A Stochastic-Based Efficient Critical Area Extractor on Open Access Platform

Abstract

Due to inefficient calculation in current critical area analyzer, in this work we present a method of extracting critical area for short faults from the mask layout of an integrated circuit. The method is based on the concept of sampling framework and the geometry computation of critical area. By constructing the density table of layout, our weighted sampling approach can be more efficient, thus more suitable for the larger layout. The algorithm has been implemented on OpenAccess platform to allow efficient extraction of the critical area from an arbitrary mask layout. The results show that this method can reduce computation cost, and can still maintain the accuracy at the same time.