Accelerating transient simulation of linear reduced order models.

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Model order reduction (MOR) techniques have been used to facilitate the analysis of dynamical systems for many years. Although existing model reduction techniques are capable of providing huge speedups in the frequency domain analysis (i.e. AC response) of linear systems, such speedups are often not obtained when performing transient analysis on the systems, particularly when coupled with other circuit components. Reduced system size, which is the ostensible goal of MOR methods, is often insufficient to improve transient simulation speed on realistic circuit problems. It can be shown that making the correct reduced order model (ROM) implementation choices is crucial to … continued below

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38 p.

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Thornquist, Heidi K.; Mei, Ting; Keiter, Eric Richard & Bond, Brad October 1, 2011.

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Description

Model order reduction (MOR) techniques have been used to facilitate the analysis of dynamical systems for many years. Although existing model reduction techniques are capable of providing huge speedups in the frequency domain analysis (i.e. AC response) of linear systems, such speedups are often not obtained when performing transient analysis on the systems, particularly when coupled with other circuit components. Reduced system size, which is the ostensible goal of MOR methods, is often insufficient to improve transient simulation speed on realistic circuit problems. It can be shown that making the correct reduced order model (ROM) implementation choices is crucial to the practical application of MOR methods. In this report we investigate methods for accelerating the simulation of circuits containing ROM blocks using the circuit simulator Xyce.

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38 p.

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  • October 1, 2011

Added to The UNT Digital Library

  • May 19, 2016, 3:16 p.m.

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  • Dec. 2, 2016, 7:01 p.m.

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Thornquist, Heidi K.; Mei, Ting; Keiter, Eric Richard & Bond, Brad. Accelerating transient simulation of linear reduced order models., report, October 1, 2011; United States. (https://digital.library.unt.edu/ark:/67531/metadc837019/: accessed April 18, 2024), University of North Texas Libraries, UNT Digital Library, https://digital.library.unt.edu; crediting UNT Libraries Government Documents Department.

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