[PATCH] D98715: [LoopVectorize] Add support for scalable vectorization of induction variables

[David Sherwood via Phabricator via llvm-commits]

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This patch adds support for the vectorization of induction variables when
using scalable vectors, which required the following changes:

1. Removed assert from InnerLoopVectorizer::getStepVector.
2. Modified InnerLoopVectorizer::createVectorIntOrFpInductionPHI to use a runtime determined value for VF and removed an assert.
3. Modified InnerLoopVectorizer::buildScalarSteps to work for scalable vectors. I did this by calculating the full vector value for each Part of the unroll factor (UF) and caching this in the VP state. This means that we are always able to extract an arbitrary element from the vector if necessary. In addition to this, I also permitted the caching of the individual lane values themselves for the known minimum number of elements in the same way we do for fixed width vectors. This is a further optimisation that improves the code quality since it avoids unnecessary extractelement operations when extracting the first lane.
4. Added an assert to InnerLoopVectorizer::widenPHIInstruction, since while testing some code paths I noticed this is currently broken for scalable vectors.

Various tests to support different cases have been added here:

  Transforms/LoopVectorize/AArch64/sve-inductions.ll


Repository:
  rG LLVM Github Monorepo

https://reviews.llvm.org/D98715

Files:
  llvm/lib/Transforms/Vectorize/LoopVectorize.cpp
  llvm/test/Transforms/LoopVectorize/AArch64/sve-inductions.ll

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