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Performance and Scaling of HPC and AI Applications on Leadership Class Intel, AMD, and NVIDIA GPU-Accelerated Systems
DescriptionAs HPC systems move into the exascale era an increasing diversity of hardware is deployed. The last decade saw the ascendance of NVIDIA GPU-accelerated systems among the largest scale HPC systems and spurred the need for application developers to consider approaches to performance portability that preserved developer productivity. This challenge has been compounded in the last several years by the introduction of the first two exascale systems, Frontier and Aurora. These systems utilize new GPUs, with Frontier utilizing the AMD MI-250X and Aurora the Intel Max 1550. In addition, these systems introduce new program models for applications. This study investigates the performance 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 applications was investigated on single GPU, single node, and multi-node scales on each of the three systems.
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