Google Git
Sign in
opensecura / 3p / openxla / iree / 998ed49bdb314e19e0c5b45474f1705082db28f1
commit998ed49bdb314e19e0c5b45474f1705082db28f1[log] [tgz]
authorHan-Chung Wang <hanhan0912@gmail.com>Tue Jul 30 10:54:06 2024 -0700
committerGitHub <noreply@github.com>Tue Jul 30 10:54:06 2024 -0700
treee6f63d474f981614a2430731b05d764e69973090
parent2c638f31a413a9d36a2b97a61fa0c179b8a62542 [diff]
[VMVX] Add support for arith.maxnumf and arith.minnumf lowering. (#18033)

Similar to what is done in CPU backend, it adds a ArithExpandOps pass to
the late stage of the pipeline. This drops the local llvm revert (i.e.,
https://github.com/llvm/llvm-project/commit/fa066687) because the VMVX
backend can emulate the ops.

The GPU test changes are because of the upstream commit. It uses
arith.maxnumf in softmax decomposition.

Note: the arith.maximum and arith.minimum ops are also expanded with the
change. They become a seq of cmp + select ops.

Existing local patches carried over:

- https://github.com/llvm/llvm-project/commit/f6431f0c
- https://github.com/llvm/llvm-project/commit/bbd4af5d

Fixes https://github.com/iree-org/iree/issues/17779

---------

Signed-off-by: hanhanW <hanhan0912@gmail.com>
5 files changed
tree: e6f63d474f981614a2430731b05d764e69973090
  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.