[petsc-users] Question about memory usage in Multigrid preconditioner
Dave May
dave.mayhem23 at gmail.com
Wed Sep 14 23:05:48 CDT 2016
On Thursday, 15 September 2016, Dave May <dave.mayhem23 at gmail.com> wrote:
>
>
> On Thursday, 15 September 2016, frank <hengjiew at uci.edu
> <javascript:_e(%7B%7D,'cvml','hengjiew at uci.edu');>> wrote:
>
>> Hi,
>>
>> I write a simple code to re-produce the error. I hope this can help to
>> diagnose the problem.
>> The code just solves a 3d poisson equation.
>>
>
> Why is the stencil width a runtime parameter?? And why is the default
> value 2? For 7-pnt FD Laplace, you only need a stencil width of 1.
>
> Was this choice made to mimic something in the real application code?
>
Please ignore - I misunderstood your usage of the param set by -P
>
>
>>
>> I run the code on a 1024^3 mesh. The process partition is 32 * 32 * 32.
>> That's when I re-produce the OOM error. Each core has about 2G memory.
>> I also run the code on a 512^3 mesh with 16 * 16 * 16 processes. The ksp
>> solver works fine.
>> I attached the code, ksp_view_pre's output and my petsc option file.
>>
>> Thank you.
>> Frank
>>
>> On 09/09/2016 06:38 PM, Hengjie Wang wrote:
>>
>> Hi Barry,
>>
>> I checked. On the supercomputer, I had the option "-ksp_view_pre" but it
>> is not in file I sent you. I am sorry for the confusion.
>>
>> Regards,
>> Frank
>>
>> On Friday, September 9, 2016, Barry Smith <bsmith at mcs.anl.gov> wrote:
>>
>>>
>>> > On Sep 9, 2016, at 3:11 PM, frank <hengjiew at uci.edu> wrote:
>>> >
>>> > Hi Barry,
>>> >
>>> > I think the first KSP view output is from -ksp_view_pre. Before I
>>> submitted the test, I was not sure whether there would be OOM error or not.
>>> So I added both -ksp_view_pre and -ksp_view.
>>>
>>> But the options file you sent specifically does NOT list the
>>> -ksp_view_pre so how could it be from that?
>>>
>>> Sorry to be pedantic but I've spent too much time in the past trying
>>> to debug from incorrect information and want to make sure that the
>>> information I have is correct before thinking. Please recheck exactly what
>>> happened. Rerun with the exact input file you emailed if that is needed.
>>>
>>> Barry
>>>
>>> >
>>> > Frank
>>> >
>>> >
>>> > On 09/09/2016 12:38 PM, Barry Smith wrote:
>>> >> Why does ksp_view2.txt have two KSP views in it while ksp_view1.txt
>>> has only one KSPView in it? Did you run two different solves in the 2 case
>>> but not the one?
>>> >>
>>> >> Barry
>>> >>
>>> >>
>>> >>
>>> >>> On Sep 9, 2016, at 10:56 AM, frank <hengjiew at uci.edu> wrote:
>>> >>>
>>> >>> Hi,
>>> >>>
>>> >>> I want to continue digging into the memory problem here.
>>> >>> I did find a work around in the past, which is to use less cores per
>>> node so that each core has 8G memory. However this is deficient and
>>> expensive. I hope to locate the place that uses the most memory.
>>> >>>
>>> >>> Here is a brief summary of the tests I did in past:
>>> >>>> Test1: Mesh 1536*128*384 | Process Mesh 48*4*12
>>> >>> Maximum (over computational time) process memory: total
>>> 7.0727e+08
>>> >>> Current process memory:
>>> total 7.0727e+08
>>> >>> Maximum (over computational time) space PetscMalloc()ed: total
>>> 6.3908e+11
>>> >>> Current space PetscMalloc()ed:
>>> total 1.8275e+09
>>> >>>
>>> >>>> Test2: Mesh 1536*128*384 | Process Mesh 96*8*24
>>> >>> Maximum (over computational time) process memory: total
>>> 5.9431e+09
>>> >>> Current process memory:
>>> total 5.9431e+09
>>> >>> Maximum (over computational time) space PetscMalloc()ed: total
>>> 5.3202e+12
>>> >>> Current space PetscMalloc()ed:
>>> total 5.4844e+09
>>> >>>
>>> >>>> Test3: Mesh 3072*256*768 | Process Mesh 96*8*24
>>> >>> OOM( Out Of Memory ) killer of the supercomputer terminated the
>>> job during "KSPSolve".
>>> >>>
>>> >>> I attached the output of ksp_view( the third test's output is from
>>> ksp_view_pre ), memory_view and also the petsc options.
>>> >>>
>>> >>> In all the tests, each core can access about 2G memory. In test3,
>>> there are 4223139840 non-zeros in the matrix. This will consume about
>>> 1.74M, using double precision. Considering some extra memory used to store
>>> integer index, 2G memory should still be way enough.
>>> >>>
>>> >>> Is there a way to find out which part of KSPSolve uses the most
>>> memory?
>>> >>> Thank you so much.
>>> >>>
>>> >>> BTW, there are 4 options remains unused and I don't understand why
>>> they are omitted:
>>> >>> -mg_coarse_telescope_mg_coarse_ksp_type value: preonly
>>> >>> -mg_coarse_telescope_mg_coarse_pc_type value: bjacobi
>>> >>> -mg_coarse_telescope_mg_levels_ksp_max_it value: 1
>>> >>> -mg_coarse_telescope_mg_levels_ksp_type value: richardson
>>> >>>
>>> >>>
>>> >>> Regards,
>>> >>> Frank
>>> >>>
>>> >>> On 07/13/2016 05:47 PM, Dave May wrote:
>>> >>>>
>>> >>>> On 14 July 2016 at 01:07, frank <hengjiew at uci.edu> wrote:
>>> >>>> Hi Dave,
>>> >>>>
>>> >>>> Sorry for the late reply.
>>> >>>> Thank you so much for your detailed reply.
>>> >>>>
>>> >>>> I have a question about the estimation of the memory usage. There
>>> are 4223139840 allocated non-zeros and 18432 MPI processes. Double
>>> precision is used. So the memory per process is:
>>> >>>> 4223139840 * 8bytes / 18432 / 1024 / 1024 = 1.74M ?
>>> >>>> Did I do sth wrong here? Because this seems too small.
>>> >>>>
>>> >>>> No - I totally f***ed it up. You are correct. That'll teach me for
>>> fumbling around with my iphone calculator and not using my brain. (Note
>>> that to convert to MB just divide by 1e6, not 1024^2 - although I
>>> apparently cannot convert between units correctly....)
>>> >>>>
>>> >>>> From the PETSc objects associated with the solver, It looks like it
>>> _should_ run with 2GB per MPI rank. Sorry for my mistake. Possibilities
>>> are: somewhere in your usage of PETSc you've introduced a memory leak;
>>> PETSc is doing a huge over allocation (e.g. as per our discussion of
>>> MatPtAP); or in your application code there are other objects you have
>>> forgotten to log the memory for.
>>> >>>>
>>> >>>>
>>> >>>>
>>> >>>> I am running this job on Bluewater
>>> >>>> I am using the 7 points FD stencil in 3D.
>>> >>>>
>>> >>>> I thought so on both counts.
>>> >>>>
>>> >>>> I apologize that I made a stupid mistake in computing the memory
>>> per core. My settings render each core can access only 2G memory on average
>>> instead of 8G which I mentioned in previous email. I re-run the job with 8G
>>> memory per core on average and there is no "Out Of Memory" error. I would
>>> do more test to see if there is still some memory issue.
>>> >>>>
>>> >>>> Ok. I'd still like to know where the memory was being used since my
>>> estimates were off.
>>> >>>>
>>> >>>>
>>> >>>> Thanks,
>>> >>>> Dave
>>> >>>>
>>> >>>> Regards,
>>> >>>> Frank
>>> >>>>
>>> >>>>
>>> >>>>
>>> >>>> On 07/11/2016 01:18 PM, Dave May wrote:
>>> >>>>> Hi Frank,
>>> >>>>>
>>> >>>>>
>>> >>>>> On 11 July 2016 at 19:14, frank <hengjiew at uci.edu> wrote:
>>> >>>>> Hi Dave,
>>> >>>>>
>>> >>>>> I re-run the test using bjacobi as the preconditioner on the
>>> coarse mesh of telescope. The Grid is 3072*256*768 and process mesh is
>>> 96*8*24. The petsc option file is attached.
>>> >>>>> I still got the "Out Of Memory" error. The error occurred before
>>> the linear solver finished one step. So I don't have the full info from
>>> ksp_view. The info from ksp_view_pre is attached.
>>> >>>>>
>>> >>>>> Okay - that is essentially useless (sorry)
>>> >>>>>
>>> >>>>> It seems to me that the error occurred when the decomposition was
>>> going to be changed.
>>> >>>>>
>>> >>>>> Based on what information?
>>> >>>>> Running with -info would give us more clues, but will create a ton
>>> of output.
>>> >>>>> Please try running the case which failed with -info
>>> >>>>> I had another test with a grid of 1536*128*384 and the same
>>> process mesh as above. There was no error. The ksp_view info is attached
>>> for comparison.
>>> >>>>> Thank you.
>>> >>>>>
>>> >>>>>
>>> >>>>> [3] Here is my crude estimate of your memory usage.
>>> >>>>> I'll target the biggest memory hogs only to get an order of
>>> magnitude estimate
>>> >>>>>
>>> >>>>> * The Fine grid operator contains 4223139840 non-zeros --> 1.8 GB
>>> per MPI rank assuming double precision.
>>> >>>>> The indices for the AIJ could amount to another 0.3 GB (assuming
>>> 32 bit integers)
>>> >>>>>
>>> >>>>> * You use 5 levels of coarsening, so the other operators should
>>> represent (collectively)
>>> >>>>> 2.1 / 8 + 2.1/8^2 + 2.1/8^3 + 2.1/8^4 ~ 300 MB per MPI rank on
>>> the communicator with 18432 ranks.
>>> >>>>> The coarse grid should consume ~ 0.5 MB per MPI rank on the
>>> communicator with 18432 ranks.
>>> >>>>>
>>> >>>>> * You use a reduction factor of 64, making the new communicator
>>> with 288 MPI ranks.
>>> >>>>> PCTelescope will first gather a temporary matrix associated with
>>> your coarse level operator assuming a comm size of 288 living on the comm
>>> with size 18432.
>>> >>>>> This matrix will require approximately 0.5 * 64 = 32 MB per core
>>> on the 288 ranks.
>>> >>>>> This matrix is then used to form a new MPIAIJ matrix on the
>>> subcomm, thus require another 32 MB per rank.
>>> >>>>> The temporary matrix is now destroyed.
>>> >>>>>
>>> >>>>> * Because a DMDA is detected, a permutation matrix is assembled.
>>> >>>>> This requires 2 doubles per point in the DMDA.
>>> >>>>> Your coarse DMDA contains 92 x 16 x 48 points.
>>> >>>>> Thus the permutation matrix will require < 1 MB per MPI rank on
>>> the sub-comm.
>>> >>>>>
>>> >>>>> * Lastly, the matrix is permuted. This uses MatPtAP(), but the
>>> resulting operator will have the same memory footprint as the unpermuted
>>> matrix (32 MB). At any stage in PCTelescope, only 2 operators of size 32 MB
>>> are held in memory when the DMDA is provided.
>>> >>>>>
>>> >>>>> From my rough estimates, the worst case memory foot print for any
>>> given core, given your options is approximately
>>> >>>>> 2100 MB + 300 MB + 32 MB + 32 MB + 1 MB = 2465 MB
>>> >>>>> This is way below 8 GB.
>>> >>>>>
>>> >>>>> Note this estimate completely ignores:
>>> >>>>> (1) the memory required for the restriction operator,
>>> >>>>> (2) the potential growth in the number of non-zeros per row due to
>>> Galerkin coarsening (I wished -ksp_view_pre reported the output from
>>> MatView so we could see the number of non-zeros required by the coarse
>>> level operators)
>>> >>>>> (3) all temporary vectors required by the CG solver, and those
>>> required by the smoothers.
>>> >>>>> (4) internal memory allocated by MatPtAP
>>> >>>>> (5) memory associated with IS's used within PCTelescope
>>> >>>>>
>>> >>>>> So either I am completely off in my estimates, or you have not
>>> carefully estimated the memory usage of your application code. Hopefully
>>> others might examine/correct my rough estimates
>>> >>>>>
>>> >>>>> Since I don't have your code I cannot access the latter.
>>> >>>>> Since I don't have access to the same machine you are running on,
>>> I think we need to take a step back.
>>> >>>>>
>>> >>>>> [1] What machine are you running on? Send me a URL if its available
>>> >>>>>
>>> >>>>> [2] What discretization are you using? (I am guessing a scalar 7
>>> point FD stencil)
>>> >>>>> If it's a 7 point FD stencil, we should be able to examine the
>>> memory usage of your solver configuration using a standard, light weight
>>> existing PETSc example, run on your machine at the same scale.
>>> >>>>> This would hopefully enable us to correctly evaluate the actual
>>> memory usage required by the solver configuration you are using.
>>> >>>>>
>>> >>>>> Thanks,
>>> >>>>> Dave
>>> >>>>>
>>> >>>>>
>>> >>>>> Frank
>>> >>>>>
>>> >>>>>
>>> >>>>>
>>> >>>>>
>>> >>>>> On 07/08/2016 10:38 PM, Dave May wrote:
>>> >>>>>>
>>> >>>>>> On Saturday, 9 July 2016, frank <hengjiew at uci.edu> wrote:
>>> >>>>>> Hi Barry and Dave,
>>> >>>>>>
>>> >>>>>> Thank both of you for the advice.
>>> >>>>>>
>>> >>>>>> @Barry
>>> >>>>>> I made a mistake in the file names in last email. I attached the
>>> correct files this time.
>>> >>>>>> For all the three tests, 'Telescope' is used as the coarse
>>> preconditioner.
>>> >>>>>>
>>> >>>>>> == Test1: Grid: 1536*128*384, Process Mesh: 48*4*12
>>> >>>>>> Part of the memory usage: Vector 125 124 3971904
>>> 0.
>>> >>>>>> Matrix 101 101
>>> 9462372 0
>>> >>>>>>
>>> >>>>>> == Test2: Grid: 1536*128*384, Process Mesh: 96*8*24
>>> >>>>>> Part of the memory usage: Vector 125 124 681672
>>> 0.
>>> >>>>>> Matrix 101 101
>>> 1462180 0.
>>> >>>>>>
>>> >>>>>> In theory, the memory usage in Test1 should be 8 times of Test2.
>>> In my case, it is about 6 times.
>>> >>>>>>
>>> >>>>>> == Test3: Grid: 3072*256*768, Process Mesh: 96*8*24. Sub-domain
>>> per process: 32*32*32
>>> >>>>>> Here I get the out of memory error.
>>> >>>>>>
>>> >>>>>> I tried to use -mg_coarse jacobi. In this way, I don't need to
>>> set -mg_coarse_ksp_type and -mg_coarse_pc_type explicitly, right?
>>> >>>>>> The linear solver didn't work in this case. Petsc output some
>>> errors.
>>> >>>>>>
>>> >>>>>> @Dave
>>> >>>>>> In test3, I use only one instance of 'Telescope'. On the coarse
>>> mesh of 'Telescope', I used LU as the preconditioner instead of SVD.
>>> >>>>>> If my set the levels correctly, then on the last coarse mesh of
>>> MG where it calls 'Telescope', the sub-domain per process is 2*2*2.
>>> >>>>>> On the last coarse mesh of 'Telescope', there is only one grid
>>> point per process.
>>> >>>>>> I still got the OOM error. The detailed petsc option file is
>>> attached.
>>> >>>>>>
>>> >>>>>> Do you understand the expected memory usage for the particular
>>> parallel LU implementation you are using? I don't (seriously). Replace LU
>>> with bjacobi and re-run this test. My point about solver debugging is still
>>> valid.
>>> >>>>>>
>>> >>>>>> And please send the result of KSPView so we can see what is
>>> actually used in the computations
>>> >>>>>>
>>> >>>>>> Thanks
>>> >>>>>> Dave
>>> >>>>>>
>>> >>>>>>
>>> >>>>>> Thank you so much.
>>> >>>>>>
>>> >>>>>> Frank
>>> >>>>>>
>>> >>>>>>
>>> >>>>>>
>>> >>>>>> On 07/06/2016 02:51 PM, Barry Smith wrote:
>>> >>>>>> On Jul 6, 2016, at 4:19 PM, frank <hengjiew at uci.edu> wrote:
>>> >>>>>>
>>> >>>>>> Hi Barry,
>>> >>>>>>
>>> >>>>>> Thank you for you advice.
>>> >>>>>> I tried three test. In the 1st test, the grid is 3072*256*768 and
>>> the process mesh is 96*8*24.
>>> >>>>>> The linear solver is 'cg' the preconditioner is 'mg' and
>>> 'telescope' is used as the preconditioner at the coarse mesh.
>>> >>>>>> The system gives me the "Out of Memory" error before the linear
>>> system is completely solved.
>>> >>>>>> The info from '-ksp_view_pre' is attached. I seems to me that the
>>> error occurs when it reaches the coarse mesh.
>>> >>>>>>
>>> >>>>>> The 2nd test uses a grid of 1536*128*384 and process mesh is
>>> 96*8*24. The 3rd test uses the
>>> same grid but a different process mesh 48*4*12.
>>> >>>>>> Are you sure this is right? The total matrix and vector
>>> memory usage goes from 2nd test
>>> >>>>>> Vector 384 383 8,193,712 0.
>>> >>>>>> Matrix 103 103 11,508,688 0.
>>> >>>>>> to 3rd test
>>> >>>>>> Vector 384 383 1,590,520 0.
>>> >>>>>> Matrix 103 103 3,508,664 0.
>>> >>>>>> that is the memory usage got smaller but if you have only 1/8th
>>> the processes and the same grid it should have gotten about 8 times bigger.
>>> Did you maybe cut the grid by a factor of 8 also? If so that still doesn't
>>> explain it because the memory usage changed by a factor of 5 something for
>>> the vectors and 3 something for the matrices.
>>> >>>>>>
>>> >>>>>>
>>> >>>>>> The linear solver and petsc options in 2nd and 3rd tests are the
>>> same in 1st test. The linear solver works fine in both test.
>>> >>>>>> I attached the memory usage of the 2nd and 3rd tests. The memory
>>> info is from the option '-log_summary'. I tried to use '-momery_info' as
>>> you suggested, but in my case petsc treated it as an unused option. It
>>> output nothing about the memory. Do I need to add sth to my code so I can
>>> use '-memory_info'?
>>> >>>>>> Sorry, my mistake the option is -memory_view
>>> >>>>>>
>>> >>>>>> Can you run the one case with -memory_view and -mg_coarse
>>> jacobi -ksp_max_it 1 (just so it doesn't iterate forever) to see how much
>>> memory is used without the telescope? Also run case 2 the same way.
>>> >>>>>>
>>> >>>>>> Barry
>>> >>>>>>
>>> >>>>>>
>>> >>>>>>
>>> >>>>>> In both tests the memory usage is not large.
>>> >>>>>>
>>> >>>>>> It seems to me that it might be the 'telescope' preconditioner
>>> that allocated a lot of memory and caused the error in the 1st test.
>>> >>>>>> Is there is a way to show how much memory it allocated?
>>> >>>>>>
>>> >>>>>> Frank
>>> >>>>>>
>>> >>>>>> On 07/05/2016 03:37 PM, Barry Smith wrote:
>>> >>>>>> Frank,
>>> >>>>>>
>>> >>>>>> You can run with -ksp_view_pre to have it "view" the KSP
>>> before the solve so hopefully it gets that far.
>>> >>>>>>
>>> >>>>>> Please run the problem that does fit with -memory_info when
>>> the problem completes it will show the "high water mark" for PETSc
>>> allocated memory and total memory used. We first want to look at these
>>> numbers to see if it is using more memory than you expect. You could also
>>> run with say half the grid spacing to see how the memory usage scaled with
>>> the increase in grid points. Make the runs also with -log_view and send all
>>> the output from these options.
>>> >>>>>>
>>> >>>>>> Barry
>>> >>>>>>
>>> >>>>>> On Jul 5, 2016, at 5:23 PM, frank <hengjiew at uci.edu> wrote:
>>> >>>>>>
>>> >>>>>> Hi,
>>> >>>>>>
>>> >>>>>> I am using the CG ksp solver and Multigrid preconditioner to
>>> solve a linear system in parallel.
>>> >>>>>> I chose to use the 'Telescope' as the preconditioner on the
>>> coarse mesh for its good performance.
>>> >>>>>> The petsc options file is attached.
>>> >>>>>>
>>> >>>>>> The domain is a 3d box.
>>> >>>>>> It works well when the grid is 1536*128*384 and the process mesh
>>> is 96*8*24. When I double the size of grid and
>>> keep the same process mesh and petsc options, I get an
>>> "out of memory" error from the super-cluster I am using.
>>> >>>>>> Each process has access to at least 8G memory, which should be
>>> more than enough for my application. I am sure that all the other parts of
>>> my code( except the linear solver ) do not use much memory. So I doubt if
>>> there is something wrong with the linear solver.
>>> >>>>>> The error occurs before the linear system is completely solved so
>>> I don't have the info from ksp view. I am not able to re-produce the error
>>> with a smaller problem either.
>>> >>>>>> In addition, I tried to use the block jacobi as the
>>> preconditioner with the same grid and same decomposition. The linear solver
>>> runs extremely slow but there is no memory error.
>>> >>>>>>
>>> >>>>>> How can I diagnose what exactly cause the error?
>>> >>>>>> Thank you so much.
>>> >>>>>>
>>> >>>>>> Frank
>>> >>>>>> <petsc_options.txt>
>>> >>>>>> <ksp_view_pre.txt><memory_test2.txt><memory_test3.txt><petsc
>>> _options.txt>
>>> >>>>>>
>>> >>>>>
>>> >>>>
>>> >>> <ksp_view1.txt><ksp_view2.txt><ksp_view3.txt><memory1.txt><m
>>> emory2.txt><petsc_options1.txt><petsc_options2.txt><petsc_options3.txt>
>>> >
>>>
>>>
>>
>
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