Interval-based robust statistical techniques for non-negative convex functions, with application to timing analysis of computer chips

Proceedings of the ACM Symposium on Applied Computing

Volumn 2, Issue , 2006, Pages 1645-1649

  Orshansky, Michael ^a   Wang, Wei Shen ^a   Ceberio, Martine ^b   Xiang, Gang ^b  

^a The University of Texas at Austin   (United States)

^b 500 W University Avenue   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER SIMULATION; MICROPROCESSOR CHIPS; MONTE CARLO METHODS; PROBABILITY DISTRIBUTIONS; ROBUSTNESS (CONTROL SYSTEMS); STATISTICAL METHODS;

CLOCK CYCLE; COMPUTER CHIPS; NON-NEGATIVE CONVEX FUNCTIONS; ROBUST STATISTICAL TECHNIQUES;

FUNCTIONS;

EID: 33751027723     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1141277.1141664     Document Type: Conference Paper

References (27)

1. D. Berleant, M.-P. Cheong, C. Chu, Y. Guan, A. Kamal, G. Sheblé, S. Ferson, and J. F. Peters, Dependable handling of uncertainty, Reliable Computing 9(6) (2003), pp. 407-418.
2. D. Berleant, L. Xie, and J. Zhang, Statool: a tool for Distribution Envelope Determination (DEnv), an interval-based algorithm for arithmetic on random variables, Reliable Computing 9(2) (2003), pp. 91-108.
3. D. Berleant and J. Zhang, Using Pearson correlation to improve envelopes around the distributions of functions, Reliable Computing, 10(2) (2004), pp. 139-161.
4. D. Berleant and J. Zhang, Representation and Problem Solving with the Distribution Envelope Determination (DEnv) Method, Reliability Engineering and System Safety, 85 (1-3) (July-Sept. 2004).
5. D. Berleant and J. Zhang, Using Pearson correlation to improve envelopes around the distributions of functions, Reliable Computing, 10(2) (2004), pp. 139-161.
6. D. Boning and S. Nassif, "Models of process variations in device and interconnect", in: A. Chandrakasan (ed.), Design of High-Performance Microcomputer Ciucruits, 2000.
7. D. Chinnery and K. Keutzer, "Closing the gap between ASICs and custom", Proc. of the Design Automation Conference DAC'2000.
8. D. Chinnery and K. Keutzer (eds.), Closing the Gap Between ASICs and Custom, Kluwer, 2002.
9. R. E. Edwards, Functional analysis: theory and applications, Dover Publ., N.Y., 1995.
10. S. Ferson, RAMAS Risk Calc 4.0: Risk Assessment with Uncertain Numbers, CRC Press, Boca Raton, Florida, 2002.
11. S. Ferson, L. Ginzburg, V. Kreinovich, and J. Lopez, "Absolute Bounds on the Mean of Sum, Product, etc.: A Probabilistic Extension of Interval Arithmetic", Extended Abstracts of the 2002 SIAM Workshop on Validated Computing, Toronto, Canada, May 23-25, 2002, pp. 70-72.
12. J. Galambos, The Asymptotic Theory of Extreme Order Statistics, Wiley, New York, 1987.
13. P. J. Huber, Robust statistics, Wiley, New York, 2004.
14. L. Jaulin, M. Kieffer, O. Didrit, and E. Walter, Applied interval analysis: with examples in parameter and state estimation, robust control and robotics, Springer-Verlag, London, 2001.
15. S. Kotz and S. Nadarajah, Extreme Value Distributions: Theory and Applications, Imperial College Press, London, UK, 2000.
16. V. Kreinovich and S. Ferson, "Computing best-possible bounds for the distribution of a sum of several variables is NP-hard", International Journal of Approximate Reasoning, to appear.
17. V. Kreinovich, S. Ferson, and L. Ginzburg, "Exact Upper Bound on the Mean of the Product of Many Random Variables With Known Expectations", Reliable Computing, 9(6) (2003), pp. 441-463.
18. V. Kreinovich and L. Longpré, "Computational complexity and feasibility of data processing and interval computations, with extension to cases when we have partial information about probabilities", In: V. Brattka, M. Schroeder, K. Weihrauch, and N. Zhong, Proceedings of the Conference on Computability and Complexity in Analysis CCA '2003, Cincinnati, Ohio, USA, August 28-30, 2003, pp. 19-54.
19. V. Kreinovich, G. N. Solopchenko, S. Ferson, L. Ginzburg, and R. Aló, "Probabilities, intervals, what next? Extension of interval computations to situations with partial information about probabilities", Proceedings of the 10th IMEKO TC7 International Symposium on Advances of Measurement Science, St. Petersburg, Russia, June 30-July 2, 2004, Vol. 1, pp. 137-142.
20. A. T. Langewisch and F. F. Choobineh, "Mean and variance bounds and propagation for ill-specified random variables", IEEE Transactions on Systems, Man, and Cybernetics, Part A, 34(4) (2004), pp. 494-506.
21. M. Orshansky, "Increasing circuit performance through statistical design techniques", in: D. Chinnery and K. Keutzer (eds.), Closing the Gap Between ASICs and Custom, Kluwer, 2002.
22. M. Orshansky and A. Bandyopadhyay, "Fast statistical timing analysis handling arbitrary delay correlations", Proc. of the Design Automation Conference DAC'2004, San Diego, California, June 7-11, 2004, pp. 337-342.
23. M. Orshansky and K. Keutzer, "A general probabilistic framework for worst case timing analysis," Proceedings of the Design Automation Conference DAC'2002, June 2002, pp. 556-561.
24. M. Orshansky and K. Keutzer, "From Blind Certainty to Informed Uncertainty," Proceedings of the TAU Workshop, December 2002.
25. S. Rajasekaran, P. Pardalos, J. Reif, and J. Rolim (eds.), Handbook on Randomized Computing, Kluwer, 2001.
26. R. Trejo and V. Kreinovich, "Error Estimations for Indirect Measurements: Randomized vs. Deterministic Algorithms For 'Black-Box' Programs", In: S. Rajasekaran, P. Pardalos, J. Reif, and J. Rolim (eds.), Handbook on Randomized Computing, Kluwer, 2001, pp. 673-729.
27. H. M. Wadsworth Jr., Handbook of statistical methods for engineers and scientists, McGraw-Hill, N.Y., 1990.