108 lines
3.5 KiB
C
108 lines
3.5 KiB
C
#include <stdio.h>
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#include <cuda.h>
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#include <cuda_runtime_api.h>
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/* Outputs some information on CUDA-enabled devices on your computer,
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* including compute capability and current memory usage.
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*
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* On Linux, compile with: nvcc -o cuda_check cuda_check.c -lcuda
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* On Windows, compile with: nvcc -o cuda_check.exe cuda_check.c -lcuda
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*
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* Authors: Thomas Unterthiner, Jan Schlüter
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*/
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int ConvertSMVer2Cores(int major, int minor)
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{
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// Returns the number of CUDA cores per multiprocessor for a given
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// Compute Capability version. There is no way to retrieve that via
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// the API, so it needs to be hard-coded.
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// See _ConvertSMVer2Cores in helper_cuda.h in NVIDIA's CUDA Samples.
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switch ((major << 4) + minor) {
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case 0x10: return 8; // Tesla
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case 0x11: return 8;
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case 0x12: return 8;
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case 0x13: return 8;
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case 0x20: return 32; // Fermi
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case 0x21: return 48;
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case 0x30: return 192; // Kepler
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case 0x32: return 192;
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case 0x35: return 192;
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case 0x37: return 192;
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case 0x50: return 128; // Maxwell
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case 0x52: return 128;
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case 0x53: return 128;
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case 0x60: return 64; // Pascal
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case 0x61: return 128;
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case 0x62: return 128;
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case 0x70: return 64; // Volta
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case 0x72: return 64; // Xavier
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case 0x75: return 64; // Turing
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default: return 0;
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}
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}
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int main()
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{
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int nGpus;
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int i;
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char name[100];
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int cc_major, cc_minor, cores, cuda_cores, threads_per_core, clockrate;
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size_t freeMem;
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size_t totalMem;
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CUresult result;
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CUdevice device;
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CUcontext context;
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result = cuInit(0);
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if (result != CUDA_SUCCESS) {
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printf("cuInit failed with error code %d: %s\n", result, cudaGetErrorString(result));
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return 1;
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}
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result = cuDeviceGetCount(&nGpus);
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if (result != CUDA_SUCCESS) {
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printf("cuDeviceGetCount failed with error code %d: %s\n", result, cudaGetErrorString(result));
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return 1;
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}
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printf("Found %d device(s).\n", nGpus);
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for (i = 0; i < nGpus; i++) {
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cuDeviceGet(&device, i);
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printf("Device: %d\n", i);
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if (cuDeviceGetName(&name[0], sizeof(name), device) == CUDA_SUCCESS) {
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printf(" Name: %s\n", &name[0]);
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}
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if (cuDeviceComputeCapability(&cc_major, &cc_minor, device) == CUDA_SUCCESS) {
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printf(" Compute Capability: %d.%d\n", cc_major, cc_minor);
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}
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if (cuDeviceGetAttribute(&cores, CU_DEVICE_ATTRIBUTE_MULTIPROCESSOR_COUNT, device) == CUDA_SUCCESS) {
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printf(" Multiprocessors: %d\n", cores);
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if (cuDeviceComputeCapability(&cc_major, &cc_minor, device) == CUDA_SUCCESS) {
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cuda_cores = cores * ConvertSMVer2Cores(cc_major, cc_minor);
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if (cuda_cores > 0) {
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printf(" CUDA Cores: %d\n", cuda_cores);
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}
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else {
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printf(" CUDA Cores: unknown\n");
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}
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}
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if (cuDeviceGetAttribute(&threads_per_core, CU_DEVICE_ATTRIBUTE_MAX_THREADS_PER_MULTIPROCESSOR, device) == CUDA_SUCCESS) {
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printf(" Concurrent threads: %d\n", cores*threads_per_core);
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}
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}
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if (cuDeviceGetAttribute(&clockrate, CU_DEVICE_ATTRIBUTE_CLOCK_RATE, device) == CUDA_SUCCESS) {
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printf(" GPU clock: %g MHz\n", clockrate/1000.);
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}
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if (cuDeviceGetAttribute(&clockrate, CU_DEVICE_ATTRIBUTE_MEMORY_CLOCK_RATE, device) == CUDA_SUCCESS) {
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printf(" Memory clock: %g MHz\n", clockrate/1000.);
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}
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cuCtxCreate(&context, 0, device);
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result = cuMemGetInfo(&freeMem, &totalMem);
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if (result == CUDA_SUCCESS ) {
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printf(" Total Memory: %ld MiB\n Free Memory: %ld MiB\n", totalMem / ( 1024 * 1024 ), freeMem / ( 1024 * 1024 ));
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} else {
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printf(" cMemGetInfo failed with error code %d: %s\n", result, cudaGetErrorString(result));
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}
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cuCtxDetach(context);
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}
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return 0;
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} |