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dc.contributor.authorRosa-Gallardo, Daniel J.
dc.contributor.authorTorre Macías, Juan Carlos de la 
dc.contributor.authorQuintana Velázquez, Fernando Manuel 
dc.contributor.authorDomínguez Morales, Juan P.
dc.contributor.authorPérez Peña, Fernando 
dc.contributor.otherIngeniería en Automática, Electrónica, Arquitectura y Redes de Computadoreses_ES
dc.contributor.otherIngeniería Informáticaes_ES
dc.date.accessioned2023-06-21T07:49:57Z
dc.date.available2023-06-21T07:49:57Z
dc.date.issued2023-05
dc.identifier.issn2352-7110
dc.identifier.urihttp://hdl.handle.net/10498/28890
dc.description.abstractThe neuromorphic engineering field aims to mimic complex biological structures by means of mathematical models, implementing them in either analog or digital circuits. These models include the dynamic characteristics of biological neurons and synapses, which are interconnected creating spiking neural networks. These are first simulated using software frameworks in order to verify the expected behavior of the implemented model. In this work, a novel software, called NESIM-RT, for simulating spiking neural networks in real time is presented. A friendly user interface allows users to design and modify the network, together with visualising its output in real time. A novel implementation of the MDHCP protocol is proposed to support online changes in the network together with allowing the simulation in a many-cores distributed architecture. The performance of the proposed software is compared with other widely-used simulators in the neuromorphic engineering field, highlighting the advantages in terms of latencies and network scalability. NESIM-RT also allows exporting the SNN model directly to SpiNNaker, enabling an immediate transition between software simulation and hardware implementationes_ES
dc.description.sponsorshipFernando M. Quintana and Juan Carlos de la Torre are funded by the Spanish Ministerio de Ciencia, Innovación Universidades under the FPU grants FPU18/04321 and FPU17/00563 . This work was partially supported by the Spanish grants (with support from the European Regional Development Fund) NEMOVISION ( PID2019-109465RB-I00 ), OPTIMALE ( FEDER-UCA18-108393 ) and MIND-ROB ( PID2019-105556GB-C33 ), together with the Andalusian Regional Project PAIDI2020 GENIUS ( P18-FR-2399 ). Besides, this publication is part of the project TED2021-131880B-I00 supported by the Spanish Ministry (with support from the European Union “NextGenerationEU”). All the authors want to thank Juan Andres Herrera Rodriguez for his support to the manuscript.es_ES
dc.formatapplication/pdfes_ES
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.sourceSoftwareX Vol. 22, may 2023, 101349es_ES
dc.subjectNeuromorphic engineeringes_ES
dc.subjectSimulationes_ES
dc.subjectSpiking neural networkses_ES
dc.titleNESIM-RT: A real-time distributed spiking neural network simulatores_ES
dc.typejournal articlees_ES
dc.rights.accessRightsopen accesses_ES
dc.identifier.doi10.1016/j.softx.2023.101349
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-109465RB-I00/ES/SISTEMAS NEUROMORFICOS PARA VISION ARTIFICIAL/ es_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-105556GB-C33/ES/PERCEPCION Y COGNICION NEUROMORFICA PARA ACTUACION ROBOTICA DE ALTA VELOCIDAD/ es_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/Junta de Andalucía//FEDER-UCA18-108393es_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/Junta de Andalucía//P18-FR-2399es_ES
dc.type.hasVersionVoRes_ES


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Attribution-NonCommercial-NoDerivatives 4.0 Internacional
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