Predicting the number of vias and dimensions of full-custom circuits using neural networks techniques

Summary form only given as follows. Block layout dimension prediction is an important activity in many VLSI design tasks. Block layout dimension prediction is harder than block area prediction and has been previously considered to be intractable. The authors obtain a solution to this problem using a neural network machine learning paradigm. The method uses a neural network to predict first the number of vias and then another neural network that uses this prediction and other circuit features to predict the width and the height of the layout of the circuit. It is noted that the presented approach has produced much better results than those published previously