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CUDA 13.2 samples update (#432)

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- Added Python samples for CUDA Python 1.0 release
- Renamed top-level `Samples` directory to `cpp` to accommodate Python samples.
This commit is contained in:
Dheemanth
2026-05-13 15:13:18 -07:00
committed by GitHub
parent a4526d5229
commit aeab82ff30
2072 changed files with 15077 additions and 1970 deletions
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cpp/0_Introduction/simpleVoteIntrinsics/.vscode/c_cpp_properties.json vendored Normal file
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{
"configurations": [
{
"name": "Linux",
"includePath": [
"${workspaceFolder}/**",
"${workspaceFolder}/../../../Common"
],
"defines": [],
"compilerPath": "/usr/local/cuda/bin/nvcc",
"cStandard": "gnu17",
"cppStandard": "gnu++14",
"intelliSenseMode": "linux-gcc-x64",
"configurationProvider": "ms-vscode.makefile-tools"
}
],
"version": 4
}

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cpp/0_Introduction/simpleVoteIntrinsics/.vscode/extensions.json vendored Normal file
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{
"recommendations": [
"nvidia.nsight-vscode-edition",
"ms-vscode.cpptools",
"ms-vscode.makefile-tools"
]
}

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cpp/0_Introduction/simpleVoteIntrinsics/CMakeLists.txt Normal file
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cmake_minimum_required(VERSION 3.20)
list(APPEND CMAKE_MODULE_PATH "${CMAKE_CURRENT_SOURCE_DIR}/../../../cmake/Modules")
project(simpleVoteIntrinsics LANGUAGES C CXX CUDA)
find_package(CUDAToolkit REQUIRED)
set(CMAKE_POSITION_INDEPENDENT_CODE ON)
set(CMAKE_CUDA_ARCHITECTURES 75 80 86 87 89 90 100 110 120)
set(CMAKE_CUDA_FLAGS "${CMAKE_CUDA_FLAGS} -Wno-deprecated-gpu-targets")
if(ENABLE_CUDA_DEBUG)
set(CMAKE_CUDA_FLAGS "${CMAKE_CUDA_FLAGS} -G") # enable cuda-gdb (may significantly affect performance on some targets)
else()
set(CMAKE_CUDA_FLAGS "${CMAKE_CUDA_FLAGS} -lineinfo") # add line information to all builds for debug tools (exclusive to -G option)
endif()
# Include directories and libraries
include_directories(../../../Common)
# Source file
# Add target for simpleVoteIntrinsics
add_executable(simpleVoteIntrinsics simpleVoteIntrinsics.cu)
target_compile_options(simpleVoteIntrinsics PRIVATE $<$<COMPILE_LANGUAGE:CUDA>:--extended-lambda>)
target_compile_features(simpleVoteIntrinsics PRIVATE cxx_std_17 cuda_std_17)
set_target_properties(simpleVoteIntrinsics PROPERTIES CUDA_SEPARABLE_COMPILATION ON)
# Include installation configuration
include(${CMAKE_CURRENT_SOURCE_DIR}/../../../cmake/InstallSamples.cmake)
setup_samples_install()

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cpp/0_Introduction/simpleVoteIntrinsics/README.md Normal file
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# simpleVoteIntrinsics - Simple Vote Intrinsics
## Description
Simple program which demonstrates how to use the Vote (__any_sync, __all_sync) intrinsic instruction in a CUDA kernel.
## Key Concepts
Vote Intrinsics
## Supported SM Architectures
[SM 5.0 ](https://developer.nvidia.com/cuda-gpus) [SM 5.2 ](https://developer.nvidia.com/cuda-gpus) [SM 5.3 ](https://developer.nvidia.com/cuda-gpus) [SM 6.0 ](https://developer.nvidia.com/cuda-gpus) [SM 6.1 ](https://developer.nvidia.com/cuda-gpus) [SM 7.0 ](https://developer.nvidia.com/cuda-gpus) [SM 7.2 ](https://developer.nvidia.com/cuda-gpus) [SM 7.5 ](https://developer.nvidia.com/cuda-gpus) [SM 8.0 ](https://developer.nvidia.com/cuda-gpus) [SM 8.6 ](https://developer.nvidia.com/cuda-gpus) [SM 8.7 ](https://developer.nvidia.com/cuda-gpus) [SM 8.9 ](https://developer.nvidia.com/cuda-gpus) [SM 9.0 ](https://developer.nvidia.com/cuda-gpus)
## Supported OSes
Linux, Windows
## Supported CPU Architecture
x86_64, armv7l, aarch64
## CUDA APIs involved
### [CUDA Runtime API](http://docs.nvidia.com/cuda/cuda-runtime-api/index.html)
cudaMemcpy, cudaFree, cudaDeviceSynchronize, cudaMalloc, cudaGetDeviceProperties
## Prerequisites
Download and install the [CUDA Toolkit](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
## References (for more details)

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cpp/0_Introduction/simpleVoteIntrinsics/simpleVoteIntrinsics.cu Normal file
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/* Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
* * Neither the name of NVIDIA CORPORATION nor the names of its
* contributors may be used to endorse or promote products derived
* from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
* OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
// System includes
#include <assert.h>
#include <stdio.h>
// CUDA runtime
#include <cuda_runtime.h>
// helper functions and utilities to work with CUDA
#include <helper_cuda.h>
#include <helper_functions.h>
#ifndef MAX
#define MAX(a, b) (a > b ? a : b)
#endif
static const char *sSDKsample = "[simpleVoteIntrinsics]\0";
////////////////////////////////////////////////////////////////////////////////
// Global types and parameters
////////////////////////////////////////////////////////////////////////////////
#define VOTE_DATA_GROUP 4
////////////////////////////////////////////////////////////////////////////////
// CUDA Voting Kernel functions
////////////////////////////////////////////////////////////////////////////////
#include "simpleVote_kernel.cuh"
// Generate the test pattern for Tests 1 and 2
void genVoteTestPattern(unsigned int *VOTE_PATTERN, int size)
{
// For testing VOTE.Any (all of these threads will return 0)
for (int i = 0; i < size / 4; i++) {
VOTE_PATTERN[i] = 0x00000000;
}
// For testing VOTE.Any (1/2 these threads will return 1)
for (int i = 2 * size / 8; i < 4 * size / 8; i++) {
VOTE_PATTERN[i] = (i & 0x01) ? i : 0;
}
// For testing VOTE.all (1/2 of these threads will return 0)
for (int i = 2 * size / 4; i < 3 * size / 4; i++) {
VOTE_PATTERN[i] = (i & 0x01) ? 0 : i;
}
// For testing VOTE.all (all of these threads will return 1)
for (int i = 3 * size / 4; i < 4 * size / 4; i++) {
VOTE_PATTERN[i] = 0xffffffff;
}
}
int checkErrors1(unsigned int *h_result, int start, int end, int warp_size, const char *voteType)
{
int i, sum = 0;
for (sum = 0, i = start; i < end; i++) {
sum += h_result[i];
}
if (sum > 0) {
printf("\t<%s>[%d - %d] = ", voteType, start, end - 1);
for (i = start; i < end; i++) {
printf("%d", h_result[i]);
}
printf("%d values FAILED\n", sum);
}
return (sum > 0);
}
int checkErrors2(unsigned int *h_result, int start, int end, int warp_size, const char *voteType)
{
int i, sum = 0;
for (sum = 0, i = start; i < end; i++) {
sum += h_result[i];
}
if (sum != warp_size) {
printf("\t<%s>[%d - %d] = ", voteType, start, end - 1);
for (i = start; i < end; i++) {
printf("%d", h_result[i]);
}
printf(" - FAILED\n");
}
return (sum != warp_size);
}
// Verification code for Kernel #1
int checkResultsVoteAnyKernel1(unsigned int *h_result, int size, int warp_size)
{
int error_count = 0;
error_count += checkErrors1(h_result, 0, VOTE_DATA_GROUP * warp_size / 4, warp_size, "Vote.Any");
error_count += checkErrors2(
h_result, VOTE_DATA_GROUP * warp_size / 4, 2 * VOTE_DATA_GROUP * warp_size / 4, warp_size, "Vote.Any");
error_count += checkErrors2(
h_result, 2 * VOTE_DATA_GROUP * warp_size / 4, 3 * VOTE_DATA_GROUP * warp_size / 4, warp_size, "Vote.Any");
error_count += checkErrors2(
h_result, 3 * VOTE_DATA_GROUP * warp_size / 4, 4 * VOTE_DATA_GROUP * warp_size / 4, warp_size, "Vote.Any");
printf((error_count == 0) ? "\tOK\n" : "\tERROR\n");
return error_count;
}
// Verification code for Kernel #2
int checkResultsVoteAllKernel2(unsigned int *h_result, int size, int warp_size)
{
int error_count = 0;
error_count += checkErrors1(h_result, 0, VOTE_DATA_GROUP * warp_size / 4, warp_size, "Vote.All");
error_count += checkErrors1(
h_result, VOTE_DATA_GROUP * warp_size / 4, 2 * VOTE_DATA_GROUP * warp_size / 4, warp_size, "Vote.All");
error_count += checkErrors1(
h_result, 2 * VOTE_DATA_GROUP * warp_size / 4, 3 * VOTE_DATA_GROUP * warp_size / 4, warp_size, "Vote.All");
error_count += checkErrors2(
h_result, 3 * VOTE_DATA_GROUP * warp_size / 4, 4 * VOTE_DATA_GROUP * warp_size / 4, warp_size, "Vote.All");
printf((error_count == 0) ? "\tOK\n" : "\tERROR\n");
return error_count;
}
// Verification code for Kernel #3
int checkResultsVoteAnyKernel3(bool *hinfo, int size)
{
int i, error_count = 0;
for (i = 0; i < size * 3; i++) {
switch (i % 3) {
case 0:
// First warp should be all zeros.
if (hinfo[i] != (i >= size * 1)) {
error_count++;
}
break;
case 1:
// First warp and half of second should be all zeros.
if (hinfo[i] != (i >= size * 3 / 2)) {
error_count++;
}
break;
case 2:
// First two warps should be all zeros.
if (hinfo[i] != (i >= size * 2)) {
error_count++;
}
break;
}
}
printf((error_count == 0) ? "\tOK\n" : "\tERROR\n");
return error_count;
}
int main(int argc, char **argv)
{
unsigned int *h_input, *h_result;
unsigned int *d_input, *d_result;
bool *dinfo = NULL, *hinfo = NULL;
int error_count[3] = {0, 0, 0};
cudaDeviceProp deviceProp;
int devID, warp_size = 32;
printf("%s\n", sSDKsample);
// This will pick the best possible CUDA capable device
devID = findCudaDevice(argc, (const char **)argv);
checkCudaErrors(cudaGetDeviceProperties(&deviceProp, devID));
// Statistics about the GPU device
printf("> GPU device has %d Multi-Processors, SM %d.%d compute capabilities\n\n",
deviceProp.multiProcessorCount,
deviceProp.major,
deviceProp.minor);
h_input = (unsigned int *)malloc(VOTE_DATA_GROUP * warp_size * sizeof(unsigned int));
h_result = (unsigned int *)malloc(VOTE_DATA_GROUP * warp_size * sizeof(unsigned int));
checkCudaErrors(
cudaMalloc(reinterpret_cast<void **>(&d_input), VOTE_DATA_GROUP * warp_size * sizeof(unsigned int)));
checkCudaErrors(
cudaMalloc(reinterpret_cast<void **>(&d_result), VOTE_DATA_GROUP * warp_size * sizeof(unsigned int)));
genVoteTestPattern(h_input, VOTE_DATA_GROUP * warp_size);
checkCudaErrors(
cudaMemcpy(d_input, h_input, VOTE_DATA_GROUP * warp_size * sizeof(unsigned int), cudaMemcpyHostToDevice));
// Start of Vote Any Test Kernel #1
printf("[VOTE Kernel Test 1/3]\n");
printf("\tRunning <<Vote.Any>> kernel1 ...\n");
{
checkCudaErrors(cudaDeviceSynchronize());
dim3 gridBlock(1, 1);
dim3 threadBlock(VOTE_DATA_GROUP * warp_size, 1);
VoteAnyKernel1<<<gridBlock, threadBlock>>>(d_input, d_result, VOTE_DATA_GROUP * warp_size);
getLastCudaError("VoteAnyKernel() execution failed\n");
checkCudaErrors(cudaDeviceSynchronize());
}
checkCudaErrors(
cudaMemcpy(h_result, d_result, VOTE_DATA_GROUP * warp_size * sizeof(unsigned int), cudaMemcpyDeviceToHost));
error_count[0] += checkResultsVoteAnyKernel1(h_result, VOTE_DATA_GROUP * warp_size, warp_size);
// Start of Vote All Test Kernel #2
printf("\n[VOTE Kernel Test 2/3]\n");
printf("\tRunning <<Vote.All>> kernel2 ...\n");
{
checkCudaErrors(cudaDeviceSynchronize());
dim3 gridBlock(1, 1);
dim3 threadBlock(VOTE_DATA_GROUP * warp_size, 1);
VoteAllKernel2<<<gridBlock, threadBlock>>>(d_input, d_result, VOTE_DATA_GROUP * warp_size);
getLastCudaError("VoteAllKernel() execution failed\n");
checkCudaErrors(cudaDeviceSynchronize());
}
checkCudaErrors(
cudaMemcpy(h_result, d_result, VOTE_DATA_GROUP * warp_size * sizeof(unsigned int), cudaMemcpyDeviceToHost));
error_count[1] += checkResultsVoteAllKernel2(h_result, VOTE_DATA_GROUP * warp_size, warp_size);
// Second Vote Kernel Test #3 (both Any/All)
hinfo = reinterpret_cast<bool *>(calloc(warp_size * 3 * 3, sizeof(bool)));
cudaMalloc(reinterpret_cast<void **>(&dinfo), warp_size * 3 * 3 * sizeof(bool));
cudaMemcpy(dinfo, hinfo, warp_size * 3 * 3 * sizeof(bool), cudaMemcpyHostToDevice);
printf("\n[VOTE Kernel Test 3/3]\n");
printf("\tRunning <<Vote.Any>> kernel3 ...\n");
{
checkCudaErrors(cudaDeviceSynchronize());
VoteAnyKernel3<<<1, warp_size * 3>>>(dinfo, warp_size);
checkCudaErrors(cudaDeviceSynchronize());
}
cudaMemcpy(hinfo, dinfo, warp_size * 3 * 3 * sizeof(bool), cudaMemcpyDeviceToHost);
error_count[2] = checkResultsVoteAnyKernel3(hinfo, warp_size * 3);
// Now free these resources for Test #1,2
checkCudaErrors(cudaFree(d_input));
checkCudaErrors(cudaFree(d_result));
free(h_input);
free(h_result);
// Free resources from Test #3
free(hinfo);
cudaFree(dinfo);
printf("\tShutting down...\n");
return (error_count[0] == 0 && error_count[1] == 0 && error_count[2] == 0) ? EXIT_SUCCESS : EXIT_FAILURE;
}

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cpp/0_Introduction/simpleVoteIntrinsics/simpleVote_kernel.cuh Normal file
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/* Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
* * Neither the name of NVIDIA CORPORATION nor the names of its
* contributors may be used to endorse or promote products derived
* from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
* OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
#ifndef SIMPLEVOTE_KERNEL_CU
#define SIMPLEVOTE_KERNEL_CU
////////////////////////////////////////////////////////////////////////////////
// Vote Any/All intrinsic kernel function tests are supported only by CUDA
// capable devices that are CUDA hardware that has SM1.2 or later
// Vote Functions (refer to section 4.4.5 in the CUDA Programming Guide)
////////////////////////////////////////////////////////////////////////////////
// Kernel #1 tests the across-the-warp vote(any) intrinsic.
// If ANY one of the threads (within the warp) of the predicated condition
// returns a non-zero value, then all threads within this warp will return a
// non-zero value
__global__ void VoteAnyKernel1(unsigned int *input, unsigned int *result, int size)
{
int tx = threadIdx.x;
int mask = 0xffffffff;
result[tx] = __any_sync(mask, input[tx]);
}
// Kernel #2 tests the across-the-warp vote(all) intrinsic.
// If ALL of the threads (within the warp) of the predicated condition returns
// a non-zero value, then all threads within this warp will return a non-zero
// value
__global__ void VoteAllKernel2(unsigned int *input, unsigned int *result, int size)
{
int tx = threadIdx.x;
int mask = 0xffffffff;
result[tx] = __all_sync(mask, input[tx]);
}
// Kernel #3 is a directed test for the across-the-warp vote(all) intrinsic.
// This kernel will test for conditions across warps, and within half warps
__global__ void VoteAnyKernel3(bool *info, int warp_size)
{
int tx = threadIdx.x;
unsigned int mask = 0xffffffff;
bool *offs = info + (tx * 3);
// The following should hold true for the second and third warp
*offs = __any_sync(mask, (tx >= (warp_size * 3) / 2));
// The following should hold true for the "upper half" of the second warp,
// and all of the third warp
*(offs + 1) = (tx >= (warp_size * 3) / 2 ? true : false);
// The following should hold true for the third warp only
if (__all_sync(mask, (tx >= (warp_size * 3) / 2))) {
*(offs + 2) = true;
}
}
#endif