[petsc-users] Matvecs and KSPSolves with multiple vectors

[Matthew Knepley]

On Thu, Dec 21, 2023 at 6:46 AM Sreeram R Venkat <srvenkat at utexas.edu>
wrote:

> Ok, I think the error I'm getting has something to do with how the
> multiple solves are being done in succession. I'll try to see if there's
> anything I'm doing wrong there.
>
> One question about the -pc_type lu -ksp_type preonly method: do you know
> which parts of the solve (factorization/triangular solves) are done on host
> and which are done on device?
>

For SEQDENSE, I believe both the factorization and solve is on device. It
is hard to see, but I believe the dispatch code is here:


https://gitlab.com/petsc/petsc/-/blob/main/src/mat/impls/dense/seq/cupm/matseqdensecupm.hpp?ref_type=heads#L368

  Thanks,

     Matt


> Thanks,
> Sreeram
>
> On Sat, Dec 16, 2023 at 10:56 PM Pierre Jolivet <pierre at joliv.et> wrote:
>
>> Unfortunately, I am not able to reproduce such a failure with your input
>> matrix.
>> I’ve used ex79 that I linked previously and the system is properly solved.
>> $ ./ex79 -pc_type hypre -ksp_type hpddm -ksp_hpddm_type cg
>> -ksp_converged_reason -ksp_view_mat ascii::ascii_info -ksp_view_rhs
>> ascii::ascii_info
>> Linear solve converged due to CONVERGED_RTOL iterations 6
>> Mat Object: 1 MPI process
>>   type: seqaijcusparse
>>   rows=289, cols=289
>>   total: nonzeros=2401, allocated nonzeros=2401
>>   total number of mallocs used during MatSetValues calls=0
>>     not using I-node routines
>> Mat Object: 1 MPI process
>>   type: seqdensecuda
>>   rows=289, cols=10
>>   total: nonzeros=2890, allocated nonzeros=2890
>>   total number of mallocs used during MatSetValues calls=0
>>
>> You mentioned in a subsequent email that you are interested in systems
>> with at most 1E6 unknowns, and up to 1E4 right-hand sides.
>> I’m not sure you can expect significant gains from using GPU for such
>> systems.
>> Probably, the fastest approach would indeed be -pc_type lu -ksp_type
>> preonly -ksp_matsolve_batch_size 100 or something, depending on the memory
>> available on your host.
>>
>> Thanks,
>> Pierre
>>
>> On 15 Dec 2023, at 9:52 PM, Sreeram R Venkat <srvenkat at utexas.edu> wrote:
>>
>> Here are the ksp_view files.  I set the options
>> -ksp_error_if_not_converged to try to get the vectors that caused the
>> error. I noticed that some of the KSPMatSolves converge while others don't.
>> In the code, the solves are called as:
>>
>> input vector v --> insert data of v into a dense mat --> KSPMatSolve()
>> --> MatMatMult() --> KSPMatSolve() --> insert data of dense mat into output
>> vector w -- output w
>>
>> The operator used in the KSP is a Laplacian-like operator, and the
>> MatMatMult is with a Mass Matrix. The whole thing is supposed to be a solve
>> with a biharmonic-like operator. I can also run it with only the first
>> KSPMatSolve (i.e. just a Laplacian-like operator). In that case, the KSP
>> reportedly converges after 0 iterations (see the next line), but this
>> causes problems in other parts of the code later on.
>>
>> I saw that sometimes the first KSPMatSolve "converges" after 0 iterations
>> due to CONVERGED_RTOL. Then, the second KSPMatSolve produces a NaN/Inf. I
>> tried setting ksp_min_it, but that didn't seem to do anything.
>>
>> I'll keep trying different options and also try to get the MWE made (this
>> KSPMatSolve is pretty performance critical for us).
>>
>> Thanks for all your help,
>> Sreeram
>>
>> On Fri, Dec 15, 2023 at 1:01 AM Pierre Jolivet <pierre at joliv.et> wrote:
>>
>>>
>>> On 14 Dec 2023, at 11:45 PM, Sreeram R Venkat <srvenkat at utexas.edu>
>>> wrote:
>>>
>>> Thanks, I will try to create a minimal reproducible example. This may
>>> take me some time though, as I need to figure out how to extract only the
>>> relevant parts (the full program this solve is used in is getting quite
>>> complex).
>>>
>>>
>>> You could just do -ksp_view_mat binary:Amat.bin -ksp_view_pmat
>>> binary:Pmat.bin -ksp_view_rhs binary:rhs.bin and send me those three files
>>> (I’m guessing your are using double-precision scalars with 32-bit PetscInt).
>>>
>>> I'll also try out some of the BoomerAMG options to see if that helps.
>>>
>>>
>>> These should work (this is where all “PCMatApply()-ready” PC are being
>>> tested):
>>> https://petsc.org/release/src/ksp/ksp/tutorials/ex79.c.html#line215
>>> You can see it’s also testing PCHYPRE + KSPHPDDM on device (but not with
>>> HIP).
>>> I’m aware the performance should not be optimal (see your comment about
>>> host/device copies), I’ve money to hire someone to work on this but: a) I
>>> need to find the correct engineer/post-doc, b) I currently don’t have good
>>> use cases (of course, I could generate a synthetic benchmark, for science).
>>> So even if you send me the three Mat, a MWE would be appreciated if the
>>> KSPMatSolve() is performance-critical for you (see point b) from above).
>>>
>>> Thanks,
>>> Pierre
>>>
>>> Thanks,
>>> Sreeram
>>>
>>> On Thu, Dec 14, 2023, 1:12 PM Pierre Jolivet <pierre at joliv.et> wrote:
>>>
>>>>
>>>>
>>>> On 14 Dec 2023, at 8:02 PM, Sreeram R Venkat <srvenkat at utexas.edu>
>>>> wrote:
>>>>
>>>> Hello Pierre,
>>>>
>>>> Thank you for your reply. I tried out the HPDDM CG as you said, and it
>>>> seems to be doing the batched solves, but the KSP is not converging due to
>>>> a NaN or Inf being generated. I also noticed there are a lot of
>>>> host-to-device and device-to-host copies of the matrices (the non-batched
>>>> KSP solve did not have any memcopies). I have attached dump.0 again. Could
>>>> you please take a look?
>>>>
>>>>
>>>> Yes, but you’d need to send me something I can run with your set of
>>>> options (if you are more confident doing this in private, you can remove
>>>> the list from c/c).
>>>> Not all BoomerAMG smoothers handle blocks of right-hand sides, and
>>>> there is not much error checking, so instead of erroring out, this may be
>>>> the reason why you are getting garbage.
>>>>
>>>> Thanks,
>>>> Pierre
>>>>
>>>> Thanks,
>>>> Sreeram
>>>>
>>>> On Thu, Dec 14, 2023 at 12:42 AM Pierre Jolivet <pierre at joliv.et>
>>>> wrote:
>>>>
>>>>> Hello Sreeram,
>>>>> KSPCG (PETSc implementation of CG) does not handle solves with
>>>>> multiple columns at once.
>>>>> There is only a single native PETSc KSP implementation which handles
>>>>> solves with multiple columns at once: KSPPREONLY.
>>>>> If you use --download-hpddm, you can use a CG (or GMRES, or more
>>>>> advanced methods) implementation which handles solves with multiple columns
>>>>> at once (via -ksp_type hpddm -ksp_hpddm_type cg or KSPSetType(ksp,
>>>>> KSPHPDDM); KSPHPDDMSetType(ksp, KSP_HPDDM_TYPE_CG);).
>>>>> I’m the main author of HPDDM, there is preliminary support for device
>>>>> matrices, but if it’s not working as intended/not faster than column by
>>>>> column, I’d be happy to have a deeper look (maybe in private), because most
>>>>> (if not all) of my users interested in (pseudo-)block Krylov solvers (i.e.,
>>>>> solvers that treat right-hand sides in a single go) are using plain host
>>>>> matrices.
>>>>>
>>>>> Thanks,
>>>>> Pierre
>>>>>
>>>>> PS: you could have a look at
>>>>> https://www.sciencedirect.com/science/article/abs/pii/S0898122121000055 to
>>>>> understand the philosophy behind block iterative methods in PETSc (and in
>>>>> HPDDM), src/mat/tests/ex237.c, the benchmark I mentioned earlier, was
>>>>> developed in the context of this paper to produce Figures 2-3. Note that
>>>>> this paper is now slightly outdated, since then, PCHYPRE and PCMG (among
>>>>> others) have been made “PCMatApply()-ready”.
>>>>>
>>>>> On 13 Dec 2023, at 11:05 PM, Sreeram R Venkat <srvenkat at utexas.edu>
>>>>> wrote:
>>>>>
>>>>> Hello Pierre,
>>>>>
>>>>> I am trying out the KSPMatSolve with the BoomerAMG preconditioner.
>>>>> However, I am noticing that it is still solving column by column (this is
>>>>> stated explicitly in the info dump attached). I looked at the code for
>>>>> KSPMatSolve_Private() and saw that as long as ksp->ops->matsolve is
>>>>> true, it should do the batched solve, though I'm not sure where that gets
>>>>> set.
>>>>>
>>>>> I am using the options -pc_type hypre -pc_hypre_type boomeramg when
>>>>> running the code.
>>>>>
>>>>> Can you please help me with this?
>>>>>
>>>>> Thanks,
>>>>> Sreeram
>>>>>
>>>>>
>>>>> On Thu, Dec 7, 2023 at 4:04 PM Mark Adams <mfadams at lbl.gov> wrote:
>>>>>
>>>>>> N.B., AMGX interface is a bit experimental.
>>>>>> Mark
>>>>>>
>>>>>> On Thu, Dec 7, 2023 at 4:11 PM Sreeram R Venkat <srvenkat at utexas.edu>
>>>>>> wrote:
>>>>>>
>>>>>>> Oh, in that case I will try out BoomerAMG. Getting AMGX to build
>>>>>>> correctly was also tricky so hopefully the HYPRE build will be easier.
>>>>>>>
>>>>>>> Thanks,
>>>>>>> Sreeram
>>>>>>>
>>>>>>> On Thu, Dec 7, 2023, 3:03 PM Pierre Jolivet <pierre at joliv.et> wrote:
>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>> On 7 Dec 2023, at 9:37 PM, Sreeram R Venkat <srvenkat at utexas.edu>
>>>>>>>> wrote:
>>>>>>>>
>>>>>>>> Thank you Barry and Pierre; I will proceed with the first option.
>>>>>>>>
>>>>>>>> I want to use the AMGX preconditioner for the KSP. I will try it
>>>>>>>> out and see how it performs.
>>>>>>>>
>>>>>>>>
>>>>>>>> Just FYI, AMGX does not handle systems with multiple RHS, and thus
>>>>>>>> has no PCMatApply() implementation.
>>>>>>>> BoomerAMG does, and there is a PCMatApply_HYPRE_BoomerAMG()
>>>>>>>> implementation.
>>>>>>>> But let us know if you need assistance figuring things out.
>>>>>>>>
>>>>>>>> Thanks,
>>>>>>>> Pierre
>>>>>>>>
>>>>>>>> Thanks,
>>>>>>>> Sreeram
>>>>>>>>
>>>>>>>> On Thu, Dec 7, 2023 at 2:02 PM Pierre Jolivet <pierre at joliv.et>
>>>>>>>> wrote:
>>>>>>>>
>>>>>>>>> To expand on Barry’s answer, we have observed repeatedly that
>>>>>>>>> MatMatMult with MatAIJ performs better than MatMult with MatMAIJ, you can
>>>>>>>>> reproduce this on your own with
>>>>>>>>> https://petsc.org/release/src/mat/tests/ex237.c.html.
>>>>>>>>> Also, I’m guessing you are using some sort of preconditioner
>>>>>>>>> within your KSP.
>>>>>>>>> Not all are “KSPMatSolve-ready”, i.e., they may treat blocks of
>>>>>>>>> right-hand sides column by column, which is very inefficient.
>>>>>>>>> You could run your code with -info dump and send us dump.0 to see
>>>>>>>>> what needs to be done on our end to make things more efficient, should you
>>>>>>>>> not be satisfied with the current performance of the code.
>>>>>>>>>
>>>>>>>>> Thanks,
>>>>>>>>> Pierre
>>>>>>>>>
>>>>>>>>> On 7 Dec 2023, at 8:34 PM, Barry Smith <bsmith at petsc.dev> wrote:
>>>>>>>>>
>>>>>>>>>
>>>>>>>>>
>>>>>>>>> On Dec 7, 2023, at 1:17 PM, Sreeram R Venkat <srvenkat at utexas.edu>
>>>>>>>>> wrote:
>>>>>>>>>
>>>>>>>>> I have 2 sequential matrices M and R (both MATSEQAIJCUSPARSE of
>>>>>>>>> size n x n) and a vector v of size n*m. v = [v_1 , v_2 ,... , v_m] where
>>>>>>>>> v_i has size n. The data for v can be stored either in column-major or
>>>>>>>>> row-major order.  Now, I want to do 2 types of operations:
>>>>>>>>>
>>>>>>>>> 1. Matvecs of the form M*v_i = w_i, for i = 1..m.
>>>>>>>>> 2. KSPSolves of the form R*x_i = v_i, for i = 1..m.
>>>>>>>>>
>>>>>>>>> From what I have read on the documentation, I can think of 2
>>>>>>>>> approaches.
>>>>>>>>>
>>>>>>>>> 1. Get the pointer to the data in v (column-major) and use it to
>>>>>>>>> create a dense matrix V. Then do a MatMatMult with M*V = W, and take the
>>>>>>>>> data pointer of W to create the vector w. For KSPSolves, use KSPMatSolve
>>>>>>>>> with R and V.
>>>>>>>>>
>>>>>>>>> 2. Create a MATMAIJ using M/R and use that for matvecs directly
>>>>>>>>> with the vector v. I don't know if KSPSolve with the MATMAIJ will know that
>>>>>>>>> it is a multiple RHS system and act accordingly.
>>>>>>>>>
>>>>>>>>> Which would be the more efficient option?
>>>>>>>>>
>>>>>>>>>
>>>>>>>>> Use 1.
>>>>>>>>>
>>>>>>>>>
>>>>>>>>> As a side-note, I am also wondering if there is a way to use
>>>>>>>>> row-major storage of the vector v.
>>>>>>>>>
>>>>>>>>>
>>>>>>>>> No
>>>>>>>>>
>>>>>>>>> The reason is that this could allow for more coalesced memory
>>>>>>>>> access when doing matvecs.
>>>>>>>>>
>>>>>>>>>
>>>>>>>>>   PETSc matrix-vector products use BLAS GMEV matrix-vector
>>>>>>>>> products for the computation so in theory they should already be
>>>>>>>>> well-optimized
>>>>>>>>>
>>>>>>>>>
>>>>>>>>> Thanks,
>>>>>>>>> Sreeram
>>>>>>>>>
>>>>>>>>>
>>>>>>>>>
>>>>>>>> <dump.0>
>>>>>
>>>>>
>>>>> <dump.0>
>>>>
>>>>
>>>>
>>> <Pmat.bin><Amat.bin><rhs.bin>
>>
>>
>>

-- 
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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