将指针数组复制到设备内存中并返回 (CUDA)

Question

我试图在我的玩具示例中使用 cublas 函数 cublasSgemmBatched。在此示例中，我首先分配二维数组：大小为 [6][5] 的 h_AA, h_BB 和大小为 [6][[=] 的 h_CC 19=]]。之后我将它复制到设备，执行 cublasSgemmBatched 并尝试将数组 d_CC 复制回主机数组 h_CC。但是，我在设备到主机复制时遇到错误 (cudaErrorLaunchFailure)，我不确定我是否将数组正确复制到设备中：

int main(){
    cublasHandle_t handle;
    cudaError_t cudaerr;
    cudaEvent_t start, stop;
    cublasStatus_t stat;
    const float alpha = 1.0f;
    const float beta = 0.0f;
    float **h_AA, **h_BB, **h_CC;
    h_AA = new float*[6];
    h_BB = new float*[6];
    h_CC = new float*[6];
    for (int i = 0; i < 6; i++){
        h_AA[i] = new float[5];
        h_BB[i] = new float[5];
        h_CC[i] = new float[1];
        for (int j = 0; j < 5; j++){
            h_AA[i][j] = j;
            h_BB[i][j] = j;
        }
        h_CC[i][0] = 1;
    }
    float **d_AA, **d_BB, **d_CC;
    cudaMalloc(&d_AA, 6 * sizeof(float*));
    cudaMalloc(&d_BB, 6 * sizeof(float*));
    cudaMalloc(&d_CC, 6 * sizeof(float*));
    cudaerr = cudaMemcpy(d_AA, h_AA, 6 * sizeof(float*), cudaMemcpyHostToDevice);
    cudaerr = cudaMemcpy(d_BB, h_BB, 6 * sizeof(float*), cudaMemcpyHostToDevice);
    cudaerr = cudaMemcpy(d_CC, h_CC, 6 * sizeof(float*), cudaMemcpyHostToDevice);
    stat = cublasCreate(&handle);
    stat = cublasSgemmBatched(handle, CUBLAS_OP_N, CUBLAS_OP_N, 1, 1, 5, &alpha,
             (const float**)d_AA, 1, (const float**)d_BB, 5, &beta, d_CC, 1, 6);
    cudaerr = cudaMemcpy(h_CC, d_CC, 6 * sizeof(float*), cudaMemcpyDeviceToHost);
    cublasDestroy(handle);
}

因此此代码有效，但是最后一个 cudaerr returns cudaErrorLaunchFailure。我试图在 Github.

上遵循此示例代码

谢谢

P.S。我不明白的是，sizeof(float*) 是什么以及 cudaMalloc 如何知道每个数组需要多少内存（就像这里我只确定 1 维的大小）。

更新：我做到了！！：

cublasHandle_t handle;
cudaError_t cudaerr;
cudaEvent_t start, stop;
cublasStatus_t stat;
const float alpha = 1.0f;
const float beta = 0.0f;

float *h_A = new float[5];
float *h_B = new float[5];
float *h_C = new float[6];
for (int i = 0; i < 5; i++)
{
    h_A[i] = i;
    h_B[i] = i;
}



float **h_AA, **h_BB, **h_CC;
h_AA = (float**)malloc(6* sizeof(float*));
h_BB = (float**)malloc(6 * sizeof(float*));
h_CC = (float**)malloc(6 * sizeof(float*));
for (int i = 0; i < 6; i++){
    cudaMalloc((void **)&h_AA[i], 5 * sizeof(float));
    cudaMalloc((void **)&h_BB[i], 5 * sizeof(float));
    cudaMalloc((void **)&h_CC[i], sizeof(float));
    cudaMemcpy(h_AA[i], h_A, 5 * sizeof(float), cudaMemcpyHostToDevice);
    cudaMemcpy(h_BB[i], h_B, 5 * sizeof(float), cudaMemcpyHostToDevice);
}
float **d_AA, **d_BB, **d_CC;
cudaMalloc(&d_AA, 6 * sizeof(float*));
cudaMalloc(&d_BB, 6 * sizeof(float*));
cudaMalloc(&d_CC, 6 * sizeof(float*));
cudaerr = cudaMemcpy(d_AA, h_AA, 6 * sizeof(float*), cudaMemcpyHostToDevice);
cudaerr = cudaMemcpy(d_BB, h_BB, 6 * sizeof(float*), cudaMemcpyHostToDevice);
cudaerr = cudaMemcpy(d_CC, h_CC, 6 * sizeof(float*), cudaMemcpyHostToDevice);
stat = cublasCreate(&handle);
    stat = cublasSgemmBatched(handle, CUBLAS_OP_N, CUBLAS_OP_N, 1, 1, 5, &alpha, 
             (const float**)d_AA, 1, (const float**)d_BB, 5, &beta, d_CC, 1, 6);
    cudaerr = cudaMemcpy(h_CC, d_CC, sizeof(float), cudaMemcpyDeviceToHost);
    for (int i = 0; i < 6;i++)
        cudaMemcpy(h_C+i, h_CC[i], sizeof(float), cudaMemcpyDeviceToHost);
cublasDestroy(handle);

Answer 1

所以，我找到了答案（感谢@Robert Crovella）：为了创建 device array of pointers to device arrays（对于批处理函数），应该首先创建 host array of pointers to device arrays，然后复制它进入 device array of pointers to device arrays。转回host也是一样：应该用intermediate host array of pointers to device arrays.

cublasHandle_t handle;
cudaError_t cudaerr;
cudaEvent_t start, stop;
cublasStatus_t stat;
const float alpha = 1.0f;
const float beta = 0.0f;

float *h_A = new float[5];
float *h_B = new float[5];
float *h_C = new float[6];
for (int i = 0; i < 5; i++)
{
    h_A[i] = i;
    h_B[i] = i;
}



float **h_AA, **h_BB, **h_CC;
h_AA = (float**)malloc(6* sizeof(float*));
h_BB = (float**)malloc(6 * sizeof(float*));
h_CC = (float**)malloc(6 * sizeof(float*));
for (int i = 0; i < 6; i++){
    cudaMalloc((void **)&h_AA[i], 5 * sizeof(float));
    cudaMalloc((void **)&h_BB[i], 5 * sizeof(float));
    cudaMalloc((void **)&h_CC[i], sizeof(float));
    cudaMemcpy(h_AA[i], h_A, 5 * sizeof(float), cudaMemcpyHostToDevice);
    cudaMemcpy(h_BB[i], h_B, 5 * sizeof(float), cudaMemcpyHostToDevice);
}
float **d_AA, **d_BB, **d_CC;
cudaMalloc(&d_AA, 6 * sizeof(float*));
cudaMalloc(&d_BB, 6 * sizeof(float*));
cudaMalloc(&d_CC, 6 * sizeof(float*));
cudaerr = cudaMemcpy(d_AA, h_AA, 6 * sizeof(float*), cudaMemcpyHostToDevice);
cudaerr = cudaMemcpy(d_BB, h_BB, 6 * sizeof(float*), cudaMemcpyHostToDevice);
cudaerr = cudaMemcpy(d_CC, h_CC, 6 * sizeof(float*), cudaMemcpyHostToDevice);
stat = cublasCreate(&handle);
    stat = cublasSgemmBatched(handle, CUBLAS_OP_N, CUBLAS_OP_N, 1, 1, 5, &alpha, 
             (const float**)d_AA, 1, (const float**)d_BB, 5, &beta, d_CC, 1, 6);
    cudaerr = cudaMemcpy(h_CC, d_CC, sizeof(float), cudaMemcpyDeviceToHost);
    for (int i = 0; i < 6;i++)
        cudaMemcpy(h_C+i, h_CC[i], sizeof(float), cudaMemcpyDeviceToHost);
cublasDestroy(handle);

将指针数组复制到设备内存中并返回 (CUDA)

Copying array of pointers into device memory and back (CUDA)

arrays

pointers

cuda

cublas