Dateien
rocm-systems/samples/7_Advanced/hipblas_saxpy/saxpy.cublas.cpp
T
Maneesh Gupta 4803ff12f1 Rename 2_Advanced to 7_Advanced
Change-Id: I51e5fa7f4c1dbf467f2d7182ec69d12d5fe548d0
2016-08-18 12:40:30 +05:30

95 Zeilen
2.5 KiB
C++

#include <random>
#include <algorithm>
#include <iostream>
#include <cmath>
// header file for the GPU API
#include <cuda_runtime.h>
#include <cublas_v2.h>
#define N (1024 * 500)
#define CHECK(cmd) \
{\
cudaError_t error = cmd; \
if (error != cudaSuccess) { \
fprintf(stderr, "error: '%s'(%d) at %s:%d\n", cudaGetErrorString(error), error,__FILE__, __LINE__); \
exit(EXIT_FAILURE);\
}\
}
#define CHECK_BLAS(cmd) \
{\
cublasStatus_t error = cmd;\
if (error != CUBLAS_STATUS_SUCCESS) { \
fprintf(stderr, "error: (%d) at %s:%d\n", error,__FILE__, __LINE__); \
exit(EXIT_FAILURE);\
}\
}
int main() {
const float a = 100.0f;
float x[N];
float y[N], y_cpu_res[N], y_gpu_res[N];
// initialize the input data
std::default_random_engine random_gen;
std::uniform_real_distribution<float> distribution(-N, N);
std::generate_n(x, N, [&]() { return distribution(random_gen); });
std::generate_n(y, N, [&]() { return distribution(random_gen); });
std::copy_n(y, N, y_cpu_res);
// Explicit GPU code:
size_t Nbytes = N*sizeof(float);
float *x_gpu, *y_gpu;
cublasHandle_t handle;
cudaDeviceProp props;
CHECK(cudaGetDeviceProperties(&props, 0/*deviceID*/));
printf ("info: running on device %s\n", props.name);
printf ("info: allocate host mem (%6.2f MB)\n", 2*Nbytes/1024.0/1024.0);
printf ("info: allocate device mem (%6.2f MB)\n", 2*Nbytes/1024.0/1024.0);
CHECK(cudaMalloc(&x_gpu, Nbytes));
CHECK(cudaMalloc(&y_gpu, Nbytes));
// Initialize the blas library
CHECK_BLAS ( cublasCreate(&handle));
// copy n elements from a vector in host memory space to a vector in GPU memory space
printf ("info: copy Host2Device\n");
CHECK_BLAS ( cublasSetVector(N, sizeof(*x), x, 1, x_gpu, 1));
CHECK_BLAS ( cublasSetVector(N, sizeof(*y), y, 1, y_gpu, 1));
printf ("info: launch 'saxpy' kernel\n");
CHECK_BLAS ( cublasSaxpy(handle, N, &a, x_gpu, 1, y_gpu, 1));
cudaDeviceSynchronize();
printf ("info: copy Device2Host\n");
CHECK_BLAS ( cublasGetVector(N, sizeof(*y_gpu_res), y_gpu, 1, y_gpu_res, 1));
// CPU implementation of saxpy
for (int i = 0; i < N; i++) {
y_cpu_res[i] = a * x[i] + y[i];
}
// verify the results
int errors = 0;
for (int i = 0; i < N; i++) {
if (fabs(y_cpu_res[i] - y_gpu_res[i]) > fabs(y_cpu_res[i] * 0.0001f))
errors++;
}
std::cout << errors << " errors" << std::endl;
CHECK( cudaFree(x_gpu));
CHECK( cudaFree(y_gpu));
CHECK_BLAS( cublasDestroy(handle));
return errors;
}