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opensecura / 3p / openxla / iree / 7812c776d5d57b13d80b6ae27f2dc86c73fddbcf
commit7812c776d5d57b13d80b6ae27f2dc86c73fddbcf[log] [tgz]
authorQuinn Dawkins <quinn.dawkins@gmail.com>Tue Aug 13 11:33:02 2024 -0400
committerGitHub <noreply@github.com>Tue Aug 13 11:33:02 2024 -0400
tree8f596e1069f86c16a335e4f943ae67b595922f5b
parent3901e6276a09f70bd3ceda0ca270df6ebf387780 [diff]
[Codegen][GPU] Add support for all other intrinsics to TileAndFuse (#18179)

This adds the ConcretizeMmaShapes pass to the LLVMGPUTileAndFuse
pipeline to add support for other intrinsic types, in particular MFMA
and WMMA variants that require reshaping of the accumulator to match
requirements of the layout.

This also reworks the reshaping code to use SingleSubgroupLayout instead
of VectorExt::PerDimLayoutAttr to drop an unneeded dialect dependency
and also simplify the IR for cases where reshaping is not needed. In
particular, when there is a unit `outer` dimension in a layout, no
additional reshaping is needed so we can omit the reshapes in such
cases. There is an option in the future to still do such reshaping so as
to pre-swizzle the data needed for the MMA during the store to shared
memory, but the details for how best to implement that are left as TODO.
9 files changed
tree: 8f596e1069f86c16a335e4f943ae67b595922f5b
  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. .dockerignore
  20. .git-blame-ignore-revs
  21. .gitattributes
  22. .gitignore
  23. .gitmodules
  24. .pre-commit-config.yaml
  25. .yamllint.yml
  26. AUTHORS
  27. BUILD.bazel
  28. CITATION.cff
  29. CMakeLists.txt
  30. configure_bazel.py
  31. CONTRIBUTING.md
  32. LICENSE
  33. MAINTAINERS.md
  34. README.md
  35. RELEASING.md
  36. 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.