petsc-3.7.7 2017-09-25
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A matrix type providing direct solvers (LU and Cholesky) for distributed and sequential matrices via the external package MUMPS. Works with MATAIJ and MATSBAIJ matrices

Use ./configure --download-mumps --download-scalapack --download-parmetis --download-metis --download-ptscotch to have PETSc installed with MUMPS

Use -pc_type cholesky or lu -pc_factor_mat_solver_package mumps to us this direct solver

Options Database Keys

-mat_mumps_icntl_1 - ICNTL(1): output stream for error messages
-mat_mumps_icntl_2 - ICNTL(2): output stream for diagnostic printing, statistics, and warning
-mat_mumps_icntl_3 - ICNTL(3): output stream for global information, collected on the host
-mat_mumps_icntl_4 - ICNTL(4): level of printing (0 to 4)
-mat_mumps_icntl_6 - ICNTL(6): permutes to a zero-free diagonal and/or scale the matrix (0 to 7)
-mat_mumps_icntl_7 - ICNTL(7): computes a symmetric permutation in sequential analysis (0 to 7). 3=Scotch, 4=PORD, 5=Metis
-mat_mumps_icntl_8 - ICNTL(8): scaling strategy (-2 to 8 or 77)
-mat_mumps_icntl_10 - ICNTL(10): max num of refinements
-mat_mumps_icntl_11 - ICNTL(11): statistics related to an error analysis (via -ksp_view)
-mat_mumps_icntl_12 - ICNTL(12): an ordering strategy for symmetric matrices (0 to 3)
-mat_mumps_icntl_13 - ICNTL(13): parallelism of the root node (enable ScaLAPACK) and its splitting
-mat_mumps_icntl_14 - ICNTL(14): percentage increase in the estimated working space
-mat_mumps_icntl_19 - ICNTL(19): computes the Schur complement
-mat_mumps_icntl_22 - ICNTL(22): in-core/out-of-core factorization and solve (0 or 1)
-mat_mumps_icntl_23 - ICNTL(23): max size of the working memory (MB) that can allocate per processor
-mat_mumps_icntl_24 - ICNTL(24): detection of null pivot rows (0 or 1)
-mat_mumps_icntl_25 - ICNTL(25): compute a solution of a deficient matrix and a null space basis
-mat_mumps_icntl_26 - ICNTL(26): drives the solution phase if a Schur complement matrix
-mat_mumps_icntl_28 - ICNTL(28): use 1 for sequential analysis and ictnl(7) ordering, or 2 for parallel analysis and ictnl(29) ordering
-mat_mumps_icntl_29 - ICNTL(29): parallel ordering 1 = ptscotch, 2 = parmetis
-mat_mumps_icntl_30 - ICNTL(30): compute user-specified set of entries in inv(A)
-mat_mumps_icntl_31 - ICNTL(31): indicates which factors may be discarded during factorization
-mat_mumps_icntl_33 - ICNTL(33): compute determinant
-mat_mumps_cntl_1 - CNTL(1): relative pivoting threshold
-mat_mumps_cntl_2 - CNTL(2): stopping criterion of refinement
-mat_mumps_cntl_3 - CNTL(3): absolute pivoting threshold
-mat_mumps_cntl_4 - CNTL(4): value for static pivoting
-mat_mumps_cntl_5 - CNTL(5): fixation for null pivots

Notes: When a MUMPS factorization fails inside a KSP solve, for example with a KSP_DIVERGED_PCSETUP_FAILED, one can find the MUMPS information about the failure by calling

         MatMumpsGetInfog(mat,....); etc.
Or you can run with -ksp_error_if_not_converged and the program will be stopped and the information printed in the error message.

See Also

PCFactorSetMatSolverPackage(), MatSolverPackage, MatMumpsSetICntl(), MatMumpsGetIcntl(), MatMumpsSetCntl(), MatMumpsGetCntl(), MatMumpsGetInfo(), MatMumpsGetInfog(), MatMumpsGetRinfo(), MatMumpsGetRinfog(), KSPGetPC(), PCGetFactor(), PCFactorGetMatrix()

Index of all Mat routines
Table of Contents for all manual pages
Index of all manual pages