Stochastic finite elements: a spectral approach
Stochastic finite elements: a spectral approach
Digital integrated circuits: a design perspective
Digital integrated circuits: a design perspective
Vector generation for maximum instantaneous current through supply lines for CMOS circuits
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
Hierarchical analysis of power distribution networks
Proceedings of the 37th Annual Design Automation Conference
Proceedings of the 37th Annual Design Automation Conference
Current signature compression for IR-drop analysis
Proceedings of the 37th Annual Design Automation Conference
Proceedings of the 37th Annual Design Automation Conference
Random walks in a supply network
Proceedings of the 40th annual Design Automation Conference
Proceedings of the 40th annual Design Automation Conference
Modeling uncertainty in flow simulations via generalized polynomial chaos
Journal of Computational Physics
Design and Analysis of Power Distribution Networks with Accurate RLC Models
VLSID '00 Proceedings of the 13th International Conference on VLSI Design
A stochastic approach To power grid analysis
Proceedings of the 41st annual Design Automation Conference
Statistical Verification of Power Grids Considering Process-Induced Leakage Current Variations
Proceedings of the 2003 IEEE/ACM international conference on Computer-aided design
Numerical Challenges in the Use of Polynomial Chaos Representations for Stochastic Processes
SIAM Journal on Scientific Computing
Sparse and efficient reduced order modeling of linear subcircuits with large number of terminals
Proceedings of the 2004 IEEE/ACM International conference on Computer-aided design
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
ICCAD '05 Proceedings of the 2005 IEEE/ACM International conference on Computer-aided design
Testing On-Die Process Variation in Nanometer VLSI
IEEE Design & Test
Statistical model order reduction for interconnect circuits considering spatial correlations
Proceedings of the conference on Design, automation and test in Europe
Proceedings of the conference on Design, automation and test in Europe
Stochastic extended Krylov subspace method for variational analysis of on-chip power grid networks
Proceedings of the 2007 IEEE/ACM international conference on Computer-aided design
Compact modeling of variational waveforms
Proceedings of the 2007 IEEE/ACM international conference on Computer-aided design
Parameterized model order reduction via a two-directional Arnoldi process
Proceedings of the 2007 IEEE/ACM international conference on Computer-aided design
Stochastic formulation of SPICE-type electronic circuit simulation with polynomial chaos
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Proceedings of the 2009 Asia and South Pacific Design Automation Conference
Generating realistic stimuli for accurate power grid analysis
ACM Transactions on Design Automation of Electronic Systems (TODAES)
System-on-Chip Test Architectures: Nanometer Design for Testability
System-on-Chip Test Architectures: Nanometer Design for Testability
Statistical analysis of large on-chip power grid networks by variational reduction scheme
Integration, the VLSI Journal
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In this paper, we investigate the impact of interconnect and device process variations on voltage fluctuations in power grids. We consider random variations in the power grid's electrical parameters as spatial stochastic processes and propose a new and efficient method to compute the stochastic voltage response of the power grid. Our approach provides an explicit analytical representation of the stochastic voltage response using orthogonal polynomials in a Hilbert space. The approach has been implemented in a prototype software called OPERA (Orthogonal Polynomial Expansions for Response Analysis). Use of OPERA on industrial power grids demonstrated speed-ups of up to two orders of magnitude. The results also show a significant variation of about 卤 35% in the nominal voltage drops at various nodes of the power grids and demonstrate the need for variation-aware power grid analysis.