How to use cudaMalloc / cudaMemcpy for a pointer to a structure containing pointers?

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一整个雨季
一整个雨季 2020-12-09 06:59

I\'ve looked all around this site and others, and nothing has worked. I\'m resorting to posting a question for my specific case.

I have a bunch of matrices, and the

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  • 2020-12-09 07:55

    You have to be aware where your memory resides. malloc allocates host memory, cudaMalloc allocates memory on the device and returns a pointer to that memory back. However, this pointer is only valid in device functions.

    What you want could be achived as followed:

    typedef struct {
        int width;
        int height;
        float* elements;
    } Matrix;
    
    int main void() {
        int rows, cols, numMat = 2; // These are actually determined at run-time
        Matrix* data = (Matrix*)malloc(numMat * sizeof(Matrix));
    
        // ... Successfully read from file into "data" ...
        Matrix* h_data = (Matrix*)malloc(numMat * sizeof(Matrix));
        memcpy(h_data, data, numMat * sizeof(Matrix);
    
        for (int i=0; i<numMat; i++){
    
            cudaMalloc(&(h_data[i].elements), rows*cols*sizeof(float));
            cudaMemcpy(h_data[i].elements, data[i].elements,  rows*cols*sizeof(float)), cudaMemcpyHostToDevice);
    
         }// matrix data is now on the gpu, now copy the "meta" data to gpu
         Matrix* d_data;
         cudaMalloc(&d_data, numMat*sizeof(Matrix)); 
         cudaMemcpy(d_data, h_data, numMat*sizeof(Matrix));
         // ... Do other things ...
    }
    

    To make things clear: Matrix* data contains the data on the host. Matrix* h_data contains a pointer to the device memory in elements which can be passed to the kernels as parameters. The memory is on the GPU. Matrix* d_data is completly on the GPU and can be used like data on the host.

    in your kernel code you kann now access the matrix values, e.g.,

    __global__ void doThings(Matrix* matrices)
    {
          matrices[i].elements[0] = 42;
    }
    
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