Genetic Improvement of GPU Software

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@Article{Langdon:2016:GPEM,
  author =       "William B. Langdon and Brian Yee Hong Lam and 
                 Marc Modat and Justyna Petke and Mark Harman",
  title =        "Genetic Improvement of {GPU} Software",
  journal =      "Genetic Programming and Evolvable Machines",
  year =         "2017",
  volume =       "18",
  number =       "1",
  month =        mar,
  pages =        "5--44",
  keywords =     "genetic algorithms, genetic programming, genetic
                 improvement, SBSE, GI-GPGPU, metaprogramming, Grammar
                 Based Genetic Programming, nVidia CUDA, parallel
                 computing, Dynamic Programming, GPGPU, GGGP",
  ISSN =         "1389-2576",
  URL =          "http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/Langdon_2016_GPEM.pdf",
  DOI =          "doi:10.1007/s10710-016-9273-9",
  size =         "40 pages",
  abstract =     "We survey Genetic Improvement (GI) of general purpose
                 computing on graphics cards. We summarise several
                 experiments which demonstrate four themes. Experiments
                 with the gzip program \cite{langdon:2010:cigpu} show
                 that genetic programming (GP) can automatically port
                 sequential C~code to parallel code. Experiments with
                 the StereoCamera program \cite{langdon:2014:EuroGP}
                 show that GI can upgrade legacy parallel code for new
                 hardware and software. Experiments with NiftyReg
                 \cite{Langdon:2014:GECCO} and BarraCUDA
                 \cite{Langdon:2015:GECCO} show that GI can make
                 substantial improvements to current parallel CUDA
                 applications. Finally, experiments with the pknotsRG
                 program \cite{langdon:2015:gi_pknots} show that with
                 semi-automated approaches, enormous speed ups can
                 sometimes be had by growing and grafting new code with
                 genetic programming in combination with human input.",
  notes =        "Electronic supplementary material
                 https://static-content.springer.com/esm/art%3A10.1007%2Fs10710-016-9273-9/MediaObjects/10710_2016_9273_MOESM1_ESM.gif

                 Presented in part at COW50: The 50th CREST Open
                 Workshop - Genetic Improvement
                 http://crest.cs.ucl.ac.uk/cow/50/ slides
                 http://crest.cs.ucl.ac.uk/cow/50/slides/cow50_Langdon.pdf
                 videos
                 http://crest.cs.ucl.ac.uk/cow/50/videos/langdon_cow50_480p.mp4
                 http://crest.cs.ucl.ac.uk/cow/50/videos/langdon_cow50_720p.mp4
                 https://youtu.be/KVaji1pvd-0

                 gismo",
}

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

Citations