Loading...
Loading...

Go to the content (press return)

SNAVA—A real-time multi-FPGA multi-model spiking neural network simulation architecture

Author
Sripad T A, A.; Sanchez, G.; Zapata, M.; Pirrone, V.; Dorta, S.; Cambria, S.; Marti, A.; Krishnamourthy, K.; Madrenas, J.
Type of activity
Journal article
Journal
Neural networks
Date of publication
2018-01-01
Volume
97
Number
January 2018
First page
28
Last page
45
DOI
https://doi.org/10.1016/j.neunet.2017.09.011 Open in new window
Repository
http://hdl.handle.net/2117/116840 Open in new window
URL
http://www.sciencedirect.com/science/article/pii/S0893608017302150?via%3Dihub Open in new window
Abstract
Spiking Neural Networks (SNN) for Versatile Applications (SNAVA) simulation platform is a scalable and programmable parallel architecture that supports real-time, large-scale, multi-model SNN computation. This parallel architecture is implemented in modern Field-Programmable Gate Arrays (FPGAs) devices to provide high performance execution and flexibility to support large-scale SNN models. Flexibility is defined in terms of programmability, which allows easy synapse and neuron implementation. Th...
Citation
Sripad T A, A., Sanchez , G., Zapata, M., Pirrone, V., Dorta, S., Cambria, S., Marti, A., Krishnamourthy, K., Madrenas, J. SNAVA—A real-time multi-FPGA multi-model spiking neural network simulation architecture. "Neural networks", 1 Gener 2018, vol. 97, núm. January 2018, p. 28-45.
Keywords
Digital neural simulation, FPGA, Neuromorphic systems, SNNs
Group of research
ISSET - Integrated Smart Sensors and Health Technologies

Participants

  • Sripad T A, Athul  (author)
  • Sanchez Rivera, Giovanny  (author)
  • Zapata Rodríguez, Mireya  (author)
  • Pirrone, Vito  (author)
  • Dorta Perez, Silvestre Taho  (author)
  • Cambria, Salvatore  (author)
  • Marti Cabarrocas, Albert  (author)
  • Krishnamourthy, Karthikeyan  (author)
  • Madrenas Boadas, Jordi  (author)

Attachments