Parallel Preconditioning with Sparse Approximate Inverses
SIAM Journal on Scientific Computing
INDUCTWISE: inductance-wise interconnect simulator and extractor
Proceedings of the 2002 IEEE/ACM international conference on Computer-aided design
On-chip interconnect modeling by wire duplication
Proceedings of the 2002 IEEE/ACM international conference on Computer-aided design
Fast algorithms for IR drop analysis in large power grid
ICCAD '05 Proceedings of the 2005 IEEE/ACM International conference on Computer-aided design
A hybrid linear equation solver and its application in quadratic placement
ICCAD '05 Proceedings of the 2005 IEEE/ACM International conference on Computer-aided design
Parallel domain decomposition for simulation of large-scale power grids
Proceedings of the 2007 IEEE/ACM international conference on Computer-aided design
Hierarchical analysis of power distribution networks
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
A multigrid-like technique for power grid analysis
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Power grid analysis using random walks
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
PowerRush: a linear simulator for power grid
Proceedings of the International Conference on Computer-Aided Design
Fast Poisson solver preconditioned method for robust power grid analysis
Proceedings of the International Conference on Computer-Aided Design
Hi-index | 0.03 |
An algorithm is presented for the fast and accurate simulation of power/ground mesh structures. Our method is a direct (noniterative) approach for simulation based upon a parallel matrix inversion algorithm. The new dimension of flexibility provided by our algorithm allows for a more accurate analysis of power/ground mesh structures using resistance, inductance, capacitance, interconnect models. Specifically, we offer a method that employs a sparse approximate inverse technique to consider more reluctance coupling terms for increased accuracy of simulation. Our algorithm shows substantial computational improvement over the best known direct and iterative numerical techniques that are applicable to these large-scale simulation problems.