RT journal article
T1 NESIM-RT: A real-time distributed spiking neural network simulator
A1 Rosa-Gallardo, Daniel J.
A1 Torre Macías, Juan Carlos de la
A1 Quintana Velázquez, Fernando Manuel
A1 Domínguez Morales, Juan P.
A1 Pérez Peña, Fernando
A2 Ingeniería en AutomáticaElectrónica, Arquitectura y Redes de Computadores
A2 Ingeniería Informática
K1 Neuromorphic engineering
K1 Simulation
K1 Spiking neural networks
AB The 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 implementation
PB Elsevier
SN 2352-7110
YR 2023
FD 2023-05
LK http://hdl.handle.net/10498/28890
UL http://hdl.handle.net/10498/28890
LA eng
NO Fernando 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.
DS Repositorio Institucional de la Universidad de Cádiz
RD 10-may-2026