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On-chip communication for neuro-glia networks

On-chip communication for neuro-glia networks

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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.

http://iet.metastore.ingenta.com/content/journals/10.1049/iet-cdt.2017.0187
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