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dc.contributor.author | López Monfort, José Javier | es_ES |
dc.contributor.author | Carnicero Victorio, Diego | es_ES |
dc.contributor.author | Ferrando Jódar, Néstor | es_ES |
dc.contributor.author | Escolano Carrasco, José | es_ES |
dc.date.accessioned | 2014-10-24T16:45:45Z | |
dc.date.available | 2014-10-24T16:45:45Z | |
dc.date.issued | 2013-04 | |
dc.identifier.issn | 0895-7177 | |
dc.identifier.uri | http://hdl.handle.net/10251/43577 | |
dc.description.abstract | The parallelization of the finite-difference time-domain (FDTD) method for room acoustic simulation using graphic processing units (GPUs) has been subject of study even prior to the introduction of GPGPU (general-purpose computing on GPUs) environments such as the compute unified device architecture (CUDA) from Nvidia. A mature architecture nowadays, CUDA offers enough flexibility and processing power to obtain important performance gains with naively ported serial CPU codes. However, careful implementation of the algorithm and appropriate usage of the different subsystems a GPU offers can lead to even further performance improvements. In this paper, we present a detailed study between different approaches to the parallelization of the FDTD method applied to room acoustics modelling, and we describe several optimization guidelines to improve the computation speed when using single precision and double precision floating point model data, nearly doubling the performance obtained by previously published implementations. (C) 2011 Elsevier Ltd. All rights reserved. | es_ES |
dc.description.sponsorship | We thank the anonymous reviewers for their valuable comments and suggestions. We would also like to thank Nvidia for its support through its Academic Partnership Program. This work has been supported by the Ministry of Education and Science under the project TEC2009-14414-C03-01. | en_EN |
dc.language | Inglés | es_ES |
dc.publisher | Elsevier | es_ES |
dc.relation.ispartof | Mathematical and Computer Modelling | es_ES |
dc.rights | Reserva de todos los derechos | es_ES |
dc.subject | Acoustics modelling | es_ES |
dc.subject | FDTD | es_ES |
dc.subject | Parallel computing | es_ES |
dc.subject | Graphics processing unit (GPU) | es_ES |
dc.subject | CUDA | es_ES |
dc.subject | Acoustics | es_ES |
dc.subject.classification | TEORIA DE LA SEÑAL Y COMUNICACIONES | es_ES |
dc.title | Parallelization of the Finite-Difference Time-Domain method for roomacoustics modelling based on CUDA | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.1016/j.mcm.2011.11.075 | |
dc.relation.projectID | info:eu-repo/grantAgreement/MICINN//TEC2009-14414-C03-01/ES/Procesado De Sonido Para Entornos Emergentes De Comunicacion/ / | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Departamento de Comunicaciones - Departament de Comunicacions | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Instituto Universitario de Telecomunicación y Aplicaciones Multimedia - Institut Universitari de Telecomunicacions i Aplicacions Multimèdia | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Instituto de Instrumentación para Imagen Molecular - Institut d'Instrumentació per a Imatge Molecular | es_ES |
dc.description.bibliographicCitation | López Monfort, JJ.; Carnicero Victorio, D.; Ferrando Jódar, N.; Escolano Carrasco, J. (2013). Parallelization of the Finite-Difference Time-Domain method for roomacoustics modelling based on CUDA. Mathematical and Computer Modelling. 57(7-8):1822-1831. doi:10.1016/j.mcm.2011.11.075 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | http://dx.doi.org/10.1016/j.mcm.2011.11.075 | es_ES |
dc.description.upvformatpinicio | 1822 | es_ES |
dc.description.upvformatpfin | 1831 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 57 | es_ES |
dc.description.issue | 7-8 | es_ES |
dc.relation.senia | 206517 | |
dc.contributor.funder | Ministerio de Ciencia e Innovación | es_ES |
dc.contributor.funder | NVIDIA | es_ES |