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A Bi-objective Hybrid Genetic Algorithm to Minimize Energy Consumption and Makespan for Precedence-constrained Applications Using Dynamic Voltage Scaling
Mezmaz, Mohand; Lee, Young Choon; Melab, Nouredine et al.
2010
 

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Abstract :
[en] 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 meta-heuristic 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.
Disciplines :
Mathematics
Author, co-author :
Mezmaz, Mohand ;  Université de Mons > Faculté Polytechnique > Mathématique et Recherche opérationnelle
Lee, Young Choon
Melab, Nouredine
Talbi, El-Ghazali
Zomaya, Albert Y.
Language :
English
Title :
A Bi-objective Hybrid Genetic Algorithm to Minimize Energy Consumption and Makespan for Precedence-constrained Applications Using Dynamic Voltage Scaling
Publication date :
20 July 2010
Event name :
IEEE Congress on Evolutionary Computation (IEEE CEC 2010) in conjunction with IEEE WCCI 2010
Event place :
Barcelone, Spain
Event date :
2010
Research unit :
F151 - Mathématique et Recherche opérationnelle
Research institute :
R500 - Institut des Sciences et du Management des Risques
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