On Tue, May 1, 2012 at 6:12 PM, Karthik Duraisamy <dkarthik at stanford.edu>wrote:
> Hello Barry, > > Thank you for your super quick response. I have attached the output of > ksp_view and it is practically the same as that when I don't use PCMG. The > part I don't understand is how PCMG able to function at the zero grid level > and still produce a much better convergence than when using the default PC. > Is there any additional smoothing or interpolation going on? > You only included one output, so I have no way of knowing what you used before. However, this is running GMRES/ILU. > Also, for Algebraic Multigrid, would you recommend BoomerAMG or ML ? > They are different algorithms. Its not possible to say generally that one is better. Try them both. Matt > Best regards, > Karthik. > > type: mg > MG: type is MULTIPLICATIVE, levels=1 cycles=v > Cycles per PCApply=1 > Not using Galerkin computed coarse grid matrices > Coarse grid solver -- level ------------------------------- > KSP Object: (mg_levels_0_) 8 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=1, initial guess is zero > tolerances: relative=1e-05, absolute=1e-50, divergence=10000 > left preconditioning > using PRECONDITIONED norm type for convergence test > PC Object: (mg_levels_0_) 8 MPI processes > type: bjacobi > block Jacobi: number of blocks = 8 > Local solve is same for all blocks, in the following KSP and PC > objects: > KSP Object: (mg_levels_0_sub_) 1 MPI processes > type: preonly > maximum iterations=10000, 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_levels_0_sub_) 1 MPI processes > type: ilu > ILU: out-of-place factorization > 0 levels of fill > tolerance for zero pivot 1e-12 > using diagonal shift to prevent zero pivot > matrix ordering: natural > factor fill ratio given 1, needed 1 > Factored matrix follows: > Matrix Object: 1 MPI processes > type: seqaij > rows=9015, cols=9015 > package used to perform factorization: petsc > total: nonzeros=517777, allocated nonzeros=517777 > total number of mallocs used during MatSetValues calls =0 > using I-node routines: found 3476 nodes, limit used is 5 > linear system matrix = precond matrix: > Matrix Object: 1 MPI processes > type: seqaij > rows=9015, cols=9015 > total: nonzeros=517777, allocated nonzeros=517777 > total number of mallocs used during MatSetValues calls =0 > using I-node routines: found 3476 nodes, limit used is 5 > linear system matrix = precond matrix: > Matrix Object: 8 MPI processes > type: mpiaij > rows=75000, cols=75000 > total: nonzeros=4427800, allocated nonzeros=4427800 > total number of mallocs used during MatSetValues calls =0 > using I-node (on process 0) routines: found 3476 nodes, limit > used is 5 > linear system matrix = precond matrix: > Matrix Object: 8 MPI processes > type: mpiaij > rows=75000, cols=75000 > total: nonzeros=4427800, allocated nonzeros=4427800 > total number of mallocs used during MatSetValues calls =0 > using I-node (on process 0) routines: found 3476 nodes, limit used is > 5 > > > > ----- Original Message ----- > From: "Barry Smith" <bsmith at mcs.anl.gov> > To: "PETSc users list" <petsc-users at mcs.anl.gov> > Sent: Tuesday, May 1, 2012 1:39:26 PM > Subject: Re: [petsc-users] Multigrid > > > On May 1, 2012, at 3:37 PM, Karthik Duraisamy wrote: > > > Hello, > > > > I have been using PETSc for a couple of years with good success, > but lately as my linear problems have become stiffer (condition numbers of > the order of 1.e20), I am looking to use better preconditioners. I tried > using PCMG with all the default options (i.e., I just specified my > preconditioner as PCMG and did not add any options to it) and I am > immediately seeing better convergence. > > > > What I am not sure of is why? I would like to know more about the > default parameters (the manual is not very explicit) and more importantly, > want to know why it is working even when I haven't specified any grid > levels and coarse grid operators. Any > > help in this regard will be appreciated. > > First run with -ksp_view to see what solver it is actually using. > > Barry > > > > > Also, ultimately I want to use algebraic multigrid so is PCML a > better option than BoomerAMG? I tried BoomerAMG with mixed results. > > > > Thanks, > > Karthik > > > > > > > > -- > > > > ======================================= > > Karthik Duraisamy > > Assistant Professor (Consulting) > > Durand Building Rm 357 > > Dept of Aeronautics and Astronautics > > Stanford University > > Stanford CA 94305 > > > > Phone: 650-721-2835 > > Web: www.stanford.edu/~dkarthik > > ======================================= > > -- What most experimenters take for granted before they begin their experiments is infinitely more interesting than any results to which their experiments lead. -- Norbert Wiener -------------- next part -------------- An HTML attachment was scrubbed... URL: <http://lists.mcs.anl.gov/pipermail/petsc-users/attachments/20120501/c6ac9a02/attachment.htm>
