dc.creatorZabala-Blanco, David
dc.creatorAzurdia-Meza, Cesar A.
dc.creatorDehghan Firoozabadi, Ali
dc.creatorPalacios Játiva, Pablo
dc.date2023-01-23T17:58:23Z
dc.date2023-01-23T17:58:23Z
dc.date2019
dc.date.accessioned2024-05-02T20:30:29Z
dc.date.available2024-05-02T20:30:29Z
dc.identifierhttp://repositorio.ucm.cl/handle/ucm/4425
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/9274668
dc.descriptionOptical 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.
dc.languageen
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 Chile
dc.rightshttp://creativecommons.org/licenses/by-nc-nd/3.0/cl/
dc.sourceIEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies, 2019, 8987659
dc.subjectCompute unified device architecture
dc.subjectOptical packet switching
dc.subjectSerial and parallel computation
dc.subjectWavelength division multiplexing
dc.titleAll-optical routers modeled through the matrix method with NVidia CUDA development framework
dc.typeArticle


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