Improving CUDA DNA Analysis Software with Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4549

  author =       "William B. Langdon and Brian Yee Hong Lam and 
                 Justyna Petke and Mark Harman",
  title =        "Improving {CUDA} {DNA} Analysis Software with Genetic
  booktitle =    "GECCO '15: Proceedings of the 2015 Annual Conference
                 on Genetic and Evolutionary Computation",
  year =         "2015",
  editor =       "Sara Silva and Anna I Esparcia-Alcazar and 
                 Manuel Lopez-Ibanez and Sanaz Mostaghim and Jon Timmis and 
                 Christine Zarges and Luis Correia and Terence Soule and 
                 Mario Giacobini and Ryan Urbanowicz and 
                 Youhei Akimoto and Tobias Glasmachers and 
                 Francisco {Fernandez de Vega} and Amy Hoover and Pedro Larranaga and 
                 Marta Soto and Carlos Cotta and Francisco B. Pereira and 
                 Julia Handl and Jan Koutnik and Antonio Gaspar-Cunha and 
                 Heike Trautmann and Jean-Baptiste Mouret and 
                 Sebastian Risi and Ernesto Costa and Oliver Schuetze and 
                 Krzysztof Krawiec and Alberto Moraglio and 
                 Julian F. Miller and Pawel Widera and Stefano Cagnoni and 
                 JJ Merelo and Emma Hart and Leonardo Trujillo and 
                 Marouane Kessentini and Gabriela Ochoa and Francisco Chicano and 
                 Carola Doerr",
  pages =        "1063--1070",
  organisation = "SIGEVO",
  address =      "Madrid",
  publisher =    "ACM",
  publisher_address = "New York, NY, USA",
  keywords =     "genetic algorithms, genetic programming, genetic
                 improvement, SBSE, Artificial Intelligence, Automatic
                 Programming, Testing, Performance, Speedup, BarraCUDA,
                 DNA sequence mapping, software, NVIDIA Tesla K40, CUDA,
                 C++, GPU, Burrows-Wheeler algorithm, BWA, parallel
                 computing, SIMD, phenotypic tabu search, genotypic tabu
                 search, GPGPU, Bioinformatics, Software engineering,
                 GP, GI, GGGP, Grow and Graft Genetic programming, Man
                 and Machine Collaborative Development, Tabu, BNF
  month =        "11-15 " # jul,
  isbn13 =       "978-1-4503-3472-3",
  URL =          "",
  URL =          "",
  DOI =          "doi:10.1145/2739480.2754652",
  abstract =     "We genetically improve BarraCUDA using a BNF grammar
                 incorporating C scoping rules with GP. Barracuda maps
                 next generation DNA sequences to the human genome using
                 the Burrows-Wheeler algorithm (BWA) on nVidia Tesla
                 parallel graphics hardware (GPUs). GI using phenotypic
                 tabu search with manually grown code can graft new
                 features giving more than 100 fold speed up on a
                 performance critical kernel without loss of accuracy.",
  notes =        "See also \cite{Langdon:2017:BDM}
                 \cite{Langdon:RN1503}. Cited by


                 Incorporated code as barracuda release 0.7.105 can be
                 downloaded from SourceForge:

                 cited by Karel Brinda PhD thesis
                 \cite{brinda:tel-01484198}, also

                 Also known as \cite{2754652} GECCO-2015 A joint meeting
                 of the twenty fourth international conference on
                 genetic algorithms (ICGA-2015) and the twentith annual
                 genetic programming conference (GP-2015)",

Genetic Programming entries for William B Langdon Brian Yee Hong Lam Justyna Petke Mark Harman