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Modern systems-on-a-chip depend heavily on hard intellectual properties, such as standard cell and datapath libraries. As the foundries accelerate their update of advanced processes with increasingly complex design rules, and the libraries grow in flexibility and size, the cost of library development becomes prohibitively high. Automated layout-migration techniques used today, which are based on layout compaction developed a decade ago, corrupt advanced design considerations by honoring only design rules, and cannot cope with some of the new challenges involved. In this paper, we present a new integer linear programming (ILP)-based layout-migration engine, called calligrapher, and make the following contributions. First, we extend the recently proposed minimum perturbation (MP) metric designed to retain original layout design intentions, while overcoming its shortcoming of biased treatment of layout objects. Second, we propose a new design-rule-constraint algorithm, and prove its linear complexity for the number of constraints generated. Compared with what has been achieved in the literature, the proposed algorithm can significantly reduce the ILP solver time by limiting the constraint size. Third, we propose an iterative migration framework based on the concept of soft constraint. With this framework, two-dimensional compaction quality can be achieved with a runtime comparable to one-dimensional compaction. We demonstrate the effectiveness of calligrapher by migrating the Berkeley low-power libraries, originally developed for the 1.2-μm MOSIS process, into TSMC 0.25- and 0.18-μm technologies. We show that even for a very compact layout, our metric and the MP metric can make a difference by as much as 20%-45%. We also show that our iterative algorithm can improve the area by 10% on average compared to the traditional technique using the MP metric, and inflates the area by merely 7.5% compared to the traditional technique using minimum-area metric.