> On 7 Dec 2023, at 9:37 PM, Sreeram R Venkat <[email protected]> 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 <[email protected] > <mailto:[email protected]>> 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 <[email protected] >>> <mailto:[email protected]>> wrote: >>> >>> >>> >>>> On Dec 7, 2023, at 1:17 PM, Sreeram R Venkat <[email protected] >>>> <mailto:[email protected]>> 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 >>
