Fast Evaluation of GP Trees on GPGPU by Optimizing Hardware Scheduling

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InProceedings{Maitre:2010:EuroGP,

• author = "Ogier Maitre and Pierre Collet and Nicolas Lachiche",
• title = "Fast Evaluation of GP Trees on GPGPU by Optimizing Hardware Scheduling",
• booktitle = "Proceedings of the 13th European Conference on Genetic Programming, EuroGP 2010",
• year = "2010",
• editor = "Anna Isabel Esparcia-Alcazar and Aniko Ekart and Sara Silva and Stephen Dignum and A. Sima Uyar",
• volume = "6021",
• series = "LNCS",
• pages = "301--312",
• address = "Istanbul",
• month = "7-9 " # apr,
• organisation = "EvoStar",
• publisher = "Springer",
• keywords = "genetic algorithms, genetic programming, GPU",
• isbn13 = "978-3-642-12147-0",
• DOI = "doi:10.1007/978-3-642-12148-7_26",
• 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.",
• 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