Fast Evaluation of GP Trees on GPGPU by Optimizing Hardware Scheduling
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @InProceedings{Maitre:2010:EuroGP,
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author = "Ogier Maitre and Pierre Collet and Nicolas Lachiche",
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title = "Fast Evaluation of GP Trees on GPGPU by Optimizing
Hardware Scheduling",
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booktitle = "Proceedings of the 13th European Conference on Genetic
Programming, EuroGP 2010",
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year = "2010",
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editor = "Anna Isabel Esparcia-Alcazar and Aniko Ekart and
Sara Silva and Stephen Dignum and A. Sima Uyar",
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volume = "6021",
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series = "LNCS",
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pages = "301--312",
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address = "Istanbul",
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month = "7-9 " # apr,
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organisation = "EvoStar",
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publisher = "Springer",
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keywords = "genetic algorithms, genetic programming, GPU",
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isbn13 = "978-3-642-12147-0",
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DOI = "doi:10.1007/978-3-642-12148-7_26",
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abstract = "This paper shows that it is possible to use General
Purpose Graphic Processing Unit cards for a fast
evaluation of different Genetic Programming trees on as
few as 32 fitness cases by using the hardware
scheduling of NVIDIA cards. Depending on the function
set, observed speedup ranges between x50 and x250 on
one half of an NVidia GTX295 GPGPU card, vs a single
core of an Intel Quad core Q8200.",
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notes = "Part of \cite{Esparcia-Alcazar:2010:GP} EuroGP'2010
held in conjunction with EvoCOP2010 EvoBIO2010 and
EvoApplications2010",
- }
Genetic Programming entries for
Ogier Maitre
Pierre Collet
Nicolas Lachiche
Citations