[DispatchCreation] Propagate tensor encodings outside dispatch regions (#24966)

Encoding propagation is currently tied to dispatch hoisting, which
prevents layout assignment from using the same rewrite rules on the
surrounding tensor graph.

Separate where propagation may happen from the rewrites themselves, and
add the function pass
`iree-dispatch-creation-propagate-data-tiling-encodings` for propagation
outside dispatches. Hoisting keeps its existing behavior. The new pass
stops at existing dispatches and block boundaries, and constant CSE
stays disabled because Flow regions do not materialize constants
themselves.

- `iree-dispatch-creation-propagate-encodings` runs in the dispatch-time
data-tiling pipeline and only swaps `set_encoding` with `tensor.cast`
producers, so adding these rewrites to it would change that pipeline.
They stay separate until bubbling through generic ops goes through the
encoding propagation interfaces (TODO(#20179)).
- Bubbling now stops at `set_encoding` ops whose encoding is not an
`EncodingAttr`, such as `#iree_encoding.padding`, instead of crashing.
`iree-dispatch-creation-hoist-encoding-ops` could already hit this
within dispatches; both passes have a regression test.

No pipeline runs the new pass yet. #24969 adds it to the experimental
early data-tiling route.

This is one of five PRs adding an experimental CPU path that
materializes data-tiling layouts before dispatch creation, so that
`linalg.mmt4d` and data-tiled convolutions fuse with their elementwise
epilogues and result unpacks.

Assisted by AI.
6 files changed
tree: 158f8dc30e8bf20872e33ef3ef8b6cda306203e4
  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. GOVERNANCE.md
  32. LICENSE
  33. MAINTAINERS.md
  34. MODULE.bazel
  35. README.md
  36. RELEASING.md
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.

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Releases notes are published on GitHub releases.

PackageRelease status
GitHub release (stable)GitHub Release
GitHub release (nightly)GitHub Release
iree-base-compilerPyPI version
iree-base-runtimePyPI version

For more details on the release process, see https://iree.dev/developers/general/release-management/.

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Operating systemBuild status
LinuxCI - Linux arm64 clang
macOSCI - macOS arm64 clang

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

DateTitleRecordingSlides
2025-06-10Data-Tiling in IREE: Achieving High Performance Through Compiler Design (AsiaLLVM)recordingslides
2025-05-17Introduction to GPU architecture and IREE's GPU CodeGen Pipelinerecordingslides
2025-02-12The Long Tail of AI: SPIR-V in IREE and MLIR (Vulkanised)recordingslides
2024-10-01Unveiling the Inner Workings of IREE: An MLIR-Based Compiler for Diverse Hardwarerecording
2021-06-09IREE Runtime Design Tech Talkrecordingslides
2020-08-20IREE CodeGen (MLIR Open Design Meeting)recordingslides
2020-03-18Interactive HAL IR Walkthroughrecording
2020-01-31End-to-end MLIR Workflow in IREE (MLIR Open Design Meeting)recordingslides

License

IREE is licensed under the terms of the Apache 2.0 License with LLVM Exceptions. See LICENSE for more information.