<<forgot to add the mailing list, so I resend it>>
In addition, I did more experiments. I increased the input mesh size, let
it has 64 elements and ran with 12 processes. It looks libmesh keeps the
original partition (got when the mesh is read in) unchanged, and does not
do repartitioning after refinement. I observed it from viewing output mesh
in paraview.
So the question is under what conditions mesh repartitioning will be
triggered in libmesh?
Thank you very much.
--Junchao Zhang
On Tue, Aug 4, 2015 at 2:58 PM, Junchao Zhang <junchao.zh...@gmail.com>
wrote:
> Hi, John,
>
> Attached are my naive AMR (adapted from adaptivity_ex2.C) and its input. I
> compiled it with `libmesh-config --cxx` -o amr_libmesh
> ../examples/amr_libmesh.cpp `libmesh-config --cxxflags --include --ldflags
> --libs` and ran it with mpirun -n 5 ./amr_libmesh -niter 5
> I opened output.gmv and I could only see partitions on four processors. I
> don't know where I can call mesh.partition(n).
>
> Thanks.
>
>
> --Junchao Zhang
>
> On Tue, Aug 4, 2015 at 2:26 PM, John Peterson <jwpeter...@gmail.com>
> wrote:
>
>>
>>
>> On Tue, Aug 4, 2015 at 1:07 PM, Junchao Zhang <junchao.zh...@gmail.com>
>> wrote:
>>
>>> Hello,
>>> I am writing a simple AMR code with libmesh. My input mesh has 4
>>> elements. I use ParallelMesh. I found I could not distribute it to more
>>> than four processes even after refinement.
>>> In my code, I firstly do mesh.read("mesh.xda"). I find libmesh reads
>>> the
>>> data and distributes it on four processes, and mesh._is_serial is set to
>>> false. After that, I call mesh_refinement.refine_and_coarsen_elements(),
>>> which calls _mesh.prepare_for_use (), and then this->partition(). But in
>>> mesh_base.C, since this->is_serial() is false, the partitioner never gets
>>> called.
>>>
>>
>>
>> What happens if you call mesh.partition(n) directly?
>>
>> Please post your entire code so we can take a look.
>>
>> --
>> John
>>
>
>
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