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POSPÍCHAL, P. SCHWARZ, J. JAROŠ, J.
Original Title
Parallel Genetic Algorithm Solving 0/1 Knapsack Problem Running on the GPU
Type
conference paper
Language
English
Original Abstract
In this work, we show that consumer-level $100 GPU can be used to significantly speed-up optimization of 0/1 Knapsack problem. We identify strong and weak points of GPU architecture and propose our parallel genetic algorithm model implemented in CUDA running entirely on the GPU. We show that GPU must be utilized for sufficiently long time in order to obtain reasonable program speedup. Then we compare results quality and speed of our model with single-threaded CPU code implemented using Galib. Peak speedup of GPU GA execution performance is 1340x resp. 134x for 4-bit resp. 40-bit problem instances while maintaining reasonable results quality.
Keywords
massively parallel, genetic algorithm, island model, CUDA, GPU, 0/1 Knapsack problem
Authors
POSPÍCHAL, P.; SCHWARZ, J.; JAROŠ, J.
RIV year
2010
Released
13. 7. 2010
Publisher
Brno University of Technology
Location
Brno
ISBN
978-80-214-4120-0
Book
16th International Conference on Soft Computing MENDEL 2010
Pages from
64
Pages to
70
Pages count
7
URL
https://www.fit.vut.cz/research/publication/9253/
BibTex
@inproceedings{BUT34660, author="Petr {Pospíchal} and Josef {Schwarz} and Jiří {Jaroš}", title="Parallel Genetic Algorithm Solving 0/1 Knapsack Problem Running on the GPU", booktitle="16th International Conference on Soft Computing MENDEL 2010", year="2010", pages="64--70", publisher="Brno University of Technology", address="Brno", isbn="978-80-214-4120-0", url="https://www.fit.vut.cz/research/publication/9253/" }