GP on SPMD parallel Graphics Hardware for mega Bioinformatics Data Mining

Created by W.Langdon from gp-bibliography.bib Revision:1.4524

  author =       "W. B. Langdon and A. P. Harrison",
  title =        "{GP} on {SPMD} parallel Graphics Hardware for mega
                 Bioinformatics Data Mining",
  journal =      "Soft Computing",
  year =         "2008",
  volume =       "12",
  number =       "12",
  pages =        "1169--1183",
  month =        oct,
  note =         "Special Issue on Distributed Bioinspired Algorithms",
  keywords =     "genetic algorithms, genetic programming, breast
                 cancer, decorin, C17orf81, S-adenosylhomocysteine
                 hydrolase, fibulin 1, Lance Miller's Uppsala GEO
                 GSE3494 tumour biopsy, Affymetrix HG-U133A, HG-U133B,
                 data mining, consumer graphics hardware, GPU, Graphics
                 Processing Unit, SIMD, parallel computing, genetic
                 programming, soft computing, evolutionary algorithm,
                 RapidMind Ubuntu GCC C++",
  URL =          "",
  URL =          "",
  DOI =          "doi:10.1007/s00500-008-0296-x",
  size =         "11 pages",
  abstract =     "We demonstrate a SIMD C++ genetic programming system
                 on a single 128 node parallel nVidia GeForce 8800 GTX
                 GPU under RapidMind's GPGPU Linux software by
                 predicting ten year+ outcome of breast cancer from a
                 dataset containing a million inputs. NCBI GEO GSE3494
                 contains hundreds of Affymetrix HG-U133A and HG-U133B
                 GeneChip biopsies. Multiple GP runs each with a
                 population of 5 million programs winnow useful
                 variables from the chaff at more than 500 million GPops
                 per second. Sources and dataset available.",
  notes =        "


Genetic Programming entries for William B Langdon Andrew P Harrison