This is the home page of SLEPc, the Scalable Library for Eigenvalue
Problem Computations. SLEPc is a software library for the solution of large scale
sparse eigenvalue problems on parallel computers. It is an extension
and can be used for linear eigenvalue problems in either standard or generalized form, with
real or complex arithmetic. It can also be used for computing a partial
SVD of a large, sparse, rectangular matrix, and to solve nonlinear eigenvalue
problems (polynomial or general).
Additionally, SLEPc provides solvers for the computation of the action of a matrix function on a vector.
The current version of SLEPc is 3.7, released in May, 2016.
SLEPc is based on the PETSc data structures and it employs the
for message-passing communication. It is being developed by researchers
from Universitat Politècnica de València (Spain).
For a summary of its functionality, download the SLEPc 1-page flyer:
|May 17, 2017
||New patch release: slepc-3.7.4 contains miscellaneous fixes.
|Sep 29, 2016
||New patch release: slepc-3.7.3 fixes some bugs in auxiliary components of SLEPc such as DS, BV and RG.
|Jul 19, 2016
||New patch release: slepc-3.7.2 contains miscellaneous fixes concerning different components of SLEPc.
|May 27, 2016
||New patch release: slepc-3.7.1 contains miscellaneous fixes, mainly related to the MFNKRYLOV and PEPJD solvers.
|May 16, 2016
||SLEPc 3.7 has been released. The distribution file is available
at the download page. A
list of changes
in this release is available.
|Mar 29, 2016
||New patch release: slepc-3.6.3 contains miscellaneous fixes.
|Mar 21, 2016
||A new SLEPc technical report STR-11 has been added in the documentation section. The report describes the contour integral solvers in SLEPc.