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opensecura / 3p / openxla / iree / 03c744ead1482abde3ee9e70293215c5b557c629
commit03c744ead1482abde3ee9e70293215c5b557c629[log] [tgz]
authorMax191 <44243577+Max191@users.noreply.github.com>Fri Oct 25 16:37:27 2024 -0700
committerGitHub <noreply@github.com>Fri Oct 25 19:37:27 2024 -0400
treeb46b670914b58a236b7a939e18f5bdbda39f24cb
parent0c2c627747586ed39ce7b1f6bfc9d8b83c4a4e69 [diff]
[GPU] Support multiple contraction dims in MmaSchedules (#18720)

This adds support for multiple M, N, and K dims in problems when
deducing a GPUMMASchedule. The new heuristic is similar to the old one,
but works on pairs of M and N dims. For example:
```
tensor<M1xM0xK1xK0> * tensor<N1xN0xK1xK0> -> tensor<M1xN1xM0xN0>
```
This will try to distribute the seeded tile counts to `M0` and `N0`
(first attempting to distribute evenly, and then distributing to N
followed by N), and then distribute the residual counts to `M1` and
`N1`. The K tile counts will be partitioned to `K0` first, and then the
residual tile counts will be partitioned to `K1`.

This PR also updates the config selection logic for the TileAndFuse
pipeline to make use of the multiple contraction dimensions in mma
schedules.

---------

Signed-off-by: Max Dawkins <max.dawkins@gmail.com>
8 files changed
tree: b46b670914b58a236b7a939e18f5bdbda39f24cb
  1. .github/
  2. build_tools/
  3. compiler/
  4. docs/
  5. experimental/
  6. integrations/
  7. lib/
  8. llvm-external-projects/
  9. runtime/
  10. samples/
  11. tests/
  12. third_party/
  13. tools/
  14. .bazel_to_cmake.cfg.py
  15. .bazelignore
  16. .bazelrc
  17. .bazelversion
  18. .clang-format
  19. .git-blame-ignore-revs
  20. .gitattributes
  21. .gitignore
  22. .gitmodules
  23. .pre-commit-config.yaml
  24. .yamllint.yml
  25. AUTHORS
  26. BUILD.bazel
  27. CITATION.cff
  28. CMakeLists.txt
  29. configure_bazel.py
  30. CONTRIBUTING.md
  31. LICENSE
  32. MAINTAINERS.md
  33. README.md
  34. RELEASING.md
  35. WORKSPACE
README.md

IREE: Intermediate Representation Execution Environment

IREE (Intermediate Representation Execution Environment, pronounced as “eerie”) is an MLIR-based end-to-end compiler and runtime that lowers Machine Learning (ML) models to a unified IR that scales up to meet the needs of the datacenter and down to satisfy the constraints and special considerations of mobile and edge deployments.

See our website for project details, user guides, and instructions on building from source.

IREE Discord Status pre-commit OpenSSF Best Practices

Project Status

IREE is still in its early phase. We have settled down on the overarching infrastructure and are actively improving various software components as well as project logistics. It is still quite far from ready for everyday use and is made available without any support at the moment. With that said, we welcome any kind of feedback on any communication channels

Release status

PackageRelease status
GitHub release (stable)GitHub Release
GitHub release (nightly)GitHub Release
Python iree-compilerPyPI version
Python iree-runtimePyPI version

Build status

CI PkgCI

Host platformBuild status
LinuxCI - Linux x64 clang
CI - Linux arm64 clang
macOSCI - macOS x64 clang
WindowsCI - Windows x64 MSVC

For the full list of workflows see https://iree.dev/developers/general/github-actions/.

Communication Channels

Related Project Channels

  • MLIR topic within LLVM Discourse: IREE is enabled by and heavily relies on MLIR. IREE sometimes is referred to in certain MLIR discussions. Useful if you are also interested in MLIR evolution.

Architecture Overview

IREE Architecture IREE Architecture

See our website for more information.

Presentations and Talks

Community meeting recordings: IREE YouTube channel

  • 2021-06-09: IREE Runtime Design Tech Talk (recording and slides)
  • 2020-08-20: IREE CodeGen: MLIR Open Design Meeting Presentation (recording and slides)
  • 2020-03-18: Interactive HAL IR Walkthrough (recording)
  • 2020-01-31: End-to-end MLIR Workflow in IREE: MLIR Open Design Meeting Presentation (recording and slides)

License

IREE is licensed under the terms of the Apache 2.0 License with LLVM Exceptions. See LICENSE for more information.