mirror of
https://github.com/NVIDIA/cuda-samples.git
synced 2026-10-13 00:08:26 +08:00
CUDA 13.2 samples update (#432)
- 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
GitHub
18
cpp/1_Utilities/deviceQuery/.vscode/c_cpp_properties.json
vendored
Normal file
18
cpp/1_Utilities/deviceQuery/.vscode/c_cpp_properties.json
vendored
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@@ -0,0 +1,18 @@
|
||||
{
|
||||
"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
|
||||
}
|
||||
7
cpp/1_Utilities/deviceQuery/.vscode/extensions.json
vendored
Normal file
7
cpp/1_Utilities/deviceQuery/.vscode/extensions.json
vendored
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@@ -0,0 +1,7 @@
|
||||
{
|
||||
"recommendations": [
|
||||
"nvidia.nsight-vscode-edition",
|
||||
"ms-vscode.cpptools",
|
||||
"ms-vscode.makefile-tools"
|
||||
]
|
||||
}
|
||||
42
cpp/1_Utilities/deviceQuery/CMakeLists.txt
Normal file
42
cpp/1_Utilities/deviceQuery/CMakeLists.txt
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@@ -0,0 +1,42 @@
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cmake_minimum_required(VERSION 3.20)
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list(APPEND CMAKE_MODULE_PATH "${CMAKE_CURRENT_SOURCE_DIR}/../../../cmake/Modules")
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project(deviceQuery LANGUAGES C CXX CUDA)
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find_package(CUDAToolkit REQUIRED)
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set(CMAKE_POSITION_INDEPENDENT_CODE ON)
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||||
|
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set(CMAKE_CUDA_ARCHITECTURES 75 80 86 87 89 90 100 110 120)
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set(CMAKE_CUDA_FLAGS "${CMAKE_CUDA_FLAGS} -Wno-deprecated-gpu-targets")
|
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if(ENABLE_CUDA_DEBUG)
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set(CMAKE_CUDA_FLAGS "${CMAKE_CUDA_FLAGS} -G") # enable cuda-gdb (may significantly affect performance on some targets)
|
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else()
|
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set(CMAKE_CUDA_FLAGS "${CMAKE_CUDA_FLAGS} -lineinfo") # add line information to all builds for debug tools (exclusive to -G option)
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endif()
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# Include directories and libraries
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include_directories(../../../Common)
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# Source file
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# Add target for deviceQuery
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add_executable(deviceQuery deviceQuery.cpp)
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target_compile_options(deviceQuery PRIVATE $<$<COMPILE_LANGUAGE:CUDA>:--extended-lambda>)
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target_compile_features(deviceQuery PRIVATE cxx_std_17 cuda_std_17)
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set_target_properties(deviceQuery PROPERTIES CUDA_SEPARABLE_COMPILATION ON)
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target_include_directories(deviceQuery PRIVATE
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${CUDAToolkit_INCLUDE_DIRS}
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)
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target_link_libraries(deviceQuery PUBLIC
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CUDA::cudart
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)
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# Include installation configuration
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include(${CMAKE_CURRENT_SOURCE_DIR}/../../../cmake/InstallSamples.cmake)
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setup_samples_install()
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35
cpp/1_Utilities/deviceQuery/README.md
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35
cpp/1_Utilities/deviceQuery/README.md
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@@ -0,0 +1,35 @@
|
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# deviceQuery - Device Query
|
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|
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## Description
|
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|
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This sample enumerates the properties of the CUDA devices present in the system.
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## Key Concepts
|
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CUDA Runtime API, Device Query
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|
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## Supported SM Architectures
|
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|
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[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)
|
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|
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## Supported OSes
|
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|
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Linux, Windows
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||||
|
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## Supported CPU Architecture
|
||||
|
||||
x86_64, armv7l, aarch64
|
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|
||||
## CUDA APIs involved
|
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|
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### [CUDA Driver API](http://docs.nvidia.com/cuda/cuda-driver-api/index.html)
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cuDeviceGetAttribute, cuSafeCallNoSync
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|
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### [CUDA Runtime API](http://docs.nvidia.com/cuda/cuda-runtime-api/index.html)
|
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cudaRuntimeGetVersion, cudaGetErrorString, cudaDeviceCanAccessPeer, cudaSetDevice, cudaGetDeviceCount, cudaDriverGetVersion, cudaGetDeviceProperties
|
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|
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## Prerequisites
|
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|
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Download and install the [CUDA Toolkit](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
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## References (for more details)
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335
cpp/1_Utilities/deviceQuery/deviceQuery.cpp
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335
cpp/1_Utilities/deviceQuery/deviceQuery.cpp
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@@ -0,0 +1,335 @@
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/* Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
|
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*
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* 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.
|
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*/
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/* This sample queries the properties of the CUDA devices present in the system
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* via CUDA Runtime API. */
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// std::system includes
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#include <cuda_runtime.h>
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#include <helper_cuda.h>
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#include <iostream>
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#include <memory>
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#include <string>
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int *pArgc = NULL;
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char **pArgv = NULL;
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#if CUDART_VERSION < 5000
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// CUDA-C includes
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#include <cuda.h>
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// This function wraps the CUDA Driver API into a template function
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template <class T> inline void getCudaAttribute(T *attribute, CUdevice_attribute device_attribute, int device)
|
||||
{
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||||
CUresult error = cuDeviceGetAttribute(attribute, device_attribute, device);
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|
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if (CUDA_SUCCESS != error) {
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fprintf(
|
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stderr, "cuSafeCallNoSync() Driver API error = %04d from file <%s>, line %i.\n", error, __FILE__, __LINE__);
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exit(EXIT_FAILURE);
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||||
}
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}
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|
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#endif /* CUDART_VERSION < 5000 */
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////////////////////////////////////////////////////////////////////////////////
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// Program main
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////////////////////////////////////////////////////////////////////////////////
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int main(int argc, char **argv)
|
||||
{
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pArgc = &argc;
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pArgv = argv;
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printf("%s Starting...\n\n", argv[0]);
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printf(" CUDA Device Query (Runtime API) version (CUDART static linking)\n\n");
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|
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int deviceCount = 0;
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cudaError_t error_id = cudaGetDeviceCount(&deviceCount);
|
||||
|
||||
if (error_id != cudaSuccess) {
|
||||
printf("cudaGetDeviceCount returned %d\n-> %s\n", static_cast<int>(error_id), cudaGetErrorString(error_id));
|
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printf("Result = FAIL\n");
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exit(EXIT_FAILURE);
|
||||
}
|
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|
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// This function call returns 0 if there are no CUDA capable devices.
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if (deviceCount == 0) {
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printf("There are no available device(s) that support CUDA\n");
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||||
}
|
||||
else {
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||||
printf("Detected %d CUDA Capable device(s)\n", deviceCount);
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}
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int dev, driverVersion = 0, runtimeVersion = 0;
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for (dev = 0; dev < deviceCount; ++dev) {
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cudaSetDevice(dev);
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cudaDeviceProp deviceProp;
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cudaGetDeviceProperties(&deviceProp, dev);
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|
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printf("\nDevice %d: \"%s\"\n", dev, deviceProp.name);
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|
||||
// Console log
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cudaDriverGetVersion(&driverVersion);
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cudaRuntimeGetVersion(&runtimeVersion);
|
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printf(" CUDA Driver Version / Runtime Version %d.%d / %d.%d\n",
|
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driverVersion / 1000,
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(driverVersion % 100) / 10,
|
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runtimeVersion / 1000,
|
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(runtimeVersion % 100) / 10);
|
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printf(" CUDA Capability Major/Minor version number: %d.%d\n", deviceProp.major, deviceProp.minor);
|
||||
|
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char msg[256];
|
||||
#if defined(WIN32) || defined(_WIN32) || defined(WIN64) || defined(_WIN64)
|
||||
sprintf_s(msg,
|
||||
sizeof(msg),
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" Total amount of global memory: %.0f MBytes "
|
||||
"(%llu bytes)\n",
|
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static_cast<float>(deviceProp.totalGlobalMem / 1048576.0f),
|
||||
(unsigned long long)deviceProp.totalGlobalMem);
|
||||
#else
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||||
snprintf(msg,
|
||||
sizeof(msg),
|
||||
" Total amount of global memory: %.0f MBytes "
|
||||
"(%llu bytes)\n",
|
||||
static_cast<float>(deviceProp.totalGlobalMem / 1048576.0f),
|
||||
(unsigned long long)deviceProp.totalGlobalMem);
|
||||
#endif
|
||||
printf("%s", msg);
|
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|
||||
printf(" (%03d) Multiprocessors, (%03d) CUDA Cores/MP: %d CUDA Cores\n",
|
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deviceProp.multiProcessorCount,
|
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_ConvertSMVer2Cores(deviceProp.major, deviceProp.minor),
|
||||
_ConvertSMVer2Cores(deviceProp.major, deviceProp.minor) * deviceProp.multiProcessorCount);
|
||||
int clockRate;
|
||||
checkCudaErrors(cudaDeviceGetAttribute(&clockRate, cudaDevAttrClockRate, dev));
|
||||
printf(" GPU Max Clock rate: %.0f MHz (%0.2f "
|
||||
"GHz)\n",
|
||||
clockRate * 1e-3f,
|
||||
clockRate * 1e-6f);
|
||||
#if CUDART_VERSION >= 5000
|
||||
int memoryClockRate;
|
||||
#if CUDART_VERSION >= 13000
|
||||
checkCudaErrors(cudaDeviceGetAttribute(&memoryClockRate, cudaDevAttrMemoryClockRate, dev));
|
||||
#else
|
||||
memoryClockRate = deviceProp.memoryClockRate;
|
||||
#endif
|
||||
printf(" Memory Clock rate: %.0f Mhz\n", memoryClockRate * 1e-3f);
|
||||
printf(" Memory Bus Width: %d-bit\n", deviceProp.memoryBusWidth);
|
||||
|
||||
if (deviceProp.l2CacheSize) {
|
||||
printf(" L2 Cache Size: %d bytes\n", deviceProp.l2CacheSize);
|
||||
}
|
||||
|
||||
#else
|
||||
// This only available in CUDA 4.0-4.2 (but these were only exposed in the
|
||||
// CUDA Driver API)
|
||||
int memoryClock;
|
||||
getCudaAttribute<int>(&memoryClock, CU_DEVICE_ATTRIBUTE_MEMORY_CLOCK_RATE, dev);
|
||||
printf(" Memory Clock rate: %.0f Mhz\n", memoryClock * 1e-3f);
|
||||
int memBusWidth;
|
||||
getCudaAttribute<int>(&memBusWidth, CU_DEVICE_ATTRIBUTE_GLOBAL_MEMORY_BUS_WIDTH, dev);
|
||||
printf(" Memory Bus Width: %d-bit\n", memBusWidth);
|
||||
int L2CacheSize;
|
||||
getCudaAttribute<int>(&L2CacheSize, CU_DEVICE_ATTRIBUTE_L2_CACHE_SIZE, dev);
|
||||
|
||||
if (L2CacheSize) {
|
||||
printf(" L2 Cache Size: %d bytes\n", L2CacheSize);
|
||||
}
|
||||
|
||||
#endif
|
||||
|
||||
printf(" Maximum Texture Dimension Size (x,y,z) 1D=(%d), 2D=(%d, "
|
||||
"%d), 3D=(%d, %d, %d)\n",
|
||||
deviceProp.maxTexture1D,
|
||||
deviceProp.maxTexture2D[0],
|
||||
deviceProp.maxTexture2D[1],
|
||||
deviceProp.maxTexture3D[0],
|
||||
deviceProp.maxTexture3D[1],
|
||||
deviceProp.maxTexture3D[2]);
|
||||
printf(" Maximum Layered 1D Texture Size, (num) layers 1D=(%d), %d layers\n",
|
||||
deviceProp.maxTexture1DLayered[0],
|
||||
deviceProp.maxTexture1DLayered[1]);
|
||||
printf(" Maximum Layered 2D Texture Size, (num) layers 2D=(%d, %d), %d "
|
||||
"layers\n",
|
||||
deviceProp.maxTexture2DLayered[0],
|
||||
deviceProp.maxTexture2DLayered[1],
|
||||
deviceProp.maxTexture2DLayered[2]);
|
||||
|
||||
printf(" Total amount of constant memory: %zu bytes\n", deviceProp.totalConstMem);
|
||||
printf(" Total amount of shared memory per block: %zu bytes\n", deviceProp.sharedMemPerBlock);
|
||||
printf(" Total shared memory per multiprocessor: %zu bytes\n", deviceProp.sharedMemPerMultiprocessor);
|
||||
printf(" Total number of registers available per block: %d\n", deviceProp.regsPerBlock);
|
||||
printf(" Warp size: %d\n", deviceProp.warpSize);
|
||||
printf(" Maximum number of threads per multiprocessor: %d\n", deviceProp.maxThreadsPerMultiProcessor);
|
||||
printf(" Maximum number of threads per block: %d\n", deviceProp.maxThreadsPerBlock);
|
||||
printf(" Max dimension size of a thread block (x,y,z): (%d, %d, %d)\n",
|
||||
deviceProp.maxThreadsDim[0],
|
||||
deviceProp.maxThreadsDim[1],
|
||||
deviceProp.maxThreadsDim[2]);
|
||||
printf(" Max dimension size of a grid size (x,y,z): (%d, %d, %d)\n",
|
||||
deviceProp.maxGridSize[0],
|
||||
deviceProp.maxGridSize[1],
|
||||
deviceProp.maxGridSize[2]);
|
||||
printf(" Maximum memory pitch: %zu bytes\n", deviceProp.memPitch);
|
||||
printf(" Texture alignment: %zu bytes\n", deviceProp.textureAlignment);
|
||||
int gpuOverlap;
|
||||
checkCudaErrors(cudaDeviceGetAttribute(&gpuOverlap, cudaDevAttrGpuOverlap, dev));
|
||||
printf(" Concurrent copy and kernel execution: %s with %d copy "
|
||||
"engine(s)\n",
|
||||
(gpuOverlap ? "Yes" : "No"),
|
||||
deviceProp.asyncEngineCount);
|
||||
int kernelExecTimeout;
|
||||
checkCudaErrors(cudaDeviceGetAttribute(&kernelExecTimeout, cudaDevAttrKernelExecTimeout, dev));
|
||||
printf(" Run time limit on kernels: %s\n", kernelExecTimeout ? "Yes" : "No");
|
||||
printf(" Integrated GPU sharing Host Memory: %s\n", deviceProp.integrated ? "Yes" : "No");
|
||||
printf(" Support host page-locked memory mapping: %s\n", deviceProp.canMapHostMemory ? "Yes" : "No");
|
||||
printf(" Alignment requirement for Surfaces: %s\n", deviceProp.surfaceAlignment ? "Yes" : "No");
|
||||
printf(" Device has ECC support: %s\n", deviceProp.ECCEnabled ? "Enabled" : "Disabled");
|
||||
#if defined(WIN32) || defined(_WIN32) || defined(WIN64) || defined(_WIN64)
|
||||
printf(" CUDA Device Driver Mode (TCC or WDDM): %s\n",
|
||||
deviceProp.tccDriver ? "TCC (Tesla Compute Cluster Driver)" : "WDDM (Windows Display Driver Model)");
|
||||
#endif
|
||||
printf(" Device supports Unified Addressing (UVA): %s\n", deviceProp.unifiedAddressing ? "Yes" : "No");
|
||||
printf(" Device supports Managed Memory: %s\n", deviceProp.managedMemory ? "Yes" : "No");
|
||||
printf(" Device supports Compute Preemption: %s\n",
|
||||
deviceProp.computePreemptionSupported ? "Yes" : "No");
|
||||
printf(" Supports Cooperative Kernel Launch: %s\n", deviceProp.cooperativeLaunch ? "Yes" : "No");
|
||||
// The property cooperativeMultiDeviceLaunch is deprecated in CUDA 13.0
|
||||
#if CUDART_VERSION < 13000
|
||||
printf(" Supports MultiDevice Co-op Kernel Launch: %s\n",
|
||||
deviceProp.cooperativeMultiDeviceLaunch ? "Yes" : "No");
|
||||
#endif
|
||||
printf(" Device PCI Domain ID / Bus ID / location ID: %d / %d / %d\n",
|
||||
deviceProp.pciDomainID,
|
||||
deviceProp.pciBusID,
|
||||
deviceProp.pciDeviceID);
|
||||
|
||||
const char *sComputeMode[] = {"Default (multiple host threads can use ::cudaSetDevice() with device "
|
||||
"simultaneously)",
|
||||
"Exclusive (only one host thread in one process is able to use "
|
||||
"::cudaSetDevice() with this device)",
|
||||
"Prohibited (no host thread can use ::cudaSetDevice() with this "
|
||||
"device)",
|
||||
"Exclusive Process (many threads in one process is able to use "
|
||||
"::cudaSetDevice() with this device)",
|
||||
"Unknown",
|
||||
NULL};
|
||||
int computeMode;
|
||||
checkCudaErrors(cudaDeviceGetAttribute(&computeMode, cudaDevAttrComputeMode, dev));
|
||||
printf(" Compute Mode:\n");
|
||||
printf(" < %s >\n", sComputeMode[computeMode]);
|
||||
}
|
||||
|
||||
// If there are 2 or more GPUs, query to determine whether RDMA is supported
|
||||
if (deviceCount >= 2) {
|
||||
cudaDeviceProp prop[64];
|
||||
int gpuid[64]; // we want to find the first two GPUs that can support P2P
|
||||
int gpu_p2p_count = 0;
|
||||
|
||||
for (int i = 0; i < deviceCount; i++) {
|
||||
checkCudaErrors(cudaGetDeviceProperties(&prop[i], i));
|
||||
|
||||
// Only boards based on Fermi or later can support P2P
|
||||
if ((prop[i].major >= 2)
|
||||
#if defined(WIN32) || defined(_WIN32) || defined(WIN64) || defined(_WIN64)
|
||||
// on Windows (64-bit), the Tesla Compute Cluster driver for windows
|
||||
// must be enabled to support this
|
||||
&& prop[i].tccDriver
|
||||
#endif
|
||||
) {
|
||||
// This is an array of P2P capable GPUs
|
||||
gpuid[gpu_p2p_count++] = i;
|
||||
}
|
||||
}
|
||||
|
||||
// Show all the combinations of support P2P GPUs
|
||||
int can_access_peer;
|
||||
|
||||
if (gpu_p2p_count >= 2) {
|
||||
for (int i = 0; i < gpu_p2p_count; i++) {
|
||||
for (int j = 0; j < gpu_p2p_count; j++) {
|
||||
if (gpuid[i] == gpuid[j]) {
|
||||
continue;
|
||||
}
|
||||
checkCudaErrors(cudaDeviceCanAccessPeer(&can_access_peer, gpuid[i], gpuid[j]));
|
||||
printf("> Peer access from %s (GPU%d) -> %s (GPU%d) : %s\n",
|
||||
prop[gpuid[i]].name,
|
||||
gpuid[i],
|
||||
prop[gpuid[j]].name,
|
||||
gpuid[j],
|
||||
can_access_peer ? "Yes" : "No");
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// csv masterlog info
|
||||
// *****************************
|
||||
// exe and CUDA driver name
|
||||
printf("\n");
|
||||
std::string sProfileString = "deviceQuery, CUDA Driver = CUDART";
|
||||
char cTemp[16];
|
||||
|
||||
// driver version
|
||||
sProfileString += ", CUDA Driver Version = ";
|
||||
#if defined(WIN32) || defined(_WIN32) || defined(WIN64) || defined(_WIN64)
|
||||
sprintf_s(cTemp, 10, "%d.%d", driverVersion / 1000, (driverVersion % 100) / 10);
|
||||
#else
|
||||
snprintf(cTemp, sizeof(cTemp), "%d.%d", driverVersion / 1000, (driverVersion % 100) / 10);
|
||||
#endif
|
||||
sProfileString += cTemp;
|
||||
|
||||
// Runtime version
|
||||
sProfileString += ", CUDA Runtime Version = ";
|
||||
#if defined(WIN32) || defined(_WIN32) || defined(WIN64) || defined(_WIN64)
|
||||
sprintf_s(cTemp, 10, "%d.%d", runtimeVersion / 1000, (runtimeVersion % 100) / 10);
|
||||
#else
|
||||
snprintf(cTemp, sizeof(cTemp), "%d.%d", runtimeVersion / 1000, (runtimeVersion % 100) / 10);
|
||||
#endif
|
||||
sProfileString += cTemp;
|
||||
|
||||
// Device count
|
||||
sProfileString += ", NumDevs = ";
|
||||
#if defined(WIN32) || defined(_WIN32) || defined(WIN64) || defined(_WIN64)
|
||||
sprintf_s(cTemp, 10, "%d", deviceCount);
|
||||
#else
|
||||
snprintf(cTemp, sizeof(cTemp), "%d", deviceCount);
|
||||
#endif
|
||||
sProfileString += cTemp;
|
||||
sProfileString += "\n";
|
||||
printf("%s", sProfileString.c_str());
|
||||
|
||||
printf("Result = PASS\n");
|
||||
|
||||
// finish
|
||||
exit(EXIT_SUCCESS);
|
||||
}
|
||||
Reference in New Issue
Block a user