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73 lines
1.8 KiB
73 lines
1.8 KiB
#include <iostream>
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#include <cuda.h>
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#include <cuda_runtime.h>
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static __global__ void debug_kernel(bool* has_debug)
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{
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// Verify using the return code if we have GPU debug flag enabled
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#if defined(__CUDACC__) && defined(__CUDACC_DEBUG__)
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*has_debug = true;
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#else
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*has_debug = false;
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#endif
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}
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int choose_cuda_device()
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{
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int nDevices = 0;
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cudaError_t err = cudaGetDeviceCount(&nDevices);
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if (err != cudaSuccess) {
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std::cerr << "Failed to retrieve the number of CUDA enabled devices"
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<< std::endl;
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return 1;
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}
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for (int i = 0; i < nDevices; ++i) {
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cudaDeviceProp prop;
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cudaError_t err = cudaGetDeviceProperties(&prop, i);
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if (err != cudaSuccess) {
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std::cerr << "Could not retrieve properties from CUDA device " << i
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<< std::endl;
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return 1;
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}
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if (prop.major >= 3) {
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err = cudaSetDevice(i);
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if (err != cudaSuccess) {
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std::cout << "Could not select CUDA device " << i << std::endl;
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} else {
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return 0;
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}
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}
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}
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std::cout << "Could not find a CUDA enabled card supporting compute >=3.0"
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<< std::endl;
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return 1;
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}
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int main(int argc, char** argv)
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{
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bool* has_debug;
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cudaError_t err = cudaMallocManaged(&has_debug, sizeof(bool));
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if (err != cudaSuccess) {
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std::cerr << "cudaMallocManaged failed:\n"
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<< " " << cudaGetErrorString(err) << std::endl;
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return 1;
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}
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debug_kernel<<<1, 1>>>(has_debug);
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err = cudaDeviceSynchronize();
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if (err != cudaSuccess) {
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std::cerr << "debug_kernel: kernel launch shouldn't have failed\n"
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<< "reason:\t" << cudaGetErrorString(err) << std::endl;
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return 1;
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}
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if (*has_debug == false) {
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std::cerr << "debug_kernel: kernel not compiled with device debug"
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<< std::endl;
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return 1;
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}
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return 0;
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}
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