Use remote ccache in mac x86_64 build (#13418)

Fully cached rebuild appears to take 20m for the build step,
compared to 1h8m for the uncached build with remote cache writes
(attempts 2 and 1 of
[this workflow
run](https://github.com/openxla/iree/actions/runs/4886873002/jobs/8724117607)).
That's unfortunately quite a bit slower than when we had caching that
restored a full ccache directory previously (e.g.
[this
run](https://github.com/openxla/iree/actions/runs/4658305324/jobs/8243824546)).
The latter was disabled in https://github.com/openxla/iree/pull/12905
because the actions/cache restore was extremely unreliable, timing out
most of the time.

The latency difference appears to be due to the cache hit rate:

```
Cacheable calls:   4850 / 4865 (99.69%)
  Hits:            4734 / 4850 (97.61%)
    Direct:        4387 / 4734 (92.67%)
    Preprocessed:   347 / 4734 ( 7.33%)
  Misses:           116 / 4850 ( 2.39%)
Uncacheable calls:   15 / 4865 ( 0.31%)
Local storage:
  Cache size (GB): 2.94 / 4.00 (73.50%)
```

vs

```
Cacheable calls:    4922 / 4937 (99.70%)
  Hits:             4080 / 4922 (82.89%)
    Direct:         3729 / 4080 (91.40%)
    Preprocessed:    351 / 4080 ( 8.60%)
  Misses:            842 / 4922 (17.11%)
Uncacheable calls:    15 / 4937 ( 0.30%)
Local storage:
  Cache size (GiB):  0.0 /  5.0 ( 0.00%)
Remote storage:
  Hits:             4080 / 4922 (82.89%)
  Misses:            842 / 4922 (17.11%)
```

We'll need to debug why we're seeing the 17% cache miss rate (I could
wildly speculate), but this is still a sizable improvement.

Part of https://github.com/openxla/iree/issues/13028
1 file changed
tree: e0cbe989de2285d60f226017b7ff28a7db833d26
  1. .devcontainer/
  2. .github/
  3. benchmarks/
  4. build_tools/
  5. compiler/
  6. docs/
  7. experimental/
  8. integrations/
  9. lib/
  10. llvm-external-projects/
  11. runtime/
  12. samples/
  13. tests/
  14. third_party/
  15. tools/
  16. .bazel_to_cmake.cfg.py
  17. .bazelignore
  18. .bazelrc
  19. .bazelversion
  20. .clang-format
  21. .dockerignore
  22. .gitignore
  23. .gitmodules
  24. .pylintrc
  25. .style.yapf
  26. .yamllint.yml
  27. AUTHORS
  28. BUILD.bazel
  29. CITATION.cff
  30. CMakeLists.txt
  31. configure_bazel.py
  32. CONTRIBUTING.md
  33. LICENSE
  34. README.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

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.