Re: [Libmesh-users] Mesh read performance

[Renato P. <re...@gm...>]

Hi

It seems that partitioning is taking a lot of time.
If I skip it, it runs much faster. >> mesh.skip_partitioning(true);
Does that make any sense?

Renato


On Sat, May 11, 2019 at 10:59 PM Renato Poli <re...@gm...> wrote:

> Hi Kirk,
>
> I see there is something related to the parallelization.
> I am using mpirun.mpich.
> With a single processor, it runs much faster than with 4 processors.
> Please find data below.
>
> Why parallel reading would be so slower?
> Any suggestions?
>
> XDR - 1 processor
> # Stopwatch "LibMesh::read": 12.7637 s
> XDR - 4 processors
> # Stopwatch "LibMesh::read": 135.473 s
> EXO - 1 processor
> # Stopwatch "LibMesh::read": 0.294671 s
> EXO - 4 processrs
> # Stopwatch "LibMesh::read": 198.897 s
>
> This is the mesh:
> ======
>  Mesh Information:
>   elem_dimensions()={2}
>   spatial_dimension()=2
>   n_nodes()=40147
>     n_local_nodes()=40147
>   n_elem()=19328
>     n_local_elem()=19328
>     n_active_elem()=19328
>   n_subdomains()=1
>   n_partitions()=1
>   n_processors()=1
>   n_threads()=1
>   processor_id()=0
>
>
> On Sat, May 11, 2019 at 7:15 PM Renato Poli <re...@gm...> wrote:
>
>> Thanks.
>> I am currently running on a virtual machine - not sure mpi is getting
>> along with that.
>> I will try other approaches and bring more information if necessary.
>>
>> rgds,
>> Renato
>>
>> On Sat, May 11, 2019 at 5:49 PM Kirk, Benjamin (JSC-EG311) <
>> ben...@na...> wrote:
>>
>>> Definitely not right, but that seems like something in your machine or
>>> filesystem.
>>>
>>> You can use the “meshtool-opt” command to convert it to XDR and try that
>>> for comparison. We’ve got users who routinely read massive meshes with
>>> ExodusII, so I’m skeptical of a performance regression.
>>>
>>> -Ben
>>>
>>>
>>>
>>>
>>> ------------------------------
>>> On: 11 May 2019 15:24, "Renato Poli" <re...@gm...> wrote:
>>>
>>> Hi
>>>
>>> I am reading in a mesh of 20.000 elements.
>>> I am using Exodus format.
>>> It takes up to 4 minutes.
>>> Is that right?
>>> How can I enhance performance?
>>>
>>> Thanks,
>>> Renato
>>>
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