The University of Southampton
University of Southampton Institutional Repository

Scalable cortical simulations on Beowulf architectures

Scalable cortical simulations on Beowulf architectures
Scalable cortical simulations on Beowulf architectures
Biologically motivated simulation of large scale neural networks is a computationally costly task. In this paper, a commodity 8-node Beowulf architecture is proposed as a scalable low cost environment for studies of cortical dynamics, By means of a distributed message-based event-driven framework, the size of memory-limited tractable problems increased 8-fold, resulting in a mere 8.3% increase in elapsed CPU time, attributable to inter-process communication overhead. The attainable network size reached over 106 neu- rons and 2.5 x 108 synapses, with a typical performance of 900 s, Beowulf processing time, per simulated second. (C) 2002 Elsevier Science B.V. All rights reserved.
cellular automata neuronal networks
0925-2312
307-315
Claverol, E.T.
e3eb160d-3309-4c6b-9fb6-6a0f9fe05ac2
Brown, A.D.
5c19e523-65ec-499b-9e7c-91522017d7e0
Chad, J.E.
d220e55e-3c13-4d1d-ae9a-1cfae8ccfbe1
Claverol, E.T.
e3eb160d-3309-4c6b-9fb6-6a0f9fe05ac2
Brown, A.D.
5c19e523-65ec-499b-9e7c-91522017d7e0
Chad, J.E.
d220e55e-3c13-4d1d-ae9a-1cfae8ccfbe1

Claverol, E.T., Brown, A.D. and Chad, J.E. (2002) Scalable cortical simulations on Beowulf architectures Neurocomputing, 43, (1), pp. 307-315.

Record type: Article

Abstract

Biologically motivated simulation of large scale neural networks is a computationally costly task. In this paper, a commodity 8-node Beowulf architecture is proposed as a scalable low cost environment for studies of cortical dynamics, By means of a distributed message-based event-driven framework, the size of memory-limited tractable problems increased 8-fold, resulting in a mere 8.3% increase in elapsed CPU time, attributable to inter-process communication overhead. The attainable network size reached over 106 neu- rons and 2.5 x 108 synapses, with a typical performance of 900 s, Beowulf processing time, per simulated second. (C) 2002 Elsevier Science B.V. All rights reserved.

Full text not available from this repository.

More information

Published date: 2002
Keywords: cellular automata neuronal networks

Identifiers

Local EPrints ID: 37943
URI: http://eprints.soton.ac.uk/id/eprint/37943
ISSN: 0925-2312
PURE UUID: 1c0c8b1d-c54c-4cf5-a80e-cc521fb8c798
ORCID for J.E. Chad: ORCID iD orcid.org/0000-0001-6442-4281

Catalogue record

Date deposited: 26 May 2006
Last modified: 12 Oct 2017 08:24

Export record

Contributors

Author: E.T. Claverol
Author: A.D. Brown
Author: J.E. Chad ORCID iD

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×