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opensecura / 3p / openxla / iree / cf8b214994ce42cbf5863702407d89ef0701a558
commitcf8b214994ce42cbf5863702407d89ef0701a558[log] [tgz]
authorbjacob <benoitjacob@google.com>Fri Mar 31 22:45:30 2023 -0400
committerGitHub <noreply@github.com>Sat Apr 01 02:45:30 2023 +0000
tree3afa9beb3242d6696a77fc45f7f6801ecc311bbf
parent8c342c75a8f6aa1128a5e34d34c96b2ea68b8f1b [diff]
Avoid more sanitizer test timeouts (#12887)

More CI timeouts with TSAN in `pack_test` reported by @stellaraccident :

https://github.com/openxla/iree/actions/runs/4580136815/jobs/8088573298?pr=12884

This PR shrinks TSAN test latency on my desktop from 12 seconds to 0.85
second. I think it preserves the really important test coverage still.
The sole substantially large remaining shape `{9, 33}` is larger in
dimension 1 because that is the inner loop dim and that's where we want
to cast the most bugs. Values are just above a power of two. And the
64->16 change is because in practice when we do "pad a lot" that is
currently incidentally due to our pad-everything-by-16x16 approach to
make buffer allocations independent of materialize-encoding, so the 16
value is what we care about in practice.
2 files changed
tree: 3afa9beb3242d6696a77fc45f7f6801ecc311bbf
  1. .github/
  2. benchmarks/
  3. build_tools/
  4. compiler/
  5. docs/
  6. experimental/
  7. integrations/
  8. lib/
  9. llvm-external-projects/
  10. runtime/
  11. samples/
  12. tests/
  13. third_party/
  14. tools/
  15. .bazel_to_cmake.cfg.py
  16. .bazelignore
  17. .bazelrc
  18. .bazelversion
  19. .clang-format
  20. .dockerignore
  21. .gitignore
  22. .gitmodules
  23. .pylintrc
  24. .style.yapf
  25. .yamllint.yml
  26. AUTHORS
  27. BUILD.bazel
  28. CITATION.cff
  29. CMakeLists.txt
  30. configure_bazel.py
  31. CONTRIBUTING.md
  32. LICENSE
  33. README.md
  34. 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.