[petsc-users] Select a preconditioner for SLEPc eigenvalue solver Jacobi-Davidson

Fande Kong fdkong.jd at gmail.com
Tue Nov 5 11:13:58 CST 2019 

How about I want to determine the ST type on runtime?

 mpirun -n 1 ./ex3  -eps_type jd -st_ksp_type gmres  -st_pc_type none
-eps_view  -eps_target  0 -eps_monitor  -st_ksp_monitor

ST is indeed STPrecond, but the passed preconditioning matrix is still
ignored.

EPS Object: 1 MPI processes
  type: jd
    search subspace is orthogonalized
    block size=1
    type of the initial subspace: non-Krylov
    size of the subspace after restarting: 6
    number of vectors after restarting from the previous iteration: 1
    threshold for changing the target in the correction equation (fix): 0.01
  problem type: symmetric eigenvalue problem
  selected portion of the spectrum: closest to target: 0. (in magnitude)
  number of eigenvalues (nev): 1
  number of column vectors (ncv): 17
  maximum dimension of projected problem (mpd): 17
  maximum number of iterations: 1700
  tolerance: 1e-08
  convergence test: relative to the eigenvalue
BV Object: 1 MPI processes
  type: svec
  17 columns of global length 100
  vector orthogonalization method: classical Gram-Schmidt
  orthogonalization refinement: if needed (eta: 0.7071)
  block orthogonalization method: GS
  doing matmult as a single matrix-matrix product
DS Object: 1 MPI processes
  type: hep
  solving the problem with: Implicit QR method (_steqr)
ST Object: 1 MPI processes
  type: precond
  shift: 0.
  number of matrices: 1
  KSP Object: (st_) 1 MPI processes
    type: gmres
      restart=30, using Classical (unmodified) Gram-Schmidt
Orthogonalization with no iterative refinement
      happy breakdown tolerance 1e-30
    maximum iterations=90, initial guess is zero
    tolerances:  relative=0.0001, absolute=1e-50, divergence=10000.
    left preconditioning
    using PRECONDITIONED norm type for convergence test
  PC Object: (st_) 1 MPI processes
    type: none
    linear system matrix = precond matrix:
    Mat Object: 1 MPI processes
      type: shell
      rows=100, cols=100
 Solution method: jd


Preconding matrix should be a SeqAIJ not shell.


Fande,

On Tue, Nov 5, 2019 at 9:07 AM Jose E. Roman <jroman at dsic.upv.es> wrote:

> Currently, the function that passes the preconditioner matrix is specific
> of STPRECOND, so you have to add
>   ierr = STSetType(st,STPRECOND);CHKERRQ(ierr);
> before
>   ierr = STPrecondSetMatForPC(st,B);CHKERRQ(ierr);
> otherwise this latter call is ignored.
>
> We may be changing a little bit the way in which ST is initialized, and
> maybe we modify this as well. It is not decided yet.
>
> Jose
>
>
> > El 5 nov 2019, a las 0:28, Fande Kong <fdkong.jd at gmail.com> escribió:
> >
> > Thanks Jose,
> >
> > I think I understand now. Another question: what is the right way to
> setup a linear preconditioning matrix for the inner linear solver of JD?
> >
> > I was trying to do something like this:
> >
> >   /*
> >      Create eigensolver context
> >   */
> >   ierr = EPSCreate(PETSC_COMM_WORLD,&eps);CHKERRQ(ierr);
> >
> >   /*
> >      Set operators. In this case, it is a standard eigenvalue problem
> >   */
> >   ierr = EPSSetOperators(eps,A,NULL);CHKERRQ(ierr);
> >   ierr = EPSSetProblemType(eps,EPS_HEP);CHKERRQ(ierr);
> >   ierr = EPSGetST(eps,&st);CHKERRQ(ierr);
> >   ierr = STPrecondSetMatForPC(st,B);CHKERRQ(ierr);
> >
> >   /*
> >      Set solver parameters at runtime
> >   */
> >   ierr = EPSSetFromOptions(eps);CHKERRQ(ierr);
> >
> >   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
> >                       Solve the eigensystem
> >      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
> */
> >
> >   ierr = EPSSolve(eps);CHKERRQ(ierr);
> >
> >
> > But did not work. A complete example is attached.  I could try to dig
> into the code, but you may already know the answer.
> >
> >
> > On Wed, Oct 23, 2019 at 3:58 AM Jose E. Roman <jroman at dsic.upv.es>
> wrote:
> > Yes, it is confusing. Here is the explanation: when you use a target,
> the preconditioner is built from matrix A-sigma*B. By default, instead of
> TARGET_MAGNITUDE we set LARGEST_MAGNITUDE, and in Jacobi-Davidson we treat
> this case by setting sigma=PETSC_MAX_REAL. In this case, the preconditioner
> is built from matrix B. The thing is that in a standard eigenproblem we
> have B=I, and hence there is no point in using a preconditioner, that is
> why we set PCNONE.
> >
> > Jose
> >
> >
> > > El 22 oct 2019, a las 19:57, Fande Kong via petsc-users <
> petsc-users at mcs.anl.gov> escribió:
> > >
> > > Hi All,
> > >
> > > It looks like the preconditioner is hard-coded in the Jacobi-Davidson
> solver. I could not select a preconditioner rather than the default setting.
> > >
> > > For example, I was trying to select LU, but PC NONE was still used.  I
> ran standard example 2 in slepc/src/eps/examples/tutorials, and had the
> following results.
> > >
> > >
> > > Thanks,
> > >
> > > Fande
> > >
> > >
> > > ./ex2 -eps_type jd -st_ksp_type gmres  -st_pc_type lu   -eps_view
> > >
> > > 2-D Laplacian Eigenproblem, N=100 (10x10 grid)
> > >
> > > EPS Object: 1 MPI processes
> > >   type: jd
> > >     search subspace is orthogonalized
> > >     block size=1
> > >     type of the initial subspace: non-Krylov
> > >     size of the subspace after restarting: 6
> > >     number of vectors after restarting from the previous iteration: 1
> > >     threshold for changing the target in the correction equation
> (fix): 0.01
> > >   problem type: symmetric eigenvalue problem
> > >   selected portion of the spectrum: largest eigenvalues in magnitude
> > >   number of eigenvalues (nev): 1
> > >   number of column vectors (ncv): 17
> > >   maximum dimension of projected problem (mpd): 17
> > >   maximum number of iterations: 1700
> > >   tolerance: 1e-08
> > >   convergence test: relative to the eigenvalue
> > > BV Object: 1 MPI processes
> > >   type: svec
> > >   17 columns of global length 100
> > >   vector orthogonalization method: classical Gram-Schmidt
> > >   orthogonalization refinement: if needed (eta: 0.7071)
> > >   block orthogonalization method: GS
> > >   doing matmult as a single matrix-matrix product
> > > DS Object: 1 MPI processes
> > >   type: hep
> > >   solving the problem with: Implicit QR method (_steqr)
> > > ST Object: 1 MPI processes
> > >   type: precond
> > >   shift: 1.79769e+308
> > >   number of matrices: 1
> > >   KSP Object: (st_) 1 MPI processes
> > >     type: gmres
> > >       restart=30, using Classical (unmodified) Gram-Schmidt
> Orthogonalization with no iterative refinement
> > >       happy breakdown tolerance 1e-30
> > >     maximum iterations=90, initial guess is zero
> > >     tolerances:  relative=0.0001, absolute=1e-50, divergence=10000.
> > >     left preconditioning
> > >     using PRECONDITIONED norm type for convergence test
> > >   PC Object: (st_) 1 MPI processes
> > >     type: none
> > >     linear system matrix = precond matrix:
> > >     Mat Object: 1 MPI processes
> > >       type: shell
> > >       rows=100, cols=100
> > >  Solution method: jd
> > >
> > >  Number of requested eigenvalues: 1
> > >  Linear eigensolve converged (1 eigenpair) due to CONVERGED_TOL;
> iterations 20
> > >  ---------------------- --------------------
> > >             k             ||Ax-kx||/||kx||
> > >  ---------------------- --------------------
> > >         7.837972            7.71944e-10
> > >  ---------------------- --------------------
> > >
> > >
> > >
> >
> > <ex3.c>
>
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://lists.mcs.anl.gov/pipermail/petsc-users/attachments/20191105/5039c22e/attachment-0001.html>

More information about the petsc-users mailing list