cublas_gbmv_example.cu

/*
 * Copyright 2020 NVIDIA Corporation.  All rights reserved.
 *
 * NOTICE TO LICENSEE:
 *
 * This source code and/or documentation ("Licensed Deliverables") are
 * subject to NVIDIA intellectual property rights under U.S. and
 * international Copyright laws.
 *
 * These Licensed Deliverables contained herein is PROPRIETARY and
 * CONFIDENTIAL to NVIDIA and is being provided under the terms and
 * conditions of a form of NVIDIA software license agreement by and
 * between NVIDIA and Licensee ("License Agreement") or electronically
 * accepted by Licensee.  Notwithstanding any terms or conditions to
 * the contrary in the License Agreement, reproduction or disclosure
 * of the Licensed Deliverables to any third party without the express
 * written consent of NVIDIA is prohibited.
 *
 * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
 * LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
 * SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE.  IT IS
 * PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
 * NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
 * DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
 * NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
 * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
 * LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
 * SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
 * DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
 * WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
 * ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
 * OF THESE LICENSED DELIVERABLES.
 *
 * U.S. Government End Users.  These Licensed Deliverables are a
 * "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
 * 1995), consisting of "commercial computer software" and "commercial
 * computer software documentation" as such terms are used in 48
 * C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
 * only as a commercial end item.  Consistent with 48 C.F.R.12.212 and
 * 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
 * U.S. Government End Users acquire the Licensed Deliverables with
 * only those rights set forth herein.
 *
 * Any use of the Licensed Deliverables in individual and commercial
 * software must include, in the user documentation and internal
 * comments to the code, the above Disclaimer and U.S. Government End
 * Users Notice.
 */

#include <cstdio>
#include <cstdlib>
#include <vector>

#include <cublas_v2.h>
#include <cuda_runtime.h>

#include "cublas_utils.h"

using data_type = double;

int main(int argc, char *argv[]) {
    cublasHandle_t cublasH = NULL;
    cudaStream_t stream = NULL;

    const int m = 2;
    const int n = 2;
    const int lda = m;

    /*
     *   A = | 1.0 2.0 |
     *       | 3.0 4.0 |
     *   x = | 5.0 6.0 |
     */

    const std::vector<data_type> A = {1.0, 3.0, 2.0, 4.0};
    const std::vector<data_type> x = {5.0, 6.0};
    std::vector<data_type> y(m, 0);
    const data_type alpha = 1.0;
    const data_type beta = 0.0;
    const int incx = 1;
    const int incy = 1;
    const int kl = 0;
    const int ku = 1;

    data_type *d_A = nullptr;
    data_type *d_x = nullptr;
    data_type *d_y = nullptr;

    cublasOperation_t transa = CUBLAS_OP_N;

    printf("A\n");
    print_matrix(m, n, A.data(), lda);
    printf("=====\n");

    printf("x\n");
    print_vector(x.size(), x.data());
    printf("=====\n");

    /* step 1: create cublas handle, bind a stream */
    CUBLAS_CHECK(cublasCreate(&cublasH));

    CUDA_CHECK(cudaStreamCreateWithFlags(&stream, cudaStreamNonBlocking));
    CUBLAS_CHECK(cublasSetStream(cublasH, stream));

    /* step 2: copy data to device */
    CUDA_CHECK(cudaMalloc(reinterpret_cast<void **>(&d_A), sizeof(data_type) * A.size()));
    CUDA_CHECK(cudaMalloc(reinterpret_cast<void **>(&d_x), sizeof(data_type) * x.size()));
    CUDA_CHECK(cudaMalloc(reinterpret_cast<void **>(&d_y), sizeof(data_type) * y.size()));

    CUDA_CHECK(cudaMemcpyAsync(d_A, A.data(), sizeof(data_type) * A.size(), cudaMemcpyHostToDevice,
                               stream));
    CUDA_CHECK(cudaMemcpyAsync(d_x, x.data(), sizeof(data_type) * x.size(), cudaMemcpyHostToDevice,
                               stream));

    /* step 3: compute */
    CUBLAS_CHECK(
        cublasDgbmv(cublasH, transa, m, n, kl, ku, &alpha, d_A, lda, d_x, incx, &beta, d_y, incy));

    /* step 4: copy data to host */
    CUDA_CHECK(cudaMemcpyAsync(y.data(), d_y, sizeof(data_type) * y.size(), cudaMemcpyDeviceToHost,
                               stream));

    CUDA_CHECK(cudaStreamSynchronize(stream));

    /*
     *   y = | 27.0 24.0 |
     */

    printf("y\n");
    print_vector(y.size(), y.data());
    printf("=====\n");

    /* free resources */
    CUDA_CHECK(cudaFree(d_A));
    CUDA_CHECK(cudaFree(d_x));
    CUDA_CHECK(cudaFree(d_y));

    CUBLAS_CHECK(cublasDestroy(cublasH));

    CUDA_CHECK(cudaStreamDestroy(stream));

    CUDA_CHECK(cudaDeviceReset());

    return EXIT_SUCCESS;
}