Genetic Programming on GPGPU cards using EASEA
Created by W.Langdon from
gp-bibliography.bib Revision:1.8010
- @InCollection{Maitre:2013:ecgpu,
-
author = "Ogier Maitre",
-
title = "Genetic Programming on {GPGPU cards} using {EASEA}",
-
booktitle = "Massively Parallel Evolutionary Computation on
{GPGPUs}",
-
publisher = "Springer",
-
year = "2013",
-
editor = "Shigeyoshi Tsutsui and Pierre Collet",
-
series = "Natural Computing Series",
-
chapter = "11",
-
pages = "227--248",
-
keywords = "genetic algorithms, genetic programming, GPU",
-
isbn13 = "978-3-642-37958-1",
-
URL = "http://www.springer.com/computer/ai/book/978-3-642-37958-1",
-
DOI = "doi:10.1007/978-3-642-37959-8_11",
-
abstract = "Genetic programming is one of the most powerful
evolutionary paradigms because it allows us to optimise
not only the parameter space but also the structure of
a solution. The search space explored by genetic
programming is therefore huge and necessitates a very
large computing power which is exactly what GPGPUs can
provide. This chapter will show how Koza-like
tree-based genetic programming can be efficiently
ported onto GPGPU processors.",
- }
Genetic Programming entries for
Ogier Maitre
Citations