Improving SSE Parallel Code with Grow and Graft Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4504

  author =       "William B. Langdon and Ronny Lorenz",
  title =        "Improving {SSE} Parallel Code with Grow and Graft
                 Genetic Programming",
  booktitle =    "GI-2017",
  year =         "2017",
  editor =       "Justyna Petke and David R. White and W. B. Langdon and 
                 Westley Weimer",
  pages =        "1537--1538",
  address =      "Berlin",
  month =        "15-19 " # jul,
  publisher =    "ACM",
  publisher_address = "New York, NY, USA",
  keywords =     "genetic algorithms, genetic programming, genetic
                 improvement, GGGP, Vienna_RNA, Bioinformatics, RNA
                 structure prediction, parallel vector SSE
  isbn13 =       "978-1-4503-4939-0",
  URL =          "",
  URL =          "",
  URL =          "",
  DOI =          "doi:10.1145/3067695.3082524",
  acmid =        "3082524",
  size =         "2 pages",
  abstract =     "RNAfold predicts the secondary structure of RNA
                 molecules from their base sequence. We apply a mixture
                 of manual and automated genetic improvements to
                 RNAfold's C source code. GI gives a 1.6 percent
                 improvement to parallel SSE4.1 code. The automatic
                 programming evolutionary system has access to Intel
                 library code and previous revisions. On 4666 curated
                 structures from RNA_STRAND, GGGP gives a combined
                 average speed up of 31.9 percent, with no loss of
  notes =        "code in


                 Also known as \cite{Langdon:2017:GECCOb}
                 \cite{Langdon:2017:ISP:3067695.3082524} GECCO-2017 A
                 Recombination of the 26th International Conference on
                 Genetic Algorithms (ICGA-2017) and the 22nd Annual
                 Genetic Programming Conference (GP-2017)",

Genetic Programming entries for William B Langdon Ronny Lorenz