Benefits of Partitioning in a Projection-based and Realizable Model-order Reduction Flow

被引:1
|
作者
Miettinen, Pekka [1 ]
Honkala, Mikko [1 ]
Roos, Janne [2 ]
Valtonen, Martti [1 ]
机构
[1] Aalto Univ, Dept Radio Sci & Engn, Sch Elect Engn, FI-00076 Aalto, Finland
[2] AWR APLAC Corp, FI-02600 Espoo, Finland
关键词
Verification simulation; Interconnect modeling; Model-order reduction; Partitioning; CIRCUITS; DESIGN;
D O I
10.1007/s10836-014-5451-y
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Model-order reduction (MOR) is a typical approach to speed up the post-layout verification simulation step in circuit design. This paper studies the benefits of using circuit partitioning in a complete MOR flow. First, an efficient reduction algorithm package comprising of partitioning, reduction, and realization parts is presented. The reduction flow is then discussed using theoretical analysis and simulations from an array of 65-nm technology node interconnect circuits. It is shown that the reduction efficiency and computational costs quickly worsen with increased circuit size when using a direct projection-based MOR approach. In contrast, by using partitioning, the MOR can retain the scalability of the reduction problem, being computationally lighter and more efficient even with larger circuits. In addition, using partitioning may improve the robustness of the MOR flow in cases with circuits with many ports or sensitive verification simulations.
引用
收藏
页码:271 / 285
页数:15
相关论文
共 50 条
  • [1] Benefits of Partitioning in a Projection-based and Realizable Model-order Reduction Flow
    Pekka Miettinen
    Mikko Honkala
    Janne Roos
    Martti Valtonen
    Journal of Electronic Testing, 2014, 30 : 271 - 285
  • [2] On projection-based algorithms for model-order reduction of interconnects
    Wang, JML
    Chu, CC
    Yu, QJ
    Kuh, ES
    IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS, 2002, 49 (11) : 1563 - 1585
  • [3] PartMOR: Partitioning-Based Realizable Model-Order Reduction Method for RLC Circuits
    Miettinen, Pekka
    Honkala, Mikko
    Roos, Janne
    Valtonen, Martti
    IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS, 2011, 30 (03) : 374 - 387
  • [4] Projection-Based Model-Order Reduction of Large-Scale Maxwell Systems
    Druskin, V. L.
    Remis, R. F.
    Zaslavsky, M.
    Zimmerling, J. T.
    2017 INTERNATIONAL CONFERENCE ON ELECTROMAGNETICS IN ADVANCED APPLICATIONS (ICEAA), 2017, : 385 - 388
  • [5] Parametric Harmonic Balance Analysis of a Rotating Component by the Projection-based Model-order Reduction
    Kang, Seung-Hoon
    Lee, Sangmin
    Hwang, Minho
    Cho, Haeseong
    Kim, Yongse
    Shin, Sangjoon
    JOURNAL OF THE KOREAN SOCIETY FOR AERONAUTICAL AND SPACE SCIENCES, 2024, 52 (06) : 431 - 439
  • [6] Assessment of Projection-Based Model Order Reduction for a Benchmark Hypersonic Flow Problem
    Chmiel, Matthew R.
    Barnett, Joshua
    Farhat, Charbel
    AIAA SCITECH 2024 FORUM, 2024,
  • [7] A projection-based algorithm for model-order reduction with H2 performance: A convex-optimization setting
    Ibrir, Salim
    AUTOMATICA, 2018, 93 : 510 - 519
  • [8] Hierarchical Model-Order Reduction Flow
    Honkala, Mikko
    Miettinen, Pekka
    Roos, Janne
    Neff, Carsten
    SCIENTIFIC COMPUTING IN ELECTRICAL ENGINEERING SCEE 2008, 2010, 14 : 539 - +
  • [9] Comparison of Projection-Based Model Order Reduction for Frequency Responses
    Won, Bo Reum
    Han, Jeong Sam
    TRANSACTIONS OF THE KOREAN SOCIETY OF MECHANICAL ENGINEERS A, 2014, 38 (09) : 933 - 941
  • [10] Projection-based order reduction of a nonlinear biophysical neuronal network model
    Lehtimakki, Mikko
    Paunonen, Lassi
    Linne, Marja-Leena
    2019 IEEE 58TH CONFERENCE ON DECISION AND CONTROL (CDC), 2019, : 1 - 6