Performance and energy efficiency analysis of 64-bit ARM using GAMESS

Abstract

Power efficiency is one of the key challenges facing the HPC co-design community, sparking interest in the ARM processor architecture as a low-power high-efficiency alternative to the high-powered systems that dominate today. Recent advances in the ARM architecture, including the introduction of 64-bit support, have only fueled more interest in ARM. While ARM-based clusters have proven to be useful for data server applications, their viability for HPC applications requires an in-depth analysis of on-node and inter-node performance. To that end, as a co-design exercise, the viability of a commercially available 64-bit ARM cluster is investigated in terms of performance and energy efficiency with the widely used quantum chemistry package GAMESS. The performance and energy efficiency metrics are also compared to a conventional x86 Intel Ivy Bridge system. A 2:1 Moonshot core to Ivy Bridge core performance ratio is observed for the GAMESS calculation types considered. Doubling the number of cores to complete the execution faster on the 64-bit ARM cluster leads to better energy efficiency compared to the Ivy Bridge system; i.e., a 32-core execution of GAMESS calculation has approximately the same performance and better energy-to-solution than a 16-core execution of the same calculation on the Ivy Bridge system.