<html><head><meta http-equiv="Content-Type" content="text/html charset=us-ascii"></head><body style="word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space; ">Hi,<div><br></div><div><br><div><div>On Aug 14, 2012, at 5:58 PM, Barry Smith <<a href="mailto:bsmith@mcs.anl.gov">bsmith@mcs.anl.gov</a>> wrote:</div><br class="Apple-interchange-newline"><blockquote type="cite"><br> Blaise,<br><br> You can run with -snes_linesearch_monitor -info -ksp_monitor_true_residual -ksp_converged_reason<br><br><br>to get much more information about what is happening and why the line search is failing.<br></blockquote><div>Focussing on the relevant part of the output, I get the following for the first SNES step</div><div><br></div><div>*** Using l2</div><div><div> Residual norms for temp_ solve.</div><div> 0 KSP preconditioned resid norm 2.352873068990e+00 true resid norm 3.742138023215e+00 ||r(i)||/||b|| 1.000000000000e+00</div><div>[0] KSPDefaultConverged(): user has provided nonzero initial guess, computing 2-norm of preconditioned RHS</div><div> 1 KSP preconditioned resid norm 7.175926524783e-01 true resid norm 8.026926174904e-01 ||r(i)||/||b|| 2.145010719836e-01</div><div> 2 KSP preconditioned resid norm 4.099791012407e-01 true resid norm 6.219898727406e-01 ||r(i)||/||b|| 1.662124349455e-01</div><div> 3 KSP preconditioned resid norm 2.769612150659e-01 true resid norm 4.622335508644e-01 ||r(i)||/||b|| 1.235212458752e-01</div><div> 4 KSP preconditioned resid norm 8.991164116822e-02 true resid norm 1.938840972976e-01 ||r(i)||/||b|| 5.181104921701e-02</div><div> 5 KSP preconditioned resid norm 1.369794733551e-02 true resid norm 2.867541652138e-02 ||r(i)||/||b|| 7.662843097578e-03</div><div> 6 KSP preconditioned resid norm 3.522245138600e-03 true resid norm 5.452585588775e-03 ||r(i)||/||b|| 1.457077626466e-03</div><div> 7 KSP preconditioned resid norm 1.117008651636e-03 true resid norm 1.551905826961e-03 ||r(i)||/||b|| 4.147110067382e-04</div><div> 8 KSP preconditioned resid norm 5.008635361807e-04 true resid norm 6.226120116381e-04 ||r(i)||/||b|| 1.663786872038e-04</div><div> 9 KSP preconditioned resid norm 2.079118910844e-04 true resid norm 3.430664466007e-04 ||r(i)||/||b|| 9.167658821571e-05</div><div> 10 KSP preconditioned resid norm 4.528126074206e-05 true resid norm 9.520866575330e-05 ||r(i)||/||b|| 2.544231804457e-05</div><div> 11 KSP preconditioned resid norm 8.441137224072e-06 true resid norm 1.519916221879e-05 ||r(i)||/||b|| 4.061625232553e-06</div><div> 12 KSP preconditioned resid norm 1.839317974157e-06 true resid norm 3.245208227421e-06 ||r(i)||/||b|| 8.672069836252e-07</div><div> 13 KSP preconditioned resid norm 4.346353491153e-07 true resid norm 7.198101954057e-07 ||r(i)||/||b|| 1.923526580100e-07</div><div> 14 KSP preconditioned resid norm 6.321413805477e-08 true resid norm 1.280486229700e-07 ||r(i)||/||b|| 3.421803850515e-08</div><div> 15 KSP preconditioned resid norm 9.029476674935e-09 true resid norm 2.193598397200e-08 ||r(i)||/||b|| 5.861885327562e-09</div><div>[0] KSPDefaultConverged(): Linear solver has converged. Residual norm 9.029476674935e-09 is less than relative tolerance 1.000000000000e-08 times initial right hand side norm 2.352873068990e+00 at iteration 15</div><div> Linear solve converged due to CONVERGED_RTOL iterations 15</div><div>[0] SNESSolve_LS(): iter=0, linear solve iterations=15</div><div><b>[0] SNESLSCheckResidual_Private(): ||J^T(F-Ax)||/||F-AX|| 4.179425981164e+00 near zero implies inconsistent rhs</b></div><div> Line search: lambdas = [1, 0.5, 0], fnorms = [2.1936e-08, 1.87107, 3.74214]</div><div> Line search terminated: lambda = 1, fnorms = 2.19338e-08</div><div><b>[0] SNESSolve_LS(): fnorm=3.7421380232151638e+00, gnorm=2.1933796240714327e-08, ynorm=5.1838420564550498e+00, lssucceed=1</b></div><div> 1 SNES Function norm 2.193379624071e-08 </div><div>[0] SNESDefaultConverged(): Converged due to function norm 2.193379624071e-08 < 3.742138023215e-08 (relative tolerance)</div><div>SNESTemp converged in in 1 iterations. SNESConvergedReason is 3 </div><div><br></div><div>*** Using bt</div><div><div><div> Residual norms for temp_ solve.</div><div> 0 KSP preconditioned resid norm 1.176436534193e+00 true resid norm 3.742138022596e+00 ||r(i)||/||b|| 9.999999998344e-01</div><div>[0] KSPDefaultConverged(): user has provided nonzero initial guess, computing 2-norm of preconditioned RHS</div><div> 1 KSP preconditioned resid norm 3.587963259712e-01 true resid norm 8.026926179905e-01 ||r(i)||/||b|| 2.145010721173e-01</div><div> 2 KSP preconditioned resid norm 2.049895509618e-01 true resid norm 6.219898720314e-01 ||r(i)||/||b|| 1.662124347560e-01</div><div> 3 KSP preconditioned resid norm 1.384806072424e-01 true resid norm 4.622335514699e-01 ||r(i)||/||b|| 1.235212460370e-01</div><div> 4 KSP preconditioned resid norm 4.495582078268e-02 true resid norm 1.938840967382e-01 ||r(i)||/||b|| 5.181104906751e-02</div><div> 5 KSP preconditioned resid norm 6.848973644691e-03 true resid norm 2.867541656135e-02 ||r(i)||/||b|| 7.662843108259e-03</div><div> 6 KSP preconditioned resid norm 1.761122593261e-03 true resid norm 5.452585577786e-03 ||r(i)||/||b|| 1.457077623530e-03</div><div> 7 KSP preconditioned resid norm 5.585043310756e-04 true resid norm 1.551905808041e-03 ||r(i)||/||b|| 4.147110016822e-04</div><div> 8 KSP preconditioned resid norm 2.504317746421e-04 true resid norm 6.226120013063e-04 ||r(i)||/||b|| 1.663786844429e-04</div><div> 9 KSP preconditioned resid norm 1.039559493091e-04 true resid norm 3.430664433173e-04 ||r(i)||/||b|| 9.167658733830e-05</div><div> 10 KSP preconditioned resid norm 2.264063167431e-05 true resid norm 9.520867156897e-05 ||r(i)||/||b|| 2.544231959867e-05</div><div> 11 KSP preconditioned resid norm 4.220568874641e-06 true resid norm 1.519916304124e-05 ||r(i)||/||b|| 4.061625452335e-06</div><div> 12 KSP preconditioned resid norm 9.196589910150e-07 true resid norm 3.245208482213e-06 ||r(i)||/||b|| 8.672070517123e-07</div><div> 13 KSP preconditioned resid norm 2.173176852660e-07 true resid norm 7.198102176806e-07 ||r(i)||/||b|| 1.923526639624e-07</div><div> 14 KSP preconditioned resid norm 3.160707194729e-08 true resid norm 1.280486368595e-07 ||r(i)||/||b|| 3.421804221680e-08</div><div> 15 KSP preconditioned resid norm 4.514738683754e-09 true resid norm 2.193598711826e-08 ||r(i)||/||b|| 5.861886168328e-09</div><div>[0] KSPDefaultConverged(): Linear solver has converged. Residual norm 4.514738683754e-09 is less than relative tolerance 1.000000000000e-08 times initial right hand side norm 1.176436534495e+00 at iteration 15</div><div> Linear solve converged due to CONVERGED_RTOL iterations 15</div><div>[0] SNESSolve_LS(): iter=0, linear solve iterations=15</div><div><b>[0] SNESLSCheckResidual_Private(): ||J^T(F-Ax)||/||F-AX|| 8.358851664967e+00 near zero implies inconsistent rhs</b></div><div>[0] VecScatterCreate(): Special case: sequential vector general scatter</div><div>[0] SNESLineSearchApply_BT(): Initial fnorm 3.742138023215e+00 gnorm 1.871069011453e+00</div><div><b> Line search: Using full step: fnorm 3.742138023215e+00 gnorm 1.871069011453e+00</b></div><div>[0] SNESSolve_LS(): fnorm=3.7421380232151638e+00, gnorm=1.8710690114527022e+00, ynorm=2.5919210284812890e+00, lssucceed=1</div><div> 1 SNES Function norm 1.871069011453e+00 </div><div><br></div></div><div><br></div><div>As expected, the KSP residuals are exactly the same. I am not sure what to make of</div><div>[0] SNESLSCheckResidual_Private(): ||J^T(F-Ax)||/||F-AX|| 8.358851664967e+00 near zero implies inconsistent rhs. </div><div>Which RHS is this referring to? the RHS for SNESSolve is 0 (second argument of SNESSolve is PETSC_NULL_OBJECT). Could this mean that there is an incompatibility between my Jacobian and my Function?</div><div><br></div><div>In all case that diverge, it looks like the gnorm in the linesearch does not decrease.</div></div></div><br><blockquote type="cite"><br> If that doesn't help you can send the code and we can play with it.<br></blockquote><div><br></div><div>The code is a bit of a pain to build but both Matt and Jed have accounts on my systems. I can arrange to give access to others if necessary.</div><div><br></div><div>Blaise</div><div><br></div><br><blockquote type="cite"><br> Barry<br><br><br><br>On Aug 14, 2012, at 5:53 PM, Blaise Bourdin <<a href="mailto:bourdin@lsu.edu">bourdin@lsu.edu</a>> wrote:<br><br><blockquote type="cite">HI,<br><br>I am trying to understand if the following behavior is normal / expected:<br><br>I am solving a quasi-static evolution where at each time step, SNESSolve is called. My validation problem is a _static_ problem with 2 time steps (i.e. 2 successive calls to SNESSolve with the same operator, jacobian, and right hand side). Furthermore, the problem is linear, so that the Jacobian is constant. I even reset the solution vector to the same value at each time step.<br><br>In this setting, I am expecting that at each time step, each SNESSolve should converge in exactly one iteration no matter what linesearch / snes type I use. Indeed, when setting the linesearch to l2 or cp, this is what I get. However, for all other choices, the second call to SNESSolve fails to converge with a SNESConvergedReason of -5 or -6.<br><br>The relevant code is as follow:<br> Call VecSet(solTemp,0.0_Kr,ierr);CHKERRQ(ierr)<br> Call FormInitialGuess(snesTemp,solTemp,MEF90Ctx,ierr);CHKERRQ(ierr)<br> Call VecCopy(solTemp,tmpvec,ierr)<br><br> Call SNESSolve(snesTemp,PETSC_NULL_OBJECT,solTemp,ierr);CHKERRQ(ierr)<br><br> Call VecCopy(tmpvec,soltemp,ierr)<br> Call SNESSolve(snesTemp,PETSC_NULL_OBJECT,solTemp,ierr);CHKERRQ(ierr)<br><br><br>Is this expected? I tried to call SNESLineSearchReset before the second call to SNESSolve, but this does not seem to have any effect.<br><br>Blaise<br><br><br><br>Below is the sample output using cp as the linesearch type in which case I get the expected convergence:<br>Solving time step 1: t= 1.00000E+00 <br> 0 SNES Function norm 3.742138023215e+00 <br> Line search terminated: lambda = 1, fnorms = 2.1936e-08<br> 1 SNES Function norm 2.193598339906e-08 <br>SNES Object:(temp_) 1 MPI processes<br> type: ls<br> maximum iterations=50, maximum function evaluations=10000<br> tolerances: relative=1e-08, absolute=1e-50, solution=1e-08<br> total number of linear solver iterations=15<br> total number of function evaluations=3<br> KSP Object: (temp_) 1 MPI processes<br> type: cg<br> maximum iterations=10000<br> tolerances: relative=1e-08, absolute=1e-50, divergence=10000<br> left preconditioning<br> using nonzero initial guess<br> using PRECONDITIONED norm type for convergence test<br> PC Object: (temp_) 1 MPI processes<br> type: icc<br> 0 levels of fill<br> tolerance for zero pivot 2.22045e-14<br> using Manteuffel shift<br> matrix ordering: natural<br> factor fill ratio given 1, needed 1<br> Factored matrix follows:<br> Matrix Object: 1 MPI processes<br> type: seqsbaij<br> rows=104, cols=104<br> package used to perform factorization: petsc<br> total: nonzeros=381, allocated nonzeros=381<br> total number of mallocs used during MatSetValues calls =0<br> block size is 1<br> linear system matrix = precond matrix:<br> Matrix Object: 1 MPI processes<br> type: seqaij<br> rows=104, cols=104<br> total: nonzeros=658, allocated nonzeros=658<br> total number of mallocs used during MatSetValues calls =0<br> not using I-node routines<br> SNESLineSearch Object: (temp_) 1 MPI processes<br> type: cp<br> maxstep=1.000000e+08, minlambda=1.000000e-12<br> tolerances: relative=1.000000e-08, absolute=1.000000e-15, lambda=1.000000e-08<br> maximum iterations=1<br>SNESTemp converged in in 1 iterations. SNESConvergedReason is 3 <br> 0 SNES Function norm 3.742138023215e+00 <br> Line search: lambdas = [1, 0], ftys = [2.42597, 4.85193]<br> Line search terminated: lambda = 2, fnorms = 2.1936e-08<br> 1 SNES Function norm 2.193598717772e-08 <br>SNES Object:(temp_) 1 MPI processes<br> type: ls<br> maximum iterations=50, maximum function evaluations=10000<br> tolerances: relative=1e-08, absolute=1e-50, solution=1e-08<br> total number of linear solver iterations=15<br> total number of function evaluations=3<br> KSP Object: (temp_) 1 MPI processes<br> type: cg<br> maximum iterations=10000<br> tolerances: relative=1e-08, absolute=1e-50, divergence=10000<br> left preconditioning<br> using nonzero initial guess<br> using PRECONDITIONED norm type for convergence test<br> PC Object: (temp_) 1 MPI processes<br> type: icc<br> 0 levels of fill<br> tolerance for zero pivot 2.22045e-14<br> using Manteuffel shift<br> matrix ordering: natural<br> factor fill ratio given 1, needed 1<br> Factored matrix follows:<br> Matrix Object: 1 MPI processes<br> type: seqsbaij<br> rows=104, cols=104<br> package used to perform factorization: petsc<br> total: nonzeros=381, allocated nonzeros=381<br> total number of mallocs used during MatSetValues calls =0<br> block size is 1<br> linear system matrix = precond matrix:<br> Matrix Object: 1 MPI processes<br> type: seqaij<br> rows=104, cols=104<br> total: nonzeros=658, allocated nonzeros=658<br> total number of mallocs used during MatSetValues calls =0<br> not using I-node routines<br> SNESLineSearch Object: (temp_) 1 MPI processes<br> type: cp<br> maxstep=1.000000e+08, minlambda=1.000000e-12<br> tolerances: relative=1.000000e-08, absolute=1.000000e-15, lambda=1.000000e-08<br> maximum iterations=1<br>SNESTemp converged in in 1 iterations. SNESConvergedReason is 3 <br><br><br>when using the default linesearch (bt), the second SNESSolve fails:<br><br>Solving time step 1: t= 1.00000E+00 <br> 0 SNES Function norm 3.742138023215e+00 <br> Line search: Using full step: fnorm 3.742138023215e+00 gnorm 2.193598339906e-08<br> 1 SNES Function norm 2.193598339906e-08 <br>SNES Object:(temp_) 1 MPI processes<br> type: ls<br> maximum iterations=50, maximum function evaluations=10000<br> tolerances: relative=1e-08, absolute=1e-50, solution=1e-08<br> total number of linear solver iterations=15<br> total number of function evaluations=2<br> KSP Object: (temp_) 1 MPI processes<br> type: cg<br> maximum iterations=10000<br> tolerances: relative=1e-08, absolute=1e-50, divergence=10000<br> left preconditioning<br> using nonzero initial guess<br> using PRECONDITIONED norm type for convergence test<br> PC Object: (temp_) 1 MPI processes<br> type: icc<br> 0 levels of fill<br> tolerance for zero pivot 2.22045e-14<br> using Manteuffel shift<br> matrix ordering: natural<br> factor fill ratio given 1, needed 1<br> Factored matrix follows:<br> Matrix Object: 1 MPI processes<br> type: seqsbaij<br> rows=104, cols=104<br> package used to perform factorization: petsc<br> total: nonzeros=381, allocated nonzeros=381<br> total number of mallocs used during MatSetValues calls =0<br> block size is 1<br> linear system matrix = precond matrix:<br> Matrix Object: 1 MPI processes<br> type: seqaij<br> rows=104, cols=104<br> total: nonzeros=658, allocated nonzeros=658<br> total number of mallocs used during MatSetValues calls =0<br> not using I-node routines<br> SNESLineSearch Object: (temp_) 1 MPI processes<br> type: bt<br> interpolation: cubic<br> alpha=1.000000e-04<br> maxstep=1.000000e+08, minlambda=1.000000e-12<br> tolerances: relative=1.000000e-08, absolute=1.000000e-15, lambda=1.000000e-08<br> maximum iterations=40<br>SNESTemp converged in in 1 iterations. SNESConvergedReason is 3 <br> 0 SNES Function norm 3.742138023215e+00 <br> Line search: Using full step: fnorm 3.742138023215e+00 gnorm 1.871069011453e+00<br> 1 SNES Function norm 1.871069011453e+00 <br> Line search: Using full step: fnorm 1.871069011453e+00 gnorm 1.247379340865e+00<br> 2 SNES Function norm 1.247379340865e+00 <br> Line search: Using full step: fnorm 1.247379340865e+00 gnorm 9.355345056231e-01<br> 3 SNES Function norm 9.355345056231e-01 <br> Line search: Using full step: fnorm 9.355345056231e-01 gnorm 7.484276044882e-01<br> 4 SNES Function norm 7.484276044882e-01 <br> Line search: Using full step: fnorm 7.484276044882e-01 gnorm 6.236896704016e-01<br> 5 SNES Function norm 6.236896704016e-01 <br> Line search: Using full step: fnorm 6.236896704016e-01 gnorm 5.345911460556e-01<br> 6 SNES Function norm 5.345911460556e-01 <br> Line search: Using full step: fnorm 5.345911460556e-01 gnorm 4.677672528597e-01<br> 7 SNES Function norm 4.677672528597e-01 <br> Line search: Using full step: fnorm 4.677672528597e-01 gnorm 4.157931136937e-01<br> 8 SNES Function norm 4.157931136937e-01 <br> Line search: Using full step: fnorm 4.157931136937e-01 gnorm 3.742138023528e-01<br> 9 SNES Function norm 3.742138023528e-01 <br> Line search: Using full step: fnorm 3.742138023528e-01 gnorm 3.401943657960e-01<br>10 SNES Function norm 3.401943657960e-01 <br> Line search: Using full step: fnorm 3.401943657960e-01 gnorm 3.118448353285e-01<br>11 SNES Function norm 3.118448353285e-01 <br> Line search: Using full step: fnorm 3.118448353285e-01 gnorm 2.878567710844e-01<br>12 SNES Function norm 2.878567710844e-01 <br> Line search: Using full step: fnorm 2.878567710844e-01 gnorm 2.672955731592e-01<br>13 SNES Function norm 2.672955731592e-01 <br> Line search: Using full step: fnorm 2.672955731592e-01 gnorm 2.494758682895e-01<br>14 SNES Function norm 2.494758682895e-01 <br> Line search: Using full step: fnorm 2.494758682895e-01 gnorm 2.338836265275e-01<br>15 SNES Function norm 2.338836265275e-01 <br> Line search: Using full step: fnorm 2.338836265275e-01 gnorm 2.201257661485e-01<br>16 SNES Function norm 2.201257661485e-01 <br> Line search: Using full step: fnorm 2.201257661485e-01 gnorm 2.078965569222e-01<br>17 SNES Function norm 2.078965569222e-01 <br> Line search: Using full step: fnorm 2.078965569222e-01 gnorm 1.969546328772e-01<br>18 SNES Function norm 1.969546328772e-01 <br> Line search: Using full step: fnorm 1.969546328772e-01 gnorm 1.871069012364e-01<br>19 SNES Function norm 1.871069012364e-01 <br> Line search: Using full step: fnorm 1.871069012364e-01 gnorm 1.781970487991e-01<br>20 SNES Function norm 1.781970487991e-01 <br> Line search: Using full step: fnorm 1.781970487991e-01 gnorm 1.700971829468e-01<br>21 SNES Function norm 1.700971829468e-01 <br> Line search: Using full step: fnorm 1.700971829468e-01 gnorm 1.627016532554e-01<br>22 SNES Function norm 1.627016532554e-01 <br> Line search: Using full step: fnorm 1.627016532554e-01 gnorm 1.559224177048e-01<br>23 SNES Function norm 1.559224177048e-01 <br> Line search: Using full step: fnorm 1.559224177048e-01 gnorm 1.496855209981e-01<br>24 SNES Function norm 1.496855209981e-01 <br> Line search: Using full step: fnorm 1.496855209981e-01 gnorm 1.439283855764e-01<br>25 SNES Function norm 1.439283855764e-01 <br> Line search: Using full step: fnorm 1.439283855764e-01 gnorm 1.385977046303e-01<br>26 SNES Function norm 1.385977046303e-01 <br> Line search: Using full step: fnorm 1.385977046303e-01 gnorm 1.336477866088e-01<br>27 SNES Function norm 1.336477866088e-01 <br> Line search: Using full step: fnorm 1.336477866088e-01 gnorm 1.290392422439e-01<br>28 SNES Function norm 1.290392422439e-01 <br> Line search: Using full step: fnorm 1.290392422439e-01 gnorm 1.247379341700e-01<br>29 SNES Function norm 1.247379341700e-01 <br> Line search: Using full step: fnorm 1.247379341700e-01 gnorm 1.207141298427e-01<br>30 SNES Function norm 1.207141298427e-01 <br> Line search: Using full step: fnorm 1.207141298427e-01 gnorm 1.169418132858e-01<br>31 SNES Function norm 1.169418132858e-01 <br> Line search: Using full step: fnorm 1.169418132858e-01 gnorm 1.133981219747e-01<br>32 SNES Function norm 1.133981219747e-01 <br> Line search: Using full step: fnorm 1.133981219747e-01 gnorm 1.100628830937e-01<br>33 SNES Function norm 1.100628830937e-01 <br> Line search: Using full step: fnorm 1.100628830937e-01 gnorm 1.069182292915e-01<br>34 SNES Function norm 1.069182292915e-01 <br> Line search: Using full step: fnorm 1.069182292915e-01 gnorm 1.039482784783e-01<br>35 SNES Function norm 1.039482784783e-01 <br> Line search: Using full step: fnorm 1.039482784783e-01 gnorm 1.011388655469e-01<br>36 SNES Function norm 1.011388655469e-01 <br> Line search: Using full step: fnorm 1.011388655469e-01 gnorm 9.847731645400e-02<br>37 SNES Function norm 9.847731645400e-02 <br> Line search: Using full step: fnorm 9.847731645400e-02 gnorm 9.595225705796e-02<br>38 SNES Function norm 9.595225705796e-02 <br> Line search: Using full step: fnorm 9.595225705796e-02 gnorm 9.355345063171e-02<br>39 SNES Function norm 9.355345063171e-02 <br> Line search: Using full step: fnorm 9.355345063171e-02 gnorm 9.127165915308e-02<br>40 SNES Function norm 9.127165915308e-02 <br> Line search: Using full step: fnorm 9.127165915308e-02 gnorm 8.909852441151e-02<br>41 SNES Function norm 8.909852441151e-02 <br> Line search: Using full step: fnorm 8.909852441151e-02 gnorm 8.702646570443e-02<br>42 SNES Function norm 8.702646570443e-02 <br> Line search: Using full step: fnorm 8.702646570443e-02 gnorm 8.504859148402e-02<br>43 SNES Function norm 8.504859148402e-02 <br> Line search: Using full step: fnorm 8.504859148402e-02 gnorm 8.315862278451e-02<br>44 SNES Function norm 8.315862278451e-02 <br> Line search: Using full step: fnorm 8.315862278451e-02 gnorm 8.135082663716e-02<br>45 SNES Function norm 8.135082663716e-02 <br> Line search: Using full step: fnorm 8.135082663716e-02 gnorm 7.961995798542e-02<br>46 SNES Function norm 7.961995798542e-02 <br> Line search: Using full step: fnorm 7.961995798542e-02 gnorm 7.796120886084e-02<br>47 SNES Function norm 7.796120886084e-02 <br> Line search: Using full step: fnorm 7.796120886084e-02 gnorm 7.637016378216e-02<br>48 SNES Function norm 7.637016378216e-02 <br> Line search: Using full step: fnorm 7.637016378216e-02 gnorm 7.484276050661e-02<br>49 SNES Function norm 7.484276050661e-02 <br> Line search: Using full step: fnorm 7.484276050661e-02 gnorm 7.337525539874e-02<br>50 SNES Function norm 7.337525539874e-02 <br>SNES Object:(temp_) 1 MPI processes<br> type: ls<br> maximum iterations=50, maximum function evaluations=10000<br> tolerances: relative=1e-08, absolute=1e-50, solution=1e-08<br> total number of linear solver iterations=693<br> total number of function evaluations=51<br> KSP Object: (temp_) 1 MPI processes<br> type: cg<br> maximum iterations=10000<br> tolerances: relative=1e-08, absolute=1e-50, divergence=10000<br> left preconditioning<br> using nonzero initial guess<br> using PRECONDITIONED norm type for convergence test<br> PC Object: (temp_) 1 MPI processes<br> type: icc<br> 0 levels of fill<br> tolerance for zero pivot 2.22045e-14<br> using Manteuffel shift<br> matrix ordering: natural<br> factor fill ratio given 1, needed 1<br> Factored matrix follows:<br> Matrix Object: 1 MPI processes<br> type: seqsbaij<br> rows=104, cols=104<br> package used to perform factorization: petsc<br> total: nonzeros=381, allocated nonzeros=381<br> total number of mallocs used during MatSetValues calls =0<br> block size is 1<br> linear system matrix = precond matrix:<br> Matrix Object: 1 MPI processes<br> type: seqaij<br> rows=104, cols=104<br> total: nonzeros=658, allocated nonzeros=658<br> total number of mallocs used during MatSetValues calls =0<br> not using I-node routines<br> SNESLineSearch Object: (temp_) 1 MPI processes<br> type: bt<br> interpolation: cubic<br> alpha=1.000000e-04<br> maxstep=1.000000e+08, minlambda=1.000000e-12<br> tolerances: relative=1.000000e-08, absolute=1.000000e-15, lambda=1.000000e-08<br> maximum iterations=40<br>SNESTemp converged in in 50 iterations. SNESConvergedReason is -5 <br><br><br><br><br><br>-- <br>Department of Mathematics and Center for Computation & Technology<br>Louisiana State University, Baton Rouge, LA 70803, USA<br>Tel. +1 (225) 578 1612, Fax +1 (225) 578 4276 <a href="http://www.math.lsu.edu/~bourdin">http://www.math.lsu.edu/~bourdin</a><br><br><br><br><br><br><br><br></blockquote><br></blockquote></div><br><div apple-content-edited="true">-- <br>Department of Mathematics and Center for Computation & Technology<br>Louisiana State University, Baton Rouge, LA 70803, USA<br>Tel. +1 (225) 578 1612, Fax +1 (225) 578 4276 <a href="http://www.math.lsu.edu/~bourdin">http://www.math.lsu.edu/~bourdin</a><br><br><br><br><br><br><br></div><br></div></body></html>