High-Performance Computing for Systems of Spiking Neurons

S. B. Furber, S. Temple and A. D. Brown

Abstract

We propose a bottom-up computer engineering approach to the Grand Challenge of understanding the Architecture of Brain and Mind as a viable complement to top-down modelling and alternative approaches informed by the skills and philosophies of other disciplines. Our approach starts from the observation that brains are built from spiking neurons and then progresses by looking for a sys-tematic way to deploy spiking neurons as components from which useful information processing functions can be constructed, at all stages being informed (but not constrained) by the neural struc-tures and microarchitectures observed by neuroscientists as playing a role in biological systems. In order to explore the behaviours of large-scale complex systems of spiking neuron components we require high-performance computing equipment, and we propose the construction of a machine spe-cifically for this task - a massively parallel computer designed to be a universal spiking neural net-work simulation engine.

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