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, 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.
| Original language | English |
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| Title of host publication | Proceedings of International Conference on High Performance Computing in Asia-Pacific Region Workshops, HPC Asia 2023 |
| Publisher | Association for Computing Machinery |
| Pages | 35-49 |
| Number of pages | 15 |
| ISBN (Electronic) | 9781450399890 |
| DOIs | |
| State | Published - Feb 27 2023 |
| Event | 2023 International Conference on High Performance Computing in Asia-Pacific Region Workshops, HPC Asia 2023 - Singapore, Singapore Duration: Feb 27 2023 → Mar 2 2023 |
Publication series
| Name | ACM International Conference Proceeding Series |
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Conference
| Conference | 2023 International Conference on High Performance Computing in Asia-Pacific Region Workshops, HPC Asia 2023 |
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| Country/Territory | Singapore |
| City | Singapore |
| Period | 02/27/23 → 03/2/23 |
Funding
This research used resources of the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy (Contract No. DE-AC05-00OR22725). Assessment of QMCPACK and ExaStar was supported by the Exascale Computing Project (17-SC-20-SC), a collaborative effort of the U.S. Department of Energy Office of Science and the National Nuclear Security Administration. VMD and NAMD work is supported by NIH grant P41-GM104601. S. H. Bryngelson acknowledges the use of the Extreme Science and Engineering Discovery Environment (XSEDE) under allocation TG-PHY210084, OLCF Summit allocation CFD154, hardware awards from the NVIDIA Academic Hardware Grants program, and support from the US Office of Naval Research under Grant No. N000142212519 (PM Dr. Julie Young). E. MacCarthy acknowledges Yang Zhang of University of Michigan, Ann Arbor, for providing the I-TASSER code. Work on PIConGPU was partially funded by the Center of Advanced Systems Understanding which is financed by Germany’s Federal Ministry of Education and Research and by the Saxon Ministry for Science, Culture and Tourism with tax funds on the basis of the budget approved by the Saxon State Parliament. The work in SPH-EXA2 is supported by the Swiss Platform for Advanced Scientific Computing (PASC) project SPH-EXA2 (2021-2024) and as part of SKACH consortium through funding from the Swiss State Secretariat for Education, Research and Innovation (SERI). Notice: This manuscript has been authored in part by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).