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LOCATION:B306
DTSTART;TZID=America/New_York:20241118T160100
DTEND;TZID=America/New_York:20241118T160700
UID:submissions.supercomputing.org_SC24_sess751_ws_p3hpc112@linklings.com
SUMMARY:Performance and Scaling of HPC and AI Applications on Leadership C
 lass Intel, AMD, and NVIDIA GPU-Accelerated Systems
DESCRIPTION:JaeHyuk Kwack, Colleen Bertoni, Umesh Unnikrishnan, Riccardo B
 alin, Khalid Hossain, Yasaman Ghadar, Timothy Williams, Abhishek Bagusetty
 , Mathialakan Thavappiragasam, Väinö Hatanpää, Archit Vasan, John Tramm, a
 nd Scott Parker (Argonne National Laboratory (ANL))\n\nAs HPC systems move
  into the exascale era an increasing diversity of hardware is deployed. Th
 e last decade saw the ascendance of NVIDIA GPU-accelerated systems among t
 he largest scale HPC systems and spurred the need for application develope
 rs to consider approaches to performance portability that preserved develo
 per productivity. This challenge has been compounded in the last several y
 ears by the introduction of the first two exascale systems, Frontier  and 
 Aurora.  These systems utilize new GPUs, with Frontier utilizing the AMD M
 I-250X and Aurora the Intel Max 1550. In addition, these systems introduce
  new program models for applications. This study investigates the performa
 nce portability of 12 HPC/ML applications on three large scale HPC systems
  that utilize GPUs from different vendors: Frontier (AMD), Aurora (Intel),
  and Polaris (NVIDIA). The performance and portability of these applicatio
 ns was investigated on single GPU, single node, and multi-node scales on e
 ach of the three systems.\n\nTag: Performance Optimization, Programming Fr
 ameworks and System Software\n\nRegistration Category: Workshop Reg Pass\n
 \nSession Chairs: CJ Newburn (NVIDIA Corporation), Scott J. Parker (Argonn
 e National Laboratory (ANL)), John Pennycook (Intel Corporation), and Kenn
 eth Weiss (Lawrence Livermore National Laboratory (LLNL))\n\n
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