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GP on SPMD parallel graphics hardware for mega Bioinformatics data mining

William B. Langdon, Andrew P. Harrison
Department of Computer Science, King’s College, London, Strand, London, WC2R 2LS, UK
Soft Computing – A Fusion of Foundations, Methodologies and Applications, Volume 12, Number 12, 1169-1183

@article{langdon2008gp,

   title={GP on SPMD parallel graphics hardware for mega bioinformatics data mining},

   author={Langdon, W.B. and Harrison, A.P.},

   journal={Soft Computing-A Fusion of Foundations, Methodologies and Applications},

   volume={12},

   number={12},

   pages={1169–1183},

   issn={1432-7643},

   year={2008},

   publisher={Springer}

}

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 available via FTP.
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