DPlace2.0: A stable and efficient analytical placement based on diffusion

Abstract

Nowadays a placement problem often involves multi-million objects and excessive fixed blockages. We present a new global placement algorithm that scales well to the modern large-scale circuit placement problems. We simulate the natural diffusion process to spread cells smoothly over the placement region, and use both analytical and discrete techniques to improve the wire length. Although any analytical wire length technique can be used in our new framework, by using the quadratic wire length model, the hessian of our formulation is extremely sparse compared with conventional formulations, which brings 24x speed up on quadratic solver. We also propose a wire linearization technique that transform quadratic star model into HPWL exactly. The overall runtime of our tool is close to the fastest placement tool in existing literature and significantly better than others. And meanwhile, we obtain competitive wire length results to the best known ones. The average total wire length is 2.2% higher than mPL6, 0.2%, 3.1%, and 9.1% better than FastPlace3.0, APlace2.0, and Capol0.2 respectively.