Cloud benchmarking and performance analysis of an HPC application in Amazon EC2

被引:0
|
作者
Tamara Dancheva
Unai Alonso
Michael Barton
机构
[1] University of the Basque Country,Mechanical Engineering
[2] University of the Basque Country,Simulation of Wave Propagation
[3] Basque Center for Applied Mathematics,undefined
[4] Ikerbasque - Basque Foundation for Sciences,undefined
来源
Cluster Computing | 2024年 / 27卷
关键词
AWS; C5n.x18large; ParallelCluster; Benchmark; HPC; EFA;
D O I
暂无
中图分类号
学科分类号
摘要
Cloud computing platforms have been continuously evolving. Features such as the Elastic Fabric Adapter (EFA) in the Amazon Web Services (AWS) platform have brought yet another revolution in the High Performance Computing (HPC) world, further accelerating the convergence of HPC and cloud computing. Other public clouds also support similar features further fueling this change. In this paper, we show how and why the performance of a large-scale computational fluid dynamics (CFD) HPC application on AWS competes very closely with the one on Beskow—a Cray XC40 supercomputer at the PDC Center for High-Performance Computing - in terms of cost-efficiency with strong scaling up to 2304 processes. We perform an extensive set of micro and macro benchmarks in both environments and conduct a comparative analysis. Until as recently as 2020 these benchmarks have notoriously yielded unsatisfactory results for the cloud platforms compared with on-premise infrastructures. Our aim is to access the HPC capabilities of the cloud, and in general to demonstrate how researchers can scale and evaluate the performance of their application in the cloud.
引用
收藏
页码:2273 / 2290
页数:17
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