写一个测试rocblas库中的SGEMM的方法

下面是一个简单的使用rocBLAS库中SGEMM函数进行矩阵乘法运算的示例代码：

#include <iostream>
#include <cstdlib>
#include <ctime>
#include "rocblas.h"

#define N 1024

int main()
{
    // 初始化rocBLAS库
    rocblas_handle handle;
    rocblas_create_handle(&handle);

    // 定义矩阵A、B、C
    float *A, *B, *C;
    A = (float*)malloc(N * N * sizeof(float));
    B = (float*)malloc(N * N * sizeof(float));
    C = (float*)malloc(N * N * sizeof(float));

    // 初始化矩阵A、B、C
    srand(time(NULL));
    for (int i = 0; i < N; i++) {
        for (int j = 0; j < N; j++) {
            A[i * N + j] = rand() / (float)RAND_MAX;
            B[i * N + j] = rand() / (float)RAND_MAX;
            C[i * N + j] = 0.0f;
        }
    }

    // 定义矩阵A、B、C在设备端上的指针
    float *dA, *dB, *dC;
    rocblas_status status;
    status = rocblas_status(rocblas_malloc((void**)&dA, N * N * sizeof(float)));
    status = rocblas_status(rocblas_malloc((void**)&dB, N * N * sizeof(float)));
    status = rocblas_status(rocblas_malloc((void**)&dC, N * N * sizeof(float)));

    // 将矩阵A、B复制到设备端
    status = rocblas_set_matrix(N, N, sizeof(float), A, N, dA, N);
    status = rocblas_set_matrix(N, N, sizeof(float), B, N, dB, N);

    // 设置矩阵A、B、C的参数
    float alpha = 1.0f, beta = 0.0f;
    rocblas_operation transa = rocblas_operation_none;
    rocblas_operation transb = rocblas_operation_none;
    rocblas_int lda = N, ldb = N, ldc = N;

    // 调用SGEMM函数进行矩阵乘法运算
    status = rocblas_sgemm(handle, transa, transb, N, N, N, &alpha, dA, lda, dB, ldb, &beta, dC, ldc);

    // 将矩阵C从设备端复制到主机端
    status = rocblas_get_matrix(N, N, sizeof(float), dC, N, C, N);

    // 输出矩阵C的前10行10列
    for (int i = 0; i < 10; i++) {
        for (int j = 0; j < 10; j++) {
            std::cout << C[i * N + j] << " ";
        }
        std::cout << std::endl;
    }

    // 释放内存
    rocblas_free(dA);
    rocblas_free(dB);
    rocblas_free(dC);
    free(A);
    free(B);
    free(C);

    // 销毁rocBLAS库句柄
    rocblas_destroy_handle(handle);

    return 0;
}

该示例代码中，首先初始化了rocBLAS库，并定义了三个大小为1024×1024的矩阵A、B、C，并对矩阵A、B进行了随机初始化。然后，分配了矩阵A、B、C在设备端上的内存，并将矩阵A、B从主机端复制到设备端。接下来，调用rocBLAS库中的SGEMM函数进行矩阵乘法运算，并将结果从设备端复制到主机端。最后，输出了矩阵C的前10行10列，并释放了内存。