MAT_MAT_SHARED Tuning
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- Dominant language
- Jupyter Notebook
- Stars
- 135
- Forks
- 55
- Avg merge
- 4d 16h
- Merged PRs (30d)
- 5
Description
Try doing a tuning of MAT_MAT_SHARED where we run multiple blocks per output tile and atomically increment the output tile.
Contributor guide
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by locating the MAT_MAT_SHARED implementation and its associated performance or correctness checks in RAJAPerf. Read how output tiles are currently computed, then investigate the requested multiple-blocks-per-output-tile and atomic-increment approach. Done means the tuning is implemented for MAT_MAT_SHARED and its existing correctness and performance checks still pass.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- cpp
- Domain
- performance
- Issue type
- Refactor
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 35/100