Late Breaking Results: Placement Initialization via a Projected Eigenvector Algorithm

Canonical methods for analytical placement of VLSI designs rely on solving nonlinear programs to minimize wirelength and cell overlap. We focus on producing initial layouts such that a global analytical placer performs better compared to existing heuristics for initialization. We reduce the problem of initialization to a quadratically constrained quadratic program. Our formulation is aware of fixed macros. We propose an efficient algorithm which can quickly generate initializations for testcases with millions of cells. We show that the our method for parameter initialization results in superior performance with respect to post-detailed placement wirelength.