1.1k citations · 4.6k across the 68 of their papers we have counts for
6 papers · 1 filter
SPAIC: A sub-W/Channel, 16-Channel General-Purpose Event-Based Analog Front-End with Dual-Mode Encoders
Shyam Narayanan, Matteo Cartiglia, Arianna Rubino +3
Low-power event-based analog front-ends (AFE) are a crucial component required to build efficient end-to-end neuromorphic processing systems for edge computing. Although several ne…
Yak: An Asynchronous Bundled Data Pipeline Description Language
Carsten Nielsen, Zhe Su, Giacomo Indiveri
The design of asynchronous circuits typically requires a judicious definition of signals and modules, combined with a proper specification of their timing constraints, which can be…
Core interface optimization for multi-core neuromorphic processors
Zhe Su, Hyunjung Hwang, Tristan Torchet +1
Hardware implementations of Spiking Neural Networks (SNNs) represent a promising approach to edge-computing for applications that require low-power and low-latency, and which canno…
Hardware Implementation of Deep Network Accelerators Towards Healthcare and Biomedical Applications
Mostafa Rahimi Azghadi, Corey Lammie, Jason K. Eshraghian +4
The advent of dedicated Deep Learning (DL) accelerators and neuromorphic processors has brought on new opportunities for applying both Deep and Spiking Neural Network (SNN) algorit…
A bi-directional Address-Event transceiver block for low-latency inter-chip communication in neuromorphic systems
Ning Qiao, Giacomo Indiveri
Neuromorphic systems typically use the Address-Event Representation (AER) to transmit signals among nodes, cores, and chips. Communication of Address-Events (AEs) between neuromorp…
A scalable multi-core architecture with heterogeneous memory structures for Dynamic Neuromorphic Asynchronous Processors (DYNAPs)
Saber Moradi, Ning Qiao, Fabio Stefanini +1
Neuromorphic computing systems comprise networks of neurons that use asynchronous events for both computation and communication. This type of representation offers several advantag…