Support better tiling algorithms for ANE
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triaged
- Dominant language
- Python
- Stars
- 5k
- Forks
- 1.2k
- Avg merge
- 2d 10h
- Merged PRs (30d)
- 581
Description
🚀 The feature, motivation and pitch
Support better tiling algorithms for ANE in linear, SDPA, matmul, bmm, etc. We noticed that we can boost performance by explicitly splitting up ops in PyTorch, but ideally this would be done by the CoreML compiler.
Alternatives
No response
Additional context
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RFC (Optional)
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Contributor guide
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
Review the linked PyTorch PR #8715 and the listed targets—linear, SDPA, matmul, and bmm—to understand the current explicit splitting approach. The issue names no files or tests, and completion criteria for changing CoreML compiler tiling algorithms are not specified.
Written by the indexing model from the issue text.
Assessment
- Domain
- compilers, machine-learning, mobile-dev
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100