sol*_*les 4 cuda gpu gpgpu blas cublas
在cuBLAS中,cublasIsamin()给出单精度数组的argmin .
这是完整的函数声明: cublasStatus_t cublasIsamin(cublasHandle_t handle, int n,
const float *x, int incx, int *result)
cuBLAS程序员指南提供有关cublasIsamin()参数的信息:

如果我使用主机(CPU)内存result,那么cublasIsamin正常工作.这是一个例子:
void argmin_experiment_hostOutput(){
float h_A[4] = {1, 2, 3, 4}; int N = 4;
float* d_A = 0;
CHECK_CUDART(cudaMalloc((void**)&d_A, N * sizeof(d_A[0])));
CHECK_CUBLAS(cublasSetVector(N, sizeof(h_A[0]), h_A, 1, d_A, 1));
cublasHandle_t handle; CHECK_CUBLAS(cublasCreate(&handle));
int result; //host memory
CHECK_CUBLAS(cublasIsamin(handle, N, d_A, 1, &result));
printf("argmin = %d, min = %f \n", result, h_A[result]);
CHECK_CUBLAS(cublasDestroy(handle));
}
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但是,如果我使用设备(GPU)内存result,那么段错误cublasIsamin.以下是段错误的示例:
void argmin_experiment_deviceOutput(){
float h_A[4] = {1, 2, 3, 4}; int N = 4;
float* d_A = 0;
CHECK_CUDART(cudaMalloc((void**)&d_A, N * sizeof(d_A[0])));
CHECK_CUBLAS(cublasSetVector(N, sizeof(h_A[0]), h_A, 1, d_A, 1));
cublasHandle_t handle; CHECK_CUBLAS(cublasCreate(&handle));
int* d_result = 0;
CHECK_CUDART(cudaMalloc((void**)&d_result, 1 * sizeof(d_result[0]))); //just enough device memory for 1 result
CHECK_CUDART(cudaMemset(d_result, 0, 1 * sizeof(d_result[0])));
CHECK_CUBLAS(cublasIsamin(handle, N, d_A, 1, d_result)); //SEGFAULT!
CHECK_CUBLAS(cublasDestroy(handle));
}
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动机:我想在多个流中同时计算几个向量的argmin().输出到主机内存需要CPU-GPU同步,并且似乎会破坏多内核并发性.所以,我想将argmin输出到设备内存.