Frequently Asked Questions
See also the PETSc FAQ.
1. Where should I send SLEPc bug reports and questions?
Send all maintenance requests to the SLEPc developers via the email address .
2. Is there a SLEPc users mailing list?
No, but SLEPc-related queries can be posted in the petsc-users mailing list.
3. How can I receive announcements of new SLEPc versions?
You can join the slepc-announce mailing list by following the instructions in the Contact section. We will update users regarding new major releases through this mailing list.
An alternative is to subscribe to the RSS news feed in the SLEPc front webpage. In addition to new releases, we will also notify the publication of patches.
4. How should I cite SLEPc?
When writing a scientific paper that makes use of SLEPc, you should cite at least reference  in the list of references. In addition, if you use specific SLEPc features (such as computational intervals) that have papers on the list, we suggest citing them as well.
5. Apart from PETSc, is it necessary to install other software to use SLEPc?
No, the only requirement to use SLEPc is to have PETSc installed on your system. Additionally, if you want to have access to eigensolvers not included in SLEPc, then you will have to install other libraries (e.g. ARPACK). See also the comment on linear solvers below.
6. I do not see any speedup when using more than one process
Does not apply for version 3.6 or later, see FAQ #10 below.
Probably you are dealing with a generalized eigenproblem (or a standard eigenproblem with
shift-and-invert) and solving the linear systems with the default direct solver.
By default, SLEPc uses a direct linear solver via PETSc's
which allows the use of direct solvers in parallel executions but is not a really parallel
factorization. In order to get speedup in parallel executions, you need to configure
PETSc with a parallel direct linear solver such as MUMPS. For details, see the section
"Solution of Linear Systems" in SLEPc's user manual.
7. Which is the recommended way of learning SLEPc?
Possibly, the best way of learning to use SLEPc is to follow these steps:
- First of all, get acquainted with PETSc if you are not already familiar with it (see the PETSc tutorials page).
- Read through the entire SLEPc Users Manual. In a first reading, one may skip the "advanced usage" sections.
- Follow the steps provided by the hands-on exercises, trying the examples in an available SLEPc installation.
- Use the example programs available in the SLEPc distribution as a basis for your own programs.
- Use the on-line manual pages for reference for individual routines.
8. From 3.0.0 to 3.1 the behaviour of shift-and-invert has changed
The shift-and-invert spectral transformation (and Cayley as well) is intended for computing the eigenvalues closest to a given value σ (the shift). Those eigenvalues closest to the shift become dominant in the transformed spectrum, so in SLEPc 3.0.0 one had to use
EPS_LARGEST_MAGNITUDE (the default) for this situation. For example (the last option can be omitted because it is the default):
$ ./ex1 -st_type sinvert -st_shift 3.5 -eps_largest_magnitude
In contrast, in SLEPc 3.1 the approach is to specify the target value directly in EPS (with EPSSetTarget) and indicate that we want to compute eigenvalues closest to the target, with
EPS_TARGET_MAGNITUDE. For example (again, the last option can be omitted):
$ ./ex1 -st_type sinvert -eps_target 3.5 -eps_target_magnitude
The value of the shift need not be provided because it is taken from the target value.
Note that another difference is that in 3.1 eigenvalues are returned in the correct order, that is, the first one is the closest to the target, and so on.
9. I get an error when retrieving the eigenvector
After the solver has finished, the solution can be retrieved with EPSGetEigenpair. In the
Vi) argument, one can pass
NULL (if the eigenvector is not required), or a valid
Vec object. This means the vector must have been created, for example with
MatCreateVecs, see for instance ex7. The same occurs with analog function in
10. I get an error when running shift-and-invert in parallel
In 3.6 and later versions, the shift-and-invert spectral transformation defaults to using
lu for solving linear systems. If you run with more than one MPI process this will fail, unless you use an external package for the parallel LU factorization. This is explained in see the section "Solution of Linear Systems" in SLEPc's user manual. In previous versions of SLEPc, this would not generate an error since it was using
redundant rather than plain