We are closely collaborating with SP9 (Neuromorphic hardware) to support big networks in real time. On the 20th and 21st of March 2017, we participated in the SP9 Quaterly in-person meeting to present the Neurorobotics Platform and our integration of SpiNNaker.
During the meeting, we identified MUSIC as a a single interface between our platform and both supercomputers from SP7 as well as SpiNNaker. We also pointed out the features we were missing in MUSIC to keep the Neurorobotics platform interactive, most importantly dynamical ports and reset.
We also presented some complex learning rules we are working on to help SP9 identify user requirements for SpiNNaker 2 design. We were surprised to learn that one of the most complicated learning rule we are working on – SPORE derived by David Kappel in Prof. Maass group – is also used as a benchmark for SpiNNaker 2 by Prof. Mayr. This reward-based learning rule can be used to train arbitrary recurrent network of spiking neurons. Confident that it will play an important role in SGA2, we sent our master student Michael Hoff from FZI, Karlsruhe to TU Graz to use this rule in a robotic setup.