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Overview of the SpiNNaker system architecture

Overview of the SpiNNaker system architecture
Overview of the SpiNNaker system architecture
SpiNNaker (a contraction of Spiking Neural Network Architecture) is a million-core computing engine whose flagship goal is to be able to simulate the behaviour of aggregates of up to a billion neurons in real time. It consists of an array of ARM9 cores, communicating via packets carried by a custom interconnect fabric. The packets are small (40 or 72 bits), and their transmission is brokered entirely by hardware, giving the overall engine an extremely high bisection bandwidth of over 5 billion packets/s. Three of the principle axioms of parallel machine design - memory coherence, synchronicity and determinism - have been discarded in the design without, surprisingly, compromising the ability to perform meaningful computations. A further attribute of the system is the acknowledgement, from the initial design stages, that the sheer size of the implementation will make component failures an inevitable aspect of day-to-day operation, and fault detection and recovery mechanisms have been built into the system at many levels of abstraction. This paper describes the architecture of the machine and outlines the underlying design philosophy; software and applications are to be described in detail elsewhere, and only introduced in passing here as necessary to illuminate the description.
interconnection architectures, parallel processors, neurocomputers, real-time distributed
1-14
Furber, Steve
5060db9f-746b-4af3-b8e0-53c8b5c9f4a0
Lester, David
be34b678-d6ce-4342-a494-1dad2aaafd75
Plana, Luis
4953a2dd-d707-4a85-a8c4-7194572163f4
Garside, Jim
49f534c3-affe-4929-921a-b518a08d2469
Painkras, Eustace
d8c4c49e-2d13-4590-98ff-cca1d9ada86b
Temple, Steve
eb5e9f04-5529-483e-8e4a-c2a02fca7f2c
Brown, A.D.
5c19e523-65ec-499b-9e7c-91522017d7e0
Furber, Steve
5060db9f-746b-4af3-b8e0-53c8b5c9f4a0
Lester, David
be34b678-d6ce-4342-a494-1dad2aaafd75
Plana, Luis
4953a2dd-d707-4a85-a8c4-7194572163f4
Garside, Jim
49f534c3-affe-4929-921a-b518a08d2469
Painkras, Eustace
d8c4c49e-2d13-4590-98ff-cca1d9ada86b
Temple, Steve
eb5e9f04-5529-483e-8e4a-c2a02fca7f2c
Brown, A.D.
5c19e523-65ec-499b-9e7c-91522017d7e0

Furber, Steve, Lester, David, Plana, Luis, Garside, Jim, Painkras, Eustace, Temple, Steve and Brown, A.D. (2012) Overview of the SpiNNaker system architecture IEEE Transactions on Computers, 99, pp. 1-14.

Record type: Article

Abstract

SpiNNaker (a contraction of Spiking Neural Network Architecture) is a million-core computing engine whose flagship goal is to be able to simulate the behaviour of aggregates of up to a billion neurons in real time. It consists of an array of ARM9 cores, communicating via packets carried by a custom interconnect fabric. The packets are small (40 or 72 bits), and their transmission is brokered entirely by hardware, giving the overall engine an extremely high bisection bandwidth of over 5 billion packets/s. Three of the principle axioms of parallel machine design - memory coherence, synchronicity and determinism - have been discarded in the design without, surprisingly, compromising the ability to perform meaningful computations. A further attribute of the system is the acknowledgement, from the initial design stages, that the sheer size of the implementation will make component failures an inevitable aspect of day-to-day operation, and fault detection and recovery mechanisms have been built into the system at many levels of abstraction. This paper describes the architecture of the machine and outlines the underlying design philosophy; software and applications are to be described in detail elsewhere, and only introduced in passing here as necessary to illuminate the description.

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More information

Published date: 12 June 2012
Keywords: interconnection architectures, parallel processors, neurocomputers, real-time distributed
Organisations: EEE

Identifiers

Local EPrints ID: 350495
URI: http://eprints.soton.ac.uk/id/eprint/350495
PURE UUID: 1b13ca62-1ff8-4b14-91ee-485995883e0d

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Date deposited: 04 Apr 2013 13:05
Last modified: 29 Sep 2017 22:56

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Contributors

Author: Steve Furber
Author: David Lester
Author: Luis Plana
Author: Jim Garside
Author: Eustace Painkras
Author: Steve Temple
Author: A.D. Brown

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