126 citations · 246 across the 7 of their papers we have counts for
7 papers
A Scalable Approach to Modeling on Accelerated Neuromorphic Hardware
Eric Müller, Elias Arnold, Oliver Breitwieser +20
Neuromorphic systems open up opportunities to enlarge the explorative space for computational research. However, it is often challenging to unite efficiency and usability. This wor…
Inference with Artificial Neural Networks on Analog Neuromorphic Hardware
Johannes Weis, Philipp Spilger, Sebastian Billaudelle +11
The neuromorphic BrainScaleS-2 ASIC comprises mixed-signal neurons and synapse circuits as well as two versatile digital microprocessors. Primarily designed to emulate spiking neur…
The Operating System of the Neuromorphic BrainScaleS-1 System
Eric Müller, Sebastian Schmitt, Christian Mauch +19
BrainScaleS-1 is a wafer-scale mixed-signal accelerated neuromorphic system targeted for research in the fields of computational neuroscience and beyond-von-Neumann computing. The…
Versatile emulation of spiking neural networks on an accelerated neuromorphic substrate
Sebastian Billaudelle, Yannik Stradmann, Korbinian Schreiber +22
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 comp…
Accelerated physical emulation of Bayesian inference in spiking neural networks
Akos F. Kungl, Sebastian Schmitt, Johann Klähn +21
The massively parallel nature of biological information processing plays an important role for its superiority to human-engineered computing devices. In particular, it may hold the…
Neuromorphic Hardware In The Loop: Training a Deep Spiking Network on the BrainScaleS Wafer-Scale System
Sebastian Schmitt, Johann Klaehn, Guillaume Bellec +22
Emulating spiking neural networks on analog neuromorphic hardware offers several advantages over simulating them on conventional computers, particularly in terms of speed and energ…
Pattern representation and recognition with accelerated analog neuromorphic systems
Mihai A. Petrovici, Sebastian Schmitt, Johann Klähn +33
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 partic…