3 papers
cs.ET2026
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…
eess.SP2024
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…
cs.AR2023
A RISC-V MCU with adaptive reverse body bias and ultra-low-power retention mode in 22 nm FD-SOI
Heiner Bauer, Marco Stolba, Stefan Scholze +7
We present a low-power, energy efficient 32-bit RISC-V microprocessor unit (MCU) in 22 nm FD-SOI. It achieves ultra-low leakage,even at high temperatures, by using an adaptive reve…