Detail publikace

Parallel Genetic Algorithm on the CUDA Architecture

Originální název

Parallel Genetic Algorithm on the CUDA Architecture

Anglický název

Parallel Genetic Algorithm on the CUDA Architecture

Jazyk

en

Originální abstrakt

This paper deals with the mapping of the parallel island-based genetic algorithm with unidirectional ring migrations to nVidia CUDA software model. The proposed mapping is tested using Rosenbrock's, Griewank's and Michalewicz's benchmark functions. The obtained results indicate that our approach leads to speedups up to seven thousand times higher compared to one CPU thread while maintaining a reasonable results quality. This clearly shows that GPUs have a potential for acceleration of GAs and allow to solve much complex tasks.

Anglický abstrakt

This paper deals with the mapping of the parallel island-based genetic algorithm with unidirectional ring migrations to nVidia CUDA software model. The proposed mapping is tested using Rosenbrock's, Griewank's and Michalewicz's benchmark functions. The obtained results indicate that our approach leads to speedups up to seven thousand times higher compared to one CPU thread while maintaining a reasonable results quality. This clearly shows that GPUs have a potential for acceleration of GAs and allow to solve much complex tasks.

BibTex


@inproceedings{BUT34649,
  author="Petr {Pospíchal} and Jiří {Jaroš} and Josef {Schwarz}",
  title="Parallel Genetic Algorithm on the CUDA Architecture",
  annote="This paper deals with the mapping of the parallel island-based genetic algorithm
with unidirectional ring migrations to nVidia CUDA software model. The proposed
mapping is tested using Rosenbrock's, Griewank's and Michalewicz's benchmark
functions. The obtained results indicate that our approach leads to speedups up
to seven thousand times higher compared to one CPU thread while maintaining
a reasonable results quality. This clearly shows that GPUs have a potential for
acceleration of GAs and allow to solve much complex tasks.",
  address="Springer Verlag",
  booktitle="Applications of Evolutionary Computation",
  chapter="34649",
  edition="Lecture Notes in Computer Science",
  howpublished="online",
  institution="Springer Verlag",
  year="2010",
  month="april",
  pages="442--451",
  publisher="Springer Verlag",
  type="conference paper"
}