A location-independent direct link neuromorphic interface

Alexander D. Rast, Johannes Partzsch, Christian Mayr, Johannes Schemmel, Stefan Hartmann, Luis A. Plana, Steve Temple, David R. Lester, Rene Schuffny, Steve Furber
2013 The 2013 International Joint Conference on Neural Networks (IJCNN)  
With neuromorphic hardware rapidly moving towards large-scale, possibly immovable systems capable of implementing brain-scale neural models in hardware, there is an emerging need to be able to integrate multi-system combinations of sensors and cortical processors over distributed, multisite configurations. If there were a standard, direct interface allowing large systems to communicate using native signalling, it would be possible to use heterogeneous resources efficiently according to their
more » ... k suitability. We propose a UDP-based AER spiking interface that permits direct bidirectional spike communications over standard networks, and demonstrate a practical implementation with two large-scale neuromorphic systems, BrainScaleS and SpiNNaker. Internally, the interfaces at either end appear as interceptors which decode and encode spikes in a standardised AER address format onto UDP frames. The system is able to run a spiking neural network distributed over the two systems, in both a side-by-side setup with a direct cable link and over the Internet between 2 widely spaced sites. Such a model not only realises a solution for connecting remote sensors or processors to a large, central neuromorphic simulation platform, but also opens possibilities for interesting automated remote neural control, such as parameter tuning, for large, complex neural systems, and suggests methods to overcome differences in timescale and simulation model between different platforms. With its entirely standard protocol and physical layer, the interface makes large neuromorphic systems a distributed, accessible resource available to all.
doi:10.1109/ijcnn.2013.6706887 dblp:conf/ijcnn/RastPMSHPTLSF13 fatcat:b2xtlac3wbbx5okaph4erl37ai