126 citations · 378 across the 19 of their papers we have counts for
5 papers · 1 filter
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…
Characterization of Off-wafer Pulse Communication in BrainScaleS Neuromorphic System
Bernhard Vogginger, Vasilis Thanasoulis, Johannes Partzsch +1
Neuromorphic VLSI systems take inspiration from biology to enable efficient emulation of large-scale spiking neural networks and to explore new computational paradigms. To establis…
Mean Field Approach for Configuring Population Dynamics on a Biohybrid Neuromorphic System
Johannes Partzsch, Christian Mayr, Massimiliano Giulioni +6
Real-time coupling of cell cultures to neuromorphic circuits necessitates a neuromorphic network that replicates biological behaviour both on a per-neuron and on a population basis…
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…