Can you do this calculation any faster?

2 次查看（过去 30 天）
Henrik
Henrik 2014-10-15
评论： Sean de Wolski 2014-10-22
Hi there
I am trying to optimize some code, an example is given below. In my code, v_ustar etc are calculated elsewhere, and depend on q. This piece of code needs to run in a quite large loop (larger than the 1:1000 given as example here), and I don't think vectorization of the entire loops is possible due to RAM issues. N is typically 16, but can be larger as well.
I use Ubuntu and MATLAB R2014a (I will probably upgrade to R2014b soon)
Thanks in advance!
N=16;
for q=1:1000
%generate some random test data
v_ustar=rand(2*N,N,N);
vstar_u=rand(2*N,N,N);
u_ustar=rand(2*N,N,N);
vstar_v=rand(2*N,N,N);
F=...
repmat(reshape(v_ustar,[2*N 1 N N]),[1 2*N 1 1]).*...
repmat(reshape(conj(vstar_u), [1 2*N N N]),[2*N 1 1 1])-...
repmat(reshape(u_ustar,[2*N 1 N N]),[1 2*N 1 1]).*...
repmat(reshape(conj(vstar_v), [1 2*N N N]),[2*N 1 1 1]);
F=reshape(F,4*N^2,[]).';
end
  4 个评论
显示 2更早的评论
Oleg Komarov
Oleg Komarov 2014-10-15
The only small improvement I can think with this amount of code is:
F =...
bsxfun(@times, reshape(v_ustar,[2*N 1 N N]), reshape(conj(vstar_u), [1 2*N N N])) -...
bsxfun(@times, reshape(u_ustar,[2*N 1 N N]), reshape(conj(vstar_v), [1 2*N N N]));
You could get rid of the `reshape()` if you store:
v_ustar(:,1,:,:) = v_ustar_list(q1,:,:,:)
and finally get to:
F =...
bsxfun(@times, v_ustar, conj(vstar_u)) -...
bsxfun(@times, u_ustar, conj(vstar_v));
Henrik
Henrik 2014-10-15
Thanks, this seems to give quite an increase in performance! If you post this as an answer I will accept it (I don't think comments can be accepted).

请先登录，再进行评论。

请先登录，再回答此问题。

采纳的回答

Sean de Wolski
Sean de Wolski 2014-10-15
编辑：Sean de Wolski 2014-10-15
Another (small) improvement you can make here is to pull some of the static computations out of the loop. For example
[2*N 1 N N]
Doesn't change at all so it's being recomputed 1000x. Instead, create a variable out of it outside of the loop and then reference this variable everywhere inside it.
What do you actually end up doing with F after the loop?
I also wouldn't be surprised if splitting the F calculation into a few separate lines might help the JIT accelerator.
  2 个评论
Henrik
Henrik 2014-10-21
Thanks, that did speed up the calculation a bit. Sorry I forgot to accept your answer.
Could you explain what you mean about splitting the calculation?
There's more background to what I'm trying to achieve here, if you're interested: http://www.mathworks.com/matlabcentral/answers/158214-find-zero-of-function-with-least-amount-of-iterations
Sean de Wolski
Sean de Wolski 2014-10-22
When you have a really long line of code like this:
F=...
repmat(reshape(v_ustar,[2*N 1 N N]),[1 2*N 1 1]).*...
repmat(reshape(conj(vstar_u), [1 2*N N N]),[2*N 1 1 1])-...
repmat(reshape(u_ustar,[2*N 1 N N]),[1 2*N 1 1]).*...
repmat(reshape(conj(vstar_v), [1 2*N N N]),[2*N 1 1 1]);
F=reshape(F,4*N^2,[]).';
The JIT might not do as good a job optimizing it. If you break each piece, i.e. each line of repmat, into its own variable and then multiply the four variables, it might do a better job optimizing each piece.

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 Loops and Conditional Statements 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