Adaptive sampling for efficient failure probability analysis of SRAM cells

IEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD

Volumn , Issue , 2009, Pages 623-630

  Jaffari, Javid ^a   Anis, Mohab ^a  

^a UNIVERSITY OF WATERLOO   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

CIRCUIT SIMULATION; COMPUTER AIDED DESIGN; COVARIANCE MATRIX; FAILURE (MECHANICAL); ITERATIVE METHODS; SAMPLING; STATIC RANDOM ACCESS STORAGE;

ADAPTIVE SAMPLING; ADAPTIVE SAMPLING METHODS; CONFIDENCE INTERVAL; ESTIMATION VARIANCE; FAILURE PROBABILITY; ORDERS OF MAGNITUDE; SAMPLING DISTRIBUTION; TWO-COMPONENT;

MONTE CARLO METHODS;

EID: 76349112696     PISSN: 10923152     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1687399.1687515     Document Type: Conference Paper

References (23)

1. S. R. Nassif, "Design for variability in DSM technologies," in IEEE International Symposium on Quality Electronic Design, pp. 451-454, 2000.
2. R. V. Joshi, S. Mukhopadhyay, D. W. Plass, Y. H. Chan, and C. C.-T. A. Devgan, "Variability analysis for sub-100 nm PD/SOI CMOS SRAM cell," in IEEE European Solid-State Circuits Conference, pp. 211-214, 2004.
3. Y. Taur and T. H. Ning, Fundamentals of modern VLSI devices, Cambridge University Press, 1998.
4. R. Heald, P. Wang, "Variability in Sub-100nm SRAM designs," in ACM International Conference on Computer Aided Design, pp. 347-352, 2004.
5. A. J. Bhavnagarwala, X. Tang, and J. D. Meindl, "The impact of intrinsic device fluctuations on CMOS SRAM cell stability," IEEE J. Solid-State Circuits, vol. 36, pp. 658-665, April 2001.
6. S. Mukhopadhyay, H. Mahmoodi, and K. Roy, "Statistical design and optimization of SRAM cell for yield enhancement," in ACM International Conference on Computer Aided Design, pp. 10-13, 2004.
7. K. Agarwal and S. Nassif, "Statistical analysis of SRAM cell stability," in ACM Design Automation Conference, pp. 57-62, 2006.
8. R. Kanj, R. Joshi, and S. Nassif, "Mixture importance sampling and its application to the analysis of SRAM designs in the presence of rare failure events," in ACM Design Automation Conference, pp. 69-72, 2006.
9. V. Veetil, D. Sylvester, and D. Blaauw, "Efficient Monte Carlo based incremental statistical timing analysis, " in ACM Design Automation Conference, pp. 676-681, 2008.
10. J. Jaffari and M. Anis, "On efficient Monte Carlo-based statistical static timing analysis of digital circuits," in ACM International Conference on Computer Aided Design, pp. 196-203, 2008.
11. D. E. Hocevar, M. R. Lightner, and T. N. Trick, "A study of variance reduction techniques for estimating circuit yields," IEEE Trans. on CAD, vol. 2, pp. 180-192, July 1983.
12. A. Owen and Y. Zhou, "Safe and effective importance sampling," J. American Stat. Association, vol. 95, pp. 135-143, March 2000.
13. T. C. Hesterberg, Advances in importance sampling, Ph.D. Dissertation, Statistics Department, Stanford University, 1988.
14. A. S. Householder, The numerical treatment of a single nonlinear equation, McGraw-Hill, 1970.
15. P. J. Smith, M. Shafi, and H. Gao, "Quick simulation: A review of importance sampling techniques in communications systems," IEEE J. Select. Areas Commun., vol. 15, pp. 597-613, May 1997.
16. P. Glasserman, P. Heidelberger, and P. Shahabuddin, "Asymptotic optimal importance sampling and stratification for pricing path-dependent options," Mathematical Finance, vol. 9, pp. 117-152, April 1999.
17. J. S. Sadowsky and J. A. Bucklew, "On large deviations theory and asymptotically efficient Monte Carlo estimation," IEEE Trans. Inform. Theory, vol. 36, pp. 579-588, March 1990.
18. R. E. Melchers, "Search-based importance sampling," Structural Safety, vol. 9, pp. 117-128, 1990.
19. J. S. Stadler and S. Roy, "Adaptive importance sampling," IEEE J. Select. Areas Commun., vol. 11, pp. 309-316, 1993.
20. I. Dimov, A. Karaivanova, R. Georgieva, and S. Ivanovska, "Parallel importance separation and adaptive Monte Carlo algorithms for multiple integrals," in LNCS: Numerical Methods and Applications, pp. 99-107, 2003.
21. H. J. Kushner and G. G. Yin, Stochastic approximation algorithms and applications, Springer, 1997.
22. B. Arouna, "Adaptative Monte Carlo method, a variance reduction technique," Monte Carlo Methods and Appl., vol. 10, pp. 1-24, 2004.
23. H. Robbins and S. Monro, "A stochastic approximation method," Annals of Mathematical Statistics, vol. 22, pp. 400-407, 1951.