BEOL Ferroelectric Compute-in-Memory Ising Machine for Simulated Bifurcation

This article likely discusses a novel hardware implementation for solving Ising problems, a type of optimization problem often used in machine learning and physics simulations. The use of ferroelectric materials and compute-in-memory architecture suggests an attempt to improve energy efficiency and speed compared to traditional computing methods. The focus on 'simulated bifurcation' indicates the application of this hardware to a specific type of computation.