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dc.contributor.authorCastro, Manuel de
dc.contributor.authorOsorio, Roberto R.
dc.contributor.authorVilariño, David L.
dc.contributor.authorGonzález Escribano, Arturo 
dc.contributor.authorLlanos Ferraris, Diego Rafael 
dc.date.accessioned2023-02-06T12:41:42Z
dc.date.available2023-02-06T12:41:42Z
dc.date.issued2023
dc.identifier.citationThe Journal of Supercomputing, 2023.es
dc.identifier.issn0920-8542es
dc.identifier.urihttps://uvadoc.uva.es/handle/10324/58513
dc.descriptionProducción Científicaes
dc.description.abstractMotion Estimation is one of the main tasks behind any video encoder. It is a compu- tationally costly task; therefore, it is usually delegated to specific or reconfigurable hardware, such as FPGAs. Over the years, multiple FPGA implementations have been developed, mainly using hardware description languages such as Verilog or VHDL. Since programming using hardware description languages is a complex task, it is desirable to use higher-level languages to develop FPGA applications.The aim of this work is to evaluate OpenCL, in terms of expressiveness, as a tool for devel- oping this kind of FPGA applications. To do so, we present and evaluate a parallel implementation of the Block Matching Motion Estimation process using OpenCL for Intel FPGAs, usable and tested on an Intel Stratix 10 FPGA. The implementa- tion efficiently processes Full HD frames completely inside the FPGA. In this work, we show the resource utilization when synthesizing the code on an Intel Stratix 10 FPGA, as well as a performance comparison with multiple CPU implementations with varying levels of optimization and vectorization capabilities. We also compare the proposed OpenCL implementation, in terms of resource utilization and perfor- mance, with estimations obtained from an equivalent VHDL implementation.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.classificationFPGAes
dc.subject.classificationOpenCLes
dc.subject.classificationMotion estimationes
dc.subject.classificationVideo codinges
dc.titleImplementation of a motion estimation algorithm for Intel FPGAs using OpenCLes
dc.typeinfo:eu-repo/semantics/articlees
dc.rights.holder© 2023 The Author(s)es
dc.identifier.doi10.1007/s11227-023-05051-3es
dc.relation.publisherversionhttps://link.springer.com/article/10.1007/s11227-023-05051-3es
dc.identifier.publicationtitleThe Journal of Supercomputinges
dc.peerreviewedSIes
dc.description.projectJunta de Castilla y León - Consejería de Educación de la Proyecto PROPHET-2 (VA226P20)es
dc.description.projectMinisterio de Economía, Industria y Competitividad: (PID2019- 104834 GB-I00) and European Regional Development Fund (ERDF) program: Project PCAS (TIN2017-88614-R)es
dc.description.projectMinisterio de Ciencia e Innovación (PID2019-104184RB-I00 / AEI / 10.13039/501100011033)es
dc.description.projectXunta de Galicia y fondos FEDER de la UE (Centro de Investigación de Galicia acreditación 2019-2022, ref. ED431G 2019/01; Consolidation Program of Competitive Reference Groups, ref. ED431C 2021/30es
dc.description.projectMinisterio de Ciencia e Innovación, Agencia Estatal de Investigación y “European Union NextGenerationEU/PRTR” : (MCIN/ AEI/10.13039/501100011033) - grant TED2021-130367B-I00es
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.essn1573-0484es
dc.rightsAtribución 4.0 Internacional*
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones
dc.subject.unesco1203.17 Informáticaes
dc.subject.unesco12 Matemáticases


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