activity
20202026
most citedLow-Power Low-Latency Keyword Spotting and Adaptive Control with a SpiNNaker 2 Prototype and Comparison with Loihi

52 citations · 126 across the 7 of their papers we have counts for

collaborators

7 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…

cs.IR2026

Do We Need Bigger Models for Science? Task-Aware Retrieval with Small Language Models

Florian Kelber, Matthias Jobst, Yuni Susanti +1

Scientific knowledge discovery increasingly relies on large language models, yet many existing scholarly assistants depend on proprietary systems with tens or hundreds of billions…

cs.DC2024

Fast Switching Serial and Parallel Paradigms of SNN Inference on Multi-core Heterogeneous Neuromorphic Platform SpiNNaker2

Jiaxin Huang, Bernhard Vogginger, Florian Kelber +3

With serial and parallel processors introduced into Spiking Neural Networks (SNNs) execution, more and more researchers are dedicated to improving the performance of the computing…

cs.ET2024★ 18 cited

SpiNNaker2: A Large-Scale Neuromorphic System for Event-Based and Asynchronous Machine Learning

Hector A. Gonzalez, Jiaxin Huang, Florian Kelber +11

The joint progress of artificial neural networks (ANNs) and domain specific hardware accelerators such as GPUs and TPUs took over many domains of machine learning research. This de…

cs.AR2021★ 22 cited

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…

cs.AR2021★ 34 cited

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…

cs.NE2020★ 52 cited

Low-Power Low-Latency Keyword Spotting and Adaptive Control with a SpiNNaker 2 Prototype and Comparison with Loihi

Yexin Yan, Terrence C. Stewart, Xuan Choo +7

We implemented two neural network based benchmark tasks on a prototype chip of the second-generation SpiNNaker (SpiNNaker 2) neuromorphic system: keyword spotting and adaptive robo…