Documentation#

A good starting point for learning SLEPc is to read the Users Manual and then follow the Hands-on exercises. See also the video-tutorials below. 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.

SLEPc Users Manual#

Manual Pages#

  • The individual manual pages for all SLEPc functions are available by selecting the top bar menu item C/Fortran API.

  • Similarly, we provide the full documentation of SLEPc’s Python interface (slepc4py API in the top bar menu).

  • The SLEPc documentation often links to PETSc Manual Pages as well as PETSc Users Manual. The PETSc documentation can be found at the PETSc website.

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]

  • STR-11: Contour Integral Spectrum Slicing Method in SLEPc - [PDF]

Video-Tutorials#

The following video-tutorials have a 10 minute duration each, and include demonstration of actual code executions.

  1. SLEPc: What is it for?

  2. SLEPc: Installation

  3. SLEPc: Compiling and running programs

  4. SLEPc: Standard eigenvalue problem

  5. SLEPc: Viewing the solution

  6. SLEPc: Spectral transformation

  7. SLEPc: How to compute different parts of the spectrum

  8. SLEPc: Matrix-free eigenproblems

Additional Documentation#