A predictive distributed congestion metric with application to technology mapping

Abstract

Due to increasing design complexities, routing congestion has become a critical problem in very large scale integration designs. This paper introduces a distributed metric to predict routing congestion and applies it to technology mapping that targets area and delay optimization. Our technology mapping algorithms are guided by a probabilistic congestion map for the subject graph to identify the congested regions, where congestion-optimal matches are favored. Experimental results on a set of benchmark circuits in a 90-nm technology show that congestion-aware mapping results in a reduction of 37%, on an average, in track overflows with marginal gate-area penalty as compared to conventional area-oriented technology mapping. For delay-oriented mapping, our algorithm improves track overflows by 20%, on an average, in addition to preserving or improving the delay, as compared to the conventional method.