特征值问题求解开源代码SLEPc
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http://www.grycap.upv.es/slepc/documentation/manual.htm
A good starting point for learning SLEPc is to read the Users Manual and then try the hands-on exercises. Application programmers can readily begin to use SLEPc from a high level (starting from one of the examples) and then gradually learn more details according to their needs.
Printable Documentation
SLEPc Users Manual - [PDF]
SLEPc Technical Reports (STR):
- STR-1: Orthogonalization Routines in SLEPc - [PDF]
- STR-2: Single Vector Iteration Methods in SLEPc - [PDF]
- STR-3: Subspace Iteration in SLEPc - [PDF]
- STR-4: Arnoldi Methods in SLEPc - [PDF]
- STR-5: Lanczos Methods in SLEPc - [PDF]
- STR-6: A Survey of Software for Sparse Eigenvalue Problems - [PDF]
- STR-7: Krylov-Schur Methods in SLEPc - [PDF]
- STR-8: Restarted Lanczos Bidiagonalization for the SVD in SLEPc - [PDF]
- STR-9: Practical Implementation of Harmonic Krylov-Schur - [PDF]
- STR-10: Davidson Type Subspace Expansions for the Linear Eigenvalue Problem - [PDF]
SLEPc Manual Pages
Index of all manual pages
Manual pages by section:
Eigenvalue Problem Solver (EPS)
Singular Value Decomposition (SVD)
Quadratic Eigenvalue Problem (QEP)
Nonlinear Eigenvalue Problem (NEP)
Matrix Function (MFN)
Spectral Transformation (ST)
Direct Solver (DS)
Inner Product (IP)
Mathematical Function (FN)
System Routines
Note: The manual pages are organized in four categories:
Beginner - Basic usage
Intermediate - Setting options for algorithms and data structures
Advanced - Setting more advanced options and customization
Developer - Interfaces intended primarily for library developers, not for typical applications programmers
Additional Online Documentation
Hands-on Exercises for SLEPc - exercises intended for learning SLEPc by example
PETSc Manual Pages
SLEPc is based on PETSc and therefore users are recommended to use the SLEPc documentation together with the one provided with PETSc.
PETSc Documentation: [PETSc website]
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