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Static Crosstalk-Noise Analysis: For Deep Sub-Micron Digital Designs. Softcover reprint of the original 1st ed. 2004
・ISBN 978-1-4757-7949-3 paper EUR 99.99
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| 著者・編者 | Pinhong Chen / Kirkpatrick, Desmond A. / Keutzer, Kurt, |
|---|---|
| 出版社 | (Springer-Verlag New York Inc., US) |
| 出版年月 | 2013 |
| ページ数 | 113 pp. |
| 言語 | ENG |
| ニュース番号 | ＜A05-38220＞ |
解説
As the feature size decreases in deep sub-micron designs, coupling capacitance becomes the dominant factor in total capacitance. The resulting crosstalk noise may be responsible for signal integrity issues and significant timing variation. Traditionally, static timing analysis tools have ignored cross coupling effects between wires altogether. Newer tools simply approximate the coupling capacitance by a 2X Miller factor in order to compute the worst case delay. The latter approach not only reduces delay calculation accuracy, but can also be shown to underestimate the delay in certain scenarios.
This book describes accurate but conservative methods for computing delay variation due to coupling. Furthermore, most of these methods are computationally efficient enough to be employed in a static timing analysis tool for complex integrated digital circuits. To achieve accuracy, a more accurate computation of the Miller factor is derived. To achieve both computational efficiency and accuracy, a variety of mechanisms for pruning the search space are detailed, including:
This book describes accurate but conservative methods for computing delay variation due to coupling. Furthermore, most of these methods are computationally efficient enough to be employed in a static timing analysis tool for complex integrated digital circuits. To achieve accuracy, a more accurate computation of the Miller factor is derived. To achieve both computational efficiency and accuracy, a variety of mechanisms for pruning the search space are detailed, including:
-Spatial pruning - reducing aggressors to those in physical proximity,
-Electrical pruning - reducing aggressors by electrical strength,
-Temporal pruning - reducing aggressors using timing windows,
-Functional pruning - reducing aggressors by Boolean functional analysis.