google / google/android-riscv64

Investigate the status of SLP vectorizer

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Description

As per [Super-Node SLP: Optimized Vectorization for Code Sequences Containing Operators and Their Inverse Elements](https://rcor.me/papers/cgo19snslp.pdf) the following benchmarks may have interesting code for SLP vectorization opportunities
- 433.milc
- 453.povray
- 454.calculix

We should just extract the interesting kernels and iterate on that if there are regressions compared to AArch64

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