[petsc-users] Why does GPU solve the large sparse matrix equations only a little faster than CPU?

Matthew Knepley knepley at gmail.com
Sun Aug 5 07:27:55 CDT 2012 

On Sat, Aug 4, 2012 at 11:23 PM, Xiangze Zeng <zengshixiangze at 163.com>wrote:

> When I change the PC type to JACOBI, the KSP type to BICG, although the
> computational speed both in the GPU and CPU are higher than that when I use
> SOR+BCGS, the computational work in the GPU doesn't seem much more
> efficient, the speed only 20% higher. Is there any proposal? The
> attachments are the output of the log_summary.
>

You also have to look at the log_summary:

VecCUSPCopyTo       3967 1.0 1.3152e+01 1.0 0.00e+00 0.0 0.0e+00 0.0e+00
0.0e+00  2  0  0  0  0   2  0  0  0  0     0
VecCUSPCopyFrom     3969 1.0 5.5139e+01 1.0 0.00e+00 0.0 0.0e+00 0.0e+00
0.0e+00  9  0  0  0  0   9  0  0  0  0     0
MatCUSPCopyTo          1 1.0 4.5194e-01 1.0 0.00e+00 0.0 0.0e+00 0.0e+00
0.0e+00  0  0  0  0  0   0  0  0  0  0     0

1) I said to use GMRES for a reason. Listen to me. BiCG uses the transpose,
which right now confuses the results

2) Look at the copies to/from the GPU. You should not be copying the vector
4000 times. Start simple until you understand
    everything about how the code is running. Use -pc_type none -ksp_type
gmres and see if you can understand the results.
    Then try different KSP and PC. Trying everything at once does not help
anyone, and it is not science.

    Matt


> Thank you!
>
> Zeng Xiangze
>
> At 2012-08-05 00:01:11,"Xiangze Zeng" <zengshixiangze at 163.com> wrote:
>
> JACOBI+GMRES takes 124s to solve one system on the GPU, 172s on the CPU.
> When I use JACOBI+BICG, it takes 123s on the GPU, 162s on the CPU. In
> http://www.mcs.anl.gov/petsc/features/gpus.html, I see " All of the
> Krylov methods except KSPIBCGS run on the GPU. "  I don't find KSPIBCGS
> in the manual, is it KSPBCGS?
>
> 在 2012-08-04 23:04:55，"Matthew Knepley" <knepley at gmail.com> 写道：
>
> On Sat, Aug 4, 2012 at 9:42 AM, Xiangze Zeng <zengshixiangze at 163.com>wrote:
>
>> Another error happens when I change the PC type. When I change it to
>> PCJACOBI,  it appears the following error message:
>>
>> [0]PETSC ERROR: --------------------- Error Message
>> ------------------------------------
>> [0]PETSC ERROR: Petsc has generated inconsistent data!
>> [0]PETSC ERROR: Divide by zero!
>> [0]PETSC ERROR:
>> ------------------------------------------------------------------------
>> [0]PETSC ERROR: Petsc Development HG revision:
>> d01946145980533f72b6500bd243b1dd3666686c  HG Date: Mon Jul 30 17:03:27 2012
>> -0500
>> [0]PETSC ERROR: See docs/changes/index.html for recent updates.
>> [0]PETSC ERROR: See docs/faq.html for hints about trouble shooting.
>> [0]PETSC ERROR: See docs/index.html for manual pages.
>> [0]PETSC ERROR:
>> ------------------------------------------------------------------------
>> [0]PETSC ERROR: ../../femsolcu/./femsolcu on a arch-cuda named hohhot by
>> hongwang Sat Aug  4 22:23:58 2012
>> [0]PETSC ERROR: Libraries linked from
>> /usr/src/petsc/petsc-dev/arch-cuda-double/lib
>> [0]PETSC ERROR: Configure run at Sat Aug  4 15:10:44 2012
>> [0]PETSC ERROR: Configure options --doCleanup=1 --with-gnu-compilers=1
>> --with-vendor-compilers=0 --CFLAGS=-march=x86-64 --CXXFLAGS=-march=x86-64
>> --with-dynamic-loading --with-python=1 --with-debugging=0 --with-log=1
>> --download-mpich=1 --with-hypre=0 --with-64-bit-indices=yes --with-x11=1
>> --with-x11-include=/usr/include/X11 --download-f-blas-lapack=1
>> --with-cuda=1 --with-cusp=1 --with-thrust=1 --download-txpetscgpu=1
>> --with-precision=double --with-cudac="nvcc -m64" --download-txpetscgpu=1
>> --with-clanguage=c --with-cuda-arch=sm_20
>> [0]PETSC ERROR:
>> ------------------------------------------------------------------------
>> [0]PETSC ERROR: KSPSolve_BCGS() line 105 in src/ksp/ksp/impls/bcgs/bcgs.c
>> [0]PETSC ERROR: KSPSolve() line 446 in src/ksp/ksp/interface/itfunc.c
>> [0]PETSC ERROR: sol_comp() line 39 in "unknowndirectory/"solve.c
>>
>>  And when I change it to PCSACUSP, PCSACUSPPOLY, it both prompts out of
>> memory(I guess it's the GPU's memory). When I change it to  PCAINVCUSP, the
>> result is not better than that when I don't change the type.
>>
>
> This is breakdown in that algorithm. Try GMRES.
>
>    Matt
>
>
>> Does it have something to do with the KSP type? Should I look for a
>> suited KSP type to match the PC type which can work on the GPU?
>>
>> 在 2012-08-04 21:44:02，"Matthew Knepley" <knepley at gmail.com> 写道：
>>
>> On Sat, Aug 4, 2012 at 5:58 AM, Xiangze Zeng <zengshixiangze at 163.com>wrote:
>>
>>> After I rerun with "deugging=no", the CPU takes 30 minutes, GPU 22
>>> minutes, a little better than before. The attachment are the output of
>>> -log_summary.
>>>
>>
>> 1) Notice how the PCApply takes most of the time, so MatMult is not very
>> important
>>
>> 2) In g_log_3, notice that every time your PC is called, the vector is
>> pulled from the GPU to the CPU.
>>     This means we do not support that PC on the GPU
>>
>> There is a restriction on PCs since not many are coded for the GPU.
>> Only PCJACOBI, PCSACUSP, PCSACUSPPOLY, and PCAINVCUSP
>> work there, see http://www.mcs.anl.gov/petsc/features/gpus.html.
>>
>>    Matt
>>
>>
>>> At 2012-08-04 14:40:33,"Azamat Mametjanov" <azamat.mametjanov at gmail.com>
>>> wrote:
>>>
>>> What happens if you try to re-run with "--with-debugging=no"?
>>>
>>> On Fri, Aug 3, 2012 at 10:00 PM, Xiangze Zeng <zengshixiangze at 163.com>wrote:
>>>
>>>> Dear Matt,
>>>>
>>>> My CPU is Intel Xeon E5-2609, GPU is Nvidia GF100 [Quadro 4000].
>>>> The size of the system is 2522469 x 2522469, and the number non-0
>>>> elements is 71773925, about 0.000012 of the total.
>>>> The output of -log_summary is in the attachment. The G_log_summary is
>>>> the output when using GPU, C_log_summary when using CPU.
>>>>
>>>> Zeng Xiangze
>>>>
>>>> 在 2012-08-03 22:28:07，"Matthew Knepley" <knepley at gmail.com> 写道：
>>>>
>>>>  On Fri, Aug 3, 2012 at 9:18 AM, Xiangze Zeng <zengshixiangze at 163.com>wrote:
>>>>
>>>>> Dear all,
>>>>>
>>>>> When I use the CPU solve the equations, it takes 78 minutes, when I
>>>>> change to use GPU, it uses 64 minutes, only 15 minutes faster. I see some
>>>>> paper say when using PETCs with GPU to solve the large sparse matrix
>>>>> equations, it can be several times faster? What's the matter?
>>>>>
>>>>
>>>> For all performance questions, we at least need the output of
>>>> -log_summary. However, we would also need to know
>>>>
>>>>   - The size and sparsity of your system
>>>>
>>>>   - The CPU and GPU you used (saying anything without knowing this is
>>>> impossible)
>>>>
>>>>    Matt
>>>>
>>>>
>>>>> Thank you!
>>>>>
>>>>> Sincerely,
>>>>> Zeng Xiangze
>>>>>
>>>>>
>>>>>
>>>>
>>>>
>>>> --
>>>> 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
>>>>
>>>>
>>>>
>>>>
>>>
>>>
>>> --
>>> Mailbox 379, School of Physics
>>> Shandong University
>>> 27 South Shanda Road, Jinan, Shandong, P.R.China, 250100
>>>
>>>
>>>
>>
>>
>> --
>> 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
>>
>>
>>
>> --
>> Mailbox 379, School of Physics
>> Shandong University
>> 27 South Shanda Road, Jinan, Shandong, P.R.China, 250100
>>
>>
>>
>
>
> --
> 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
>
>
>
> --
> Mailbox 379, School of Physics
> Shandong University
> 27 South Shanda Road, Jinan, Shandong, P.R.China, 250100
>
>
>
>
> --
> Mailbox 379, School of Physics
> Shandong University
> 27 South Shanda Road, Jinan, Shandong, P.R.China, 250100
>
>
>


-- 
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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