In this paper, we propose an SKB-tree representation for two modern floorplaning problems: fixed-outline and voltage-island driven floorplanning. Since SKB-tree can dynamically allocate regions for blocks so that all blocks can be placed into a specific outline for each solution, it is a suitable representation for dealing with the fixed-outline constraint. Due to this good property, we also use it to deal with the voltage-island driven floorplanning. Different from previous works, we constrain blocks of the same voltage to be placed into one region to save power routing resource, simplify power planning, and reduce IR Drop. Experimental results show the feasibility of SKB-tree. For the fixed-outline constraint with zero deadspace, SKB-tree achieved significantly better wirelength than A-FP, Parquet 4.0, ZDS, and SAFFOA. SKB-tree can get better results than other fixed-outline driven floorplanners because it only needs to focus on wirelength optimization during simulated annealing. Besides, for voltage island driven floorplanning, SKB-tree also consumes less power and wirelength.

Fixed outline floorplanning has recently attracted more attention due to its usefulness in solving real problems in industry. This paper applies two convex optimization methods, named UFO, to solve this problem, which consists of a global distribution stage followed by a local legalization phase. In the first stage, modules are transformed into circles, and a push-pull (PP) model is proposed to uniformly distribute modules over the fixed outline with consideration of their wirelength. Due to the quality of the PP model, we obtain good results after the first stage. Therefore, it is not necessary to consider wirelength in the legalization phase. In order to maintain good results of the first stage, we propose a procedure to extract the geometric relations of the modules from the results of the first stage and store it in constraint graphs. Then, the locations and shapes of the modules are determined by second-order cone programming, which penalizes overlap and obeys the boundary constraints. Finally, we extend the UFO methodology to consider pre-placed modules in a fixed outline. We have implemented two convex functions on MATLAB, and experimental results have demonstrated that UFO clearly outperforms the results reported in the literature on the GSRC and MCNC benchmarks.