Arm meets Cloud: A Case Study of MPI Library Performance on AWS Arm-based HPC Cloud with Elastic Fabric Adapter

Abstract

Recent advances in HPC Cloud field has made multi-core high performance VM services more accessible. Emerging Arm based HPC systems are also receiving more attention. Amazon Web Service recently announced new c6gn instances with Gravition 2 Arm CPU on each node and support of Elastic Fabric Adapter, which make them the leading high performance Arm-based cloud system vendor. In this paper, we characterize the performance and capability of the AWS Arm architecture. We explore the performance optimization of current MPI libraries based on features of Arm-based cloud systems and Scalable Reliable Datagram protocol of Elastic Fabric Adapter and evaluate the impact of our optimization of high-performance MPI libraries. Our study shows that the performance optimization for MPI library on AWS Arm systems significantly improves the performance of MPI communication for both benchmark and application level. We gain up to 86% performance improvement in micro-benchmark level col-lective communication operations and up to 9% improvement in Weather Research and Forecasting application level. This paper provides a comprehensive performance evaluation for several popular MPI libraries on AWS Arm-based Cloud systems with EFA support. HPC application developers and users are able to get insights from our study to achieve better performance of their applications on Arm-based cloud systems with EFA support.