Acceleration of Grammatical Evolution Using Graphics Processing Units
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F11%3APU96181" target="_blank" >RIV/00216305:26230/11:PU96181 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Acceleration of Grammatical Evolution Using Graphics Processing Units
Original language description
Several papers show that symbolic regression is suitable for data analysis and prediction in financial markets. Grammatical Evolution (GE), a grammar-based form of Genetic Programming (GP), has been successfully applied in solving various tasks includingsymbolic regression. However, often the computational effort to calculate the fitness of a solution in GP can limit the area of possible application and/or the extent of experimentation undertaken. This paper deals with utilizing mainstream graphics processing units (GPU) for acceleration of GE solving symbolic regression. GPU optimization details are discussed and the NVCC compiler is analyzed. We design an effective mapping of the algorithm to the CUDA framework, and in so doing must tackle constraints of the GPU approach, such as the PCI-express bottleneck and main memory transactions. This is the first occasion GE has been adapted for running on a GPU. We measure our implementation running on one core of CPU Core i7 and GPU GTX
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
<a href="/en/project/GAP103%2F10%2F1517" target="_blank" >GAP103/10/1517: Natural Computing on Unconventional Platforms</a><br>
Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)
Others
Publication year
2011
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 2011 GECCO conference companion on Genetic and evolutionary computation
ISBN
978-1-4503-0690-4
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
431-439
Publisher name
Association for Computing Machinery
Place of publication
New York
Event location
Dublin
Event date
Jul 12, 2011
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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