Are we ready for broader adoption of ARM in the HPC community: Performance and Energy Efficiency Analysis of Benchmarks and Applications Executed on High-End ARM Systems

A set of benchmarks, including numerical libraries and real-world scientific applications, were run on several modern ARM systems (Amazon Graviton 3/2, Futjutsu A64FX, Ampere Altra, Thunder X2) and compared to x86 systems (Intel and AMD) as well as to hybrid Intel x86/NVIDIA GPUs systems. For benchmarking automation, the application kernel module of XDMoD was used. XDMoD is a comprehensive suite for HPC resource utilization and performance monitoring. The application kernel module enables continuous performance monitoring of HPC resources through the regular execution of user applications. It has been used on the Ookami system (one of the first USA-based Fujitsu ARM A64FX SVE 512 systems). The applications used for this study span a variety of computational paradigms: HPCC (several HPC benchmarks), NWChem (ab initio chemistry), Open Foam(partial differential equation solver), GROMACS (biomolecular simulation), AI Benchmark Alpha (AI benchmark) and Enzo (adaptive mesh refinement). ARM performance, while generally slower, was nonetheless shown in many cases to be comparable to current x86 counterparts and often outperforms previous generations of x86 CPUs. In terms of energy efficiency, which considers both power consumption and execution time, ARM was shown in most cases to be more energy efficient than x86 processors. In cases where GPU performance was tested, the GPU systems showed the fastest speed and the highest energy efficiency. Given the high core count per node, comparable performance, and competitive pricing, current high-end ARM CPUs are already a valid choice as a primary HPC system processor.