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N2S3, an Open-Source Scalable Spiking Neuromorphic Hardware Simulator

Authors :
Boulet, Pierre
Devienne, Philippe
Falez, Pierre
Polito, Guillermo
Shahsavari, Mahyar
Tirilly, Pierre
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL)
Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)
Université de Lille 1, Sciences et Technologies
CRIStAL UMR 9189
Source :
[Research Report] Université de Lille 1, Sciences et Technologies; CRIStAL UMR 9189. 2017
Publication Year :
2017
Publisher :
HAL CCSD, 2017.

Abstract

One of the most promising approaches to overcome the end of Moore's law is neuromorphic computing. Indeed, neural networks already have a great impact on machine learning applications and offer very nice properties to cope with the problems of nanoelectronics manufacturing, such as a good tolerance to device variability and circuit defects, and a low activity, leading to low energy consumption. We present here N2S3 (for Neural Network Scalable Spiking Simulator), an open-source simulator that is built to help design spiking neuromorphic circuits based on nanoelectronics. N2S3 is an event-based simulator and its main properties are flexibility, extensibility, and scalability. One of our goals with the release of N2S3 as open-source software is to promote the reproducibility of research on neuromorphic hardware. We designed N2S3 to be used as a library, to be easily extended with new models and to provide a user-friendly special purpose language to describe the simulations.

Details

Language :
English
Database :
OpenAIRE
Journal :
[Research Report] Université de Lille 1, Sciences et Technologies; CRIStAL UMR 9189. 2017
Accession number :
edsair.dedup.wf.001..bb4ecd2dbb10dea05984ddaaa7209e30