ARPACK Users' Guide: Solution of Large-Scale Eigenvalue Problems with Implicitly Restarted Arnoldi Methods

作者: R. B. Lehoucq , D. C. Sorensen , C. Yang

DOI: 10.1137/1.9780898719628

关键词: Eigenvalues and eigenvectorsParallel computingSingular value decompositionArnoldi iterationAlgorithmProjection (linear algebra)Trace (linear algebra)FactorizationEigendecomposition of a matrixComputer scienceSubroutine

摘要: List of figures tables Preface 1. Introduction to ARPACK. Important features Getting started Reverse communication interface Availability Installation Documentation Dependence on LAPACK and BLAS Expected performance P_ARPACK Contributed additions Trouble shooting problems 2. with Directory structure contents An example for a symmetric Eigenvalue problem 3. General use Naming conventions, Precisions, types Shift invert spectral transformation mode shift-Invert Using the computational modes Computational real Postprocessing Eigenvectors using dseupd nonsymmetric dneupd complex zneupd 4. The implicitly restarted Arnoldi method: Krylov subspaces projection methods factorization Restarting method generalized Stopping Criterion 5. routines. ARPACK subroutines routines used by Appendix A. Templates driver Symmetric drivers Real Nonsymmetric Complex Band singular value decomposition B. Tracking progress Obtaining trace output Check-pointing C. XYaupd Routines. DSAUPD DNAUPD ZNAUPD Bibliography Index.

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