Practical methods of optimization; (2nd ed.)
Practical methods of optimization; (2nd ed.)
DAC '97 Proceedings of the 34th annual Design Automation Conference
Design and analysis of power distribution networks in PowerPC microprocessors
DAC '98 Proceedings of the 35th annual Design Automation Conference
Full-chip verification methods for DSM power distribution systems
DAC '98 Proceedings of the 35th annual Design Automation Conference
On Finding the Maxima of a Set of Vectors
Journal of the ACM (JACM)
A static pattern-independent technique for power grid voltage integrity verification
Proceedings of the 40th annual Design Automation Conference
Early-stage power grid analysis for uncertain working modes
Proceedings of the 2004 international symposium on Physical design
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
A Monte Carlo approach for maximum power estimation based on extreme value theory
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Proceedings of the International Conference on Computer-Aided Design
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Identifying worst-case voltage drop conditions in every module supplied by the power grid is a crucial problem in modern IC design. In this paper we develop a novel methodology for power grid verification which is based on accurately constructing the space of current variations of the supplied modules and locating its precise points that yield the worst-case voltage drop conditions. The construction of the current space is performed via plain simulation and statistical extrapolation using results from extreme value theory. The method overcomes limitations of past methods which either relied on loosely bounding the worst-case voltage drop, or abstracted the current space in a vague and incomplete set of bound-type constraints. Experimental results verify the potential of the proposed method to identify worst-case conditions and demonstrate the pessimism inherent in previous bound-type approaches.