reduce number of threads in simple_test_parallel test function #153
+1
−1
Conversation
This file contains hidden or 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
Signed-off-by: Simon Davies <simongdavies@users.noreply.github.com>
dblnz
approved these changes
Jan 22, 2025
ludfjig
approved these changes
Jan 23, 2025
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
3 participants
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Outdated suggestions cannot be applied.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 latest KVM runner image causes the test
simple_test-parallelto fail. The failure is due to execution time of a function call taking longer than the default maximum execution time.This test currently creates 100 threads to test parallel execution, and, since 100 is an arbitrary number and the test is not a scalability test this PR resolves that issue by reducing the number of threads to 50.
Note that this issue does not appear to be related to #47 (or at least applying suggested mitigations for that issue does not fix this one).
#152 opened to capture the fact that we need some scalability benchmarks