TRLan software package This software package implements the thick-restart Lanczos method. It can be used on either a single address space machine or a distributed parallel machine. The user can choose to implement or use a matrix-vector multiplication routine in any form convenient. Most of the arithmetic computations in the software are done through calls to BLAS and LAPACK. The software is written in Fortran 90. Because Fortran 90 offers many utility functions such functions such as dynamic memory management, timing functions, random number generator and so on, the program is easily portable to different machines without modifying the source code. It can also be easily accessed from other language such as C or C++. Since the software is highly modularized, it relatively easy to adopt it for different type of situation. For example if the eigenvalue problem may have some symmetry and only a portion of the physical domain is discretized, then the dot-product routine needs to be modified. In this software, this modification is limited to one subroutine. It also can be instructed to write checkpoint files so that it can be restarted is a later time.

References in zbMATH (referenced in 51 articles )

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  1. Aishima, Kensuke: On convergence of iterative projection methods for symmetric eigenvalue problems (2017)
  2. Bosch, Jessica; Greif, Chen: Numerical solution of linear eigenvalue problems (2017)
  3. Dax, Achiya: The numerical rank of Krylov matrices (2017)
  4. Zhang, Zhongming Teng Lei-Hong: A block Lanczos method for the linear response eigenvalue problem (2017)
  5. Campos, Carmen; Roman, Jose E.: Restarted Q-Arnoldi-type methods exploiting symmetry in quadratic eigenvalue problems (2016)
  6. Kestyn, James; Polizzi, Eric; Tang, Ping Tak Peter: Feast eigensolver for non-Hermitian problems (2016)
  7. Li, Ruipeng; Xi, Yuanzhe; Vecharynski, Eugene; Yang, Chao; Saad, Yousef: A thick-restart Lanczos algorithm with polynomial filtering for Hermitian eigenvalue problems (2016)
  8. Teng, Zhongming; Zhou, Yunkai; Li, Ren-Cang: A block Chebyshev-Davidson method for linear response eigenvalue problems (2016)
  9. Vecharynski, Eugene; Yang, Chao; Xue, Fei: Generalized preconditioned locally harmonic residual method for non-Hermitian eigenproblems (2016)
  10. Wu, Gang; Zhang, Lu; Xu, Ting-ting: A framework of the harmonic Arnoldi method for evaluating $\varphi$-functions with applications to exponential integrators (2016)
  11. Aishima, Kensuke: Global convergence of the restarted Lanczos and Jacobi-Davidson methods for symmetric eigenvalue problems (2015)
  12. Feng, Ting-Ting; Wu, Gang; Xu, Ting-Ting: An inexact shift-and-invert Arnoldi algorithm for large non-Hermitian generalised Toeplitz eigenproblems (2015)
  13. Gu, M.: Subspace iteration randomization and singular value problems (2015)
  14. Potts, Daniel; Tasche, Manfred: Fast ESPRIT algorithms based on partial singular value decompositions (2015)
  15. Wu, Lingfei; Stathopoulos, Andreas: A preconditioned hybrid SVD method for accurately computing singular triplets of large matrices (2015)
  16. Golyandina, Nina; Korobeynikov, Anton: Basic singular spectrum analysis and forecasting with R (2014)
  17. Zhou, Yunkai; Chelikowsky, James R.; Saad, Yousef: Chebyshev-filtered subspace iteration method free of sparse diagonalization for solving the Kohn-Sham equation (2014)
  18. Baglama, James; Reichel, Lothar: An implicitly restarted block Lanczos bidiagonalization method using Leja shifts (2013)
  19. Huang, Tsung-Ming; Kuo, Yueh-Cheng; Wang, Weichung: Computing extremal eigenvalues for three-dimensional photonic crystals with wave vectors near the Brillouin zone center (2013)
  20. Wu, Gang; Zhang, Ying; Wei, Yimin: Accelerating the Arnoldi-type algorithm for the PageRank problem and the ProteinRank problem (2013)

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