Locality-Driven Parallel Power Grid Optimization

Abstract

Large very large-scale-integration power/ground distribution networks are challenging to analyze and design due to the sheer network complexity. In this paper, a parallel sizing optimization approach is presented to minimize the wiring area of a power grid while meeting <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">IR</i> drop and electromigration constraints. Motivated by a proposed two-level hierarchical optimization, we present a novel locality-driven partitioning scheme to allow for divide-and-conquer-based scalable optimization of large power grids, which is infeasible via flat optimization. Unlike existing partitioning-based strategies, the proposed method is very flexible in terms of choice of partitioning boundaries and sizes. Equally importantly, it allows for simultaneous sizing of multiple partitions, leading itself naturally to parallelization.