[petsc-users] Bad memory scaling with PETSc 3.10

[Fande Kong]

Thanks for your plots.

The new algorithms should be scalable in terms of the memory usage. I am
puzzled by these plots since the memory usage increases exponentially.  It
may come from somewhere else? How do you measure the memory?  The memory is
for the entire simulation or just PtAP? Could you measure the memory for
PtAP only? Maybe several factors affect the memory usage not only PtAP.

 I will grab some data from my own simulations.

Are you running ex43?

Fande,



On Fri, May 3, 2019 at 8:14 AM Myriam Peyrounette <
myriam.peyrounette at idris.fr> wrote:

> And the attached files... Sorry
>
> Le 05/03/19 à 16:11, Myriam Peyrounette a écrit :
>
> Hi,
>
> I plotted new scalings (memory and time) using the new algorithms. I used
> the options *-options_left true *to make sure that the options are
> effectively used. They are.
>
> I don't have access to the platform I used to run my computations on, so I
> ran them on a different one. In particular, I can't reach problem size =
> 1e8 and the values might be different from the previous scalings I sent
> you. But the comparison of the PETSc versions and options is still
> relevant.
>
> I plotted the scalings of reference: the "good" one (PETSc 3.6.4) in
> green, the "bad" one (PETSc 3.10.2) in blue.
>
> I used the commit d330a26 (3.11.1) for all the other scalings, adding
> different sets of options:
>
> *Light blue* -> -matptap_via
> allatonce  -mat_freeintermediatedatastructures 1
> *Orange* -> -matptap_via allatonce_*merged* -mat_freeintermediatedatastructures
> 1
> *Purple* -> -matptap_via allatonce  -mat_freeintermediatedatastructures 1 *-inner_diag_matmatmult_via
> scalable -inner_offdiag_matmatmult_via scalable*
> *Yellow*: -matptap_via allatonce_*merged* -mat_freeintermediatedatastructures
> 1 *-inner_diag_matmatmult_via scalable -inner_offdiag_matmatmult_via
> scalable*
>
> Conclusion: with regard to memory, the two algorithms imply a similarly
> good improvement of the scaling. The use of the
> -inner_(off)diag_matmatmult_via options is also very interesting. The
> scaling is still not as good as 3.6.4 though.
> With regard to time, I noted a real improvement in time execution! I used
> to spend 200-300s on these executions. Now they take 10-15s. Beside that,
> the "_merged" versions are more efficient. And the
> -inner_(off)diaf_matmatmult_via options are slightly expensive but it is
> not critical.
>
> What do you think? Is it possible to match again the scaling of PETSc
> 3.6.4? Is it worthy keeping investigating?
>
> Myriam
>
>
> Le 04/30/19 à 17:00, Fande Kong a écrit :
>
> HI Myriam,
>
> We are interesting how the new algorithms perform. So there are two new
> algorithms you could try.
>
> Algorithm 1:
>
> -matptap_via allatonce  -mat_freeintermediatedatastructures 1
>
> Algorithm 2:
>
> -matptap_via allatonce_merged -mat_freeintermediatedatastructures 1
>
>
> Note that you need to use the current petsc-master, and also please put
> "-snes_view" in your script so that we can confirm these options are
> actually get set.
>
> Thanks,
>
> Fande,
>
>
> On Tue, Apr 30, 2019 at 2:26 AM Myriam Peyrounette via petsc-users <
> petsc-users at mcs.anl.gov> wrote:
>
>> Hi,
>>
>> that's really good news for us, thanks! I will plot again the memory
>> scaling using these new options and let you know. Next week I hope.
>>
>> Before that, I just need to clarify the situation. Throughout our
>> discussions, we mentionned a number of options concerning the scalability:
>>
>> -matptatp_via scalable
>> -inner_diag_matmatmult_via scalable
>> -inner_diag_matmatmult_via scalable
>> -mat_freeintermediatedatastructures
>> -matptap_via allatonce
>> -matptap_via allatonce_merged
>>
>> Which ones of them are compatible? Should I use all of them at the same
>> time? Is there redundancy?
>>
>> Thanks,
>>
>> Myriam
>>
>> Le 04/25/19 à 21:47, Zhang, Hong a écrit :
>>
>> Myriam:
>> Checking MatPtAP() in petsc-3.6.4, I realized that it uses different
>> algorithm than petsc-10 and later versions. petsc-3.6 uses out-product for
>> C=P^T * AP, while petsc-3.10 uses local transpose of P. petsc-3.10
>> accelerates data accessing, but doubles the memory of P.
>>
>> Fande added two new implementations for MatPtAP() to petsc-master which
>> use much smaller and scalable memories with slightly higher computing time
>> (faster than hypre though). You may use these new implementations if you
>> have concern on memory scalability. The option for these new implementation
>> are:
>> -matptap_via allatonce
>> -matptap_via allatonce_merged
>>
>> Hong
>>
>> On Mon, Apr 15, 2019 at 12:10 PM hzhang at mcs.anl.gov <hzhang at mcs.anl.gov>
>> wrote:
>>
>>> Myriam:
>>> Thank you very much for providing these results!
>>> I have put effort to accelerate execution time and avoid using global
>>> sizes in PtAP, for which the algorithm of transpose of P_local and P_other
>>> likely doubles the memory usage. I'll try to investigate why it becomes
>>> unscalable.
>>> Hong
>>>
>>>> Hi,
>>>>
>>>> you'll find the new scaling attached (green line). I used the version
>>>> 3.11 and the four scalability options :
>>>> -matptap_via scalable
>>>> -inner_diag_matmatmult_via scalable
>>>> -inner_offdiag_matmatmult_via scalable
>>>> -mat_freeintermediatedatastructures
>>>>
>>>> The scaling is much better! The code even uses less memory for the
>>>> smallest cases. There is still an increase for the larger one.
>>>>
>>>> With regard to the time scaling, I used KSPView and LogView on the two
>>>> previous scalings (blue and yellow lines) but not on the last one (green
>>>> line). So we can't really compare them, am I right? However, we can see
>>>> that the new time scaling looks quite good. It slightly increases from ~8s
>>>> to ~27s.
>>>>
>>>> Unfortunately, the computations are expensive so I would like to avoid
>>>> re-run them if possible. How relevant would be a proper time scaling for
>>>> you?
>>>>
>>>> Myriam
>>>>
>>>> Le 04/12/19 à 18:18, Zhang, Hong a écrit :
>>>>
>>>> Myriam :
>>>> Thanks for your effort. It will help us improve PETSc.
>>>> Hong
>>>>
>>>> Hi all,
>>>>>
>>>>> I used the wrong script, that's why it diverged... Sorry about that.
>>>>> I tried again with the right script applied on a tiny problem (~200
>>>>> elements). I can see a small difference in memory usage (gain ~ 1mB).
>>>>> when adding the -mat_freeintermediatestructures option. I still have to
>>>>> execute larger cases to plot the scaling. The supercomputer I am used
>>>>> to
>>>>> run my jobs on is really busy at the moment so it takes a while. I hope
>>>>> I'll send you the results on Monday.
>>>>>
>>>>> Thanks everyone,
>>>>>
>>>>> Myriam
>>>>>
>>>>>
>>>>> Le 04/11/19 à 06:01, Jed Brown a écrit :
>>>>> > "Zhang, Hong" <hzhang at mcs.anl.gov> writes:
>>>>> >
>>>>> >> Jed:
>>>>> >>>> Myriam,
>>>>> >>>> Thanks for the plot. '-mat_freeintermediatedatastructures' should
>>>>> not affect solution. It releases almost half of memory in C=PtAP if C is
>>>>> not reused.
>>>>> >>> And yet if turning it on causes divergence, that would imply a bug.
>>>>> >>> Hong, are you able to reproduce the experiment to see the memory
>>>>> >>> scaling?
>>>>> >> I like to test his code using an alcf machine, but my hands are
>>>>> full now. I'll try it as soon as I find time, hopefully next week.
>>>>> > I have now compiled and run her code locally.
>>>>> >
>>>>> > Myriam, thanks for your last mail adding configuration and removing
>>>>> the
>>>>> > MemManager.h dependency.  I ran with and without
>>>>> > -mat_freeintermediatedatastructures and don't see a difference in
>>>>> > convergence.  What commands did you run to observe that difference?
>>>>>
>>>>> --
>>>>> 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
> --
>
>
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