8 papers
Spiking Neural Networks for Energy-Efficient Object Detection in Forward-Looking Sonar Imagery
Gwenevere Frank, Gert Cauwenberghs
Autonomous underwater vehicles (AUVs) are increasingly important tools in industries ranging from research, to energy, to defense. AUVs are power-constrained platforms operating in…
HiAER-Spike Software-Hardware Reconfigurable Platform for Event-Driven Neuromorphic Computing at Scale
Gwenevere Frank, Gopabandhu Hota, Keli Wang +12
In this work, we present HiAER-Spike, a modular, reconfigurable, event-driven neuromorphic computing platform designed to execute large spiking neural networks with up to 160 milli…
NeuroAI and Beyond
Jean-Marc Fellous, Gert Cauwenberghs, Cornelia Fermüller +2
Neuroscience and Artificial Intelligence (AI) have made significant progress in the past few years but have only been loosely inter-connected. Based on a workshop held in August 20…
Clo-HDnn: A 4.66 TFLOPS/W and 3.78 TOPS/W Continual On-Device Learning Accelerator with Energy-efficient Hyperdimensional Computing via Progressive Search
Chang Eun Song, Weihong Xu, Keming Fan +10
Clo-HDnn is an on-device learning (ODL) accelerator designed for emerging continual learning (CL) tasks. Clo-HDnn integrates hyperdimensional computing (HDC) along with low-cost Kr…
Quantifying Data Requirements for EEG Independent Component Analysis Using AMICA
Gwenevere Frank, Seyed Yahya Shirazi, Jason Palmer +3
Independent Component Analysis (ICA) is an important step in EEG processing for a wide-ranging set of applications. However, ICA requires well-designed studies and data collection…
HiAER-Spike: Hardware-Software Co-Design for Large-Scale Reconfigurable Event-Driven Neuromorphic Computing
Gwenevere Frank, Gopabandhu Hota, Keli Wang +8
In this work, we present HiAER-Spike, a modular, reconfigurable, event-driven neuromorphic computing platform designed to execute large spiking neural networks with up to 160 milli…
An Exploration of Optimal Parameters for Efficient Blind Source Separation of EEG Recordings Using AMICA
Gwenevere Frank, Seyed Yahya Shirazi, Jason Palmer +3
EEG continues to find a multitude of uses in both neuroscience research and medical practice, and independent component analysis (ICA) continues to be an important tool for analyzi…
Multi-level, Forming Free, Bulk Switching Trilayer RRAM for Neuromorphic Computing at the Edge
Jaeseoung Park, Ashwani Kumar, Yucheng Zhou +9
Resistive memory-based reconfigurable systems constructed by CMOS-RRAM integration hold great promise for low energy and high throughput neuromorphic computing. However, most RRAM…