[petsc-users] CUDA with complex number

[recrusader]

Dear Paul,

Thank you very much for your consideration.
Actually, if the codes have been finished for complex number-based
computation in PETSc, I can do some testings.
It will be ok for me. If lots of codes need to be written regarding what I
said, I am not sure whether I have enough time.
After all, I am not familiar with PETSc and CUDA.

Best,
Yujie

On Mon, Jan 23, 2012 at 5:09 PM, Paul Mullowney <paulm at txcorp.com> wrote:

> **
> Yujie,
>
> I'm developing GPU code for PETSc that will, at some point, support
> complex numbers. However, I cannot give you a time frame as to when that
> will be complete as I have several other tasks that are higher priority
> right now.
>
> -Paul
>
> Dear Barry,
>
> For complex number-based implementation, will the functions in Vec, Mat,
> KSP, and PC having been realized for real number work at least at the
> running level?
> Do I need to do more coding for them?
>
> To my knowledge, Victor Minden finished most of the coding work for GPU
> implementation in PETSc with your and Matt's help.
> However, it seems there is not people to further realize and optimize
> other GPU functions in PETSc.
> Do you think GPU-based computation is not important or has low efficiency
> compared to current CPU-based implementation in PETSc?
>
>
> Thank you very much,
> Yujie
>
>
> On Mon, Jan 23, 2012 at 3:46 PM, Barry Smith <bsmith at mcs.anl.gov> wrote:
>
>>
>>   Yujie,
>>
>>    As I said we have never tried it. You are welcome to try it following
>> the directions I gave. You must realize that we do not have an army of
>> people to support GPUs so you are largely on your on in terms of getting
>> things done and need to use your initiative in trying things yourself and
>> working through the problems that may arise.
>>
>>   Barry
>>
>> On Jan 23, 2012, at 3:36 PM, recrusader wrote:
>>
>> > Dear Paul,
>> >
>> > Please find the changelog in the following link for CUSP 0.2.0
>> > http://code.google.com/p/cusp-library/source/browse/CHANGELOG
>> >
>> > They has added cusp:complex class to support complex number-based
>> operation.
>> >
>> > does it not work for PETSc?
>> >
>> > Thanks a lot,
>> > Yujie
>> >
>> >
>> > On Mon, Jan 23, 2012 at 3:28 PM, Paul Mullowney <paulm at txcorp.com>
>> wrote:
>> > I would claim that Petsc does not support GPU capabilities for complex
>> numbers right now.
>> >
>> > The CUSP library is templated over the scalar type (i.e. float or
>> double), however I don't think it supports complex numbers. Although, I
>> could be wrong on this.
>> >
>> > It could be somewhat straightforward to move from CUSP to CUSPARSE
>> (yes, these are different Nvidia libraries). I believe CUSPARSE supports
>> SpMV for complex types. It also supports triangular solve for complex types.
>> >
>> > -Paul
>> >
>> >
>> >     This is an installation issue, please send all installation issues
>> to petsc-maint at mcs.anl.gov with the entire configure.log
>> >
>> >
>> >
>> >
>> >    You can try editing config/PETSc/packages/cuda.py and removing the
>> two lines
>> >
>> >     if self.scalartypes.scalartype == 'complex':
>> >       raise RuntimeError('Must use real numbers with CUDA')
>> >
>> >    As it says we have never tested for complex so I do not know how far
>> it is from working.
>> >
>> >     Barry
>> >
>> > On Jan 23, 2012, at 1:24 PM, recrusader wrote:
>> >
>> > Dear PETSc Developers,
>> >
>> > I am compiling PETSc-dev using GPU in complex number mode.
>> > However, when I configure PETSc-dev, I get the following errors
>> > "
>> >
>> *******************************************************************************
>> >         UNABLE to CONFIGURE with GIVEN OPTIONS    (see configure.log
>> > for details):
>> >
>> -------------------------------------------------------------------------------
>> > Cannot use cuda with complex numbers it is not coded for this capability
>> >
>> *******************************************************************************
>> > "
>> > I have checked CUSP. The latest version can support complex number.
>> > What should I do for CUDA?
>> > Thank you very much.
>> >
>> > Best,
>> > Yujie
>> >
>> >
>>
>>
>
>
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