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opensecura / 3p / openxla / iree / ed32801d29a3d9a4855165df6e95175615662e14
commited32801d29a3d9a4855165df6e95175615662e14[log] [tgz]
authorbjacob <benoitjacob@google.com>Wed Nov 08 16:40:12 2023 -0500
committerGitHub <noreply@github.com>Wed Nov 08 16:40:12 2023 -0500
tree2e6b6322dcedfc13ca420c46f00f2535bb4372f5
parent3e2ae27c1d9a4b67bd80c55330882831cf4da3b8 [diff]
Resolve `host` CPU to `generic` outside of x86 (#15481)

Following https://github.com/openxla/iree/pull/15477, `cpu` is treated
as a x86-only thing, except for the special value `host` that gets
resolved to the actual host CPU and CPU features.

JitGlobals creates a host target, that gets resolved accordingly. The
resolved CPU is then recorded in a `hal.devices.targets` attribute. If
the CPU field is set to the actual host CPU identifier there, then that
will trigger the error message about that being a x86-only thing:

```
error: Resolution of target CPU to target CPU features is not implemented on this target architecture. Pass explicit CPU features instead of a CPU on this architecture, or implement that.
```

So this needs to be left empty in that case. No functional
difference, as that CPU is just ignored anyway (which is what the error
message is about).
1 file changed
tree: 2e6b6322dcedfc13ca420c46f00f2535bb4372f5
  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

License

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