Search Results for author: Eric Müller

Found 18 papers, 0 papers with code

Spiking Neural Network Equalization on Neuromorphic Hardware for IM/DD Optical Communication

no code implementations1 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.

Spiking Neural Network Equalization for IM/DD Optical Communication

no code implementations9 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.

Demonstrating BrainScaleS-2 Inter-Chip Pulse-Communication using EXTOLL

no code implementations24 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.

The BrainScaleS-2 accelerated neuromorphic system with hybrid plasticity

no code implementations26 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.

BrainScaleS Large Scale Spike Communication using Extoll

no code implementations30 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.

Demonstrating Analog Inference on the BrainScaleS-2 Mobile System

no code implementations29 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.

Total Energy

Extending BrainScaleS OS for BrainScaleS-2

no code implementations30 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.

The Operating System of the Neuromorphic BrainScaleS-1 System

no code implementations30 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.

Brain-Inspired Hardware for Artificial Intelligence: Accelerated Learning in a Physical-Model Spiking Neural Network

no code implementations24 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.

reinforcement Learning

Demonstrating Advantages of Neuromorphic Computation: A Pilot Study

no code implementations8 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.

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