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🏛️國立陽明交通大學機構典藏

Author: search.filters.author.Yang, CTSubject: search.filters.subject.parallel loop scheduling

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Now showing 1 - 3 of 3
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    Item type:Item,
    An intelligent parallel loop scheduling for parallelizing compilers
    (2000-03-01)
    Fann, YW
    ;
    Yang, CT
    ;
    Tseng, SS
    ;
    Tsai, CJ
    ;
    資訊工程學系
    In this paper we propose a knowledge-based approach to solving loop-scheduling problems. A rule-based system, called IPLS, is developed by combining a repertory grid and an attribute ordering table to construct a knowledge base. IPLS chooses an appropriate scheduling algorithm by inferring some features of loops and assigning parallel loops to multiprocessors to achieve significant speedup. Because more attributes are proposed, the accuracy of selection of an appropriate scheduling method is improved. In addition, the refined IPLS system can automatically adjust the attributes in the knowledge base according to profile information; therefore, IPLS has the capability of feedback learning. The experimental results show that our approach can achieve greater speedup on multiprocessor systems than can others.
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    A performance-based approach to dynamic workload distribution for master-slave applications on grid environments
    (2006)
    Shih, WC
    ;
    Yang, CT
    ;
    Tseng, SS
    ;
    資訊工程學系
    ;
    Department of Computer Science
    Effective workload distribution techniques can significantly reduce the total completion time of a program on and computing environments. In this paper, we propose a dynamic performance-based workload partition approach for master-slave types of applications on grids. Furthermore, we implement two types of applications and conduct the experimentations on our grid testbed. Experimental results showed that our method could execute more efficiently than traditional schemes.
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    Using knowledge-based techniques on loop parallelization for parallelizing compilers
    (1997-05-01)
    Yang, CT
    ;
    Tseng, SS
    ;
    Chuang, CD
    ;
    Shih, WC
    ;
    資訊工程學系
    In this paper we propose a knowledge-based approach for solving data dependence testing and loop scheduling problems. A rule-based system, called the K-Test, is developed by repertory grid and attribute ording table to construct the knowledge base. The K-Test chooses an appropriate testing algorithm according to some features of the input program by using knowledge-based techniques, and then applies the resulting test to detect data dependences for loop parallelization. Another rule-based system, called the KPLS, is also proposed to be able to choose an appropriate scheduling by inferring some features of loops and assign parallel loops on multiprocessors for achieving high speedup. The experimental results show that the graceful speedup obtained by our compiler is obvious.