Exploring source-to-source compiler transformation of OpenMP SIMD constructs for Intel AVX and Arm SVE vector architectures

Patrick J. Flynn, Xinyao Yi, Yonghong Yan

Abstract: Over the past decade, SIMD (single instruction multiple data) or vector architectures have made significant advances, now existing across a wide range of devices from commodity CPUs to high performance computing (HPC) cores. Intel's AVX (Advanced Vector Extensions) architecture has been one of the most popular SIMD extensions to commodity and HPC CPUs from Intel. Over the past few years, Arm has made significant inroads with its new SVE (Scalable Vector Extension), used in the supercomputer of the top place on the Top500 list. As SIMD has become more advanced and more important, it has become equally important the compilers support these architecture extensions. In this paper, we present our approach of source-to-source compiler transformation of explicit vectorization constructs using the OpenMP SIMD directive. We present the design of a unified IR that is easily translated to AVX and SVE vector architectures. Finally, we conduct performance evaluations on Intel AVX and Arm SVE to demonstrate how this method of vectorization can bridge the gap between auto- and manual- vectorization.