Fix broken KPM scalar optimization, use 5-arg mul! instead #72
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
Codecov Report
@@ Coverage Diff @@
## master #72 +/- ##
==========================================
+ Coverage 56.20% 56.72% +0.52%
==========================================
Files 15 15
Lines 2288 2267 -21
==========================================
Hits 1286 1286
+ Misses 1002 981 -21
Continue to review full report at Codecov.
|
threading cleanup transpose mul fix for A != I use thread buffers only when needed fix commented BLAS version activate BLAS codepath
|
It turns out the |
more stringent test comment [skip ci]
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Outdated suggestions cannot be applied.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.
The clever scalar version of the KPM iteration inherited from Elsa was broken. Since Julia 1.3 we have 5-argument
mul!that implements a similar scalar algorithm. It is also multithreaded to boot. This PR uses such facility, and fixes KPM in the process (I used the computation in https://discourse.julialang.org/t/kernel-polynomial-method/34240/3 as reference). A side effect is that the code is again much clearer and closer to the original algorithm.