Application Experiences on a GPU-Accelerated Arm-based HPC Testbed
Wael R Elwasif, William F. Godoy, Nick Hagerty, J. Austin Harris, Óscar Hernández, Bálint Joó, Paul R. C. Kent, Damien Lebrun-Grandié, Elijah MacCarthy, Veronica Melesse Vergara, Bronson Messer, Ross Miller, Sarp Oral, Sergei I. Bastrakov, Michael Bußmann, Alexander Debus, Klaus Steiniger, Jan Stephan, René Widera, Spencer H. Bryngelson · 2023
This paper assesses and reports the experience of ten teams working to port, validate, and benchmark several High Performance Computing applications on a novel GPU-accelerated Arm testbed system. The testbed consists of eight NVIDIA Arm HPC Developer Kit systems, each one equipped with a server-class Arm CPU from Ampere Computing and two data center GPUs from NVIDIA Corp. The systems are connected together using InfiniBand interconnect. The selected applications and mini-apps are written using several programming languages and use multiple accelerator-based programming models for GPUs such as CUDA, OpenACC, and OpenMP offloading. Working on application porting requires a robust and easy-to-access programming environment, including a variety of compilers and optimized scientific libraries. The goal of this work is to evaluate platform readiness and assess the effort required from developers to deploy well-established scientific workloads on current and future generation Arm-based GPU-accelerated HPC systems. The reported case studies demonstrate that the current level of maturity and diversity of software and tools is already adequate for large-scale production deployments.