Fastest way for page-wise computation - FOR vs ARRAYFUN vs PAGEFUN

9 次查看(过去 30 天)
I'd like to know the fastest way to deal with a 3D array in a page-wise way. Suppose I have the following data:
rng(0);
data = randi([1, 10], 10, 10, 1000); % sample data
and I want to know the inverse matrix of each page of this data. I compared three approaches to compute this:
% Approach1 - FOR loop
tic;
data_inv1 = zeros(10,10,1000);
for ii = 1:size(data,3)
data_inv1(:,:,ii) = inv(data(:,:,ii));
end
time1 = toc;
% Approach2 - Arrayfun
tic;
data_inv2 = arrayfun(@(ii)inv(data(:,:,ii)), 1:size(data,3), 'UniformOutput', false);
time2 = toc;
% Approach3 - Pagefun
tic;
data_gpu = gpuArray(data);
data_inv3 = pagefun(@inv, data_gpu);
time3 = toc;
% Comparison of elapsed times
fprintf('FOR-loop: %.8f sec\n', time1);
fprintf('Arrayfun: %.8f sec\n', time2);
fprintf('Pagefun: %.8f sec\n', time3);
The results on my computer are shown below:
FOR-loop: 0.01121580 sec
Arrayfun: 0.01491200 sec
Pagefun: 0.01317000 sec
Surprisingly, the use of the for-loop was the fastest. I expected that pagefun will give me the fastest computation but that was not the case.
Has anyone tried different approaches to speedup the page-wise computation? Is there anyway to make a good use of pagefun?
  4 个评论
dpb
dpb 2022-5-7
Yes...sorry, I intended as the additional overhead with the higher-level constructs, not the inherent memcopy of addressing planes.
In theory, MATLAB should be able to address data(:,:,ii) in place without the explicit copy.
Joss Knight
Joss Knight 2022-5-9
What GPU do you have? I suspect pagefun will be faster if you process in single precision.

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