[petsc-users] Using PCFIELDSPLIT with -pc_fieldsplit_type schur
Matthew Knepley
knepley at gmail.com
Wed Jan 11 21:21:05 CST 2017
On Wed, Jan 11, 2017 at 8:31 PM, Barry Smith <bsmith at mcs.anl.gov> wrote:
>
> Thanks, this is very useful information. It means that
>
> 1) the approximate Sp is actually a very good approximation to the true
> Schur complement S, since using Sp^-1 to precondition S gives iteration
> counts from 8 to 13.
>
> 2) using ilu(0) as a preconditioner for Sp is not good, since replacing
> Sp^-1 with ilu(0) of Sp gives absurd iteration counts. This is actually not
> super surprising since ilu(0) is generally "not so good" for elasticity.
>
> So the next step is to try using -fieldsplit_FE_split_ksp_monitor
> -fieldsplit_FE_split_pc_type gamg
>
> the one open question is if any options should be passed to the gamg to
> tell it that the underly problem comes from "elasticity"; that is something
> about the null space.
>
> Mark Adams, since the GAMG is coming from inside another preconditioner
> it may not be easy for the easy for the user to attach the near null space
> to that inner matrix. Would it make sense for there to be a GAMG command
> line option to indicate that it is a 3d elasticity problem so GAMG could
> set up the near null space for itself? or does that not make sense?
>
We could do that if somehow we knew the problem geometry, which is the
origin of Mark's PCSetCoordinates() interface.
Matt
> Barry
>
>
>
> > On Jan 11, 2017, at 7:47 PM, David Knezevic <david.knezevic at akselos.com>
> wrote:
> >
> > I've attached the two log files. Using cholesky for "FE_split" seems to
> have helped a lot!
> >
> > David
> >
> >
> > --
> > David J. Knezevic | CTO
> > Akselos | 210 Broadway, #201 | Cambridge, MA | 02139
> >
> > Phone: +1-617-599-4755
> >
> > This e-mail and any attachments may contain confidential material for
> the sole use of the intended recipient(s). Any review or distribution by
> others is strictly prohibited. If you are not the intended recipient,
> please contact the sender and delete all copies.
> >
> > On Wed, Jan 11, 2017 at 8:32 PM, Barry Smith <bsmith at mcs.anl.gov> wrote:
> >
> > Can you please run with all the monitoring on? So we can see the
> convergence of all the inner solvers
> > -fieldsplit_FE_split_ksp_monitor
> >
> > Then run again with
> >
> > -fieldsplit_FE_split_ksp_monitor -fieldsplit_FE_split_pc_type cholesky
> >
> >
> > and send both sets of results
> >
> > Barry
> >
> >
> > > On Jan 11, 2017, at 6:32 PM, David Knezevic <
> david.knezevic at akselos.com> wrote:
> > >
> > > On Wed, Jan 11, 2017 at 5:52 PM, Dave May <dave.mayhem23 at gmail.com>
> wrote:
> > > so I gather that I'll have to look into a user-defined approximation
> to S.
> > >
> > > Where does the 2x2 block system come from?
> > > Maybe someone on the list knows the right approximation to use for S.
> > >
> > > The model is 3D linear elasticity using a finite element
> discretization. I applied substructuring to part of the system to
> "condense" it, and that results in the small A00 block. The A11 block is
> just standard 3D elasticity; no substructuring was applied there. There are
> constraints to connect the degrees of freedom on the interface of the
> substructured and non-substructured regions.
> > >
> > > If anyone has suggestions for a good way to precondition this type of
> system, I'd be most appreciative!
> > >
> > > Thanks,
> > > David
> > >
> > >
> > >
> > > -----------------------------------------
> > >
> > > 0 KSP Residual norm 5.405528187695e+04
> > > 1 KSP Residual norm 2.187814910803e+02
> > > 2 KSP Residual norm 1.019051577515e-01
> > > 3 KSP Residual norm 4.370464012859e-04
> > > KSP Object: 1 MPI processes
> > > type: cg
> > > maximum iterations=1000
> > > tolerances: relative=1e-06, absolute=1e-50, divergence=10000.
> > > left preconditioning
> > > using nonzero initial guess
> > > using PRECONDITIONED norm type for convergence test
> > > PC Object: 1 MPI processes
> > > type: fieldsplit
> > > FieldSplit with Schur preconditioner, factorization FULL
> > > Preconditioner for the Schur complement formed from Sp, an
> assembled approximation to S, which uses (lumped, if requested) A00's
> diagonal's inverse
> > > Split info:
> > > Split number 0 Defined by IS
> > > Split number 1 Defined by IS
> > > KSP solver for A00 block
> > > KSP Object: (fieldsplit_RB_split_) 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: (fieldsplit_RB_split_) 1 MPI processes
> > > type: cholesky
> > > Cholesky: out-of-place factorization
> > > tolerance for zero pivot 2.22045e-14
> > > matrix ordering: natural
> > > factor fill ratio given 0., needed 0.
> > > Factored matrix follows:
> > > Mat Object: 1 MPI processes
> > > type: seqaij
> > > rows=324, cols=324
> > > package used to perform factorization: mumps
> > > total: nonzeros=3042, allocated nonzeros=3042
> > > total number of mallocs used during MatSetValues calls
> =0
> > > MUMPS run parameters:
> > > SYM (matrix type): 2
> > > PAR (host participation): 1
> > > ICNTL(1) (output for error): 6
> > > ICNTL(2) (output of diagnostic msg): 0
> > > ICNTL(3) (output for global info): 0
> > > ICNTL(4) (level of printing): 0
> > > ICNTL(5) (input mat struct): 0
> > > ICNTL(6) (matrix prescaling): 7
> > > ICNTL(7) (sequentia matrix ordering):7
> > > ICNTL(8) (scalling strategy): 77
> > > ICNTL(10) (max num of refinements): 0
> > > ICNTL(11) (error analysis): 0
> > > ICNTL(12) (efficiency control):
> 0
> > > ICNTL(13) (efficiency control):
> 0
> > > ICNTL(14) (percentage of estimated workspace
> increase): 20
> > > ICNTL(18) (input mat struct):
> 0
> > > ICNTL(19) (Shur complement info):
> 0
> > > ICNTL(20) (rhs sparse pattern):
> 0
> > > ICNTL(21) (solution struct):
> 0
> > > ICNTL(22) (in-core/out-of-core facility):
> 0
> > > ICNTL(23) (max size of memory can be allocated
> locally):0
> > > ICNTL(24) (detection of null pivot rows):
> 0
> > > ICNTL(25) (computation of a null space basis):
> 0
> > > ICNTL(26) (Schur options for rhs or solution):
> 0
> > > ICNTL(27) (experimental parameter):
> -24
> > > ICNTL(28) (use parallel or sequential ordering):
> 1
> > > ICNTL(29) (parallel ordering):
> 0
> > > ICNTL(30) (user-specified set of entries in
> inv(A)): 0
> > > ICNTL(31) (factors is discarded in the solve
> phase): 0
> > > ICNTL(33) (compute determinant):
> 0
> > > CNTL(1) (relative pivoting threshold): 0.01
> > > CNTL(2) (stopping criterion of refinement):
> 1.49012e-08
> > > CNTL(3) (absolute pivoting threshold): 0.
> > > CNTL(4) (value of static pivoting): -1.
> > > CNTL(5) (fixation for null pivots): 0.
> > > RINFO(1) (local estimated flops for the
> elimination after analysis):
> > > [0] 29394.
> > > RINFO(2) (local estimated flops for the assembly
> after factorization):
> > > [0] 1092.
> > > RINFO(3) (local estimated flops for the
> elimination after factorization):
> > > [0] 29394.
> > > INFO(15) (estimated size of (in MB) MUMPS internal
> data for running numerical factorization):
> > > [0] 1
> > > INFO(16) (size of (in MB) MUMPS internal data used
> during numerical factorization):
> > > [0] 1
> > > INFO(23) (num of pivots eliminated on this
> processor after factorization):
> > > [0] 324
> > > RINFOG(1) (global estimated flops for the
> elimination after analysis): 29394.
> > > RINFOG(2) (global estimated flops for the assembly
> after factorization): 1092.
> > > RINFOG(3) (global estimated flops for the
> elimination after factorization): 29394.
> > > (RINFOG(12) RINFOG(13))*2^INFOG(34) (determinant):
> (0.,0.)*(2^0)
> > > INFOG(3) (estimated real workspace for factors on
> all processors after analysis): 3888
> > > INFOG(4) (estimated integer workspace for factors
> on all processors after analysis): 2067
> > > INFOG(5) (estimated maximum front size in the
> complete tree): 12
> > > INFOG(6) (number of nodes in the complete tree): 53
> > > INFOG(7) (ordering option effectively use after
> analysis): 2
> > > INFOG(8) (structural symmetry in percent of the
> permuted matrix after analysis): 100
> > > INFOG(9) (total real/complex workspace to store
> the matrix factors after factorization): 3888
> > > INFOG(10) (total integer space store the matrix
> factors after factorization): 2067
> > > INFOG(11) (order of largest frontal matrix after
> factorization): 12
> > > INFOG(12) (number of off-diagonal pivots): 0
> > > INFOG(13) (number of delayed pivots after
> factorization): 0
> > > INFOG(14) (number of memory compress after
> factorization): 0
> > > INFOG(15) (number of steps of iterative refinement
> after solution): 0
> > > INFOG(16) (estimated size (in MB) of all MUMPS
> internal data for factorization after analysis: value on the most memory
> consuming processor): 1
> > > INFOG(17) (estimated size of all MUMPS internal
> data for factorization after analysis: sum over all processors): 1
> > > INFOG(18) (size of all MUMPS internal data
> allocated during factorization: value on the most memory consuming
> processor): 1
> > > INFOG(19) (size of all MUMPS internal data
> allocated during factorization: sum over all processors): 1
> > > INFOG(20) (estimated number of entries in the
> factors): 3042
> > > INFOG(21) (size in MB of memory effectively used
> during factorization - value on the most memory consuming processor): 1
> > > INFOG(22) (size in MB of memory effectively used
> during factorization - sum over all processors): 1
> > > INFOG(23) (after analysis: value of ICNTL(6)
> effectively used): 5
> > > INFOG(24) (after analysis: value of ICNTL(12)
> effectively used): 1
> > > INFOG(25) (after factorization: number of pivots
> modified by static pivoting): 0
> > > INFOG(28) (after factorization: number of null
> pivots encountered): 0
> > > INFOG(29) (after factorization: effective number
> of entries in the factors (sum over all processors)): 3042
> > > INFOG(30, 31) (after solution: size in Mbytes of
> memory used during solution phase): 0, 0
> > > INFOG(32) (after analysis: type of analysis done):
> 1
> > > INFOG(33) (value used for ICNTL(8)): -2
> > > INFOG(34) (exponent of the determinant if
> determinant is requested): 0
> > > linear system matrix = precond matrix:
> > > Mat Object: (fieldsplit_RB_split_) 1 MPI
> processes
> > > type: seqaij
> > > rows=324, cols=324
> > > total: nonzeros=5760, allocated nonzeros=5760
> > > total number of mallocs used during MatSetValues calls =0
> > > using I-node routines: found 108 nodes, limit used is 5
> > > KSP solver for S = A11 - A10 inv(A00) A01
> > > KSP Object: (fieldsplit_FE_split_) 1 MPI processes
> > > type: cg
> > > maximum iterations=10000, initial guess is zero
> > > tolerances: relative=1e-05, absolute=1e-50, divergence=10000.
> > > left preconditioning
> > > using PRECONDITIONED norm type for convergence test
> > > PC Object: (fieldsplit_FE_split_) 1 MPI processes
> > > type: bjacobi
> > > block Jacobi: number of blocks = 1
> > > Local solve is same for all blocks, in the following KSP and
> PC objects:
> > > KSP Object: (fieldsplit_FE_split_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: (fieldsplit_FE_split_sub_) 1
> MPI processes
> > > type: ilu
> > > ILU: out-of-place factorization
> > > 0 levels of fill
> > > tolerance for zero pivot 2.22045e-14
> > > matrix ordering: natural
> > > factor fill ratio given 1., needed 1.
> > > Factored matrix follows:
> > > Mat Object: 1 MPI processes
> > > type: seqaij
> > > rows=28476, cols=28476
> > > package used to perform factorization: petsc
> > > total: nonzeros=1037052, allocated nonzeros=1037052
> > > total number of mallocs used during MatSetValues
> calls =0
> > > using I-node routines: found 9489 nodes, limit
> used is 5
> > > linear system matrix = precond matrix:
> > > Mat Object: 1 MPI processes
> > > type: seqaij
> > > rows=28476, cols=28476
> > > total: nonzeros=1037052, allocated nonzeros=1037052
> > > total number of mallocs used during MatSetValues calls =0
> > > using I-node routines: found 9489 nodes, limit used is
> 5
> > > linear system matrix followed by preconditioner matrix:
> > > Mat Object: (fieldsplit_FE_split_) 1 MPI
> processes
> > > type: schurcomplement
> > > rows=28476, cols=28476
> > > Schur complement A11 - A10 inv(A00) A01
> > > A11
> > > Mat Object: (fieldsplit_FE_split_)
> 1 MPI processes
> > > type: seqaij
> > > rows=28476, cols=28476
> > > total: nonzeros=1017054, allocated nonzeros=1017054
> > > total number of mallocs used during MatSetValues calls
> =0
> > > using I-node routines: found 9492 nodes, limit used
> is 5
> > > A10
> > > Mat Object: 1 MPI processes
> > > type: seqaij
> > > rows=28476, cols=324
> > > total: nonzeros=936, allocated nonzeros=936
> > > total number of mallocs used during MatSetValues calls
> =0
> > > using I-node routines: found 5717 nodes, limit used
> is 5
> > > KSP of A00
> > > KSP Object: (fieldsplit_RB_split_)
> 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: (fieldsplit_RB_split_)
> 1 MPI processes
> > > type: cholesky
> > > Cholesky: out-of-place factorization
> > > tolerance for zero pivot 2.22045e-14
> > > matrix ordering: natural
> > > factor fill ratio given 0., needed 0.
> > > Factored matrix follows:
> > > Mat Object: 1 MPI processes
> > > type: seqaij
> > > rows=324, cols=324
> > > package used to perform factorization: mumps
> > > total: nonzeros=3042, allocated nonzeros=3042
> > > total number of mallocs used during
> MatSetValues calls =0
> > > MUMPS run parameters:
> > > SYM (matrix type): 2
> > > PAR (host participation): 1
> > > ICNTL(1) (output for error): 6
> > > ICNTL(2) (output of diagnostic msg): 0
> > > ICNTL(3) (output for global info): 0
> > > ICNTL(4) (level of printing): 0
> > > ICNTL(5) (input mat struct): 0
> > > ICNTL(6) (matrix prescaling): 7
> > > ICNTL(7) (sequentia matrix ordering):7
> > > ICNTL(8) (scalling strategy): 77
> > > ICNTL(10) (max num of refinements): 0
> > > ICNTL(11) (error analysis): 0
> > > ICNTL(12) (efficiency control):
> 0
> > > ICNTL(13) (efficiency control):
> 0
> > > ICNTL(14) (percentage of estimated
> workspace increase): 20
> > > ICNTL(18) (input mat struct):
> 0
> > > ICNTL(19) (Shur complement info):
> 0
> > > ICNTL(20) (rhs sparse pattern):
> 0
> > > ICNTL(21) (solution struct):
> 0
> > > ICNTL(22) (in-core/out-of-core facility):
> 0
> > > ICNTL(23) (max size of memory can be
> allocated locally):0
> > > ICNTL(24) (detection of null pivot rows):
> 0
> > > ICNTL(25) (computation of a null space
> basis): 0
> > > ICNTL(26) (Schur options for rhs or
> solution): 0
> > > ICNTL(27) (experimental parameter):
> -24
> > > ICNTL(28) (use parallel or sequential
> ordering): 1
> > > ICNTL(29) (parallel ordering):
> 0
> > > ICNTL(30) (user-specified set of entries
> in inv(A)): 0
> > > ICNTL(31) (factors is discarded in the
> solve phase): 0
> > > ICNTL(33) (compute determinant):
> 0
> > > CNTL(1) (relative pivoting threshold):
> 0.01
> > > CNTL(2) (stopping criterion of
> refinement): 1.49012e-08
> > > CNTL(3) (absolute pivoting threshold):
> 0.
> > > CNTL(4) (value of static pivoting):
> -1.
> > > CNTL(5) (fixation for null pivots):
> 0.
> > > RINFO(1) (local estimated flops for the
> elimination after analysis):
> > > [0] 29394.
> > > RINFO(2) (local estimated flops for the
> assembly after factorization):
> > > [0] 1092.
> > > RINFO(3) (local estimated flops for the
> elimination after factorization):
> > > [0] 29394.
> > > INFO(15) (estimated size of (in MB) MUMPS
> internal data for running numerical factorization):
> > > [0] 1
> > > INFO(16) (size of (in MB) MUMPS internal
> data used during numerical factorization):
> > > [0] 1
> > > INFO(23) (num of pivots eliminated on this
> processor after factorization):
> > > [0] 324
> > > RINFOG(1) (global estimated flops for the
> elimination after analysis): 29394.
> > > RINFOG(2) (global estimated flops for the
> assembly after factorization): 1092.
> > > RINFOG(3) (global estimated flops for the
> elimination after factorization): 29394.
> > > (RINFOG(12) RINFOG(13))*2^INFOG(34)
> (determinant): (0.,0.)*(2^0)
> > > INFOG(3) (estimated real workspace for
> factors on all processors after analysis): 3888
> > > INFOG(4) (estimated integer workspace for
> factors on all processors after analysis): 2067
> > > INFOG(5) (estimated maximum front size in
> the complete tree): 12
> > > INFOG(6) (number of nodes in the complete
> tree): 53
> > > INFOG(7) (ordering option effectively use
> after analysis): 2
> > > INFOG(8) (structural symmetry in percent
> of the permuted matrix after analysis): 100
> > > INFOG(9) (total real/complex workspace to
> store the matrix factors after factorization): 3888
> > > INFOG(10) (total integer space store the
> matrix factors after factorization): 2067
> > > INFOG(11) (order of largest frontal matrix
> after factorization): 12
> > > INFOG(12) (number of off-diagonal pivots):
> 0
> > > INFOG(13) (number of delayed pivots after
> factorization): 0
> > > INFOG(14) (number of memory compress after
> factorization): 0
> > > INFOG(15) (number of steps of iterative
> refinement after solution): 0
> > > INFOG(16) (estimated size (in MB) of all
> MUMPS internal data for factorization after analysis: value on the most
> memory consuming processor): 1
> > > INFOG(17) (estimated size of all MUMPS
> internal data for factorization after analysis: sum over all processors): 1
> > > INFOG(18) (size of all MUMPS internal data
> allocated during factorization: value on the most memory consuming
> processor): 1
> > > INFOG(19) (size of all MUMPS internal data
> allocated during factorization: sum over all processors): 1
> > > INFOG(20) (estimated number of entries in
> the factors): 3042
> > > INFOG(21) (size in MB of memory
> effectively used during factorization - value on the most memory consuming
> processor): 1
> > > INFOG(22) (size in MB of memory
> effectively used during factorization - sum over all processors): 1
> > > INFOG(23) (after analysis: value of
> ICNTL(6) effectively used): 5
> > > INFOG(24) (after analysis: value of
> ICNTL(12) effectively used): 1
> > > INFOG(25) (after factorization: number of
> pivots modified by static pivoting): 0
> > > INFOG(28) (after factorization: number of
> null pivots encountered): 0
> > > INFOG(29) (after factorization: effective
> number of entries in the factors (sum over all processors)): 3042
> > > INFOG(30, 31) (after solution: size in
> Mbytes of memory used during solution phase): 0, 0
> > > INFOG(32) (after analysis: type of
> analysis done): 1
> > > INFOG(33) (value used for ICNTL(8)): -2
> > > INFOG(34) (exponent of the determinant if
> determinant is requested): 0
> > > linear system matrix = precond matrix:
> > > Mat Object: (fieldsplit_RB_split_)
> 1 MPI processes
> > > type: seqaij
> > > rows=324, cols=324
> > > total: nonzeros=5760, allocated nonzeros=5760
> > > total number of mallocs used during MatSetValues
> calls =0
> > > using I-node routines: found 108 nodes, limit used
> is 5
> > > A01
> > > Mat Object: 1 MPI processes
> > > type: seqaij
> > > rows=324, cols=28476
> > > total: nonzeros=936, allocated nonzeros=936
> > > total number of mallocs used during MatSetValues calls
> =0
> > > using I-node routines: found 67 nodes, limit used is
> 5
> > > Mat Object: 1 MPI processes
> > > type: seqaij
> > > rows=28476, cols=28476
> > > total: nonzeros=1037052, allocated nonzeros=1037052
> > > total number of mallocs used during MatSetValues calls =0
> > > using I-node routines: found 9489 nodes, limit used is 5
> > > linear system matrix = precond matrix:
> > > Mat Object: () 1 MPI processes
> > > type: seqaij
> > > rows=28800, cols=28800
> > > total: nonzeros=1024686, allocated nonzeros=1024794
> > > total number of mallocs used during MatSetValues calls =0
> > > using I-node routines: found 9600 nodes, limit used is 5
> > >
> > > ---------------------------------------------- PETSc Performance
> Summary: ----------------------------------------------
> > >
> > > /home/dknez/akselos-dev/scrbe/build/bin/fe_solver-opt_real on a
> arch-linux2-c-opt named david-Lenovo with 1 processor, by dknez Wed Jan 11
> 17:22:10 2017
> > > Using Petsc Release Version 3.7.3, unknown
> > >
> > > Max Max/Min Avg Total
> > > Time (sec): 9.638e+01 1.00000 9.638e+01
> > > Objects: 2.030e+02 1.00000 2.030e+02
> > > Flops: 1.732e+11 1.00000 1.732e+11 1.732e+11
> > > Flops/sec: 1.797e+09 1.00000 1.797e+09 1.797e+09
> > > MPI Messages: 0.000e+00 0.00000 0.000e+00 0.000e+00
> > > MPI Message Lengths: 0.000e+00 0.00000 0.000e+00 0.000e+00
> > > MPI Reductions: 0.000e+00 0.00000
> > >
> > > Flop counting convention: 1 flop = 1 real number operation of type
> (multiply/divide/add/subtract)
> > > e.g., VecAXPY() for real vectors of length
> N --> 2N flops
> > > and VecAXPY() for complex vectors of
> length N --> 8N flops
> > >
> > > Summary of Stages: ----- Time ------ ----- Flops ----- ---
> Messages --- -- Message Lengths -- -- Reductions --
> > > Avg %Total Avg %Total counts
> %Total Avg %Total counts %Total
> > > 0: Main Stage: 9.6379e+01 100.0% 1.7318e+11 100.0% 0.000e+00
> 0.0% 0.000e+00 0.0% 0.000e+00 0.0%
> > >
> > > ------------------------------------------------------------
> ------------------------------------------------------------
> > > See the 'Profiling' chapter of the users' manual for details on
> interpreting output.
> > > Phase summary info:
> > > Count: number of times phase was executed
> > > Time and Flops: Max - maximum over all processors
> > > Ratio - ratio of maximum to minimum over all
> processors
> > > Mess: number of messages sent
> > > Avg. len: average message length (bytes)
> > > Reduct: number of global reductions
> > > Global: entire computation
> > > Stage: stages of a computation. Set stages with PetscLogStagePush()
> and PetscLogStagePop().
> > > %T - percent time in this phase %F - percent flops in
> this phase
> > > %M - percent messages in this phase %L - percent message
> lengths in this phase
> > > %R - percent reductions in this phase
> > > Total Mflop/s: 10e-6 * (sum of flops over all processors)/(max time
> over all processors)
> > > ------------------------------------------------------------
> ------------------------------------------------------------
> > > Event Count Time (sec) Flops
> --- Global --- --- Stage --- Total
> > > Max Ratio Max Ratio Max Ratio Mess Avg
> len Reduct %T %F %M %L %R %T %F %M %L %R Mflop/s
> > > ------------------------------------------------------------
> ------------------------------------------------------------
> > >
> > > --- Event Stage 0: Main Stage
> > >
> > > VecDot 42 1.0 2.2411e-05 1.0 8.53e+03 1.0 0.0e+00
> 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 380
> > > VecTDot 77761 1.0 1.4294e+00 1.0 4.43e+09 1.0 0.0e+00
> 0.0e+00 0.0e+00 1 3 0 0 0 1 3 0 0 0 3098
> > > VecNorm 38894 1.0 9.1002e-01 1.0 2.22e+09 1.0 0.0e+00
> 0.0e+00 0.0e+00 1 1 0 0 0 1 1 0 0 0 2434
> > > VecScale 38882 1.0 3.7314e-01 1.0 1.11e+09 1.0 0.0e+00
> 0.0e+00 0.0e+00 0 1 0 0 0 0 1 0 0 0 2967
> > > VecCopy 38908 1.0 2.1655e-02 1.0 0.00e+00 0.0 0.0e+00
> 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 0
> > > VecSet 77887 1.0 3.2034e-01 1.0 0.00e+00 0.0 0.0e+00
> 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 0
> > > VecAXPY 77777 1.0 1.8382e+00 1.0 4.43e+09 1.0 0.0e+00
> 0.0e+00 0.0e+00 2 3 0 0 0 2 3 0 0 0 2409
> > > VecAYPX 38875 1.0 1.2884e+00 1.0 2.21e+09 1.0 0.0e+00
> 0.0e+00 0.0e+00 1 1 0 0 0 1 1 0 0 0 1718
> > > VecAssemblyBegin 68 1.0 1.9407e-04 1.0 0.00e+00 0.0 0.0e+00
> 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 0
> > > VecAssemblyEnd 68 1.0 2.6941e-05 1.0 0.00e+00 0.0 0.0e+00
> 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 0
> > > VecScatterBegin 48 1.0 4.6349e-04 1.0 0.00e+00 0.0 0.0e+00
> 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 0
> > > MatMult 38891 1.0 4.3045e+01 1.0 8.03e+10 1.0 0.0e+00
> 0.0e+00 0.0e+00 45 46 0 0 0 45 46 0 0 0 1866
> > > MatMultAdd 38889 1.0 3.5360e+01 1.0 7.91e+10 1.0 0.0e+00
> 0.0e+00 0.0e+00 37 46 0 0 0 37 46 0 0 0 2236
> > > MatSolve 77769 1.0 4.8780e+01 1.0 7.95e+10 1.0 0.0e+00
> 0.0e+00 0.0e+00 51 46 0 0 0 51 46 0 0 0 1631
> > > MatLUFactorNum 1 1.0 1.9575e-02 1.0 2.49e+07 1.0 0.0e+00
> 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 1274
> > > MatCholFctrSym 1 1.0 9.4891e-04 1.0 0.00e+00 0.0 0.0e+00
> 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 0
> > > MatCholFctrNum 1 1.0 3.7885e-04 1.0 0.00e+00 0.0 0.0e+00
> 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 0
> > > MatILUFactorSym 1 1.0 4.1780e-03 1.0 0.00e+00 0.0 0.0e+00
> 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 0
> > > MatConvert 1 1.0 3.0041e-05 1.0 0.00e+00 0.0 0.0e+00
> 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 0
> > > MatScale 2 1.0 2.7180e-05 1.0 2.53e+04 1.0 0.0e+00
> 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 930
> > > MatAssemblyBegin 32 1.0 4.0531e-06 1.0 0.00e+00 0.0 0.0e+00
> 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 0
> > > MatAssemblyEnd 32 1.0 1.2032e-02 1.0 0.00e+00 0.0 0.0e+00
> 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 0
> > > MatGetRow 114978 1.0 5.9254e-03 1.0 0.00e+00 0.0 0.0e+00
> 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 0
> > > MatGetRowIJ 2 1.0 2.1458e-06 1.0 0.00e+00 0.0 0.0e+00
> 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 0
> > > MatGetSubMatrice 6 1.0 1.5707e-02 1.0 0.00e+00 0.0 0.0e+00
> 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 0
> > > MatGetOrdering 2 1.0 3.2425e-04 1.0 0.00e+00 0.0 0.0e+00
> 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 0
> > > MatZeroEntries 6 1.0 3.0580e-03 1.0 0.00e+00 0.0 0.0e+00
> 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 0
> > > MatView 7 1.0 3.5119e-03 1.0 0.00e+00 0.0 0.0e+00
> 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 0
> > > MatAXPY 1 1.0 1.9384e-02 1.0 0.00e+00 0.0 0.0e+00
> 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 0
> > > MatMatMult 1 1.0 2.7120e-03 1.0 3.16e+05 1.0 0.0e+00
> 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 117
> > > MatMatMultSym 1 1.0 1.8010e-03 1.0 0.00e+00 0.0 0.0e+00
> 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 0
> > > MatMatMultNum 1 1.0 6.1703e-04 1.0 3.16e+05 1.0 0.0e+00
> 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 513
> > > KSPSetUp 4 1.0 9.8944e-05 1.0 0.00e+00 0.0 0.0e+00
> 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 0
> > > KSPSolve 1 1.0 9.3380e+01 1.0 1.73e+11 1.0 0.0e+00
> 0.0e+00 0.0e+00 97100 0 0 0 97100 0 0 0 1855
> > > PCSetUp 4 1.0 6.6326e-02 1.0 2.53e+07 1.0 0.0e+00
> 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 381
> > > PCSetUpOnBlocks 5 1.0 2.4082e-02 1.0 2.49e+07 1.0 0.0e+00
> 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 1036
> > > PCApply 5 1.0 9.3376e+01 1.0 1.73e+11 1.0 0.0e+00
> 0.0e+00 0.0e+00 97100 0 0 0 97100 0 0 0 1855
> > > KSPSolve_FS_0 5 1.0 7.0214e-04 1.0 0.00e+00 0.0 0.0e+00
> 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 0
> > > KSPSolve_FS_Schu 5 1.0 9.3372e+01 1.0 1.73e+11 1.0 0.0e+00
> 0.0e+00 0.0e+00 97100 0 0 0 97100 0 0 0 1855
> > > KSPSolve_FS_Low 5 1.0 2.1377e-03 1.0 0.00e+00 0.0 0.0e+00
> 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 0
> > > ------------------------------------------------------------
> ------------------------------------------------------------
> > >
> > > Memory usage is given in bytes:
> > >
> > > Object Type Creations Destructions Memory Descendants'
> Mem.
> > > Reports information only for process 0.
> > >
> > > --- Event Stage 0: Main Stage
> > >
> > > Vector 92 92 9698040 0.
> > > Vector Scatter 24 24 15936 0.
> > > Index Set 51 51 537876 0.
> > > IS L to G Mapping 3 3 240408 0.
> > > Matrix 16 16 77377776 0.
> > > Krylov Solver 6 6 7888 0.
> > > Preconditioner 6 6 6288 0.
> > > Viewer 1 0 0 0.
> > > Distributed Mesh 1 1 4624 0.
> > > Star Forest Bipartite Graph 2 2 1616 0.
> > > Discrete System 1 1 872 0.
> > > ============================================================
> ============================================================
> > > Average time to get PetscTime(): 0.
> > > #PETSc Option Table entries:
> > > -ksp_monitor
> > > -ksp_view
> > > -log_view
> > > #End of PETSc Option Table entries
> > > Compiled without FORTRAN kernels
> > > Compiled with full precision matrices (default)
> > > sizeof(short) 2 sizeof(int) 4 sizeof(long) 8 sizeof(void*) 8
> sizeof(PetscScalar) 8 sizeof(PetscInt) 4
> > > Configure options: --with-shared-libraries=1 --with-debugging=0
> --download-suitesparse --download-blacs --download-ptscotch=yes
> --with-blas-lapack-dir=/opt/intel/system_studio_2015.2.050/mkl
> --CXXFLAGS=-Wl,--no-as-needed --download-scalapack --download-mumps
> --download-metis --prefix=/home/dknez/software/libmesh_install/opt_real/petsc
> --download-hypre --download-ml
> > > -----------------------------------------
> > > Libraries compiled on Wed Sep 21 17:38:52 2016 on david-Lenovo
> > > Machine characteristics: Linux-4.4.0-38-generic-x86_64-
> with-Ubuntu-16.04-xenial
> > > Using PETSc directory: /home/dknez/software/petsc-src
> > > Using PETSc arch: arch-linux2-c-opt
> > > -----------------------------------------
> > >
> > > Using C compiler: mpicc -fPIC -Wall -Wwrite-strings
> -Wno-strict-aliasing -Wno-unknown-pragmas -fvisibility=hidden -g -O
> ${COPTFLAGS} ${CFLAGS}
> > > Using Fortran compiler: mpif90 -fPIC -Wall -ffree-line-length-0
> -Wno-unused-dummy-argument -g -O ${FOPTFLAGS} ${FFLAGS}
> > > -----------------------------------------
> > >
> > > Using include paths: -I/home/dknez/software/petsc-src/arch-linux2-c-opt/include
> -I/home/dknez/software/petsc-src/include -I/home/dknez/software/petsc-src/include
> -I/home/dknez/software/petsc-src/arch-linux2-c-opt/include
> -I/home/dknez/software/libmesh_install/opt_real/petsc/include
> -I/usr/lib/openmpi/include/openmpi/opal/mca/event/libevent2021/libevent
> -I/usr/lib/openmpi/include/openmpi/opal/mca/event/libevent2021/libevent/include
> -I/usr/lib/openmpi/include -I/usr/lib/openmpi/include/openmpi
> > > -----------------------------------------
> > >
> > > Using C linker: mpicc
> > > Using Fortran linker: mpif90
> > > Using libraries: -Wl,-rpath,/home/dknez/software/petsc-src/arch-linux2-c-opt/lib
> -L/home/dknez/software/petsc-src/arch-linux2-c-opt/lib -lpetsc
> -Wl,-rpath,/home/dknez/software/libmesh_install/opt_real/petsc/lib
> -L/home/dknez/software/libmesh_install/opt_real/petsc/lib -lcmumps
> -ldmumps -lsmumps -lzmumps -lmumps_common -lpord -lmetis -lHYPRE
> -Wl,-rpath,/usr/lib/openmpi/lib -L/usr/lib/openmpi/lib
> -Wl,-rpath,/usr/lib/gcc/x86_64-linux-gnu/5 -L/usr/lib/gcc/x86_64-linux-gnu/5
> -Wl,-rpath,/usr/lib/x86_64-linux-gnu -L/usr/lib/x86_64-linux-gnu
> -Wl,-rpath,/lib/x86_64-linux-gnu -L/lib/x86_64-linux-gnu -lmpi_cxx
> -lstdc++ -lscalapack -lml -lmpi_cxx -lstdc++ -lumfpack -lklu -lcholmod
> -lbtf -lccolamd -lcolamd -lcamd -lamd -lsuitesparseconfig
> -Wl,-rpath,/opt/intel/system_studio_2015.2.050/mkl/lib/intel64
> -L/opt/intel/system_studio_2015.2.050/mkl/lib/intel64 -lmkl_intel_lp64
> -lmkl_sequential -lmkl_core -lpthread -lm -lhwloc -lptesmumps -lptscotch
> -lptscotcherr -lscotch -lscotcherr -lX11 -lm -lmpi_usempif08
> -lmpi_usempi_ignore_tkr -lmpi_mpifh -lgfortran -lm -lgfortran -lm
> -lquadmath -lm -lmpi_cxx -lstdc++ -lrt -lm -lpthread -lz
> -Wl,-rpath,/usr/lib/openmpi/lib -L/usr/lib/openmpi/lib
> -Wl,-rpath,/usr/lib/gcc/x86_64-linux-gnu/5 -L/usr/lib/gcc/x86_64-linux-gnu/5
> -Wl,-rpath,/usr/lib/x86_64-linux-gnu -L/usr/lib/x86_64-linux-gnu
> -Wl,-rpath,/lib/x86_64-linux-gnu -L/lib/x86_64-linux-gnu
> -Wl,-rpath,/usr/lib/x86_64-linux-gnu -L/usr/lib/x86_64-linux-gnu -ldl
> -Wl,-rpath,/usr/lib/openmpi/lib -lmpi -lgcc_s -lpthread -ldl
> > > -----------------------------------------
> > >
> > >
> > >
> > >
> > > On Wed, Jan 11, 2017 at 4:49 PM, Dave May <dave.mayhem23 at gmail.com>
> wrote:
> > > It looks like the Schur solve is requiring a huge number of iterates
> to converge (based on the instances of MatMult).
> > > This is killing the performance.
> > >
> > > Are you sure that A11 is a good approximation to S? You might consider
> trying the selfp option
> > >
> > > http://www.mcs.anl.gov/petsc/petsc-current/docs/manualpages/PC/
> PCFieldSplitSetSchurPre.html#PCFieldSplitSetSchurPre
> > >
> > > Note that the best approx to S is likely both problem and
> discretisation dependent so if selfp is also terrible, you might want to
> consider coding up your own approx to S for your specific system.
> > >
> > >
> > > Thanks,
> > > Dave
> > >
> > >
> > > On Wed, 11 Jan 2017 at 22:34, David Knezevic <
> david.knezevic at akselos.com> wrote:
> > > I have a definite block 2x2 system and I figured it'd be good to apply
> the PCFIELDSPLIT functionality with Schur complement, as described in
> Section 4.5 of the manual.
> > >
> > > The A00 block of my matrix is very small so I figured I'd specify a
> direct solver (i.e. MUMPS) for that block.
> > >
> > > So I did the following:
> > > - PCFieldSplitSetIS to specify the indices of the two splits
> > > - PCFieldSplitGetSubKSP to get the two KSP objects, and to set the
> solver and PC types for each (MUMPS for A00, ILU+CG for A11)
> > > - I set -pc_fieldsplit_schur_fact_type full
> > >
> > > Below I have pasted the output of "-ksp_view -ksp_monitor -log_view"
> for a test case. It seems to converge well, but I'm concerned about the
> speed (about 90 seconds, vs. about 1 second if I use a direct solver for
> the entire system). I just wanted to check if I'm setting this up in a good
> way?
> > >
> > > Many thanks,
> > > David
> > >
> > > ------------------------------------------------------------
> -----------------------
> > >
> > > 0 KSP Residual norm 5.405774214400e+04
> > > 1 KSP Residual norm 1.849649014371e+02
> > > 2 KSP Residual norm 7.462775074989e-02
> > > 3 KSP Residual norm 2.680497175260e-04
> > > KSP Object: 1 MPI processes
> > > type: cg
> > > maximum iterations=1000
> > > tolerances: relative=1e-06, absolute=1e-50, divergence=10000.
> > > left preconditioning
> > > using nonzero initial guess
> > > using PRECONDITIONED norm type for convergence test
> > > PC Object: 1 MPI processes
> > > type: fieldsplit
> > > FieldSplit with Schur preconditioner, factorization FULL
> > > Preconditioner for the Schur complement formed from A11
> > > Split info:
> > > Split number 0 Defined by IS
> > > Split number 1 Defined by IS
> > > KSP solver for A00 block
> > > KSP Object: (fieldsplit_RB_split_) 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: (fieldsplit_RB_split_) 1 MPI processes
> > > type: cholesky
> > > Cholesky: out-of-place factorization
> > > tolerance for zero pivot 2.22045e-14
> > > matrix ordering: natural
> > > factor fill ratio given 0., needed 0.
> > > Factored matrix follows:
> > > Mat Object: 1 MPI processes
> > > type: seqaij
> > > rows=324, cols=324
> > > package used to perform factorization: mumps
> > > total: nonzeros=3042, allocated nonzeros=3042
> > > total number of mallocs used during MatSetValues calls
> =0
> > > MUMPS run parameters:
> > > SYM (matrix type): 2
> > > PAR (host participation): 1
> > > ICNTL(1) (output for error): 6
> > > ICNTL(2) (output of diagnostic msg): 0
> > > ICNTL(3) (output for global info): 0
> > > ICNTL(4) (level of printing): 0
> > > ICNTL(5) (input mat struct): 0
> > > ICNTL(6) (matrix prescaling): 7
> > > ICNTL(7) (sequentia matrix ordering):7
> > > ICNTL(8) (scalling strategy): 77
> > > ICNTL(10) (max num of refinements): 0
> > > ICNTL(11) (error analysis): 0
> > > ICNTL(12) (efficiency control):
> 0
> > > ICNTL(13) (efficiency control):
> 0
> > > ICNTL(14) (percentage of estimated workspace
> increase): 20
> > > ICNTL(18) (input mat struct):
> 0
> > > ICNTL(19) (Shur complement info):
> 0
> > > ICNTL(20) (rhs sparse pattern):
> 0
> > > ICNTL(21) (solution struct):
> 0
> > > ICNTL(22) (in-core/out-of-core facility):
> 0
> > > ICNTL(23) (max size of memory can be allocated
> locally):0
> > > ICNTL(24) (detection of null pivot rows):
> 0
> > > ICNTL(25) (computation of a null space basis):
> 0
> > > ICNTL(26) (Schur options for rhs or solution):
> 0
> > > ICNTL(27) (experimental parameter):
> -24
> > > ICNTL(28) (use parallel or sequential ordering):
> 1
> > > ICNTL(29) (parallel ordering):
> 0
> > > ICNTL(30) (user-specified set of entries in
> inv(A)): 0
> > > ICNTL(31) (factors is discarded in the solve
> phase): 0
> > > ICNTL(33) (compute determinant):
> 0
> > > CNTL(1) (relative pivoting threshold): 0.01
> > > CNTL(2) (stopping criterion of refinement):
> 1.49012e-08
> > > CNTL(3) (absolute pivoting threshold): 0.
> > > CNTL(4) (value of static pivoting): -1.
> > > CNTL(5) (fixation for null pivots): 0.
> > > RINFO(1) (local estimated flops for the
> elimination after analysis):
> > > [0] 29394.
> > > RINFO(2) (local estimated flops for the assembly
> after factorization):
> > > [0] 1092.
> > > RINFO(3) (local estimated flops for the
> elimination after factorization):
> > > [0] 29394.
> > > INFO(15) (estimated size of (in MB) MUMPS internal
> data for running numerical factorization):
> > > [0] 1
> > > INFO(16) (size of (in MB) MUMPS internal data used
> during numerical factorization):
> > > [0] 1
> > > INFO(23) (num of pivots eliminated on this
> processor after factorization):
> > > [0] 324
> > > RINFOG(1) (global estimated flops for the
> elimination after analysis): 29394.
> > > RINFOG(2) (global estimated flops for the assembly
> after factorization): 1092.
> > > RINFOG(3) (global estimated flops for the
> elimination after factorization): 29394.
> > > (RINFOG(12) RINFOG(13))*2^INFOG(34) (determinant):
> (0.,0.)*(2^0)
> > > INFOG(3) (estimated real workspace for factors on
> all processors after analysis): 3888
> > > INFOG(4) (estimated integer workspace for factors
> on all processors after analysis): 2067
> > > INFOG(5) (estimated maximum front size in the
> complete tree): 12
> > > INFOG(6) (number of nodes in the complete tree): 53
> > > INFOG(7) (ordering option effectively use after
> analysis): 2
> > > INFOG(8) (structural symmetry in percent of the
> permuted matrix after analysis): 100
> > > INFOG(9) (total real/complex workspace to store
> the matrix factors after factorization): 3888
> > > INFOG(10) (total integer space store the matrix
> factors after factorization): 2067
> > > INFOG(11) (order of largest frontal matrix after
> factorization): 12
> > > INFOG(12) (number of off-diagonal pivots): 0
> > > INFOG(13) (number of delayed pivots after
> factorization): 0
> > > INFOG(14) (number of memory compress after
> factorization): 0
> > > INFOG(15) (number of steps of iterative refinement
> after solution): 0
> > > INFOG(16) (estimated size (in MB) of all MUMPS
> internal data for factorization after analysis: value on the most memory
> consuming processor): 1
> > > INFOG(17) (estimated size of all MUMPS internal
> data for factorization after analysis: sum over all processors): 1
> > > INFOG(18) (size of all MUMPS internal data
> allocated during factorization: value on the most memory consuming
> processor): 1
> > > INFOG(19) (size of all MUMPS internal data
> allocated during factorization: sum over all processors): 1
> > > INFOG(20) (estimated number of entries in the
> factors): 3042
> > > INFOG(21) (size in MB of memory effectively used
> during factorization - value on the most memory consuming processor): 1
> > > INFOG(22) (size in MB of memory effectively used
> during factorization - sum over all processors): 1
> > > INFOG(23) (after analysis: value of ICNTL(6)
> effectively used): 5
> > > INFOG(24) (after analysis: value of ICNTL(12)
> effectively used): 1
> > > INFOG(25) (after factorization: number of pivots
> modified by static pivoting): 0
> > > INFOG(28) (after factorization: number of null
> pivots encountered): 0
> > > INFOG(29) (after factorization: effective number
> of entries in the factors (sum over all processors)): 3042
> > > INFOG(30, 31) (after solution: size in Mbytes of
> memory used during solution phase): 0, 0
> > > INFOG(32) (after analysis: type of analysis done):
> 1
> > > INFOG(33) (value used for ICNTL(8)): -2
> > > INFOG(34) (exponent of the determinant if
> determinant is requested): 0
> > > linear system matrix = precond matrix:
> > > Mat Object: (fieldsplit_RB_split_) 1 MPI
> processes
> > > type: seqaij
> > > rows=324, cols=324
> > > total: nonzeros=5760, allocated nonzeros=5760
> > > total number of mallocs used during MatSetValues calls =0
> > > using I-node routines: found 108 nodes, limit used is 5
> > > KSP solver for S = A11 - A10 inv(A00) A01
> > > KSP Object: (fieldsplit_FE_split_) 1 MPI processes
> > > type: cg
> > > maximum iterations=10000, initial guess is zero
> > > tolerances: relative=1e-05, absolute=1e-50, divergence=10000.
> > > left preconditioning
> > > using PRECONDITIONED norm type for convergence test
> > > PC Object: (fieldsplit_FE_split_) 1 MPI processes
> > > type: bjacobi
> > > block Jacobi: number of blocks = 1
> > > Local solve is same for all blocks, in the following KSP and
> PC objects:
> > > KSP Object: (fieldsplit_FE_split_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: (fieldsplit_FE_split_sub_) 1
> MPI processes
> > > type: ilu
> > > ILU: out-of-place factorization
> > > 0 levels of fill
> > > tolerance for zero pivot 2.22045e-14
> > > matrix ordering: natural
> > > factor fill ratio given 1., needed 1.
> > > Factored matrix follows:
> > > Mat Object: 1 MPI processes
> > > type: seqaij
> > > rows=28476, cols=28476
> > > package used to perform factorization: petsc
> > > total: nonzeros=1017054, allocated nonzeros=1017054
> > > total number of mallocs used during MatSetValues
> calls =0
> > > using I-node routines: found 9492 nodes, limit
> used is 5
> > > linear system matrix = precond matrix:
> > > Mat Object: (fieldsplit_FE_split_)
> 1 MPI processes
> > > type: seqaij
> > > rows=28476, cols=28476
> > > total: nonzeros=1017054, allocated nonzeros=1017054
> > > total number of mallocs used during MatSetValues calls =0
> > > using I-node routines: found 9492 nodes, limit used is
> 5
> > > linear system matrix followed by preconditioner matrix:
> > > Mat Object: (fieldsplit_FE_split_) 1 MPI
> processes
> > > type: schurcomplement
> > > rows=28476, cols=28476
> > > Schur complement A11 - A10 inv(A00) A01
> > > A11
> > > Mat Object: (fieldsplit_FE_split_)
> 1 MPI processes
> > > type: seqaij
> > > rows=28476, cols=28476
> > > total: nonzeros=1017054, allocated nonzeros=1017054
> > > total number of mallocs used during MatSetValues calls
> =0
> > > using I-node routines: found 9492 nodes, limit used
> is 5
> > > A10
> > > Mat Object: 1 MPI processes
> > > type: seqaij
> > > rows=28476, cols=324
> > > total: nonzeros=936, allocated nonzeros=936
> > > total number of mallocs used during MatSetValues calls
> =0
> > > using I-node routines: found 5717 nodes, limit used
> is 5
> > > KSP of A00
> > > KSP Object: (fieldsplit_RB_split_)
> 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: (fieldsplit_RB_split_)
> 1 MPI processes
> > > type: cholesky
> > > Cholesky: out-of-place factorization
> > > tolerance for zero pivot 2.22045e-14
> > > matrix ordering: natural
> > > factor fill ratio given 0., needed 0.
> > > Factored matrix follows:
> > > Mat Object: 1 MPI processes
> > > type: seqaij
> > > rows=324, cols=324
> > > package used to perform factorization: mumps
> > > total: nonzeros=3042, allocated nonzeros=3042
> > > total number of mallocs used during
> MatSetValues calls =0
> > > MUMPS run parameters:
> > > SYM (matrix type): 2
> > > PAR (host participation): 1
> > > ICNTL(1) (output for error): 6
> > > ICNTL(2) (output of diagnostic msg): 0
> > > ICNTL(3) (output for global info): 0
> > > ICNTL(4) (level of printing): 0
> > > ICNTL(5) (input mat struct): 0
> > > ICNTL(6) (matrix prescaling): 7
> > > ICNTL(7) (sequentia matrix ordering):7
> > > ICNTL(8) (scalling strategy): 77
> > > ICNTL(10) (max num of refinements): 0
> > > ICNTL(11) (error analysis): 0
> > > ICNTL(12) (efficiency control):
> 0
> > > ICNTL(13) (efficiency control):
> 0
> > > ICNTL(14) (percentage of estimated
> workspace increase): 20
> > > ICNTL(18) (input mat struct):
> 0
> > > ICNTL(19) (Shur complement info):
> 0
> > > ICNTL(20) (rhs sparse pattern):
> 0
> > > ICNTL(21) (solution struct):
> 0
> > > ICNTL(22) (in-core/out-of-core facility):
> 0
> > > ICNTL(23) (max size of memory can be
> allocated locally):0
> > > ICNTL(24) (detection of null pivot rows):
> 0
> > > ICNTL(25) (computation of a null space
> basis): 0
> > > ICNTL(26) (Schur options for rhs or
> solution): 0
> > > ICNTL(27) (experimental parameter):
> -24
> > > ICNTL(28) (use parallel or sequential
> ordering): 1
> > > ICNTL(29) (parallel ordering):
> 0
> > > ICNTL(30) (user-specified set of entries
> in inv(A)): 0
> > > ICNTL(31) (factors is discarded in the
> solve phase): 0
> > > ICNTL(33) (compute determinant):
> 0
> > > CNTL(1) (relative pivoting threshold):
> 0.01
> > > CNTL(2) (stopping criterion of
> refinement): 1.49012e-08
> > > CNTL(3) (absolute pivoting threshold):
> 0.
> > > CNTL(4) (value of static pivoting):
> -1.
> > > CNTL(5) (fixation for null pivots):
> 0.
> > > RINFO(1) (local estimated flops for the
> elimination after analysis):
> > > [0] 29394.
> > > RINFO(2) (local estimated flops for the
> assembly after factorization):
> > > [0] 1092.
> > > RINFO(3) (local estimated flops for the
> elimination after factorization):
> > > [0] 29394.
> > > INFO(15) (estimated size of (in MB) MUMPS
> internal data for running numerical factorization):
> > > [0] 1
> > > INFO(16) (size of (in MB) MUMPS internal
> data used during numerical factorization):
> > > [0] 1
> > > INFO(23) (num of pivots eliminated on this
> processor after factorization):
> > > [0] 324
> > > RINFOG(1) (global estimated flops for the
> elimination after analysis): 29394.
> > > RINFOG(2) (global estimated flops for the
> assembly after factorization): 1092.
> > > RINFOG(3) (global estimated flops for the
> elimination after factorization): 29394.
> > > (RINFOG(12) RINFOG(13))*2^INFOG(34)
> (determinant): (0.,0.)*(2^0)
> > > INFOG(3) (estimated real workspace for
> factors on all processors after analysis): 3888
> > > INFOG(4) (estimated integer workspace for
> factors on all processors after analysis): 2067
> > > INFOG(5) (estimated maximum front size in
> the complete tree): 12
> > > INFOG(6) (number of nodes in the complete
> tree): 53
> > > INFOG(7) (ordering option effectively use
> after analysis): 2
> > > INFOG(8) (structural symmetry in percent
> of the permuted matrix after analysis): 100
> > > INFOG(9) (total real/complex workspace to
> store the matrix factors after factorization): 3888
> > > INFOG(10) (total integer space store the
> matrix factors after factorization): 2067
> > > INFOG(11) (order of largest frontal matrix
> after factorization): 12
> > > INFOG(12) (number of off-diagonal pivots):
> 0
> > > INFOG(13) (number of delayed pivots after
> factorization): 0
> > > INFOG(14) (number of memory compress after
> factorization): 0
> > > INFOG(15) (number of steps of iterative
> refinement after solution): 0
> > > INFOG(16) (estimated size (in MB) of all
> MUMPS internal data for factorization after analysis: value on the most
> memory consuming processor): 1
> > > INFOG(17) (estimated size of all MUMPS
> internal data for factorization after analysis: sum over all processors): 1
> > > INFOG(18) (size of all MUMPS internal data
> allocated during factorization: value on the most memory consuming
> processor): 1
> > > INFOG(19) (size of all MUMPS internal data
> allocated during factorization: sum over all processors): 1
> > > INFOG(20) (estimated number of entries in
> the factors): 3042
> > > INFOG(21) (size in MB of memory
> effectively used during factorization - value on the most memory consuming
> processor): 1
> > > INFOG(22) (size in MB of memory
> effectively used during factorization - sum over all processors): 1
> > > INFOG(23) (after analysis: value of
> ICNTL(6) effectively used): 5
> > > INFOG(24) (after analysis: value of
> ICNTL(12) effectively used): 1
> > > INFOG(25) (after factorization: number of
> pivots modified by static pivoting): 0
> > > INFOG(28) (after factorization: number of
> null pivots encountered): 0
> > > INFOG(29) (after factorization: effective
> number of entries in the factors (sum over all processors)): 3042
> > > INFOG(30, 31) (after solution: size in
> Mbytes of memory used during solution phase): 0, 0
> > > INFOG(32) (after analysis: type of
> analysis done): 1
> > > INFOG(33) (value used for ICNTL(8)): -2
> > > INFOG(34) (exponent of the determinant if
> determinant is requested): 0
> > > linear system matrix = precond matrix:
> > > Mat Object: (fieldsplit_RB_split_)
> 1 MPI processes
> > > type: seqaij
> > > rows=324, cols=324
> > > total: nonzeros=5760, allocated nonzeros=5760
> > > total number of mallocs used during MatSetValues
> calls =0
> > > using I-node routines: found 108 nodes, limit used
> is 5
> > > A01
> > > Mat Object: 1 MPI processes
> > > type: seqaij
> > > rows=324, cols=28476
> > > total: nonzeros=936, allocated nonzeros=936
> > > total number of mallocs used during MatSetValues calls
> =0
> > > using I-node routines: found 67 nodes, limit used is
> 5
> > > Mat Object: (fieldsplit_FE_split_) 1 MPI
> processes
> > > type: seqaij
> > > rows=28476, cols=28476
> > > total: nonzeros=1017054, allocated nonzeros=1017054
> > > total number of mallocs used during MatSetValues calls =0
> > > using I-node routines: found 9492 nodes, limit used is 5
> > > linear system matrix = precond matrix:
> > > Mat Object: () 1 MPI processes
> > > type: seqaij
> > > rows=28800, cols=28800
> > > total: nonzeros=1024686, allocated nonzeros=1024794
> > > total number of mallocs used during MatSetValues calls =0
> > > using I-node routines: found 9600 nodes, limit used is 5
> > >
> > >
> > > ---------------------------------------------- PETSc Performance
> Summary: ----------------------------------------------
> > >
> > > /home/dknez/akselos-dev/scrbe/build/bin/fe_solver-opt_real on a
> arch-linux2-c-opt named david-Lenovo with 1 processor, by dknez Wed Jan 11
> 16:16:47 2017
> > > Using Petsc Release Version 3.7.3, unknown
> > >
> > > Max Max/Min Avg Total
> > > Time (sec): 9.179e+01 1.00000 9.179e+01
> > > Objects: 1.990e+02 1.00000 1.990e+02
> > > Flops: 1.634e+11 1.00000 1.634e+11 1.634e+11
> > > Flops/sec: 1.780e+09 1.00000 1.780e+09 1.780e+09
> > > MPI Messages: 0.000e+00 0.00000 0.000e+00 0.000e+00
> > > MPI Message Lengths: 0.000e+00 0.00000 0.000e+00 0.000e+00
> > > MPI Reductions: 0.000e+00 0.00000
> > >
> > > Flop counting convention: 1 flop = 1 real number operation of type
> (multiply/divide/add/subtract)
> > > e.g., VecAXPY() for real vectors of length
> N --> 2N flops
> > > and VecAXPY() for complex vectors of
> length N --> 8N flops
> > >
> > > Summary of Stages: ----- Time ------ ----- Flops ----- ---
> Messages --- -- Message Lengths -- -- Reductions --
> > > Avg %Total Avg %Total counts
> %Total Avg %Total counts %Total
> > > 0: Main Stage: 9.1787e+01 100.0% 1.6336e+11 100.0% 0.000e+00
> 0.0% 0.000e+00 0.0% 0.000e+00 0.0%
> > >
> > > ------------------------------------------------------------
> ------------------------------------------------------------
> > > See the 'Profiling' chapter of the users' manual for details on
> interpreting output.
> > > Phase summary info:
> > > Count: number of times phase was executed
> > > Time and Flops: Max - maximum over all processors
> > > Ratio - ratio of maximum to minimum over all
> processors
> > > Mess: number of messages sent
> > > Avg. len: average message length (bytes)
> > > Reduct: number of global reductions
> > > Global: entire computation
> > > Stage: stages of a computation. Set stages with PetscLogStagePush()
> and PetscLogStagePop().
> > > %T - percent time in this phase %F - percent flops in
> this phase
> > > %M - percent messages in this phase %L - percent message
> lengths in this phase
> > > %R - percent reductions in this phase
> > > Total Mflop/s: 10e-6 * (sum of flops over all processors)/(max time
> over all processors)
> > > ------------------------------------------------------------
> ------------------------------------------------------------
> > > Event Count Time (sec) Flops
> --- Global --- --- Stage --- Total
> > > Max Ratio Max Ratio Max Ratio Mess Avg
> len Reduct %T %F %M %L %R %T %F %M %L %R Mflop/s
> > > ------------------------------------------------------------
> ------------------------------------------------------------
> > >
> > > --- Event Stage 0: Main Stage
> > >
> > > VecDot 42 1.0 2.4080e-05 1.0 8.53e+03 1.0 0.0e+00
> 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 354
> > > VecTDot 74012 1.0 1.2440e+00 1.0 4.22e+09 1.0 0.0e+00
> 0.0e+00 0.0e+00 1 3 0 0 0 1 3 0 0 0 3388
> > > VecNorm 37020 1.0 8.3580e-01 1.0 2.11e+09 1.0 0.0e+00
> 0.0e+00 0.0e+00 1 1 0 0 0 1 1 0 0 0 2523
> > > VecScale 37008 1.0 3.5800e-01 1.0 1.05e+09 1.0 0.0e+00
> 0.0e+00 0.0e+00 0 1 0 0 0 0 1 0 0 0 2944
> > > VecCopy 37034 1.0 2.5754e-02 1.0 0.00e+00 0.0 0.0e+00
> 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 0
> > > VecSet 74137 1.0 3.0537e-01 1.0 0.00e+00 0.0 0.0e+00
> 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 0
> > > VecAXPY 74029 1.0 1.7233e+00 1.0 4.22e+09 1.0 0.0e+00
> 0.0e+00 0.0e+00 2 3 0 0 0 2 3 0 0 0 2446
> > > VecAYPX 37001 1.0 1.2214e+00 1.0 2.11e+09 1.0 0.0e+00
> 0.0e+00 0.0e+00 1 1 0 0 0 1 1 0 0 0 1725
> > > VecAssemblyBegin 68 1.0 2.0432e-04 1.0 0.00e+00 0.0 0.0e+00
> 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 0
> > > VecAssemblyEnd 68 1.0 2.5988e-05 1.0 0.00e+00 0.0 0.0e+00
> 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 0
> > > VecScatterBegin 48 1.0 4.6921e-04 1.0 0.00e+00 0.0 0.0e+00
> 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 0
> > > MatMult 37017 1.0 4.1269e+01 1.0 7.65e+10 1.0 0.0e+00
> 0.0e+00 0.0e+00 45 47 0 0 0 45 47 0 0 0 1853
> > > MatMultAdd 37015 1.0 3.3638e+01 1.0 7.53e+10 1.0 0.0e+00
> 0.0e+00 0.0e+00 37 46 0 0 0 37 46 0 0 0 2238
> > > MatSolve 74021 1.0 4.6602e+01 1.0 7.42e+10 1.0 0.0e+00
> 0.0e+00 0.0e+00 51 45 0 0 0 51 45 0 0 0 1593
> > > MatLUFactorNum 1 1.0 1.7209e-02 1.0 2.44e+07 1.0 0.0e+00
> 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 1420
> > > MatCholFctrSym 1 1.0 8.8310e-04 1.0 0.00e+00 0.0 0.0e+00
> 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 0
> > > MatCholFctrNum 1 1.0 3.6907e-04 1.0 0.00e+00 0.0 0.0e+00
> 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 0
> > > MatILUFactorSym 1 1.0 3.7372e-03 1.0 0.00e+00 0.0 0.0e+00
> 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 0
> > > MatAssemblyBegin 29 1.0 2.1458e-06 1.0 0.00e+00 0.0 0.0e+00
> 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 0
> > > MatAssemblyEnd 29 1.0 9.9473e-03 1.0 0.00e+00 0.0 0.0e+00
> 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 0
> > > MatGetRow 58026 1.0 2.8155e-03 1.0 0.00e+00 0.0 0.0e+00
> 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 0
> > > MatGetRowIJ 2 1.0 0.0000e+00 0.0 0.00e+00 0.0 0.0e+00
> 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 0
> > > MatGetSubMatrice 6 1.0 1.5399e-02 1.0 0.00e+00 0.0 0.0e+00
> 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 0
> > > MatGetOrdering 2 1.0 3.0112e-04 1.0 0.00e+00 0.0 0.0e+00
> 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 0
> > > MatZeroEntries 6 1.0 2.9490e-03 1.0 0.00e+00 0.0 0.0e+00
> 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 0
> > > MatView 7 1.0 3.4356e-03 1.0 0.00e+00 0.0 0.0e+00
> 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 0
> > > KSPSetUp 4 1.0 9.4891e-05 1.0 0.00e+00 0.0 0.0e+00
> 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 0
> > > KSPSolve 1 1.0 8.8793e+01 1.0 1.63e+11 1.0 0.0e+00
> 0.0e+00 0.0e+00 97100 0 0 0 97100 0 0 0 1840
> > > PCSetUp 4 1.0 3.8375e-02 1.0 2.44e+07 1.0 0.0e+00
> 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 637
> > > PCSetUpOnBlocks 5 1.0 2.1250e-02 1.0 2.44e+07 1.0 0.0e+00
> 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 1150
> > > PCApply 5 1.0 8.8789e+01 1.0 1.63e+11 1.0 0.0e+00
> 0.0e+00 0.0e+00 97100 0 0 0 97100 0 0 0 1840
> > > KSPSolve_FS_0 5 1.0 7.5364e-04 1.0 0.00e+00 0.0 0.0e+00
> 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 0
> > > KSPSolve_FS_Schu 5 1.0 8.8785e+01 1.0 1.63e+11 1.0 0.0e+00
> 0.0e+00 0.0e+00 97100 0 0 0 97100 0 0 0 1840
> > > KSPSolve_FS_Low 5 1.0 2.1019e-03 1.0 0.00e+00 0.0 0.0e+00
> 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 0
> > > ------------------------------------------------------------
> ------------------------------------------------------------
> > >
> > > Memory usage is given in bytes:
> > >
> > > Object Type Creations Destructions Memory Descendants'
> Mem.
> > > Reports information only for process 0.
> > >
> > > --- Event Stage 0: Main Stage
> > >
> > > Vector 91 91 9693912 0.
> > > Vector Scatter 24 24 15936 0.
> > > Index Set 51 51 537888 0.
> > > IS L to G Mapping 3 3 240408 0.
> > > Matrix 13 13 64097868 0.
> > > Krylov Solver 6 6 7888 0.
> > > Preconditioner 6 6 6288 0.
> > > Viewer 1 0 0 0.
> > > Distributed Mesh 1 1 4624 0.
> > > Star Forest Bipartite Graph 2 2 1616 0.
> > > Discrete System 1 1 872 0.
> > > ============================================================
> ============================================================
> > > Average time to get PetscTime(): 0.
> > > #PETSc Option Table entries:
> > > -ksp_monitor
> > > -ksp_view
> > > -log_view
> > > #End of PETSc Option Table entries
> > > Compiled without FORTRAN kernels
> > > Compiled with full precision matrices (default)
> > > sizeof(short) 2 sizeof(int) 4 sizeof(long) 8 sizeof(void*) 8
> sizeof(PetscScalar) 8 sizeof(PetscInt) 4
> > > Configure options: --with-shared-libraries=1 --with-debugging=0
> --download-suitesparse --download-blacs --download-ptscotch=yes
> --with-blas-lapack-dir=/opt/intel/system_studio_2015.2.050/mkl
> --CXXFLAGS=-Wl,--no-as-needed --download-scalapack --download-mumps
> --download-metis --prefix=/home/dknez/software/libmesh_install/opt_real/petsc
> --download-hypre --download-ml
> > > -----------------------------------------
> > > Libraries compiled on Wed Sep 21 17:38:52 2016 on david-Lenovo
> > > Machine characteristics: Linux-4.4.0-38-generic-x86_64-
> with-Ubuntu-16.04-xenial
> > > Using PETSc directory: /home/dknez/software/petsc-src
> > > Using PETSc arch: arch-linux2-c-opt
> > > -----------------------------------------
> > >
> > > Using C compiler: mpicc -fPIC -Wall -Wwrite-strings
> -Wno-strict-aliasing -Wno-unknown-pragmas -fvisibility=hidden -g -O
> ${COPTFLAGS} ${CFLAGS}
> > > Using Fortran compiler: mpif90 -fPIC -Wall -ffree-line-length-0
> -Wno-unused-dummy-argument -g -O ${FOPTFLAGS} ${FFLAGS}
> > > -----------------------------------------
> > >
> > > Using include paths: -I/home/dknez/software/petsc-src/arch-linux2-c-opt/include
> -I/home/dknez/software/petsc-src/include -I/home/dknez/software/petsc-src/include
> -I/home/dknez/software/petsc-src/arch-linux2-c-opt/include
> -I/home/dknez/software/libmesh_install/opt_real/petsc/include
> -I/usr/lib/openmpi/include/openmpi/opal/mca/event/libevent2021/libevent
> -I/usr/lib/openmpi/include/openmpi/opal/mca/event/libevent2021/libevent/include
> -I/usr/lib/openmpi/include -I/usr/lib/openmpi/include/openmpi
> > > -----------------------------------------
> > >
> > > Using C linker: mpicc
> > > Using Fortran linker: mpif90
> > > Using libraries: -Wl,-rpath,/home/dknez/software/petsc-src/arch-linux2-c-opt/lib
> -L/home/dknez/software/petsc-src/arch-linux2-c-opt/lib -lpetsc
> -Wl,-rpath,/home/dknez/software/libmesh_install/opt_real/petsc/lib
> -L/home/dknez/software/libmesh_install/opt_real/petsc/lib -lcmumps
> -ldmumps -lsmumps -lzmumps -lmumps_common -lpord -lmetis -lHYPRE
> -Wl,-rpath,/usr/lib/openmpi/lib -L/usr/lib/openmpi/lib
> -Wl,-rpath,/usr/lib/gcc/x86_64-linux-gnu/5 -L/usr/lib/gcc/x86_64-linux-gnu/5
> -Wl,-rpath,/usr/lib/x86_64-linux-gnu -L/usr/lib/x86_64-linux-gnu
> -Wl,-rpath,/lib/x86_64-linux-gnu -L/lib/x86_64-linux-gnu -lmpi_cxx
> -lstdc++ -lscalapack -lml -lmpi_cxx -lstdc++ -lumfpack -lklu -lcholmod
> -lbtf -lccolamd -lcolamd -lcamd -lamd -lsuitesparseconfig
> -Wl,-rpath,/opt/intel/system_studio_2015.2.050/mkl/lib/intel64
> -L/opt/intel/system_studio_2015.2.050/mkl/lib/intel64 -lmkl_intel_lp64
> -lmkl_sequential -lmkl_core -lpthread -lm -lhwloc -lptesmumps -lptscotch
> -lptscotcherr -lscotch -lscotcherr -lX11 -lm -lmpi_usempif08
> -lmpi_usempi_ignore_tkr -lmpi_mpifh -lgfortran -lm -lgfortran -lm
> -lquadmath -lm -lmpi_cxx -lstdc++ -lrt -lm -lpthread -lz
> -Wl,-rpath,/usr/lib/openmpi/lib -L/usr/lib/openmpi/lib
> -Wl,-rpath,/usr/lib/gcc/x86_64-linux-gnu/5 -L/usr/lib/gcc/x86_64-linux-gnu/5
> -Wl,-rpath,/usr/lib/x86_64-linux-gnu -L/usr/lib/x86_64-linux-gnu
> -Wl,-rpath,/lib/x86_64-linux-gnu -L/lib/x86_64-linux-gnu
> -Wl,-rpath,/usr/lib/x86_64-linux-gnu -L/usr/lib/x86_64-linux-gnu -ldl
> -Wl,-rpath,/usr/lib/openmpi/lib -lmpi -lgcc_s -lpthread -ldl
> > > -----------------------------------------
> > >
> > >
> > >
> > >
> > >
> > >
> > >
> >
> >
> > <logfile_1.txt><logfile_2.txt>
>
>
--
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
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