Efficient large-scale power grid analysis based on preconditioned krylov-subspace iterative methods

  • Authors:
  • Tsung-Hao Chen;Charlie Chung-Ping Chen

  • Affiliations:
  • Electrical and Computer Engineering, University of Wisconsin-Madison, Madison, WI;-

  • Venue:
  • Proceedings of the 38th annual Design Automation Conference
  • Year:
  • 2001

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Abstract

In this paper, we propose preconditioned Krylov-subspace iterative methods to perform efficient DC and transient simulations for large-scale linear circuits with an emphasis on power delivery circuits. We also prove that a circuit with inductors can be simplified from MNA to NA format, and the matrix becomes an s.p.d matrix. This property makes it suitable for the conjugate gradient with incomplete Cholesky decomposition as the preconditioner, which is faster than other direct and iterative methods. Extensive experimental results on large-scale industrial power grid circuits show that our method is over 200 times faster for DC analysis and around 10 times faster for transient simulation compared to SPICE3. Furthermore, our algorithm reduces over 75% of memory usage than SPICE3 while the accuracy is not compromised.