[GPU][VectDist] Refactor multiReducOp lowering to reduce acc at the end. (#17974)

The main motivation behind this commit is to fix the numerics issue we
find in Attention GPU C++ pipeline. Where our output seems to be some
scale off from reference (i.e out = k * ref). Through experiments we
determine that the cause of the issue is the multiReducOp distribution,
which is required for scaling/merge computation.

Through analyzing of IR and experimentation, reducing the srcVector and
non constant accumulator at the same time with another multiDimReduction
seems to output numerically wrong values.

This commit fixes numerical issue by refactoring the distribution of
multireductionOp to 3 steps. First every thread locally reduce the
srcVector it holds with combiningIdentity as localInit. Second, it does
a subgroup/warp reduce amongs other threads. Finally, each thread does a
local reduction of the intermediate reduced data it has with the
accumulator it holds.

---------

Signed-off-by: Stanley Winata <stanley.winata@amd.com>
4 files changed
tree: ef5d69113aec10a17f3b0a2f08b702226f965da4
  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
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  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.