Google Git
Sign in
opensecura / 3p / openxla / iree / 9c857e4413d1464c03f2317bba36522046e21a40
commit9c857e4413d1464c03f2317bba36522046e21a40[log] [tgz]
authorBen Vanik <ben.vanik@gmail.com>Wed May 08 20:33:45 2024 -0700
committerBen Vanik <ben.vanik@gmail.com>Mon Jul 29 20:32:22 2024 -0700
treeb78a40d1267b67e4709eb17171eb72d594cbf6e5
parent324e4ccc286aac534d6d13ebcbf240d96c12e604 [diff]
Adding `#hal.device.alias` attribute for resolving device configs.
This allows for less verbose "I don't care, pick something for me"
attributes that are expanded into the full target devices and their
executable configurations. Resolution happens early in the process so
that any flags that may be influencing the resolved configurations are
captured and no longer required by the pipeline.

Tests and tooling could use these attributes in place of
`#hal.device.target` but would need to run the pass as part of their
pipeline in order to perform the expansion. Resolving in a pass
vs doing so inline also allows for signaling errors and passing in
scoped device target registries instead of relying on the globals that
are not available in API usage.
12 files changed
tree: b78a40d1267b67e4709eb17171eb72d594cbf6e5
  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.

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.