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fuchsia / third_party / llvm-project / 315ba7740663208f8bc45a7e4f145dc1df79500c
commit315ba7740663208f8bc45a7e4f145dc1df79500c[log] [tgz]
authorAndrzej Warzyński <andrzej.warzynski@arm.com>Thu Sep 19 19:53:11 2024 +0100
committerGitHub <noreply@github.com>Thu Sep 19 19:53:11 2024 +0100
treed937bd7abf8cc946f19f418a3dec27ff444f341b
parentd1335fb86466221b0499db5fc8f158f1f64d9542 [diff]
[mlir][linalg] Vectorisation of tensor.extract - dynamic shapes (#100582)

This PR removes the assumption that reading from a dynamic tensor is
always a gather load:

```mlir
%extracted = tensor.extract %src[%c79, %3] : tensor<?x?xf32>
```

That assumption was originally introduced to simplify the implementation
and to reduce the number of cases to consider. Now that the
vectorisation of `tensor.extract` has been around for > 1 year and has
been quite stable, we can safely relax it.

This is a relatively small change - rather than using the parent linalg
Op to infer the target output shape (not possible with dynamic shapes),
the vectorizer will use the (previously constructed) output vector
shape instead.

As expected, the following test required updating (`vector.gather` ->
`vector.transfer_read`):
*
@masked_dynamic_vectorize_nd_tensor_extract_with_affine_apply_contiguous

Similar test for scalable vectors is also added.
3 files changed
tree: d937bd7abf8cc946f19f418a3dec27ff444f341b
  1. .ci/
  2. .github/
  3. bolt/
  4. clang/
  5. clang-tools-extra/
  6. cmake/
  7. compiler-rt/
  8. cross-project-tests/
  9. flang/
  10. libc/
  11. libclc/
  12. libcxx/
  13. libcxxabi/
  14. libunwind/
  15. lld/
  16. lldb/
  17. llvm/
  18. llvm-libgcc/
  19. mlir/
  20. offload/
  21. openmp/
  22. polly/
  23. pstl/
  24. runtimes/
  25. third-party/
  26. utils/
  27. .clang-format
  28. .clang-tidy
  29. .git-blame-ignore-revs
  30. .gitattributes
  31. .gitignore
  32. .mailmap
  33. CODE_OF_CONDUCT.md
  34. CONTRIBUTING.md
  35. LICENSE.TXT
  36. pyproject.toml
  37. README.md
  38. SECURITY.md
README.md

The LLVM Compiler Infrastructure

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Welcome to the LLVM project!

This repository contains the source code for LLVM, a toolkit for the construction of highly optimized compilers, optimizers, and run-time environments.

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