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opensecura / 3p / openxla / iree / b44581a390956a21c653200da4273d8d03d23571
commitb44581a390956a21c653200da4273d8d03d23571[log] [tgz]
authorStanley Winata <68087699+raikonenfnu@users.noreply.github.com>Wed Jun 05 10:27:05 2024 -0700
committerGitHub <noreply@github.com>Wed Jun 05 10:27:05 2024 -0700
tree74d1fd7fa5697637c8594f1313bc807e33eb178d
parent9d60462ebe1bd5dcd0cc8cb8ca7a5e45523c1bd4 [diff]
[LLVMGPU][ROCM][Layoutv1] Landing Implementation of WMMA on layoutV1 (#17580)

Introducing WMMA on layoutv1. This feature is required/a prerequisite
for getting FA2 on RDNA3 GPUs.
This PR brings:

1. WMMA on layoutV1
2. Ensuring VectorX is specified to prevent unexpected behavior for
"step" setting in SIMT index.
3. Update of amdgpu_distribute_vectors/distribution of contract such
that it follow the newer style of `set_contraction_layout_attributes`
for setting intrinsic types as opposed to the less safer method of
inferring intrinsic types.
4. Update of tests to match above.

Co-authored-by: Groverkss <groverkss@gmail.com>

---------

Co-authored-by: Kunwar Grover <groverkss@gmail.com>
10 files changed
tree: 74d1fd7fa5697637c8594f1313bc807e33eb178d
  1. .devcontainer/
  2. .github/
  3. build_tools/
  4. compiler/
  5. docs/
  6. experimental/
  7. integrations/
  8. lib/
  9. llvm-external-projects/
  10. runtime/
  11. samples/
  12. tests/
  13. third_party/
  14. tools/
  15. .bazel_to_cmake.cfg.py
  16. .bazelignore
  17. .bazelrc
  18. .bazelversion
  19. .clang-format
  20. .dockerignore
  21. .git-blame-ignore-revs
  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.

CI Status IREE Discord Status

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!

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.