<div dir="ltr"><br><div class="gmail_extra"><br><div class="gmail_quote">On 11 January 2017 at 22:29, David Knezevic <span dir="ltr"><<a href="mailto:david.knezevic@akselos.com" target="_blank">david.knezevic@akselos.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr"><div class="gmail_extra">Thanks very much for the input. I tried with "selfp" and it's about the same (log below), </div></div></blockquote><div><br></div><div>Yeah, looks similar.<br></div><div> </div><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr"><div class="gmail_extra">so I gather that I'll have to look into a user-defined approximation to S.</div></div></blockquote><div><br></div><div>Where does the 2x2 block system come from?<br></div><div>Maybe someone on the list knows the right approximation to use for S.<br><br></div><div><br> </div><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr"><div class="gmail_extra"><br></div><div class="gmail_extra">Thanks,</div><div class="gmail_extra">David</div><div class="gmail_extra"><br></div><div class="gmail_extra"><br></div><div class="gmail_extra">------------------------------<wbr>-----------</div><div class="gmail_extra"><br></div><div class="gmail_extra"><div class="gmail_extra"> 0 KSP Residual norm 5.405528187695e+04 </div><div class="gmail_extra"> 1 KSP Residual norm 2.187814910803e+02 </div><div class="gmail_extra"> 2 KSP Residual norm 1.019051577515e-01 </div><div class="gmail_extra"> 3 KSP Residual norm 4.370464012859e-04 </div><div class="gmail_extra">KSP Object: 1 MPI processes</div><div class="gmail_extra"> type: cg</div><div class="gmail_extra"> maximum iterations=1000</div><div class="gmail_extra"> tolerances: relative=1e-06, absolute=1e-50, divergence=10000.</div><div class="gmail_extra"> left preconditioning</div><div class="gmail_extra"> using nonzero initial guess</div><div class="gmail_extra"> using PRECONDITIONED norm type for convergence test</div><div class="gmail_extra">PC Object: 1 MPI processes</div><div class="gmail_extra"> type: fieldsplit</div><div class="gmail_extra"> FieldSplit with Schur preconditioner, factorization FULL</div><div class="gmail_extra"> Preconditioner for the Schur complement formed from Sp, an assembled approximation to S, which uses (lumped, if requested) A00's diagonal's inverse</div><div class="gmail_extra"> Split info:</div><div class="gmail_extra"> Split number 0 Defined by IS</div><div class="gmail_extra"> Split number 1 Defined by IS</div><div class="gmail_extra"> KSP solver for A00 block</div><div class="gmail_extra"> KSP Object: (fieldsplit_RB_split_) 1 MPI processes</div><div class="gmail_extra"> type: preonly</div><div class="gmail_extra"> maximum iterations=10000, initial guess is zero</div><div class="gmail_extra"> tolerances: relative=1e-05, absolute=1e-50, divergence=10000.</div><div class="gmail_extra"> left preconditioning</div><div class="gmail_extra"> using NONE norm type for convergence test</div><div class="gmail_extra"> PC Object: (fieldsplit_RB_split_) 1 MPI processes</div><div class="gmail_extra"> type: cholesky</div><div class="gmail_extra"> Cholesky: out-of-place factorization</div><div class="gmail_extra"> tolerance for zero pivot 2.22045e-14</div><div class="gmail_extra"> matrix ordering: natural</div><div class="gmail_extra"> factor fill ratio given 0., needed 0.</div><div class="gmail_extra"> Factored matrix follows:</div><div class="gmail_extra"> Mat Object: 1 MPI processes</div><div class="gmail_extra"> type: seqaij</div><div class="gmail_extra"> rows=324, cols=324</div><div class="gmail_extra"> package used to perform factorization: mumps</div><div class="gmail_extra"> total: nonzeros=3042, allocated nonzeros=3042</div><div class="gmail_extra"> total number of mallocs used during MatSetValues calls =0</div><div class="gmail_extra"> MUMPS run parameters:</div><div class="gmail_extra"> SYM (matrix type): 2 </div><div class="gmail_extra"> PAR (host participation): 1 </div><div class="gmail_extra"> ICNTL(1) (output for error): 6 </div><div class="gmail_extra"> ICNTL(2) (output of diagnostic msg): 0 </div><div class="gmail_extra"> ICNTL(3) (output for global info): 0 </div><div class="gmail_extra"> ICNTL(4) (level of printing): 0 </div><div class="gmail_extra"> ICNTL(5) (input mat struct): 0 </div><div class="gmail_extra"> ICNTL(6) (matrix prescaling): 7 </div><div class="gmail_extra"> ICNTL(7) (sequentia matrix ordering):7 </div><div class="gmail_extra"> ICNTL(8) (scalling strategy): 77 </div><div class="gmail_extra"> ICNTL(10) (max num of refinements): 0 </div><div class="gmail_extra"> ICNTL(11) (error analysis): 0 </div><div class="gmail_extra"> ICNTL(12) (efficiency control): 0 </div><div class="gmail_extra"> ICNTL(13) (efficiency control): 0 </div><div class="gmail_extra"> ICNTL(14) (percentage of estimated workspace increase): 20 </div><div class="gmail_extra"> ICNTL(18) (input mat struct): 0 </div><div class="gmail_extra"> ICNTL(19) (Shur complement info): 0 </div><div class="gmail_extra"> ICNTL(20) (rhs sparse pattern): 0 </div><div class="gmail_extra"> ICNTL(21) (solution struct): 0 </div><div class="gmail_extra"> ICNTL(22) (in-core/out-of-core facility): 0 </div><div class="gmail_extra"> ICNTL(23) (max size of memory can be allocated locally):0 </div><div class="gmail_extra"> ICNTL(24) (detection of null pivot rows): 0 </div><div class="gmail_extra"> ICNTL(25) (computation of a null space basis): 0 </div><div class="gmail_extra"> ICNTL(26) (Schur options for rhs or solution): 0 </div><div class="gmail_extra"> ICNTL(27) (experimental parameter): -24 </div><div class="gmail_extra"> ICNTL(28) (use parallel or sequential ordering): 1 </div><div class="gmail_extra"> ICNTL(29) (parallel ordering): 0 </div><div class="gmail_extra"> ICNTL(30) (user-specified set of entries in inv(A)): 0 </div><div class="gmail_extra"> ICNTL(31) (factors is discarded in the solve phase): 0 </div><div class="gmail_extra"> ICNTL(33) (compute determinant): 0 </div><div class="gmail_extra"> CNTL(1) (relative pivoting threshold): 0.01 </div><div class="gmail_extra"> CNTL(2) (stopping criterion of refinement): 1.49012e-08 </div><div class="gmail_extra"> CNTL(3) (absolute pivoting threshold): 0. </div><div class="gmail_extra"> CNTL(4) (value of static pivoting): -1. </div><div class="gmail_extra"> CNTL(5) (fixation for null pivots): 0. </div><div class="gmail_extra"> RINFO(1) (local estimated flops for the elimination after analysis): </div><div class="gmail_extra"> [0] 29394. </div><div class="gmail_extra"> RINFO(2) (local estimated flops for the assembly after factorization): </div><div class="gmail_extra"> [0] 1092. </div><div class="gmail_extra"> RINFO(3) (local estimated flops for the elimination after factorization): </div><div class="gmail_extra"> [0] 29394. </div><div class="gmail_extra"> INFO(15) (estimated size of (in MB) MUMPS internal data for running numerical factorization): </div><div class="gmail_extra"> [0] 1 </div><div class="gmail_extra"> INFO(16) (size of (in MB) MUMPS internal data used during numerical factorization): </div><div class="gmail_extra"> [0] 1 </div><div class="gmail_extra"> INFO(23) (num of pivots eliminated on this processor after factorization): </div><div class="gmail_extra"> [0] 324 </div><div class="gmail_extra"> RINFOG(1) (global estimated flops for the elimination after analysis): 29394. </div><div class="gmail_extra"> RINFOG(2) (global estimated flops for the assembly after factorization): 1092. </div><div class="gmail_extra"> RINFOG(3) (global estimated flops for the elimination after factorization): 29394. </div><div class="gmail_extra"> (RINFOG(12) RINFOG(13))*2^INFOG(34) (determinant): (0.,0.)*(2^0)</div><div class="gmail_extra"> INFOG(3) (estimated real workspace for factors on all processors after analysis): 3888 </div><div class="gmail_extra"> INFOG(4) (estimated integer workspace for factors on all processors after analysis): 2067 </div><div class="gmail_extra"> INFOG(5) (estimated maximum front size in the complete tree): 12 </div><div class="gmail_extra"> INFOG(6) (number of nodes in the complete tree): 53 </div><div class="gmail_extra"> INFOG(7) (ordering option effectively use after analysis): 2 </div><div class="gmail_extra"> INFOG(8) (structural symmetry in percent of the permuted matrix after analysis): 100 </div><div class="gmail_extra"> INFOG(9) (total real/complex workspace to store the matrix factors after factorization): 3888 </div><div class="gmail_extra"> INFOG(10) (total integer space store the matrix factors after factorization): 2067 </div><div class="gmail_extra"> INFOG(11) (order of largest frontal matrix after factorization): 12 </div><div class="gmail_extra"> INFOG(12) (number of off-diagonal pivots): 0 </div><div class="gmail_extra"> INFOG(13) (number of delayed pivots after factorization): 0 </div><div class="gmail_extra"> INFOG(14) (number of memory compress after factorization): 0 </div><div class="gmail_extra"> INFOG(15) (number of steps of iterative refinement after solution): 0 </div><div class="gmail_extra"> INFOG(16) (estimated size (in MB) of all MUMPS internal data for factorization after analysis: value on the most memory consuming processor): 1 </div><div class="gmail_extra"> INFOG(17) (estimated size of all MUMPS internal data for factorization after analysis: sum over all processors): 1 </div><div class="gmail_extra"> INFOG(18) (size of all MUMPS internal data allocated during factorization: value on the most memory consuming processor): 1 </div><div class="gmail_extra"> INFOG(19) (size of all MUMPS internal data allocated during factorization: sum over all processors): 1 </div><div class="gmail_extra"> INFOG(20) (estimated number of entries in the factors): 3042 </div><div class="gmail_extra"> INFOG(21) (size in MB of memory effectively used during factorization - value on the most memory consuming processor): 1 </div><div class="gmail_extra"> INFOG(22) (size in MB of memory effectively used during factorization - sum over all processors): 1 </div><div class="gmail_extra"> INFOG(23) (after analysis: value of ICNTL(6) effectively used): 5 </div><div class="gmail_extra"> INFOG(24) (after analysis: value of ICNTL(12) effectively used): 1 </div><div class="gmail_extra"> INFOG(25) (after factorization: number of pivots modified by static pivoting): 0 </div><div class="gmail_extra"> INFOG(28) (after factorization: number of null pivots encountered): 0</div><div class="gmail_extra"> INFOG(29) (after factorization: effective number of entries in the factors (sum over all processors)): 3042</div><div class="gmail_extra"> INFOG(30, 31) (after solution: size in Mbytes of memory used during solution phase): 0, 0</div><div class="gmail_extra"> INFOG(32) (after analysis: type of analysis done): 1</div><div class="gmail_extra"> INFOG(33) (value used for ICNTL(8)): -2</div><div class="gmail_extra"> INFOG(34) (exponent of the determinant if determinant is requested): 0</div><div class="gmail_extra"> linear system matrix = precond matrix:</div><div class="gmail_extra"> Mat Object: (fieldsplit_RB_split_) 1 MPI processes</div><div class="gmail_extra"> type: seqaij</div><div class="gmail_extra"> rows=324, cols=324</div><div class="gmail_extra"> total: nonzeros=5760, allocated nonzeros=5760</div><div class="gmail_extra"> total number of mallocs used during MatSetValues calls =0</div><div class="gmail_extra"> using I-node routines: found 108 nodes, limit used is 5</div><div class="gmail_extra"> KSP solver for S = A11 - A10 inv(A00) A01 </div><div class="gmail_extra"> KSP Object: (fieldsplit_FE_split_) 1 MPI processes</div><div class="gmail_extra"> type: cg</div><div class="gmail_extra"> maximum iterations=10000, initial guess is zero</div><div class="gmail_extra"> tolerances: relative=1e-05, absolute=1e-50, divergence=10000.</div><div class="gmail_extra"> left preconditioning</div><div class="gmail_extra"> using PRECONDITIONED norm type for convergence test</div><div class="gmail_extra"> PC Object: (fieldsplit_FE_split_) 1 MPI processes</div><div class="gmail_extra"> type: bjacobi</div><div class="gmail_extra"> block Jacobi: number of blocks = 1</div><div class="gmail_extra"> Local solve is same for all blocks, in the following KSP and PC objects:</div><div class="gmail_extra"> KSP Object: (fieldsplit_FE_split_sub_) 1 MPI processes</div><div class="gmail_extra"> type: preonly</div><div class="gmail_extra"> maximum iterations=10000, initial guess is zero</div><div class="gmail_extra"> tolerances: relative=1e-05, absolute=1e-50, divergence=10000.</div><div class="gmail_extra"> left preconditioning</div><div class="gmail_extra"> using NONE norm type for convergence test</div><div class="gmail_extra"> PC Object: (fieldsplit_FE_split_sub_) 1 MPI processes</div><div class="gmail_extra"> type: ilu</div><div class="gmail_extra"> ILU: out-of-place factorization</div><div class="gmail_extra"> 0 levels of fill</div><div class="gmail_extra"> tolerance for zero pivot 2.22045e-14</div><div class="gmail_extra"> matrix ordering: natural</div><div class="gmail_extra"> factor fill ratio given 1., needed 1.</div><div class="gmail_extra"> Factored matrix follows:</div><div class="gmail_extra"> Mat Object: 1 MPI processes</div><div class="gmail_extra"> type: seqaij</div><div class="gmail_extra"> rows=28476, cols=28476</div><div class="gmail_extra"> package used to perform factorization: petsc</div><div class="gmail_extra"> total: nonzeros=1037052, allocated nonzeros=1037052</div><div class="gmail_extra"> total number of mallocs used during MatSetValues calls =0</div><div class="gmail_extra"> using I-node routines: found 9489 nodes, limit used is 5</div><div class="gmail_extra"> linear system matrix = precond matrix:</div><div class="gmail_extra"> Mat Object: 1 MPI processes</div><div class="gmail_extra"> type: seqaij</div><div class="gmail_extra"> rows=28476, cols=28476</div><div class="gmail_extra"> total: nonzeros=1037052, allocated nonzeros=1037052</div><div class="gmail_extra"> total number of mallocs used during MatSetValues calls =0</div><div class="gmail_extra"> using I-node routines: found 9489 nodes, limit used is 5</div><div class="gmail_extra"> linear system matrix followed by preconditioner matrix:</div><div class="gmail_extra"> Mat Object: (fieldsplit_FE_split_) 1 MPI processes</div><div class="gmail_extra"> type: schurcomplement</div><div class="gmail_extra"> rows=28476, cols=28476</div><div class="gmail_extra"> Schur complement A11 - A10 inv(A00) A01</div><div class="gmail_extra"> A11</div><div class="gmail_extra"> Mat Object: (fieldsplit_FE_split_) 1 MPI processes</div><div class="gmail_extra"> type: seqaij</div><div class="gmail_extra"> rows=28476, cols=28476</div><div class="gmail_extra"> total: nonzeros=1017054, allocated nonzeros=1017054</div><div class="gmail_extra"> total number of mallocs used during MatSetValues calls =0</div><div class="gmail_extra"> using I-node routines: found 9492 nodes, limit used is 5</div><div class="gmail_extra"> A10</div><div class="gmail_extra"> Mat Object: 1 MPI processes</div><div class="gmail_extra"> type: seqaij</div><div class="gmail_extra"> rows=28476, cols=324</div><div class="gmail_extra"> total: nonzeros=936, allocated nonzeros=936</div><div class="gmail_extra"> total number of mallocs used during MatSetValues calls =0</div><div class="gmail_extra"> using I-node routines: found 5717 nodes, limit used is 5</div><div class="gmail_extra"> KSP of A00</div><div class="gmail_extra"> KSP Object: (fieldsplit_RB_split_) 1 MPI processes</div><div class="gmail_extra"> type: preonly</div><div class="gmail_extra"> maximum iterations=10000, initial guess is zero</div><div class="gmail_extra"> tolerances: relative=1e-05, absolute=1e-50, divergence=10000.</div><div class="gmail_extra"> left preconditioning</div><div class="gmail_extra"> using NONE norm type for convergence test</div><div class="gmail_extra"> PC Object: (fieldsplit_RB_split_) 1 MPI processes</div><div class="gmail_extra"> type: cholesky</div><div class="gmail_extra"> Cholesky: out-of-place factorization</div><div class="gmail_extra"> tolerance for zero pivot 2.22045e-14</div><div class="gmail_extra"> matrix ordering: natural</div><div class="gmail_extra"> factor fill ratio given 0., needed 0.</div><div class="gmail_extra"> Factored matrix follows:</div><div class="gmail_extra"> Mat Object: 1 MPI processes</div><div class="gmail_extra"> type: seqaij</div><div class="gmail_extra"> rows=324, cols=324</div><div class="gmail_extra"> package used to perform factorization: mumps</div><div class="gmail_extra"> total: nonzeros=3042, allocated nonzeros=3042</div><div class="gmail_extra"> total number of mallocs used during MatSetValues calls =0</div><div class="gmail_extra"> MUMPS run parameters:</div><div class="gmail_extra"> SYM (matrix type): 2 </div><div class="gmail_extra"> PAR (host participation): 1 </div><div class="gmail_extra"> ICNTL(1) (output for error): 6 </div><div class="gmail_extra"> ICNTL(2) (output of diagnostic msg): 0 </div><div class="gmail_extra"> ICNTL(3) (output for global info): 0 </div><div class="gmail_extra"> ICNTL(4) (level of printing): 0 </div><div class="gmail_extra"> ICNTL(5) (input mat struct): 0 </div><div class="gmail_extra"> ICNTL(6) (matrix prescaling): 7 </div><div class="gmail_extra"> ICNTL(7) (sequentia matrix ordering):7 </div><div class="gmail_extra"> ICNTL(8) (scalling strategy): 77 </div><div class="gmail_extra"> ICNTL(10) (max num of refinements): 0 </div><div class="gmail_extra"> ICNTL(11) (error analysis): 0 </div><div class="gmail_extra"> ICNTL(12) (efficiency control): 0 </div><div class="gmail_extra"> ICNTL(13) (efficiency control): 0 </div><div class="gmail_extra"> ICNTL(14) (percentage of estimated workspace increase): 20 </div><div class="gmail_extra"> ICNTL(18) (input mat struct): 0 </div><div class="gmail_extra"> ICNTL(19) (Shur complement info): 0 </div><div class="gmail_extra"> ICNTL(20) (rhs sparse pattern): 0 </div><div class="gmail_extra"> ICNTL(21) (solution struct): 0 </div><div class="gmail_extra"> ICNTL(22) (in-core/out-of-core facility): 0 </div><div class="gmail_extra"> ICNTL(23) (max size of memory can be allocated locally):0 </div><div class="gmail_extra"> ICNTL(24) (detection of null pivot rows): 0 </div><div class="gmail_extra"> ICNTL(25) (computation of a null space basis): 0 </div><div class="gmail_extra"> ICNTL(26) (Schur options for rhs or solution): 0 </div><div class="gmail_extra"> ICNTL(27) (experimental parameter): -24 </div><div class="gmail_extra"> ICNTL(28) (use parallel or sequential ordering): 1 </div><div class="gmail_extra"> ICNTL(29) (parallel ordering): 0 </div><div class="gmail_extra"> ICNTL(30) (user-specified set of entries in inv(A)): 0 </div><div class="gmail_extra"> ICNTL(31) (factors is discarded in the solve phase): 0 </div><div class="gmail_extra"> ICNTL(33) (compute determinant): 0 </div><div class="gmail_extra"> CNTL(1) (relative pivoting threshold): 0.01 </div><div class="gmail_extra"> CNTL(2) (stopping criterion of refinement): 1.49012e-08 </div><div class="gmail_extra"> CNTL(3) (absolute pivoting threshold): 0. </div><div class="gmail_extra"> CNTL(4) (value of static pivoting): -1. </div><div class="gmail_extra"> CNTL(5) (fixation for null pivots): 0. </div><div class="gmail_extra"> RINFO(1) (local estimated flops for the elimination after analysis): </div><div class="gmail_extra"> [0] 29394. </div><div class="gmail_extra"> RINFO(2) (local estimated flops for the assembly after factorization): </div><div class="gmail_extra"> [0] 1092. </div><div class="gmail_extra"> RINFO(3) (local estimated flops for the elimination after factorization): </div><div class="gmail_extra"> [0] 29394. </div><div class="gmail_extra"> INFO(15) (estimated size of (in MB) MUMPS internal data for running numerical factorization): </div><div class="gmail_extra"> [0] 1 </div><div class="gmail_extra"> INFO(16) (size of (in MB) MUMPS internal data used during numerical factorization): </div><div class="gmail_extra"> [0] 1 </div><div class="gmail_extra"> INFO(23) (num of pivots eliminated on this processor after factorization): </div><div class="gmail_extra"> [0] 324 </div><div class="gmail_extra"> RINFOG(1) (global estimated flops for the elimination after analysis): 29394. </div><div class="gmail_extra"> RINFOG(2) (global estimated flops for the assembly after factorization): 1092. </div><div class="gmail_extra"> RINFOG(3) (global estimated flops for the elimination after factorization): 29394. </div><div class="gmail_extra"> (RINFOG(12) RINFOG(13))*2^INFOG(34) (determinant): (0.,0.)*(2^0)</div><div class="gmail_extra"> INFOG(3) (estimated real workspace for factors on all processors after analysis): 3888 </div><div class="gmail_extra"> INFOG(4) (estimated integer workspace for factors on all processors after analysis): 2067 </div><div class="gmail_extra"> INFOG(5) (estimated maximum front size in the complete tree): 12 </div><div class="gmail_extra"> INFOG(6) (number of nodes in the complete tree): 53 </div><div class="gmail_extra"> INFOG(7) (ordering option effectively use after analysis): 2 </div><div class="gmail_extra"> INFOG(8) (structural symmetry in percent of the permuted matrix after analysis): 100 </div><div class="gmail_extra"> INFOG(9) (total real/complex workspace to store the matrix factors after factorization): 3888 </div><div class="gmail_extra"> INFOG(10) (total integer space store the matrix factors after factorization): 2067 </div><div class="gmail_extra"> INFOG(11) (order of largest frontal matrix after factorization): 12 </div><div class="gmail_extra"> INFOG(12) (number of off-diagonal pivots): 0 </div><div class="gmail_extra"> INFOG(13) (number of delayed pivots after factorization): 0 </div><div class="gmail_extra"> INFOG(14) (number of memory compress after factorization): 0 </div><div class="gmail_extra"> INFOG(15) (number of steps of iterative refinement after solution): 0 </div><div class="gmail_extra"> INFOG(16) (estimated size (in MB) of all MUMPS internal data for factorization after analysis: value on the most memory consuming processor): 1 </div><div class="gmail_extra"> INFOG(17) (estimated size of all MUMPS internal data for factorization after analysis: sum over all processors): 1 </div><div class="gmail_extra"> INFOG(18) (size of all MUMPS internal data allocated during factorization: value on the most memory consuming processor): 1 </div><div class="gmail_extra"> INFOG(19) (size of all MUMPS internal data allocated during factorization: sum over all processors): 1 </div><div class="gmail_extra"> INFOG(20) (estimated number of entries in the factors): 3042 </div><div class="gmail_extra"> INFOG(21) (size in MB of memory effectively used during factorization - value on the most memory consuming processor): 1 </div><div class="gmail_extra"> INFOG(22) (size in MB of memory effectively used during factorization - sum over all processors): 1 </div><div class="gmail_extra"> INFOG(23) (after analysis: value of ICNTL(6) effectively used): 5 </div><div class="gmail_extra"> INFOG(24) (after analysis: value of ICNTL(12) effectively used): 1 </div><div class="gmail_extra"> INFOG(25) (after factorization: number of pivots modified by static pivoting): 0 </div><div class="gmail_extra"> INFOG(28) (after factorization: number of null pivots encountered): 0</div><div class="gmail_extra"> INFOG(29) (after factorization: effective number of entries in the factors (sum over all processors)): 3042</div><div class="gmail_extra"> INFOG(30, 31) (after solution: size in Mbytes of memory used during solution phase): 0, 0</div><div class="gmail_extra"> INFOG(32) (after analysis: type of analysis done): 1</div><div class="gmail_extra"> INFOG(33) (value used for ICNTL(8)): -2</div><div class="gmail_extra"> INFOG(34) (exponent of the determinant if determinant is requested): 0</div><div class="gmail_extra"> linear system matrix = precond matrix:</div><div class="gmail_extra"> Mat Object: (fieldsplit_RB_split_) 1 MPI processes</div><div class="gmail_extra"> type: seqaij</div><div class="gmail_extra"> rows=324, cols=324</div><div class="gmail_extra"> total: nonzeros=5760, allocated nonzeros=5760</div><div class="gmail_extra"> total number of mallocs used during MatSetValues calls =0</div><div class="gmail_extra"> using I-node routines: found 108 nodes, limit used is 5</div><div class="gmail_extra"> A01</div><div class="gmail_extra"> Mat Object: 1 MPI processes</div><div class="gmail_extra"> type: seqaij</div><div class="gmail_extra"> rows=324, cols=28476</div><div class="gmail_extra"> total: nonzeros=936, allocated nonzeros=936</div><div class="gmail_extra"> total number of mallocs used during MatSetValues calls =0</div><div class="gmail_extra"> using I-node routines: found 67 nodes, limit used is 5</div><div class="gmail_extra"> Mat Object: 1 MPI processes</div><div class="gmail_extra"> type: seqaij</div><div class="gmail_extra"> rows=28476, cols=28476</div><div class="gmail_extra"> total: nonzeros=1037052, allocated nonzeros=1037052</div><div class="gmail_extra"> total number of mallocs used during MatSetValues calls =0</div><div class="gmail_extra"> using I-node routines: found 9489 nodes, limit used is 5</div><div class="gmail_extra"> linear system matrix = precond matrix:</div><div class="gmail_extra"> Mat Object: () 1 MPI processes</div><div class="gmail_extra"> type: seqaij</div><div class="gmail_extra"> rows=28800, cols=28800</div><div class="gmail_extra"> total: nonzeros=1024686, allocated nonzeros=1024794</div><div class="gmail_extra"> total number of mallocs used during MatSetValues calls =0</div><div class="gmail_extra"> using I-node routines: found 9600 nodes, limit used is 5</div><div><br></div></div><div class="gmail_extra"><div class="gmail_extra">------------------------------<wbr>---------------- PETSc Performance Summary: ------------------------------<wbr>----------------</div><div class="gmail_extra"><br></div><div class="gmail_extra">/home/dknez/akselos-dev/scrbe/<wbr>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</div><div class="gmail_extra">Using Petsc Release Version 3.7.3, unknown </div><div class="gmail_extra"><br></div><div class="gmail_extra"> Max Max/Min Avg Total </div><div class="gmail_extra">Time (sec): 9.638e+01 1.00000 9.638e+01</div><div class="gmail_extra">Objects: 2.030e+02 1.00000 2.030e+02</div><div class="gmail_extra">Flops: 1.732e+11 1.00000 1.732e+11 1.732e+11</div><div class="gmail_extra">Flops/sec: 1.797e+09 1.00000 1.797e+09 1.797e+09</div><div class="gmail_extra">MPI Messages: 0.000e+00 0.00000 0.000e+00 0.000e+00</div><div class="gmail_extra">MPI Message Lengths: 0.000e+00 0.00000 0.000e+00 0.000e+00</div><div class="gmail_extra">MPI Reductions: 0.000e+00 0.00000</div><div class="gmail_extra"><br></div><div class="gmail_extra">Flop counting convention: 1 flop = 1 real number operation of type (multiply/divide/add/subtract)</div><div class="gmail_extra"> e.g., VecAXPY() for real vectors of length N --> 2N flops</div><div class="gmail_extra"> and VecAXPY() for complex vectors of length N --> 8N flops</div><div class="gmail_extra"><br></div><div class="gmail_extra">Summary of Stages: ----- Time ------ ----- Flops ----- --- Messages --- -- Message Lengths -- -- Reductions --</div><div class="gmail_extra"> Avg %Total Avg %Total counts %Total Avg %Total counts %Total </div><div class="gmail_extra"> 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% </div><div class="gmail_extra"><br></div><div class="gmail_extra">------------------------------<wbr>------------------------------<wbr>------------------------------<wbr>------------------------------</div><div class="gmail_extra">See the 'Profiling' chapter of the users' manual for details on interpreting output.</div><div class="gmail_extra">Phase summary info:</div><div class="gmail_extra"> Count: number of times phase was executed</div><div class="gmail_extra"> Time and Flops: Max - maximum over all processors</div><div class="gmail_extra"> Ratio - ratio of maximum to minimum over all processors</div><div class="gmail_extra"> Mess: number of messages sent</div><div class="gmail_extra"> Avg. len: average message length (bytes)</div><div class="gmail_extra"> Reduct: number of global reductions</div><div class="gmail_extra"> Global: entire computation</div><div class="gmail_extra"> Stage: stages of a computation. Set stages with PetscLogStagePush() and PetscLogStagePop().</div><div class="gmail_extra"> %T - percent time in this phase %F - percent flops in this phase</div><div class="gmail_extra"> %M - percent messages in this phase %L - percent message lengths in this phase</div><div class="gmail_extra"> %R - percent reductions in this phase</div><div class="gmail_extra"> Total Mflop/s: 10e-6 * (sum of flops over all processors)/(max time over all processors)</div><div class="gmail_extra">------------------------------<wbr>------------------------------<wbr>------------------------------<wbr>------------------------------</div><div class="gmail_extra">Event Count Time (sec) Flops --- Global --- --- Stage --- Total</div><div class="gmail_extra"> Max Ratio Max Ratio Max Ratio Mess Avg len Reduct %T %F %M %L %R %T %F %M %L %R Mflop/s</div><div class="gmail_extra">------------------------------<wbr>------------------------------<wbr>------------------------------<wbr>------------------------------</div><div class="gmail_extra"><br></div><div class="gmail_extra">--- Event Stage 0: Main Stage</div><div class="gmail_extra"><br></div><div class="gmail_extra">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</div><div class="gmail_extra">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</div><div class="gmail_extra">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</div><div class="gmail_extra">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</div><div class="gmail_extra">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</div><div class="gmail_extra">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</div><div class="gmail_extra">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</div><div class="gmail_extra">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</div><div class="gmail_extra">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</div><div class="gmail_extra">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</div><div class="gmail_extra">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</div><div class="gmail_extra">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</div><div class="gmail_extra">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</div><div class="gmail_extra">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</div><div class="gmail_extra">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</div><div class="gmail_extra">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</div><div class="gmail_extra">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</div><div class="gmail_extra">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</div><div class="gmail_extra">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</div><div class="gmail_extra">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</div><div class="gmail_extra">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</div><div class="gmail_extra">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</div><div class="gmail_extra">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</div><div class="gmail_extra">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</div><div class="gmail_extra">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</div><div class="gmail_extra">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</div><div class="gmail_extra">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</div><div class="gmail_extra">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</div><div class="gmail_extra">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</div><div class="gmail_extra">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</div><div class="gmail_extra">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</div><div class="gmail_extra">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</div><div class="gmail_extra">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</div><div class="gmail_extra">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</div><div class="gmail_extra">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</div><div class="gmail_extra">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</div><div class="gmail_extra">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</div><div class="gmail_extra">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</div><div class="gmail_extra">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</div><div class="gmail_extra">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</div><div class="gmail_extra">------------------------------<wbr>------------------------------<wbr>------------------------------<wbr>------------------------------</div><div class="gmail_extra"><br></div><div class="gmail_extra">Memory usage is given in bytes:</div><div class="gmail_extra"><br></div><div class="gmail_extra">Object Type Creations Destructions Memory Descendants' Mem.</div><div class="gmail_extra">Reports information only for process 0.</div><div class="gmail_extra"><br></div><div class="gmail_extra">--- Event Stage 0: Main Stage</div><div class="gmail_extra"><br></div><div class="gmail_extra"> Vector 92 92 9698040 0.</div><div class="gmail_extra"> Vector Scatter 24 24 15936 0.</div><div class="gmail_extra"> Index Set 51 51 537876 0.</div><div class="gmail_extra"> IS L to G Mapping 3 3 240408 0.</div><div class="gmail_extra"> Matrix 16 16 77377776 0.</div><div class="gmail_extra"> Krylov Solver 6 6 7888 0.</div><div class="gmail_extra"> Preconditioner 6 6 6288 0.</div><div class="gmail_extra"> Viewer 1 0 0 0.</div><div class="gmail_extra"> Distributed Mesh 1 1 4624 0.</div><div class="gmail_extra">Star Forest Bipartite Graph 2 2 1616 0.</div><div class="gmail_extra"> Discrete System 1 1 872 0.</div><div class="gmail_extra">==============================<wbr>==============================<wbr>==============================<wbr>==============================</div><div class="gmail_extra">Average time to get PetscTime(): 0.</div><div class="gmail_extra">#PETSc Option Table entries:</div><div class="gmail_extra">-ksp_monitor</div><div class="gmail_extra">-ksp_view</div><div class="gmail_extra">-log_view</div><div class="gmail_extra">#End of PETSc Option Table entries</div><div class="gmail_extra">Compiled without FORTRAN kernels</div><div class="gmail_extra">Compiled with full precision matrices (default)</div><div class="gmail_extra">sizeof(short) 2 sizeof(int) 4 sizeof(long) 8 sizeof(void*) 8 sizeof(PetscScalar) 8 sizeof(PetscInt) 4</div><div class="gmail_extra">Configure options: --with-shared-libraries=1 --with-debugging=0 --download-suitesparse --download-blacs --download-ptscotch=yes --with-blas-lapack-dir=/opt/<wbr>intel/system_studio_2015.2.<wbr>050/mkl --CXXFLAGS=-Wl,--no-as-needed --download-scalapack --download-mumps --download-metis --prefix=/home/dknez/software/<wbr>libmesh_install/opt_real/petsc --download-hypre --download-ml</div><div class="gmail_extra">------------------------------<wbr>-----------</div><div class="gmail_extra">Libraries compiled on Wed Sep 21 17:38:52 2016 on david-Lenovo </div><div class="gmail_extra">Machine characteristics: Linux-4.4.0-38-generic-x86_64-<wbr>with-Ubuntu-16.04-xenial</div><div class="gmail_extra">Using PETSc directory: /home/dknez/software/petsc-src</div><div class="gmail_extra">Using PETSc arch: arch-linux2-c-opt</div><div class="gmail_extra">------------------------------<wbr>-----------</div><div class="gmail_extra"><br></div><div class="gmail_extra">Using C compiler: mpicc -fPIC -Wall -Wwrite-strings -Wno-strict-aliasing -Wno-unknown-pragmas -fvisibility=hidden -g -O ${COPTFLAGS} ${CFLAGS}</div><div class="gmail_extra">Using Fortran compiler: mpif90 -fPIC -Wall -ffree-line-length-0 -Wno-unused-dummy-argument -g -O ${FOPTFLAGS} ${FFLAGS} </div><div class="gmail_extra">------------------------------<wbr>-----------</div><div class="gmail_extra"><br></div><div class="gmail_extra">Using include paths: -I/home/dknez/software/petsc-<wbr>src/arch-linux2-c-opt/include -I/home/dknez/software/petsc-<wbr>src/include -I/home/dknez/software/petsc-<wbr>src/include -I/home/dknez/software/petsc-<wbr>src/arch-linux2-c-opt/include -I/home/dknez/software/<wbr>libmesh_install/opt_real/<wbr>petsc/include -I/usr/lib/openmpi/include/<wbr>openmpi/opal/mca/event/<wbr>libevent2021/libevent -I/usr/lib/openmpi/include/<wbr>openmpi/opal/mca/event/<wbr>libevent2021/libevent/include -I/usr/lib/openmpi/include -I/usr/lib/openmpi/include/<wbr>openmpi</div><div class="gmail_extra">------------------------------<wbr>-----------</div><div class="gmail_extra"><br></div><div class="gmail_extra">Using C linker: mpicc</div><div class="gmail_extra">Using Fortran linker: mpif90</div><div class="gmail_extra">Using libraries: -Wl,-rpath,/home/dknez/<wbr>software/petsc-src/arch-<wbr>linux2-c-opt/lib -L/home/dknez/software/petsc-<wbr>src/arch-linux2-c-opt/lib -lpetsc -Wl,-rpath,/home/dknez/<wbr>software/libmesh_install/opt_<wbr>real/petsc/lib -L/home/dknez/software/<wbr>libmesh_install/opt_real/<wbr>petsc/lib -lcmumps -ldmumps -lsmumps -lzmumps -lmumps_common -lpord -lmetis -lHYPRE -Wl,-rpath,/usr/lib/openmpi/<wbr>lib -L/usr/lib/openmpi/lib -Wl,-rpath,/usr/lib/gcc/x86_<wbr>64-linux-gnu/5 -L/usr/lib/gcc/x86_64-linux-<wbr>gnu/5 -Wl,-rpath,/usr/lib/x86_64-<wbr>linux-gnu -L/usr/lib/x86_64-linux-gnu -Wl,-rpath,/lib/x86_64-linux-<wbr>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_<wbr>studio_2015.2.050/mkl/lib/<wbr>intel64 -L/opt/intel/system_studio_<wbr>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/<wbr>lib -L/usr/lib/openmpi/lib -Wl,-rpath,/usr/lib/gcc/x86_<wbr>64-linux-gnu/5 -L/usr/lib/gcc/x86_64-linux-<wbr>gnu/5 -Wl,-rpath,/usr/lib/x86_64-<wbr>linux-gnu -L/usr/lib/x86_64-linux-gnu -Wl,-rpath,/lib/x86_64-linux-<wbr>gnu -L/lib/x86_64-linux-gnu -Wl,-rpath,/usr/lib/x86_64-<wbr>linux-gnu -L/usr/lib/x86_64-linux-gnu -ldl -Wl,-rpath,/usr/lib/openmpi/<wbr>lib -lmpi -lgcc_s -lpthread -ldl </div><div class="gmail_extra">------------------------------<wbr>-----------</div><div><br></div></div><div class="gmail_extra"><br></div><div class="gmail_extra"><br></div><div class="gmail_extra"><br><div class="gmail_quote">On Wed, Jan 11, 2017 at 4:49 PM, Dave May <span dir="ltr"><<a href="mailto:dave.mayhem23@gmail.com" target="_blank">dave.mayhem23@gmail.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex"><div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">It looks like the Schur solve is requiring a huge number of iterates to converge (based on the instances of MatMult).</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">This is killing the performance.</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"><br class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"></div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">Are you sure that A11 is a good approximation to S? You might consider trying the selfp option</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"><br class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"></div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"><a href="http://www.mcs.anl.gov/petsc/petsc-current/docs/manualpages/PC/PCFieldSplitSetSchurPre.html#PCFieldSplitSetSchurPre" class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg" target="_blank">http://www.mcs.anl.gov/petsc/p<wbr>etsc-current/docs/manualpages/<wbr>PC/PCFieldSplitSetSchurPre.<wbr>html#PCFieldSplitSetSchurPre</a><br class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"></div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"><br class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"></div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">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.</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"><br class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"></div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"><br class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"></div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">Thanks,</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> Dave</div></div></div><div class="m_6920403594308095878gmail-HOEnZb"><div class="m_6920403594308095878gmail-h5"><div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"><br class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"></div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"><br class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"><div class="gmail_quote m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">On Wed, 11 Jan 2017 at 22:34, David Knezevic <<a href="mailto:david.knezevic@akselos.com" class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg" target="_blank">david.knezevic@akselos.com</a>> wrote:<br class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"></div><blockquote class="gmail_quote m_6920403594308095878gmail-m_-7298681589884001740gmail_msg" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex"><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">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.</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"><br class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"></div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">The A00 block of my matrix is very small so I figured I'd specify a direct solver (i.e. MUMPS) for that block.</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"><br class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"></div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">So I did the following:</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">- PCFieldSplitSetIS to specify the indices of the two splits</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">- PCFieldSplitGetSubKSP to get the two KSP objects, and to set the solver and PC types for each (MUMPS for A00, ILU+CG for A11)</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">- I set -pc_fieldsplit_schur_fact_type full</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"><br class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"></div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">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?</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"><br class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"></div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">Many thanks,</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">David</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"><br class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"></div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">------------------------------<wbr>------------------------------<wbr>-----------------------</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"><br class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"></div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> 0 KSP Residual norm 5.405774214400e+04 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> 1 KSP Residual norm 1.849649014371e+02 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> 2 KSP Residual norm 7.462775074989e-02 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> 3 KSP Residual norm 2.680497175260e-04 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">KSP Object: 1 MPI processes</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> type: cg</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> maximum iterations=1000</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> tolerances: relative=1e-06, absolute=1e-50, divergence=10000.</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> left preconditioning</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> using nonzero initial guess</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> using PRECONDITIONED norm type for convergence test</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">PC Object: 1 MPI processes</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> type: fieldsplit</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> FieldSplit with Schur preconditioner, factorization FULL</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> Preconditioner for the Schur complement formed from A11</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> Split info:</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> Split number 0 Defined by IS</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> Split number 1 Defined by IS</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> KSP solver for A00 block</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> KSP Object: (fieldsplit_RB_split_) 1 MPI processes</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> type: preonly</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> maximum iterations=10000, initial guess is zero</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> tolerances: relative=1e-05, absolute=1e-50, divergence=10000.</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> left preconditioning</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> using NONE norm type for convergence test</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> PC Object: (fieldsplit_RB_split_) 1 MPI processes</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> type: cholesky</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> Cholesky: out-of-place factorization</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> tolerance for zero pivot 2.22045e-14</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> matrix ordering: natural</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> factor fill ratio given 0., needed 0.</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> Factored matrix follows:</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> Mat Object: 1 MPI processes</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> type: seqaij</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> rows=324, cols=324</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> package used to perform factorization: mumps</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> total: nonzeros=3042, allocated nonzeros=3042</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> total number of mallocs used during MatSetValues calls =0</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> MUMPS run parameters:</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> SYM (matrix type): 2 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> PAR (host participation): 1 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(1) (output for error): 6 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(2) (output of diagnostic msg): 0 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(3) (output for global info): 0 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(4) (level of printing): 0 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(5) (input mat struct): 0 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(6) (matrix prescaling): 7 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(7) (sequentia matrix ordering):7 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(8) (scalling strategy): 77 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(10) (max num of refinements): 0 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(11) (error analysis): 0 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(12) (efficiency control): 0 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(13) (efficiency control): 0 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(14) (percentage of estimated workspace increase): 20 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(18) (input mat struct): 0 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(19) (Shur complement info): 0 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(20) (rhs sparse pattern): 0 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(21) (solution struct): 0 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(22) (in-core/out-of-core facility): 0 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(23) (max size of memory can be allocated locally):0 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(24) (detection of null pivot rows): 0 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(25) (computation of a null space basis): 0 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(26) (Schur options for rhs or solution): 0 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(27) (experimental parameter): -24 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(28) (use parallel or sequential ordering): 1 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(29) (parallel ordering): 0 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(30) (user-specified set of entries in inv(A)): 0 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(31) (factors is discarded in the solve phase): 0 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(33) (compute determinant): 0 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> CNTL(1) (relative pivoting threshold): 0.01 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> CNTL(2) (stopping criterion of refinement): 1.49012e-08 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> CNTL(3) (absolute pivoting threshold): 0. </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> CNTL(4) (value of static pivoting): -1. </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> CNTL(5) (fixation for null pivots): 0. </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> RINFO(1) (local estimated flops for the elimination after analysis): </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> [0] 29394. </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> RINFO(2) (local estimated flops for the assembly after factorization): </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> [0] 1092. </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> RINFO(3) (local estimated flops for the elimination after factorization): </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> [0] 29394. </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFO(15) (estimated size of (in MB) MUMPS internal data for running numerical factorization): </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> [0] 1 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFO(16) (size of (in MB) MUMPS internal data used during numerical factorization): </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> [0] 1 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFO(23) (num of pivots eliminated on this processor after factorization): </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> [0] 324 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> RINFOG(1) (global estimated flops for the elimination after analysis): 29394. </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> RINFOG(2) (global estimated flops for the assembly after factorization): 1092. </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> RINFOG(3) (global estimated flops for the elimination after factorization): 29394. </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> (RINFOG(12) RINFOG(13))*2^INFOG(34) (determinant): (0.,0.)*(2^0)</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(3) (estimated real workspace for factors on all processors after analysis): 3888 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(4) (estimated integer workspace for factors on all processors after analysis): 2067 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(5) (estimated maximum front size in the complete tree): 12 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(6) (number of nodes in the complete tree): 53 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(7) (ordering option effectively use after analysis): 2 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(8) (structural symmetry in percent of the permuted matrix after analysis): 100 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(9) (total real/complex workspace to store the matrix factors after factorization): 3888 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(10) (total integer space store the matrix factors after factorization): 2067 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(11) (order of largest frontal matrix after factorization): 12 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(12) (number of off-diagonal pivots): 0 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(13) (number of delayed pivots after factorization): 0 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(14) (number of memory compress after factorization): 0 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(15) (number of steps of iterative refinement after solution): 0 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(16) (estimated size (in MB) of all MUMPS internal data for factorization after analysis: value on the most memory consuming processor): 1 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(17) (estimated size of all MUMPS internal data for factorization after analysis: sum over all processors): 1 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(18) (size of all MUMPS internal data allocated during factorization: value on the most memory consuming processor): 1 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(19) (size of all MUMPS internal data allocated during factorization: sum over all processors): 1 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(20) (estimated number of entries in the factors): 3042 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(21) (size in MB of memory effectively used during factorization - value on the most memory consuming processor): 1 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(22) (size in MB of memory effectively used during factorization - sum over all processors): 1 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(23) (after analysis: value of ICNTL(6) effectively used): 5 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(24) (after analysis: value of ICNTL(12) effectively used): 1 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(25) (after factorization: number of pivots modified by static pivoting): 0 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(28) (after factorization: number of null pivots encountered): 0</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(29) (after factorization: effective number of entries in the factors (sum over all processors)): 3042</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(30, 31) (after solution: size in Mbytes of memory used during solution phase): 0, 0</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(32) (after analysis: type of analysis done): 1</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(33) (value used for ICNTL(8)): -2</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(34) (exponent of the determinant if determinant is requested): 0</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> linear system matrix = precond matrix:</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> Mat Object: (fieldsplit_RB_split_) 1 MPI processes</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> type: seqaij</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> rows=324, cols=324</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> total: nonzeros=5760, allocated nonzeros=5760</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> total number of mallocs used during MatSetValues calls =0</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> using I-node routines: found 108 nodes, limit used is 5</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> KSP solver for S = A11 - A10 inv(A00) A01 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> KSP Object: (fieldsplit_FE_split_) 1 MPI processes</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> type: cg</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> maximum iterations=10000, initial guess is zero</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> tolerances: relative=1e-05, absolute=1e-50, divergence=10000.</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> left preconditioning</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> using PRECONDITIONED norm type for convergence test</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> PC Object: (fieldsplit_FE_split_) 1 MPI processes</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> type: bjacobi</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> block Jacobi: number of blocks = 1</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> Local solve is same for all blocks, in the following KSP and PC objects:</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> KSP Object: (fieldsplit_FE_split_sub_) 1 MPI processes</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> type: preonly</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> maximum iterations=10000, initial guess is zero</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> tolerances: relative=1e-05, absolute=1e-50, divergence=10000.</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> left preconditioning</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> using NONE norm type for convergence test</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> PC Object: (fieldsplit_FE_split_sub_) 1 MPI processes</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> type: ilu</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ILU: out-of-place factorization</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> 0 levels of fill</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> tolerance for zero pivot 2.22045e-14</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> matrix ordering: natural</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> factor fill ratio given 1., needed 1.</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> Factored matrix follows:</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> Mat Object: 1 MPI processes</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> type: seqaij</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> rows=28476, cols=28476</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> package used to perform factorization: petsc</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> total: nonzeros=1017054, allocated nonzeros=1017054</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> total number of mallocs used during MatSetValues calls =0</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> using I-node routines: found 9492 nodes, limit used is 5</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> linear system matrix = precond matrix:</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> Mat Object: (fieldsplit_FE_split_) 1 MPI processes</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> type: seqaij</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> rows=28476, cols=28476</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> total: nonzeros=1017054, allocated nonzeros=1017054</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> total number of mallocs used during MatSetValues calls =0</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> using I-node routines: found 9492 nodes, limit used is 5</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> linear system matrix followed by preconditioner matrix:</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> Mat Object: (fieldsplit_FE_split_) 1 MPI processes</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> type: schurcomplement</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> rows=28476, cols=28476</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> Schur complement A11 - A10 inv(A00) A01</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> A11</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> Mat Object: (fieldsplit_FE_split_) 1 MPI processes</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> type: seqaij</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> rows=28476, cols=28476</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> total: nonzeros=1017054, allocated nonzeros=1017054</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> total number of mallocs used during MatSetValues calls =0</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> using I-node routines: found 9492 nodes, limit used is 5</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> A10</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> Mat Object: 1 MPI processes</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> type: seqaij</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> rows=28476, cols=324</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> total: nonzeros=936, allocated nonzeros=936</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> total number of mallocs used during MatSetValues calls =0</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> using I-node routines: found 5717 nodes, limit used is 5</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> KSP of A00</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> KSP Object: (fieldsplit_RB_split_) 1 MPI processes</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> type: preonly</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> maximum iterations=10000, initial guess is zero</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> tolerances: relative=1e-05, absolute=1e-50, divergence=10000.</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> left preconditioning</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> using NONE norm type for convergence test</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> PC Object: (fieldsplit_RB_split_) 1 MPI processes</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> type: cholesky</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> Cholesky: out-of-place factorization</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> tolerance for zero pivot 2.22045e-14</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> matrix ordering: natural</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> factor fill ratio given 0., needed 0.</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> Factored matrix follows:</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> Mat Object: 1 MPI processes</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> type: seqaij</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> rows=324, cols=324</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> package used to perform factorization: mumps</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> total: nonzeros=3042, allocated nonzeros=3042</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> total number of mallocs used during MatSetValues calls =0</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> MUMPS run parameters:</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> SYM (matrix type): 2 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> PAR (host participation): 1 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(1) (output for error): 6 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(2) (output of diagnostic msg): 0 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(3) (output for global info): 0 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(4) (level of printing): 0 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(5) (input mat struct): 0 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(6) (matrix prescaling): 7 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(7) (sequentia matrix ordering):7 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(8) (scalling strategy): 77 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(10) (max num of refinements): 0 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(11) (error analysis): 0 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(12) (efficiency control): 0 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(13) (efficiency control): 0 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(14) (percentage of estimated workspace increase): 20 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(18) (input mat struct): 0 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(19) (Shur complement info): 0 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(20) (rhs sparse pattern): 0 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(21) (solution struct): 0 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(22) (in-core/out-of-core facility): 0 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(23) (max size of memory can be allocated locally):0 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(24) (detection of null pivot rows): 0 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(25) (computation of a null space basis): 0 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(26) (Schur options for rhs or solution): 0 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(27) (experimental parameter): -24 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(28) (use parallel or sequential ordering): 1 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(29) (parallel ordering): 0 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(30) (user-specified set of entries in inv(A)): 0 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(31) (factors is discarded in the solve phase): 0 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> ICNTL(33) (compute determinant): 0 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> CNTL(1) (relative pivoting threshold): 0.01 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> CNTL(2) (stopping criterion of refinement): 1.49012e-08 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> CNTL(3) (absolute pivoting threshold): 0. </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> CNTL(4) (value of static pivoting): -1. </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> CNTL(5) (fixation for null pivots): 0. </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> RINFO(1) (local estimated flops for the elimination after analysis): </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> [0] 29394. </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> RINFO(2) (local estimated flops for the assembly after factorization): </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> [0] 1092. </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> RINFO(3) (local estimated flops for the elimination after factorization): </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> [0] 29394. </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFO(15) (estimated size of (in MB) MUMPS internal data for running numerical factorization): </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> [0] 1 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFO(16) (size of (in MB) MUMPS internal data used during numerical factorization): </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> [0] 1 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFO(23) (num of pivots eliminated on this processor after factorization): </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> [0] 324 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> RINFOG(1) (global estimated flops for the elimination after analysis): 29394. </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> RINFOG(2) (global estimated flops for the assembly after factorization): 1092. </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> RINFOG(3) (global estimated flops for the elimination after factorization): 29394. </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> (RINFOG(12) RINFOG(13))*2^INFOG(34) (determinant): (0.,0.)*(2^0)</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(3) (estimated real workspace for factors on all processors after analysis): 3888 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(4) (estimated integer workspace for factors on all processors after analysis): 2067 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(5) (estimated maximum front size in the complete tree): 12 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(6) (number of nodes in the complete tree): 53 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(7) (ordering option effectively use after analysis): 2 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(8) (structural symmetry in percent of the permuted matrix after analysis): 100 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(9) (total real/complex workspace to store the matrix factors after factorization): 3888 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(10) (total integer space store the matrix factors after factorization): 2067 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(11) (order of largest frontal matrix after factorization): 12 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(12) (number of off-diagonal pivots): 0 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(13) (number of delayed pivots after factorization): 0 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(14) (number of memory compress after factorization): 0 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(15) (number of steps of iterative refinement after solution): 0 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(16) (estimated size (in MB) of all MUMPS internal data for factorization after analysis: value on the most memory consuming processor): 1 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(17) (estimated size of all MUMPS internal data for factorization after analysis: sum over all processors): 1 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(18) (size of all MUMPS internal data allocated during factorization: value on the most memory consuming processor): 1 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(19) (size of all MUMPS internal data allocated during factorization: sum over all processors): 1 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(20) (estimated number of entries in the factors): 3042 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(21) (size in MB of memory effectively used during factorization - value on the most memory consuming processor): 1 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(22) (size in MB of memory effectively used during factorization - sum over all processors): 1 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(23) (after analysis: value of ICNTL(6) effectively used): 5 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(24) (after analysis: value of ICNTL(12) effectively used): 1 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(25) (after factorization: number of pivots modified by static pivoting): 0 </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(28) (after factorization: number of null pivots encountered): 0</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(29) (after factorization: effective number of entries in the factors (sum over all processors)): 3042</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(30, 31) (after solution: size in Mbytes of memory used during solution phase): 0, 0</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(32) (after analysis: type of analysis done): 1</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(33) (value used for ICNTL(8)): -2</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> INFOG(34) (exponent of the determinant if determinant is requested): 0</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> linear system matrix = precond matrix:</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> Mat Object: (fieldsplit_RB_split_) 1 MPI processes</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> type: seqaij</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> rows=324, cols=324</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> total: nonzeros=5760, allocated nonzeros=5760</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> total number of mallocs used during MatSetValues calls =0</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> using I-node routines: found 108 nodes, limit used is 5</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> A01</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> Mat Object: 1 MPI processes</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> type: seqaij</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> rows=324, cols=28476</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> total: nonzeros=936, allocated nonzeros=936</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> total number of mallocs used during MatSetValues calls =0</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> using I-node routines: found 67 nodes, limit used is 5</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> Mat Object: (fieldsplit_FE_split_) 1 MPI processes</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> type: seqaij</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> rows=28476, cols=28476</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> total: nonzeros=1017054, allocated nonzeros=1017054</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> total number of mallocs used during MatSetValues calls =0</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> using I-node routines: found 9492 nodes, limit used is 5</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> linear system matrix = precond matrix:</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> Mat Object: () 1 MPI processes</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> type: seqaij</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> rows=28800, cols=28800</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> total: nonzeros=1024686, allocated nonzeros=1024794</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> total number of mallocs used during MatSetValues calls =0</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> using I-node routines: found 9600 nodes, limit used is 5</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"><br class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"></div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"><br class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"></div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">------------------------------<wbr>---------------- PETSc Performance Summary: ------------------------------<wbr>----------------</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"><br class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"></div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">/home/dknez/akselos-dev/scrbe/<wbr>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</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">Using Petsc Release Version 3.7.3, unknown </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"><br class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"></div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> Max Max/Min Avg Total </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">Time (sec): 9.179e+01 1.00000 9.179e+01</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">Objects: 1.990e+02 1.00000 1.990e+02</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">Flops: 1.634e+11 1.00000 1.634e+11 1.634e+11</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">Flops/sec: 1.780e+09 1.00000 1.780e+09 1.780e+09</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">MPI Messages: 0.000e+00 0.00000 0.000e+00 0.000e+00</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">MPI Message Lengths: 0.000e+00 0.00000 0.000e+00 0.000e+00</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">MPI Reductions: 0.000e+00 0.00000</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"><br class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"></div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">Flop counting convention: 1 flop = 1 real number operation of type (multiply/divide/add/subtract)</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> e.g., VecAXPY() for real vectors of length N --> 2N flops</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> and VecAXPY() for complex vectors of length N --> 8N flops</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"><br class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"></div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">Summary of Stages: ----- Time ------ ----- Flops ----- --- Messages --- -- Message Lengths -- -- Reductions --</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> Avg %Total Avg %Total counts %Total Avg %Total counts %Total </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> 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% </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"><br class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"></div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">------------------------------<wbr>------------------------------<wbr>------------------------------<wbr>------------------------------</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">See the 'Profiling' chapter of the users' manual for details on interpreting output.</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">Phase summary info:</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> Count: number of times phase was executed</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> Time and Flops: Max - maximum over all processors</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> Ratio - ratio of maximum to minimum over all processors</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> Mess: number of messages sent</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> Avg. len: average message length (bytes)</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> Reduct: number of global reductions</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> Global: entire computation</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> Stage: stages of a computation. Set stages with PetscLogStagePush() and PetscLogStagePop().</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> %T - percent time in this phase %F - percent flops in this phase</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> %M - percent messages in this phase %L - percent message lengths in this phase</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> %R - percent reductions in this phase</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> Total Mflop/s: 10e-6 * (sum of flops over all processors)/(max time over all processors)</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">------------------------------<wbr>------------------------------<wbr>------------------------------<wbr>------------------------------</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">Event Count Time (sec) Flops --- Global --- --- Stage --- Total</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> Max Ratio Max Ratio Max Ratio Mess Avg len Reduct %T %F %M %L %R %T %F %M %L %R Mflop/s</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">------------------------------<wbr>------------------------------<wbr>------------------------------<wbr>------------------------------</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"><br class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"></div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">--- Event Stage 0: Main Stage</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"><br class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"></div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">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</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">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</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">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</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">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</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">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</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">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</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">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</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">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</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">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</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">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</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">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</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">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</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">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</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">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</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">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</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">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</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">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</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">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</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">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</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">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</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">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</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">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</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">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</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">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</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">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</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">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</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">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</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">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</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">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</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">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</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">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</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">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</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">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</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">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</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">------------------------------<wbr>------------------------------<wbr>------------------------------<wbr>------------------------------</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"><br class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"></div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">Memory usage is given in bytes:</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"><br class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"></div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">Object Type Creations Destructions Memory Descendants' Mem.</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">Reports information only for process 0.</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"><br class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"></div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">--- Event Stage 0: Main Stage</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"><br class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"></div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> Vector 91 91 9693912 0.</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> Vector Scatter 24 24 15936 0.</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> Index Set 51 51 537888 0.</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> IS L to G Mapping 3 3 240408 0.</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> Matrix 13 13 64097868 0.</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> Krylov Solver 6 6 7888 0.</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> Preconditioner 6 6 6288 0.</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> Viewer 1 0 0 0.</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> Distributed Mesh 1 1 4624 0.</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">Star Forest Bipartite Graph 2 2 1616 0.</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"> Discrete System 1 1 872 0.</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">==============================<wbr>==============================<wbr>==============================<wbr>==============================</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">Average time to get PetscTime(): 0.</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">#PETSc Option Table entries:</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">-ksp_monitor</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">-ksp_view</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">-log_view</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">#End of PETSc Option Table entries</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">Compiled without FORTRAN kernels</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">Compiled with full precision matrices (default)</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">sizeof(short) 2 sizeof(int) 4 sizeof(long) 8 sizeof(void*) 8 sizeof(PetscScalar) 8 sizeof(PetscInt) 4</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">Configure options: --with-shared-libraries=1 --with-debugging=0 --download-suitesparse --download-blacs --download-ptscotch=yes --with-blas-lapack-dir=/opt/in<wbr>tel/system_studio_2015.2.050/<wbr>mkl --CXXFLAGS=-Wl,--no-as-needed --download-scalapack --download-mumps --download-metis --prefix=/home/dknez/software/<wbr>libmesh_install/opt_real/petsc --download-hypre --download-ml</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">------------------------------<wbr>-----------</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">Libraries compiled on Wed Sep 21 17:38:52 2016 on david-Lenovo </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">Machine characteristics: Linux-4.4.0-38-generic-x86_64-<wbr>with-Ubuntu-16.04-xenial</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">Using PETSc directory: /home/dknez/software/petsc-src</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">Using PETSc arch: arch-linux2-c-opt</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">------------------------------<wbr>-----------</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"><br class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"></div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">Using C compiler: mpicc -fPIC -Wall -Wwrite-strings -Wno-strict-aliasing -Wno-unknown-pragmas -fvisibility=hidden -g -O ${COPTFLAGS} ${CFLAGS}</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">Using Fortran compiler: mpif90 -fPIC -Wall -ffree-line-length-0 -Wno-unused-dummy-argument -g -O ${FOPTFLAGS} ${FFLAGS} </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">------------------------------<wbr>-----------</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"><br class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"></div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">Using include paths: -I/home/dknez/software/petsc-s<wbr>rc/arch-linux2-c-opt/include -I/home/dknez/software/petsc-s<wbr>rc/include -I/home/dknez/software/petsc-s<wbr>rc/include -I/home/dknez/software/petsc-s<wbr>rc/arch-linux2-c-opt/include -I/home/dknez/software/libmesh<wbr>_install/opt_real/petsc/<wbr>include -I/usr/lib/openmpi/include/ope<wbr>nmpi/opal/mca/event/libevent20<wbr>21/libevent -I/usr/lib/openmpi/include/ope<wbr>nmpi/opal/mca/event/libevent20<wbr>21/libevent/include -I/usr/lib/openmpi/include -I/usr/lib/openmpi/include/ope<wbr>nmpi</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">------------------------------<wbr>-----------</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"><br class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"></div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">Using C linker: mpicc</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">Using Fortran linker: mpif90</div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">Using libraries: -Wl,-rpath,/home/dknez/softwar<wbr>e/petsc-src/arch-linux2-c-opt/<wbr>lib -L/home/dknez/software/petsc-s<wbr>rc/arch-linux2-c-opt/lib -lpetsc -Wl,-rpath,/home/dknez/softwar<wbr>e/libmesh_install/opt_real/<wbr>petsc/lib -L/home/dknez/software/libmesh<wbr>_install/opt_real/petsc/lib -lcmumps -ldmumps -lsmumps -lzmumps -lmumps_common -lpord -lmetis -lHYPRE -Wl,-rpath,/usr/lib/openmpi/li<wbr>b -L/usr/lib/openmpi/lib -Wl,-rpath,/usr/lib/gcc/x86_64<wbr>-linux-gnu/5 -L/usr/lib/gcc/x86_64-linux-gn<wbr>u/5 -Wl,-rpath,/usr/lib/x86_64-lin<wbr>ux-gnu -L/usr/lib/x86_64-linux-gnu -Wl,-rpath,/lib/x86_64-linux-g<wbr>nu -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_s<wbr>tudio_2015.2.050/mkl/lib/intel<wbr>64 -L/opt/intel/system_studio_201<wbr>5.2.050/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/li<wbr>b -L/usr/lib/openmpi/lib -Wl,-rpath,/usr/lib/gcc/x86_64<wbr>-linux-gnu/5 -L/usr/lib/gcc/x86_64-linux-gn<wbr>u/5 -Wl,-rpath,/usr/lib/x86_64-lin<wbr>ux-gnu -L/usr/lib/x86_64-linux-gnu -Wl,-rpath,/lib/x86_64-linux-g<wbr>nu -L/lib/x86_64-linux-gnu -Wl,-rpath,/usr/lib/x86_64-lin<wbr>ux-gnu -L/usr/lib/x86_64-linux-gnu -ldl -Wl,-rpath,/usr/lib/openmpi/li<wbr>b -lmpi -lgcc_s -lpthread -ldl </div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg">------------------------------<wbr>-----------</div></div><div class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"><br class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"></div><br class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"><br class="m_6920403594308095878gmail-m_-7298681589884001740gmail_msg"></div><br 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