Area Optimization in Floorplanning Using AP-TCG

Abstract

Most of existing floorplanning algorithms evaluate the target area after packing all of the blocks, but random perturbation will make the target area larger or less unpredictably. In this paper, a unified non-slicing area prejudged transitive closure graph (AP-TCG) algorithm is proposed, which can estimate the target area before packing. AP-TCG can indicate whether the perturbation is beneficial to the area. We discard the adverse perturbation and continue to the next permutation. This technology always makes the target area less and less. Unlike most of the existing floorplanner algorithms, APTCG is performing without Simulated Annealing (SA) scheme because of its self-convergence property. Inherited the nice properties from geometric representation of transitive closure graph (TCG), the solution space is finite (n!*n!) and every solution is feasible. The experimental results from MCNC and GSRC benchmarks show that our algorithm is efficient and effective.