Efficient matrix operation: how to avoid for loop

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Hi all,
I need to speed up a matrix operation and don't know how.
Here's a toy example of what I need to do:
A = randi(10,[4,10])
A =
3 8 8 5 1 1 9 9 4 2
8 9 4 3 4 10 5 8 8 7
4 1 2 10 1 5 2 6 1 2
1 7 1 5 4 7 3 10 1 4
B = randi(10,[2,10])
B =
3 3 4 10 3 7 5 6 8 8
8 1 4 8 8 6 10 5 8 5
C = zeros(size(A,1),size(B,1),size(B,2));
for i = 1:size(B,2)
C(:,:,i) = A(:,i).*B(:,i)';
end
C(:,:,1)
ans =
9 24
24 64
12 32
3 8
In other words C is a 3 dimensional tensor and C(:,:,i) is a matrix in which the column k is A(:,i)*C(k,i).
How can I compute C (or compute and store the same informations of C in some other way) in a more efficient way, possibly avoiding the for loop?
Thanks

Accepted Answer

Allen
Allen on 24 Dec 2019
Roberto, this should help with consolidating your code as well as improving the overall performance. Benchtests that I ran were orders of magnitude faster when comparing to size(A) = [4, 1e+6] and size(B) = [2, 1e+6].
C = reshape(A,[size(A,1),1,size(A,2)]).*reshape(B,[1,size(B)]);

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