Data parallel density-based genetic clustering on CUDA architecture
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F14%3A86092261" target="_blank" >RIV/61989100:27240/14:86092261 - isvavai.cz</a>
Alternative codes found
RIV/61989100:27740/14:86092261
Result on the web
<a href="http://dx.doi.org/10.1002/cpe.3054" target="_blank" >http://dx.doi.org/10.1002/cpe.3054</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1002/cpe.3054" target="_blank" >10.1002/cpe.3054</a>
Alternative languages
Result language
angličtina
Original language name
Data parallel density-based genetic clustering on CUDA architecture
Original language description
Evolutionary clustering algorithms have been proven as a good ability to find clusters in data. Among their advantages belong the abilities to adapt to data and to determine the number of clusters automatically, thus requiring less a priori assumptions about analyzed objects than traditional clustering methods. Unfortunately, such a clustering by genetic algorithms and evolutionary algorithms in general suffers from high computational costs when it comes to recurrent fitness function evaluation. Computing on graphic processing units (GPUs) is a recent programming and development paradigm bringing high performance parallel computing closer to general audience. Modern general purpose GPUs are composed of tens to thousands of computational cores that canexecute programs in parallel using the single instruction multiple data parallel processing approach. General purpose GPU programs need to be designed and implemented in a data parallel way and with respect to the architecture of target d
Czech name
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Czech description
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Classification
Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Concurrency Computation Practice and Experience
ISSN
1532-0626
e-ISSN
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Volume of the periodical
26
Issue of the periodical within the volume
5
Country of publishing house
US - UNITED STATES
Number of pages
16
Pages from-to
1097-1112
UT code for WoS article
000332983700007
EID of the result in the Scopus database
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