Special Session: Neuromorphic hardware design and reliability from traditional CMOS to emerging technologies

TL;DR

This paper reviews recent advances in neuromorphic hardware, comparing traditional CMOS approaches with emerging technologies like integrated photonics, and discusses reliability challenges such as device variability and aging.

Contribution

It provides a comprehensive overview of hardware design and reliability issues in neuromorphic computing, highlighting emerging approaches and mitigation techniques.

Findings

Traditional CMOS approaches face scalability and power challenges.

Emerging integrated photonics offer promising alternatives.

Device variability and aging significantly impact reliability.

Abstract

The field of neuromorphic computing has been rapidly evolving in recent years, with an increasing focus on hardware design and reliability. This special session paper provides an overview of the recent developments in neuromorphic computing, focusing on hardware design and reliability. We first review the traditional CMOS-based approaches to neuromorphic hardware design and identify the challenges related to scalability, latency, and power consumption. We then investigate alternative approaches based on emerging technologies, specifically integrated photonics approaches within the NEUROPULS project. Finally, we examine the impact of device variability and aging on the reliability of neuromorphic hardware and present techniques for mitigating these effects. This review is intended to serve as a valuable resource for researchers and practitioners in neuromorphic computing.