Solution methods for very highly integrated circuits.

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While advances in manufacturing enable the fabrication of integrated circuits containing tens-to-hundreds of millions of devices, the time-sensitive modeling and simulation necessary to design these circuits poses a significant computational challenge. This is especially true for mixed-signal integrated circuits where detailed performance analyses are necessary for the individual analog/digital circuit components as well as the full system. When the integrated circuit has millions of devices, performing a full system simulation is practically infeasible using currently available Electrical Design Automation (EDA) tools. The principal reason for this is the time required for the nonlinear solver to compute the solutions of large ... continued below

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29 p.

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Nong, Ryan; Thornquist, Heidi K.; Chen, Yao; Mei, Ting; Santarelli, Keith R. & Tuminaro, Raymond Stephen December 1, 2010.

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Description

While advances in manufacturing enable the fabrication of integrated circuits containing tens-to-hundreds of millions of devices, the time-sensitive modeling and simulation necessary to design these circuits poses a significant computational challenge. This is especially true for mixed-signal integrated circuits where detailed performance analyses are necessary for the individual analog/digital circuit components as well as the full system. When the integrated circuit has millions of devices, performing a full system simulation is practically infeasible using currently available Electrical Design Automation (EDA) tools. The principal reason for this is the time required for the nonlinear solver to compute the solutions of large linearized systems during the simulation of these circuits. The research presented in this report aims to address the computational difficulties introduced by these large linearized systems by using Model Order Reduction (MOR) to (i) generate specialized preconditioners that accelerate the computation of the linear system solution and (ii) reduce the overall dynamical system size. MOR techniques attempt to produce macromodels that capture the desired input-output behavior of larger dynamical systems and enable substantial speedups in simulation time. Several MOR techniques that have been developed under the LDRD on 'Solution Methods for Very Highly Integrated Circuits' will be presented in this report. Among those presented are techniques for linear time-invariant dynamical systems that either extend current approaches or improve the time-domain performance of the reduced model using novel error bounds and a new approach for linear time-varying dynamical systems that guarantees dimension reduction, which has not been proven before. Progress on preconditioning power grid systems using multi-grid techniques will be presented as well as a framework for delivering MOR techniques to the user community using Trilinos and the Xyce circuit simulator, both prominent world-class software tools.

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29 p.

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  • Report No.: SAND2010-8815
  • Grant Number: AC04-94AL85000
  • DOI: 10.2172/1011611 | External Link
  • Office of Scientific & Technical Information Report Number: 1011611
  • Archival Resource Key: ark:/67531/metadc841785

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Office of Scientific & Technical Information Technical Reports

Reports, articles and other documents harvested from the Office of Scientific and Technical Information.

Office of Scientific and Technical Information (OSTI) is the Department of Energy (DOE) office that collects, preserves, and disseminates DOE-sponsored research and development (R&D) results that are the outcomes of R&D projects or other funded activities at DOE labs and facilities nationwide and grantees at universities and other institutions.

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  • December 1, 2010

Added to The UNT Digital Library

  • May 19, 2016, 3:16 p.m.

Description Last Updated

  • Dec. 1, 2016, 10:57 p.m.

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Nong, Ryan; Thornquist, Heidi K.; Chen, Yao; Mei, Ting; Santarelli, Keith R. & Tuminaro, Raymond Stephen. Solution methods for very highly integrated circuits., report, December 1, 2010; United States. (digital.library.unt.edu/ark:/67531/metadc841785/: accessed April 21, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.