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A bi-objective hybrid genetic algorithm to minimize energy consumption and makespan for precedence-constrained applications using dynamic voltage scaling

El-Ghazali Talbi 1 Mohand Mezmaz 2 Young Choon Lee 3 Nouredine Melab 1 Albert Zomaya 3
1 DOLPHIN - Parallel Cooperative Multi-criteria Optimization
LIFL - Laboratoire d'Informatique Fondamentale de Lille, Inria Lille - Nord Europe
2 LIFL - Laboratoire d'Informatique Fondamentale de Lille
3 Centre for Distributed and High Performance Computing
Abstract : Precedence-constrained parallel applications are one of the most typical application model used in scientific and engineering fields. Almost all efforts, on this kind of applications, have focused on the minimization of makespan (completion time). It is only recently that much attention has been paid to energy consumption. In this paper, we address the precedence-constrained parallel applications on heterogeneous computing systems (HCSs). We propose a new bi-objective hybrid genetic algorithm that takes into account, not only makespan, but also energy consumption. This metaheuristic adopts dynamic voltage scaling (DVS) to minimize energy consumption. Our study provides promising results showing the significance and potential of DVS. The experimental results from our comparative evaluation study confirm the superior performance of our approach over the other known heuristics on the two criteria energy saving and completion time.
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Conference papers
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https://hal.inria.fr/hal-00837546
Contributor : Talbi El-Ghazali Connect in order to contact the contributor
Submitted on : Saturday, June 22, 2013 - 6:53:08 PM
Last modification on : Thursday, January 20, 2022 - 5:27:53 PM

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CNRS | INRIA | LIFL | UNIV-LILLE3 | CRISTAL | CRISTAL-DOLPHIN

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El-Ghazali Talbi, Mohand Mezmaz, Young Choon Lee, Nouredine Melab, Albert Zomaya. A bi-objective hybrid genetic algorithm to minimize energy consumption and makespan for precedence-constrained applications using dynamic voltage scaling. WCCI 2010 - IEEE World Congress on Computational Intelligence, Jul 2010, Barcelona, Spain. ⟨10.1109/CEC.2010.5586540⟩. ⟨hal-00837546⟩

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