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arXiv · 2209.09731

Application Experiences on a GPU-Accelerated Arm-based HPC Testbed

Abstract

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 built by GIGABYTE, each one equipped with a server-class Arm CPU from Ampere Computing and A100 data center GPU from NVIDIA Corp. The systems are connected together using Infiniband high-bandwidth low-latency 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.

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BibTeXRIS

Wael Elwasif, William Godoy, Nick Hagerty, J. Austin Harris, Oscar Hernandez, Balint Joo, Paul Kent, Damien Lebrun-Grandie, Elijah Maccarthy, Veronica G. Melesse Vergara, Bronson Messer, Ross Miller, Sarp Opal, Sergei Bastrakov, Michael Bussmann, Alexander Debus, Klaus Steinger, Jan Stephan, Rene Widera, Spencer H. Bryngelson, Henry Le Berre, Anand Radhakrishnan, Jefferey Young, Sunita Chandrasekaran, Florina Ciorba, Osman Simsek, Kate Clark Filippo Spiga, Jeff Hammond, John E. Stone. David Hardy, Sebastian Keller, Jean-Guillaume Piccinali. Christian Trott. 2022-09-20. Application Experiences on a GPU-Accelerated Arm-based HPC Testbed. https://doi.org/10.1145/3581576.3581621

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