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2017 | OriginalPaper | Chapter

AMOSA with Analytical Tuning Parameters for Heterogeneous Computing Scheduling Problem

Authors : Héctor Joaquín Fraire Huacuja, Juan Frausto-Solís, J. David Terán-Villanueva, José Carlos Soto-Monterrubio, J. Javier González Barbosa, Guadalupe Castilla-Valdez

Published in: Nature-Inspired Design of Hybrid Intelligent Systems

Publisher: Springer International Publishing

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Abstract

In this paper, the analytical parameter tuning for the Archive Multi-objective Simulated Annealing (AMOSA) is described. The analytical tuning method yields the initial and final temperature, and the maximum metropolis length. The analytically tuned AMOSA is used to solve the Heterogeneous Computing Scheduling Problem with independent tasks and it is compared versus the AMOSA without parameter tuning. We approach this problem as multi-objective, considering the makespan and the energy consumption. Also, in the last years this problem has gained importance due to the energy awareness in high performance computing centers (HPCC). The hypervolume, generational distance, and spread metrics were used in order to measure the performance of the implemented algorithms.

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Metadata
Title
AMOSA with Analytical Tuning Parameters for Heterogeneous Computing Scheduling Problem
Authors
Héctor Joaquín Fraire Huacuja
Juan Frausto-Solís
J. David Terán-Villanueva
José Carlos Soto-Monterrubio
J. Javier González Barbosa
Guadalupe Castilla-Valdez
Copyright Year
2017
Book
Nature-Inspired Design of Hybrid Intelligent Systems

Print ISBN: 978-3-319-47053-5

Electronic ISBN: 978-3-319-47054-2

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-47054-2_46

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