On Mon, Aug 17, 2020 at 7:05 PM Fande Kong <fdkong...@gmail.com> wrote:
> IIRC, Chaco does not produce an arbitrary number of subdomains. The number
> needs to be like 2^n.
>
No, Chaco can do an arbitrary number.
Thanks,
Matt
> ParMETIS and PTScotch are much better, and they are production-level code.
> If there is no particular reason, I would like to suggest staying with
> ParMETIS and PTScotch.
>
> Thanks,
>
> Fande,
>
>
>
> On Fri, Aug 14, 2020 at 10:07 AM Eda Oktay <eda.ok...@metu.edu.tr> wrote:
>
>> Dear Barry,
>>
>> Thank you for answering. I am sending a sample code and a binary file.
>>
>> Thanks!
>>
>> Eda
>>
>> Barry Smith <bsm...@petsc.dev>, 14 Ağu 2020 Cum, 18:49 tarihinde şunu
>> yazdı:
>>
>>>
>>> Could be a bug in Chaco or its call from PETSc for the special case
>>> of one process. Could you send a sample code that demonstrates the problem?
>>>
>>> Barry
>>>
>>>
>>> > On Aug 14, 2020, at 8:53 AM, Eda Oktay <eda.ok...@metu.edu.tr> wrote:
>>> >
>>> > Hi all,
>>> >
>>> > I am trying to try something. I am using the same MatPartitioning
>>> codes for both CHACO and ParMETIS:
>>> >
>>> > ierr =
>>> MatConvert(SymmA,MATMPIADJ,MAT_INITIAL_MATRIX,&AL);CHKERRQ(ierr);
>>> > ierr = MatPartitioningCreate(MPI_COMM_WORLD,&part);CHKERRQ(ierr);
>>> > ierr = MatPartitioningSetAdjacency(part,AL);CHKERRQ(ierr);
>>> >
>>> > ierr = MatPartitioningSetFromOptions(part);CHKERRQ(ierr);
>>> > ierr = MatPartitioningApply(part,&partitioning);CHKERRQ(ierr);
>>> >
>>> > After obtaining the IS, I apply this to my original nonsymmetric
>>> matrix and try to get an approximate edge cut.
>>> >
>>> > Except for 1 partitioning, my program completely works for 2,4 and 16
>>> partitionings. However, for 1, ParMETIS gives results where CHACO I guess
>>> doesn't since I am getting errors about the index set.
>>> >
>>> > What is the difference between CHACO and ParMETIS that one works for 1
>>> partitioning and one doesn't?
>>> >
>>> > Thanks!
>>> >
>>> > Eda
>>>
>>>
--
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.cse.buffalo.edu/~knepley/>
