Efficient Power Network Analysis with Modeling of Inductive Effects

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概要

• 論文の詳細を見る

• In this paper, an efficient method is proposed to accurately analyze large-scale power/ground (P/G) networks, where inductive parasitics are modeled with the partial reluctance. The method is based on frequency-domain circuit analysis and the technique of vector fitting [14], and obtains the time-domain voltage response at given P/G nodes. The frequency-domain circuit equation including partial reluctances is derived, and then solved with the GMRES algorithm with rescaling, preconditioning and recycling techniques. With the merit of sparsified reluctance matrix and iterative solving techniques for the frequency-domain circuit equations, the proposed method is able to handle large-scale P/G networks with complete inductive modeling. Numerical results show that the proposed method is orders of magnitude faster than HSPICE, several times faster than INDUCTWISE [4], and capable of handling the inductive P/G structures with more than 100, 000 wire segments.

• （社）電子情報通信学会の論文
• 2010-06-01

著者

• HONG Xianlong

  Dept. of Computer Science and Technology, TNList, Tsinghua University

• ZENG Shan

  Dept. of Computer Science and Technology, Tsinghua University

• YU Wenjian

  Dept. of Computer Science and Technology, Tsinghua National Laboratory for Information Science and T

• CHENG Chung-Kuan

  Dept. of Computer Science and Engineering, University of California, San Diego

• Hong Xianlong

  Eda Lab Department Of Computer Science And Technology Tsinghua University

• Hong Xianlong

  Dept. Of Computer Science And Technology Tsinghua National Laboratory For Information Science And Te

• Hong Xianlong

  Dept. Of Computer Science And Technology Tnlist Tsinghua University

• Zeng Shan

  Dept. Of Computer Science And Technology Tsinghua University

• Yu Wenjian

  Dept. Of Computer Science And Technology Tsinghua National Laboratory For Information Science And Te

• Yu Wenjian

  Dept. Computer Science & Technology Tsinghua Univ.

• Hong Xianlong

  Dept. Of Computer Science And Technology Tsinghua National Laboratory For Information Science And Te

• Cheng Chung‐kuan

  Dept. Of Computer Science And Engineering University Of California

• Cheng Chung-Kuan

  Dept. of Computer Science and Engineering, University of California

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