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Distributed configuration of massively-parallel simulation on SpiNNaker neuromorphic hardware

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3 Author(s)
Thomas Sharp ; School of Computer Science, The University of Manchester, M13 9PL, UK ; Cameron Patterson ; Steve Furber

SpiNNaker is a massively-parallel neuromorphic computing architecture designed to model very large, biologically plausible spiking neural networks in real-time. A SpiNNaker machine consists of up to 216 homogeneous eighteen-core multiprocessor chips, each with an on-board router which forms links with neighbouring chips for packet-switched interprocessor communications. The architecture is designed for dynamic reconfiguration and optimised for transmission of neural activity data, which presents a challenge for machine configuration, program loading and simulation monitoring given a lack of globally-shared memory resources, intrinsic addressing mode or sideband configuration channel. We propose distributed software mechanisms to address these problems and present experiments which demonstrate the necessity of this approach in contrast to centralised mechanisms.

Published in:

Neural Networks (IJCNN), The 2011 International Joint Conference on

Date of Conference:

July 31 2011-Aug. 5 2011