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Performance and energy task migration model for heterogeneous clusters

Abstract: This article presents a set of linear regression models to predict the impact of task migration on different objectives, like performance and energy consumption. It allows to establish whether at a given moment the migration of a task is profitable in terms of performance or energy consumption. Also, it can be used to determine the best node to migrate a task depending on the objective. The model uses a small set of parameters that are easily measurable. It has been validated against a small heterogeneous cluster using the Slurm resource manager. The model captures the tendencies observed in the results of the experiments, with average relative errors below 3.5% in execution time and 2.5% in energy consumption.

 Fuente: Journal of Supercomputing, 2021, 77(9), 10053 - 10064

Editorial: Kluwer Academic Publishers

 Fecha de publicación: 01/09/2021

Nº de páginas: 12

Tipo de publicación: Artículo de Revista

 DOI: 10.1007/s11227-021-03663-1

ISSN: 0920-8542,1573-0484

Proyecto español: PID2019-105660RB-C22

Url de la publicación: https://doi.org/10.1007/s11227-021-03663-1