On-chip communication for neuro-glia networks

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Abstract

Hardware has become more prone to faults as a result of geometric scaling, wear-out and faults caused during the manufacturing process, therefore, the reliability of hardware is reliant on the need to continually adapt to faults. A computational model of biological self-repair in the brain, derived from observing the role of astrocytes (a glial cell found in the mammalian brain), has captured self-repair within models of neural networks known as neuro-glia networks. This astrocyte-driven repair process can address the issues of faulty synapse connections between neurons. These astrocyte cells are distributed throughout a neuro-glia network and regulate synaptic activity, and it has been observed in computational models that this can result in a fine-grained self-repair process. Therefore, mapping neuro-glia networks to hardware provides a strategy for achieving self-repair in hardware. The internal interconnecting of these networks in hardware is a challenge. Previous work has focused on addressing neuron to astrocyte communication (local), however, the global self-repair process is dependent on the communication infrastructure between astrocyte-to-astrocyte; e.g. astrocyte network. This study addresses the key challenge of providing a scalable communication interconnect for global astrocyte network requirements and how it integrates with existing local communication mechanism. Area/power results demonstrate scalable implementations with the ring topology while meeting timing requirements.
Original languageEnglish
Pages (from-to)130-138
Number of pages9
JournalIET Computers and Digital Techniques
Volume12
Issue number4
Early online date8 May 2018
DOIs
Publication statusPublished - 1 Jul 2018

Keywords

  • Integrated circuit interconnections
  • Neural chips

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