Efficiency analysis for AI applications in HPC systems. Cases study : K-Means
Rivas, Jose Maria (Universitat Autònoma de Barcelona)
Wong, Álvaro (Universitat Autònoma de Barcelona)
Suppi Boldrito, Remo (Universitat Autònoma de Barcelona)
Luque, Emilio (Universitat Autònoma de Barcelona)
Rexachs del Rosario, Dolores Isabel (Universitat Autònoma de Barcelona)

Imprint:	Cham, Switzerland: Springer, 2023
Description:	8 pàg.
Abstract:	Currently, many AI applications require large-scale computing and memory to solve problems. The combination of AI applications and HPC sometimes does not efficiently use the available resources. Furthermore, a lot of idle times is caused by communication, resulting in increased runtime. This paper describes a methodology for AI parallel applications that analyses the performance and efficiency of these applications running on HPC resources to make decisions and select the most appropriate system resources. We validate our proposal by analysing the efficiency of the K-Means application obtaining an efficiency of 99% on a target machine.
Grants:	Agencia Estatal de Investigación PID2020-112496GB-I00
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Language:	Anglès
Series:	Lecture Notes in Computer Science ; 14074
Document:	Capítol de llibre ; recerca ; Versió acceptada per publicar
Subject:	AI applications ; HPC performance and efficiency ; PAS2P methodology
Published in:	Computational Science - ICCS 2023, 2023, p. 373-380, ISBN 978-3-031-36021-3

DOI: 10.1007/978-3-031-36021-3_39

Postprint 9 p, 536.5 KB

The record appears in these collections:
Research literature > UAB research groups literature > Research Centres and Groups (research output) > Engineering > HPC4EAS (High Performance Computing for Efficient Applications and Simulation Research Group)
Books and collections > Book chapters