EMBRACE: emulating biologically-inspired architectures on hardware

Authors:
L. McDaid;J. Harkin;S. Hall;T. Dowrick;Y. Chen;J. Marsland
Affiliations:
Intelligent Systems Research Centre, University of Ulster, N. Ireland;Intelligent Systems Research Centre, University of Ulster, N. Ireland;Department of Electrical Eng. & Electronics, University of Liverpool, UK;Department of Electrical Eng. & Electronics, University of Liverpool, UK;Department of Electrical Eng. & Electronics, University of Liverpool, UK;Department of Electrical Eng. & Electronics, University of Liverpool, UK
Venue:
NN'08 Proceedings of the 9th WSEAS International Conference on Neural Networks
Year:
2008

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Abstract

This paper highlights and discusses the current challenges in the implementation of large scale Spiking Neural Networks (SNNs) in hardware. A mixed-mode approach to realising scalable SNNs on a reconfigurable hardware platform is presented. The approach uses compact low power analogue spiking neuron cells, with a weight storage capability, interconnected using Network on Chip (NoC) routers. Results presented show that this route to hardware implementation is promising.