A new control strategy for an artificial intelligence approach to VLSI layout compaction

In the past years, research work on knowledge-based expert systems for VLSI-CAD tools has always concentrated on floorplanning, placement, routing, and cell generation. A knowledge-based approach to VLSI layout compaction has not been published in any journal, as far as the authors know. In this paper an expert compactor interpreting layout constraints by modularized and extensible knowledge experts is presented. The key goal of this paper is to elucidate the novel features of the new control scheduling model of our knowledge-based expert compactor. Experimental results show that the presented control strategy is applicable to achieve an expert compactor competing with the conventional algorithmic approaches.