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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/38736

    Title: An efficient optimization technique for task matching and scheduling in heterogeneous computing systems
    Authors: Chuang, Po-Jen;Wei, Chia-Hsin
    Contributors: 淡江大學電機工程學系
    Keywords: 最佳化;任務符合;排程;異質性計算;基因演算法;模擬退火演算法;Optimization;Task Matching;Scheduling;Heterogeneous Computing;Genetic Algorithm;Simulated Annealing Algorithm
    Date: 2002-12
    Issue Date: 2013-03-07 14:47:08 (UTC+8)
    Publisher: New York: Institute of Electrical and Electronics Engineers (IEEE)
    Abstract: A new optimization technique, the Genetic Annealing Algorithm (GAA), is proposed in this paper to solve the task matching and scheduling problem in a heterogeneous computing system. The GAA is simple in design; it employs only the stir operation, a novel idea with the annealing concept, to locate optimal solutions, Experimental evaluation shows that compared with the Genetic Algorithm, Simulated Annealing and Guide Evolutionary Simulated Annealing approaches, the GAA yields constantly favorable performance in terms of speedup, running time, cost and complexity.
    Relation: Parallel and Distributed Systems, 2002. Proceedings. Ninth International Conference on, pp.419-424
    DOI: 10.1109/ICPADS.2002.1183433
    Appears in Collections:[Graduate Institute & Department of Electrical Engineering] Proceeding

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