Hybrid floorplanning based on partial clustering and module restructuring

In this paper, we propose a hybrid floorplanning methodology. Two hierarchical strategies for avoiding local optima during iterative improvement are proposed: (1) Partial Clustering, and (2) Module Restructuring. These strategies work for localizing nets connecting small modules in small regions, and conceal such small modules and their nets during the iterative improvement phase. This method is successful in reducing both area and wire length in addition to reducing the computational time required for optimization. Although our method only searches slicing floorplans, the results are superior to the results obtained even with non-slicing floorplans. We applied our method to the largest MCNC floorplan benchmark example, ami49, and industrial data. For the ami49 benchmark, we obtained results superior to any published results for both estimated area and routing results.