Reconfigurable platforms and the challenges for large-scale implementations of spiking neural networks

Jim Harkin, Fearghal Morgan, Steve Hall, Piotr Dudek, Thomas Dowrick, Liam McDaid

Research output: Chapter in Book or Conference Publication/ProceedingConference Publicationpeer-review

23 Citations (Scopus)

Abstract

FPGA devices have witnessed popularity in their use for the rapid prototyping of biological Spiking Neural Network (SNNs) applications, as they offer the key requirement of reconfigurability. However, FPGAs do not efficiently realise the biological neuron/synaptic models. Also their routing structures cannot accommodate the high levels of neuron inter-connectivity inherent in complex SNNs. This paper highlights and discusses the current challenges of implementing large scale SNNs on reconfigurable FPGAs. The paper presents a novel Field Programmable Neural Network (FPNN) architecture incorporating low power analogue synapse and a network on chip architecture for SNN routing and configuration. Initial results are presented.

Original languageEnglish
Title of host publicationProceedings - 2008 International Conference on Field Programmable Logic and Applications, FPL
PublisherIEEE Computer Society
Pages483-486
Number of pages4
ISBN (Print)9781424419616
DOIs
Publication statusPublished - 2008
Event2008 International Conference on Field Programmable Logic and Applications, FPL - Heidelberg, Germany
Duration: 8 Sep 200810 Sep 2008

Publication series

NameProceedings - 2008 International Conference on Field Programmable Logic and Applications, FPL

Conference

Conference2008 International Conference on Field Programmable Logic and Applications, FPL
Country/TerritoryGermany
CityHeidelberg
Period8/09/0810/09/08

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