Statistical Crosstalk Noise Analysis Using First Order Parameterized Approach for Aggressor Grouping

Abstract

With decreasing process nodes and increasing design density, crosstalk analysis is a must for getting design closure in the UDSM era. In addition to this, while crosstalk analysis is complex in itself, the new process nodes are showing increasing variations of process parameters for devices and interconnect. This in turn adds more complexity to crosstalk analysis. Standard techniques of factoring in the effects of process variations (corner-based analysis) is particularly ineffective for crosstalk analysis, so we need to look at techniques of statistical analysis of crosstalk in a manner similar to that used for timing. We look at a basic infrastructure for doing statistical crosstalk analysis - and look at how it can incorporate the effects of variations in cell variations and on aggressor slew. We also look at aggressor window clustering as a technique to reduce pessimism in crosstalk - and see how this technique can be modified to take in the effect of process variations. We lay the theoretical framework for these techniques in this paper, and show the results of a prototype implementation on real designs. We show that using this framework and techniques shows a close correlation with Monte-Carlo simulations.