A coarse-grained parallelization of genetic algorithms

Genetic algorithms are frequently used to solve optimization problems. However, the problems become increasingly complex and time consuming. One solution to speed up the genetic algorithm processing is to use parallelization. The proposed parallelization method is coarse-grained and employs two leve...

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Veröffentlicht in:International journal of advances in intelligent informatics Jg. 4; H. 1; S. 1 - 10
Hauptverfasser: Rathomi, Muhamad Radzi, Pulungan, Reza
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Universitas Ahmad Dahlan 01.03.2018
Schlagworte:
Coarse-grained
Genetic algorithms
GPU
MPI
Parallelization
ISSN:2442-6571, 2442-6571
Online-Zugang:Volltext
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Zusammenfassung:Genetic algorithms are frequently used to solve optimization problems. However, the problems become increasingly complex and time consuming. One solution to speed up the genetic algorithm processing is to use parallelization. The proposed parallelization method is coarse-grained and employs two levels of parallelization: message passing with MPI and Single Instruction Multiple Threads with GPU. Experimental results show that the accuracy of the proposed approach is similar to the sequential genetic algorithm. Parallelization with coarse-grained method, however, can improve the processing and convergence speed of genetic algorithms.
ISSN:2442-6571
2442-6571
DOI:10.26555/ijain.v4i1.137