[petsc-users] KSP_CONVERGED_STEP_LENGTH
Harshad Sahasrabudhe
hsahasra at purdue.edu
Tue Sep 13 13:01:40 CDT 2016
Hi Barry,
I compiled with mpich configured using --enable-g=meminit to get rid of MPI
errors in Valgrind. Doing this reduced the number of errors to 2. I have
attached the Valgrind output.
I'm using GAMG+GMRES for in each linear iteration of SNES. The linear
solver converges with CONVERGED_RTOL for the first 6 iterations and
with CONVERGED_STEP_LENGTH after that. I'm still very confused about why
this is happening. Any thoughts/ideas?
Thanks,
Harshad
On Thu, Sep 8, 2016 at 11:26 PM, Barry Smith <bsmith at mcs.anl.gov> wrote:
>
> Install your MPI with --download-mpich as a PETSc ./configure option,
> this will eliminate all the MPICH valgrind errors. Then send as an
> attachment the resulting valgrind file.
>
> I do not 100 % trust any code that produces such valgrind errors.
>
> Barry
>
>
>
> > On Sep 8, 2016, at 10:12 PM, Harshad Sahasrabudhe <hsahasra at purdue.edu>
> wrote:
> >
> > Hi Barry,
> >
> > Thanks for the reply. My code is in C. I ran with Valgrind and found
> many "Conditional jump or move depends on uninitialized value(s)", "Invalid
> read" and "Use of uninitialized value" errors. I think all of them are from
> the libraries I'm using (LibMesh, Boost, MPI, etc.). I'm not really sure
> what I'm looking for in the Valgrind output. At the end of the file, I get:
> >
> > ==40223== More than 10000000 total errors detected. I'm not reporting
> any more.
> > ==40223== Final error counts will be inaccurate. Go fix your program!
> > ==40223== Rerun with --error-limit=no to disable this cutoff. Note
> > ==40223== that errors may occur in your program without prior warning
> from
> > ==40223== Valgrind, because errors are no longer being displayed.
> >
> > Can you give some suggestions on how I should proceed?
> >
> > Thanks,
> > Harshad
> >
> > On Thu, Sep 8, 2016 at 1:59 PM, Barry Smith <bsmith at mcs.anl.gov> wrote:
> >
> > This is very odd. CONVERGED_STEP_LENGTH for KSP is very specialized
> and should never occur with GMRES.
> >
> > Can you run with valgrind to make sure there is no memory corruption?
> http://www.mcs.anl.gov/petsc/documentation/faq.html#valgrind
> >
> > Is your code fortran or C?
> >
> > Barry
> >
> > > On Sep 8, 2016, at 10:38 AM, Harshad Sahasrabudhe <hsahasra at purdue.edu>
> wrote:
> > >
> > > Hi,
> > >
> > > I'm using GAMG + GMRES for my Poisson problem. The solver converges
> with KSP_CONVERGED_STEP_LENGTH at a residual of 9.773346857844e-02, which
> is much higher than what I need (I need a tolerance of at least 1E-8). I am
> not able to figure out which tolerance I need to set to avoid convergence
> due to CONVERGED_STEP_LENGTH.
> > >
> > > Any help is appreciated! Output of -ksp_view and -ksp_monitor:
> > >
> > > 0 KSP Residual norm 3.121347818142e+00
> > > 1 KSP Residual norm 9.773346857844e-02
> > > Linear solve converged due to CONVERGED_STEP_LENGTH iterations 1
> > > KSP Object: 1 MPI processes
> > > type: gmres
> > > GMRES: restart=30, using Classical (unmodified) Gram-Schmidt
> Orthogonalization with no iterative refinement
> > > GMRES: happy breakdown tolerance 1e-30
> > > maximum iterations=10000, initial guess is zero
> > > tolerances: relative=1e-08, absolute=1e-50, divergence=10000
> > > left preconditioning
> > > using PRECONDITIONED norm type for convergence test
> > > PC Object: 1 MPI processes
> > > type: gamg
> > > MG: type is MULTIPLICATIVE, levels=2 cycles=v
> > > Cycles per PCApply=1
> > > Using Galerkin computed coarse grid matrices
> > > Coarse grid solver -- level -------------------------------
> > > KSP Object: (mg_coarse_) 1 MPI processes
> > > type: preonly
> > > maximum iterations=1, initial guess is zero
> > > tolerances: relative=1e-05, absolute=1e-50, divergence=10000
> > > left preconditioning
> > > using NONE norm type for convergence test
> > > PC Object: (mg_coarse_) 1 MPI processes
> > > type: bjacobi
> > > block Jacobi: number of blocks = 1
> > > Local solve is same for all blocks, in the following KSP and
> PC objects:
> > > KSP Object: (mg_coarse_sub_) 1 MPI processes
> > > type: preonly
> > > maximum iterations=1, initial guess is zero
> > > tolerances: relative=1e-05, absolute=1e-50, divergence=10000
> > > left preconditioning
> > > using NONE norm type for convergence test
> > > PC Object: (mg_coarse_sub_) 1 MPI processes
> > > type: lu
> > > LU: out-of-place factorization
> > > tolerance for zero pivot 2.22045e-14
> > > using diagonal shift on blocks to prevent zero pivot
> [INBLOCKS]
> > > matrix ordering: nd
> > > factor fill ratio given 5, needed 1.91048
> > > Factored matrix follows:
> > > Mat Object: 1 MPI processes
> > > type: seqaij
> > > rows=284, cols=284
> > > package used to perform factorization: petsc
> > > total: nonzeros=7726, allocated nonzeros=7726
> > > total number of mallocs used during MatSetValues
> calls =0
> > > using I-node routines: found 133 nodes, limit used
> is 5
> > > linear system matrix = precond matrix:
> > > Mat Object: 1 MPI processes
> > > type: seqaij
> > > rows=284, cols=284
> > > total: nonzeros=4044, allocated nonzeros=4044
> > > total number of mallocs used during MatSetValues calls =0
> > > not using I-node routines
> > > linear system matrix = precond matrix:
> > > Mat Object: 1 MPI processes
> > > type: seqaij
> > > rows=284, cols=284
> > > total: nonzeros=4044, allocated nonzeros=4044
> > > total number of mallocs used during MatSetValues calls =0
> > > not using I-node routines
> > > Down solver (pre-smoother) on level 1 ------------------------------
> -
> > > KSP Object: (mg_levels_1_) 1 MPI processes
> > > type: chebyshev
> > > Chebyshev: eigenvalue estimates: min = 0.195339, max = 4.10212
> > > maximum iterations=2
> > > tolerances: relative=1e-05, absolute=1e-50, divergence=10000
> > > left preconditioning
> > > using nonzero initial guess
> > > using NONE norm type for convergence test
> > > PC Object: (mg_levels_1_) 1 MPI processes
> > > type: sor
> > > SOR: type = local_symmetric, iterations = 1, local iterations
> = 1, omega = 1
> > > linear system matrix = precond matrix:
> > > Mat Object: () 1 MPI processes
> > > type: seqaij
> > > rows=9036, cols=9036
> > > total: nonzeros=192256, allocated nonzeros=192256
> > > total number of mallocs used during MatSetValues calls =0
> > > not using I-node routines
> > > Up solver (post-smoother) same as down solver (pre-smoother)
> > > linear system matrix = precond matrix:
> > > Mat Object: () 1 MPI processes
> > > type: seqaij
> > > rows=9036, cols=9036
> > > total: nonzeros=192256, allocated nonzeros=192256
> > > total number of mallocs used during MatSetValues calls =0
> > > not using I-node routines
> > >
> > > Thanks,
> > > Harshad
> >
> >
>
>
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