How can i speed up the following?

2 vues (au cours des 30 derniers jours)
Bill Hannon
Bill Hannon le 25 Avr 2016
Commenté : Bill Hannon le 29 Avr 2016
Can anyone help me speed up what is written below? I have a large code and this routine, while seemingly fast, gets called a great deal.
a = rand(31,31);
TmTn = rand(301,301,31,31);
f = zeros(size(TmTn,1),size(TmTn,2));
[qe pe] = size(a);
for p = 1:pe
for q = 1:qe;
f = f + a(q,p).*TmTn(:,:,p,q);
end
end
Note: I have tried various sequences of permute, repmat, direct multiplication, moving the sum, parfor and reshape.
Thanks in advance, Bill
  2 commentaires
Adam
Adam le 28 Avr 2016
Have you run the profile on your full "large code" to determine how much of the total time is actually spent on this routine?
Bill Hannon
Bill Hannon le 28 Avr 2016
Yes. Several times. The script above gets called ~2000 times. It is the slowest (~0.5sec/call) portion of the large (~30min) code.

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Réponse acceptée

Roger Stafford
Roger Stafford le 29 Avr 2016
You can turn this into ordinary matrix multiplication. Since matlab is specially optimized for matrix multiplication, it might be faster.
a = rand(31,31);
TmTn = rand(301,301,31,31);
a2 = reshape(a.',[],1); % Transpose 'a' and make it a column vector
TmTn2 = reshape(TmTn,[],31^2); % Change TmTn to a 2D matrix
f = reshape(TmTn2*a2,301,301); % Use ordinary matrix multiplication and then reshape back
  1 commentaire
Bill Hannon
Bill Hannon le 29 Avr 2016
Superb & thank you. Thank you all. That was the reduction I needed.

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Plus de réponses (2)

Arnab Sen
Arnab Sen le 28 Avr 2016
Hi Bill, You can try to replace the loop by vectorization. Something like below:
a = rand(31,31); TmTn = rand(301,301,31,31);
f = zeros(size(TmTn,1),size(TmTn,2));
[qe pe] = size(a);
TmTn2=reshape(TmTn,301*31,301*31);
TmTn1=mat2cell(TmTn2,size(TmTn,1)*ones(1,p),size(TmTn,2)*ones(1,q));
b=a';
C= cellfun(@(x,y) x.*y, mat2cell(b,ones(1,pe),ones(1,qe)),TmTn1, 'UniformOutput',false);
f=sum(cat(3,C{:,:}),3);
Using 'perfor' is another option where we can multiple for loops in parallel. For more detail refer to the following link:
  2 commentaires
Adam
Adam le 28 Avr 2016
Modifié(e) : Adam le 28 Avr 2016
Be careful using cellfun if speed is your aim, it is almost always slower than a for loop, but in either case the profiler or a timeit wrapped around the two options should help to check that.
Working with cell arrays in general is a lot less performant than numeric arrays if you are able to use numeric arrays instead.
Bill Hannon
Bill Hannon le 28 Avr 2016
Thank you for the (any) suggestion(s). I tic/toced the current and suggest cellfun approach while in debug mode. The cellfun approach is 3 times slower than the for loop.

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Jan
Jan le 28 Avr 2016
This seems to be a problem for FEX: MMX or FEX: MTIMESX .
  1 commentaire
Bill Hannon
Bill Hannon le 28 Avr 2016
The MMX & MTIMESX documentation leads me to believe they focus on matrix products and not element by element multiplication. Am i mistaken?

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