[petsc-users] KSP solve time and iterations
Stefano Zampini
stefano.zampini at gmail.com
Fri Jan 18 15:18:51 CST 2019
> On Jan 18, 2019, at 6:47 PM, Valerio Barnabei <valerio.barnabei at gmail.com> wrote:
>
> Hello (again),
> I'm trying to figure out how to change my program in order to use MATIS type and PCBDD.
> I managed to build my MATIS matrix successfully, but my code is now slower. I think the main issue is that i'm using MatSetValues inside the element loop, and passing as values the e-th local element matrix.
The only reason I may think about a slower code, is that MatSetValues for MATIS has indirect memory access when mapping global-to-local.
Are you preallocating the matrix properly? I mean, are you calling MatISSetPreallocation with the same input used for MatMPIAIJSetPreallocation?
> In a sort of pseudocode, where B is the shape functions matrix and D is a “diffusion” matrix:
>
> for e in localElements
> for qp in quadraturePoints{
> for n in localNodes {
> for m in localNodes {
> ke += weights[qp]*detJ[qp]*B[n]^T* D*B[m];
> }
> }
> For n in localNodes{
> For m in localNodes{
> fe[n] -= ke[n* localNodes +m]*ge[e][m];//ge is a simple array that lets me easily take into account Dirichlet conditions, for my simple case
> }
> for n in localNodes{
> // idx [n]=LM [e][n];
> //LM is the DOF array (rows are Local elements, columns are local nodes, values are global dofs, i.e. row/col indices for global assembly of K, negative values are prescribed DOFs
> }
> MatSetValues(K, localNodes, (PetscInt*) &idx [0], localNodes, (PetscInt*) &idx [0], (PetscScalar*) &ke[0], ADD_VALUES);
> //same for VecSetValues
> }
> Just to clarify: the array I used to create the map is a unique array for each process, without the negative values of the prescribed DOFs; the array I’m using in matsetvalues is each time the portion of the array used for the map relative to the current element. In addition to that: the code is working, it gives the same result of an older version where I used MATAIJ, but the portion of the element assembly loop is slower, and so is the solving process (compared using PCNONE on both, obtained same iterations to converge, same norm_2 of solution vector).
> I guess using MatSetValues outside of the loop, using the same large array I used to create the map for the matIS is supposed to be better, but I cannot see a way to use it with this elemental assembly logic.
MatSetValues (and MatSetValuesLocal) expects 2d data for the entries. Calling these once per element is the best you can do.
> Stefano suggested to use MatSetValuesLocal: in that case what is supposed to be idx? (I’m using global indices now).
You should use the corresponding local indices. I mean, if your local -> global map is (0,1,2) -> (31,44,77), then, in place of 44, you should use 1 as idx for MatSetValuesLocal
> If I use MatSetValuesLocal, can I stick with this logic of adding values inside the element loop?
Same loop, same entries. Only local indices in place of the global ones
> Is there any other way you suggest to assign values for this case?Any suggestion would be really appreciated.
> I’m not sure I explained my issue properly, I can give any further information needed.
>
> Valerio
>
>
> Il giorno ven 18 gen 2019 alle ore 15:55 Valerio Barnabei <valerio.barnabei at gmail.com <mailto:valerio.barnabei at gmail.com>> ha scritto:
> The mail was still incomplete. Sorry, i will write it again.
> Apologies.
>
> Il giorno ven 18 gen 2019 alle ore 15:53 Valerio Barnabei <valerio.barnabei at gmail.com <mailto:valerio.barnabei at gmail.com>> ha scritto:
> Hello,
> I'm trying to figure out how to change my program in order to use MATIS type and PCBDD.
> I managed to build my MATIS matrix successfully, but my code is now slower. I think the main issue is that i'm using MatSetValues inside the element loop, and passing as values the e-th local element matrix. In a sort of pseudocode:
>
> for e in localElements:{
> for (int qp=0;qp<ngp_tot;qp++)
> for(int A=0;A<Nnodesloc;A++){
> for(int B=0;B<Nnodesloc;B++){
> //Bat dot temp (NB: ba_n0=bat_0n)
> double prod=temp[0][A][qp]*BaT[B][0][qp]+temp[1][A][qp]*BaT[B][1][qp];
> //ke[A][B]+=weights[qp]*detJ[qp]*prod;
> ke[A*Nnodesloc+B]+=weights[qp]*detJ[qp]*prod;
>
>
> ?
> Actually i have lots of doubts:
> -when using ISLocalToGlobalMappingCreate(), what's the blocksize?
>
> Il giorno lun 14 gen 2019 alle ore 15:08 Valerio Barnabei <valerio.barnabei at gmail.com <mailto:valerio.barnabei at gmail.com>> ha scritto:
> Thank you Stefano for your quick answer, I will try to change PC as you suggest, and I will read something about MATIS type. I will let you know if I still have doubts.
>
> Valerio
>
> Il giorno dom 13 gen 2019 alle ore 16:08 Stefano Zampini <stefano.zampini at gmail.com <mailto:stefano.zampini at gmail.com>> ha scritto:
> What problem are you trying to solve?
> For standard elliptic problems (e.g. poisson or elasticity) you should use a preconditioner that scales, for example PCGAMG or BoomerAMG from HYPRE (PCHYPRE, if you configured PETSc with support for HYPRE via --download-hypre)
> Alternatively, since you are using FEM with local Assembly, you can use PCBDDC, but this requires few extra calls
>
> - call MatSetType(K,MATIS)
> - provide an ISLocalToGlobalMapping of local to global degrees of freedom before you set preallocation via MatSetLocalToGlobalMapping (if you provide this call, then you can use MatSetValuesLocal for both AIJ amd MATIS types)
>
>
>
> Il giorno dom 13 gen 2019 alle ore 17:59 Valerio Barnabei via petsc-users <petsc-users at mcs.anl.gov <mailto:petsc-users at mcs.anl.gov>> ha scritto:
> Hello everybody,
>
> I have some doubts about the parallel solution of a simple FEM ksp problem. I searched in the mailing list but the information I found are not helping me.
> I need to control manually the parallel assemble of the main matrix, but I would like to use PetSC for the solution of the final linear system K*U=F.
> The algorithm I am using, loads an already decomposed FEM domain, and each process contributes to the global matrix assembly using its portion of domain decomposition (made in pre-processing). In the element loop, at each element I load the element submatrix in the global matrix via MatSetValue function. Then, out of the element loop, I write
> /*
> ...matrix preallocation
> ...calculate element local stiffness matrix (local in a FEM sense and local in a domain decomposition sense)
> MatSetValue (ADD)
> */
> and then
> ierr=MatAssemblyBegin(K,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
> ierr=MatAssemblyEnd(K,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
> ierr=VecAssemblyBegin(F);CHKERRQ(ierr);
> ierr=VecAssemblyEnd(F);CHKERRQ(ierr);
>
> This part scales perfectly and is sufficiently fast.
> My K matrix is a sort of banded diagonal matrix: my preallocation is not perfect, but it works at this stage of my work.
> Finally I solve the system with the ksp logic:
>
> ierr=KSPCreate(PETSC_COMM_WORLD,&ksp);CHKERRQ(ierr);
> ierr=KSPSetOperators(ksp,K,K);CHKERRQ(ierr);
> ierr=KSPGetPC(ksp,&pc);CHKERRQ(ierr);
> ierr=PCSetType(pc,PCBJACOBI);CHKERRQ(ierr); //or PCNONE, or PCJACOBI, the behaviour is almost identical, the iteration number lowers but is still really high
> ierr=KSPSetTolerances(ksp,1.e-7,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT);CHKERRQ(ierr);
> ierr=KSPSetFromOptions(ksp);CHKERRQ(ierr);
> ierr=KSPSolve(ksp,F,sol);
>
> When I run the code I am noticing some strange behaviours. Indeed, the numerical solution appear right, and the code scales if I make a simple strong-scaling test. However, the ksp_log and log_view (see below, logs for a 160k quad linear element uniform 2dmesh) shows me a huge number of iterations, and the time spent in "solve" function is very high. Furthermore, the more I increase the problem size keeping a constant load per process (weak scaling) the more iterations seems to be needed for convergence. In general, when increasing the problem size (i.e. 16M elements) the convergence is not achieved before the maximum iteration number is achieved.
>
> Question 1: Am I doing it right? Or am I making some trouble with the MPI communication management? (i'm aware that my domain decomposition does not match the petsc matrix decomposition, I'm expecting it to cripple my algorithm a bit)
> Question 2: Why the solver takes so much time and so many iterations? the problem is really simple, and the solution appears correct when plotted. Am I ill conditioning the system?
> Thanks in advance for your help. I can add any further information if needed.
>
> Valerio
>
>
> --
> Stefano
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