Google Git
Sign in
opensecura / 3p / openxla / iree / 006af5d072e1078a539dfdc11be3ab9a6dfa1129
commit006af5d072e1078a539dfdc11be3ab9a6dfa1129[log] [tgz]
authorLei Zhang <antiagainst@gmail.com>Tue May 21 09:38:02 2024 -0700
committerGitHub <noreply@github.com>Tue May 21 09:38:02 2024 -0700
treeeee386d7bf3bf5961ed45c735d76fcc1f07de27f
parenta36773a2420b48f0906c710389b0f9965504c10f [diff]
[GPU] Support specifying LLVMGPU backend target features (#17451)

This commit adds a new `features` field to the `#iree_gpu.target` to
allow specifying additional LLVMGPU backend target features, e.g.,
"+sramecc,+xnack" for HIP `gfx942`. The new features can be specified
via the `--iree-rocm-target-features` command-line option.

Along the way, dropped the hardcoded "+sramecc,-xnack" feature set for
all `gfx9*` targets--for both of them, from the AMDGPU doc
(https://llvm.org/docs/AMDGPUUsage.html), we have

> If not specified for code object V4 or above, generate code
> that can be loaded and executed in a process with either
> setting of SRAMECC (XNACK replay).

So that means it should be fine to be missing by default.

Fixes https://github.com/iree-org/iree/issues/17402
Progress towards https://github.com/iree-org/iree/issues/16341
10 files changed
tree: eee386d7bf3bf5961ed45c735d76fcc1f07de27f
  1. .devcontainer/
  2. .github/
  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. .git-blame-ignore-revs
  22. .gitignore
  23. .gitmodules
  24. .yamllint.yml
  25. AUTHORS
  26. BUILD.bazel
  27. CITATION.cff
  28. CMakeLists.txt
  29. configure_bazel.py
  30. CONTRIBUTING.md
  31. LICENSE
  32. MAINTAINERS.md
  33. README.md
  34. RELEASING.md
  35. 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.