CAVIAR: A 45k neuron, 5M synapse, 12G connects/s AER hardware sensory-processing-learning-actuating system for high-speed visual object recognition and tracking
et al. ; 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. © 2009 IEEE. ; This work was supported by the European Commission under Grant IST-2001-34124 (CAVIAR). The work of R. Serrano-Gotarredona was supported by the Spanish Ministry of Education and Science under FPU scholarship. The work of L. Camuñas-Mesa was supported by the Spanish Ministry of Education and Science under FPI scholarship. ; Peer Reviewed