accelerate 3D matrix multiptication using bsxfun

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barak messica
barak messica 2024-7-6
评论： Walter Roberson 2024-7-6
Hi
I have athe following code
it takes forever to run, and disable my CPU in the prosess...
I'm looking for a way to make it run better (GPU is also an option)
norm_mode is 256x256 double matrix (X,Y) image
fields is 16384x15 complex double matrix (time,mode)
in the end' I need a 3D matrix take each norm_mode image will also be a function for time and suming all the modes- 3D matrix 256x256x16384
that is the total_field
do you have any sugestions on how to make it run better?
Thanks,
Barak
function total_field = BuildSpatialField(fields,fiber, sim, others)
total_field = zeros( newSize, newSize, length(others.t) ); % total_field(X,Y,t)
h = waitbar(0, 'calculate field...');
for ii=1:others.modes
norm_mode = % load new phi
tmp = bsxfun(@times, norm_mode, reshape(fields(:,ii),1,1,[]));
total_field = total_field + tmp;
waitbar(ii/others.modes, h, ['mode ' num2str(ii) ' from ' num2str(others.modes)]);
end
close(h);
end

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回答（1 个）

Viktor
Viktor 2024-7-6
256x256x16384 as double array needs around 8 Gb RAM and as complex double 16 Gb. Do you have that much memory? Matlab can take forever to tell you, it ran out of memory.
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Viktor
Viktor 2024-7-6
编辑：Walter Roberson 2024-7-6
Thanks for the hint.
There is no performance difference accessing single elements in 1xn, nx1 or 1x1xn vectors.
I think i came to the conclusion since matlab uses 1xn by default.
But i found out that extracting a column vector from a matrix is faster than extracting a row vector.
https://de.mathworks.com/matlabcentral/answers/216512-which-is-faster-a-row-vector-or-a-column-vector-can-anyone-answer-me-please#answer_178976
Walter Roberson
Walter Roberson 2024-7-6
@Viktor
As i understand bsxfun(@times, norm_mode, fields), it is the same as: norm_mode .* fields.
Not exactly
  • bxsfun is not supported for as many datatypes as implicit expansion is supported
  • historically it has been mixed as to whether bxsfun or implicit expansion is more efficient; there have been cases where bxsfun is notably more efficient, and there have been cases where implicit expansion is a bit more efficient.
So, the internal implementation is different between the two cases.
Mathworks is not putting effort into optimizing bxsfun, but is putting effort into optimizing implicit expansion.

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