[petsc-users] Smaller assemble time with increasing processors
Matthew Knepley
knepley at gmail.com
Mon Jul 3 09:03:45 CDT 2023
On Mon, Jul 3, 2023 at 9:56 AM Runfeng Jin <jsfaraway at gmail.com> wrote:
> Hi, impressive performance!
> I use the newest version of petsc(release branch), and it almost deletes
> all assembly and stash time in large processors (assembly time
> 64-4s/128-2s/256-0.2s, stash time all below 2s). For the zero programming
> cost, it really incredible.
> The order code has a regular arrangement of the number of
> nonzero-elements across rows, so I can have a good rough preallocation. And
> from the data, dedicatedly arrange data and roughly acquiring the max
> number of non-zero elements in rows can have a better performance than the
> new version without preallocation. However, in reality, I will use the
> newer version without preallocation for:1)less effort in programming and
> also nearly the same good performance 2) good memory usage(I see no
> unneeded memory after assembly) 3) dedicated preallocation is usually not
> very easy and cause extra time cost.
> Maybe it will be better that leave some space for the user to do a
> slight direction for the preallocation and thus acquire better performance.
> But have no idea how to direct it.
> And I am very curious about how petsc achieves this. How can it not
> know anything but achieve so good performance, and no wasted memory? May
> you have an explanation about this?
>
We use a hash table to store the nonzeros on the fly, and then convert to
packed storage on assembly.
Thanks,
Matt
> assemble time:
> version\processors 4 8 16 32
> 64 128 256
> old 14677s 4694s 1124s 572s
> 38s 8s 2s
> new 50s 28s 15s
> 7.8s 4s 2s 0.4s
> older 27s 24s 19s
> 12s 14s - -
> stash time(max among all processors):
> version\processors 4 8 16 32
> 64 128 256
> old 3145s 2554s 673s 329s
> 201s 142s 138s
> new 2s 1s ~0s
> ~0s ~0s ~0s ~0s
> older 10s 73s 18s 5s
> 1s - -
> old: my poor preallocation
> new: newest version of petsc that do not preallocation
> older: the best preallocation version of my code.
>
>
> Runfeng
>
> Barry Smith <bsmith at petsc.dev> 于2023年7月3日周一 12:19写道：
>
>>
>> The main branch of PETSc now supports filling sparse matrices without
>> providing any preallocation information.
>>
>> You can give it a try. Use your current fastest code but just remove
>> ALL the preallocation calls. I would be interested in what kind of
>> performance you get compared to your best current performance.
>>
>> Barry
>>
>>
>>
>> On Jul 2, 2023, at 11:24 PM, Runfeng Jin <jsfaraway at gmail.com> wrote:
>>
>> Hi! Good advice!
>> I set value with MatSetValues() API, which sets one part of a row at
>> a time(I use a kind of tiling technology so I cannot get all values of a
>> row at a time).
>> I tested the number of malloc in these three cases. The number of
>> mallocs is decreasing with the increase of processors, and all these are
>> very large(the matrix is 283234*283234, as can see in the following). This
>> should be due to the unqualified preallocation. I use a rough
>> preallocation, that every processor counts the number of nonzero elements
>> for the first 10 rows, and uses the largest one to preallocate memory for
>> all local rows. It seems that not work well.
>>
>> number_of_processors number_of_max_mallocs_among_all_processors
>> 64 20000
>> 128 17000
>> 256 11000
>>
>> I change my way to preallocate. I evenly take 100 rows in every local
>> matrix and take the largest one to preallocate memory for all local rows.
>> Now the assemble time is reduced to a very small time.
>>
>> number_of_processors number_of_max_mallocs_among_all_processors
>> 64 3000
>> 128 700
>> 256 500
>>
>> Event Count Time (sec) Flop
>> --- Global ---
>> --- Stage ---- Total
>> Max Ratio Max Ratio Max Ratio Mess
>> AvgLen Reduct %T %F %M %L %R %T %F %M %L %R Mflop/s
>> 64 1 1.0 3.8999e+01 1.0 0.00e+00 0.0
>> 7.1e+03 2.9e+05 1.1e+01 15 0 1 8 3 15 0 1 8
>> 3 0
>>
>> 128 1 1.0 8.5714e+00 1.0 0.00e+00 0.0 2.6e+04
>> 8.1e+04 1.1e+01 5 0 1 4 3 5 0 1 4 3
>> 0
>> 256 1 1.0 2.5512e+00 1.0 0.00e+00 0.0 1.0e+05
>> 2.3e+04 1.1e+01 2 0 1 3 3 2 0 1 3 3
>> 0
>>
>> So the reason "why assemble time is smaller with the increasing number of
>> processors " may be because more processors divide the malloc job so that
>> total time is reduced?
>> If so, I still have some questions:
>> 1. If preallocation is not accurate, will the performance of the
>> assembly be affected? I mean, when processors receive the elements that
>> should be stored in their local by MPI, then will the new mallocs happen
>> at this time point?
>> 2. I can not give an accurate preallocation for the large cost, so is
>> there any better way to preallocate for my situation?
>>
>>
>>
>> Barry Smith <bsmith at petsc.dev> 于2023年7月2日周日 00:16写道：
>>
>>>
>>> I see no reason not to trust the times below, they seem reasonable.
>>> You get more than 2 times speed from 64 to 128 and then about 1.38 from 128
>>> to 256.
>>>
>>> The total amount of data moved (number of messages moved times
>>> average length) goes from 7.0e+03 * 2.8e+05 1.9600e+09 to 2.1060e+09
>>> to 2.3000e+09. A pretty moderate amount of data increase, but note that
>>> each time you double the number of ranks, you also increase substantially
>>> the network's hardware to move data, so one would hope for a good speed up.
>>>
>>> Also, the load balance is very good, near 1. Often with assembly, we
>>> see very out-of-balance, and it is difficult to get good speedup when the
>>> balance is really off.
>>>
>>> It looks like over 90% of the entire run time is coming from setting
>>> and assembling the values? Also the setting values time dominates assembly
>>> time more with more ranks. Are you setting a single value at a time or a
>>> collection of them? How big are the vectors?
>>>
>>> Run all three cases with -info :vec to see some information about how
>>> many mallocs where move to hold the stashed vector entries.
>>>
>>>
>>>
>>>
>>> On Jun 30, 2023, at 10:25 PM, Runfeng Jin <jsfaraway at gmail.com> wrote:
>>>
>>>
>>>
>>> Hi,
>>> Thanks for your reply. I try to use PetscLogEvent(), and the result
>>> shows same conclusion.
>>> What I have done is :
>>> ----------------
>>> PetscLogEvent Mat_assemble_event, Mat_setvalue_event,
>>> Mat_setAsse_event;
>>> PetscClassId classid;
>>> PetscLogDouble user_event_flops;
>>> PetscClassIdRegister("Test assemble and set value", &classid);
>>> PetscLogEventRegister("Test only assemble", classid,
>>> &Mat_assemble_event);
>>> PetscLogEventRegister("Test only set values", classid,
>>> &Mat_setvalue_event);
>>> PetscLogEventRegister("Test both assemble and set values", classid,
>>> &Mat_setAsse_event);
>>> PetscLogEventBegin(Mat_setAsse_event, 0, 0, 0, 0);
>>> PetscLogEventBegin(Mat_setvalue_event, 0, 0, 0, 0);
>>> ...compute elements and use MatSetValues. No call for assembly
>>> PetscLogEventEnd(Mat_setvalue_event, 0, 0, 0, 0);
>>>
>>> PetscLogEventBegin(Mat_assemble_event, 0, 0, 0, 0);
>>> MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY);
>>> MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY);
>>> PetscLogEventEnd(Mat_assemble_event, 0, 0, 0, 0);
>>> PetscLogEventEnd(Mat_setAsse_event, 0, 0, 0, 0);
>>> ----------------
>>>
>>> And the output as follows. By the way, dose petsc recorde all time
>>> between PetscLogEventBegin and PetscLogEventEnd? or just test the time of
>>> petsc API?
>>>
>>>
>>> It is all of the time.
>>>
>>> ----------------
>>> Event Count Time (sec) Flop
>>> --- Global --- --- Stage ---- Total
>>> Max Ratio *Max* Ratio Max Ratio Mess
>>> AvgLen Reduct %T %F %M %L %R %T %F %M %L %R Mflop/s
>>> 64new 1 1.0 *2.3775e+02* 1.0 0.00e+00 0.0 6.2e+03 2.3e+04
>>> 9.0e+00 52 0 1 1 2 52 0 1 1 2 0
>>> 128new 1 1.0* 6.9945e+01* 1.0 0.00e+00 0.0 2.5e+04 1.1e+04
>>> 9.0e+00 30 0 1 1 2 30 0 1 1 2 0
>>> 256new 1 1.0 *1.7445e+01* 1.0 0.00e+00 0.0 9.9e+04 5.2e+03
>>> 9.0e+00 10 0 1 1 2 10 0 1 1 2 0
>>>
>>> 64:
>>> only assemble 1 1.0 *2.6596e+02 *1.0 0.00e+00 0.0 7.0e+03 2.8e+05
>>> 1.1e+01 55 0 1 8 3 55 0 1 8 3 0
>>> only setvalues 1 1.0 *1.9987e+02* 1.0 0.00e+00 0.0 0.0e+00 0.0e+00
>>> 0.0e+00 41 0 0 0 0 41 0 0 0 0 0
>>> Test both 1 1.0 4.*6580e+02* 1.0 0.00e+00 0.0 7.0e+03 2.8e+05
>>> 1.5e+01 96 0 1 8 4 96 0 1 8 4 0
>>>
>>> 128:
>>> only assemble 1 1.0 *6.9718e+01* 1.0 0.00e+00 0.0 2.6e+04 8.1e+04
>>> 1.1e+01 30 0 1 4 3 30 0 1 4 3 0
>>> only setvalues 1 1.0 *1.4438e+02* 1.1 0.00e+00 0.0 0.0e+00 0.0e+00
>>> 0.0e+00 60 0 0 0 0 60 0 0 0 0 0
>>> Test both 1 1.0 *2.1417e+02* 1.0 0.00e+00 0.0 2.6e+04 8.1e+04
>>> 1.5e+01 91 0 1 4 4 91 0 1 4 4 0
>>>
>>> 256:
>>> only assemble 1 1.0 *1.7482e+01* 1.0 0.00e+00 0.0 1.0e+05 2.3e+04
>>> 1.1e+01 10 0 1 3 3 10 0 1 3 3 0
>>> only setvalues 1 1.0 *1.3717e+02* 1.1 0.00e+00 0.0 0.0e+00 0.0e+00
>>> 0.0e+00 78 0 0 0 0 78 0 0 0 0 0
>>> Test both 1 1.0 *1.5475e+02* 1.0 0.00e+00 0.0 1.0e+05 2.3e+04
>>> 1.5e+01 91 0 1 3 4 91 0 1 3 4 0
>>>
>>>
>>>
>>> Runfeng
>>>
>>> Barry Smith <bsmith at petsc.dev> 于2023年6月30日周五 23:35写道：
>>>
>>>>
>>>> You cannot look just at the VecAssemblyEnd() time, that will very
>>>> likely give the wrong impression of the total time it takes to put the
>>>> values in.
>>>>
>>>> You need to register a new Event and put a PetscLogEvent() just
>>>> before you start generating the vector entries and calling VecSetValues()
>>>> and put the PetscLogEventEnd() just after the VecAssemblyEnd() this is the
>>>> only way to get an accurate accounting of the time.
>>>>
>>>> Barry
>>>>
>>>>
>>>> > On Jun 30, 2023, at 11:21 AM, Runfeng Jin <jsfaraway at gmail.com>
>>>> wrote:
>>>> >
>>>> > Hello!
>>>> >
>>>> > When I use PETSc build a sbaij matrix, I find a strange thing. When I
>>>> increase the number of processors, the assemble time become smaller. All
>>>> these are totally same matrix. The assemble time mainly arouse from message
>>>> passing, which because I use dynamic workload that it is random for which
>>>> elements are computed by which processor.
>>>> > But from instinct, if use more processors, then more possible that
>>>> the processor computes elements storing in other processors. But from the
>>>> output of log_view, It seems when use more processors, the processors
>>>> compute more elements storing in its local(infer from that, with more
>>>> processors, less total amount of passed messages).
>>>> >
>>>> > What could cause this happened? Thank you!
>>>> >
>>>> >
>>>> > Following is the output of log_view for 64\128\256 processors. Every
>>>> row is time profiler of VecAssemblyEnd.
>>>> >
>>>> >
>>>> ------------------------------------------------------------------------------------------------------------------------
>>>> > processors Count Time (sec)
>>>> Flop
>>>> --- Global --- ---
>>>> Stage ---- Total
>>>> > Max Ratio Max
>>>> Ratio Max Ratio Mess AvgLen Reduct
>>>> %T %F %M %L %R %T %F %M %L %R Mflop/s
>>>> > 64 1 1.0 2.3775e+02
>>>> 1.0 0.00e+00 0.0 6.2e+03 2.3e+04 9.0e+00
>>>> 52 0 1 1 2 52 0 1 1 2
>>>> 0
>>>> > 128 1 1.0 6.9945e+01
>>>> 1.0 0.00e+00 0.0 2.5e+04 1.1e+04 9.0e+00
>>>> 30 0 1 1 2 30 0 1 1 2
>>>> 0
>>>> > 256 1 1.0 1.7445e+01
>>>> 1.0 0.00e+00 0.0 9.9e+04 5.2e+03 9.0e+00
>>>> 10 0 1 1 2 10 0 1 1 2
>>>> 0
>>>> >
>>>> > Runfeng Jin
>>>>
>>>>
>>>
>>
--
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/~knepley/>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://lists.mcs.anl.gov/pipermail/petsc-users/attachments/20230703/ddb188e3/attachment-0001.html>
More information about the petsc-users
mailing list