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opensecura / 3p / openxla / iree / d341128edf91ce9b032d16e7eca278f5fa4892a7
commitd341128edf91ce9b032d16e7eca278f5fa4892a7[log] [tgz]
authorMax191 <44243577+Max191@users.noreply.github.com>Wed Oct 02 08:59:43 2024 -0700
committerGitHub <noreply@github.com>Wed Oct 02 11:59:43 2024 -0400
treee079dde678989648141d328a2c6753b37bc3f653
parent66c339742cad5c207e487bcc6e90105eebca0daf [diff]
[ExternalInterfaces] Make fill non-hoistableLeafOp, hoist linalg init operands (#18634)

This PR changes the HoistableOpInterface implementation for LinalgOps to
make DPS init operands hoistable. If there is real computation on the
init of a linalg op, then we would want to hoist that computation. The
main way the current policy (not hoisting init operands) affects
hoisting today is by preventing linalg.fill ops from being hoisted into
splat constants, since the init operands are usually linalg.fill or
tensor.empty. Since we want to preserve the behavior of not hoisting
fills (and instead fusing them with consumers to handle in codegen), the
interface implementation now treats fill ops as non-HoistableLeafOps.

This PR disables the top-k test on rocm, since it exposed a bug in rocm
codegen, but we want to move progress forward on GPU data tiling. The
test should be added back once the bug is resolved.

---------

Signed-off-by: Max Dawkins <max.dawkins@gmail.com>
3 files changed
tree: e079dde678989648141d328a2c6753b37bc3f653
  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.