Contiguous memory and relational operators

1 次查看(过去 30 天)
I have a 2D matrix of floats called data (approx size 1E5 x 2E2) and wish to test some conditions many times (>1e9 times) eg
data(i:j, h) <= k, where k is a float
This process is a real bottleneck in my code according to the profiler.
Here the author (Jan) seems to suggest running permute.m to make the memory contiguous before applying the inequality operator.
I am unclear how to order the permutation though. What have I missed? (or is the permute trick only valid in dimensions above 2?)
tmp = permute(data(i:j, h) , orderVec); %where does orderVec come from???
tmp <= k %this is now fast
  2 个评论
James Tursa
James Tursa 2013-2-22
The permute "trick" was mentioned because the other post had : for the trailing dimension. What is your exact situation for subscripting? Is it always of the form (i:j,h) with i, j, and h scalars but changing each iteration?
Matlab2010
Matlab2010 2013-3-5
编辑:Matlab2010 2013-3-5
yes thats correct, it is always of the form (i:j,h) with the scalars i, j, and h changing each iteration.
does this help at all?

请先登录,再进行评论。

采纳的回答

Jan
Jan 2013-2-22
The permute method is useful, when a large multi-dimensional array is indexed repeatedly. In the other thread it was P(M, 4, N) with large M and N. Then calling P(:,i,:) repeatedly consumes much more time than getting Q(:, :, i) after:
Q = permute(P, [1,3,2]);
In your case, the comparison could be performed once only:
comp = (data <= k);
And instead of comparing in a loop, the vector comp(i:j, h) can be used directly. But I assume this is not a dramatic improvement. More precise advices are possible if you post the relevant part of the code.

更多回答(0 个)

类别

Help CenterFile Exchange 中查找有关 Elementary Math 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