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A communication infrastructure for emulating large-scale neural networks models
Barrera, A.G.; Moreno Aróstegui, Juan Manuel
Universitat Politècnica de Catalunya. Departament d'Enginyeria Electrònica; Universitat Politècnica de Catalunya. AHA - Arquitectures Hardware Avançades
This paper presents the SEPELYNS architecture that permits to in- terconnect multiple spiking neurons focused on hardware implementations. SEPELYNS can connect millions of neur ons with thousands of synapses per neuron in a layered fabric that provides some capabilities such as connectivity, expansion, flexibility, bio-plausibility and reusing of resources that allows si- mulation of very large networks. We presen t the three layers of this architecture (neuronal, network adapters and networks on chip layers) and explain its per- formance parameters such as throughput, latency and hardware resources. Some application examples of large neural networks on SEPELYNS are studied; these will show that use of on-chip parallel networks could permit the hardware simulation of populations of spiking neurons.
Peer Reviewed
Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Telemàtica i xarxes d'ordinadors::Serveis telemàtics i de comunicació multimèdia
Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Telemàtica i xarxes d'ordinadors
Xarxes neuronals (Informàtica)
Neural networks (Computer science)
Xarxes neuronals (Informàtica)

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