A scalable chip multiprocessor for large-scale neural simulation

Lead Research Organisation: University of Southampton
Department Name: Electronics and Computer Science

Abstract

See Joint Proposal D232208

Publications

10 25 50
 
Description The human brain remains as one of the great frontiers of science - how does this organ upon which we all depend so critically actually do its job? A great deal is known about the underlying technology - the neuron - and we can observe large-scale brain activity through techniques such as magnetic resonance imaging, but this knowledge barely starts to tell us how the brain works. Something is happening at the intermediate levels of processing that we have yet to begin to understand, but the essence of the brain's information processing function probably lies in these intermediate levels. To get at these middle layers requires that we build models of very large systems of spiking neurons, with structures inspired by the increasingly detailed findings of neuroscience, in order to investigate the emergent behaviours of those systems.

High-performance microprocessors have reached a brick wall in terms of improving single-thread performance. The technology advances that have delivered exponential performance gains over the last 3 decades will not deliver the same gains in the future, and a new approach is required. Industry giants, including Intel, are all agreed that the continuing increases in chip transistor count can no longer be turned into making one processor faster, but should instead be turned into putting more processors onto a chip. This delivers more total performance, but through parallelism, not single-thread performance.

The grant was an early stepping stone to a much larger vision of creating a system containing a million cores; (subsequently funded by EPSRC EP/D079594/1, Samsung and others). "Project findings" is not really an appropriate term. It was an (extremely successful) enabling project.
Exploitation Route See "potential use" in the follow-on project, EPSRC EP/D079594/1. See "exploitation routes" in the follow-on project, EPSRC EP/D079594/1.
Sectors Digital/Communication/Information Technologies (including Software)

Electronics

Pharmaceuticals and Medical Biotechnology

URL http://www.cs.manchester.ac.uk/apt
 
Description See apt/cs/manchester.ac.uk/projects/SpiNNaker
First Year Of Impact 2008
Sector Digital/Communication/Information Technologies (including Software)
 
Description A R M Ltd 
Organisation Arm Limited
Country United Kingdom 
Sector Private 
Start Year 2006
 
Description Silistix Ltd 
Organisation Silistix Ltd
Country United Kingdom 
Sector Private 
Start Year 2006