[petsc-users] Reuse symbolic factorization with petsc - mumps

[Thibault Faney]

Thank you this works perfectly.


On Thu, Mar 14, 2013 at 4:20 PM, Hong Zhang <hzhang at mcs.anl.gov> wrote:

> On Thu, Mar 14, 2013 at 2:52 PM, Thibault Faney <tibo at berkeley.edu> wrote:
> > Hong:
> >
> > thank you for your answer.
> > I can replace DIFFERENT_NONZERO_PATTERN by SAME_NONZERO_PATTERN, however
> > this will give me the wrong answer as the zero pattern changes from a
> time
> > step to another (e.g. the matrix A at time step 1 has more zeros than at
> > time step 2) . What I can precompute is the maximal non-zero pattern. Do
> you
> > mean I should compute the facorization for the maximal zero pattern
> before
> > time iterations and then use SAME_NONZERO_PATTERN during the iterations ?
>
> Yes.
> Hong
> >
> >
> > On Thu, Mar 14, 2013 at 3:29 PM, Hong Zhang <hzhang at mcs.anl.gov> wrote:
> >>
> >> Tibo:
> >>
> >> Replace
> >> call KSPSetOperators(KSP_A, A, A, DIFFERENT_NONZERO_PATTERN, ierr)
> >> with
> >> call KSPSetOperators(KSP_A, A, A, SAME_NONZERO_PATTERN, ierr)
> >>
> >> Run your code with option '-log_summary' to see the number of calling
> >> MatLUSymbolic() and MatLUNumeric().
> >>
> >> Hong
> >>
> >> >
> >> > I am using the cray-petsc implementation on the NERSC system.
> >> > Specifically,
> >> > I have implemented a runge kutta solver, and I need to solve a linear
> >> > system
> >> > Ax = b several times per time step. I am using PETSC to interface with
> >> > the
> >> > MUMPS solver for direct factorization.
> >> >
> >> > The matrix A is constant over a whole time step, but changes at each
> >> > time
> >> > step. What I do now is that at the beginning of each time step, I
> >> > compute
> >> > the matrix A, use the MUMPS solver to compute a LU factorization of A,
> >> > and
> >> > then use KSPSolve to solve each linear system during the same time
> step.
> >> > Here is an example of the succession of calls (inspired from example
> >> > ex52.c):
> >> >
> >> > Once per time step:
> >> > call KSPSetOperators(KSP_A, A, A, DIFFERENT_NONZERO_PATTERN, ierr)
> >> > call KSPSetType(KSP_A, KSPPREONLY, ierr);
> >> > call KSPGetPC(KSP_A, PC_A, ierr)
> >> > call KSPSetTolerances(KSP_A, 1.d-20, PETSC_DEFAULT_DOUBLE_PRECISION,
> >> > PETSC_DEFAULT_DOUBLE_PRECISION, PETSC_DEFAULT_INTEGER, ierr)
> >> > call PCSetType(PC_A, PCLU, ierr)
> >> > call PCFactorSetMatSolverPackage(PC_A, MATSOLVERMUMPS, ierr)
> >> > call PCFactorSetUpMatSolverPackage(PC_A, ierr)
> >> > call PCFactorGetMatrix(PC_A, PC_A, ierr)
> >> > call MatMumpsSetIcntl(PC_A, 7, 5, ierr)
> >> > call PCSetup(PC_A, ierr)
> >> > call KSPSetUp(KSP_A, ierr)
> >> >
> >> > Then several times per time step:
> >> > call KSPSolve( KSP_A, b, x, ierr)
> >> >
> >> > This works fine.
> >> > However, I am able to precompute the maximal sparsity pattern of A
> >> > before
> >> > the time iterations. Therefore, I would like to use this information
> by
> >> > precomputing the symbolic factorization before the time iterations
> >> > start,
> >> > and only compute the numerical factorization at each time step. Is
> there
> >> > a
> >> > way to use MUMPS in PETSC to do this ? I would appreciate any
> >> > help/reference
> >> > on this topic.
> >> >
> >> > Thank you,
> >> >
> >> > Tibo
> >
> >
>
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