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opensecura / 3p / openxla / iree / e6ff0b99c8ba6ade02a8a44f06f7920f7033133a
commite6ff0b99c8ba6ade02a8a44f06f7920f7033133a[log] [tgz]
authorStanley Winata <68087699+raikonenfnu@users.noreply.github.com>Thu Aug 29 07:05:18 2024 -0700
committerGitHub <noreply@github.com>Thu Aug 29 15:05:18 2024 +0100
tree5c5d19c6bc7d6e6dce5c1798222944c2d3c3dc65
parentdfaf12c1a56f1ff69bda1fdb7a42399eb1c9d96e [diff]
[Codegen] Resolve constantOp with multiple layouts users. (#18354)

Main motivation is to handle distribution of constantOp who has users
with different layouts.

Original use case is to ensure we can distribute attention when the tile
size for M,K1,N is the same. Which means the init of 1st contract, and
IV's init uses the same constantOp.

Since constantOp can only hold a single layout, but multiple to_layout
ops with different layouts, for each user, there will be non resolved
to_layout op(s). only one of the to_layout op can be resolved properly,
the rest would be a "non trivial" resolution since layouts are
different.

To solve this issue, we introduce a mechanism that detect these cases
and make a copy of the arith.constant that get used by other users, when
we are trying to resolve for the current constantOp.

Signed-off-by: Stanley Winata <stanley.winata@amd.com>
2 files changed
tree: 5c5d19c6bc7d6e6dce5c1798222944c2d3c3dc65
  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.