About: Non-negative Matrix Factorization on GPU

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rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	Today, the need of large data collection processing increase. Such type of data can has very large dimension and hidden relationships. Analyzing this type of data leads to many errors and noise, therefore, dimension reduction techniques are applied. Many techniques of reduction were developed, e.g. SVD, SDD, PCA, ICA. and NMF. Non-negative matrix factorization (NMF) has main advantage in processing of non-negative values which are easily interpretable as images, but other applications can be found in different areas as well. Both, data analysis and dimension reduction methods, need a lot of computation power. In these clays, many algorithms are rewritten with the GPU utilization, because GPU brings massive parallel architecture and very good ratio between performance and price. This paper introduce computation of NMF on GPU using CUDA technology. Today, the need of large data collection processing increase. Such type of data can has very large dimension and hidden relationships. Analyzing this type of data leads to many errors and noise, therefore, dimension reduction techniques are applied. Many techniques of reduction were developed, e.g. SVD, SDD, PCA, ICA. and NMF. Non-negative matrix factorization (NMF) has main advantage in processing of non-negative values which are easily interpretable as images, but other applications can be found in different areas as well. Both, data analysis and dimension reduction methods, need a lot of computation power. In these clays, many algorithms are rewritten with the GPU utilization, because GPU brings massive parallel architecture and very good ratio between performance and price. This paper introduce computation of NMF on GPU using CUDA technology. (en)
Title	Non-negative Matrix Factorization on GPU Non-negative Matrix Factorization on GPU (en)
skos:prefLabel	Non-negative Matrix Factorization on GPU Non-negative Matrix Factorization on GPU (en)
skos:notation	RIV/61989100:27240/10:86077801!RIV11-MPO-27240___
http://linked.open...avai/riv/aktivita	P
http://linked.open...avai/riv/aktivity	P(FR-TI1/420)
http://linked.open...vai/riv/dodaniDat	2011
http://linked.open...aciTvurceVysledku	Gajdoš, Petr Snášel, Václav Platoš, Jan Krömer, Pavel
http://linked.open.../riv/druhVysledku	D - Článek ve sborníku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Vysoká škola báňská - Technická univerzita Ostrava / Fakulta elektrotechniky a informatiky
http://linked.open...dnocenehoVysledku	275070
http://linked.open...ai/riv/idVysledku	RIV/61989100:27240/10:86077801
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	GPU computing; CUDA; parallelism; NMF (en)
http://linked.open.../riv/klicoveSlovo	CUDA parallelism GPU computing NMF
http://linked.open...ontrolniKodProRIV	[C08E892E8BCF]
http://linked.open...v/mistoKonaniAkce	Charles Univ, Prague, CZECH REPUBLIC
http://linked.open...i/riv/mistoVydani	Berlin Heidelberg
http://linked.open...i/riv/nazevZdroje	Networked Digital Technologie
http://linked.open...in/vavai/riv/obor	IN
http://linked.open...ichTvurcuVysledku	4 (xsd:int)
http://linked.open...cetTvurcuVysledku	4 (xsd:int)
http://linked.open...vavai/riv/projekt	*Integrovaný softwarový systém pro optimalizaci řízení technologických procesů a predikci kvality produkce velkých technologických celků využívající pokročilé matematické metody, modelování a umělou inteligenci
http://linked.open...UplatneniVysledku	2010
http://linked.open...iv/tvurceVysledku	Krömer, Pavel Platoš, Jan Snášel, Václav Gajdoš, Petr
http://linked.open...vavai/riv/typAkce	WRD - Světová
http://linked.open...ain/vavai/riv/wos	000289452700004
http://linked.open.../riv/zahajeniAkce	2010-07-07 (xsd:date)
issn	1865-0929
number of pages	10 (xsd:int)
http://purl.org/ne...btex#hasPublisher	Springer-Verlag. (Berlin; Heidelberg)
https://schema.org/isbn	978-3-642-14291-8
http://localhost/t...ganizacniJednotka	27240

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