Please use this identifier to cite or link to this item:
http://hdl.handle.net/20.500.12386/32583
Title: | Astrophysical data mining with GPU. A case study: Genetic classification of globular clusters | Authors: | CAVUOTI, STEFANO Garofalo, M. BRESCIA, Massimo Paolillo, Maurizio Pescape', A. Longo, G. Ventre, G. |
Issue Date: | 2014 | Journal: | NEW ASTRONOMY | Number: | 26 | First Page: | 12 | Abstract: | We present a multi-purpose genetic algorithm, designed and implemented with GPGPU/CUDA parallel computing technology. The model was derived from our CPU serial implementation, named GAME (Genetic Algorithm Model Experiment). It was successfully tested and validated on the detection of candidate Globular Clusters in deep, wide-field, single band HST images. The GPU version of GAME will be made available to the community by integrating it into the web application DAMEWARE (DAta Mining Web Application REsource, http://dame.dsf.unina.it/beta_info.html), a public data mining service specialized on massive astrophysical data. Since genetic algorithms are inherently parallel, the GPGPU computing paradigm leads to a speedup of a factor of 200× in the training phase with respect to the CPU based version. | URI: | http://hdl.handle.net/20.500.12386/32583 | URL: | https://www.sciencedirect.com/science/article/pii/S1384107613000456?via%3Dihub http://arxiv.org/abs/1304.0597v1 |
ISSN: | 1384-1076 | DOI: | 10.1016/j.newast.2013.04.004 | Bibcode ADS: | 2014NewA...26...12C | Fulltext: | open |
Appears in Collections: | 1.01 Articoli in rivista |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
1304.0597.pdf | postprint | 461.02 kB | Adobe PDF | View/Open |
New astr. 26_2014.pdf | [Administrators only] | 1.24 MB | Adobe PDF |
Page view(s)
33
checked on Apr 18, 2024
Download(s)
7
checked on Apr 18, 2024
Google ScholarTM
Check
Altmetric
Altmetric
Items in DSpace are published in Open Access, unless otherwise indicated.