A Convergence Study of the Discrete FGDLS Algorithm(Parallel/Distributed Algorithms, <Special Section> Parallel/Distributed Computing and Networking)
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概要
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The Feedback-Guided Dynamic Loop Scheduling (FGDLS) algorithm [1] is a recent dynamic approach to the scheduling of a parallel loop within a sequential outer loop. Earlier papers have analysed convergence under the assumption that the workload is a positive, continuous, function of a continuous argument (the iteration number). However, this assumption is unrealistic since it is known that the iteration number is a discrete variable. In this paper we extend the proof of convergence of the algorithm to the case where the iteration number is treated as a discrete variable. We are able to establish convergence of the FGDLS algorithm for the case when the workload is monotonically decreasing.
- 社団法人電子情報通信学会の論文
- 2006-02-01
著者
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Yang L
The Department Of Computer Science St. Francis Xavier University
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Yang Laurence
The Department Of Computer Science St. Francis Xavier University
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TABIRCA Sabin
Boole Centre for Research in Informatics, University College Cork
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TABIRCA Tatiana
the Boole Centre for Research in Informatics
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Tabirca Sabin
Boole Centre For Research In Informatics University College Cork
関連論文
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- Toward Incremental Parallelization Using Navigational Programming(Parallel/Distributed Programming Models, Paradigms and Tools, Parallel/Distributed Computing and Networking)
- A Convergence Study of the Discrete FGDLS Algorithm(Parallel/Distributed Algorithms, Parallel/Distributed Computing and Networking)
- Evaluation of the Feedback Guided Dynamic Loop Scheduling (FGDLS) Algorithms(Distributed, Grid and P2P Computing)(Hardware/Software Support for High Performance Scientific and Engineering Computing)