Preconditioned Multishift BiCG for h2-Optimal Model Reduction

Mian Ilyas Ahmad, Daniel B. Szyld, Martin B. Van Gijzen

Research output: Contribution to journalArticleScientificpeer-review

15 Citations (Scopus)

Abstract

We propose the use of a multishift biconjugate gradient method (BiCG) in combina-tion with a suitable chosen polynomial preconditioning, to eficiently solve the two sets of multiple shifted linear systems arising at each iteration of the iterative rational Krylov algorithm (IRKA) [Gugercin, Antoulas, and Beattie, SIAM J. Matrix Anal. Appl., 30 (2008), pp. 609-638] for H2-optimal model reduction of linear systems. The idea is to construct in advance bases for the two preconditioned Krylov subspaces (one for the matrix and one for its adjoint). By exploiting the shift-invariant property of Krylov subspaces, these bases are then reused inside the model reduction methods for the other shifts. The polynomial preconditioner is chosen to maintain this shift-invariant property. This means that the shifted systems can be solved without additional matrix-vector prod-ucts. The performance of our proposed implementation is illustrated through numerical experiments.

Original languageEnglish
Pages (from-to)401-424
Number of pages24
JournalSIAM Journal on Matrix Analysis and Applications
Volume38
Issue number2
DOIs
Publication statusPublished - 2017

Keywords

  • BiCG
  • IRKA
  • Model order reduction
  • Polynomial preconditioning
  • Shifted linear systems

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