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opensecura / 3p / openxla / iree / f0e8cda0776973feb5a8caeca86929211733eb64
commitf0e8cda0776973feb5a8caeca86929211733eb64[log] [tgz]
authorMax191 <44243577+Max191@users.noreply.github.com>Fri Aug 09 08:56:33 2024 -0700
committerGitHub <noreply@github.com>Fri Aug 09 15:56:33 2024 +0000
tree194660dce2c22a3d183c0aa26c888147f662e22b
parent1fddcd6429754fd0f92b22fb4f570ff768f21337 [diff]
[Codegen][IGEMM] Add new pass for IGEMM transformation with reshape propagation (#18161)

This PR adds a new pass to perform the IGEMM transformation in Codegen.
The new pass uses the `Conv2DToIm2colOp` patterns plus some reshape
propagation and cleanup patterns. The PR also adds a control function on
the `Conv2DToIm2colOp` patterns, in order to avoid transforming
configured operations.

This separates the `Conv2DToIm2colOp` transformation from the
codegen-specific IGEMM pipeline, and addresses an issue with fusions
that requires reshape propagation. When there are consumers of the
convolution op, the consumer needs to also be collapsed in order to tile
and fuse it with the GEMM.

Adding reshape propagation is just one solution to the fusion issue. The
other potential solution is to allow the im2col op to have multiple M
dimensions in its result, and create a multi-M contraction instead of
the collapsed version. This second solution is ideal as long as backends
are able to handle the multi-M contraction, but it requires more work to
change the im2col op semantics. For now this PR fixes the issue, and the
alternative solution is left as a TODO.

---------

Signed-off-by: Max Dawkins <max.dawkins@gmail.com>
11 files changed
tree: 194660dce2c22a3d183c0aa26c888147f662e22b
  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.