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    SpiNNaker: a 1-W 18-core system-on-chip for massively-parallel neural network simulation

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    Authors
    Painkras, Eustace
    Plana, Luis A.
    Garside, Jim D.
    Temple, Steve
    Galluppi, Francesco
    Patterson, Cameron
    Lester, David R.
    Brown, Andrew D.
    Furber, Steve B.
    Affiliation
    University of Manchester
    Issue Date
    2013-08
    Subjects
    chip multiprocessor
    energy-efficiency
    asynchronous interconnect
    gals
    network-on-chip
    neuromorphic hardware
    spiking neural networks
    real-time simulation
    
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    Abstract
    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):1943
    Publisher
    IEEE
    Journal
    IEEE Journal of Solid-State Circuits
    URI
    http://hdl.handle.net/10547/593703
    DOI
    10.1109/JSSC.2013.2259038
    Additional Links
    http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6515159
    http://eprints.soton.ac.uk/350493/
    Type
    Article
    Language
    en
    ISSN
    0018-9200
    1558-173X
    ae974a485f413a2113503eed53cd6c53
    10.1109/JSSC.2013.2259038
    Scopus Count
    Collections
    Centre for Research in Distributed Technologies (CREDIT)

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