GP on SPMD parallel graphics hardware for mega Bioinformatics data mining

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...

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Bibliographic Details
Published inSoft computing (Berlin, Germany) Vol. 12; no. 12; pp. 1169 - 1183
Main Authors Langdon, W. B., Harrison, A. P.
Format Journal Article
LanguageEnglish
Published Berlin/Heidelberg Springer-Verlag 01.10.2008
Springer Nature B.V
Subjects
Artificial Intelligence
Bioinformatics
Computational Intelligence
Control
Data mining
Engineering
Focus
Genetic algorithms
Mathematical Logic and Foundations
Mechatronics
Robotics
Stream Processor
Single Instruction Multiple Data
Genetic Programming
Graphic Hardware
Cartesian Genetic Programming
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Summary: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.
ISSN:1432-7643
1433-7479
DOI:10.1007/s00500-008-0296-x