Monte Carlo based statistical timing analysis using an efficient sampling method

被引：1

作者：

Yang, Zhixi ^{[1
]}

Yang, Jun ^{[1
]}

Xing, Kefei ^{[1
]}

Yang, Guang ^{[1
]}

机构：

[1] Natl Univ Def Technol, Coll Mechantron Engn & Automat, Changsha 410073, Hunan, Peoples R China

来源：

IEICE ELECTRONICS EXPRESS | 2016年 / 13卷 / 24期

关键词：

Monte Carlo; statistical static timing analysis (SSTA); efficient sampling;

D O I：

10.1587/elex.13.20160735

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Statistical static timing analysis (SSTA) is one of the most commonly used methods for analyzing timing behavior under process variations (PVs). Monte Carlo (MC) simulation is a straightforward and effective method for SSTA. In this paper, a new sampling method is proposed to improve an MC-based approach by reducing the number of simulation samples. This method utilizes stratification with an importance analysis for the selection of samples of PVs. Extensive simulations are performed to show that the proposed method achieves a better precision on ISCAS 89 benchmarks compared to other MC simulation approaches.

引用

页码：1 / 10

页数：10

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