Self-Repairing Hardware with Astrocyte-Neuron Networks

Research output: Chapter in Book/Report/Conference proceedingConference contribution

14 Citations (Scopus)
13 Downloads (Pure)

Abstract

A Self-rePAiring spiking Neural NEtwoRk(SPANNER) hardware architecture is presented in this paper. Itis based on a software model of an astrocyte-neuron networkwhich previously demonstrated the ability to self-detect faultsand self-repair autonomously. Experimental results in this papershow that when faults occur at the synapse, remaining healthysynapses of the same neuron are enhanced by the feedback fromthe astrocyte, which enables the system functionality to bemaintained. This is the first time that astrocytes cells mergedwithin spiking neurons demonstrate a self-repairing capability inhardware. This achieves a much more fine-grained repaircapability in hardware compared to the conventional faulttolerance techniques.
Original languageEnglish
Title of host publicationUnknown Host Publication
PublisherIEEE
Pages1350-1353
Number of pages4
ISBN (Print)978-1-4799-5340-0
DOIs
Publication statusE-pub ahead of print - 11 Aug 2016
EventIEEE International Symposium on Circuits and Systems (ISCAS) - Canada
Duration: 11 Aug 2016 → …

Conference

ConferenceIEEE International Symposium on Circuits and Systems (ISCAS)
Period11/08/16 → …

Keywords

  • Astrocyte
  • spiking neural networks
  • fault tolerance
  • FPGAs
  • repair

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