An innovative Steiner tree based approach for polygon partitioning

As device technology continues to scale past 65 nm, the heavy application of resolution enhancement techniques (RET) makes the complexity, run time and quality issues in mask data preparation (MDP) grow severely. As one major and core step in MDP, polygon partitioning converts the complex layout shapes into trapezoids suitable for mask writing. The partitioning run time and quality of the resulting polygon partitions directly impacts the cost, integrity, and quality of the written mask. In this work, we introduce an innovative approach to solve the polygon partition problem by constructing a variant Steiner minimal tree: minimal partition tree (MPT). We prove the equivalence between MPT and the optimal polygon partition. Also, the solution search space for MPT is further reduced for the efficiency of the MPT algorithms. Finally, a generic MPT algorithm flow and a linear-time heuristic algorithm based on it are proposed. Experiments show that MPT solves the polygon partitioning with very promising and high quality results.