Algorithmic and Optimization Foundations for VLSI CAD

4 credits

Algorithmic techniques and optimization frameworks for large-scale, difficult optimizations. Primal-dual multicommodity flow approximations, approximations for geometric and graph Steiner formulations, continuous placement optimization, heuristics for Boolean satisfiability, multilevel methods, semidefinite programming, and application to other formulations (e.g., scheduling). Prerequisites: CSE 241A or CSE 242A, or consent of instructor.