On finding supernodes for sparse matrix computations
SIAM Journal on Matrix Analysis and Applications
Hierarchical analysis of power distribution networks
Proceedings of the 37th Annual Design Automation Conference
Efficient large-scale power grid analysis based on preconditioned krylov-subspace iterative methods
Proceedings of the 38th annual Design Automation Conference
How to efficiently capture on-chip inductance effects: introducing a new circuit element K
Proceedings of the 2000 IEEE/ACM international conference on Computer-aided design
Random walks in a supply network
Proceedings of the 40th annual Design Automation Conference
Power network analysis using an adaptive algebraic multigrid approach
Proceedings of the 40th annual Design Automation Conference
Power grid reduction based on algebraic multigrid principles
Proceedings of the 40th annual Design Automation Conference
A multigrid-like technique for power grid analysis
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Fast decap allocation based on algebraic multigrid
Proceedings of the 2006 IEEE/ACM international conference on Computer-aided design
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The continuing VLSI technology scaling leads to increasingly significant power supply fluctuations, which need to be modeled accurately in circuit design and verification. Meanwhile, the huge size of power grid requires its analysis to be fast and highly scalable. Algebraic multigrid (AMG) has been recognized as a promising approach for fast power grid analysis. We propose several techniques to improve AMG-based power grid analysis: (1) dynamic reduction threshold, (2) weighted interpolation and (3) a new error smoothing scheme. Experimental results on power grid with up to 1.6 million nodes show that these techniques can improve accuracy by over 10 times compared to a reported industrial method while retaining the same fast speed.