KIP-Veröffentlichungen

Jahr 2019
Autor(en) Sebastian Billaudelle*, Yannik Stradmann*, Korbinian Schreiber*, Benjamin Cramer*, Andreas Baumbach*, Dominik Dold*, Julian Göltz*, Akos F. Kungl*, Timo C. Wunderlich*, Andreas Hartel, Eric Müller, Oliver Breitwieser, Christian Mauch, Mitja Kleider, Andreas Grübl, David Stöckel, Christian Pehle, Arthur Heimbrecht, Philipp Spilger, Gerd Kiene, Vitali Karasenko, Walter Senn, Mihai A. Petrovici^, Johannes Schemmel^, Karlheinz Meier^
Titel Versatile emulation of spiking neural networks on an accelerated neuromorphic substrate
KIP-Nummer HD-KIP 19-119
KIP-Gruppe(n) F9
Dokumentart Paper
Keywords (angezeigt) neuromorphic engineering, spiking neurons, physical emulation, sampling, inference, plasticity, biological modelling
Quelle 2020 IEEE International Symposium on Circuits and Systems (ISCAS) (pp. 1-5). IEEE
doi https://doi.org/10.1109/ISCAS45731.2020.9180741
Abstract (de)

Abstract (en)

We present first experimental results on the novel BrainScaleS-2 neuromorphic architecture based on an analog neuro-synaptic core and augmented by embedded microprocessors for complex plasticity and experiment control. The high acceleration factor of 1000 compared to biological dynamics enables the execution of computationally expensive tasks, by allowing the fast emulation of long-duration experiments or rapid iteration over many consecutive trials. The flexibility of our architecture is demonstrated in a suite of five distinct experiments, which emphasize different aspects of the BrainScaleS-2 system.

bibtex
@inproceedings{billaudelle2020versatile,
  author   = {Billaudelle, Sebastian and Stradmann, Yannik and Schreiber, Korbinian and Cramer, Benjamin and Baumbach, Andreas and Dold, Dominik and G{\"o}ltz, Julian and Kungl, Akos F and Wunderlich, Timo C and Hartel, Andreas and others},
  title    = {Versatile emulation of spiking neural networks on an accelerated neuromorphic substrate},
  booktitle = {2020 IEEE International Symposium on Circuits and Systems (ISCAS)},
  year     = {2020},
  volume   = {},
  pages    = {1--5},
  organization = {IEEE}
}
Datei pdf
URL ArXiv
URL IEEE
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