mirror of
https://github.com/NVIDIA/cuda-samples.git
synced 2024-11-24 19:39:17 +08:00
256 lines
7.2 KiB
C++
256 lines
7.2 KiB
C++
/* Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
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*
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions
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* are met:
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* * Redistributions of source code must retain the above copyright
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* notice, this list of conditions and the following disclaimer.
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* * Redistributions in binary form must reproduce the above copyright
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* notice, this list of conditions and the following disclaimer in the
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* documentation and/or other materials provided with the distribution.
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* * Neither the name of NVIDIA CORPORATION nor the names of its
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* contributors may be used to endorse or promote products derived
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* from this software without specific prior written permission.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
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* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
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* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
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* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
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* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
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* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
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* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
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* OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
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* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
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* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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*/
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/* This example demonstrates how to use the CUBLAS library
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* by scaling an array of floating-point values on the device
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* and comparing the result to the same operation performed
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* on the host.
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*/
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/* Includes, system */
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#include <stdio.h>
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#include <stdlib.h>
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#include <string.h>
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/* Includes, cuda */
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#include <cublas_v2.h>
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#include <cuda_runtime.h>
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#include <helper_cuda.h>
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/* Matrix size */
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#define N (275)
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/* Host implementation of a simple version of sgemm */
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static void simple_sgemm(int n, float alpha, const float *A, const float *B,
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float beta, float *C) {
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int i;
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int j;
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int k;
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for (i = 0; i < n; ++i) {
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for (j = 0; j < n; ++j) {
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float prod = 0;
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for (k = 0; k < n; ++k) {
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prod += A[k * n + i] * B[j * n + k];
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}
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C[j * n + i] = alpha * prod + beta * C[j * n + i];
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}
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}
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}
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/* Main */
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int main(int argc, char **argv) {
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cublasStatus_t status;
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float *h_A;
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float *h_B;
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float *h_C;
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float *h_C_ref;
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float *d_A = 0;
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float *d_B = 0;
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float *d_C = 0;
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float alpha = 1.0f;
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float beta = 0.0f;
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int n2 = N * N;
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int i;
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float error_norm;
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float ref_norm;
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float diff;
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cublasHandle_t handle;
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int dev = findCudaDevice(argc, (const char **)argv);
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if (dev == -1) {
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return EXIT_FAILURE;
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}
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/* Initialize CUBLAS */
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printf("simpleCUBLAS test running..\n");
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status = cublasCreate(&handle);
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if (status != CUBLAS_STATUS_SUCCESS) {
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fprintf(stderr, "!!!! CUBLAS initialization error\n");
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return EXIT_FAILURE;
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}
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/* Allocate host memory for the matrices */
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h_A = reinterpret_cast<float *>(malloc(n2 * sizeof(h_A[0])));
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if (h_A == 0) {
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fprintf(stderr, "!!!! host memory allocation error (A)\n");
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return EXIT_FAILURE;
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}
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h_B = reinterpret_cast<float *>(malloc(n2 * sizeof(h_B[0])));
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if (h_B == 0) {
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fprintf(stderr, "!!!! host memory allocation error (B)\n");
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return EXIT_FAILURE;
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}
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h_C = reinterpret_cast<float *>(malloc(n2 * sizeof(h_C[0])));
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if (h_C == 0) {
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fprintf(stderr, "!!!! host memory allocation error (C)\n");
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return EXIT_FAILURE;
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}
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/* Fill the matrices with test data */
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for (i = 0; i < n2; i++) {
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h_A[i] = rand() / static_cast<float>(RAND_MAX);
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h_B[i] = rand() / static_cast<float>(RAND_MAX);
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h_C[i] = rand() / static_cast<float>(RAND_MAX);
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}
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/* Allocate device memory for the matrices */
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if (cudaMalloc(reinterpret_cast<void **>(&d_A), n2 * sizeof(d_A[0])) !=
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cudaSuccess) {
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fprintf(stderr, "!!!! device memory allocation error (allocate A)\n");
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return EXIT_FAILURE;
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}
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if (cudaMalloc(reinterpret_cast<void **>(&d_B), n2 * sizeof(d_B[0])) !=
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cudaSuccess) {
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fprintf(stderr, "!!!! device memory allocation error (allocate B)\n");
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return EXIT_FAILURE;
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}
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if (cudaMalloc(reinterpret_cast<void **>(&d_C), n2 * sizeof(d_C[0])) !=
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cudaSuccess) {
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fprintf(stderr, "!!!! device memory allocation error (allocate C)\n");
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return EXIT_FAILURE;
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}
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/* Initialize the device matrices with the host matrices */
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status = cublasSetVector(n2, sizeof(h_A[0]), h_A, 1, d_A, 1);
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if (status != CUBLAS_STATUS_SUCCESS) {
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fprintf(stderr, "!!!! device access error (write A)\n");
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return EXIT_FAILURE;
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}
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status = cublasSetVector(n2, sizeof(h_B[0]), h_B, 1, d_B, 1);
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if (status != CUBLAS_STATUS_SUCCESS) {
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fprintf(stderr, "!!!! device access error (write B)\n");
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return EXIT_FAILURE;
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}
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status = cublasSetVector(n2, sizeof(h_C[0]), h_C, 1, d_C, 1);
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if (status != CUBLAS_STATUS_SUCCESS) {
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fprintf(stderr, "!!!! device access error (write C)\n");
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return EXIT_FAILURE;
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}
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/* Performs operation using plain C code */
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simple_sgemm(N, alpha, h_A, h_B, beta, h_C);
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h_C_ref = h_C;
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/* Performs operation using cublas */
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status = cublasSgemm(handle, CUBLAS_OP_N, CUBLAS_OP_N, N, N, N, &alpha, d_A,
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N, d_B, N, &beta, d_C, N);
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if (status != CUBLAS_STATUS_SUCCESS) {
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fprintf(stderr, "!!!! kernel execution error.\n");
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return EXIT_FAILURE;
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}
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/* Allocate host memory for reading back the result from device memory */
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h_C = reinterpret_cast<float *>(malloc(n2 * sizeof(h_C[0])));
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if (h_C == 0) {
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fprintf(stderr, "!!!! host memory allocation error (C)\n");
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return EXIT_FAILURE;
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}
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/* Read the result back */
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status = cublasGetVector(n2, sizeof(h_C[0]), d_C, 1, h_C, 1);
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if (status != CUBLAS_STATUS_SUCCESS) {
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fprintf(stderr, "!!!! device access error (read C)\n");
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return EXIT_FAILURE;
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}
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/* Check result against reference */
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error_norm = 0;
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ref_norm = 0;
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for (i = 0; i < n2; ++i) {
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diff = h_C_ref[i] - h_C[i];
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error_norm += diff * diff;
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ref_norm += h_C_ref[i] * h_C_ref[i];
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}
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error_norm = static_cast<float>(sqrt(static_cast<double>(error_norm)));
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ref_norm = static_cast<float>(sqrt(static_cast<double>(ref_norm)));
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if (fabs(ref_norm) < 1e-7) {
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fprintf(stderr, "!!!! reference norm is 0\n");
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return EXIT_FAILURE;
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}
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/* Memory clean up */
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free(h_A);
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free(h_B);
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free(h_C);
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free(h_C_ref);
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if (cudaFree(d_A) != cudaSuccess) {
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fprintf(stderr, "!!!! memory free error (A)\n");
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return EXIT_FAILURE;
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}
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if (cudaFree(d_B) != cudaSuccess) {
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fprintf(stderr, "!!!! memory free error (B)\n");
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return EXIT_FAILURE;
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}
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if (cudaFree(d_C) != cudaSuccess) {
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fprintf(stderr, "!!!! memory free error (C)\n");
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return EXIT_FAILURE;
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}
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/* Shutdown */
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status = cublasDestroy(handle);
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if (status != CUBLAS_STATUS_SUCCESS) {
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fprintf(stderr, "!!!! shutdown error (A)\n");
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return EXIT_FAILURE;
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}
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if (error_norm / ref_norm < 1e-6f) {
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printf("simpleCUBLAS test passed.\n");
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exit(EXIT_SUCCESS);
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} else {
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printf("simpleCUBLAS test failed.\n");
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exit(EXIT_FAILURE);
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}
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}
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