71 citations · 73 across the 5 of their papers we have counts for
5 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…
Event-based Neural Decoding for Neuroprosthetic Motor Control
Khaleelulla Khan Nazeer, Sirine Arfa, Matthias Jobst +2
A substantial number of patients experience diminished mobility due to disabilities, diseases, or accidents. Although modern prostheses, powered by deep neural networks, hold the p…
An End-to-End DNN Inference Framework for the SpiNNaker2 Neuromorphic MPSoC
Matthias Jobst, Tim Langer, Chen Liu +3
This work presents a multi-layer DNN scheduling framework as an extension of OctopuScheduler, providing an end-to-end flow from PyTorch models to inference on a single SpiNNaker2 c…
Neuromorphic Intermediate Representation: A Unified Instruction Set for Interoperable Brain-Inspired Computing
Jens E. Pedersen, Steven Abreu, Matthias Jobst +12
Spiking neural networks and neuromorphic hardware platforms that simulate neuronal dynamics are getting wide attention and are being applied to many relevant problems using Machine…
Deploying Machine Learning Models to Ahead-of-Time Runtime on Edge Using MicroTVM
Chen Liu, Matthias Jobst, Liyuan Guo +3
In the past few years, more and more AI applications have been applied to edge devices. However, models trained by data scientists with machine learning frameworks, such as PyTorch…