[petsc-users] petsc4py help with parallel execution

Thu Nov 15 11:24:18 CST 2018

If you say your program is parallel by just looking at the output from the
top command, you are probably linking against a multithreaded blas library

Il giorno Gio 15 Nov 2018, 20:09 Matthew Knepley via petsc-users <
petsc-users at mcs.anl.gov> ha scritto:

> On Thu, Nov 15, 2018 at 11:59 AM Ivan Voznyuk <ivan.voznyuk.work at gmail.com>
> wrote:
>
>> Hi Matthew,
>>
>> Does it mean that by using just command python3 simple_code.py (without
>> mpiexec) you *cannot* obtain a parallel execution?
>>
>
> As I wrote before, its not impossible. You could be directly calling PMI,
> but I do not think you are doing that.
>
>
>> It s been 5 days we are trying to understand with my colleague how he
>> managed to do so.
>> It means that by using simply python3 simple_code.py he gets 8 processors
>> workiing.
>> By the way, we wrote in his code few lines:
>> rank = PETSc.COMM_WORLD.Get_rank()
>> size = PETSc.COMM_WORLD.Get_size()
>> and we got rank = 0, size = 1
>>
>
> This is MPI telling you that you are only running on 1 processes.
>
>
>> However, we compilator arrives to KSP.solve(), somehow it turns on 8
>> processors.
>>
>
> Why do you think its running on 8 processes?
>
>
>> This problem is solved on his PC in 5-8 sec (in parallel, using *python3
>> simple_code.py*), on mine it takes 70-90 secs (in sequantial, but with
>> the same command *python3 simple_code.py*)
>>
>
> I think its much more likely that there are differences in the solver (use
> -ksp_view to see exactly what solver was used), then
> to think it is parallelism. Moreover, you would never ever ever see that
> much speedup on a laptop since all these computations
> are bandwidth limited.
>
>   Thanks,
>
>      Matt
>
>
>> So, conclusion is that on his computer this code works in the same way as
>> scipy: all the code is executed in sequantial mode, but when it comes to
>> solution of system of linear equations, it runs on all available
>> processors. All this with just running python3 my_code.py (without any
>> mpi-smth)
>>
>> Is it an exception / abnormal behavior? I mean, is it something irregular
>> that you, developers, have never seen?
>>
>> Thanks and have a good evening!
>> Ivan
>>
>> P.S. I don't think I know the answer regarding Scipy...
>>
>>
>> On Thu, Nov 15, 2018 at 2:39 PM Matthew Knepley <knepley at gmail.com>
>> wrote:
>>
>>> On Thu, Nov 15, 2018 at 8:07 AM Ivan Voznyuk <
>>> ivan.voznyuk.work at gmail.com> wrote:
>>>
>>>> Hi Matthew,
>>>> Thanks for your reply!
>>>>
>>>> Let me precise what I mean by defining few questions:
>>>>
>>>> 1. In order to obtain a parallel execution of simple_code.py, do I need
>>>> to go with mpiexec python3 simple_code.py, or I can just launch python3
>>>> simple_code.py?
>>>>
>>>
>>> mpiexec -n 2 python3 simple_code.py
>>>
>>>
>>>> 2. This simple_code.py consists of 2 parts: a) preparation of matrix b)
>>>> solving the system of linear equations with PETSc. If I launch mpirun (or
>>>> mpiexec) -np 8 python3 simple_code.py, I suppose that I will basically
>>>> obtain 8 matrices and 8 systems to solve. However, I need to prepare only
>>>> one matrix, but launch this code in parallel on 8 processors.
>>>>
>>>
>>> When you create the Mat object, you give it a communicator (here
>>> PETSC_COMM_WORLD). That allows us to distribute the data. This is all
>>> covered extensively in the manual and the online tutorials, as well as the
>>> example code.
>>>
>>>
>>>> In fact, here attached you will find a similar code (scipy_code.py)
>>>> with only one difference: the system of linear equations is solved with
>>>> scipy. So when I solve it, I can clearly see that the solution is obtained
>>>> in a parallel way. However, I do not use the command mpirun (or mpiexec). I
>>>> just go with python3 scipy_code.py.
>>>>
>>>
>>> Why do you think its running in parallel?
>>>
>>>   Thanks,
>>>
>>>      Matt
>>>
>>>
>>>> In this case, the first part (creation of the sparse matrix) is not
>>>> parallel, whereas the solution of system is found in a parallel way.
>>>> So my question is, Do you think that it s possible to have the same
>>>> behavior with PETSC? And what do I need for this?
>>>>
>>>> I am asking this because for my colleague it worked! It means that he
>>>> launches the simple_code.py on his computer using the command python3
>>>> simple_code.py (and not mpi-smth python3 simple_code.py) and he obtains a
>>>> parallel execution of the same code.
>>>>
>>>> Thanks for your help!
>>>> Ivan
>>>>
>>>>
>>>> On Thu, Nov 15, 2018 at 11:54 AM Matthew Knepley <knepley at gmail.com>
>>>> wrote:
>>>>
>>>>> On Thu, Nov 15, 2018 at 4:53 AM Ivan Voznyuk via petsc-users <
>>>>> petsc-users at mcs.anl.gov> wrote:
>>>>>
>>>>>> Dear PETSC community,
>>>>>>
>>>>>> I have a question regarding the parallel execution of petsc4py.
>>>>>>
>>>>>> I have a simple code (here attached simple_code.py) which solves a
>>>>>> system of linear equations Ax=b using petsc4py. To execute it, I use the
>>>>>> command python3 simple_code.py which yields a sequential performance. With
>>>>>> a colleague of my, we launched this code on his computer, and this time the
>>>>>> execution was in parallel. Although, he used the same command python3
>>>>>> simple_code.py (without mpirun, neither mpiexec).
>>>>>>
>>>>>> I am not sure what you mean. To run MPI programs in parallel, you
>>>>> need a launcher like mpiexec or mpirun. There are Python programs (like
>>>>> nemesis) that use the launcher API directly (called PMI), but that is not
>>>>> part of petsc4py.
>>>>>
>>>>>   Thanks,
>>>>>
>>>>>      Matt
>>>>>
>>>>>> My configuration: Ubuntu x86_64 Ubuntu 16.04, Intel Core i7, PETSc
>>>>>> 3.10.2, PETSC_ARCH=arch-linux2-c-debug, petsc4py 3.10.0 in virtualenv
>>>>>>
>>>>>> In order to parallelize it, I have already tried:
>>>>>> - use 2 different PCs
>>>>>> - use Ubuntu 16.04, 18.04
>>>>>> - use different architectures (arch-linux2-c-debug,
>>>>>> linux-gnu-c-debug, etc)
>>>>>> - ofc use different configurations (my present config can be found in
>>>>>> make.log that I attached here)
>>>>>> - mpi from mpich, openmpi
>>>>>>
>>>>>> Nothing worked.
>>>>>>
>>>>>> Do you have any ideas?
>>>>>>
>>>>>> Thanks and have a good day,
>>>>>> Ivan
>>>>>>
>>>>>> --
>>>>>> Ivan VOZNYUK
>>>>>> PhD in Computational Electromagnetics
>>>>>>
>>>>>
>>>>>
>>>>> --
>>>>> 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.cse.buffalo.edu/~knepley/>
>>>>>
>>>>
>>>>
>>>> --
>>>> Ivan VOZNYUK
>>>> PhD in Computational Electromagnetics
>>>> +33 (0)6.95.87.04.55
>>>> My webpage <https://ivanvoznyukwork.wixsite.com/webpage>
>>>> My LinkedIn <http://linkedin.com/in/ivan-voznyuk-b869b8106>
>>>>
>>>
>>>
>>> --
>>> 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.cse.buffalo.edu/~knepley/>
>>>
>>
>>
>> --
>> Ivan VOZNYUK
>> PhD in Computational Electromagnetics
>> +33 (0)6.95.87.04.55
>> My webpage <https://ivanvoznyukwork.wixsite.com/webpage>
>> My LinkedIn <http://linkedin.com/in/ivan-voznyuk-b869b8106>
>>
>
>
> --
> 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.cse.buffalo.edu/~knepley/>
>
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