From the 1 of 4 linked papers with an AI index.
4 papers
A Low-Power Sparse Convolution Accelerator with Idle-First-Task-Assignment for Edge Vision
Jingyue Zhuge, Johannes Partzsch, Christian Mayr
The paper presents a low‑power ASIC accelerator that uses bitmap‑based sparse convolution and an idle‑first‑task‑assignment scheduler to efficiently run edge‑vision models like VGG…
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…
Efficient Deployment of Spiking Neural Networks on SpiNNaker2 for DVS Gesture Recognition Using Neuromorphic Intermediate Representation
Sirine Arfa, Bernhard Vogginger, Chen Liu +3
Spiking Neural Networks (SNNs) are highly energy-efficient during inference, making them particularly suitable for deployment on neuromorphic hardware. Their ability to process eve…