A communication infrastructure for emulating large-scale neural networks models
Document typeConference report
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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.
CitationBarrera, A.; Moreno, J. A communication infrastructure for emulating large-scale neural networks models. A: International Conference on Artificial Neural Networks. "Artificial Neural Networks and Machine Learning-ICANN 2012: 22nd International Conference on Artificial Neural Networks, Lausanne, Switzerland, September 11-14, 2012, proceedings, part I". Lausanne: Springer, 2012, p. 129-136.
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