Title :
Modeling Spiking Neural Networks on SpiNNaker
Author :
Jin, Xin ; Luján, Mikel ; Plana, Luis A. ; Davies, Sergio ; Temple, Steve ; Furber, Steve B.
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;
Journal_Title :
Computing in Science & Engineering
DOI :
10.1109/MCSE.2010.112