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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 neurons and 2.5 x 108 synapses, with a typical performance of 900 s, Beowulf processing time, per simulated second.
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), 307-315. (doi:10.1016/S0925-2312(01)00668-3).

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 neurons and 2.5 x 108 synapses, with a typical performance of 900 s, Beowulf processing time, per simulated second.

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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: 16 Mar 2024 02:35

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Contributors

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

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