SkyPlace: A New Mixed-size Placement Framework using Modularity-based Clustering and SDP Relaxation

Electrostatics-based placement has made a great success and inspired many placement algorithms. However, the recent direction of improvement is missing two important problems for mixed-size placement - 1) how to initialize placement and 2) how to handle large macros in the analytical placement. In this paper, we propose our new mixed-size placer, SkyPlace which is enhanced by novel placement initialization using macro-aware clustering and semidefinite programming. Experimental results show that SkyPlace clearly outperforms the leading-edge placer on academic benchmarks.