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
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;
}