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Leveraging the SIMD capability of modern CPU architectures is mandatory totake full benefit of their increasing performance. To exploit this feature,binary executables must be explicitly vectorized by the developers or anautomatic vectorization tool. This why the compilation research community hascreated several strategies to transform a scalar code into a vectorizedimplementation. However, the majority of the approaches focus on regularalgorithms, such as affine loops, that can be vectorized with few datatransformations. In this paper, we present a new approach that allowautomatically vectorizing scalar codes with chaotic data accesses as long astheir operations can be statically inferred. We describe how our methodtransforms a graph of scalar instructions into a vectorized one using differentheuristics with the aim of reducing the number or cost of the instructions.Finally, we demonstrate the interest of our approach on various computationalkernels using Intel AVX-512 and ARM SVE.

Autovesk: Automatic vectorized code generation from unstructured static kernels using graph transformations