Nonlinear programming strategies on high-performance computers

Jia Kang, Naiyuan Chiang, Carl D. Laird, Victor M. Zavala

Abstract: In this tutorial we discuss fundamental concepts that enable the solution of large-scale structured nonlinear programming problems on high-performance computers. We focus on linear algebra parallelization strategies and discuss how such strategies influence the choice of algorithmic frameworks capable of enforcing global convergence and deal with nonconvexities. We also discuss how the characteristics of different computing architectures influence the choice of algorithmic strategies.