round reduction size up to nearest power of two to avoid overloading cache #65
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
|
Good catch, this is certainly ok. |
abergeron
added a commit
that referenced
this pull request
Aug 5, 2015
round reduction size up to nearest power of two to avoid overloading cache
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Hi, in
reduction.py,ReductionKernel._get_basic_kernelis cached according to its argumentsmaxlsandnd, wheremaxlsis the smaller of the reduction size andself.init_local_size(= 1024 on my machine). If there are a lot of small reductions, there will be many different versions of the basic kernel in the cache, too many to fit in the cache. However, one of the first things that the basic kernel does is to roundmaxlsup to the nearest power of two. This patch does the rounding up before caching so that there are at most lg(self.init_local_size) different versions of the basic kernel for each value ofnd. (It also does the rounding again afterwards, to avoid breaking anything.) I think this fixes the problem with small reductions without costing anything for larger reductions.