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Publication Detail
Grow and Graft a better CUDA pknotsRG for RNA pseudoknot free energy calculation
  • Publication Type:
    Conference
  • Authors:
    Langdon WB, Harman M
  • Publisher:
    ACM
  • Publication date:
    2015
  • Pagination:
    805, 810
  • Published proceedings:
    Genetic Improvement 2015 Workshop
  • Editors:
    Langdon WB,Petke J,White DR
  • ISBN-13:
    978-1-4503-3488-4
  • Addresses:
    Madrid
  • Notes:
    organisation: SIGEVO publisher_address: New York, NY, USA keywords: genetic algorithms, genetic programming, genetic improvement, SBSE, BNF grammar, GPGPU, Bioinformatics, Software engineering, Artificial Intelligence, Automatic Programming size: 6 pages notes: http://geneticimprovement2015.com/ Slides: http://geneticimprovement2015.com/wp-content/uploads/2015/07/langdon_2015_gi_pknots_slides.pdf Slides: http://www.cs.ucl.ac.uk/staff/W.Langdon/gecco2015/gi_2015_slides/langdon/langdon_2015_gi_pknots_slides.pdf Code http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/gp-code/pknotsGI.tar.gz GECCO-2015 A joint meeting of the twenty fourth international conference on genetic algorithms (ICGA-2015) and the twentieth annual genetic programming conference (GP-2015). Also known as \cite2768418 Distributed at GECCO-2015.
Abstract
Grow and graft genetic programming greatly improves GPGPU dynamic programming software for predicting the minimum binding energy for folding of RNA molecules. The parallel code inserted into the existing CUDA version of pknots was grown using a BNF grammar. On an nVidia Tesla K40 GPU GGGP gives a speed up of up to 10000 times.
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