SpiNNaker: a 1-W 18-core system-on-chip for massively-parallel neural network simulation
Authors
Painkras, EustacePlana, Luis A.
Garside, Jim D.
Temple, Steve
Galluppi, Francesco
Patterson, Cameron
Lester, David R.
Brown, Andrew D.
Furber, Steve B.
Affiliation
University of ManchesterIssue Date
2013-08Subjects
chip multiprocessorenergy-efficiency
asynchronous interconnect
gals
network-on-chip
neuromorphic hardware
spiking neural networks
real-time simulation
Metadata
Show full item recordAbstract
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 experiments. It can model up to a billion neurons and a trillion synapses in biological real time. The basic building block is the SpiNNaker Chip Multiprocessor (CMP), which is a custom-designed globally asynchronous locally synchronous (GALS) system with 18 ARM968 processor nodes residing in synchronous islands, surrounded by a lightweight, packet-switched asynchronous communications infrastructure. In this paper, we review the design requirements for its very demanding target application, the SpiNNaker micro-architecture and its implementation issues. We also evaluate the SpiNNaker CMP, which contains 100 million transistors in a 102-mm2 die, provides a peak performance of 3.96 GIPS, and has a peak power consumption of 1 W when all processor cores operate at the nominal frequency of 180 MHz. SpiNNaker chips are fully operational and meet their power and performance requirements.Citation
Painkras, E. et al (2013) 'SpiNNaker: A 1-W 18-Core System-on-Chip for Massively-Parallel Neural Network Simulation' IEEE Journal of Solid-State Circuits 48 (8):1943Publisher
IEEEAdditional Links
http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6515159http://eprints.soton.ac.uk/350493/
Type
ArticleLanguage
enISSN
0018-92001558-173X
ae974a485f413a2113503eed53cd6c53
10.1109/JSSC.2013.2259038