[petsc-dev] Performance of Petsc + ViennaCL 1.5.1 (branch:petsc-dev/next)

[Mani Chandra]

I forgot to mention that it is indeed the code I sent in January, but I
also attached it in the first email in this thread.

Cheers,
Mani
On Feb 23, 2014 10:42 AM, "Mani Chandra" <mc0710 at gmail.com> wrote:

> Hi Karl,
>
> I have attached the code already in my last email. It is the last
> attachment. The memory leak has been fixed. Thanks!
>
> Cheers,
> Mani
> On Feb 23, 2014 5:57 AM, "Karl Rupp" <rupp at mcs.anl.gov> wrote:
>
>> Hi Mani,
>>
>> thanks for the quick feedback.
>>
>> > I tested the updated implementation of the viennacl bindings in
>>
>>> petsc-dev/next and I get rather poor performance when using viennacl on
>>> either cpu or gpu. I am using the TS module (type:theta) with a simple
>>> advection equation in 2D with resolution 256x256 and 8 variables.
>>>
>>
>> Good, this has about 500k unknowns, so OpenCL kernel launch overhead
>> should not be a show-stopper.
>>
>>  I
>>> tested with the following cases:
>>>
>>> 1) Single cpu with petsc's old aij mat and vec implementation
>>> 2) Viennacl mat and vec and using VecViennaCLGetArrayRead/Write in the
>>> residual evaluation function on an intel cpu with intel's opencl.
>>> 3) Viennacl mat and vec and using VecViennaCLGetArrayRead/Write in the
>>> residual evaluation function on an nvidia gpu.
>>>
>>> The first case is the fastest and the other cases are 2-3 times slower.
>>> Attached are the log summaries for each cases and the code I used to
>>> test with. I am running using the following command:
>>>
>>> time ./petsc_opencl -ts_monitor -snes_monitor -ts_dt 0.01 -ts_max_steps
>>> 10 -ts_type theta -log_summary
>>>
>>
>> As Matt already noted, the bottleneck here is the frequent copy from/to
>> the device. I see 90% of the time spent in MatFDColorApply, so this is
>> where we need to look at. Is there any chance you can send me the code to
>> reproduce this directly? Is it the same you sent me back in January?
>>
>> Btw: Mani, does the memory still get filled up on the GPU for larger time
>> steps?
>>
>> Best regards,
>> Karli
>>
>>
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