[petsc-dev] Broken MatMatMult_MPIAIJ_MPIDense

[Jose E. Roman]

The man page of MatMatMult says:
"In the special case where matrix B (and hence C) are dense you can create the correctly sized matrix C yourself and then call this routine with MAT_REUSE_MATRIX, rather than first having MatMatMult() create it for you."

If you are going to change the usage, don't forget to remove this sentence. This use case is what we use in SLEPc and is now causing trouble.
Jose



> El 22 sept 2019, a las 18:49, Pierre Jolivet via petsc-dev <petsc-dev at mcs.anl.gov> escribió:
> 
> 
>> On 22 Sep 2019, at 6:33 PM, Smith, Barry F. <bsmith at mcs.anl.gov> wrote:
>> 
>> 
>>  Ok. So we definitely need better error checking and to clean up the code, comments and docs 
>> 
>>  As the approaches for these computations of products get more complicated it becomes a bit harder to support the use of a raw product matrix so I don't think we want to add all the code needed to call the symbolic part (after the fact) when the matrix is raw.
> 
> To the best of my knowledge, there is only a single method (not taking MR 2069 into account) that uses a MPIDense B and for which these approaches are necessary, so it’s not like there is a hundred of code paths to fix, but I understand your point.
> 
>> Would that make things terribly difficult for you not being able to use a raw matrix?
> 
> Definitely not, but that would require some more memory + one copy after the MatMatMult (depending on the size of your block Krylov space, that can be quite large, and that defeats the purpose of MR 2032 of being more memory efficient).
> (BTW, I now remember that I’ve been using this “feature” since our SC16 paper on block Krylov methods)
> 
>>  I suspect that the dense case was just lucky that using a raw matrix worked. 
> 
> I don’t think so, this is clearly the intent of MatMatMultNumeric_MPIDense (vs. MatMatMultNumeric_MPIAIJ_MPIDense).
> 
>>  The removal of the de facto support for REUSE on the raw matrix should be added to the changes document.
>> 
>>  Sorry for the difficulties. We have trouble testing all the combinations of possible usage, even a coverage tool would not have indicated a problems the lack of lda support. 
> 
> No problem!
> 
> Thank you,
> Pierre
> 
>> Hong,
>> 
>>    Can you take a look at these things on Monday and maybe get a clean into a MR so it gets into the release?
>> 
>>  Thanks
>> 
>> 
>>  Barry
>> 
>> 
>> 
>> 
>> 
>>> On Sep 22, 2019, at 11:12 AM, Pierre Jolivet <pierre.jolivet at enseeiht.fr> wrote:
>>> 
>>> 
>>>> On 22 Sep 2019, at 6:03 PM, Smith, Barry F. <bsmith at mcs.anl.gov> wrote:
>>>> 
>>>> 
>>>> 
>>>>> On Sep 22, 2019, at 10:14 AM, Pierre Jolivet via petsc-dev <petsc-dev at mcs.anl.gov> wrote:
>>>>> 
>>>>> FWIW, I’ve fixed MatMatMult and MatTransposeMatMult here https://gitlab.com/petsc/petsc/commit/93d7d1d6d29b0d66b5629a261178b832a925de80 (with MAT_INITIAL_MATRIX).
>>>>> I believe there is something not right in your MR (2032) with MAT_REUSE_MATRIX (without having called MAT_INITIAL_MATRIX first), cf. https://gitlab.com/petsc/petsc/merge_requests/2069#note_220269898.
>>>>> Of course, I’d love to be proved wrong!
>>>> 
>>>> I don't understand the context.
>>>> 
>>>>  MAT_REUSE_MATRIX requires that the C matrix has come from a previous call with MAT_INITIAL_MATRIX, you cannot just put any matrix in the C location.
>>> 
>>> 1) It was not the case before the MR, I’ve used that “feature” (which may be specific for MatMatMult_MPIAIJ_MPIDense) for as long as I can remember
>>> 2) If it is not the case anymore, I think it should be mentioned somewhere (and not only in the git log, because I don’t think all users will go through that)
>>> 3) This comment should be removed from the code as well: https://www.mcs.anl.gov/petsc/petsc-dev/src/mat/impls/aij/mpi/mpimatmatmult.c.html#line398
>>> 
>>>> This is documented in the manual page. We should have better error checking that this is the case so the code doesn't crash at memory access but instead produces a very useful error message if the matrix was not obtained with MAT_INITIAL_MATRIX. 
>>>> 
>>>> Is this the issue or do I not understand?
>>> 
>>> This is exactly the issue.
>>> 
>>>> Barry
>>>> 
>>>> BTW: yes MAT_REUSE_MATRIX has different meanings for different matrix operations in terms of where the matrix came from, this is suppose to be all documented in each methods manual page but some may be missing or incomplete, and error checking is probably not complete for all cases.  Perhaps the code should be changed to have multiple different names for each reuse case for clarity to user?
>>> 
>>> Definitely, cf. above.
>>> 
>>> Thanks,
>>> Pierre
>>> 
>>>>> 
>>>>> Thanks,
>>>>> Pierre
>>>>> 
>>>>>> On 22 Sep 2019, at 5:04 PM, Zhang, Hong <hzhang at mcs.anl.gov> wrote:
>>>>>> 
>>>>>> I'll check it tomorrow.
>>>>>> Hong
>>>>>> 
>>>>>> On Sun, Sep 22, 2019 at 1:04 AM Pierre Jolivet via petsc-dev <petsc-dev at mcs.anl.gov> wrote:
>>>>>> Jed,
>>>>>> I’m not sure how easy it is to put more than a few lines of code on GitLab, so I’ll just send the (tiny) source here, as a follow-up of our discussion https://gitlab.com/petsc/petsc/merge_requests/2069#note_220229648.
>>>>>> Please find attached a .cpp showing the brokenness of C=A*B with A of type MPIAIJ and B of type MPIDense when the LDA of B is not equal to its number of local rows.
>>>>>> It does [[1,1];[1,1]] * [[0,1,2,3];[0,1,2,3]]
>>>>>> C should be equal to 2*B, but it’s not, unless lda = m (= 1).
>>>>>> Mat Object: 2 MPI processes
>>>>>> type: mpidense
>>>>>> 0.0000000000000000e+00 1.0000000000000000e+00 2.0000000000000000e+00 3.0000000000000000e+00
>>>>>> 0.0000000000000000e+00 1.0000000000000000e+00 2.0000000000000000e+00 3.0000000000000000e+00
>>>>>> 
>>>>>> If you change Bm here https://www.mcs.anl.gov/petsc/petsc-dev/src/mat/impls/aij/mpi/mpimatmatmult.c.html#line549 to the LDA of B, you’ll get the correct result.
>>>>>> Mat Object: 2 MPI processes
>>>>>> type: mpidense
>>>>>> 0.0000000000000000e+00 2.0000000000000000e+00 4.0000000000000000e+00 6.0000000000000000e+00
>>>>>> 0.0000000000000000e+00 2.0000000000000000e+00 4.0000000000000000e+00 6.0000000000000000e+00
>>>>>> 
>>>>>> Unfortunately, w.r.t. MR 2069, I still don’t get the same results with a plain view LDA > m (KO) and a view + duplicate LDA = m (OK).
>>>>>> So there might be something else to fix (or this might not even be a correct fix), but the only reproducer I have right now is the full solver.
>>>>>> 
>>>>>> Thanks,
>>>>>> Pierre
>>>>>> 
>>>>> 
>>>> 
>>> 
>> 
>