no code implementations • 17 Mar 2017 • Mihai A. Petrovici, Sebastian Schmitt, Johann Klähn, David Stöckel, Anna Schroeder, Guillaume Bellec, Johannes Bill, Oliver Breitwieser, Ilja Bytschok, Andreas Grübl, Maurice Güttler, Andreas Hartel, Stephan Hartmann, Dan Husmann, Kai Husmann, Sebastian Jeltsch, Vitali Karasenko, Mitja Kleider, Christoph Koke, Alexander Kononov, Christian Mauch, Eric Müller, Paul Müller, Johannes Partzsch, Thomas Pfeil, Stefan Schiefer, Stefan Scholze, Anand Subramoney, Vasilis Thanasoulis, Bernhard Vogginger, Robert Legenstein, Wolfgang Maass, René Schüffny, Christian Mayr, Johannes Schemmel, Karlheinz Meier
Despite being originally inspired by the central nervous system, artificial neural networks have diverged from their biological archetypes as they have been remodeled to fit particular tasks.
no code implementations • 6 Jul 2018 • Akos F. Kungl, Sebastian Schmitt, Johann Klähn, Paul Müller, Andreas Baumbach, Dominik Dold, Alexander Kugele, Nico Gürtler, Luziwei Leng, Eric Müller, Christoph Koke, Mitja Kleider, Christian Mauch, Oliver Breitwieser, Maurice Güttler, Dan Husmann, Kai Husmann, Joscha Ilmberger, Andreas Hartel, Vitali Karasenko, Andreas Grübl, Johannes Schemmel, Karlheinz Meier, Mihai A. Petrovici
The massively parallel nature of biological information processing plays an important role for its superiority to human-engineered computing devices.
no code implementations • 8 Nov 2018 • Timo Wunderlich, Akos F. Kungl, Eric Müller, Andreas Hartel, Yannik Stradmann, Syed Ahmed Aamir, Andreas Grübl, Arthur Heimbrecht, Korbinian Schreiber, David Stöckel, Christian Pehle, Sebastian Billaudelle, Gerd Kiene, Christian Mauch, Johannes Schemmel, Karlheinz Meier, Mihai A. Petrovici
Neuromorphic devices represent an attempt to mimic aspects of the brain's architecture and dynamics with the aim of replicating its hallmark functional capabilities in terms of computational power, robust learning and energy efficiency.
no code implementations • 24 Sep 2019 • Timo C. Wunderlich, Akos F. Kungl, Eric Müller, Johannes Schemmel, Mihai Petrovici
Future developments in artificial intelligence will profit from the existence of novel, non-traditional substrates for brain-inspired computing.
no code implementations • 30 Dec 2019 • 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
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.
no code implementations • 30 Mar 2020 • Eric Müller, Christian Mauch, Philipp Spilger, Oliver Julien Breitwieser, Johann Klähn, David Stöckel, Timo Wunderlich, Johannes Schemmel
BrainScaleS-2 is a mixed-signal accelerated neuromorphic system targeted for research in the fields of computational neuroscience and beyond-von-Neumann computing.
no code implementations • 30 Mar 2020 • Eric Müller, Sebastian Schmitt, Christian Mauch, Sebastian Billaudelle, Andreas Grübl, Maurice Güttler, Dan Husmann, Joscha Ilmberger, Sebastian Jeltsch, Jakob Kaiser, Johann Klähn, Mitja Kleider, Christoph Koke, José Montes, Paul Müller, Johannes Partzsch, Felix Passenberg, Hartmut Schmidt, Bernhard Vogginger, Jonas Weidner, Christian Mayr, Johannes Schemmel
We present operation and development methodologies implemented for the BrainScaleS-1 neuromorphic architecture and walk through the individual components of BrainScaleS OS constituting the software stack for BrainScaleS-1 platform operation.
no code implementations • 23 Jun 2020 • Philipp Spilger, Eric Müller, Arne Emmel, Aron Leibfried, Christian Mauch, Christian Pehle, Johannes Weis, Oliver Breitwieser, Sebastian Billaudelle, Sebastian Schmitt, Timo C. Wunderlich, Yannik Stradmann, Johannes Schemmel
We present software facilitating the usage of the BrainScaleS-2 analog neuromorphic hardware system as an inference accelerator for artificial neural networks.
no code implementations • 23 Jun 2020 • Johannes Weis, Philipp Spilger, Sebastian Billaudelle, Yannik Stradmann, Arne Emmel, Eric Müller, Oliver Breitwieser, Andreas Grübl, Joscha Ilmberger, Vitali Karasenko, Mitja Kleider, Christian Mauch, Korbinian Schreiber, Johannes Schemmel
The neuromorphic BrainScaleS-2 ASIC comprises mixed-signal neurons and synapse circuits as well as two versatile digital microprocessors.
no code implementations • 29 Mar 2021 • Yannik Stradmann, Sebastian Billaudelle, Oliver Breitwieser, Falk Leonard Ebert, Arne Emmel, Dan Husmann, Joscha Ilmberger, Eric Müller, Philipp Spilger, Johannes Weis, Johannes Schemmel
We present the BrainScaleS-2 mobile system as a compact analog inference engine based on the BrainScaleS-2 ASIC and demonstrate its capabilities at classifying a medical electrocardiogram dataset.
no code implementations • 30 Nov 2021 • Tobias Thommes, Niels Buwen, Andreas Grübl, Eric Müller, Ulrich Brüning, Johannes Schemmel
The BrainScaleS Neuromorphic Computing System is currently connected to a compute cluster via Gigabit-Ethernet network technology.
no code implementations • 26 Jan 2022 • Christian Pehle, Sebastian Billaudelle, Benjamin Cramer, Jakob Kaiser, Korbinian Schreiber, Yannik Stradmann, Johannes Weis, Aron Leibfried, Eric Müller, Johannes Schemmel
Since the beginning of information processing by electronic components, the nervous system has served as a metaphor for the organization of computational primitives.
no code implementations • 24 Feb 2022 • Tobias Thommes, Sven Bordukat, Andreas Grübl, Vitali Karasenko, Eric Müller, Johannes Schemmel
The BrainScaleS-2 (BSS-2) Neuromorphic Computing System currently consists of multiple single-chip setups, which are connected to a compute cluster via Gigabit-Ethernet network technology.
no code implementations • 21 Mar 2022 • Eric Müller, Elias Arnold, Oliver Breitwieser, Milena Czierlinski, Arne Emmel, Jakob Kaiser, Christian Mauch, Sebastian Schmitt, Philipp Spilger, Raphael Stock, Yannik Stradmann, Johannes Weis, Andreas Baumbach, Sebastian Billaudelle, Benjamin Cramer, Falk Ebert, Julian Göltz, Joscha Ilmberger, Vitali Karasenko, Mitja Kleider, Aron Leibfried, Christian Pehle, Johannes Schemmel
Neuromorphic systems open up opportunities to enlarge the explorative space for computational research.
no code implementations • 9 May 2022 • Elias Arnold, Georg Böcherer, Eric Müller, Philipp Spilger, Johannes Schemmel, Stefano Calabrò, Maxim Kuschnerov
A spiking neural network (SNN) equalizer model suitable for electronic neuromorphic hardware is designed for an IM/DD link.
no code implementations • 1 Jun 2022 • Elias Arnold, Georg Böcherer, Eric Müller, Philipp Spilger, Johannes Schemmel, Stefano Calabrò, Maxim Kuschnerov
A spiking neural network (SNN) non-linear equalizer model is implemented on the mixed-signal neuromorphic hardware system BrainScaleS-2 and evaluated for an IM/DD link.
no code implementations • 17 Aug 2022 • Benjamin Cramer, Markus Kreft, Sebastian Billaudelle, Vitali Karasenko, Aron Leibfried, Eric Müller, Philipp Spilger, Johannes Weis, Johannes Schemmel, Miguel A. Muñoz, Viola Priesemann, Johannes Zierenberg
The extent of memory about past inputs is commonly quantified by the autocorrelation time of collective dynamics.
no code implementations • 23 Dec 2022 • Philipp Spilger, Elias Arnold, Luca Blessing, Christian Mauch, Christian Pehle, Eric Müller, Johannes Schemmel
Neuromorphic systems require user-friendly software to support the design and optimization of experiments.
no code implementations • 13 Feb 2023 • Christian Pehle, Luca Blessing, Elias Arnold, Eric Müller, Johannes Schemmel
Building on this work has the potential to enable scalable gradient estimation in large-scale neuromorphic hardware as a continuous measurement of the system state would be prohibitive and energy-inefficient in such instances.
no code implementations • 28 Feb 2023 • Elias Arnold, Georg Böcherer, Florian Strasser, Eric Müller, Philipp Spilger, Sebastian Billaudelle, Johannes Weis, Johannes Schemmel, Stefano Calabrò, Maxim Kuschnerov
The SNN demapper is implemented in software and on the analog neuromorphic hardware system BrainScaleS-2 (BSS-2).
no code implementations • 22 Mar 2023 • Hartmut Schmidt, José Montes, Andreas Grübl, Maurice Güttler, Dan Husmann, Joscha Ilmberger, Jakob Kaiser, Christian Mauch, Eric Müller, Lars Sterzenbach, Johannes Schemmel, Sebastian Schmitt
The first-generation of BrainScaleS, also referred to as BrainScaleS-1, is a neuromorphic system for emulating large-scale networks of spiking neurons.
1 code implementation • 28 Mar 2023 • Jakob Kaiser, Raphael Stock, Eric Müller, Johannes Schemmel, Sebastian Schmitt
The BrainScaleS-2 (BSS-2) system implements physical models of neurons as well as synapses and aims for an energy-efficient and fast emulation of biological neurons.
no code implementations • 29 Aug 2023 • Julian Göltz, Sebastian Billaudelle, Laura Kriener, Luca Blessing, Christian Pehle, Eric Müller, Johannes Schemmel, Mihai A. Petrovici
Recent efforts have fostered significant progress towards deep learning in spiking networks, both theoretical and in silico.
no code implementations • 31 Dec 2023 • Korbinian Schreiber, Timo Wunderlich, Philipp Spilger, Sebastian Billaudelle, Benjamin Cramer, Yannik Stradmann, Christian Pehle, Eric Müller, Mihai A. Petrovici, Johannes Schemmel, Karlheinz Meier
Bees display the remarkable ability to return home in a straight line after meandering excursions to their environment.
no code implementations • 30 Jan 2024 • Eric Müller, Moritz Althaus, Elias Arnold, Philipp Spilger, Christian Pehle, Johannes Schemmel
Traditional neuromorphic hardware architectures rely on event-driven computation, where the asynchronous transmission of events, such as spikes, triggers local computations within synapses and neurons.
no code implementations • 30 Jan 2024 • Elias Arnold, Philipp Spilger, Jan V. Straub, Eric Müller, Dominik Dold, Gabriele Meoni, Johannes Schemmel
We demonstrate the training of two deep spiking neural network models, using the MNIST and EuroSAT datasets, that exceed the physical size constraints of a single-chip BrainScaleS-2 system.