research-article

Rapid evaluation and evolution of neural models using graphics card hardware

Authors:

Thomas F. Clayton,

Leena N. Patel,

Alan F. Murray,

Iain A.B. LindsayAuthors Info & Claims

GECCO '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation

Pages 299 - 306

https://doi.org/10.1145/1389095.1389149

Published: 12 July 2008 Publication History

Abstract

This paper compares three common evolutionary algorithms and our modified GA, a Distributed Adaptive Genetic Algorithm (DAGA). The optimal approach is sought to adapt, in near real-time, biological model behaviour to that of real biology within a laboratory. Near real-time adaptation is achieved with a Graphics Processing Unit (GPU). This, together with evolutionary computation, enables new forms of experimentation such as online testing, where biology and computational model are simultaneously stimulated and their responses compared. Rapid analysis and validation provide a platform that is required for rapid prototyping, and along with online testing, can provide new insight into the cause of biological behaviour. In this context, results demonstrate that our DAGA implementation is more efficient than the other three evolutionary algorithms due to its suitability to the adaptation environment, namely the large population sizes promoted by the GPU architecture.

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Cited By

Pedemonte MAlba ELuna FLanzi P(2011)Bitwise operations for GPU implementation of genetic algorithmsProceedings of the 13th annual conference companion on Genetic and evolutionary computation10.1145/2001858.2002031(439-446)Online publication date: 12-Jul-2011
https://dl.acm.org/doi/10.1145/2001858.2002031
Tsutsui SFujimoto NLanzi P(2011)ACO with tabu search on a GPU for solving QAPs using move-cost adjusted thread assignmentProceedings of the 13th annual conference on Genetic and evolutionary computation10.1145/2001576.2001785(1547-1554)Online publication date: 12-Jul-2011
https://dl.acm.org/doi/10.1145/2001576.2001785
Tsutsui SFujimoto N(2011)Fast QAP solving by ACO with 2-opt local search on a GPU2011 IEEE Congress of Evolutionary Computation (CEC)10.1109/CEC.2011.5949702(812-819)Online publication date: Jun-2011
https://doi.org/10.1109/CEC.2011.5949702
Show More Cited By

Index Terms

Rapid evaluation and evolution of neural models using graphics card hardware
1. Computing methodologies
  1. Modeling and simulation
    1. Model development and analysis
      1. Modeling methodologies

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cover image ACM Conferences

GECCO '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation

July 2008

1814 pages

ISBN:9781605581309

DOI:10.1145/1389095

Conference Chair:
Conor Ryan
University of Limerick, Ireland
,
Editor:
Maarten Keijzer
Chordiant Software International B.V., The Netherlands

Copyright © 2008 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 12 July 2008

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GECCO08

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GECCO08: Genetic and Evolutionary Computation Conference

July 12 - 16, 2008

GA, Atlanta, USA

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Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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Cited By

Pedemonte MAlba ELuna FLanzi P(2011)Bitwise operations for GPU implementation of genetic algorithmsProceedings of the 13th annual conference companion on Genetic and evolutionary computation10.1145/2001858.2002031(439-446)Online publication date: 12-Jul-2011
https://dl.acm.org/doi/10.1145/2001858.2002031
Tsutsui SFujimoto NLanzi P(2011)ACO with tabu search on a GPU for solving QAPs using move-cost adjusted thread assignmentProceedings of the 13th annual conference on Genetic and evolutionary computation10.1145/2001576.2001785(1547-1554)Online publication date: 12-Jul-2011
https://dl.acm.org/doi/10.1145/2001576.2001785
Tsutsui SFujimoto N(2011)Fast QAP solving by ACO with 2-opt local search on a GPU2011 IEEE Congress of Evolutionary Computation (CEC)10.1109/CEC.2011.5949702(812-819)Online publication date: Jun-2011
https://doi.org/10.1109/CEC.2011.5949702
Langdon W(2011)Graphics processing units and genetic programming: an overviewSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-011-0695-215:8(1657-1669)Online publication date: 1-Aug-2011
https://dl.acm.org/doi/10.1007/s00500-011-0695-2
Rouhipour MBentley PShayani H(2010)Systemic computation using graphics processorsProceedings of the 9th international conference on Evolvable systems: from biology to hardware10.5555/1885332.1885346(121-132)Online publication date: 6-Sep-2010
https://dl.acm.org/doi/10.5555/1885332.1885346
Tsutsui SFujimoto N(2010)An analytical study of GPU computation for solving QAPs by parallel evolutionary computation with independent runIEEE Congress on Evolutionary Computation10.1109/CEC.2010.5585960(1-8)Online publication date: Jul-2010
https://doi.org/10.1109/CEC.2010.5585960
Rouhipour MBentley PShayani H(2010)Fast bio-inspired computation using a GPU-based systemic computerParallel Computing10.1016/j.parco.2010.07.00436:10-11(591-617)Online publication date: 1-Oct-2010
https://dl.acm.org/doi/10.1016/j.parco.2010.07.004
Rouhipour MBentley PShayani H(2010)Systemic Computation Using Graphics ProcessorsEvolvable Systems: From Biology to Hardware10.1007/978-3-642-15323-5_11(121-132)Online publication date: 2010
https://doi.org/10.1007/978-3-642-15323-5_11
Tsutsui SFujimoto NRothlauf F(2009)Solving quadratic assignment problems by genetic algorithms with GPU computationProceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers10.1145/1570256.1570355(2523-2530)Online publication date: 8-Jul-2009
https://dl.acm.org/doi/10.1145/1570256.1570355

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