How to add matrices dimension by dimension without using a loop?

Hi all,

I've got this huge loop that takes a lot of time to be computed:

for i1=1:xN
    for j1=1:zN
        for i2=1:xN
            for j2=1:zN
                for j3=1:zN
J(i1,j1,i2,j2,j3) = (ldp(i2,j2,j3) - ld(i1,j1,j2))*pdf_transp(i1,j1,i2,j2,j3);
                end
            end
        end
    end
end

xN and zN are 300 and 7 for now, but it easily takes several minutes to compute.

I have tried to use repmat and permute and then do something like this

ld_old =  permute(repmat(ld,[1 1 1 xN zN]),[1 2 4 3 5]);
ld_new = permute(repmat(ldp,[1 1 1 xN zN]),[4 5 1 2 3]);
J2 = (ld_new(:)-ld_old(:)).*pdf_transp(:);

That is much faster, but still pretty slow. Is there a more efficient way for this kind of operation?

Thanks!

[Stephen23]

Instead of using repmat, you might be able to use bsxfun and avoid this whole business. bsxfun can save a lot memory in these kind of situations, which speed things up.

Answer 1

[James Tursa]

Don't know if this will be faster than your repmat code, but try this:

J = bsxfun(@minus,reshape(ldp,1,1,i2,j2,j3),reshape(ld,i1,j1,1,j2,1)).*pdf_transp;

[Tintin Milou]

Very neat. Thanks, James. Just had to change the i2,j2, and so on to xN and zN.

[James Tursa]

Yes, that was a typo and good catch by you.

[Tintin Milou]

By the way, do you expect running the bsxfun on CUDA would improve the performance by quite a bit?