9 papers · 1 filter
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…
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…
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…
Extending BrainScaleS OS for BrainScaleS-2
Eric Müller, Christian Mauch, Philipp Spilger +5
BrainScaleS-2 is a mixed-signal accelerated neuromorphic system targeted for research in the fields of computational neuroscience and beyond-von-Neumann computing. To augment its f…
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…