Less Expensive and High Quality Stopping Criteria for MC-Based Analog IC Yield Optimization

摘要

This paper investigates the stopping criteria for Monte-Carlo (MC)-based yield optimization of analog integrated circuits. Available stopping criteria are briefly reviewed and a new adaptive criterion, called combined global and local improvement (ComImp) is presented. Experimental results show that the proposed stopping criterion has the following two advantages: (1) low risk of early termination before the optimum has been reached with the desired accuracy; (2) less additional function evaluations after the convergence has already been reached.