NDLI: A wafer-scale neuromorphic hardware system for large-scale neural modeling

Content Provider	IEEE Xplore Digital Library
Author	Schemmel, J. Brüderle, D. Grübl, A. Hock, M. Meier, K. Millner, S.
Copyright Year	2010
Description	Author affiliation: Kirchhoff Institute for Physics, University of Heidelberg Im Neuenheimer Feld 227, 69120 Heidelberg, Germany (Schemmel, J.; Brüderle, D.; Grübl, A.; Hock, M.; Meier, K.; Millner, S.)
Abstract	Modeling neural tissue is an important tool to investigate biological neural networks. Until recently, most of this modeling has been done using numerical methods. In the European research project "FACETS" this computational approach is complemented by different kinds of neuromorphic systems. A special emphasis lies in the usability of these systems for neuroscience. To accomplish this goal an integrated software/hardware framework has been developed which is centered around a unified neural system description language, called PyNN, that allows the scientist to describe a model and execute it in a transparent fashion on either a neuromorphic hardware system or a numerical simulator. A very large analog neuromorphic hardware system developed within FACETS is able to use complex neural models as well as realistic network topologies, i.e. it can realize more than 10000 synapses per neuron, to allow the direct execution of models which previously could have been simulated numerically only.
Starting Page	1947
Ending Page	1950
File Size	1552250
Page Count	4
File Format	PDF
ISBN	9781424453085
DOI	10.1109/ISCAS.2010.5536970
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-05-30
Publisher Place	France
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Neuromorphics Hardware Large-scale systems Semiconductor device modeling Biological system modeling Numerical simulation Biological tissues Biological neural networks Biology computing Usability
Content Type	Text
Resource Type	Article

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