34 citations · 66 across the 7 of their papers we have counts for
7 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…
68-Channel Highly-Integrated Neural Signal Processing PSoC with On-Chip Feature Extraction, Compression, and Hardware Accelerators for Neuroprosthetics in 22nm FDSOI
Liyuan Guo, Annika Weiße, Seyed Mohammad Ali Zeinolabedin +13
Multi-channel electrophysiology systems for recording of neuronal activity face significant data throughput limitations, hampering real-time, data-informed experiments. These limit…
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…
Switched-Capacitor Realization of Presynaptic Short-Term-Plasticity and Stop-Learning Synapses in 28 nm CMOS
Marko Noack, Johannes Partzsch, Christian Mayr +5
Synaptic dynamics, such as long- and short-term plasticity, play an important role in the complexity and biological realism achievable when running neural networks on a neuromorphi…
A Biological-Realtime Neuromorphic System in 28 nm CMOS using Low-Leakage Switched Capacitor Circuits
Christian Mayr, Johannes Partzsch, Marko Noack +5
A switched-capacitor (SC) neuromorphic system for closed-loop neural coupling in 28 nm CMOS is presented, occupying 600 um by 600 um. It offers 128 input channels (i.e. presynaptic…