A Novel, Energy-Aware Task Duplication-Based Scheduling Algorithm of Parallel Tasks on Clusters
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Beijing Key Laboratory of Information Service Engineering, Beijing Union University, No. 97 Beisihuan East Road, Chaoyang District, Beijing 100101, China
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Computer and Engineering School, Beihang University, No. 37 Xueyuanlu, Haidian District, Beijing 100191, China
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Author to whom correspondence should be addressed.
Academic Editor: Fazal M. Mahomed
Math. Comput. Appl. 2017, 22(1), 2; https://doi.org/10.3390/mca22010002
Received: 21 September 2016 / Revised: 9 December 2016 / Accepted: 19 December 2016 / Published: 27 December 2016
Increasing energy has become an important issue in high performance clusters. To balance the energy and performance, we proposed a novel, energy-aware duplication-based scheduling (NEADS). An existing energy-aware duplication-based algorithm replicates all qualified predecessor tasks in a bottom-up manner. Some tasks without direct relation may be replicated to the same processor, which cannot reduce the communication energy. Instead, the computation overhead may be increased. In contrast, the proposed algorithm only replicates the directly correlated predecessor tasks in the energy threshold range without lengthening the schedule length. The proposed algorithm is compared with the non-duplication algorithm and existing duplicated-based algorithm. Extensive experimental results show that the proposed algorithm can effectively reduce energy consumption in various applications. It has advantages over other algorithms on computation-intensive applications.
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MDPI and ACS Style
Liang, A.; Pang, Y. A Novel, Energy-Aware Task Duplication-Based Scheduling Algorithm of Parallel Tasks on Clusters. Math. Comput. Appl. 2017, 22, 2.
AMA Style
Liang A, Pang Y. A Novel, Energy-Aware Task Duplication-Based Scheduling Algorithm of Parallel Tasks on Clusters. Mathematical and Computational Applications. 2017; 22(1):2.
Chicago/Turabian StyleLiang, Aihua; Pang, Yu. 2017. "A Novel, Energy-Aware Task Duplication-Based Scheduling Algorithm of Parallel Tasks on Clusters" Math. Comput. Appl. 22, no. 1: 2.
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