CAVIAR: a 45k neuron, 5M synapse, 12G connects/s AER hardware sensory-processing- learning-actuating system for high-speed visual object recognition and tracking.
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. It 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.
Serrano-Gotarredona
Rafael
R
Austriamicrosystems, Valencia, Spain. rserrano@imse.cnm.es
Oster
Matthias
M
Lichtsteiner
Patrick
P
Linares-Barranco
Alejandro
A
Paz-Vicente
Rafael
R
Gomez-Rodriguez
Francisco
F
Camunas-Mesa
Luis
L
Berner
Raphael
R
Rivas-Perez
Manuel
M
Delbruck
Tobi
T
Liu
Shih-Chii
SC
Douglas
Rodney
R
Hafliger
Philipp
P
Jimenez-Moreno
Gabriel
G
Civit Ballcels
Anton
A
Serrano-Gotarredona
Teresa
T
Acosta-Jimenez
Antonio J
AJ
Linares-Barranco
Bernabé
B
D000200:Action Potentials; D001185:Artificial Intelligence; D003201:Computers; D006801:Humans; D007858:Learning / Q000502:physiology; D009039:Motion Perception / Q000502:physiology; D016571:Neural Networks, Computer; D009474:Neurons / Q000502:physiology; D010364:Pattern Recognition, Visual / Q000502:physiology; D011597:Psychomotor Performance / Q000502:physiology; D012160:Retina / Q000502:physiology; D013569:Synapses / Q000502:physiology; D013997:Time Factors; D014785:Vision, Ocular / Q000502:physiology; D014796:Visual Perception / Q000502:physiology