MATLAB: 3D gpuArray vs cells of 2D gpuArrays major speed difference!

gpuarrayParallel Computing Toolboxslicingspeed

Can anybody explain why these codes have drastically different runtimes?
I have a shared setup routine
clear all
y = gpuArray.rand(1000, 1000, 'single');
W = cell(1, 5);
WFull = gpuArray.zeros(1000, 1000, 5);
for j = 1:5
   W{j} = gpuArray.rand(1000, 1000, 'single');
   WFull(:,:,j) = W{j};
end
Version 1 (finishes in 1.4 seconds on my machine)
z = gpuArray.zeros(1000, 1000, 5);
tic
for i = 1:1000
   for j = 1:size(W)
      z(:,:,j) = W{j}*y;
   end
end
toc
vs. Version 2 (finishes in 39 seconds on my machine… 27x times slower)
z = gpuArray.zeros(1000, 1000, 5);
tic
for i = 1:1000
   for j = 1:size(WFull, 3)
      z(:,:,j) = WFull(:,:,j)*y;
   end
end
toc
Do you think that slicing large 3D gpuArrays is just really slow compared to looking up cell array values?

Best Answer

Do you think that slicing large 3D gpuArrays is just really slow compared to looking up cell array values?
Yes, it is faster to look-up a cell than to pull a slice out of a 3D array, and that's true for normal arrays as well, as long as there is a small number of slices/cells. Of course, you should really be including the time needed to allocate memory to each W{j} in your comparison.
Another reason is that you have a syntax error in your for-loop over W{j}. It's only doing 1 loop iteration instead of 5,
   >> for j=1:size(W), j, end 
j =
       1
This is biasing the comparison to some degree.
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