Fast and efficient Lagrangian Relaxation-based Discrete Gate Sizing

Discrete gate sizing has attracted a lot of attention recently as the EDA industry faces the challenge of optimizing large standard cell-based circuits. The discreteness of the problem, along with complex timing models, stringent constraints and ever increasing circuit sizes make the problem very difficult to tackle. Lagrangian Relaxation is an effective technique to handle complex constrained optimization problems and therefore has been used for gate sizing. In this paper, we propose an improved Lagrangian Relaxation formulation for leakage power minimization that accounts for maximum gate input slew and maximum gate output capacitance in addition to the circuit timing constraints. We also present a fast topological greedy heuristic to solve the Lagrangian Relaxation Subproblem and a complementary procedure to fix the few remaining slew and capacitace violations. The experimental results, generated by using the ISPD 2012 Discrete Gate Sizing Contest infrastructure, show that our technique is able to optimize a circuit with up to 959K gates within only 51 minutes. Comparing to the ISPD Contest top three teams, our technique obtained on average 18.9%, 16.7% and 43.8% less leakage power, while being 38, 31 and 39 times faster.