Efficient implementation for loops
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I have a for loop which is slowing down the performance, which I'm sure there is a way to speed it up but I don't know how.
Suppose you have two matrices
A = randn(4,2,10); B = randn(2,10);
The result you want is C of dimension 4 * 10. In a for loop implementation, it is:
for i = 1 : 10
C(:,i) = A(:,:,i) * B(:,i)
end
How can I get C without using for loops?
Thanks in advance
回答（1 个）
Sean de Wolski
2015-7-14
Preallocating C will make this much faster:
Before the loop:
C = zeros(4,10);
4 个评论
Tao Yang
2015-7-14
Sean de Wolski
2015-7-14
Yeah, it could be rewritten as a larger matrix multiplication with a few reshapes and permutes but why bother? It's already blazingly fast!
Let me make it a little bigger and time it:
A = randn(400,20,10000);
B = randn(20,10000);
tic
C = zeros(400,10000);
for i = 1:10000
C(:,i) = A(:,:,i)*B(:,i);
end
toc
So now I'm doing a whole lot more math in (on my wimpy laptop) ... drum roll
Elapsed time is 0.213792 seconds.
Less than a quarter of a second!
Loops aren't slow in MATLAB. Inefficiencies within loops like not preallocating slow MATLAB down.
Tao Yang
2015-7-14
Sean de Wolski
2015-7-16
Have you profiled it to see if that is the bottleneck?
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