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A resource-aware scheduling algorithm with reduced task duplication on heterogeneous computing systems

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Abstract

To satisfy the high-performance requirements of application executions, many kinds of task scheduling algorithms have been proposed. Among them, duplication-based scheduling algorithms achieve higher performance compared to others. However, because of their greedy feature, they duplicate parents of each task as long as the finish time can be reduced, which leads to a superfluous consumption of resource. However, a large amount of duplications are unnecessary because slight delay of some uncritical tasks does not affect the overall makespan. Moreover, these redundant duplications would occupy the resources, delay the execution of subsequent tasks, and increase the schedule makespan consequently. In this paper, we propose a novel duplication-based algorithm designed to overcome the above drawbacks. The proposed algorithm is to schedule tasks with the least redundant duplications. An optimizing scheme is introduced to search and remove redundancy for a schedule generated by the proposed algorithm further. Randomly generated directed acyclic graphs and two real-world applications are tested in our experiments. Experimental results show that the proposed algorithm can save up to 15.59  % resource consumption compared with the other algorithms. The makespan has improvement as well.

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Acknowledgments

The authors would like to thank the five anonymous reviewers for their constructive comments to improve the presentation of the paper. This research was partially funded by the Key Program of National Natural Science Foundation of China (Grant No. 61133005)and the National Natural Science Foundation of China (Grant Nos. 61070057,61103047,61370095),the Ph.D. Programs Foundation of Ministry of Education of China(20100161110019), the National Science Foundation for Distinguished Young Scholars of Hunan (12JJ1011), the Innovation Fund Designated for Graduate Students of Hunan Province (No. CX2013B142), and the Project of National Natural Science Foundation of China under grant 61202109.

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Authors and Affiliations

  1. College of Information Science and Engineering, Hunan University, Changsha , 410082, Hunan, China

    Jing Mei, Kenli Li & Keqin Li

  2. National Supercomputing Center in Changsha, Changsha , 410082, Hunan, China

    Kenli Li

  3. Department of Computer Science, State University of New York, New Paltz, NY , 12561, USA

    Keqin Li

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  1. Jing Mei
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  2. Kenli Li
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Correspondence to Kenli Li.

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Mei, J., Li, K. & Li, K. A resource-aware scheduling algorithm with reduced task duplication on heterogeneous computing systems. J Supercomput 68, 1347–1377 (2014). https://doi.org/10.1007/s11227-014-1090-4

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