[petsc-dev] Bad scaling of GAMG in FieldSplit

Thu Jul 26 11:56:43 CDT 2018

On Thu, Jul 26, 2018 at 10:35 AM, Junchao Zhang <jczhang at mcs.anl.gov> wrote:

> On Thu, Jul 26, 2018 at 11:15 AM, Fande Kong <fdkong.jd at gmail.com> wrote:
>
>>
>>
>> On Thu, Jul 26, 2018 at 9:51 AM, Junchao Zhang <jczhang at mcs.anl.gov>
>> wrote:
>>
>>> Hi, Pierre,
>>>   From your log_view files, I see you did strong scaling. You used 4X
>>> more cores, but the execution time only dropped from 3.9143e+04
>>> to 1.6910e+04.
>>>   From my previous analysis of a GAMG weak scaling test, it looks
>>> communication is one of the reasons that caused poor scaling.  In your
>>> case,  VecScatterEnd time was doubled from 1.5575e+03 to 3.2413e+03. Its
>>> time percent jumped from 1% to 17%. This time can contribute to the big
>>> time ratio in MatMultAdd ant MatMultTranspose, misleading you guys thinking
>>> there was load-imbalance computation-wise.
>>>   The reason is that I found in the interpolation and restriction phases
>>> of gamg, the communication pattern is very bad. Few processes communicate
>>> with hundreds of neighbors with message sizes of a few bytes.
>>>
>>
>> We may need to truncate interpolation/restriction operators. Also do some
>> aggressive coarsening.  Unfortunately, GAMG currently does not support.
>>
>
>  Are these gamg options the truncation you thought?
>

> -pc_gamg_threshold[] <thresh,default=0> - Before aggregating the graph
> GAMG will remove small values from the graph on each level
> -pc_gamg_threshold_scale <scale,default=1> - Scaling of threshold on each
> coarser grid if not specified
>

Nope.  Totally different things.

Fande

>
>
>> Fande,
>>
>>
>>> If we can avoid this pattern algorithmically (which I don't know), or
>>> find ways with faster communication (which I am working), then we can get
>>> better scalability.
>>>
>>> --Junchao Zhang
>>>
>>> On Thu, Jul 26, 2018 at 10:02 AM, Pierre Jolivet <
>>> pierre.jolivet at enseeiht.fr> wrote:
>>>
>>>>
>>>>
>>>> > On 26 Jul 2018, at 4:24 PM, Karl Rupp <rupp at iue.tuwien.ac.at> wrote:
>>>> >
>>>> > Hi Pierre,
>>>> >
>>>> >> I’m using GAMG on a shifted Laplacian with these options:
>>>> >> -st_fieldsplit_pressure_ksp_type preonly
>>>> >> -st_fieldsplit_pressure_pc_composite_type additive
>>>> >> -st_fieldsplit_pressure_pc_type composite
>>>> >> -st_fieldsplit_pressure_sub_0_ksp_pc_type jacobi
>>>> >> -st_fieldsplit_pressure_sub_0_pc_type ksp
>>>> >> -st_fieldsplit_pressure_sub_1_ksp_pc_gamg_square_graph 10
>>>> >> -st_fieldsplit_pressure_sub_1_ksp_pc_type gamg
>>>> >> -st_fieldsplit_pressure_sub_1_pc_type ksp
>>>> >> and I end up with the following logs on 512 (top) and 2048 (bottom)
>>>> processes:
>>>> >> MatMult          1577790 1.0 3.1967e+03 1.2 4.48e+12 1.6 7.6e+09
>>>> 5.6e+03 0.0e+00  7 71 75 63  0   7 71 75 63  0 650501
>>>> >> MatMultAdd        204786 1.0 1.3412e+02 5.5 1.50e+10 1.7 5.5e+08
>>>> 2.7e+02 0.0e+00  0  0  5  0  0   0  0  5  0  0 50762
>>>> >> MatMultTranspose  204786 1.0 4.6790e+01 4.3 1.50e+10 1.7 5.5e+08
>>>> 2.7e+02 0.0e+00  0  0  5  0  0   0  0  5  0  0 145505
>>>> >> [..]
>>>> >> KSPSolve_FS_3       7286 1.0 7.5506e+02 1.0 9.14e+11 1.8 7.3e+09
>>>> 1.5e+03 2.6e+05  2 14 71 16 34   2 14 71 16 34 539009
>>>> >> MatMult          1778795 1.0 3.5511e+03 4.1 1.46e+12 1.9 4.0e+10
>>>> 2.4e+03 0.0e+00  7 66 75 61  0   7 66 75 61  0 728371
>>>> >> MatMultAdd        222360 1.0 2.5904e+0348.0 4.31e+09 1.9 2.4e+09
>>>> 1.3e+02 0.0e+00 14  0  4  0  0  14  0  4  0  0  2872
>>>> >> MatMultTranspose  222360 1.0 1.8736e+03421.8 4.31e+09 1.9 2.4e+09
>>>> 1.3e+02 0.0e+00  0  0  4  0  0   0  0  4  0  0  3970
>>>> >> [..]
>>>> >> KSPSolve_FS_3       7412 1.0 2.8939e+03 1.0 2.66e+11 2.1 3.5e+10
>>>> 6.1e+02 2.7e+05 17 11 67 14 28  17 11 67 14 28 148175
>>>> >> MatMultAdd and MatMultTranspose (performed by GAMG) somehow ruin the
>>>> scalability of the overall solver. The pressure space “only” has 3M
>>>> unknowns so I’m guessing that’s why GAMG is having a hard time strong
>>>> scaling.
>>>> >
>>>> > 3M unknowns divided by 512 processes implies less than 10k unknowns
>>>> per process. It is not unusual to see strong scaling roll off at this size.
>>>> Also note that the time per call(!) for "MatMult" is the same for both
>>>> cases, indicating that your run into a latency-limited regime.
>>>> >
>>>> > Also, have a look at the time ratios: With 2048 processes, MatMultAdd
>>>> and MatMultTranspose show a time ratio of 48 and 421, respectively. Maybe
>>>> one of your MPI ranks is getting a huge workload?
>>>>
>>>> Maybe inside GAMG itself (how could I check this?), but since the
>>>> timing and ratio of the MatMult look OK and the distribution of the
>>>> pressure space is the same as the other three fields, I’m guessing this
>>>> does not come from my global Mat, but I may be wrong.
>>>>
>>>> >> For the other fields, the matrix is somehow distributed nicely,
>>>> i.e., I don’t want to change the overall distribution of the matrix.
>>>> >> Do you have any suggestion to improve the performance of GAMG in
>>>> that scenario? I had two ideas in mind but please correct me if I’m wrong
>>>> or if this is not doable:
>>>> >> 1) before setting up GAMG, first use a PCTELESCOPE to avoid having
>>>> too many processes work on this small problem
>>>> >> 2) have the sub_0_ and the sub_1_ work on two different
>>>> nonoverlapping communicators of size PETSC_COMM_WORLD/2, do the solve
>>>> concurrently, and then sum the solutions (only worth doing because of
>>>> -pc_composite_type additive). I have no idea if this easily doable with
>>>> PETSc command line arguments
>>>> >
>>>> > 1) is the more flexible approach, as you have better control over the
>>>> system sizes after 'telescoping’.
>>>>
>>>> Right, but the advantage of 2) is that I wouldn't have one half or more
>>>> of processes idling and I could overlap the solves of both subpc in the
>>>> PCCOMPOSITE.
>>>>
>>>> I’m attaching the -log_view for both runs (I trimmed some options).
>>>>
>>>> Thanks for your help,
>>>> Pierre
>>>>
>>>>
>>>>
>>>> > Best regards,
>>>> > Karli
>>>>
>>>>
>>>>
>>>
>>
>
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