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

1 次查看（过去 30 天）
Tintin Milou
Tintin Milou 2015-2-17
评论： Stephen23 2015-2-17
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!
  1 个评论
Stephen23
Stephen23 2015-2-17
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.

请先登录，再进行评论。

请先登录，再回答此问题。

采纳的回答

James Tursa
James Tursa 2015-2-17
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;
  3 个评论
显示 1更早的评论
Tintin Milou
Tintin Milou 2015-2-17
By the way, do you expect running the bsxfun on CUDA would improve the performance by quite a bit?

请先登录，再进行评论。

更多回答（0 个）

类别

在 Help Center 和 File Exchange 中查找有关 Logical 的更多信息

标签

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by