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2010-07-20 - Colloque/Article dans les actes avec comité de lecture - Anglais - 8 page(s)

Mezmaz Mohand , Lee Young Choon, Melab Nouredine, Talbi El-Ghazali, Zomaya Albert Y., "A Bi-objective Hybrid Genetic Algorithm to Minimize Energy Consumption and Makespan for Precedence-constrained Applications Using Dynamic Voltage Scaling" in IEEE Congress on Evolutionary Computation (IEEE CEC 2010) in conjunction with IEEE WCCI 2010, 25–32, Barcelone, Espagne, 2010

  • Codes CREF : Recherche opérationnelle (DI1150)
  • Unités de recherche UMONS : Mathématique et Recherche opérationnelle (F151)
  • Instituts UMONS : Institut des Sciences et du Management des Risques (Risques)

Abstract(s) :

(Anglais) 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.