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Behavioral simulation and synthesis of biological neuron systems using synthesizable VHDL

Behavioral simulation and synthesis of biological neuron systems using synthesizable VHDL
Behavioral simulation and synthesis of biological neuron systems using synthesizable VHDL
Neurons are complex biological entities which form the basis of nervous systems. Insight can be gained into neuron behavior through the use of computer models and as a result many such models have been developed. However, there exists a trade-off between biological accuracy and simulation time with the most realistic results requiring extensive computation. To address this issue, a novel approach is described in this paper that allows complex models of real biological systems to be simulated at a speed greater than real time and with excellent accuracy. The approach is based on a specially developed neuron model VHDL library which allows complex neuron systems to be implemented on field programmable gate array (FPGA) hardware. The locomotion system of the nematode Caenorhabditis elegans is used as a case study and the measured results show that the real time FPGA based implementation performs 288 times faster than traditional ModelSim simulations for the same accuracy.
vhdl, neuron, network, hardware, simulation
0925-2312
2392- 2406
Bailey, J.A.
7b855f30-6803-47cd-bc2e-920aaa96c1d4
Wilcock, R.
039894e9-f32d-49e0-9ebd-fb13bc489feb
Wilson, P.R.
8a65c092-c197-4f43-b8fc-e12977783cb3
Chad, J.E.
d220e55e-3c13-4d1d-ae9a-1cfae8ccfbe1
Bailey, J.A.
7b855f30-6803-47cd-bc2e-920aaa96c1d4
Wilcock, R.
039894e9-f32d-49e0-9ebd-fb13bc489feb
Wilson, P.R.
8a65c092-c197-4f43-b8fc-e12977783cb3
Chad, J.E.
d220e55e-3c13-4d1d-ae9a-1cfae8ccfbe1

Bailey, J.A., Wilcock, R., Wilson, P.R. and Chad, J.E. (2011) Behavioral simulation and synthesis of biological neuron systems using synthesizable VHDL. Neurocomputing, 74 (14-15), 2392- 2406. (doi:10.1016/j.neucom.2011.04.001).

Record type: Article

Abstract

Neurons are complex biological entities which form the basis of nervous systems. Insight can be gained into neuron behavior through the use of computer models and as a result many such models have been developed. However, there exists a trade-off between biological accuracy and simulation time with the most realistic results requiring extensive computation. To address this issue, a novel approach is described in this paper that allows complex models of real biological systems to be simulated at a speed greater than real time and with excellent accuracy. The approach is based on a specially developed neuron model VHDL library which allows complex neuron systems to be implemented on field programmable gate array (FPGA) hardware. The locomotion system of the nematode Caenorhabditis elegans is used as a case study and the measured results show that the real time FPGA based implementation performs 288 times faster than traditional ModelSim simulations for the same accuracy.

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Paper-2010-11-01v4.pdf - Author's Original
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More information

e-pub ahead of print date: 17 April 2011
Published date: July 2011
Keywords: vhdl, neuron, network, hardware, simulation
Organisations: EEE, Centre for Biological Sciences

Identifiers

Local EPrints ID: 272285
URI: https://eprints.soton.ac.uk/id/eprint/272285
ISSN: 0925-2312
PURE UUID: bbcca083-af48-4044-bcdd-290caa9da14b
ORCID for J.E. Chad: ORCID iD orcid.org/0000-0001-6442-4281

Catalogue record

Date deposited: 16 May 2011 13:03
Last modified: 31 Jul 2019 00:54

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