A software framework for tuning the dynamics of neuromorphic silicon towards biology

Authors:
Daniel Brüderle;Andreas Grübl;Karlheinz Meier;Eilif Mueller;Johannes Schemmel
Affiliations:
Kirchhoff Institute for Physics, University of Heidelberg, Heidelberg, Germany;Kirchhoff Institute for Physics, University of Heidelberg, Heidelberg, Germany;Kirchhoff Institute for Physics, University of Heidelberg, Heidelberg, Germany;Kirchhoff Institute for Physics, University of Heidelberg, Heidelberg, Germany;Kirchhoff Institute for Physics, University of Heidelberg, Heidelberg, Germany
Venue:
IWANN'07 Proceedings of the 9th international work conference on Artificial neural networks
Year:
2007

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Abstract

This paper presents configuration methods for an existing neuromorphic hardware and shows first experimental results. The utilized mixed-signal VLSI device implements a highly accelerated network of integrate-and-fire neurons. We present a software framework, which provides the possibility to interface the hardware and explore it from the point of view of neuroscience. It allows to directly compare both spike times and membrane potentials which are emulated by the hardware or are computed by the software simulator NEST, respectively, from within a single software scope. Membrane potential and spike timing dependent plasticity measurements are shown which illustrate the capabilities of the software framework and document the functionality of the chip.