A-B Nodes Classification for Power Estimation

In this paper, an optimization for the classical statistical power estimation method is proposed. This technique is applied to the individual nodes. The optimization is based on two observations. Firstly, a small percentage of both the nodes and the estimated power requires nearly a half of the total simulation time. On the other hand, the statistical method produces results with better accuracy than those specified by the user. This additional precision enables to reduce the run time for the slow convergence nodes with no loss of accuracy. A simple partitioning of the nodes into two groups, A and B, with normal and high computational cost respectively, leads to a modified stopping criterion with dramatic savings in the run time.