DocumentCode
1312154
Title
Modeling Spiking Neural Networks on SpiNNaker
Author
Jin, Xin ; Luján, Mikel ; Plana, Luis A. ; Davies, Sergio ; Temple, Steve ; Furber, Steve B.
Volume
12
Issue
5
fYear
2010
Firstpage
91
Lastpage
97
Abstract
SpiNNaker is a massively parallel architecture with more than a million processing cores that can model up to 1 billion spiking neurons in biological real time. Here, we offer an overview of our research project and describe the first experiments with these test chips running spiking neurons based on Eugene Izhikevich´s model. Note that we´re not targeting artificial neural networks (such as perceptrons or multilayer networks) that were inspired by, but don´t model, biologically plausible neural systems.
Keywords
neural chips; parallel architectures; Eugene Izhikevich model; SpiNNaker; biological plausible neural systems; parallel architecture; spiking neural network modelling; test chips; Biological system modeling; Biomembranes; Computational modeling; Mathematical model; Neurons; Routing; Massively parallel computing; biological real-time computing; globally asynchronous locally synchronous design; multicore system-on-chip; neural modeling; spiking neural net simulation;
fLanguage
English
Journal_Title
Computing in Science & Engineering
Publisher
ieee
ISSN
1521-9615
Type
jour
DOI
10.1109/MCSE.2010.112
Filename
5562477
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