@article{10902/25067,
year = {2021},
month = {9},
url = {http://hdl.handle.net/10902/25067},
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.},
organization = {Acknowledgements This work has been supported by the Spanish Science and Technology Commission under contract PID2019-105660RB-C22 and the European HiPEAC Network of Excellence.},
publisher = {Kluwer Academic Publishers},
publisher = {Journal of Supercomputing, 2021, 77(9), 10053 - 10064},
title = {Performance and energy task migration model for heterogeneous clusters},
author = {Stafford Fernández, Esteban and Bosque Orero, José Luis},
}