Langdon, WB and Harrison, AP (2008) GP on SPMD parallel graphics hardware for mega Bioinformatics data mining. Soft Computing, 12 (12). pp. 1169-1183. DOI https://doi.org/10.1007/s00500-008-0296-x
Langdon, WB and Harrison, AP (2008) GP on SPMD parallel graphics hardware for mega Bioinformatics data mining. Soft Computing, 12 (12). pp. 1169-1183. DOI https://doi.org/10.1007/s00500-008-0296-x
Langdon, WB and Harrison, AP (2008) GP on SPMD parallel graphics hardware for mega Bioinformatics data mining. Soft Computing, 12 (12). pp. 1169-1183. DOI https://doi.org/10.1007/s00500-008-0296-x
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 available via FTP. © Springer-Verlag 2008.
| Item Type: | Article |
|---|---|
| Subjects: | Q Science > QA Mathematics Q Science > QH Natural history > QH301 Biology |
| Divisions: | Faculty of Science and Health Faculty of Science and Health > Mathematics, Statistics and Actuarial Science, School of |
| SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
| Depositing User: | Unnamed user with email elements@essex.ac.uk |
| Date Deposited: | 30 Sep 2011 10:23 |
| Last Modified: | 30 Oct 2024 19:44 |
| URI: | http://repository.essex.ac.uk/id/eprint/831 |