Fan-out and Fan-in properties of superconducting neuromorphic circuits

TL;DR

This paper investigates the fan-in and fan-out capabilities of superconducting neuromorphic circuits using Josephson junctions, demonstrating potential for high connectivity levels comparable to the human brain, with implications for energy-efficient neuromorphic hardware.

Contribution

The study provides the first detailed analysis and simulation of fan-in and fan-out limits in superconductive neuromorphic circuits, highlighting their potential for scalable brain-inspired computing.

Findings

Fan-out can reach levels of 1-to-10,000 based on junction count and circuit size.

Fan-in is limited to a few hundred-to-1 with current technology.

Superconductive circuits can achieve high connectivity similar to biological neural networks.

Abstract

Neuromorphic computing has the potential to further the success of software-based artificial neural networks (ANNs) by designing hardware from a different perspective. Current research in neuromorphic hardware targets dramatic improvements to ANN performance by increasing energy efficiency, speed of operation, and even seeks to extend the utility of ANNs by natively adding functionality such as spiking operation. One promising neuromorphic hardware platform is based on superconductive electronics, which has the potential to incorporate all of these advantages at the device level in addition to offering the potential of near lossless communications both within the neuromorphic circuits as well as between disparate superconductive chips. Here we explore one of the fundamental brain-inspired architecture components, the fan-in and fan-out as realized in superconductive circuits based on Josephson junctions. From our calculations and WRSPICE simulations we find that the fan-out should be limited only by junction count and circuit size limitations, and we demonstrate results in simulation at a level of 1-to-10,000, similar to that of the human brain. We find that fan-in has more limitations, but a fan-in level on the order of a few 100-to-1 should be achievable based on current technology. We discuss our findings and the critical parameters that set the limits on fan-in and fan-out in the context of superconductive neuromorphic circuits.