DocumentCode
2334510
Title
A bi-objective hybrid genetic algorithm to minimize energy consumption and makespan for precedence-constrained applications using dynamic voltage scaling
Author
Mezmaz, Mohand ; Lee, Young Choon ; Melab, Nouredine ; Talbi, El-Ghazali ; Zomaya, Albert Y.
Author_Institution
Math. & Operational Res. Dept., Univ. of Mons, Mons, Belgium
fYear
2010
fDate
18-23 July 2010
Firstpage
1
Lastpage
8
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.
Keywords
genetic algorithms; parallel processing; power aware computing; scheduling; biobjective hybrid genetic algorithm; dynamic voltage scaling; energy consumption minimization; energy saving; heterogeneous computing system; makespan minimization; precedence-constrained parallel application; Electronic mail; Energy consumption; Schedules; Scheduling; Scheduling algorithm; Voltage control;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation (CEC), 2010 IEEE Congress on
Conference_Location
Barcelona
Print_ISBN
978-1-4244-6909-3
Type
conf
DOI
10.1109/CEC.2010.5586540
Filename
5586540
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