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Scalable cortical simulations on Beowulf architectures

Claverol, E.T., Brown, A.D. and Chad, J.E. (2002) Scalable cortical simulations on Beowulf architectures Neurocomputing, 43, (1), pp. 307-315. (doi:10.1016/S0925-2312(01)00668-3).

Record type: Article


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.

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Published date: 2002
Keywords: cellular automata neuronal networks


Local EPrints ID: 37943
ISSN: 0925-2312
PURE UUID: 1c0c8b1d-c54c-4cf5-a80e-cc521fb8c798
ORCID for J.E. Chad: ORCID iD

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Date deposited: 26 May 2006
Last modified: 17 Jul 2017 15:40

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

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