Multiprocessor Scheduling with Support by Genetic Algorithms-Based Learning Classifier System

Authors:
Jerzy P. Nowacki;Grzegorz Pycka;Franciszek Seredynski
Affiliations:
-;-;-
Venue:
IPDPS '00 Proceedings of the 15 IPDPS 2000 Workshops on Parallel and Distributed Processing
Year:
2000

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Abstract

The paper proposes using genetic algorithms - based learning classifier system (CS) to solve multiprocessor scheduling problem. After initial mapping tasks of a parallel program into processors of a parallel system, the agents associated with tasks perform migration to find an allocation providing the minimal execution time of the program. Decisions concerning agents' actions are produced by the CS, upon a presentation by an agent information about its current situation. Results of experimental study of the scheduler are presented.