Using analog computers in today's largest computational challenges

TL;DR

This paper explores the potential of modern analog computers as energy-efficient, fast alternatives for large-scale scientific computing, especially in solving differential equations and fluid dynamics, through performance measurements and hybrid models.

Contribution

It demonstrates the feasibility and advantages of analog and hybrid computing models for scientific applications, supported by performance data and proposed models.

Findings

Analog computers show promising performance for differential equations.

Hybrid digital-analog models can enhance computational efficiency.

Analog computing offers energy-efficient solutions for large-scale problems.

Abstract

Analog computers can be revived as a feasible technology platform for low precision, energy efficient and fast computing. We justify this statement by measuring the performance of a modern analog computer and comparing it with that of traditional digital processors. General statements are made about the solution of ordinary and partial differential equations. Computational fluid dynamics are discussed as an example of large scale scientific computing applications. Several models are proposed which demonstrate the benefits of analog and digital-analog hybrid computing.