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opensecura / 3p / openxla / iree / db590705390f7182d8d329483585265ab5524dcf
commitdb590705390f7182d8d329483585265ab5524dcf[log] [tgz]
authorNirvedh Meshram <96096277+nirvedhmeshram@users.noreply.github.com>Fri Nov 01 11:26:56 2024 -0500
committerGitHub <noreply@github.com>Fri Nov 01 11:26:56 2024 -0500
treeec822aa6c9f88a99a0f3175931312df294ee37d7
parentbb542eee65fa0a498963df1f2ee2f205a3dd8bd0 [diff]
[GPU] Disable unaligned to instrinsic batch matmul codegen with vector distribute (#18935)

This path doesnt support all batch matmul shapes but tries to and fails 
e.g. https://github.com/iree-org/iree/issues/18601

So this PR makes this change because by default we should favor higher
functionality support over performance. Solution is to keep this path
behind a flag which is off by default.

Fixes : https://github.com/iree-org/iree/issues/18601

If we bail out here, we will go down SIMT (note that we do anyway for
non batch matmul GEMMs for such shapes) for now with Tile and Fuse
pipeline support planned for the future. In the time being models who
have shapes that are supported by this path can do so using the provided
flag. And tuners can always use this pipeline if it works for the shape.
We can also turn this on by default if we can add correct heuristics on
when it is okay to use this path.

---------

Signed-off-by: Nirvedh <nirvedh@gmail.com>
2 files changed
tree: ec822aa6c9f88a99a0f3175931312df294ee37d7
  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.