Accelerating event based simulation for multi-synapse spiking neural networks

Authors:
Michiel D’Haene;Benjamin Schrauwen;Dirk Stroobandt
Affiliations:
Department of Electronics and Information Systems, Ghent University, Ghent, Belgium;Department of Electronics and Information Systems, Ghent University, Ghent, Belgium;Department of Electronics and Information Systems, Ghent University, Ghent, Belgium
Venue:
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part I
Year:
2006

Citing 5
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Abstract

The simulation of large spiking neural networks (SNN) is still a very time consuming task. Therefore most simulations are limited to rather unrealistic small or medium sized networks (typically hundreds of neurons). In this paper, some methods for the fast simulation of large SNN are discussed. Our results equally amongst others show that event based simulation is an efficient way of simulating SNN, although not all neuron models are suited for an event based approach. We compare some models and discuss several techniques for accelerating the simulation of more complex models. Finally we present an algorithm that is able to handle multi-synapse models efficiently.