Parameter finding methods for oscillators with a specified oscillation frequency
Proceedings of the 44th annual Design Automation Conference
Proceedings of the 2008 Asia and South Pacific Design Automation Conference
Periodic steady-state analysis augmented with design equality constraints
Proceedings of the conference on Design, automation and test in Europe
Proceedings of the 2009 Asia and South Pacific Design Automation Conference
PiCAP: a parallel and incremental capacitance extraction considering stochastic process variation
Proceedings of the 46th Annual Design Automation Conference
Proceedings of the 2010 Asia and South Pacific Design Automation Conference
A Fast Non-Monte-Carlo Yield Analysis and Optimization by Stochastic Orthogonal Polynomials
ACM Transactions on Design Automation of Electronic Systems (TODAES)
A new uncertainty budgeting based method for robust analog/mixed-signal design
Proceedings of the 49th Annual Design Automation Conference
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
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With technology scaling down to 90nm and below, many yield-driven design and optimization methodologies have been proposed to cope with the prominent process variation and to increase the yield. A critical issue that affects the efficiency of those methods is to estimate the yield when given design parameters under variations. Existing methods either use Monte Carlo method in performance domain where thousands of simulations are required, or use local search in parameter domain where a number of simulations are required to characterize the point on the yield boundary defined by performance constraints. To improve efficiency, in this paper we propose QuickYield, a yield surface boundary determination by surface-point finding and global-search. Experiments on a number of different circuits show that for the same accuracy, QuickYield is up to 519X faster compared with the Monte Carlo approach, and up to 4.7X faster compared with YENSS, the fastest approach reported in literature.