2 papers
cs.AR2025
Modeling and Optimizing Performance Bottlenecks for Neuromorphic Accelerators
Jason Yik, Walter Gallego Gomez, Andrew Cheng +8
Neuromorphic accelerators offer promising platforms for machine learning (ML) inference by leveraging event-driven, spatially-expanded architectures that naturally exploit unstruct…
cs.AR2024
A Fully-Configurable Open-Source Software-Defined Digital Quantized Spiking Neural Core Architecture
Shadi Matinizadeh, Noah Pacik-Nelson, Ioannis Polykretis +9
We introduce QUANTISENC, a fully configurable open-source software-defined digital quantized spiking neural core architecture to advance research in neuromorphic computing. QUANTIS…