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CAVIAR: A 45k Neuron, 5M Synapse, 12G Connects/s AER Hardware Sensory--Processing--Learning--Actuating System for High-Speed Visual Object Recognition and Tracking.

Authors :
Gotarredona, Rafael Serrano
Oster, Matthias
Lichtsteiner, Patrick
Linares-Barranco, Alejandro
Paz-Vicente, Rafael
Gómez-Rodríguez, Francisco
Camuñas-Mesa, Luis
Berner, Raphael
Rivas-Pérez, Manuel
Delbrück, Tobi
Liu, Shih-Chii
Douglas, Rodney
Häfliger, Philipp
Jiménez-Moreno, Gabriel
Ballcels, Anton Civit
Serrano-Gotarredona, Teresa
Acosta-Jiménez, Antonio J.
Linares-Barranco, Bernabé
Source :
IEEE Transactions on Neural Networks; Sep2009, Vol. 20 Issue 9, p1417-1438, 22p, 15 Diagrams, 5 Charts, 8 Graphs
Publication Year :
2009

Abstract

This paper describes CAVIAR, a massively parallel hardware implementation of a spike-based sensing-processing- learning-actuating system inspired by the physiology of the nervous system. CAVIAR uses the asychronous address-event representation (AER) communication framework and was developed in the context of a European Union funded project. has four custom mixed-signal AER chips, five custom digital AER interface components, 45k neurons (spiking cells), up to 5M synapses, performs 12G synaptic operations per second, and achieves millisecond object recognition and tracking latencies. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10459227
Volume :
20
Issue :
9
Database :
Complementary Index
Journal :
IEEE Transactions on Neural Networks
Publication Type :
Academic Journal
Accession number :
44232970
Full Text :
https://doi.org/10.1109/TNN.2009.2023653