A Convergence Study of the Discrete FGDLS Algorithm

Authors:
Sabin Tabirca;Tatiana Tabirca;Laurence T. Yang
Affiliations:
The author is with Boole Centre for Research in Informatics, University College Cork, College Road, Cork, Ireland.,;The author is supported by the Boole Centre for Research in Informatics, UCC, Cork, Ireland.,;The author is with the Department of Computer Science, St. Francis Xavier University, Antigonish, B2G 2W5, Canada. E-mail: lyang@stfx.ca
Venue:
IEICE - Transactions on Information and Systems
Year:
2006

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A performance-based parallel loop scheduling on grid environments

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GPC'07 Proceedings of the 2nd international conference on Advances in grid and pervasive computing

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Abstract

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.