On 19/3/2018 6:32 PM, Matthew Knepley wrote:
On Mon, Mar 19, 2018 at 5:19 AM, TAY wee-beng <zon...@gmail.com
<mailto:zon...@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 <zon...@gmail.com
<mailto:zon...@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
<zon...@gmail.com <mailto:zon...@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/>
