[petsc-users] Extremely slow DMNetwork Jacobian assembly
Justin Chang
jychang48 at gmail.com
Wed May 8 17:10:11 CDT 2019
Yeah I noticed that too. So could that possibly imply that the row/col
indices used in my MatSetValues() extend beyond what was originally
allocated in the DMCreateMatrix() function?
On Wed, May 8, 2019 at 4:00 PM Dave May <dave.mayhem23 at gmail.com> wrote:
>
>
> On Wed, 8 May 2019 at 20:34, Justin Chang via petsc-users <
> petsc-users at mcs.anl.gov> wrote:
>
>> So here's the branch/repo to the working example I have:
>>
>> https://github.com/jychang48/petsc-dss/tree/single-bus-vertex
>>
>> Type 'make' to compile the dss, it should work with the latest petsc-dev
>>
>> To test the performance, I've taken an existing IEEE 13-bus and
>> duplicated it N times to create a long radial-like network. I have three
>> sizes where N = 100, 500, and 1000. Those test files are listed as:
>>
>> input/test_100.m
>> input/test_500.m
>> input/test_1000.m
>>
>> I also created another set of examples where the IEEE 13-bus is fully
>> balanced (but the program will crash ar the solve step because I used some
>> unrealistic parameters for the Y-bus matrices and probably have some zeros
>> somewhere). They are listed as:
>>
>> input/test2_100.m
>> input/test2_500.m
>> input/test2_1000.m
>>
>> The dof count and matrices for the test2_*.m files are slightly larger
>> than their respective test_*.m but they have a bs=6.
>>
>> To run these tests, type the following:
>>
>> ./dpflow -input input/test_100.m
>>
>> I have a timer that shows how long it takes to compute the Jacobian.
>> Attached are the log outputs I have for each of the six cases.
>>
>> Turns out that only the first call to the SNESComputeJacobian() is slow,
>> all the subsequent calls are fast as I expect. This makes me think it still
>> has something to do with matrix allocation.
>>
>
> I think it is a preallocation issue.
> Looking to some of the output files (test_1000.out, test_100.out), under
> Mat Object I see this in the KSPView
>
> total number of mallocs used during MatSetValues calls =10000
>
>
>
>
>
>>
>> Thanks for the help everyone,
>>
>> Justin
>>
>> On Wed, May 8, 2019 at 12:36 PM Matthew Knepley <knepley at gmail.com>
>> wrote:
>>
>>> On Wed, May 8, 2019 at 2:30 PM Justin Chang <jychang48 at gmail.com> wrote:
>>>
>>>> Hi everyone,
>>>>
>>>> Yes I have these lines in my code:
>>>>
>>>> ierr = DMCreateMatrix(networkdm,&J);CHKERRQ(ierr);
>>>> ierr =
>>>> MatSetOption(J,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr);
>>>>
>>>
>>> Okay, its not allocation. So maybe Hong is right that its setting great
>>> big element matrices. We will see with the example.
>>>
>>> Thanks,
>>>
>>> Matt
>>>
>>>
>>>> I tried -info and here's my output:
>>>>
>>>> [0] PetscInitialize(): PETSc successfully started: number of processors
>>>> = 1
>>>> [0] PetscInitialize(): Running on machine: jchang31606s.domain
>>>> [0] PetscCommDuplicate(): Duplicating a communicator 4436504608
>>>> 140550815662944 max tags = 2147483647
>>>> [0] PetscCommDuplicate(): Using internal PETSc communicator 4436504608
>>>> 140550815662944
>>>> [0] PetscCommDuplicate(): Using internal PETSc communicator 4436504608
>>>> 140550815662944
>>>> Base power = 0.166667, numbus = 115000, numgen = 5000, numyl = 75000,
>>>> numdl = 5000, numlbr = 109999, numtbr = 5000
>>>>
>>>> **** Power flow dist case ****
>>>>
>>>> Base power = 0.166667, nbus = 115000, ngen = 5000, nwye = 75000, ndelta
>>>> = 5000, nbranch = 114999
>>>> [0] PetscCommDuplicate(): Duplicating a communicator 4436505120
>>>> 140550815683104 max tags = 2147483647
>>>> [0] PetscCommDuplicate(): Using internal PETSc communicator 4436505120
>>>> 140550815683104
>>>> [0] PetscCommDuplicate(): Using internal PETSc communicator 4436505120
>>>> 140550815683104
>>>> [0] PetscCommDuplicate(): Using internal PETSc communicator 4436505120
>>>> 140550815683104
>>>> [0] PetscCommDuplicate(): Using internal PETSc communicator 4436505120
>>>> 140550815683104
>>>> [0] PetscCommDuplicate(): Using internal PETSc communicator 4436505120
>>>> 140550815683104
>>>> [0] PetscCommDuplicate(): Using internal PETSc communicator 4436505120
>>>> 140550815683104
>>>> [0] PetscCommDuplicate(): Using internal PETSc communicator 4436505120
>>>> 140550815683104
>>>> [0] PetscCommDuplicate(): Using internal PETSc communicator 4436505120
>>>> 140550815683104
>>>> [0] PetscCommDuplicate(): Using internal PETSc communicator 4436505120
>>>> 140550815683104
>>>> [0] PetscCommDuplicate(): Using internal PETSc communicator 4436505120
>>>> 140550815683104
>>>> [0] PetscCommDuplicate(): Using internal PETSc communicator 4436505120
>>>> 140550815683104
>>>> [0] PetscCommDuplicate(): Using internal PETSc communicator 4436505120
>>>> 140550815683104
>>>> [0] MatAssemblyEnd_SeqAIJ(): Matrix size: 620000 X 620000; storage
>>>> space: 0 unneeded,10799928 used
>>>> [0] MatAssemblyEnd_SeqAIJ(): Number of mallocs during MatSetValues() is
>>>> 0
>>>> [0] MatAssemblyEnd_SeqAIJ(): Maximum nonzeros in any row is 28
>>>> [0] MatCheckCompressedRow(): Found the ratio (num_zerorows
>>>> 0)/(num_localrows 620000) < 0.6. Do not use CompressedRow routines.
>>>> [0] MatSeqAIJCheckInode(): Found 205000 nodes of 620000. Limit used: 5.
>>>> Using Inode routines
>>>> [0] PetscCommDuplicate(): Using internal PETSc communicator 4436505120
>>>> 140550815683104
>>>> [0] PetscCommDuplicate(): Using internal PETSc communicator 4436504608
>>>> 140550815662944
>>>> [0] DMGetDMSNES(): Creating new DMSNES
>>>> [0] DMGetDMKSP(): Creating new DMKSP
>>>> [0] PetscCommDuplicate(): Using internal PETSc communicator 4436505120
>>>> 140550815683104
>>>> 0 SNES Function norm 1155.45
>>>>
>>>> nothing else -info related shows up as I'm iterating through the vertex
>>>> loop.
>>>>
>>>> I'll have a MWE for you guys to play with shortly.
>>>>
>>>> Thanks,
>>>> Justin
>>>>
>>>> On Wed, May 8, 2019 at 12:10 PM Smith, Barry F. <bsmith at mcs.anl.gov>
>>>> wrote:
>>>>
>>>>>
>>>>> Justin,
>>>>>
>>>>> Are you providing matrix entries that connect directly one
>>>>> vertex to another vertex ACROSS an edge? I don't think that is supported by
>>>>> the DMNetwork model. The assumption is that edges are only connected to
>>>>> vertices and vertices are only connected to neighboring edges.
>>>>>
>>>>> Everyone,
>>>>>
>>>>> I second Matt's reply.
>>>>>
>>>>> How is the DMNetwork preallocating for the Jacobian? Does it take
>>>>> into account coupling between neighboring vertices/edges? Or does it assume
>>>>> no coupling. Or assume full coupling. If it assumes no coupling and the
>>>>> user has a good amount of coupling it will be very slow.
>>>>>
>>>>> There would need to be a way for the user provide the coupling
>>>>> information between neighboring vertices/edges if it assumes no coupling.
>>>>>
>>>>> Barry
>>>>>
>>>>>
>>>>> > On May 8, 2019, at 7:44 AM, Matthew Knepley via petsc-users <
>>>>> petsc-users at mcs.anl.gov> wrote:
>>>>> >
>>>>> > On Wed, May 8, 2019 at 4:45 AM Justin Chang via petsc-users <
>>>>> petsc-users at mcs.anl.gov> wrote:
>>>>> > Hi guys,
>>>>> >
>>>>> > I have a fully working distribution system solver written using
>>>>> DMNetwork, The idea is that each electrical bus can have up to three phase
>>>>> nodes, and each phase node has two unknowns: voltage magnitude and angle.
>>>>> In a completely balanced system, each bus has three nodes, but in an
>>>>> unbalanced system some of the buses can be either single phase or two-phase.
>>>>> >
>>>>> > The working DMNetwork code I developed, loosely based on the SNES
>>>>> network/power.c, essentially represents each vertex as a bus.
>>>>> DMNetworkAddNumVariables() function will add either 2, 4, or 6 unknowns to
>>>>> each vertex. If every single bus had the same number of variables, the mat
>>>>> block size = 2, 4, or 6, and my code is both fast and scalable. However, if
>>>>> the unknowns per DMNetwork vertex unknowns are not the same across, then my
>>>>> SNESFormJacobian function becomes extremely extremely slow. Specifically,
>>>>> the MatSetValues() calls when the col/row global indices contain an offset
>>>>> value that points to a neighboring bus vertex.
>>>>> >
>>>>> > I have never seen MatSetValues() be slow unless it is allocating.
>>>>> Did you confirm that you are not allocating, with -info?
>>>>> >
>>>>> > Thanks,
>>>>> >
>>>>> > MAtt
>>>>> >
>>>>> > Why is that? Is it because I no longer have a uniform block
>>>>> structure and lose the speed/optimization benefits of iterating through an
>>>>> AIJ matrix? I see three potential workarounds:
>>>>> >
>>>>> > 1) Treat every vertex as a three phase bus and "zero out" all the
>>>>> unused phase node dofs and put a 1 in the diagonal. The problem I see with
>>>>> this is that I will have unnecessary degrees of freedom (aka non-zeros in
>>>>> the matrix). From the distribution systems I've seen, it's possible that
>>>>> anywhere from 1/3 to 1/2 of the buses will be two-phase or less, meaning I
>>>>> may have nearly twice the amount of dofs than necessary if I wanted to
>>>>> preserve the block size = 6 for the AU mat.
>>>>> >
>>>>> > 2) Treat every phase node as a vertex aka solve a single-phase power
>>>>> flow solver. That way I guarantee to have a block size = 2, this is what
>>>>> Domenico's former student did in his thesis work. The problem I see with
>>>>> this is that I have a larger graph, which can take more time to setup and
>>>>> parallelize.
>>>>> >
>>>>> > 3) Create a "fieldsplit" where I essentially have three "blocks" -
>>>>> one for buses with all three phases, another for buses with only two
>>>>> phases, one for single-phase buses. This way each block/fieldsplit will
>>>>> have a consistent block size. I am not sure if this will solve the
>>>>> MatSetValues() issues, but it's, but can anyone give pointers on how to go
>>>>> about achieving this?
>>>>> >
>>>>> > Thanks,
>>>>> > Justin
>>>>> >
>>>>> >
>>>>> > --
>>>>> > 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/
>>>>>
>>>>>
>>>
>>> --
>>> 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/>
>>>
>>
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