[petsc-users] Matvecs and KSPSolves with multiple vectors

[Mark Adams]

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
>>>
>>>
>>>
>>
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