[petsc-users] using DMDA with python

[Somdeb Bandopadhyay]

Hi again,
       Please allow me to explain in detail here:-

   1. I am using Zang's (jcp 1994) method for incompressible flow on
   generalized collocated grid.
   2. The main difference lies on the calculation of the grid matrix, for
   which I am using Gaitonde et al (2002)'s work
   3. I want to use python to set up the domain , grid(structured) and
   boundary/initial conditions.
   4. I want petsc to a) decompose the domain with dmda b) use ksp for
   linear solver.


I * have not* used petsc4py rigorously , so before trying his venture I wnt
to know whether it is feasible or not, and if there is any example for
similar work (so that I can copy their approach, to be precise)

Have a very good day.

Somdeb

On Wed, Oct 5, 2016 at 10:23 AM, Somdeb Bandopadhyay <sb020287 at gmail.com>
wrote:

> Hi again Sir,
>              Thank you very much for the quick response. I am planning to
> implement a mustiphase algorithm on collocated grid. I already qrote a C
> code for 2d case, but it wasn't very generalized . So for the final
> version, I intend to use python as a script to interact with PETSc kernels.
>
> Somdeb
>
>
> On Wed, Oct 5, 2016 at 10:12 AM, Matthew Knepley <knepley at gmail.com>
> wrote:
>
>> On Tue, Oct 4, 2016 at 9:02 PM, Somdeb Bandopadhyay <sb020287 at gmail.com>
>> wrote:
>>
>>> Dear all,
>>>             I want to write a solver for incompressible navier stokes
>>> using python and I want to use PETsc (particularly dmda & ksp) for this.
>>> May I know if this type of work is feasible/already done?
>>>
>>
>> How do you plan to discretize your system? DMDA supports only collocation
>> discretizations, so some sort of penalty for pressure would
>> have to be employed.
>>
>>   Thanks,
>>
>>      Matt
>>
>>
>>>             I intend to run my solver in a cluster and so am slightly
>>> concerned about the performance if I use python with petsc.
>>>             My deepest apologies if this mail of mine caused you any
>>> inconvenience.
>>>
>>> Somdeb
>>>
>>
>>
>>
>> --
>> 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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