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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 대한전자공학회 JOURNAL OF SEMICONDUCTOR TECHNOLOGY AND SCIENCE Journal of Semiconductor Technology and Science Vol.15 No.1
- 발행연도
- 2015.2
- 수록면
- 101 - 113 (13page)
이용수
초록· 키워드
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The Monte-Carlo (MC) technique is very efficient solution for statistical problem. Various MC methods can easily be applied to statistical circuit performance analysis. Recently, as the number of process parameters and their impact, has increasingly affected circuit performance, a sufficient sample size is required in order to consider high dimensionality, profound nonlinearity, and stringent accuracy requirements. Also, it is important to identify the performance of circuit as soon as possible. In this paper, Fast MC method is proposed for efficient analysis of circuit performance. The proposed method analyzes performance using enhanced-precision Latin Hypercube Sampling Monte Carlo (LHSMC). To increase the accuracy of the analysis, we calculate the effective dimension for the low discrepancy value on critical parameters. This will guarantee a robust input vector for the critical parameters. Using a 90㎚ process parameter and OP-AMP, we verified the accuracy and reliability of the proposed method in comparison with the standard MC, LHS and Quasi Monte Carlo (QMC).
목차
Abstract
Ⅰ. INTRODUCTION
Ⅱ. BACKGROUND AND RELATED WORK
Ⅲ. PROPOSED FAST MONTE CARLO
Ⅳ. EXPERIMENTAL RESULTS
Ⅴ. CONCLUSIONS
REFERENCES
참고문헌 (20)
참고문헌 신청
1. [학술대회논문] - M.Mani / 2005 / An Efficient Algorithm for Statistical Minimization of Total Power under Timing Yield Constraints / IEEE/ACM DAC
2. [학술대회논문] - K.Chopra / 2005 / Parametric Yield Maximization using Gate Sizing based on Efficient Statistical Power and Delay Gradient Computation / Proc. International conference on Computer Aided Design : 1023 ~ 1028
3. [학술지(정기간행물)] - M. Keramat / 1997 / Worst Case Efficiency of LHSMC Yield Estimator of Electrical Circuits / Proc. ISCAS 3 : 1660 ~ 1663
4. [학술대회논문] - R. Kanj / 2006 / Mixture Important Sampling and Its Application to the Analysis of SRAM Design in the Presence of Rare Failure Events / Proc. Design Automation Conference : 69 ~ 72
5. [학술대회논문] - S. Tasiran / 2006 / Smart Monte Carlo for yield Estimation / Proc. ACM/IEEE TAU
2. [학술대회논문] - K.Chopra / 2005 / Parametric Yield Maximization using Gate Sizing based on Efficient Statistical Power and Delay Gradient Computation / Proc. International conference on Computer Aided Design : 1023 ~ 1028
3. [학술지(정기간행물)] - M. Keramat / 1997 / Worst Case Efficiency of LHSMC Yield Estimator of Electrical Circuits / Proc. ISCAS 3 : 1660 ~ 1663
4. [학술대회논문] - R. Kanj / 2006 / Mixture Important Sampling and Its Application to the Analysis of SRAM Design in the Presence of Rare Failure Events / Proc. Design Automation Conference : 69 ~ 72
5. [학술대회논문] - S. Tasiran / 2006 / Smart Monte Carlo for yield Estimation / Proc. ACM/IEEE TAU
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