I have the following large, very inefficient loop.
P is a [2000 x 200 x 5] matrix
D is a [2000 x 200 x 5] matrix
S is a [200 x 1005] matrix
PS is a [2000 x 1000 x 5] matrix
I want to compute the following loop:
for k=1:2000
for n=1:200
for t=1:5
P(k,n,t) = sum(S(n,t+1:t+1000) .* PS(k,1:1000,t));
end
end
end
Obviously this is very inefficient. I tried parfor
, but I would rather a vectorized solution. I tried couple of things with bsxfun
, but also never managed to get it working.
Thank you.
Here's an almost (almost because we still have a loop, but with only 5 iterations) vectorized approach using powerful matrix-multiplication
-
out = zeros(2000,200,5);
for t=1:size(P,3) %// size(P,3) = 5
out(:,:,t) = PS(:,:,t)*S(:,t+1:t+1000).';
end
Runtime tests and verify output -
%// Inputs
D = rand(2000,200,5);
S = rand(200,1005);
PS = rand(2000,1000,5);
disp('--------------------- No Matrix-mult-fun')
tic
P = zeros(2000,200,5);
for k=1:2000
for n=1:200
for t=1:5
P(k,n,t) = sum(S(n,t+1:t+1000) .* PS(k,1:1000,t));
end
end
end
toc
disp('--------------------- Fun fun Matrix-mult-fun')
tic
out = zeros(2000,200,5);
for t=1:size(P,3) %// size(P,3) = 5
out(:,:,t) = PS(:,:,t)*S(:,t+1:t+1000).';
end
toc
error_val = max(abs(P(:)-out(:)))
Output -
--------------------- No Matrix-mult-fun
Elapsed time is 70.223008 seconds.
--------------------- Fun fun Matrix-mult-fun
Elapsed time is 0.624308 seconds.
error_val =
1.08e-12