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Robust and passive model order reduction for circuits containing susceptance elements
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Source International Conference on Computer Aided Design archive
Proceedings of the 2002 IEEE/ACM international conference on Computer-aided design table of contents
San Jose, California
Pages: 761 - 766  
Year of Publication: 2002
ISBN ~ ISSN:1092-3152 , 0-7803-7607-2
Authors
Hui Zheng  Carnegie Mellon University, Pittsburgh, PA
Lawrence T. Pileggi  Carnegie Mellon University, Pittsburgh, PA
Sponsors
: IEEE Circuits & Systems Society
IEEE-CS\DATC : IEEE Computer Society
SIGDA: ACM Special Interest Group on Design Automation
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 10,   Downloads (12 Months): 20,   Citation Count: 9
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ABSTRACT

Numerous approaches have been proposed to address the overwhelming modeling problems that result from the emergence of magnetic coupling as a dominant performance factor for ICsand packaging. Firstly, model order reduction (MOR) methods have been extended to robustly capture very high frequency behaviors for large RLC systems via methods such as PRIMA[8] with guaranteed passivity. In addition, new models of the magnetic couplings in terms of susceptance (inverse of inductance) have shown great promise for robust sparsification of otherwise intractable inductance coupling-matrix problems [3--5]. However, model order reduction via PRIMA for circuits that include susceptance elements does not guarantee passivity. Moreover, susceptance elements are incompatible with the path tracing algorithms that provide the fundamental runtime efficiency of RICE [10]. In this paper a novel MOR algorithm, SMOR, is proposed as an extension of ENOR [11] which exploits the matrix properties of susceptance-based circuits for runtime efficiency, and provides for a numerically stable, provably passive MOR using a new or-thonormalization strategy.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
D. Ling and A. Ruehli, Circuit Analysis, Simulation and Design -- Advances in CAD for VLSI, Vol. 3, Part II, Chapter 11, Elsevier Science Publisher B. V., North-Holland, 1987
 
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7
P. Feldmann and R. W. Freund, "Efficient Linear Circuit Analysis by Padé Approximation via the Lanczos Process, "IEEE Trans. on CAD, vol. 14, pp. 639--49, May 1995
 
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A. Odabasioglu, M. Celik and L. T. Pileggi, "PRIMA: Passive Reduced-Order Interconnect Macromodeling Algorithm," IEEE Trans. on CAD, vol. 17, no. 8, pp. 645--654, August 1998
 
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C. L. Ratzlaff and L. T. Pillage, "RICE: Rapid Interconnect Circuit Evaluation Using AWE," IEEE Trans. on CAD, vol. 13, no. 6, pp. 763--776, Jun. 1994
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M. Celik, L. Pileggi, and A. Odabasioglu, IC Interconnect Analysis, Kluwer Academic Publishers, 2002.
 
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T. Zhang, G.H. Golub, and K.H. Law. "Eigenvalue Perturbation and Generalized Krylov Subspace Method," Technical Report SCCM-98-01, Department of Computer Science, Stanford University, 1998.
 
15
Matlab User's Guide, The Math Works, Inc., Natick, MA, 2000

CITED BY  9

Collaborative Colleagues:
Hui Zheng: colleagues
Lawrence T. Pileggi: colleagues