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An Energy-Efficient Scheduling Algorithm Using Dynamic Voltage Scaling for Parallel Applications on Clusters

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5 Author(s)
Xiaojun Ruan ; Department of Computer Science and Software Engineering, Auburn University, Auburn, AL 36849. ; Xiao Qin ; Ziliang Zong ; Kiranmai Bellam
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In the past decade cluster computing platforms have been widely applied to support a variety of scientific and commercial applications, many of which are parallel in nature. However, scheduling parallel applications on large scale clusters is technically challenging due to significant communication latencies and high energy consumption. As such, shortening schedule length and conserving energy consumption are two major concerns in designing economical and environmentally friendly clusters. In this paper, we propose an energy-efficient scheduling algorithm (TDVAS) using the dynamic voltage scaling technique to provide significant energy savings for clusters. The TDVAS algorithm aims at judiciously leveraging processor idle times to lower processor voltages (i.e., the dynamic voltage scaling technique or DVS), thereby reducing energy consumption experienced by parallel applications running on clusters. Reducing processor voltages, however, can inevitably lead to increased execution times of parallel task. The salient feature of the TDVAS algorithm is to tackle this problem by exploiting tasks precedence constraints. Thus, TDVAS applies the DVS technique to parallel tasks followed by idle processor times to conserve energy consumption without increasing schedule lengths of parallel applications. Experimental results clearly show that the TDVAS algorithm is conducive to reducing energy dissipation in large-scale clusters without adversely affecting system performance.

Published in:

Computer Communications and Networks, 2007. ICCCN 2007. Proceedings of 16th International Conference on

Date of Conference:

13-16 Aug. 2007