126 citations · 203 across the 6 of their papers we have counts for
6 papers
The SpiNNaker2 chip: a many-core platform for flexible and scalable brain-inspired computing
Stefan Scholze, Johannes Partzsch, Sebastian Höppner +27
In deep learning, efficiency gets more and more important to compensate for the ongoing growth in model sizes and applications. Neuromorphic hardware has long been advocated as an…
Hardware Implementation of an OPC UA Server for Industrial Field Devices
Heiner Bauer, Sebastian Höppner, Chris Iatrou +13
Industrial plants suffer from a high degree of complexity and incompatibility in their communication infrastructure, caused by a wild mix of proprietary technologies. This prevents…
The SpiNNaker 2 Processing Element Architecture for Hybrid Digital Neuromorphic Computing
Sebastian Höppner, Yexin Yan, Andreas Dixius +15
This paper introduces the processing element architecture of the second generation SpiNNaker chip, implemented in 22nm FDSOI. On circuit level, the chip features adaptive body bias…
Dynamic Power Management for Neuromorphic Many-Core Systems
Sebastian Hoeppner, Bernhard Vogginger, Yexin Yan +12
This work presents a dynamic power management architecture for neuromorphic many core systems such as SpiNNaker. A fast dynamic voltage and frequency scaling (DVFS) technique is pr…
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…