【CUDA编程4】获取device详细信息

CUDA编程，从某种意义而言，可以划分为异构系统编程，其实是一个CPU+GPU模式。其中，CPU被称为Host，而GPU被称为Device。

#include <cuda_runtime.h>
#include <stdio.h>int main(int argc,char** argv)
{int deviceCount = 0;cudaError_t error_id = cudaGetDeviceCount(&deviceCount);if(error_id!=cudaSuccess){printf("cudaGetDeviceCount returned %d\n ->%s\n",(int)error_id,cudaGetErrorString(error_id));printf("Result = FAIL\n");exit(EXIT_FAILURE);}if(deviceCount==0){printf("There are no available device(s) that support CUDA\n");}else{printf("Detected %d CUDA Capable device(s)\n",deviceCount);}int dev=0, driverVersion=0, runtimeVersion=0;cudaSetDevice(dev);cudaDeviceProp deviceProp;cudaGetDeviceProperties(&deviceProp,dev);printf("Device %d:\"%s\"\n",dev,deviceProp.name);cudaDriverGetVersion(&driverVersion);cudaRuntimeGetVersion(&runtimeVersion);printf("  CUDA Driver Version / Runtime Version         %d.%d  /  %d.%d\n",driverVersion/1000,(driverVersion%100)/10,runtimeVersion/1000,(runtimeVersion%100)/10);printf("  CUDA Capability Major/Minor version number:   %d.%d\n",deviceProp.major,deviceProp.minor);printf("  Total amount of global memory:                %.2f GBytes (%llu bytes)\n",(float)deviceProp.totalGlobalMem/pow(1024.0,3),deviceProp.totalGlobalMem);printf("  GPU Clock rate:                               %.0f MHz (%0.2f GHz)\n",deviceProp.clockRate*1e-3f,deviceProp.clockRate*1e-6f);printf("  Memory Bus width:                             %d-bits\n",deviceProp.memoryBusWidth);if (deviceProp.l2CacheSize){printf("  L2 Cache Size:                              %d bytes\n",deviceProp.l2CacheSize);}printf("  Max 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("  Max Layered Texture Size (dim) x layers       1D=(%d) x %d,2D=(%d,%d) x %d\n",deviceProp.maxTexture1DLayered[0],deviceProp.maxTexture1DLayered[1],deviceProp.maxTexture2DLayered[0],deviceProp.maxTexture2DLayered[1],deviceProp.maxTexture2DLayered[2]);printf("  Total amount of constant memory               %lu bytes\n",deviceProp.totalConstMem);printf("  Total amount of shared memory per block:      %lu bytes\n",deviceProp.sharedMemPerBlock);printf("  Total number of registers available per block:%d\n",deviceProp.regsPerBlock);printf("  Wrap size:                                    %d\n",deviceProp.warpSize);printf("  Maximun number of thread per multiprocesser:  %d\n",deviceProp.maxThreadsPerMultiProcessor);printf("  Maximun number of thread per block:           %d\n",deviceProp.maxThreadsPerBlock);printf("  Maximun size of each dimension of a block:    %d x %d x %d\n",deviceProp.maxThreadsDim[0],deviceProp.maxThreadsDim[1],deviceProp.maxThreadsDim[2]);printf("  Maximun size of each dimension of a grid:     %d x %d x %d\n",deviceProp.maxGridSize[0],deviceProp.maxGridSize[1],deviceProp.maxGridSize[2]);printf("  Maximu memory pitch                           %lu bytes\n",deviceProp.memPitch);printf("----------------------------------------------------------\n");printf("Number of multiprocessors:                      %d\n", deviceProp.multiProcessorCount);printf("Total amount of constant memory:                %4.2f KB\n",deviceProp.totalConstMem/1024.0);printf("Total amount of shared memory per block:        %4.2f KB\n",deviceProp.sharedMemPerBlock/1024.0);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 block:           %d\n", deviceProp.maxThreadsPerBlock);printf("Maximum number of threads per multiprocessor:  %d\n",deviceProp.maxThreadsPerMultiProcessor);printf("Maximum number of warps per multiprocessor:     %d\n",deviceProp.maxThreadsPerMultiProcessor/32);return EXIT_SUCCESS;
}

将上述代码保存为device_info.cu，然后编译运行：

nvcc -o device_info device_info.cu
./device_info

输出为：

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