Port iree.runtime to nanobind. (#14214)

I believe that this should be a no-op for users. There is one minor API
change (the MappedMemory class no longer implements the buffer protocol,
but I've seen no evidence that this was actually used since it was a
less functional way to get a host ndarray).

More adventurous use of nanobind is possible in the future (i.e. using
`ndarray` and `dlpack` interop for sharing across frameworks), but using
that will most likely necessitate API changes, which I was working to
avoid.

Aside from relatively mechanical differences from pybind11, the main
issues were that the buffer protocol and array support was dropped in
nanobind. This required some direct coding against the C API to achieve
the same characteristics. I think this is actually an improvement as the
pybind11 implementations of these features was neither efficient nor
obvious what it was doing.

A build time dependency on `nanobind` is added. When building Python
wheels, this gets satisfied automatically. Otherwise, the docker images
have been updated to pre-install the necessary Python package. In
addition, there is now a build time dependency on NumPy headers, which
should already be installed (pybind11 vendored stripped down copies of
these headers in an effort to avoid this, but I opted to just do the
normal thing).

Nanobind's performance is [quite
compelling](https://nanobind.readthedocs.io/en/latest/benchmark.html)
and owes to a combination of favoring more efficient binding styles that
would basically be a rewrite in pybind11 and exclusive use of the new
Python 3.8+ vectorcall ABI. Since the runtime is performance critical
and the cost of Python calls is already quite visibly adding overhead on
traces, it makes sense to baseline on the most efficient implementation.
In addition, the compile-time savings seem to be real and the build is
noticeably faster (this was not a primary consideration, just a nice
bonus).
21 files changed
tree: 48a4d91c394c6ad289588922e0dc2a915974e14f
  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.