SpiNNaker: A 1-W 18-Core System-on-Chip for Massively-Parallel Neural Network Simulation

The modelling of large systems of spiking neurons is computationally very demanding in terms of processing power and communication. SpiNNaker - Spiking Neural Network architecture - is a massively parallel computer system designed to provide a cost-effective and flexible simulator for neuroscience e...

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Bibliographic Details
Published in:	IEEE journal of solid-state circuits Vol. 48; no. 8; pp. 1943 - 1953
Main Authors:	Painkras, Eustace, Plana, Luis A., Garside, Jim, Temple, Steve, Galluppi, Francesco, Patterson, Cameron, Lester, David R., Brown, Andrew D., Furber, Steve B.
Format:	Journal Article Conference Proceeding
Language:	English
Published:	New York, NY IEEE 01.08.2013 Institute of Electrical and Electronics Engineers
Subjects:	Applied sciences Asynchronous interconnect Biological system modeling Brain modeling chip multiprocessor Computational modeling Computer systems Electric, optical and optoelectronic circuits Electronics energy efficiency Exact sciences and technology globally asynchronous locally synchronous (GALS) Hardware Integrated circuits Integrated circuits by function (including memories and processors) network-on-chip Neural networks neuromorphic hardware Neurons real-time simulation Semiconductor electronics. Microelectronics. Optoelectronics. Solid state devices spiking neural networks (SNNs) System-on-chip Transistors Spiking neuron Processor Asynchronous interconnect neuromorphic hardware Modeling Implementation Multiprocessor Microelectronic fabrication Parallel system globally asynchronous locally synchronous (GALS) energy efficiency Parallel processing chip multiprocessor Chemical mechanical polishing Computer design spiking neural networks (SNNs) Large scale system Globally asynchronous locally synchronous Packet switching network-on-chip System design System on a chip Parallel architectures Parallel computer Neural network Synapse real-time simulation Integrated circuit Computer system Simulator Asynchronous transmission
ISSN:	0018-9200, 1558-173X
Online Access:	Get full text
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