一阶参数化攻击者分组统计串扰噪声分析

Sachin Shrivastava, H. Parameswaran
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引用次数: 2

摘要

随着工艺节点的减少和设计密度的增加,在UDSM时代,串扰分析是获得设计闭合的必要手段。此外,虽然串扰分析本身就很复杂,但新的工艺节点显示出设备和互连的工艺参数越来越多的变化。这反过来又增加了串声分析的复杂性。考虑过程变化影响的标准技术(基于角落的分析)对于串扰分析尤其无效,因此我们需要以类似于用于计时的方式来研究串扰的统计分析技术。我们研究了进行统计串扰分析的基本基础设施,并研究了它如何结合细胞变异和攻击者杀戮的变化的影响。我们还将攻击性窗口聚类视为一种减少串音中的悲观情绪的技术,并了解如何修改该技术以吸收进程变化的影响。本文为这些技术奠定了理论框架,并在实际设计中展示了原型实现的结果。我们表明,使用该框架和技术显示与蒙特卡罗模拟密切相关。
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Statistical Crosstalk Noise Analysis Using First Order Parameterized Approach for Aggressor Grouping
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.
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