JADAMILU: a software code for computing selected eigenvalues of large sparse symmetric matrices A new software code for computing selected eigenvalues and associated eigenvectors of a real symmetric matrix is described. The eigenvalues are either the smallest or those closest to some specified target, which may be in the interior of the spectrum. The underlying algorithm combines the Jacobi-Davidson method with efficient multilevel incomplete LU (ILU) preconditioning. Key features are modest memory requirements and robust convergence to accurate solutions. Parameters needed for incomplete LU preconditioning are automatically computed and may be updated at run time depending on the convergence pattern. The software is easy to use by non-experts and its top level routines are written in FORTRAN 77. Its potentialities are demonstrated on a few applications taken from computational physics (Source: http://cpc.cs.qub.ac.uk/summaries/)

References in zbMATH (referenced in 16 articles , 1 standard article )

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  1. Wen, Zaiwen; Zhang, Yin: Accelerating convergence by augmented Rayleigh-Ritz projections for large-scale eigenpair computation (2017)
  2. Kestyn, James; Polizzi, Eric; Tang, Ping Tak Peter: Feast eigensolver for non-Hermitian problems (2016)
  3. Li, Ruipeng; Xi, Yuanzhe; Vecharynski, Eugene; Yang, Chao; Saad, Yousef: A thick-restart Lanczos algorithm with polynomial filtering for Hermitian eigenvalue problems (2016)
  4. Baye, Daniel: The Lagrange-mesh method (2015)
  5. Liu, Xin; Wen, Zaiwen; Zhang, Yin: An efficient Gauss-Newton algorithm for symmetric low-rank product matrix approximations (2015)
  6. Röhrig-Zöllner, Melven; Thies, Jonas; Kreutzer, Moritz; Alvermann, Andreas; Pieper, Andreas; Basermann, Achim; Hager, Georg; Wellein, Gerhard; Fehske, Holger: Increasing the performance of the Jacobi-Davidson method by blocking (2015)
  7. Lessmann, Markus; Würtz, Rolf P.: Learning invariant object recognition from temporal correlation in a hierarchical network (2014) ioport
  8. Andrzejewski, Janusz: On optimizing Jacobi-Davidson method for calculating eigenvalues in low dimensional structures using eight band $\boldk\cdot\boldp$ model (2013)
  9. Liu, Xin; Wen, Zaiwen; Zhang, Yin: Limited memory block Krylov subspace optimization for computing dominant singular value decompositions (2013)
  10. Pilón, Horacio Olivares: $\textHe^3+_2$ and $\textHeH^2+$ molecular ions in a strong magnetic field: The Lagrange-mesh approach (2012)
  11. Romero, Eloy; Cruz, Manuel B.; Roman, Jose E.; Vasconcelos, Paulo B.: A parallel implementation of the Jacobi-Davidson eigensolver for unsymmetric matrices (2011)
  12. Saad, Yousef: Numerical methods for large eigenvalue problems (2011)
  13. Stathopoulos, Andreas; McCombs, James R.: PRIMME: preconditioned iterative multimethod eigensolver -- methods and software description (2010)
  14. Hochstenbach, Michiel E.; Notay, Yvan: Controlling inner iterations in the Jacobi-Davidson method (2009)
  15. Schenk, Olaf; Bollhöfer, Matthias; Römer, Rudolf A.: On large-scale diagonalization techniques for the Anderson model of localization (2008)
  16. Bollhöfer, Matthias; Notay, Yvan: JADAMILU: a software code for computing selected eigenvalues of large sparse symmetric matrices (2007)