The function MatMarkDiagonal_SeqAIJ() takes care of this. Matt
On Mon, Apr 27, 2009 at 9:34 AM, SUN Chun <Chun.SUN at 3ds.com> wrote: > Hello, > > I have an update to this problem: > > I found that in MatRelax_SeqAIJ function (mat/impl/aij/seq/aij.c), I have: > > diag = a->diag and: > > diag[i] is has exactly the same value of a->i[i] for each row i. This gives > me n=0 when doing forward pass of zero initial guess. That explains why > setting -pc_sor_forward will give me identical results as if I run pure > DSCG. > > I assume that this a->diag[] stores the sparse column index of diagonal > entries of a matrix. Now it seems to be improperly set. I will pursue this > further in debugger. Do you know which function it should be set during the > assembly process? That would point a short-cut for me.... > > Thanks again! > Chun > > > -----Original Message----- > From: petsc-users-bounces at mcs.anl.gov [mailto: > petsc-users-bounces at mcs.anl.gov] On Behalf Of SUN Chun > Sent: Monday, April 27, 2009 9:13 AM > To: PETSc users list > Subject: SSOR problem > > Hello, > > I have an *particular* Ax=b which I want to solve with CG preconditioned > by SSOR using PETSc. Then some specific strange things happen. Please > allow me to describe all the symptoms that I found here. Thanks for your > help: > > 0) All solves are in serial. > > 1) A 20-line academic code and another matlab code converge the solution > with identical residual history and number of iterations (76), they > match well. If I run without SSOR (just diagonal scaled CG): PETSc, > academic code, and matlab all match well with same number (180) of > iterations. > > 2) PETSc with SSOR seems to give me -8 indefinite pc. If I play with > omega other than using 1.0 (as in Gauss-Seidel), sometimes (with > omega=1.2) I see stagnation and it won't converge then exceeds the > maximum iteration allowed (500). Residuals even don't go down. If I > don't say -ksp_diagonal_scale, I get -8 too. So, PETSc with SSOR either > gives me -8 or -3. > > 3) The above was run with -pc_sor_symmetric. However, if I ran with > -pc_sor_forward, I got a convergence curve identical to what I have > without any preconditioner, with same iterations (180). If I ran with > -pc_sor_backward, it gives me -8 indefinite pc. > > 4) If I increase any of the number of -pc_sor_its (or lits) to 2, it > converges (but still don't match the matlab/academic code). > > 5) The matrix has good condition number (~8000), maximum diagonal is > about 6, minimum diagonal is about 1.1. There's no zero or negative > diagonal entries in this matrix. It's spd otherwise matlab won't be able > to solve it. > > 6) The behavior is independent of rhs. I've tried random rhs and get the > same scenario. > > 7) Here is the confusing part: All other matrices that we have except > for this one can be solved by PETSc with same settings very well. And > they match the academic code and matlab code. It's just this matrix that > exhibits the strange behavior. I tend to eliminate the possibility of > interface problem because all other matrices and other preconditioner > settings work well. > > We're running out of ideas here, if you have any insight please say > anything or point any directions. > > Thanks a lot, > Chun > > > > -- 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/20090427/4ce40fe6/attachment.htm>
