Remove the need for split_reduction match callback (#11795)

This match callback was introduced to replace the original "match all
generics/fills + split" approach, which itself required re-matching
because of:

1. `apply_patterns` invalidating the parent function handle and thus all
handles to nested ops;
2. `fuse_into_containing_op` not preserving the order of payload
operations associated with the handle (and rather returning the results
in the order in which they ended up being fused).

Remedy 1. by marking `apply_patterns` as only reading and not consuming
the function handle, thus avoiding its invalidation. This is made
possible by the implementation of `apply_patterns` using the rewrite
driver with tracking that preserves the handles even when the associated
operations were affected.

Remedy 2. by fusing one op at a time to obtain the handle to the op
after fusion. This hit an issue with canonicalization effectively fusing
a `fill` op into the loop when it is directly consumed, confusing the
fusion op. Work around it by performing fusion inside a
non-canonicalized sequence.

This allows us to remove the `split_reduction` matcher and related code,
as well as to simplify the transformation script by removing mutliple
`take_first` that became redundant.
6 files changed
tree: f0cef00fc47847fd51bf4792c14d3e5c421c5448
  1. .github/
  2. benchmarks/
  3. build_tools/
  4. compiler/
  5. docs/
  6. experimental/
  7. integrations/
  8. llvm-external-projects/
  9. runtime/
  10. samples/
  11. tests/
  12. third_party/
  13. tools/
  14. .bazelignore
  15. .bazelrc
  16. .bazelversion
  17. .clang-format
  18. .dockerignore
  19. .gitignore
  20. .gitmodules
  21. .pylintrc
  22. .style.yapf
  23. .yamllint.yml
  24. AUTHORS
  25. BUILD.bazel
  26. CITATION.cff
  27. CMakeLists.txt
  28. configure_bazel.py
  29. CONTRIBUTING.md
  30. LICENSE
  31. README.md
  32. 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

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

  • 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.