How is PETSc used to solve linear eigenvalue problems?
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).
Which is the scalable library for eigenvalue problem computations?
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.
Which is MPI standard does SLEPc use?
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:
Which is the latest version of the SLEPc library?
For a summary of its functionality, download the SLEPc 1-page flyer: New patch release: slepc-3.15.1 contains various configuration and compilation fixes, and bug fixes in SVDCROSS and SVDCYCLIC. SLEPc 3.15 has been released. The distribution file is available at the download page.
What kind of problem can SLEPc be used for?
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).
When does the next version of SLEPc come out?
The current version of SLEPc is 3.15, released in March, 2021. 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).