DocumentCode
2324401
Title
Dynamic mapping and load balancing with parallel genetic algorithms
Author
Seredynski, F.
Author_Institution
Inst. of Comput. Sci., Polish Acad. of Sci., Warsaw, Poland
fYear
1994
fDate
27-29 Jun 1994
Firstpage
834
Abstract
The paper presents an approach to dynamic mapping and load balancing of parallel programs in MIMD multicomputers, based on coordinated migration of processes of a parallel program. A program graph is interpreted as a multi-agent system with locally defined goals and actions, operating in some environment. A parallel genetic algorithm (island model) is developed to work out a set of collective decisions concerning processes´ migration. Presented experiments show a behavior of the algorithm
Keywords
genetic algorithms; optimisation; parallel algorithms; parallel programming; resource allocation; MIMD multicomputers; coordinated migration; dynamic mapping; island model; load balancing; locally defined goals; multi-agent system; parallel genetic algorithm; parallel genetic algorithms; parallel programs; process migration; program graph; Computational efficiency; Computational modeling; Computer science; Cost function; Genetic algorithms; Heuristic algorithms; Load management; Multiagent systems;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 1994. IEEE World Congress on Computational Intelligence., Proceedings of the First IEEE Conference on
Conference_Location
Orlando, FL
Print_ISBN
0-7803-1899-4
Type
conf
DOI
10.1109/ICEC.1994.349946
Filename
349946
Link To Document