Autovesk: Automatic vectorized code generation from unstructured static kernels using graph transformations
Abstract
Leveraging the SIMD capability of modern CPU architectures is mandatory to take full advantage of their increased performance.
To exploit this capability, binary executables must be vectorized, either manually by developers or automatically by a tool. For this
reason, the compilation research community has created several strategies to transform a scalar code into a vectorized implementation.
However, most existing automatic vectorization techniques in modern compilers are designed for regular codes, leaving irregular
applications with non-contiguous data access patterns at a disadvantage. We present in this paper a new tool, Autovesk, that
automatically generates vectorized code from scalar code, specifically targeting irregular data access patterns. We describe how our
method transforms a graph of scalar instructions into a vectorized one using different heuristics to reduce the number or cost of
the instructions. Finally, we demonstrate the effectiveness of our approach on various computational kernels using Intel AVX-512
and ARM SVE. We compare the speedups of Autovesk vectorized code over GCC, Clang LLVM and Intel automatic vectorization
optimizations. We achieve competitive results in linear kernels and up to 11x speedups in irregular ones.
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