Could I use the `mxGPUArray` format data in the cuda kernel function?

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I am new in compiling the mexcuda. I am trying to use the mxGPUArray as inputs of cuda kernel. My sample.cu code is as below. It is a simple plus function. The inputs are two vectors in CPU. The output is one vector in CPU.
But it gives the error at the line of
% z[row] = x[row] * y[row] line error
error: expression must be a pointer to a complete object type
Must I use the cudaMemcpy function, with transfering the mxGPUArray* data to a double* format?
#include "mex.h"
#include "gpu/mxGPUArray.h"
__global__ void plus(mxGPUArray*x, mxGPUArray* y, mxGPUArray* z, int N)
{
int row = blockIdx.x*blockDim.x + threadIdx.x;
if (row < N)
{
z[row] = x[row] * y[row];% error is here
}
}
void mexFunction(int nlhs, mxArray *plhs[], int nrhs, mxArray const *prhs[])
{
mxGPUArray* d_x = mxGPUCopyFromMxArray(prhs[0]);
mxGPUArray* d_y = mxGPUCopyFromMxArray(prhs[1]);
int N = (int)(mxGPUGetNumberOfElements(d_x));
mxGPUArray* d_z = mxGPUCreateGPUArray(mxGPUGetNumberOfDimensions(d_x),
mxGPUGetDimensions(d_x),
mxGPUGetClassID(d_x),
mxGPUGetComplexity(d_x),
MX_GPU_DO_NOT_INITIALIZE);
// =========================================================================
// gpu computing
// =========================================================================
int const threadsPerBlock = 256;
int blocksPerGrid;
blocksPerGrid = (N + threadsPerBlock - 1) / threadsPerBlock;
plus <<<blocksPerGrid, threadsPerBlock>>>(d_x, d_y, d_z,N);
plhs[0] = mxGPUCreateMxArrayOnCPU(d_z);
mxGPUDestroyGPUArray(d_x);
mxGPUDestroyGPUArray(d_y);
mxGPUDestroyGPUArray(d_z);
}
I don't want to do many copy steps. So I did not transfer the mxGPUArray into another double array. Any suggestion would be appreciated. Thank you.

Answers (1)

Joss Knight
Joss Knight on 25 Jan 2021
Edited: Joss Knight on 25 Jan 2021
No. You have to get the GPU data pointer using the mxGPUGetData function.

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