[petsc-users] Performance of the Telescope Multigrid Preconditioner
Matthew Knepley
knepley at gmail.com
Tue Oct 4 13:24:28 CDT 2016
On Tue, Oct 4, 2016 at 1:13 PM, frank <hengjiew at uci.edu> wrote:
> Hi,
> This question is follow-up of the thread "Question about memory usage in
> Multigrid preconditioner".
> I used to have the "Out of Memory(OOM)" problem when using the
> CG+Telescope MG solver with 32768 cores. Adding the "-matrap 0;
> -matptap_scalable" option did solve that problem.
>
> Then I test the scalability by solving a 3d poisson eqn for 1 step. I used
> one sub-communicator in all the tests. The difference between the petsc
> options in those tests are: 1 the pc_telescope_reduction_factor; 2 the
> number of multigrid levels in the up/down solver. The function "ksp_solve"
> is timed. It is kind of slow and doesn't scale at all.
>
1) The number of levels cannot be different in the up/down smoothers. Why
are you using a / ?
2) We need to see what solver you actually constructed, so give us the
output of -ksp_view
3) For any performance questions, we need the output of -log_view
4) It looks like you are fixing the number of levels as you scale up. This
makes the coarse problem much bigger, and is not a scalable way to proceed.
Have you looked at the ratio of coarse grid time to level time?
5) Did you look at the options in this paper:
https://arxiv.org/abs/1604.07163
Thanks,
Matt
> Test1: 512^3 grid points
> Core# telescope_reduction_factor MG levels# for up/down
> solver Time for KSPSolve (s)
> 512 8 4 /
> 3 6.2466
> 4096 64 5 /
> 3 0.9361
> 32768 64 4 /
> 3 4.8914
>
> Test2: 1024^3 grid points
> Core# telescope_reduction_factor MG levels# for up/down
> solver Time for KSPSolve (s)
> 4096 64 5 / 4
> 3.4139
> 8192 128 5 /
> 4 2.4196
> 16384 32 5 / 3
> 5.4150
> 32768 64 5 /
> 3 5.6067
> 65536 128 5 /
> 3 6.5219
>
> I guess I didn't set the MG levels properly. What would be the efficient
> way to arrange the MG levels?
> Also which preconditionr at the coarse mesh of the 2nd communicator should
> I use to improve the performance?
>
> I attached the test code and the petsc options file for the 1024^3 cube
> with 32768 cores.
>
> Thank you.
>
> Regards,
> Frank
>
>
>
>
>
>
> On 09/15/2016 03:35 AM, Dave May wrote:
>
> HI all,
>
> I the only unexpected memory usage I can see is associated with the call
> to MatPtAP().
> Here is something you can try immediately.
> Run your code with the additional options
> -matrap 0 -matptap_scalable
>
> I didn't realize this before, but the default behaviour of MatPtAP in
> parallel is actually to to explicitly form the transpose of P (e.g.
> assemble R = P^T) and then compute R.A.P.
> You don't want to do this. The option -matrap 0 resolves this issue.
>
> The implementation of P^T.A.P has two variants.
> The scalable implementation (with respect to memory usage) is selected via
> the second option -matptap_scalable.
>
> Try it out - I see a significant memory reduction using these options for
> particular mesh sizes / partitions.
>
> I've attached a cleaned up version of the code you sent me.
> There were a number of memory leaks and other issues.
> The main points being
> * You should call DMDAVecGetArrayF90() before VecAssembly{Begin,End}
> * You should call PetscFinalize(), otherwise the option -log_summary
> (-log_view) will not display anything once the program has completed.
>
>
> Thanks,
> Dave
>
>
> On 15 September 2016 at 08:03, Hengjie Wang <hengjiew at uci.edu> wrote:
>
>> Hi Dave,
>>
>> Sorry, I should have put more comment to explain the code.
>> The number of process in each dimension is the same: Px = Py=Pz=P. So is
>> the domain size.
>> So if the you want to run the code for a 512^3 grid points on 16^3
>> cores, you need to set "-N 512 -P 16" in the command line.
>> I add more comments and also fix an error in the attached code. ( The
>> error only effects the accuracy of solution but not the memory usage. )
>>
>> Thank you.
>> Frank
>>
>>
>> On 9/14/2016 9:05 PM, Dave May wrote:
>>
>>
>>
>> On Thursday, 15 September 2016, Dave May <dave.mayhem23 at gmail.com> wrote:
>>
>>>
>>>
>>> On Thursday, 15 September 2016, frank <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_op
>>>>> tions3.txt>
>>>>> >
>>>>>
>>>>>
>>>>
>>>
>>
>>
>
>
--
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
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