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dc.contributor.authorConte, Dajana
dc.contributor.authorCuesta Montero, Eduardo 
dc.contributor.authorValentino, Carmine
dc.date.accessioned2023-06-23T12:09:08Z
dc.date.available2023-06-23T12:09:08Z
dc.date.issued2023
dc.identifier.citationNumerical Algorithms, 2023.es
dc.identifier.issn1017-1398es
dc.identifier.urihttps://uvadoc.uva.es/handle/10324/59952
dc.descriptionProducción Científicaes
dc.description.abstractIn the present paper, a parallel-in-time discretization of linear systems of Volterra equations of type u¯(t)=u¯0+∫t0K(t−s)u¯(s) d s+f¯(t),0<t≤T, is addressed. Related to the analytical solution, a general enough functional setting is firstly stated. Related to the numerical solution, a parallel numerical scheme based on the Non-Stationary Wave Relaxation (NSWR) method for the time discretization is proposed, and its convergence is studied as well. A CUDA parallel implementation of the method is carried out in order to exploit Graphics Processing Units (GPUs), which are nowadays widely employed for reducing the computational time of several general purpose applications. The performance of these methods is compared to some sequential implementation. It is revealed throughout several experiments of special interest in practical applications the good performance of the parallel approach.es
dc.format.mimetypeapplication/pdfes
dc.language.isoenges
dc.publisherSpringeres
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subject.classificationParallel-in-timees
dc.subject.classificationVolterra equationses
dc.subject.classificationWave relaxationes
dc.subject.classificationGPUes
dc.titleNon-stationary wave relaxation methods for general linear systems of Volterra equations: convergence and parallel GPU implementationes
dc.typeinfo:eu-repo/semantics/articlees
dc.rights.holder© 2023 The Author(s)es
dc.identifier.doi10.1007/s11075-023-01567-0es
dc.relation.publisherversionhttps://link.springer.com/article/10.1007/s11075-023-01567-0es
dc.identifier.publicationtitleNumerical Algorithmses
dc.peerreviewedSIes
dc.description.projectMinisterio de Universidades e Investigación de Italia (MUR), a través del proyecto PRIN 2017 (No. 2017JYCLSF) “Aproximación preservadora de estructuras de problemas evolutivos”es
dc.description.projectPublicación en abierto financiada por el Consorcio de Bibliotecas Universitarias de Castilla y León (BUCLE), con cargo al Programa Operativo 2014ES16RFOP009 FEDER 2014-2020 DE CASTILLA Y LEÓN, Actuación:20007-CL - Apoyo Consorcio BUCLEes
dc.identifier.essn1572-9265es
dc.rightsAtribución 4.0 Internacional*
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones
dc.subject.unesco12 Matemáticases


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