Event Detail
Session: 14:Statistical Techniques for Timing Analysis and Design
Type: Regular Session
Track: DFM and the Manufacturing Interface
Day:
Tuesday
Time: 4:30 PM - 6:30 PM
Room: 6E
Chair: Michael Orshansky - UT
14.1 Comparative Analysis of Conventional and Statistical Design Techniques, S. Burns, M. Ketkar, N. Menezes, K. Bowman, J. Tschanz, V. De - Intel
14.2 Fast Second-Order Statistical Static Timing Analysis Using Parameter Dimension Reduction, Z. Feng, P. Li - Texas A&M, Y. Zhan - AMD
14.3 NonLinear Statistical Static Timing Analysis for NonGaussian Variation Sources, L. Cheng - UC
14.4 Beyond Low-Order Statistical Response Surfaces: Latent Variable Regression for Efficient, Highly Nonlinear Fitting, A. Singhee, R. Rutenbar - CMU
Abstract: Managing variability in design continues to be a big challenge. Statitical techniques are applicable to understand the impact of variability, and enable variability-aware design. This session presents four papers dealing with statistical issues in design. The first paper gives an investigation of the impact of variability-aware optimization and evaluates the importance of using full-fledged statistical techniques for optimization. The next two papers provide improvements on core techniques for statistical timing analysis, including techiques for managing the explosion in the number of variables and methods for speeding up the max operation. The final paper provides a generic technique for constructing highly non-linear response surface models using neural networks.
