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POSPÍCHAL, P.
Original Title
GPU-Based Acceleration of the Genetic Algorithm
Type
article in a collection out of WoS and Scopus
Language
English
Original Abstract
Genetic algorithm, a robust, stochastic optimization technique, is effective insolving many practical problems in science, engineering, and business domains. Unfortunatelly, execution usually takes a long time. In this paper, I study possibility of utilization consumer-level graphics cards for acceleration of GA's. A mapping of parallel island genetic algorithm to CUDA software model is designed and tested on GeForce 8800GTX, GTX260-SP216 and GTX285 GPU's using Rosenbrock's, Griewank's and Michalewicz's benchmark functions. Results indicates that this optimization leads to speedups up to seven thousand times compared to single CPU thread while maintaing reasonable results quality.
Keywords
Parallel Genetic Algorithm, PGA, CUDA, Island Model, Galib, Speedup, GPU
Authors
RIV year
2010
Released
16. 9. 2010
Publisher
Faculty of Information Technology BUT
Location
Brno
ISBN
978-80-214-4140-8
Book
Počítačové architektury a diagnostika 2010
Pages from
75
Pages to
80
Pages count
6
BibTex
@inproceedings{BUT34930, author="Petr {Pospíchal}", title="GPU-Based Acceleration of the Genetic Algorithm", booktitle="Počítačové architektury a diagnostika 2010", year="2010", pages="75--80", publisher="Faculty of Information Technology BUT", address="Brno", isbn="978-80-214-4140-8" }