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/Report/Conference proceedingConference contributionpeer-review

    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. ©2008 IEEE.
    Original languageEnglish
    Title of host publicationProceedings - 2008 International Conference on Field Programmable Logic and Applications, FPL|Proc. - Int. Conf. Field Programmable Logic Appl., FPL
    Pages483-486
    Number of pages3
    DOIs
    Publication statusPublished - 2008
    Event2008 International Conference on Field Programmable Logic and Applications, FPL - Heidelberg
    Duration: 1 Jul 2008 → …

    Conference

    Conference2008 International Conference on Field Programmable Logic and Applications, FPL
    CityHeidelberg
    Period1/07/08 → …

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