Energy-Efficient Scheduling for Parallel Applications Running on Heterogeneous Clusters Ziliang Zong†, Xiao Qin†*, Xiaojun Ruan†, Kiranmai Bellam†, Mais Nijim‡, and Mohamed Alghamdi§ †Department of Computer Science and Software Engineering Auburn University, Auburn, AL 36849 {zzong, xqin, xruan, kbellam}@eng.auburn.edu ‡Department of Computer Science University of Southern Mississippi, Hattiesburg, MS 39406 mnijim@usm.edu §Department of Computer Science New Mexico Institute of Mining and Technology, Socorro, NM 87801   High performance clusters have been widely used to provide amazing computing capability for both commercial and scientific applications. However, huge power consumption has prevented the further application of large-scale clusters. Designing energy-efficient scheduling algorithms for parallel applications running on clusters, especially on the high performance heterogeneous clusters, is highly desirable. In this regard, we propose a novel scheduling strategy called energy efficient task duplication schedule (EETDS for short), which can significantly conserve power by judiciously shrinking communication energy cost when allocating parallel tasks to heterogeneous computing nodes. We present the preliminary simulation results for Gaussian and FFT parallel task models to prove the efficiency of our algorithm.    This paper appeared in the Proceedings of the 36th International Conference on Parallel Processing (ICPP), Sept. 2007. * Corresponding author. http://www.eng.auburn.edu/~xqin Acknowledgment: The work reported in this paper was supported by the US National Science Foundation under Grant No. CCF-0702781, Auburn University under a startup grant, New Mexico Institute of Mining and Technology under Grant No. 103295, the Intel Corporation under Grant No. 2005-04-070, and the Altera Corporation under an equipment grant.

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