Ising Machines: Principles and Practices

4.0 credits

This course provides a systematic treatment of a number of related concepts in computing that are outside mainstream (von Neumann) approach. The primary goal is to help students understand the foundation of the on-going research of a particular type of von Neumann architecture: Ising machines. Topics include a basic review of thermodynamics (such as Gibbs-Boltzmann distribution, Langevin dynamics), computational methods inspired by it (such as Markov chain Monte Carlo methods, energy-based models: a subset of machine learning algorithms), and hardware design of Ising machines.