Abstract
Excessive energy consumption has become a critical issue in high performance computing. Task scheduling algorithms affect not only schedule length but also energy consumption. To shorten schedule length of parallel tasks with precedence constraints, scheduling algorithms could duplicate tasks on critical paths to avoid communication delay caused by inter-task dependence. However, task duplications incur more energy consumption. In this paper, we propose a heuristic Processor Reduction Optimizing (PRO) method to reduce the number of processors used to run parallel tasks, thereby decreasing system energy consumption. The PRO method can find appropriate time slots to accommodate tasks immigrated from low-utilized processors. The PRO method can be combined with existing duplication-based scheduling algorithms, such as Task Duplication Scheduling (TDS), Energy-Aware Duplication (EAD) scheduling and Performance-Energy Balanced Duplication (PEBD) scheduling. Experimental results show that the proposed PRO method can effectively decrease the number of used processors and save energy while maintaining schedule length.
An abstract containing some preliminary results of this paper appeared in the Chinese Journal of Computer, 2012, 35(3): 591-602. This paper is an extended English version based on the same study.
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References
Huang, J.G., Chen, J.E., Chen, S.Q.: Parallel-job scheduling on cluster computing systems. Chinese Journal of Computer 27(6), 765–771 (2004)
Ranaweera, S., Agrawal, D.P.: A task duplication based scheduling algorithm for heterogeneous systems. In: The Parallel and Distributed Processing Symposium, Atlanta, USA, pp. 445–450 (2000)
Zong, Z.L., Manzanares, A., Ruan, X.J., Qin, X.: EAD and PEBD: Two energy-aware duplication scheduling algorithms for parallel tasks on homogeneous clusters. IEEE Transactions on Computers 60(3), 360–374 (2011)
Standard Task Graph Set web site (2011): http://www.kasahara.elec.waseda.ac.jp/schedule
Sih, G.C., Lee, E.A.: A compile time scheduling heuristic for interconnection-constrained heterogeneous processors architectures. IEEE Transactions on Parallel and Distributed Systems 4(2), 175–187 (1993)
Pande, S.S., Agrawal, D.P., Mauney, J.: A scalable scheduling method for functional parallelism on distributed memory multiprocessors. IEEE Transactions on Parallel and Distributed Systems 6(4), 388–399 (1995)
Li, X., Jia, Z.P., Ju, L., Zhao, Y.H., Zong, Z.L.: Energy Efficient Scheduling and Optimization for Parallel Tasks on Homogeneous Clusters. Chinese Journal of Computer 35(3), 591–602 (2012) (in Chinese)
Gerasoulis, A., Yang, T.: Scheduling program task graphs on MIMD architectures. Parallel Algorithm Derivation and Program Transformation, 153–186 (1993)
Zhou, H.B.: Scheduling DAGs on a Bounded number of Processors. In: International Conference of Parallel and Distributed Processing Techniques and Applications, pp. 823–834 (1996)
Sarkar, V.: Partitioning and scheduling parallel programs for multiprocessors. The MIT Press (1989)
Yang, T., Gerasoulis, A.: List scheduling with and without communication delays. Parallel Computing 19, 1321–1344 (1993)
Kwok, Y.K., Ahmad, I.: Efficient Scheduling of Arbitrary Task Graphs to Multiprocessors Using a Parallel Genetic Algorithm. J. Parallel and Distributed Computing 47(1), 58–77 (1997)
Gupta, M., Singh, S.: Greening of the Internet. In: The ACM Conference on Applications, Technologies, Architectures and Protocols for Computer Communications (SIGCOMM 2003), Karlsrhue, Germany, pp. 19–26 (2003)
Hsu, C.H., Feng, W.C.: A Feasibility Analysis of Power Awareness in Commodity-Based High-Performance Clusters. In: IEEE Cluster Computing (Cluster 2005), Burlington, USA, pp. 1–10 (2005)
Darbha, S., Agrawal, D.P.: A Task Duplication Based Scalable Scheduling Algorithm for Distributed Memory Systems. J. Parallel and Distr. Comp. 46(1), 15–27 (1997)
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Li, X., Zhao, Y., Li, Y., Ju, L., Jia, Z. (2014). An Improved Energy-Efficient Scheduling for Precedence Constrained Tasks in Multiprocessor Clusters. In: Sun, Xh., et al. Algorithms and Architectures for Parallel Processing. ICA3PP 2014. Lecture Notes in Computer Science, vol 8630. Springer, Cham. https://doi.org/10.1007/978-3-319-11197-1_25
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DOI: https://doi.org/10.1007/978-3-319-11197-1_25
Publisher Name: Springer, Cham
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