Simulation of spiking neural networks — architectures and implementations

Abstract

The fast simulation of large networks of spiking neurons is a major task for the examination of biology-inspired vision systems. Networks of this type label features by synchronization of spikes and there is strong demand to simulate these effects in real world environments. As the calculations for one model neuron are complex, the digital simulation of large networks is not efficient using existing simulation systems. Consequently, it is necessary to develop special simulation techniques. This article introduces a wide range of concepts for the different parts of digital simulator systems for large vision networks and presents accelerators based on these foundations.