Fix Lidar lag spike from RaycastLiDARSensor.cs #172
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
|
So too much division of jobs is not good. 🤔 |
Autumn60
approved these changes
Sep 28, 2024
It's the opposite: before, all calculations were carried out on a single job; now, by giving job's tasks with 256 raycasts, calculations are parallel and equaly distributed between jobs. |
|
Understood. |
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Outdated suggestions cannot be applied.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.
Fixed a performance bug when using lidar by changing the minimum raycast calculation per job.
As we see in the unity editor's profiling tool, there's a lag spike every time lidar run, and a single job seems to perform all the calculations.
After changing the
minCommandsPerJobparameter fromRaycastCommand.ScheduleBatchinsideRaycastLiDARSensor.cswith a constant value of256(arbitrary value), we can see an improvement: there are no more lag peaks, the frame rate is now stable and tasks are better distributed between jobs.