I'd like to send a 3D array src
of size size
in each dimension, flattened into a 1D array of size length = size * size * size
, into a kernel, compute a result and store it in dst
. However, at the end, dst
improperly contains all 0s. Here is my code:
int size = 256;
int length = size * size * size;
int bytes = length * sizeof(float);
// Allocate source and destination arrays on the host and initialize source array
float *src, *dst;
cudaMallocHost(&src, bytes);
cudaMallocHost(&dst, bytes);
for (int i = 0; i < length; i++) {
src[i] = i;
}
// Allocate source and destination arrays on the device
struct cudaPitchedPtr srcGPU, dstGPU;
struct cudaExtent extent = make_cudaExtent(size*sizeof(float), size, size);
cudaMalloc3D(&srcGPU, extent);
cudaMalloc3D(&dstGPU, extent);
// Copy to the device, execute kernel, and copy back to the host
cudaMemcpy(srcGPU.ptr, src, bytes, cudaMemcpyHostToDevice);
myKernel<<<numBlocks, blockSize>>>((float *)srcGPU.ptr, (float *)dstGPU.ptr);
cudaMemcpy(dst, dstGPU.ptr, bytes, cudaMemcpyDeviceToHost);
I've left out my error checking of cudaMallocHost()
, cudaMalloc()
and cudaMemcpy()
for clarity. No error is triggered by this code in any case.
What is the correct use of cudaMalloc3D()
with cudaMemcpy()
?
Please let me know if I should post a minimal test case for the kernel as well, or if the problem can be found in the code above.