Estimation of peak power dissipation in VLSI circuits using the limiting distributions of extreme order statistics

In this paper, we present a statistical method for estimating the peak power dissipation in very large scale integrated (VLSI) circuits. The method is based on the theory of extreme order statistics and its application to the probabilistic distributions of the cycle-by-cycle power consumption, the maximum-likelihood estimation, and the Monte-Carlo simulation. It enables us to predict the maximum power of a VLSI circuit in the set of constrained input vector pairs as well as the complete set of all possible input vector pairs. The simulation-based nature of the proposed method allows us to avoid the limitations of a gate-level delay model and a gate-level circuit structure. Most significantly, the proposed method produces maximum power estimates to satisfy user-specified error and confidence levels. Experimental results show that this method typically produces maximum power estimates within 5% of the actual value and with a 90% confidence level by only simulating less than 2500 input vectors.