Does the direct solver work in parallel? Because when I try it with more than 1 processor, I get:
[0]PETSC ERROR: MatCholeskyFactorSymbolic() line 2319 in src/mat/interface/matrix.c [0]PETSC ERROR: No support for this operation for this object type! [0]PETSC ERROR: Mat type mpisbaij! [0]PETSC ERROR: PCSetUp_Cholesky() line 237 in src/ksp/pc/impls/factor/cholesky/cholesky.c [0]PETSC ERROR: PCSetUp() line 798 in src/ksp/pc/interface/precon.c [0]PETSC ERROR: KSPSetUp() line 234 in src/ksp/ksp/interface/itfunc.c [0]PETSC ERROR: KSPSolve() line 334 in src/ksp/ksp/interface/itfunc.c [1]PETSC ERROR: MatCholeskyFactorSymbolic() line 2319 in src/mat/interface/matrix.c [1]PETSC ERROR: No support for this operation for this object type! [1]PETSC ERROR: Mat type mpisbaij! [1]PETSC ERROR: PCSetUp_Cholesky() line 237 in src/ksp/pc/impls/factor/cholesky/cholesky.c [1]PETSC ERROR: PCSetUp() line 798 in src/ksp/pc/interface/precon.c [1]PETSC ERROR: KSPSetUp() line 234 in src/ksp/ksp/interface/itfunc.c [1]PETSC ERROR: KSPSolve() line 334 in src/ksp/ksp/interface/itfunc.c Billy. Quoting Hong Zhang <hzhang at mcs.anl.gov>: > > > Which solvers are more appropriate for symmetric matrices? > > Iterative solvers: ksp_type cg, pc_type icc > Direct solvers: ksp_type preonly, pc_type cc > > Non-symmetric solvers also work, but the above solvers > are more efficient in general. > > You can run petsc code with various ksp/pc combinations, > and use the option '-log_summary' to evaluate the performance. > Using '-help' to see all solver options. > > Hong > >
