A Convergence Study of the Discrete FGDLS Algorithm

Sabin TABIRCA
Tatiana TABIRCA
Laurence T. YANG

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E89-D    No.2    pp.673-678
Publication Date: 2006/02/01
Online ISSN: 1745-1361
DOI: 10.1093/ietisy/e89-d.2.673
Print ISSN: 0916-8532
Type of Manuscript: Special Section PAPER (Special Section on Parallel/Distributed Computing and Networking)
Category: Parallel/Distributed Algorithms
Keyword: 
parallel loop scheduling,  feedback-guided dynamic loop scheduling,  convergence,  

Full Text: PDF(212.3KB)>>
Buy this Article


Summary: 
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.

open access publishing via