Using Arm Scalable Vector Extension to Optimize OPEN MPI Dong Zhong1,2, Pavel Shamis4, Qinglei Cao1,2, George Bosilca1,2, Shinji Sumimoto3, Kenichi Miura3, and Jack Dongarra1,2 1Innovative Computing Laboratory, The University of Tennessee, US 2fdzhong,
[email protected], fbosilca,
[email protected] 3Fujitsu Ltd, fsumimoto.shinji,
[email protected] 4Arm,
[email protected] Abstract— As the scale of high-performance computing (HPC) with extension instruction sets. systems continues to grow, increasing levels of parallelism must SVE is a vector extension for AArch64 execution mode be implored to achieve optimal performance. Recently, the for the A64 instruction set of the Armv8 architecture [4], [5]. processors support wide vector extensions, vectorization becomes much more important to exploit the potential peak performance Unlike other SIMD architectures, SVE does not define the size of target architecture. Novel processor architectures, such as of the vector registers, instead it provides a range of different the Armv8-A architecture, introduce Scalable Vector Extension values which permit vector code to adapt automatically to the (SVE) - an optional separate architectural extension with a new current vector length at runtime with the feature of Vector set of A64 instruction encodings, which enables even greater Length Agnostic (VLA) programming [6], [7]. Vector length parallelisms. In this paper, we analyze the usage and performance of the constrains in the range from a minimum of 128 bits up to a SVE instructions in Arm SVE vector Instruction Set Architec- maximum of 2048 bits in increments of 128 bits. ture (ISA); and utilize those instructions to improve the memcpy SVE not only takes advantage of using long vectors but also and various local reduction operations.