Detail výsledku

Acceleration of grammatical evolution using graphics processing units: computational intelligence on consumer games and graphics hardware

POSPÍCHAL, P.; SCHWARZ, J.; JAROŠ, J. Acceleration of grammatical evolution using graphics processing units: computational intelligence on consumer games and graphics hardware. In Genetic and Evolutionary Computation Conference, GECCO'11 - Companion Publication. New York: Association for Computing Machinery, 2011. p. 431-438. ISBN: 978-1-4503-0690-4.
Typ
článek ve sborníku konference
Jazyk
anglicky
Autoři
Pospíchal Petr, Ing., UPSY (FIT)
Schwarz Josef, doc. Ing., CSc., UPSY (FIT)
Jaroš Jiří, prof. Ing., Ph.D., UPSY (FIT)
Abstrakt


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 including symbolic 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 480 together with a GE library written in JAVA, GEVA.

 Results indicate that our algorithm offers the same convergence, and it is suitable for a larger number of regression points where GPU is able to reach speedups of up to 39 times faster when compared to GEVA on a  serial CPU code written in C. In conclusion, properly utilized, GPU can offer an interesting performance boost for GE tackling symbolic regression. 
Klíčová slova

CUDA, grammatical evolution, graphics chips, GPU, GPGPU, speedup, symbolic regression

Rok
2011
Strany
431–438
Sborník
Genetic and Evolutionary Computation Conference, GECCO'11 - Companion Publication
Konference
Genetic and Evolutionary Computations Conference 2011
ISBN
978-1-4503-0690-4
Vydavatel
Association for Computing Machinery
Místo
New York
DOI
10.1145/2001858.2002030
EID Scopus
2-s2.0-80051950282
BibTeX 
@inproceedings{BUT76469,
  author="Petr {Pospíchal} and Josef {Schwarz} and Jiří {Jaroš}",
  title="Acceleration of grammatical evolution using graphics processing units: computational intelligence on consumer games and graphics hardware",
  booktitle="Genetic and Evolutionary Computation Conference, GECCO'11 - Companion Publication",
  year="2011",
  pages="431--438",
  publisher="Association for Computing Machinery",
  address="New York",
  doi="10.1145/2001858.2002030",
  isbn="978-1-4503-0690-4"
}
Projekty
Bezpečné, spolehlivé a adaptivní počítačové systémy, VUT, Vnitřní projekty VUT, FIT-S-10-1, zahájení: 2010-03-01, ukončení: 2010-12-31, ukončen
Natural computing na nekonvenčních platformách, GAČR, Standardní projekty, GAP103/10/1517, zahájení: 2010-01-01, ukončení: 2013-12-31, řešení
Výzkum informačních technologií z hlediska bezpečnosti, MŠMT, Institucionální prostředky SR ČR (např. VZ, VC), MSM0021630528, zahájení: 2007-01-01, ukončení: 2013-12-31, řešení
Výzkumné skupiny
Výzkumná skupina aplikovaných evolučních algoritmů (VZ EVA)
Pracoviště
Ústav počítačových systémů (UPSY)
Nahoru