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dc.contributor.authorZabala-Blanco, David
dc.contributor.authorAzurdia-Meza, Cesar A.
dc.contributor.authorDehghan Firoozabadi, Ali
dc.contributor.authorPalacios Játiva, Pablo
dc.date.accessioned2023-01-23T17:58:23Z
dc.date.available2023-01-23T17:58:23Z
dc.date.issued2019
dc.identifier.urihttp://repositorio.ucm.cl/handle/ucm/4425
dc.description.abstractOptical packet switching (OPS) is a promising technology in order to satisfy the ever-increasing need for bandwidth. With this technology, data packets, which consist of a header and a payload, are assembled and transmitted over a wavelength division multiplexing network. Headers are processed electronically in the routers that comprise the network. This processing must be carried out as quickly and efficiently as possible in order to avoid packet loss. On the other hand, parallel computing has recently been extended and popularized thanks to the NVidia compute unified device architecture (CUDA) development framework. In this programming paradigm, several threads run the same code simultaneously in order to reduce the overall processing time. This work shows that an optical routing algorithm for OPS can perform better under parallel execution, depending on the amount of data to be processed. A routing method based on simple matrices is presented, and the computation time between a traditional sequential programming languages (C++), and CUDA C is presented. Other performance metrics related to the router dimensioning are also considered.es_CL
dc.language.isoenes_CL
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 Chile*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/cl/*
dc.sourceIEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies, 2019, 8987659es_CL
dc.subjectCompute unified device architecturees_CL
dc.subjectOptical packet switchinges_CL
dc.subjectSerial and parallel computationes_CL
dc.subjectWavelength division multiplexinges_CL
dc.titleAll-optical routers modeled through the matrix method with NVidia CUDA development frameworkes_CL
dc.typeArticlees_CL
dc.ucm.facultadFacultad de Ciencias de la Ingenieríaes_CL
dc.ucm.indexacionScopuses_CL
dc.ucm.uriieeexplore.ieee.org/document/8987659es_CL
dc.ucm.doidoi.org/10.1109/CHILECON47746.2019.8987659es_CL


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Atribución-NoComercial-SinDerivadas 3.0 Chile
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