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Speeding up computation of the max/min of a set of gaussians for statistical timing analysis and optimization

Published: 29 May 2013 Publication History

Abstract

Statistical static timing analysis (SSTA) involves computation of maximum (max) and minimum (min) of Gaussian random variables. Typically, the max or min of a set of Gaussians is performed iteratively in a pair-wise fashion, wherein the result of each pair-wise max or min operation is approximated to a Gaussian by matching moments of the true result obtained using Clark's approach [1]. The approximation error in the final result is thus a function of the order in which the pair-wise operations are performed.
In this paper, we analyze known "run-time expensive" ordering techniques that attempt to reduce this error in the context of SSTA and SSTA driven optimization. We propose new techniques to speeding up the computation of the max/min of a set of Gaussians by special handling of prevalent "zero error" cases. Two new methods are presented using these techniques that provide more than 60% run-time savings (3X speed-up) in max/min operations. This translates to an overall run-time improvement of 2--17% for a single SSTA run and an improvement of up to 8 hours (55%) in an SSTA driven optimization run.

References

[1]
C. E. Clark, "The greatest of a finite set of random variables," in Operations Research, Vol. 9, No. 2 (Mar - Apr), 1961, pp. 145--162.
[2]
C. Visweswariah, "Death, taxes and failing chips," in Proc. of the Design Automation Conf., 2003, pp. 343--347.
[3]
A. Devgan and C. Kashyap, "Block-based static timing analysis with uncertainty," in Proc. Intl. Conf. on Computer-Aided Design, 2003, pp. 607--614.
[4]
D. Blaauw, K. Chopra, A. Srivastava, and L. Scheffer, "Statistical timing analysis: From basic principles to state-of-the-art," in IEEE Transactions on Computer-Aided Design, 27(4) April 2008, pp. 589--607.
[5]
C. Visweswariah, K. Ravindran, K. Kalafala, S. G. Walker, and S. Narayan, "First-order incremental block-based statistical timing analysis," in Proc. of the Design Automation Conf., 2004, pp. 331--336.
[6]
M. Cain, "The moment-generating function of the minimum of bivariate normal random variables," The American Statistician, vol. 48, no. 2, pp. 124--125, May 1994.
[7]
H. Chang and S. S. Sapatnekar, "Statistical timing analysis considering spatial correlations using a single PERT-like traversal," in Proc. Intl. Conf. on Computer-Aided Design, 2003, pp. 621--625.
[8]
D. Sinha, H. Zhou, and N. V. Shenoy, "Advances in computation of the maximum of a set of Gaussian random variables," in IEEE Transactions on Computer-Aided Design, 26(8) August 2007, pp. 1522--1533.
[9]
D. Sinha, N. V. Shenoy, and H. Zhou, "Statistical timing yield optimization by gate sizing," in IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 14(10) October 2006, pp. 1140--1146.

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  • (2016)Multivariate Modeling of Variability Supporting Non-Gaussian and Correlated ParametersIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2015.245904235:2(197-210)Online publication date: 1-Feb-2016

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    cover image ACM Conferences
    DAC '13: Proceedings of the 50th Annual Design Automation Conference
    May 2013
    1285 pages
    ISBN:9781450320719
    DOI:10.1145/2463209
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 29 May 2013

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    1. statistical timing
    2. variability

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    • (2016)Multivariate Modeling of Variability Supporting Non-Gaussian and Correlated ParametersIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2015.245904235:2(197-210)Online publication date: 1-Feb-2016

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