Gate Sizing by Lagrangian Relaxation Revisited

Abstract

In this paper, we formulate the generalized convex sizing (GCS) problem that unifies the sizing problems and applies to sequential circuits with clock-skew optimization. We revisit the approach to solve the sizing problem by Lagrangian relaxation, point out several misunderstandings in the previous paper, and extend the approach to handle general convex delay functions in the GCS problems. We identify a class of proper GCS problems whose objective functions in the simplified dual problem are differentiable and transform the simultaneous sizing and clock-skew optimization problem into a proper GCS problem. We design an algorithm based on the method of feasible directions and min-cost network flow to solve proper GCS problems. The algorithm will provide evidences for infeasible GCS problems according to a condition derived by us. Experimental results confirm the efficiency and the effectiveness of our algorithm when the Elmore delay model is used.