Optimalization of parallel GNG by neurons assigned to processes
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F17%3A10236161" target="_blank" >RIV/61989100:27240/17:10236161 - isvavai.cz</a>
Alternative codes found
RIV/61989100:27740/17:10236161
Result on the web
<a href="https://link.springer.com/chapter/10.1007%2F978-3-319-59105-6_6" target="_blank" >https://link.springer.com/chapter/10.1007%2F978-3-319-59105-6_6</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-59105-6_6" target="_blank" >10.1007/978-3-319-59105-6_6</a>
Alternative languages
Result language
angličtina
Original language name
Optimalization of parallel GNG by neurons assigned to processes
Original language description
The size, complexity and dimensionality of data collections are ever increasing from the beginning of the computer era. Clustering is used to reveal structures and to reduce large amounts of raw data. There are two main issues when clustering based on unsupervised learning, such as Growing Neural Gas (GNG) [9], is performed on vast high dimensional data collection - the fast growth of computational complexity with respect to growing data dimensionality, and the specific similarity measurement in a high-dimensional space. These two factors reduce the effectiveness of clustering algorithms in many real applications. The growth of computational complexity can be partially solved using the parallel computation facilities, such as High Performance Computing (HPC) cluster with MPI. An effective parallel implementation of GNG is discussed in this paper, while the main focus is on minimizing of interprocess communication. The achieved speed-up was better than previous approach and the results from the standard and parallel version of GNG are same.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10200 - Computer and information sciences
Result continuities
Project
<a href="/en/project/LM2015070" target="_blank" >LM2015070: IT4Innovations National Supercomputing Center</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Lecture Notes in Computer Science. Volume 10244
ISBN
978-3-319-59104-9
ISSN
0302-9743
e-ISSN
neuvedeno
Number of pages
10
Pages from-to
63-72
Publisher name
Springer
Place of publication
Cham
Event location
Białystok
Event date
Jun 16, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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