[petsc-users] using real and complex together

[Sam Guo]

Hi Matt,
   Since I use MUMPS as preconditioner, complex uses too much memory if my
input matrix is real. Ideally if I can compile real and complex into
different symbols (like MUMPS) , I can load both version without conflict.

Thanks,
Sam

On Mon, Sep 28, 2020 at 12:52 PM Matthew Knepley <knepley at gmail.com> wrote:

> On Mon, Sep 28, 2020 at 3:43 PM Sam Guo <sam.guo at cd-adapco.com> wrote:
>
>> Hi Stefano and PETSc dev team,
>>    I want to try your suggestion to always load complex version of PETSc
>> but if my input matrix A is real, I want to create shell matrix to
>> matrix-vector and factorization using real only.
>>
>
> I do not think that will work as you expect. I will try to explain below.
>
>
>>    I still need to understand how MatRealPart works. Does it just zero
>> out the image numerical values or does it delete the image memory?
>>
>
> When we have complex values, we use the "complex" type to allocate and
> store them. Thus you cannot talk about just the memory to store imaginary
> parts.
> MatRealPart sets the imaginary parts of all the matrix elements to zero.
>
>
>> If my input matrix A is real, how do I create a shell matrix to matrix
>> -vector multiplication y=A*x where A is real, PestcScalar = complex, x and
>> y are Vec? I notice there is a VecRealPart but it seems it just zeros the
>> image numerical values. It seems I still have to create a PetscReal
>> pointer  to copy the real part of PetacScalar pointers like following. Can
>> you comment on it?
>>
>
> What you suggest would mean rewriting the matrix multiplication algorithm
> by hand after extracting the values. I am not sure if this
> is really what you want to do. Is the matrix memory really your limiting
> factor? Even if you tried to do this with templates, the memory
> from temporaries would be very hard to control.
>
>   Thanks,
>
>      Matt
>
>
>> Thanks,
>> Sam
>>
>> PetscScalar *px = nullptr;
>> VecGetArrayRead(x, &px);
>> PetscScalar *py = nullptr;
>> VecGetArray(y, &py);
>> int localSize = 0;
>> VecGetLocalSize(x, &localSize);
>> std::vector<PetasReal> realX(localSize); // I am using c++ to call PETSc
>>
>> //retrieve real part
>> for(int i = 0; i < localSize; i++)  realX[i] = PetscRealPart(px[i]);
>>
>> // do real matrix-vector multiplication
>> // realY=A*realX
>> // here where realY is std::vector<PetscReal>
>>
>> //put real part back to py
>>   for(int i = 0; i < localSize; i++)  pv[i] = realY[i];
>> VecRestoreArray(y,&py);
>>
>> On Tue, May 26, 2020 at 1:49 PM Sam Guo <sam.guo at cd-adapco.com> wrote:
>>
>>> Thanks
>>>
>>> On Tuesday, May 26, 2020, Stefano Zampini <stefano.zampini at gmail.com>
>>> wrote:
>>>
>>>> All the solvers/matrices/vectors works for PetscScalar types (i.e. in
>>>> your case complex)
>>>> If you need to solve for the real part only, you can duplicate the
>>>> matrix and call MatRealPart to zero out the imaginary part. But the solve
>>>> will always run in the complex space
>>>> You should not be worried about doubling the memory for a matrix (i.e.
>>>> real and imaginary part)
>>>>
>>>>
>>>> On May 26, 2020, at 11:28 PM, Sam Guo <sam.guo at cd-adapco.com> wrote:
>>>>
>>>> complex version is needed since matrix sometimes is real and sometimes
>>>> is complex. I want to solve real matrix without allocating memory for
>>>> imaginary part((except eigen pairs).
>>>>
>>>> On Tuesday, May 26, 2020, Zhang, Hong <hzhang at mcs.anl.gov> wrote:
>>>>
>>>>> You can build PETSc with complex version, and declare some variables
>>>>> as 'PETSC_REAL'.
>>>>> Hong
>>>>>
>>>>> ------------------------------
>>>>> *From:* petsc-users <petsc-users-bounces at mcs.anl.gov> on behalf of
>>>>> Sam Guo <sam.guo at cd-adapco.com>
>>>>> *Sent:* Tuesday, May 26, 2020 1:00 PM
>>>>> *To:* PETSc <petsc-users at mcs.anl.gov>
>>>>> *Subject:* [petsc-users] using real and complex together
>>>>>
>>>>> Dear PETSc dev team,
>>>>>    Can I use both real and complex versions together?
>>>>>
>>>>> Thanks,
>>>>> Sam
>>>>>
>>>>
>>>>
>
> --
> 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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