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opensecura / 3p / openxla / iree / 37c79f07d346d969bab825eef37d333c56c7f729
commit37c79f07d346d969bab825eef37d333c56c7f729[log] [tgz]
authorMaheshRavishankar <1663364+MaheshRavishankar@users.noreply.github.com>Tue Jun 27 11:31:33 2023 -0700
committerGitHub <noreply@github.com>Tue Jun 27 11:31:33 2023 -0700
tree9b7425c90593a7a71cc8a56ba667988d476dff2a
parentfc0dd6ba6899bad16f10ec1d1964592ff1695b0b [diff]
Add support for lowering ops that implement the `UKernelOpInterface` on the CUDA path. (#14101)

This change add support for lowering operations that implement the
`UKernelOpInterface` on the CUDA backend. This allows custom
dispatches to use ops that implement and be compiled down to CUDA.

Unlike the CPU side, the CUDA side needs more information than just
the number of workgroups to use. It also needs the workgroup size. To
allow specifying this, an #iree_codegen.export_config attribute is
added. This allows specifying the workgroup size to use on the custom
dispatch. This information is used to set the workgroup size to use
during `MaterializeInterfaces` in HAL.

An example of the bitcode usage is added with this PR. Since there are
no in-tree examples of CUDA micro-kernels, the bit code is linked
using the `iree-link-bitcode` (which is the
`iree-llvmcpu-link-bitcode` renamed).

Fixes #14028
32 files changed
tree: 9b7425c90593a7a71cc8a56ba667988d476dff2a
  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. README.md
  33. 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.