Evolutionary clustering on CUDA

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F12%3A86088876" target="_blank" >RIV/61989100:27240/12:86088876 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.3233/978-1-61499-098-7-909" target="_blank" >http://dx.doi.org/10.3233/978-1-61499-098-7-909</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3233/978-1-61499-098-7-909" target="_blank" >10.3233/978-1-61499-098-7-909</a>

Result language
angličtina
Original language name
Evolutionary clustering on CUDA
Original language description
Unsupervised clustering of large data sets is a complicated task. Due to its complexity, various meta-heuristic machine learning algorithms have been used to automate the clustering process. Genetic and evolutionary algorithms have been deployed to findclusters in data sets with success. The GPU computing is a recent programming paradigm introducing high performance parallel computing to general audience. This work presents an acceleration of a genetic algorithm for density based clustering on the GPUusing the nVidia compute unified device architecture (CUDA)
Czech name
—
Czech description
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Project
<a href="/en/project/ED1.1.00%2F02.0070" target="_blank" >ED1.1.00/02.0070: IT4Innovations Centre of Excellence</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Publication year
2012
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Frontiers in Artificial Intelligence and Applications. Volume 251
ISBN
978-1-61499-176-2
ISSN
0922-6389
e-ISSN
—
Number of pages
2
Pages from-to
909-910
Publisher name
IOS Press
Place of publication
Amsterodam
Event location
Praha
Event date
Jun 4, 2012
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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