Linear constraint graph for floorplan optimization with soft blocks

In this paper, we propose the linear constraint graph (LCG) as an efficient general floorplan representation. For n blocks, an LCG has at most 2n+3 vertices and at most 6n+2 edges. Operations with direct geometric meanings are developed to perturb the LCGs. We apply the LCGs to the floorplan optimization with soft blocks to leverage its advantage in terms of the sizes of the graphs, which will improve the efficiency of solving a complex mathematical program in the inner loop of the optimization that decide the block shapes without introducing overlaps to the non-slicing floorplans. Experimental results confirm that the LCGs are effective and efficient.