A Real-Time Hybrid Neuron Network for Highly Parallel Cognitive Systems

G.J. Christiaanse*, A. Zjajo, C. Galuzzi, R. van Leuken

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingAcademicpeer-review

Abstract

For comprehensive understanding of how neurons communicate with each other, new tools need to be developed that can accurately mimic the behaviour of such neurons and neuron networks under 'real-time' constraints. In this paper, we propose an easily customisable, highly pipelined, neuron network design, which executes optimally scheduled floating-point operations for maximal amount of biophysically plausible neurons per FPGA family type. To reduce the required amount of resources without adverse effect on the calculation latency, a single exponent instance is used for multiple neuron calculation operations. Experimental results indicate that the proposed network design allows the simulation of up to 1188 neurons on Virtex7 (XC7VX550T) device in brain real-time yielding a speed-up of x12.4 compared to the state-of-the art.
Original languageEnglish
Title of host publication2016 38TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC)
PublisherIEEE
Pages792-795
Number of pages4
Publication statusPublished - Aug 2016
Event38th Annual International Conference of the IEEE-Engineering in Medicine and Biology Society (EMBC) - Orlando, United States
Duration: 16 Aug 201620 Aug 2016
https://embc.embs.org/2016/#:~:text=August%2016%2D20%2C%202016,USA%20on%20August%2016%2D20.

Publication series

SeriesIEEE Engineering in Medicine and Biology Society Conference Proceedings
ISSN1557-170X

Conference

Conference38th Annual International Conference of the IEEE-Engineering in Medicine and Biology Society (EMBC)
Abbreviated titleEmpowering Individuals Healthcare Decisions through Technology
Country/TerritoryUnited States
CityOrlando
Period16/08/1620/08/16
Internet address

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