[petsc-users] Data decomposition in PETsc for Poisson solver

Matthew Knepley knepley at gmail.com
Fri Jun 29 19:38:47 CDT 2012


On Fri, Jun 29, 2012 at 6:22 PM, Michele Rosso <mrosso at uci.edu> wrote:

>  Hi Jed,
>
> thank you for your reply.
> I checked the PETSc version currently installed on my system (Blue Gene
> P); it is 3.1-p2
> so I will use the DA type.
> Also, I cannot take advantage of DMDAGlobalToNatural since version 3.1
> does not support it.
> I was able to solve a simple Poisson system successfully but the solution
> vector is not in the correct order
> and I do not understand how to fix this. Is there an equivalent to DMDAGlobalToNatural
> in version 3.1?
>

The code is here:

http://www.mcs.anl.gov/petsc/petsc-current/src/dm/impls/da/dagtol.c.html#DMDANaturalToGlobalBegin

It should work in 3.1 with minor alterations. Otherwise, you can build your
own 3.3.

   Matt


> Thank you,
> Michele
>
>
>  On 06/26/2012 11:36 AM, Jed Brown wrote:
>
> On Tue, Jun 26, 2012 at 10:24 AM, Michele Rosso <mrosso at uci.edu> wrote:
>
>>  Thanks Jed for your reply.
>>
>> 1) I will use the DMDA object type then. I am still not very clear about
>> the difference between DA and DMDA though.
>>
>
>  DM is the generic interface, DMDA is the structured grid implementation.
> It used to be called just DA and managed a bit different. Maybe you were
> looking at old docs?
>
>
>>
>> 2) I am not interested in having ghost nodes updated. I want the proper
>> values of the solution on the proper processor.
>>      I have to fill the known-terms-vector with nodes-dependent values (
>> in contrast with  ex45f.F, where vector b is filled with 1s, thus there
>> is
>>      no dependence on the grid location). Since every processor defines
>> "non-local" (according to the PETSc internal ordering) components, the
>> vector is re-arranged
>>      and so is the solution vector.  So I will have on every process a
>> solution  which partially should be on a difference process. And this is
>> not about ghost cell.
>>     Sorry for this long explanation but I am trying to be as clear as I
>> can.
>>
>
>
> http://www.mcs.anl.gov/petsc/petsc-current/docs/manualpages/DM/DMDAGlobalToNaturalBegin.html
>
>
>>
>> Thank you fro your help and patience,
>>
>> Michele
>>
>>
>>
>>
>>
>>
>>
>>
>>
>>  On 06/26/2012 10:42 AM, Jed Brown wrote:
>>
>> On Tue, Jun 26, 2012 at 9:37 AM, Michele Rosso <mrosso at uci.edu> wrote:
>>
>>>  Hi,
>>>
>>> I need some help to use the PETSc library inside my Fortran 95 code.
>>> My goal is to solve a symmetric linear system that derives from the
>>> finite difference discretization
>>> of the Poisson equation. I will use the preconditioned conjugate method.
>>>
>>> I am mostly interested in how to decompose my data among the different
>>> processes.
>>> In particular:
>>>
>>> 1) Since my code already implements the 2D-decomposition, would it be
>>> best to build the matrix with the  DMDA object type, DA object type
>>>      or the regular Mat type?
>>>
>>
>>  It is certainly easiest to just use DMDA (and you will get geometric
>> multigrid for free, which is unbeatable for this problem), but you can work
>> directly with Mat if you prefer. See src/ksp/ksp/examples/tutorials/ex45f.F
>> for a Fortran example.
>>
>>
>>>
>>> 2) After inserting values into a vector/matrix, PETSc performs any
>>> needed message passing of nonlocal components, thus the values locally
>>> contained on a process  may be communicated to another process.  How can I
>>> revert this at the end of the computation, that is, how can I be sure that
>>> the local solution vector contains the values associated to the grid nodes
>>> contained into the hosting process?
>>>
>>
>>  Please read the section of the user's manual on local versus global
>> spaces and the structured grid decompositions. If you use DM, there is
>> DMGlobalToLocalBegin/End that update the ghost points in the local vectors.
>>
>>
>>>
>>>
>>> Thank you,
>>>
>>> Michele
>>>
>>
>>
>>
>>
>
>
>


-- 
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
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