An optoelectronic heterostructure for neuromorphic computing: CdS/V₃O₅

Superconducting optoelectronic circuits for neuromorphic computing

We propose a hybrid semiconductor-superconductor hardware platform for the implementation of neural networks and large-scale neuromorphic computing. The platform combines semiconducting few-photon light-emitting diodes with superconducting-nanowire single-photon detectors to behave as spiking neurons. These processing units are connected via a network of optical waveguides, and variable weights...

Stochastic induced dynamics in neuromorphic optoelectronic oscillators

We investigate the dynamics of optoelectronic oscillator (OEO) systems based on resonant tunneling diode photodetector (RTD-PD) and laser diode hybrid integrated circuits. We demonstrate that RTD-based OEOs can be noise-activated in either monostable or bistable operating conditions, providing a rich variety of signal outputs—spiking, square pulses, bursting—and behaviours—stochastic and cohere...

Tutorial: Neuromorphic computing

ReRAM-Based Neuromorphic Computing

Artificial neural networks are currently being used as a promising means to solve problems in machine learning and computer science [1–3]. These networks are loosely inspired by massively parallel biological neural systems, but they are often implemented on mostly sequential hardware computing platforms, ignoring key features of real neural processing systems, such as their ability to carry out...

Automotive Computing, Neuromorphic Computing, and Beyond

Welcome to 2018 and IEEE Micro’s 38th year. I’m delighted about last year’s issues. In addition to the traditional special issues on Hot Chips and Top Picks, we had special issues on cognitive architectures, architectures for the post-Moore era, Cool Chips and Hot Interconnects, and ultra-low-power processors. I deeply appreciate the efforts of everyone who reviewed the many articles submitted ...