EASEA: a generic optimization tool for GPU machines in asynchronous island model
Created by W.Langdon from
gp-bibliography.bib Revision:1.7964
- @Article{krueg11ease,
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author = "Laurent A. Baumes and Frederic Kruger and
Pierre Collet",
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title = "{EASEA}: a generic optimization tool for {GPU}
machines in asynchronous island model",
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journal = "Computer Methods in Materials Science",
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year = "2011",
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volume = "11",
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number = "3",
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pages = "489--499",
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keywords = "genetic algorithms, genetic programming, GPGPU,
Evolutionary Algorithms, Island Model, Parallelism,
Zeolite Materials",
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ISSN = "1641-8581",
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publisher = "The AGH University of Science and Technology Press,
Open Access",
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URL = "http://icube-publis.unistra.fr/docs/7407/baumes.pdf",
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URL = "http://cmms-editorial.agh.edu.pl/abstract.php?p_id=373",
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size = "11 pages",
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abstract = "Very recently, we presented an efficient
implementation of Evolutionary Algorithms (EAs) using
Graphics Processing Units (GPU) for solving microporous
crystal structures. Because of both the inherent
complexity of zeolitic materials and the constant
pressure to accelerate R and D solutions, an
asynchronous island model running on clusters of
machines equipped with GPU cards, i.e. the current
trend for super-computers and cloud computing, is
presented. This last improvement of the EASEA platform
allows an effortless exploitation of hierarchical
massively parallel systems. It is demonstrated that
supra-linear speedup over one machine and linear
speedup considering clusters of different sizes are
obtained. Such an island implementation over several
potentially heterogeneous machines opens new horizon
for various domains of application where computation
time for optimisation remains the principal
bottleneck.",
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notes = "Address LSIIT , Illkirch, FRA",
- }
Genetic Programming entries for
Laurent Allan Baumes
Frederic Kruger
Pierre Collet
Citations