[petsc-users] Using factored complex matrices from MUMPS as a preconditioner in PETSC

[Evan Um]

Hi Hong,

Thanks for your kind email. I write another email to make sure I understand
it correctly. Does the zipped file from
https://www.mcs.anl.gov/petsc/developers/index.html#browsing have the
updated feature?

Best,
Evan


   - https://bitbucket.org/petsc/petsc/get/master.tar.gz




On Wed, Oct 11, 2017 at 7:56 AM, Hong <hzhang at mcs.anl.gov> wrote:

> Evan:
> The branch is already merged to master. Just use petsc master branch.
> Hong
>
> Hi Matt,
>>
>> Still unclear to me. I go to https://bitbucket.org/petsc
>> /petsc/addon/pipelines/home#!/ and then https://bitbucket.org/pet
>> sc/petsc/branches/. I don't see any tarred file or directory named "update-mumps-5.1.1-cntl".
>> Could you explain how to download the modified version from the site a
>> little bit in detail? Thank you very much for your help.
>>
>> Evan
>>
>>
>>
>>
>> On Wed, Oct 11, 2017 at 1:54 AM, Matthew Knepley <knepley at gmail.com>
>> wrote:
>>
>>> On Tue, Oct 10, 2017 at 10:30 PM, Evan Um <evanum at gmail.com> wrote:
>>>
>>>> Dear Hong,
>>>>
>>>> I just tried to check PETSC develeoper website but couldn't find the
>>>> updated dev version with name of hzang/update-mumps-5.1.1-cntl.
>>>>
>>>
>>> Hong means a branch. You get the dev repository and checkout that branch
>>>
>>>   git checkout  hzang/update-mumps-5.1.1-cntl
>>>
>>>   Thanks,
>>>
>>>    Matt
>>>
>>>
>>>> . Could you please let me know the location of the updated dev version?
>>>> Where do I need to visit to check out the dev version with the new control
>>>> switches? Thank you very much for your help.
>>>>
>>>> Best,
>>>> Evan
>>>>
>>>>
>>>>
>>>>
>>>>
>>>>
>>>> On Tue, Oct 3, 2017 at 8:34 AM, Hong <hzhang at mcs.anl.gov> wrote:
>>>>
>>>>> Evan,
>>>>> ICNTL(35) and CNTL(7) are added to petsc-mumps interface in branch
>>>>> hzhang/update-mumps-5.1.1-cntl
>>>>>
>>>>> You may give it a try. Once it passes our regression tests, I'll merge
>>>>> it to petsc master branch.
>>>>>
>>>>> Hong
>>>>>
>>>>>
>>>>> On Sun, Sep 24, 2017 at 8:08 PM, Hong <hzhang at mcs.anl.gov> wrote:
>>>>>
>>>>>> I'll check it.
>>>>>> Hong
>>>>>>
>>>>>> On Sun, Sep 24, 2017 at 3:42 PM, Evan Um <evanum at gmail.com> wrote:
>>>>>>
>>>>>>> Hi Barry,
>>>>>>>
>>>>>>> Thanks for your comments. To activate block low rank (BLR)
>>>>>>> approximation in MUMPS version 5.1.1, a user needs to turn on the
>>>>>>> functionality (i.e. ICNTL(35)=1) and specify the tolerance value (e.g.
>>>>>>> CNTL(7)=1e-4). In PETSC, I think that we can set up ICNTL and CNTL
>>>>>>> parameters for MUMPS. I was wondering if we can still use BLR approximation
>>>>>>> for a preconditioner for Krylov solvers.
>>>>>>>
>>>>>>> Best,
>>>>>>> Evan
>>>>>>>
>>>>>>>
>>>>>>> On Sat, Sep 23, 2017 at 6:45 PM, Barry Smith <bsmith at mcs.anl.gov>
>>>>>>> wrote:
>>>>>>>
>>>>>>>>
>>>>>>>> > On Sep 23, 2017, at 8:38 PM, Evan Um <evanum at gmail.com> wrote:
>>>>>>>> >
>>>>>>>> > Dear PETSC Users,
>>>>>>>> >
>>>>>>>> > My system matrix comes from finite element modeling and is
>>>>>>>> complex and unstructured. Its typical size is a few millions-by a few
>>>>>>>> millions. I wondering if I can use MUMPS parallel direct solver as a
>>>>>>>> preconditioner in PETSC. For example, I want to pass factored matrices to
>>>>>>>> Krylov iterative solvers such as QMR. Is there any PETSC+MUMPS example code
>>>>>>>> for the purpose?
>>>>>>>>
>>>>>>>>   You don't pass factored matrices you just pass the original
>>>>>>>> matrix and use -pc_type lu -pc_factor_mat_solver_package mumps
>>>>>>>>
>>>>>>>> > Can PETSC call the latest MUMPS that supports block low rank
>>>>>>>> approximation?
>>>>>>>>
>>>>>>>>   No, send us info on it and we'll see if we can add an interface
>>>>>>>>
>>>>>>>>
>>>>>>>> >
>>>>>>>> > In advance, thank you very much for your comments.
>>>>>>>> >
>>>>>>>> > Best,
>>>>>>>> > Evan
>>>>>>>> >
>>>>>>>> >
>>>>>>>> >
>>>>>>>> >
>>>>>>>> >
>>>>>>>>
>>>>>>>>
>>>>>>>
>>>>>>
>>>>>
>>>>
>>>
>>>
>>> --
>>> What most experimenters take for granted before they begin their
>>> experiments is infinitely more interesting than any results to which their
>>> experiments lead.
>>> -- Norbert Wiener
>>>
>>> https://www.cse.buffalo.edu/~knepley/ <http://www.caam.rice.edu/~mk51/>
>>>
>>
>>
>
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