TICER: realizable reduction of extracted RC circuits
ICCAD '99 Proceedings of the 1999 IEEE/ACM international conference on Computer-aided design
Introduction to algorithms
A linear-time heuristic for improving network partitions
DAC '82 Proceedings of the 19th Design Automation Conference
Model Order Reduction Techniques for Linear Systems with Large Numbers of Terminals
Proceedings of the conference on Design, automation and test in Europe - Volume 2
Exploiting input information in a model reduction algorithm for massively coupled parasitic networks
Proceedings of the 41st annual Design Automation Conference
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
An efficient method for terminal reduction of interconnect circuits considering delay variations
ICCAD '05 Proceedings of the 2005 IEEE/ACM International conference on Computer-aided design
Model order reduction of linear networks with massive ports via frequency-dependent port packing
Proceedings of the 43rd annual Design Automation Conference
Sparse implicit projection (SIP) for reduction of general many-terminal networks
Proceedings of the 2008 IEEE/ACM International Conference on Computer-Aided Design
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Poor man's TBR: a simple model reduction scheme
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
New spectral methods for ratio cut partitioning and clustering
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
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In this paper, we propose an efficient Aggregating based Model Order Reduction method (AMOR) for many-terminal interconnect circuits. The proposed AMOR method is based on the observation that those adjacent nodes of interconnect circuits with almost the same voltage can be aggregated together as a "super node". Motivated by such an idea, we propose an efficient spectral partition algorithm in AMOR method to partition the nodes into groups with almost the same voltages. The reduced-order models are then obtained by aggregating the adjacent nodes within the same groups together as "super nodes" in AMOR method. The efficiency of AMOR method is not limited by the numbers of the terminals of the networks. Moreover, noticing that the aggregating procedure can be regarded as mapping the original problem into a coarse-grid problem in multigrid method, we propose a computation-efficient smoothing procedure to further improve the simulation accuracy of the reduced-order models. With such a strategy, the simulation accuracy of the reduced-order models can always be guaranteed. Numerical results have demonstrated that, without the smoothing procedure, the reduced-order models obtained by AMOR can still achieve higher simulation efficiency in terms of accuracy and CPU time than the reduced-order models obtained by the existing elimination based methods. With the smoothing procedure, the simulation accuracy of the reduced-order models can further be improved with several iterations.