A true congestion prediction method based on router´s intelligence

This paper presents a true probabilistic congestion prediction method based on router´s intelligence to be used in placement stage of physical design flow. The bend distributions for IBM-PL ACE benchmarks were extracted after detailed routing and used to guide the probabilistic method. Furthermore, router´s behavior for congestion minimization was modeled and used in our prediction method. The experimental results show that for IBM-PLACE benchmarks, our estimation method predicted the congestion more accurately than a recent method by about 19%.