17 citations · 26 across the 9 of their papers we have counts for
9 papers
Short-reach Optical Communications: A Real-world Task for Neuromorphic Hardware
Elias Arnold, Eike-Manuel Edelmann, Alexander von Bank +3
Spiking neural networks (SNNs) emulated on dedicated neuromorphic accelerators promise to offer energy-efficient signal processing. However, the neuromorphic advantage over traditi…
jaxsnn: Event-driven Gradient Estimation for Analog Neuromorphic Hardware
Eric Müller, Moritz Althaus, Elias Arnold +3
Traditional neuromorphic hardware architectures rely on event-driven computation, where the asynchronous transmission of events, such as spikes, triggers local computations within…
Scalable Network Emulation on Analog Neuromorphic Hardware
Elias Arnold, Philipp Spilger, Jan V. Straub +4
We present a novel software feature for the BrainScaleS-2 accelerated neuromorphic platform that facilitates the partitioned emulation of large-scale spiking neural networks. This…
Spiking Neural Network Nonlinear Demapping on Neuromorphic Hardware for IM/DD Optical Communication
Elias Arnold, Georg Böcherer, Florian Strasser +7
Neuromorphic computing implementing spiking neural networks (SNN) is a promising technology for reducing the footprint of optical transceivers, as required by the fast-paced growth…
Event-based Backpropagation for Analog Neuromorphic Hardware
Christian Pehle, Luca Blessing, Elias Arnold +2
Neuromorphic computing aims to incorporate lessons from studying biological nervous systems in the design of computer architectures. While existing approaches have successfully imp…
hxtorch.snn: Machine-learning-inspired Spiking Neural Network Modeling on BrainScaleS-2
Philipp Spilger, Elias Arnold, Luca Blessing +4
Neuromorphic systems require user-friendly software to support the design and optimization of experiments. In this work, we address this need by presenting our development of a mac…
Spiking Neural Network Equalization on Neuromorphic Hardware for IM/DD Optical Communication
Elias Arnold, Georg Böcherer, Eric Müller +4
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. The BER 2e-…
Spiking Neural Network Equalization for IM/DD Optical Communication
Elias Arnold, Georg Böcherer, Eric Müller +4
A spiking neural network (SNN) equalizer model suitable for electronic neuromorphic hardware is designed for an IM/DD link. The SNN achieves the same bit-error-rate as an artificia…
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…