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 of PETSc 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 3.14, released in September, 2020.

SLEPc is based on the PETSc data structures and it employs the MPI standard 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:  

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