[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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