About: Image segmentation using CUDA implementations of the Runge-Kutta-Merson and GMRES methods

Facets (new session)
Description
Metadata
Settings
- owl:sameAs
- Inference Rule:

About: Image segmentation using CUDA implementations of the Runge-Kutta-Merson and GMRES methods Goto Sponge NotDistinct Permalink

An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

Attributes	Values
rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
rdfs:seeAlso	http://gcoe-mi.jp/english/publish_list/pub_inner/id:4/cid:17
Description	Modern GPUs are well suited for performing image processing tasks. We utilize their high computational performance and memory bandwidth for image segmentation purposes. We segment cardiac MRI data by means of numerical solution of an anisotropic partial differential equation of the Allen-Cahn type. We implement two different algorithms for solving the equation on the CUDA architecture. One of them is based on the Runge-Kutta-Merson method for the approximation of solutions of ordinary differential equations, the other uses the GMRES method for the numerical solution of systems of linear equations. In our experiments, the CUDA implementations of both algorithms are about 3--9 times faster than corresponding 12-threaded OpenMP implementations. Modern GPUs are well suited for performing image processing tasks. We utilize their high computational performance and memory bandwidth for image segmentation purposes. We segment cardiac MRI data by means of numerical solution of an anisotropic partial differential equation of the Allen-Cahn type. We implement two different algorithms for solving the equation on the CUDA architecture. One of them is based on the Runge-Kutta-Merson method for the approximation of solutions of ordinary differential equations, the other uses the GMRES method for the numerical solution of systems of linear equations. In our experiments, the CUDA implementations of both algorithms are about 3--9 times faster than corresponding 12-threaded OpenMP implementations. (en)
Title	Image segmentation using CUDA implementations of the Runge-Kutta-Merson and GMRES methods Image segmentation using CUDA implementations of the Runge-Kutta-Merson and GMRES methods (en)
skos:prefLabel	Image segmentation using CUDA implementations of the Runge-Kutta-Merson and GMRES methods Image segmentation using CUDA implementations of the Runge-Kutta-Merson and GMRES methods (en)
skos:notation	RIV/68407700:21340/11:00189320!RIV12-MSM-21340___
http://linked.open...avai/predkladatel	Fakulta jaderná a fyzikálně inženýrská
http://linked.open...avai/riv/aktivita	S Z
http://linked.open...avai/riv/aktivity	S, Z(MSM6840770010)
http://linked.open...iv/cisloPeriodika	3
http://linked.open...vai/riv/dodaniDat	2012
http://linked.open...aciTvurceVysledku	Oberhuber, Tomáš Žabka, Vítězslav
http://linked.open.../riv/druhVysledku	J - Článek v odborném periodiku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	České vysoké učení technické v Praze / Fakulta jaderná a fyzikálně inženýrská
http://linked.open...dnocenehoVysledku	203558
http://linked.open...ai/riv/idVysledku	RIV/68407700:21340/11:00189320
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	CUDA; image segmentation; Allen-Cahn equation; Runge-Kutta-Merson; GMRES (en)
http://linked.open.../riv/klicoveSlovo	CUDA image segmentation Allen-Cahn equation GMRES Runge-Kutta-Merson
http://linked.open...odStatuVydavatele	JP - Japonsko
http://linked.open...ontrolniKodProRIV	[808627CE038A]
http://linked.open...i/riv/nazevZdroje	Journal of Math-for-Industry
http://linked.open...in/vavai/riv/obor	IN
http://linked.open...ichTvurcuVysledku	2 (xsd:int)
http://linked.open...cetTvurcuVysledku	4 (xsd:int)
http://linked.open...UplatneniVysledku	2011
http://linked.open...v/svazekPeriodika	2011
http://linked.open...iv/tvurceVysledku	Oberhuber, Tomáš Suzuki, A. Žabka, Vítězslav Vacata, J.
http://linked.open...n/vavai/riv/zamer	Aplikovaná matematika v technických a fyzikálních vědách
issn	1884-4774
number of pages	7 (xsd:int)
http://localhost/t...ganizacniJednotka	21340
is http://linked.open...avai/riv/vysledek of	Image segmentation using CUDA implementations of the Runge-Kutta-Merson and GMRES methods Image segmentation using CUDA implementations of the Runge-Kutta-Merson and GMRES methods

Faceted Search & Find service v1.16.118 as of Jun 21 2024

Alternative Linked Data Documents: ODE Content Formats:

RDF

ODATA

Microdata

About

OpenLink Virtuoso version 07.20.3240 as of Jun 21 2024, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (126 GB total memory, 58 GB memory in use)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software