On Wed, Apr 9, 2008 at 3:25 PM, Shi Jin <jinzishuai at yahoo.com> wrote: > Thank you very much. > > > > > > Is there something particular about this rowsum method? > > > > No. If you use a -ksp_rtol of 1.e-12 and still get different > > answers, this needs to be investigated. > > > > > > I have tried even with -ksp_rtol 1.e-20 but still got different results. > > Here is what I got when solving the mass matrix with > > -pc_type jacobi > -pc_jacobi_rowsum 1 > -ksp_type cg > -sub_pc_type icc > -ksp_rtol 1.e-20 > -ksp_monitor > -ksp_view > > 0 KSP Residual norm 2.975203858623e+00 > 1 KSP Residual norm 2.674371671721e-01 > 2 KSP Residual norm 1.841074927355e-01 > KSP Object: > type: cg > maximum iterations=10000, initial guess is zero > tolerances: relative=1e-20, absolute=1e-50, divergence=10000 > left preconditioning > PC Object: > type: jacobi > linear system matrix = precond matrix: > Matrix Object: > type=seqaij, rows=8775, cols=8775 > total: nonzeros=214591, allocated nonzeros=214591 > not using I-node routines > > I realize that the iteration ended when the residual norm is quite large. > Do you think this indicates something wrong here?
Can you run with -ksp_converged_reason It appears that the solve fails rather than terminates with an answer. Is it possible that your matrix is not SPD? Matt > Thank you again. > > Shi > > > > __________________________________________________ > Do You Yahoo!? > Tired of spam? Yahoo! Mail has the best spam protection around > http://mail.yahoo.com > > -- 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
