A Randomized Greedy Algorithm for the Pattern Fill Problem for DFM Applications

This work deals with the dummy fill and negative fill insertion problem with constraints on the minimum and maximum pattern density within a moving rectangular window. It is shown that the general class of such problems is at least NP-hard. A greedy randomized algorithm for this problem is proposed, and its proof of convergence and some experimental results are presented. More detailed account of our implementation and results are available in [7].