138 citations · 285 across the 22 of their papers we have counts for
11 papers · 1 filter
Emulating insect brains for neuromorphic navigation
Korbinian Schreiber, Timo Wunderlich, Philipp Spilger +8
Bees display the remarkable ability to return home in a straight line after meandering excursions to their environment. Neurobiological imaging studies have revealed that this capa…
An accurate and flexible analog emulation of AdEx neuron dynamics in silicon
Sebastian Billaudelle, Johannes Weis, Philipp Dauer +1
Analog neuromorphic hardware promises fast brain emulation on the one hand and an efficient implementation of novel, brain-inspired computing paradigms on the other. Bridging this…
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…
The BrainScaleS-2 accelerated neuromorphic system with hybrid plasticity
Christian Pehle, Sebastian Billaudelle, Benjamin Cramer +7
Since the beginning of information processing by electronic components, the nervous system has served as a metaphor for the organization of computational primitives. Brain-inspired…
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…
hxtorch: PyTorch for BrainScaleS-2 -- Perceptrons on Analog Neuromorphic Hardware
Philipp Spilger, Eric Müller, Arne Emmel +10
We present software facilitating the usage of the BrainScaleS-2 analog neuromorphic hardware system as an inference accelerator for artificial neural networks. The accelerator hard…
Surrogate gradients for analog neuromorphic computing
Benjamin Cramer, Sebastian Billaudelle, Simeon Kanya +9
To rapidly process temporal information at a low metabolic cost, biological neurons integrate inputs as an analog sum but communicate with spikes, binary events in time. Analog neu…
Accelerated Analog Neuromorphic Computing
Johannes Schemmel, Sebastian Billaudelle, Phillip Dauer +1
This paper presents the concepts behind the BrainScales (BSS) accelerated analog neuromorphic computing architecture. It describes the second-generation BrainScales-2 (BSS-2) versi…
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…
Fast and energy-efficient neuromorphic deep learning with first-spike times
Julian Göltz, Laura Kriener, Andreas Baumbach +9
For a biological agent operating under environmental pressure, energy consumption and reaction times are of critical importance. Similarly, engineered systems are optimized for sho…
Demonstrating Advantages of Neuromorphic Computation: A Pilot Study
Timo Wunderlich, Akos F. Kungl, Eric Müller +14
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 com…