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Rapport (Rapport De Recherche) Année : 2017

N2S3, an Open-Source Scalable Spiking Neuromorphic Hardware Simulator

Résumé

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.
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Dates et versions

hal-01432133 , version 1 (12-01-2017)
hal-01432133 , version 2 (12-01-2017)

Licence

Paternité - Partage selon les Conditions Initiales

Identifiants

  • HAL Id : hal-01432133 , version 2

Citer

Pierre Boulet, Philippe Devienne, Pierre Falez, Guillermo Polito, Mahyar Shahsavari, et al.. N2S3, an Open-Source Scalable Spiking Neuromorphic Hardware Simulator. [Research Report] Université de Lille 1, Sciences et Technologies; CRIStAL UMR 9189. 2017. ⟨hal-01432133v2⟩
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