Mathematics of Operations Research
Operations Research
Statistical Timing Analysis Considering Spatial Correlations using a Single Pert-Like Traversal
Proceedings of the 2003 IEEE/ACM international conference on Computer-aided design
Leakage Current Variability in Nanometer Technologies, invited
IWSOC '05 Proceedings of the Fifth International Workshop on System-on-Chip for Real-Time Applications
Projection-based performance modeling for inter/intra-die variations
ICCAD '05 Proceedings of the 2005 IEEE/ACM International conference on Computer-aided design
Design for Manufacturability and Statistical Design: A Comprehensive Approach
Design for Manufacturability and Statistical Design: A Comprehensive Approach
Non-linear statistical static timing analysis for non-Gaussian variation sources
Proceedings of the 44th annual Design Automation Conference
Within-die process variations: how accurately can they be statistically modeled?
Proceedings of the 2008 Asia and South Pacific Design Automation Conference
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 47th Design Automation Conference
Proceedings of the 2010 Asia and South Pacific Design Automation Conference
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Theory and Applications of Robust Optimization
SIAM Review
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This paper proposes a novel methodology for robust analog/mixed-signal IC design by introducing a notion of budget of uncertainty. This method employs a new conic uncertainty model to capture process variability and describes variability-affected circuit design as a set-based robust optimization problem. For a pre-specified yield requirement, the proposed method conducts uncertainty budgeting by associating performance yield with the size of uncertainty set for process variations. Hence the uncertainty budgeting problem can be further translated into a tractable robust optimization problem. Compared with the existing robust design flow based on ellipsoid model, this method is able to produce more reliable design solutions by allowing varying size of conic uncertainty set at different design points. In addition, the proposed method addresses the limitation that the size of ellipsoid model is calculated solely relying on the distribution of process parameters, while neglecting the dependence of circuit performance upon these design parameters. The proposed robust design framework has been verified on various analog/mixed-signal circuits to demonstrate its efficiency against ellipsoid model. An up to 24% reduction of design cost has been achieved by using the uncertainty budgeting based method.