX:ParallelThreadExecutionISAVersion3.2"></a><span class="itemName" name="path"><strong>PTX: Parallel Thread Execution ISA Version 3.2 </strong></span><br/>
<br/>
<span class="description">This document describes PTX, a low-level parallel thread execution virtual machine and instruction set architecture (ISA). PTX exposes the GPU as a data-parallel computing device.</span></td>
<td rowspan ="1" width="5" align="left" valign="top" class="verticalBder"> </td>
<td rowspan ="1" align="right" valign="top" class="itemMinspec">
<p><span class="links">
<a href="doc/ptx_isa_3.2.pdf" name="path">Open</a><br />
</p>
</td>
</tr> <tr>
<td colspan="3" class="separator"><a id="$Anchor"><hr /></a></td>
</tr>
<tr>
<td width="71%" rowspan ="1" align="left" valign="top" class="title"><a name="ComputeCommandLineProfilerUserGuide"></a><span class="itemName" name="path"><strong>Compute Command Line Profiler User Guide </strong></span><br/>
<br/>
<span class="description">The Compute Command Line Profiler is a command line based profiling tool that can be used to measure performance and find potential opportunities for CUDA and OpenCL optimizations, to achieve maximum performance from NVIDIA GPUs. The Compute Command Line Profiler provides metrics in the form of plots and counter values presented in tables and as graphs. It tracks events with hardware counters on signals in the chip; this is explained in detail in the chapter entitled, "Compute Command Line Profiler Counters."</span></td>
<td rowspan ="1" width="5" align="left" valign="top" class="verticalBder"> </td>
<td rowspan ="1" align="right" valign="top" class="itemMinspec">
<p><span class="links">
<a href="doc/Compute_Command_Line_Profiler_User_Guide.pdf" name="path">Open</a><br />
</p>
</td>
</tr> <tr>
<td colspan="3" class="separator"><a id="$Anchor"><hr /></a></td>
</tr>
<tr>
<td width="71%" rowspan ="1" align="left" valign="top" class="title"><a name="CUDAKeplerCompatibilityGuide"></a><span class="itemName" name="path"><strong>CUDA Kepler Compatibility Guide </strong></span><br/>
<br/>
<span class="description">The Kepler Compatibility Guide for CUDA Applications is intended to help developers ensure that their NVIDIA CUDA applications will run effectively on GPUs based on the NVIDIA Kepler Architecture. This document provides guidance to developers who are already familiar with programming in CUDA C/C++ and want to make sure that their software applications are compatible with Kepler.</span></td>
<td rowspan ="1" width="5" align="left" valign="top" class="verticalBder"> </td>
<td rowspan ="1" align="right" valign="top" class="itemMinspec">
<p><span class="links">
<a href="doc/Kepler_Compatibility_Guide.pdf" name="path">Open</a><br />
</p>
</td>
</tr> <tr>
<td colspan="3" class="separator"><a id="$Anchor"><hr /></a></td>
</tr>
<tr>
<td width="71%" rowspan ="1" align="left" valign="top" class="title"><a name="CUDAKeplerTuningGuide"></a><span class="itemName" name="path"><strong>CUDA Kepler Tuning Guide </strong></span><br/>
<br/>
<span class="description">An overview on how to tune applications for Kepler to further increase these speedups is provided. More details are available in the CUDA C Programming Guide (version 5.5 and later) as noted throughout the document..</span></td>
<td rowspan ="1" width="5" align="left" valign="top" class="verticalBder"> </td>
<td rowspan ="1" align="right" valign="top" class="itemMinspec">
<p><span class="links">
<a href="doc/Kepler_Tuning_Guide.pdf" name="path">Open</a><br />
</p>
</td>
</tr> <tr>
<td colspan="3" class="separator"><a id="$Anchor"><hr /></a></td>
</tr>
<tr>
<td width="71%" rowspan ="1" align="left" valign="top" class="title"><a name="CUBLASLibraryUserGuide"></a><span class="itemName" name="path"><strong>CUBLAS Library User Guide </strong></span><br/>
<br/>
<span class="description">The CUBLAS library is an implementation of BLAS (Basic Linear Algebra Subprograms) on top of the NVIDIA CUDA runtime. It allows the user to access the computational resources of NVIDIA Graphical Processing Unit (GPU), but does not auto-parallelize across multiple GPUs.</span></td>
<td rowspan ="1" width="5" align="left" valign="top" class="verticalBder"> </td>
<td rowspan ="1" align="right" valign="top" class="itemMinspec">
<p><span class="links">
<a href="doc/CUBLAS_Library.pdf" name="path">Open</a><br />
</p>
</td>
</tr> <tr>
<td colspan="3" class="separator"><a id="$Anchor"><hr /></a></td>
</tr>
<tr>
<td width="71%" rowspan ="1" align="left" valign="top" class="title"><a name="CUFFTLibraryUserGuide"></a><span class="itemName" name="path"><strong>CUFFT Library User Guide </strong></span><br/>
<br/>
<span class="description">This document describes CUFFT, the NVIDIA CUDA Fast Fourier Transform (FFT) library. The FFT is a divide-and-conquer algorithm for efficiently computing discrete Fourier transforms of complex or real-valued data sets, and it is one of the most important and widely used numerical algorithms, with applications that include computational physics and general signal processing. The CUFFT library provides a simple interface for computing parallel FFTs on an NVIDIA GPU, which allows users to leverage the floating-point power and parallelism of the GPU without having to develop a custom, GPUbased FFT implementation.</span></td>
<td rowspan ="1" width="5" align="left" valign="top" class="verticalBder"> </td>
<td rowspan ="1" align="right" valign="top" class="itemMinspec">
<p><span class="links">
<a href="doc/CUFFT_Library.pdf" name="path">Open</a><br />
</p>
</td>
</tr> <tr>
<td colspan="3" class="separator"><a id="$Anchor"><hr /></a></td>
</tr>
<tr>
<td width="71%" rowspan ="1" align="left" valign="top" class="title"><a name="CUSPARSELibraryUserGuide"></a><span class="itemName" name="path"><strong>CUSPARSE Library User Guide </strong></span><br/>
<br/>
<span class="description">The NVIDIA CUDA CUSPARSE library contains a set of basic linear algebra subroutines used for handling sparse matrices and is designed to be called from C or C++. These subroutines can be classified in four categories.</span></td>
<td rowspan ="1" width="5" align="left" valign="top" class="verticalBder"> </td>
<td rowspan ="1" align="right" valign="top" class="itemMinspec">
<p><span class="links">
<a href="doc/CUSPARSE_Library.pdf" name="path">Open</a><br />
</p>
</td>
</tr> <tr>
<td colspan="3" class="separator"><a id="$Anchor"><hr /></a></td>
</tr>
<tr>
<td width="71%" rowspan ="1" align="left" valign="top" class="title"><a name="CURANDLibraryUserGuide"></a><span class="itemName" name="path"><strong>CURAND Library User Guide </strong></span><br/>
<br/>
<span class="description">The NVIDIA CURAND library provides facilities that focus on the simple and efficient generation of high-quality pseudorandom and quasirandom numbers.</span></td>
<td rowspan ="1" width="5" align="left" valign="top" class="verticalBder"> </td>
<td rowspan ="1" align="right" valign="top" class="itemMinspec">
<p><span class="links">
<a href="doc/CURAND_Library.pdf" name="path">Open</a><br />
</p>
</td>
</tr> <tr>
<td colspan="3" class="separator"><a id="$Anchor"><hr /></a></td>
</tr>
<tr>
<td width="71%" rowspan ="1" align="left" valign="top" class="title"><a name="NVIDIAPerformancePrimitives(NPP)LibraryUserGuide"></a><span class="itemName" name="path"><strong>NVIDIA Performance Primitives (NPP) Library User Guide </strong></span><br/>
<br/>
<span class="description">NVIDIA NPP is a library of functions for performing CUDA accelerated processing. The initial set of functionality in the library focuses on imaging and video processing and is widely applicable for developers in these areas. NPP will evolve over time to encompass more of the compute heavy tasks in a variety of problem domains. The NPP library is written to maximize flexibility, while maintaining high performance.</span></td>
<td rowspan ="1" width="5" align="left" valign="top" class="verticalBder"> </td>
<td rowspan ="1" align="right" valign="top" class="itemMinspec">
<p><span class="links">
<a href="doc/NPP_Library.pdf" name="path">Open</a><br />
</p>
</td>
</tr> <tr>
<td colspan="3" class="separator"><a id="$Anchor"><hr /></a></td>
</tr>
<tr>
<td width="71%" rowspan ="1" align="left" valign="top" class="title"><a name="CUDAProfilerToolsSDKInterface(CUPTI)UserGuide"></a><span class="itemName" name="path"><strong>CUDA Profiler Tools SDK Interface (CUPTI) User Guide </strong></span><br/>
<br/>
<span class="description">The CUDA Profiling Tools Interface (CUPTI) enables the creation of profiling and tracing tools that target CUDA applications. CUPTI provides four APIs, the Activity API, the Callback API, the Event API, and the Metric API. Using these APIs, you can develop profiling tools that give insight into the CPU and GPU behavior of CUDA applications. CUPTI is delivered as a dynamic library on all platforms supported by CUDA.</span></td>
<td rowspan ="1" width="5" align="left" valign="top" class="verticalBder"> </td>
<td rowspan ="1" align="right" valign="top" class="itemMinspec">
<p><span class="links">
<a href="doc/CUPTI_Library.pdf" name="path">Open</a><br />
</p>
</td>
</tr> <tr>
<td colspan="3" class="separator"><a id="$Anchor"><hr /></a></td>
</tr>
<tr>
<td width="71%" rowspan ="1" align="left" valign="top" class="title"><a name="CUDAProfilerToolsSDKInterfaceReleaseNotes"></a><span class="itemName" name="path"><strong>CUDA Profiler Tools SDK Interface Release Notes </strong></span><br/>
<br/>
<span class="description">The CUDA Profiler Tools Interface Release Notes.</span></td>
<td rowspan ="1" width="5" align="left" valign="top" class="verticalBder"> </td>
<td rowspan ="1" align="right" valign="top" class="itemMinspec">
<p><span class="links">
<a href="doc/CUPTI_Release_Notes.txt" name="path">Open</a><br />
</p>
</td>
</tr> <tr>
<td colspan="3" class="separator"><a id="$Anchor"><hr /></a></td>
</tr>
<tr>
<td width="71%" rowspan ="1" align="left" valign="top" class="title"><a name="ThrustQuickStartGuide"></a><span class="itemName" name="path"><strong>Thrust Quick Start Guide </strong></span><br/>
<br/>
<span class="description">Thrust is a C++ template library for CUDA based on the Standard Template Library (STL). Thrust allows you to implement high performance parallel applications with minimal programming effort through a high-level interface that is fully interoperable with CUDA C.</span></td>
<td rowspan ="1" width="5" align="left" valign="top" class="verticalBder"> </td>
<td rowspan ="1" align="right" valign="top" class="itemMinspec">
<p><span class="links">
<a href="doc/Thrust_Quick_Start_Guide.pdf" name="path">Open</a><br />
</p>
</td>
</tr> <tr>
<td colspan="3" class="separator"><a id="$Anchor"><hr /></a></td>
</tr>
<tr>
<td width="71%" rowspan ="1" align="left" valign="top" class="title"><a name="NVIDIACUDAH.264VideoEncoderLibraryUserGuide"></a><span class="itemName" name="path"><strong>NVIDIA CUDA H.264 Video Encoder Library User Guide </strong></span><br/>
<br/>
<span class="description">The NVIDIA CUDA H.264 Video Encoder is a library for performing CUDA accelerated video encoding. The functionality in the library takes raw YUV frames as input and generates NAL packets. This encoder supports up to various profiles up to High Profile @ Level 4.1.</span></td>
<td rowspan ="1" width="5" align="left" valign="top" class="verticalBder"> </td>
<td rowspan ="1" align="right" valign="top" class="itemMinspec">
<p><span class="links">
<a href="doc/CUDA_Video_Encoder.pdf" name="path">Open</a><br />
</p>
</td>
</tr> <tr>
<td colspan="3" class="separator"><a id="$Anchor"><hr /></a></td>
</tr>
<tr>
<td width="71%" rowspan ="1" align="left" valign="top" class="title"><a name="NVIDIACUDAVideoDecoderLibraryUserGuide"></a><span class="itemName" name="path"><strong>NVIDIA CUDA Video Decoder Library User Guide </strong></span><br/>
<br/>
<span class="description">The CUDA Video Decoder API gives developers access to hardware video decoding capabilities on NVIDIA GPU. The actual hardware decode can run on either Video Processor (VP) or CUDA hardware, depending on the hardware capabilities and the codecs. This API supports the following video stream formats for Linux and Windows platforms: MPEG-2, VC-1, and H.264 (AVCHD).</span></td>
<td rowspan ="1" width="5" align="left" valign="top" class="verticalBder"> </td>
<td rowspan ="1" align="right" valign="top" class="itemMinspec">
<p><span class="links">
<a href="doc/CUDA_Video_Decoder.pdf" name="path">Open</a><br />
</p>
</td>
</tr> <tr>
<td colspan="3" class="separator"><a id="$Anchor"><hr /></a></td>
</tr>
<tr>
<td width="71%" rowspan ="1" align="left" valign="top" class="title"><a name="CUDASamples(PDF)"></a><span class="itemName" name="path"><strong>CUDA Samples (PDF) </strong></span><br/>
<br/>
<span class="description">CUDA Samples Getting Started, Guide to New Samples, and Release Notes (PDF).</span></td>
<td rowspan ="1" width="5" align="left" valign="top" class="verticalBder"> </td>
<td rowspan ="1" align="right" valign="top" class="itemMinspec">
<p><span class="links">
<a href="doc/CUDA_Samples.pdf" name="path">Open</a><br />
</p>
</td>
</tr> <tr>
<td colspan="3" class="separator"><a id="$Anchor"><hr /></a></td>
</tr>
<tr>
<td width="71%" rowspan ="1" align="left" valign="top" class="title"><a name="CUDASamples(TXT)"></a><span class="itemName" name="path"><strong>CUDA Samples (TXT) </strong></span><br/>
<br/>
<span class="description">CUDA Samples Getting Started, Guide to New Samples, and Release Notes (TXT).</span></td>
<td rowspan ="1" width="5" align="left" valign="top" class="verticalBder"> </td>
<td rowspan ="1" align="right" valign="top" class="itemMinspec">
<p><span class="links">
<a href="doc/CUDA_Samples.txt" name="path">Open</a><br />
</p>
</td>
</tr> <tr>
<td colspan="3" class="separator"><a id="$Anchor"><hr /></a></td>
</tr>
<tr>
<td width="71%" rowspan ="1" align="left" valign="top" class="title"><a name="CUDASamplesEndUserLicenseAgreement"></a><span class="itemName" name="path"><strong>CUDA Samples End User License Agreement </strong></span><br/>
<br/>
<span class="description">This is the Software License Agreement for developers or licensees.</span></td>
<td rowspan ="1" width="5" align="left" valign="top" class="verticalBder"> </td>
<td rowspan ="1" align="right" valign="top" class="itemMinspec">
<p><span class="links">
<a href="doc/License.pdf" name="path">Open</a><br />
</p>
</td>
</tr>
<!-- generated html end -->
</table>
</div>
<div align="right" style=" color:#999999;">Last Update: 5/13/2013</div>
</td>
</tr>
</table>
</body>
</html>