Ukernels: simplify the architecture-specific bitcode build. (#16126)

This PR basically re-does how we build and link architecture-specific
and generic bitcode, for CPU ukernels.

The main change is that we now build one separate ukernel bitcode file
for each CPU architecture, and it's the only thing that `iree-compile`
needs to load and link to. Before, it had to load and link together 3
different bitcode modules, two of which were actually compiled as
WebAssembly for genericity, and it involved weak symbols. Full inlining
is really important for performance here, and in this system, it
depended on two fragile mechanisms:
1. Reinterpreting a WebAssembly module as a native module.
2. Weak symbols.

That was done out of a concern for sharing generic code across
same-bitness architectures, but that turned out be substantially more
complex in both the ukernels and the compiler, and to suffer from
problems described in #16000, which this PR fixes. Namely, the inlining
across these modules and down to the calling dispatch function was
brittle, never worked outside of x86, and to make even that work, we had
to do some illegal target-attribute stripping that was effectively UB
and caused issues described in
https://github.com/llvm/llvm-project/issues/78206 (originally filed as a
LLVM bug but then understood to be caused by our own illegal
attribute-stripping).

So, we now build completely separate bitcode for each target CPU
architecture that we are supporting in `iree-compile`. At the moment,
that's roughly 20k of code for each additional architecture for which we
don't have dedicated optimized code paths. For comparison, each
architecture that does have dedicated code weighs roughly 100k. I found
that surprisingly large, until I remembered that IR is far more verbose
than object code. There are ways to control that if and when that
becomes a major concern:
* We could further trim the supported CPU architectures, but note that
we gain simplicity from not doing so at the moment.
* We could leave bitcode files separate rather than embedding them in
`iree-compile`, allowing each user to obtain their own for their target
architecture.
* We could just embed the ukernels *source* code, as pure C is so cheap
to compile - the main cost would be now having to essentially build/ship
`clang` as part of iree-compile, but supporting only C and not C++
shouldn't be that bad.
* One problem that that would also solve is that at the moment, for CPU
architectures for which `iree-compile` allows the user to pick from
multiple ABIs (looking at you, RISC-V --- you need to grow up, pick an
ABI and settle in life), compiling ukernels from source at that time
would make it trivial to have ukernels built for the right ABI. For now
in this PR we just pick whichever ABI our tests are currently using.

Note: this PR is broken into a few thematic commits to help reviewing.

Fixes #16000
20 files changed
tree: 7386b6adedc6b7cfb700606fb33b73f4e021a562
  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.

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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!

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