[petsc-users] Bad memory scaling with PETSc 3.10
Dave May
dave.mayhem23 at gmail.com
Tue Mar 26 05:55:40 CDT 2019
On Tue, 26 Mar 2019 at 10:36, Myriam Peyrounette <
myriam.peyrounette at idris.fr> wrote:
> Oh you were right, the three options are unsused (-matptap_via scalable,
> -inner_offdiag_matmatmult_via scalable and -inner_diag_matmatmult_via
> scalable). Does this mean I am not using the associated PtAP functions?
>
No - not necessarily. All it means is the options were not parsed.
If your matrices have an option prefix associated with them (e.g. abc) ,
then you need to provide the option as
-abc_matptap_via scalable
If you are not sure if you matrices have a prefix, look at the result of
-ksp_view (see below for an example)
Mat Object: 2 MPI processes
type: mpiaij
rows=363, cols=363, bs=3
total: nonzeros=8649, allocated nonzeros=8649
total number of mallocs used during MatSetValues calls =0
Mat Object: (B_) 2 MPI processes
type: mpiaij
rows=363, cols=363, bs=3
total: nonzeros=8649, allocated nonzeros=8649
total number of mallocs used during MatSetValues calls =0
The first matrix has no options prefix, but the second does and it's called
"B_".
> Myriam
>
> Le 03/26/19 à 11:10, Dave May a écrit :
>
>
> On Tue, 26 Mar 2019 at 09:52, Myriam Peyrounette via petsc-users <
> petsc-users at mcs.anl.gov> wrote:
>
>> How can I be sure they are indeed used? Can I print this information in
>> some log file?
>>
> Yes. Re-run the job with the command line option
>
> -options_left true
>
> This will report all options parsed, and importantly, will also indicate
> if any options were unused.
>
>
> Thanks
> Dave
>
> Thanks in advance
>>
>> Myriam
>>
>> Le 03/25/19 à 18:24, Matthew Knepley a écrit :
>>
>> On Mon, Mar 25, 2019 at 10:54 AM Myriam Peyrounette via petsc-users <
>> petsc-users at mcs.anl.gov> wrote:
>>
>>> Hi,
>>>
>>> thanks for the explanations. I tried the last PETSc version (commit
>>> fbc5705bc518d02a4999f188aad4ccff5f754cbf), which includes the patch you
>>> talked about. But the memory scaling shows no improvement (see scaling
>>> attached), even when using the "scalable" options :(
>>>
>>> I had a look at the PETSc functions MatPtAPNumeric_MPIAIJ_MPIAIJ and
>>> MatPtAPSymbolic_MPIAIJ_MPIAIJ (especially at the differences before and
>>> after the first "bad" commit), but I can't find what induced this memory
>>> issue.
>>>
>> Are you sure that the option was used? It just looks suspicious to me
>> that they use exactly the same amount of memory. It should be different,
>> even if it does not solve the problem.
>>
>> Thanks,
>>
>> Matt
>>
>>> Myriam
>>>
>>>
>>>
>>>
>>> Le 03/20/19 à 17:38, Fande Kong a écrit :
>>>
>>> Hi Myriam,
>>>
>>> There are three algorithms in PETSc to do PtAP ( const char
>>> *algTypes[3] = {"scalable","nonscalable","hypre"};), and can be specified
>>> using the petsc options: -matptap_via xxxx.
>>>
>>> (1) -matptap_via hypre: This call the hypre package to do the PtAP
>>> trough an all-at-once triple product. In our experiences, it is the most
>>> memory efficient, but could be slow.
>>>
>>> (2) -matptap_via scalable: This involves a row-wise algorithm plus an
>>> outer product. This will use more memory than hypre, but way faster. This
>>> used to have a bug that could take all your memory, and I have a fix at
>>> https://bitbucket.org/petsc/petsc/pull-requests/1452/mpiptap-enable-large-scale-simulations/diff.
>>> When using this option, we may want to have extra options such as
>>> -inner_offdiag_matmatmult_via scalable -inner_diag_matmatmult_via
>>> scalable to select inner scalable algorithms.
>>>
>>> (3) -matptap_via nonscalable: Suppose to be even faster, but use more
>>> memory. It does dense matrix operations.
>>>
>>>
>>> Thanks,
>>>
>>> Fande Kong
>>>
>>>
>>>
>>>
>>> On Wed, Mar 20, 2019 at 10:06 AM Myriam Peyrounette via petsc-users <
>>> petsc-users at mcs.anl.gov> wrote:
>>>
>>>> More precisely: something happens when upgrading the functions
>>>> MatPtAPNumeric_MPIAIJ_MPIAIJ and/or MatPtAPSymbolic_MPIAIJ_MPIAIJ.
>>>>
>>>> Unfortunately, there are a lot of differences between the old and new
>>>> versions of these functions. I keep investigating but if you have any idea,
>>>> please let me know.
>>>>
>>>> Best,
>>>>
>>>> Myriam
>>>>
>>>> Le 03/20/19 à 13:48, Myriam Peyrounette a écrit :
>>>>
>>>> Hi all,
>>>>
>>>> I used git bisect to determine when the memory need increased. I found
>>>> that the first "bad" commit is aa690a28a7284adb519c28cb44eae20a2c131c85.
>>>>
>>>> Barry was right, this commit seems to be about an evolution of MatPtAPSymbolic_MPIAIJ_MPIAIJ.
>>>> You mentioned the option "-matptap_via scalable" but I can't find any
>>>> information about it. Can you tell me more?
>>>>
>>>> Thanks
>>>>
>>>> Myriam
>>>>
>>>>
>>>> Le 03/11/19 à 14:40, Mark Adams a écrit :
>>>>
>>>> Is there a difference in memory usage on your tiny problem? I assume
>>>> no.
>>>>
>>>> I don't see anything that could come from GAMG other than the RAP stuff
>>>> that you have discussed already.
>>>>
>>>> On Mon, Mar 11, 2019 at 9:32 AM Myriam Peyrounette <
>>>> myriam.peyrounette at idris.fr> wrote:
>>>>
>>>>> The code I am using here is the example 42 of PETSc (
>>>>> https://www.mcs.anl.gov/petsc/petsc-3.9/src/ksp/ksp/examples/tutorials/ex42.c.html).
>>>>> Indeed it solves the Stokes equation. I thought it was a good idea to use
>>>>> an example you might know (and didn't find any that uses GAMG functions). I
>>>>> just changed the PCMG setup so that the memory problem appears. And it
>>>>> appears when adding PCGAMG.
>>>>>
>>>>> I don't care about the performance or even the result rightness here,
>>>>> but only about the difference in memory use between 3.6 and 3.10. Do you
>>>>> think finding a more adapted script would help?
>>>>>
>>>>> I used the threshold of 0.1 only once, at the beginning, to test its
>>>>> influence. I used the default threshold (of 0, I guess) for all the other
>>>>> runs.
>>>>>
>>>>> Myriam
>>>>>
>>>>> Le 03/11/19 à 13:52, Mark Adams a écrit :
>>>>>
>>>>> In looking at this larger scale run ...
>>>>>
>>>>> * Your eigen estimates are much lower than your tiny test problem.
>>>>> But this is Stokes apparently and it should not work anyway. Maybe you have
>>>>> a small time step that adds a lot of mass that brings the eigen estimates
>>>>> down. And your min eigenvalue (not used) is positive. I would expect
>>>>> negative for Stokes ...
>>>>>
>>>>> * You seem to be setting a threshold value of 0.1 -- that is very high
>>>>>
>>>>> * v3.6 says "using nonzero initial guess" but this is not in v3.10.
>>>>> Maybe we just stopped printing that.
>>>>>
>>>>> * There were some changes to coasening parameters in going from v3.6
>>>>> but it does not look like your problem was effected. (The coarsening algo
>>>>> is non-deterministic by default and you can see small difference on
>>>>> different runs)
>>>>>
>>>>> * We may have also added a "noisy" RHS for eigen estimates by default
>>>>> from v3.6.
>>>>>
>>>>> * And for non-symetric problems you can try -pc_gamg_agg_nsmooths 0,
>>>>> but again GAMG is not built for Stokes anyway.
>>>>>
>>>>>
>>>>> On Tue, Mar 5, 2019 at 11:53 AM Myriam Peyrounette <
>>>>> myriam.peyrounette at idris.fr> wrote:
>>>>>
>>>>>> I used PCView to display the size of the linear system in each level
>>>>>> of the MG. You'll find the outputs attached to this mail (zip file) for
>>>>>> both the default threshold value and a value of 0.1, and for both 3.6 and
>>>>>> 3.10 PETSc versions.
>>>>>>
>>>>>> For convenience, I summarized the information in a graph, also
>>>>>> attached (png file).
>>>>>>
>>>>>> As you can see, there are slight differences between the two versions
>>>>>> but none is critical, in my opinion. Do you see anything suspicious in the
>>>>>> outputs?
>>>>>>
>>>>>> + I can't find the default threshold value. Do you know where I can
>>>>>> find it?
>>>>>>
>>>>>> Thanks for the follow-up
>>>>>>
>>>>>> Myriam
>>>>>>
>>>>>> Le 03/05/19 à 14:06, Matthew Knepley a écrit :
>>>>>>
>>>>>> On Tue, Mar 5, 2019 at 7:14 AM Myriam Peyrounette <
>>>>>> myriam.peyrounette at idris.fr> wrote:
>>>>>>
>>>>>>> Hi Matt,
>>>>>>>
>>>>>>> I plotted the memory scalings using different threshold values. The
>>>>>>> two scalings are slightly translated (from -22 to -88 mB) but this gain is
>>>>>>> neglectable. The 3.6-scaling keeps being robust while the 3.10-scaling
>>>>>>> deteriorates.
>>>>>>>
>>>>>>> Do you have any other suggestion?
>>>>>>>
>>>>>> Mark, what is the option she can give to output all the GAMG data?
>>>>>>
>>>>>> Also, run using -ksp_view. GAMG will report all the sizes of its
>>>>>> grids, so it should be easy to see
>>>>>> if the coarse grid sizes are increasing, and also what the effect of
>>>>>> the threshold value is.
>>>>>>
>>>>>> Thanks,
>>>>>>
>>>>>> Matt
>>>>>>
>>>>>>> Thanks
>>>>>>> Myriam
>>>>>>>
>>>>>>> Le 03/02/19 à 02:27, Matthew Knepley a écrit :
>>>>>>>
>>>>>>> On Fri, Mar 1, 2019 at 10:53 AM Myriam Peyrounette via petsc-users <
>>>>>>> petsc-users at mcs.anl.gov> wrote:
>>>>>>>
>>>>>>>> Hi,
>>>>>>>>
>>>>>>>> I used to run my code with PETSc 3.6. Since I upgraded the PETSc
>>>>>>>> version
>>>>>>>> to 3.10, this code has a bad memory scaling.
>>>>>>>>
>>>>>>>> To report this issue, I took the PETSc script ex42.c and slightly
>>>>>>>> modified it so that the KSP and PC configurations are the same as
>>>>>>>> in my
>>>>>>>> code. In particular, I use a "personnalised" multi-grid method. The
>>>>>>>> modifications are indicated by the keyword "TopBridge" in the
>>>>>>>> attached
>>>>>>>> scripts.
>>>>>>>>
>>>>>>>> To plot the memory (weak) scaling, I ran four calculations for each
>>>>>>>> script with increasing problem sizes and computations cores:
>>>>>>>>
>>>>>>>> 1. 100,000 elts on 4 cores
>>>>>>>> 2. 1 million elts on 40 cores
>>>>>>>> 3. 10 millions elts on 400 cores
>>>>>>>> 4. 100 millions elts on 4,000 cores
>>>>>>>>
>>>>>>>> The resulting graph is also attached. The scaling using PETSc 3.10
>>>>>>>> clearly deteriorates for large cases, while the one using PETSc 3.6
>>>>>>>> is
>>>>>>>> robust.
>>>>>>>>
>>>>>>>> After a few tests, I found that the scaling is mostly sensitive to
>>>>>>>> the
>>>>>>>> use of the AMG method for the coarse grid (line 1780 in
>>>>>>>> main_ex42_petsc36.cc). In particular, the performance strongly
>>>>>>>> deteriorates when commenting lines 1777 to 1790 (in
>>>>>>>> main_ex42_petsc36.cc).
>>>>>>>>
>>>>>>>> Do you have any idea of what changed between version 3.6 and version
>>>>>>>> 3.10 that may imply such degradation?
>>>>>>>>
>>>>>>>
>>>>>>> I believe the default values for PCGAMG changed between versions. It
>>>>>>> sounds like the coarsening rate
>>>>>>> is not great enough, so that these grids are too large. This can be
>>>>>>> set using:
>>>>>>>
>>>>>>>
>>>>>>> https://www.mcs.anl.gov/petsc/petsc-current/docs/manualpages/PC/PCGAMGSetThreshold.html
>>>>>>>
>>>>>>> There is some explanation of this effect on that page. Let us know
>>>>>>> if setting this does not correct the situation.
>>>>>>>
>>>>>>> Thanks,
>>>>>>>
>>>>>>> Matt
>>>>>>>
>>>>>>>
>>>>>>>> Let me know if you need further information.
>>>>>>>>
>>>>>>>> Best,
>>>>>>>>
>>>>>>>> Myriam Peyrounette
>>>>>>>>
>>>>>>>>
>>>>>>>> --
>>>>>>>> Myriam Peyrounette
>>>>>>>> CNRS/IDRIS - HLST
>>>>>>>> --
>>>>>>>>
>>>>>>>>
>>>>>>>
>>>>>>> --
>>>>>>> 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/%7Eknepley/>
>>>>>>>
>>>>>>>
>>>>>>> --
>>>>>>> Myriam Peyrounette
>>>>>>> CNRS/IDRIS - HLST
>>>>>>> --
>>>>>>>
>>>>>>>
>>>>>>
>>>>>> --
>>>>>> 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/%7Eknepley/>
>>>>>>
>>>>>>
>>>>>> --
>>>>>> Myriam Peyrounette
>>>>>> CNRS/IDRIS - HLST
>>>>>> --
>>>>>>
>>>>>>
>>>>> --
>>>>> Myriam Peyrounette
>>>>> CNRS/IDRIS - HLST
>>>>> --
>>>>>
>>>>>
>>>> --
>>>> Myriam Peyrounette
>>>> CNRS/IDRIS - HLST
>>>> --
>>>>
>>>>
>>>> --
>>>> Myriam Peyrounette
>>>> CNRS/IDRIS - HLST
>>>> --
>>>>
>>>>
>>> --
>>> Myriam Peyrounette
>>> CNRS/IDRIS - HLST
>>> --
>>>
>>>
>>
>> --
>> 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/%7Eknepley/>
>>
>>
>> --
>> Myriam Peyrounette
>> CNRS/IDRIS - HLST
>> --
>>
>>
> --
> Myriam Peyrounette
> CNRS/IDRIS - HLST
> --
>
>
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