Circuits that Solve Optimization Problems by Exploiting Physics Inequalities

Optimization is vital to Engineering, Artificial Intelligence, and to many areas of Science. Mathematically, we usually employ steepest-descent, or other digital algorithms. For example, Deep Learning is an optimization problem, Fig. 12.1.1. Everyday applications of optimization range from aerodynamic design of vehicles by fluid mechanics and physical stress optimization of bridges in civil engineering; to scheduling of airline crews and routing of delivery trucks in operations research. Furthermore, optimization is also indispensable in machine learning, reinforcement learning, computer vision, and speech processing. Given the preponderance of massive datasets and computations today, there has been a surge of activity in the design of hardware accelerators for neural network training and inference.