Krylov-subspace methods for reduced-order modeling in circuit simulation

被引:299
|
作者
Freund, RW [1 ]
机构
[1] Bell Labs, Lucent Technol, Murray Hill, NJ 07974 USA
关键词
Lanczos algorithm; Arnoldi process; linear dynamical system; VLSI interconnect; transfer function; Pade approximation; stability; passivity; positive real function;
D O I
10.1016/S0377-0427(00)00396-4
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
The simulation of electronic circuits involves the numerical solution of very large-scale, sparse, in general nonlinear, systems of differential-algebraic equations. Often, the size of these systems can be reduced considerably by replacing the equations corresponding to linear subcircuits by approximate models of much smaller state-space dimension. In this paper, we describe the use of Krylov-subspace methods for generating such reduced-order models of linear subcircuits. Particular emphasis is on reduced-order modeling techniques that preserve the passivity of linear RLC subcircuits. (C) 2000 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:395 / 421
页数:27
相关论文
共 50 条
  • [41] Error estimation of reduced-order modeling of high speed RLCG circuit
    Lu, NL
    Hajj, IN
    [J]. IEEE SYMPOSIUM ON IC/PACKAGE DESIGN INTEGRATION - PROCEEDINGS, 1998, : 143 - 148
  • [42] Causal reduced-order modeling of distributed structures in a transient circuit simulator
    Mohan, R
    Choi, MJ
    Mick, SE
    Hart, FP
    Chandrasekar, K
    Cangellaris, AC
    Franzon, PD
    Steer, MB
    [J]. IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES, 2004, 52 (09) : 2207 - 2214
  • [43] Reveal: An Extensible Reduced-Order Model Builder for Simulation and Modeling
    Agarwal, Khushbu
    Sharma, Poorva
    Ma, Jinliang
    Lo, Chaomei
    Gorton, Ian
    Liu, Yan
    [J]. COMPUTING IN SCIENCE & ENGINEERING, 2014, 16 (02) : 44 - 53
  • [44] Numerical simulation and reduced-order modeling of airfoil gust response
    Zaide, Avi
    Raveh, Daniella
    [J]. AIAA Journal, 2006, 44 (08): : 1826 - 1834
  • [45] Numerical simulation and reduced-order modeling of airfoil gust response
    Zaide, Avi
    Raveh, Daniella
    [J]. AIAA JOURNAL, 2006, 44 (08) : 1826 - 1834
  • [46] A CLASS OF APPROXIMATE INVERSE PRECONDITIONERS BASED ON KRYLOV-SUBSPACE METHODS FOR LARGE-SCALE NONCONVEX OPTIMIZATION
    Al-Baali, Mehiddin
    Caliciotti, Andrea
    Fasano, Giovanni
    Roma, Massimo
    [J]. SIAM JOURNAL ON OPTIMIZATION, 2020, 30 (03) : 1954 - 1979
  • [47] Efficient large-scale power grid analysis based on preconditioned Krylov-subspace iterative methods
    Chen, TH
    Chen, CCP
    [J]. 38TH DESIGN AUTOMATION CONFERENCE PROCEEDINGS 2001, 2001, : 559 - 562
  • [48] Performance Analysis of Multi-GPU Implementations of Krylov-Subspace Methods Applied to FEA of Electromagnetic Phenomena
    Peixoto de Camargos, Ana Flavia
    Silva, Viviane Cristine
    [J]. IEEE TRANSACTIONS ON MAGNETICS, 2015, 51 (03)
  • [49] Krylov Subspace Methods for Model Order Reduction in Computational Electromagnetics
    Bonotto, Matteo
    Cenedese, Angelo
    Bettini, Paolo
    [J]. IFAC PAPERSONLINE, 2017, 50 (01): : 6355 - 6360
  • [50] Exploring the Exponential Integrators with Krylov Subspace Algorithms for Nonlinear Circuit Simulation
    Wang, Xinyuan
    Zhuang, Hao
    Cheng, Chung-Kuan
    [J]. 2017 IEEE/ACM INTERNATIONAL CONFERENCE ON COMPUTER-AIDED DESIGN (ICCAD), 2017, : 163 - 168