use autotuning for CUDA kernels by default #82
Merged
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
JuliaGPU/KernelAbstractions.jl#206 added the ability to automatically tune the workgroupsize of CUDA kernels. This PR stops hardcoding a default workgroupsize and lets KernelAbstractions handle that. This does change the workgroupsize from being statically sized to being dynamically sized, but in my testing, even with fairly small workgroupsizes, that didn't really make a difference.
Open
|
Cool, thanks for having a look. Should I be surprised that CI passes even though the KernelAbstractions.jl update isn't tagged yet? |
|
Previously if you passed |
|
That PR should now be in the latest KernelAbstractions release, so this should be ready to go barring any other concerns. |
mcabbott
reviewed
Feb 9, 2021
Co-authored-by: Michael Abbott <32575566+mcabbott@users.noreply.github.com>
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Outdated suggestions cannot be applied.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.
JuliaGPU/KernelAbstractions.jl#206 added the ability to automatically tune the workgroupsize of CUDA kernels. This PR stops hardcoding a default workgroupsize and lets KernelAbstractions handle that. This does change the workgroupsize from being statically sized to being dynamically sized, but in my testing, even with fairly small workgroupsizes, that didn't really make a difference.