[petsc-users] Problem with solving Poisson eqn for some cases
TAY wee-beng
zonexo at gmail.com
Wed Mar 21 03:59:03 CDT 2018
On 19/3/2018 6:32 PM, Matthew Knepley wrote:
> On Mon, Mar 19, 2018 at 5:19 AM, TAY wee-beng <zonexo at gmail.com
> <mailto:zonexo at gmail.com>> wrote:
>
>
> On 17/3/2018 1:15 AM, Matthew Knepley wrote:
>> On Fri, Mar 16, 2018 at 12:54 PM, TAY wee-beng <zonexo at gmail.com
>> <mailto:zonexo at gmail.com>> wrote:
>>
>>
>> On 15/3/2018 6:21 PM, Matthew Knepley wrote:
>>> On Thu, Mar 15, 2018 at 3:51 PM, TAY wee-beng
>>> <zonexo at gmail.com <mailto:zonexo at gmail.com>> wrote:
>>>
>>> Hi,
>>>
>>> I'm running a CFD code which solves the momentum and
>>> Poisson eqns.
>>>
>>> Due to poor scaling with HYPRE at higher cpu no., I
>>> decided to try using PETSc with boomeramg and gamg.
>>>
>>> I tested for some small cases and it work well. However,
>>> for the large problem which has poor scaling, it gives
>>> an error when I change my Poisson solver from pure HYPRE
>>> to PETSc with boomeramg and gamg.
>>>
>>> The error is :
>>>
>>> Caught signal number 11 SEGV: Segmentation Violation,
>>> probably memory access out of range
>>>
>>> I tried using:
>>>
>>> -poisson_ksp_type richardson -poisson_pc_type hypre
>>> -poisson_pc_type_hypre boomeramg
>>>
>>> -poisson_ksp_type gmres -poisson_pc_type hypre
>>> -poisson_pc_type_hypre boomeramg
>>>
>>> -poisson_pc_type gamg -poisson_pc_gamg_agg_nsmooths 1
>>>
>>> but they all gave similar error.
>>>
>>> So why is this so? How should I troubleshoot? I am now
>>> running a debug ver of PETSc to check the error msg.
>>>
>>>
>>> 1) For anything like this, we would like to see a stack
>>> trace from the debugger or valgrind output.
>>>
>>> 2) We do have several Poisson examples. Does it fail for you
>>> on those?
>> Hi,
>>
>> Can you recommend me some suitable egs? Esp in Fortran?
>>
>>
>> Here is 2D Poisson
>>
>> https://bitbucket.org/petsc/petsc/src/4b6141395f14f0c7d1415a2ff0158eec75a27d63/src/snes/examples/tutorials/ex5f.F90?at=master&fileviewer=file-view-default
>> <https://bitbucket.org/petsc/petsc/src/4b6141395f14f0c7d1415a2ff0158eec75a27d63/src/snes/examples/tutorials/ex5f.F90?at=master&fileviewer=file-view-default>
>>
>>>
Hi,
I tried to use the different options like ML, MG BoomerAMG and while
they worked for the small problem, it failed for the large problem. I
checked and compared the 2D Poisson example with my 3D Poisson
subroutine. I found that my subroutine is very similar to my momentum
subroutine, which is based on KSPSolve:
0. DMDACreate, DMDACreate3d etc
1. Assemble matrix
2. KSPSetOperators, KSPSetType etc
3. KSPSolve
However, the 2D Poisson example uses SNESSetDM, SNESSolve etc. So does
it matter if I use SNESSolve or KSPSolve?
I also didn't set any nullspace. Is this required for a Poisson eqn solve?
Thanks
>
>>> 3) You can also try ML, which is the same type of MG as
>>> GAMG. (--download-ml).
>>>
> I have recompiled PETSc with ML. Is there an example command line
> options which I can use for ML?
>
>
> -pc_type ml
>
> Another question is generally speaking, is geometric multigrid
> (GMG) faster than algebraic?
>
>
> No, only for the setup time.
>
> I tested on a small problem and the time taken varies from 1.15min
> (HYPRE, geometric) to 3.25 (GAMG). BoomerAMG is 1.45min.
>
>
> I am not sure what you are running when you say Hypre geometric.
>
> Besides HYPRE, is there any other GMG I can use?
>
>
> As I said above, it does not converge any faster and the solve is not
> faster, its all setup time, so small problems will look faster.
> You should be doing 10-20 iterates. If you are doing more, MG is not
> working.
>
> If you truly have a structured grid, then use DMDA in PETSc and you
> can use GMG with
>
> -pc_type mg -pc_mg_nlevels <n>
>
> Matt
>
>> My cluster can't connect to the internet. Where can I 1st
>> download it?
>>
>> Similarly, how can I find out the location of the ext
>> software by myself?
>>
>>
>> The locations are all in the configure Python modules:
>>
>> https://bitbucket.org/petsc/petsc/src/4b6141395f14f0c7d1415a2ff0158eec75a27d63/config/BuildSystem/config/packages/ml.py?at=master&fileviewer=file-view-default
>> <https://bitbucket.org/petsc/petsc/src/4b6141395f14f0c7d1415a2ff0158eec75a27d63/config/BuildSystem/config/packages/ml.py?at=master&fileviewer=file-view-default>
>>
>> Thanks,
>>
>> Matt
>>
>>> Thanks,
>>>
>>> Matt
>>>
>>>
>>> --
>>> Thank you very much.
>>>
>>> Yours sincerely,
>>>
>>> ================================================
>>> TAY Wee-Beng (Zheng Weiming) 郑伟明
>>> Personal research webpage:
>>> http://tayweebeng.wixsite.com/website
>>> <http://tayweebeng.wixsite.com/website>
>>> Youtube research showcase:
>>> https://www.youtube.com/channel/UC72ZHtvQNMpNs2uRTSToiLA
>>> <https://www.youtube.com/channel/UC72ZHtvQNMpNs2uRTSToiLA>
>>> linkedin: www.linkedin.com/in/tay-weebeng
>>> <http://www.linkedin.com/in/tay-weebeng>
>>> ================================================
>>>
>>>
>>>
>>>
>>> --
>>> 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/%7Emk51/>
>>
>>
>>
>>
>> --
>> 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/%7Emk51/>
>
>
>
>
> --
> 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/%7Emk51/>
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