Is there any chance your Jacobian may have a null space? (For example with
Neumann boundary conditions there is often a nullspace)
If not run with with -ksp_type fgmres and send the same output.
Something is screwy with the linear system convergence, could be several
things including either a null space problem or that your Jacobian that you
provide is terribly wrong.
Barry
21 SNES Function norm 2.987064584431e+02
0 KSP preconditioned resid norm 3.076322725615e+05 true resid norm
2.987064584431e+02 ||r(i)||/||b|| 1.000000000000e+00
1 KSP preconditioned resid norm 1.990965035897e+01 true resid norm
1.933504170956e+02 ||r(i)||/||b|| 6.472923890006e-01
2 KSP preconditioned resid norm 6.941661213523e-05 true resid norm
7.058455368301e+01 ||r(i)||/||b|| 2.363007283167e-01
> On Sep 7, 2015, at 8:49 PM, Gideon Simpson <[email protected]> wrote:
>
> Got it, fixing that, and returning to the original question, this is what I
> now get, when I use those two flags:
>
> 0 SNES Function norm 1.132185384796e-08
> 0 KSP preconditioned resid norm 3.846486104194e-09 true resid norm
> 1.132185384796e-08 ||r(i)||/||b|| 1.000000000000e+00
> 1 KSP preconditioned resid norm 2.813743504021e-14 true resid norm
> 4.325870388320e-13 ||r(i)||/||b|| 3.820814547168e-05
> 1 SNES Function norm 2.177599365111e-12
> Nonlinear solve converged due to CONVERGED_SNORM_RELATIVE iterations 1
> 0 SNES Function norm 5.066222213176e+03
> 0 KSP preconditioned resid norm 3.135087050041e+01 true resid norm
> 5.066222213176e+03 ||r(i)||/||b|| 1.000000000000e+00
> 1 KSP preconditioned resid norm 1.498184175046e-04 true resid norm
> 4.217739703330e-01 ||r(i)||/||b|| 8.325216553590e-05
> 1 SNES Function norm 8.482593852817e+02
> 0 KSP preconditioned resid norm 2.667293100105e+02 true resid norm
> 8.482593852817e+02 ||r(i)||/||b|| 1.000000000000e+00
> 1 KSP preconditioned resid norm 8.682642450862e-02 true resid norm
> 2.946982065167e+00 ||r(i)||/||b|| 3.474152029792e-03
> 2 KSP preconditioned resid norm 8.943933962588e-08 true resid norm
> 1.594643891705e-01 ||r(i)||/||b|| 1.879901265314e-04
> 2 SNES Function norm 6.543140468549e+02
> 0 KSP preconditioned resid norm 1.538341367076e+02 true resid norm
> 6.543140468549e+02 ||r(i)||/||b|| 1.000000000000e+00
> 1 KSP preconditioned resid norm 8.294478035133e-03 true resid norm
> 2.460794611648e-01 ||r(i)||/||b|| 3.760876942007e-04
> 2 KSP preconditioned resid norm 1.879002692918e-08 true resid norm
> 6.977344225129e-02 ||r(i)||/||b|| 1.066360145968e-04
> 3 SNES Function norm 5.766430557220e+02
> 0 KSP preconditioned resid norm 1.362249760236e+02 true resid norm
> 5.766430557220e+02 ||r(i)||/||b|| 1.000000000000e+00
> 1 KSP preconditioned resid norm 1.565721843210e-02 true resid norm
> 5.601235825427e-01 ||r(i)||/||b|| 9.713523417730e-04
> 2 KSP preconditioned resid norm 6.900043171759e-08 true resid norm
> 6.087965439352e-02 ||r(i)||/||b|| 1.055759777030e-04
> 4 SNES Function norm 5.235211958260e+02
> 0 KSP preconditioned resid norm 1.533523981591e+02 true resid norm
> 5.235211958260e+02 ||r(i)||/||b|| 1.000000000000e+00
> 1 KSP preconditioned resid norm 1.030969535942e-02 true resid norm
> 3.160110525368e-01 ||r(i)||/||b|| 6.036260901303e-04
> 2 KSP preconditioned resid norm 2.066614364159e-08 true resid norm
> 6.884372743978e-02 ||r(i)||/||b|| 1.315013183586e-04
> 5 SNES Function norm 4.752913229649e+02
> 0 KSP preconditioned resid norm 1.848133067820e+02 true resid norm
> 4.752913229649e+02 ||r(i)||/||b|| 1.000000000000e+00
> 1 KSP preconditioned resid norm 1.745259702307e-02 true resid norm
> 4.900437912538e-01 ||r(i)||/||b|| 1.031038791529e-03
> 2 KSP preconditioned resid norm 1.045643600156e-07 true resid norm
> 8.388613982820e-02 ||r(i)||/||b|| 1.764941537432e-04
> 6 SNES Function norm 4.220255380391e+02
> 0 KSP preconditioned resid norm 2.549151165192e+02 true resid norm
> 4.220255380391e+02 ||r(i)||/||b|| 1.000000000000e+00
> 1 KSP preconditioned resid norm 2.794436126782e-02 true resid norm
> 7.053097905720e-01 ||r(i)||/||b|| 1.671249076180e-03
> 2 KSP preconditioned resid norm 2.890094997586e-07 true resid norm
> 1.285407273503e-01 ||r(i)||/||b|| 3.045804477795e-04
> 7 SNES Function norm 3.805408907074e+02
> 0 KSP preconditioned resid norm 5.225410707531e+02 true resid norm
> 3.805408907074e+02 ||r(i)||/||b|| 1.000000000000e+00
> 1 KSP preconditioned resid norm 1.810631909992e-03 true resid norm
> 2.341273724704e-01 ||r(i)||/||b|| 6.152489211741e-04
> 8 SNES Function norm 3.764619752339e+02
> 0 KSP preconditioned resid norm 6.256830807263e+03 true resid norm
> 3.764619752339e+02 ||r(i)||/||b|| 1.000000000000e+00
> 1 KSP preconditioned resid norm 1.034356591467e+00 true resid norm
> 1.404676339819e+01 ||r(i)||/||b|| 3.731256892403e-02
> 2 KSP preconditioned resid norm 1.014544916729e-05 true resid norm
> 3.741004783833e+00 ||r(i)||/||b|| 9.937271304780e-03
> 9 SNES Function norm 3.761182227091e+02
> 0 KSP preconditioned resid norm 3.988264999623e+03 true resid norm
> 3.761182227091e+02 ||r(i)||/||b|| 1.000000000000e+00
> 1 KSP preconditioned resid norm 4.115167379340e-01 true resid norm
> 6.409965438916e+00 ||r(i)||/||b|| 1.704242190858e-02
> 2 KSP preconditioned resid norm 1.515961219888e-06 true resid norm
> 2.115087826060e+00 ||r(i)||/||b|| 5.623465438140e-03
> 10 SNES Function norm 3.740017190063e+02
> 0 KSP preconditioned resid norm 1.142561025658e+03 true resid norm
> 3.740017190063e+02 ||r(i)||/||b|| 1.000000000000e+00
> 1 KSP preconditioned resid norm 3.746046512685e-02 true resid norm
> 7.402316700861e-01 ||r(i)||/||b|| 1.979219967365e-03
> 2 KSP preconditioned resid norm 1.588755510089e-06 true resid norm
> 6.682186870202e-01 ||r(i)||/||b|| 1.786672769301e-03
> 11 SNES Function norm 3.725903477238e+02
> 0 KSP preconditioned resid norm 1.435759974780e+03 true resid norm
> 3.725903477238e+02 ||r(i)||/||b|| 1.000000000000e+00
> 1 KSP preconditioned resid norm 7.389097536786e-01 true resid norm
> 9.211825929813e+00 ||r(i)||/||b|| 2.472373744003e-02
> 2 KSP preconditioned resid norm 2.785754916084e-06 true resid norm
> 8.219867808452e-01 ||r(i)||/||b|| 2.206140835013e-03
> 12 SNES Function norm 3.716162097231e+02
> 0 KSP preconditioned resid norm 4.010267719047e+02 true resid norm
> 3.716162097231e+02 ||r(i)||/||b|| 1.000000000000e+00
> 1 KSP preconditioned resid norm 2.404383077173e-01 true resid norm
> 2.467625408789e+00 ||r(i)||/||b|| 6.640252346978e-03
> 2 KSP preconditioned resid norm 8.431973894553e-07 true resid norm
> 2.411034602455e-01 ||r(i)||/||b|| 6.487969414067e-04
> 13 SNES Function norm 3.674168632847e+02
> 0 KSP preconditioned resid norm 2.697546464095e+02 true resid norm
> 3.674168632847e+02 ||r(i)||/||b|| 1.000000000000e+00
> 1 KSP preconditioned resid norm 1.100811362173e-01 true resid norm
> 1.260981844274e+00 ||r(i)||/||b|| 3.432019513205e-03
> 2 KSP preconditioned resid norm 8.921252511737e-07 true resid norm
> 1.549846956307e-01 ||r(i)||/||b|| 4.218224886174e-04
> 14 SNES Function norm 3.532395445266e+02
> 0 KSP preconditioned resid norm 4.455211776575e+01 true resid norm
> 3.532395445266e+02 ||r(i)||/||b|| 1.000000000000e+00
> 1 KSP preconditioned resid norm 1.681410748806e-02 true resid norm
> 7.130040117764e-02 ||r(i)||/||b|| 2.018471665543e-04
> 2 KSP preconditioned resid norm 1.060849362790e-07 true resid norm
> 2.654058947496e-02 ||r(i)||/||b|| 7.513481966050e-05
> 15 SNES Function norm 3.182438872366e+02
> 0 KSP preconditioned resid norm 1.515566740696e+02 true resid norm
> 3.182438872366e+02 ||r(i)||/||b|| 1.000000000000e+00
> 1 KSP preconditioned resid norm 4.959786024091e-02 true resid norm
> 5.035985128637e-01 ||r(i)||/||b|| 1.582429492163e-03
> 2 KSP preconditioned resid norm 2.945498964959e-07 true resid norm
> 8.727232650514e-02 ||r(i)||/||b|| 2.742309593531e-04
> 16 SNES Function norm 3.091759892779e+02
> 0 KSP preconditioned resid norm 7.834551377727e+01 true resid norm
> 3.091759892779e+02 ||r(i)||/||b|| 1.000000000000e+00
> 1 KSP preconditioned resid norm 4.992168699741e-02 true resid norm
> 5.040095342951e-01 ||r(i)||/||b|| 1.630170361781e-03
> 2 KSP preconditioned resid norm 3.192091055088e-07 true resid norm
> 4.561900072730e-02 ||r(i)||/||b|| 1.475502701029e-04
> 17 SNES Function norm 2.987839504359e+02
> 0 KSP preconditioned resid norm 9.384044359119e+02 true resid norm
> 2.987839504359e+02 ||r(i)||/||b|| 1.000000000000e+00
> 1 KSP preconditioned resid norm 2.206851078700e-01 true resid norm
> 1.939469657735e+00 ||r(i)||/||b|| 6.491210973364e-03
> 2 KSP preconditioned resid norm 1.074373330828e-06 true resid norm
> 5.530732277225e-01 ||r(i)||/||b|| 1.851080778990e-03
> 18 SNES Function norm 2.987073622777e+02
> 0 KSP preconditioned resid norm 9.576546391157e+03 true resid norm
> 2.987073622777e+02 ||r(i)||/||b|| 1.000000000000e+00
> 1 KSP preconditioned resid norm 3.670797073017e+00 true resid norm
> 3.409551583039e+01 ||r(i)||/||b|| 1.141435402542e-01
> 2 KSP preconditioned resid norm 2.278475684614e-05 true resid norm
> 6.179819087650e+00 ||r(i)||/||b|| 2.068853958110e-02
> 19 SNES Function norm 2.987067936734e+02
> 0 KSP preconditioned resid norm 2.381986890301e+04 true resid norm
> 2.987067936734e+02 ||r(i)||/||b|| 1.000000000000e+00
> 1 KSP preconditioned resid norm 2.870471171439e+01 true resid norm
> 2.593775594691e+02 ||r(i)||/||b|| 8.683349858880e-01
> 2 KSP preconditioned resid norm 1.628164409392e-04 true resid norm
> 2.546845295549e+01 ||r(i)||/||b|| 8.526238269403e-02
> 20 SNES Function norm 2.987067502910e+02
> 0 KSP preconditioned resid norm 3.191539882357e+04 true resid norm
> 2.987067502910e+02 ||r(i)||/||b|| 1.000000000000e+00
> 1 KSP preconditioned resid norm 1.528735548091e+01 true resid norm
> 1.390234679490e+02 ||r(i)||/||b|| 4.654178983689e-01
> 2 KSP preconditioned resid norm 5.890475574699e-05 true resid norm
> 1.018047198868e+01 ||r(i)||/||b|| 3.408182767468e-02
> 21 SNES Function norm 2.987064584431e+02
> 0 KSP preconditioned resid norm 3.076322725615e+05 true resid norm
> 2.987064584431e+02 ||r(i)||/||b|| 1.000000000000e+00
> 1 KSP preconditioned resid norm 1.990965035897e+01 true resid norm
> 1.933504170956e+02 ||r(i)||/||b|| 6.472923890006e-01
> 2 KSP preconditioned resid norm 6.941661213523e-05 true resid norm
> 7.058455368301e+01 ||r(i)||/||b|| 2.363007283167e-01
> 22 SNES Function norm 2.987064525262e+02
> 0 KSP preconditioned resid norm 1.312500251239e+06 true resid norm
> 2.987064525262e+02 ||r(i)||/||b|| 1.000000000000e+00
> 1 KSP preconditioned resid norm 3.194187039215e+01 true resid norm
> 2.898773744566e+02 ||r(i)||/||b|| 9.704422921065e-01
> 2 KSP preconditioned resid norm 2.998846844269e-04 true resid norm
> 2.698070936922e+01 ||r(i)||/||b|| 9.032516419058e-02
> 23 SNES Function norm 2.987064121622e+02
> 0 KSP preconditioned resid norm 1.022854344216e+05 true resid norm
> 2.987064121622e+02 ||r(i)||/||b|| 1.000000000000e+00
> 1 KSP preconditioned resid norm 8.602644501358e+00 true resid norm
> 8.634709464365e+01 ||r(i)||/||b|| 2.890701073962e-01
> 2 KSP preconditioned resid norm 9.288860381060e-05 true resid norm
> 4.471246585837e+01 ||r(i)||/||b|| 1.496869971244e-01
> 24 SNES Function norm 2.987063973426e+02
> 0 KSP preconditioned resid norm 2.876191744212e+05 true resid norm
> 2.987063973426e+02 ||r(i)||/||b|| 1.000000000000e+00
> 1 KSP preconditioned resid norm 4.701586788162e+01 true resid norm
> 4.356767962106e+02 ||r(i)||/||b|| 1.458545247395e+00
> 2 KSP preconditioned resid norm 1.533781032398e-04 true resid norm
> 1.001779383020e+02 ||r(i)||/||b|| 3.353725905879e-01
> 25 SNES Function norm 2.987063920553e+02
> 0 KSP preconditioned resid norm 1.373321357604e+05 true resid norm
> 2.987063920553e+02 ||r(i)||/||b|| 1.000000000000e+00
> 1 KSP preconditioned resid norm 2.804687152206e+02 true resid norm
> 2.541993895057e+03 ||r(i)||/||b|| 8.510008364956e+00
> 2 KSP preconditioned resid norm 2.556287913942e-03 true resid norm
> 8.346997816018e+02 ||r(i)||/||b|| 2.794382054761e+00
> 26 SNES Function norm 2.987063919786e+02
> 0 KSP preconditioned resid norm 1.292036277396e+05 true resid norm
> 2.987063919786e+02 ||r(i)||/||b|| 1.000000000000e+00
> 1 KSP preconditioned resid norm 2.282180994978e+01 true resid norm
> 2.073562667335e+02 ||r(i)||/||b|| 6.941808823037e-01
> 2 KSP preconditioned resid norm 1.163542587614e-04 true resid norm
> 2.367571914844e+01 ||r(i)||/||b|| 7.926083868380e-02
> 27 SNES Function norm 2.987063393145e+02
> 0 KSP preconditioned resid norm 2.447152171843e+05 true resid norm
> 2.987063393145e+02 ||r(i)||/||b|| 1.000000000000e+00
> 1 KSP preconditioned resid norm 2.283727214797e+01 true resid norm
> 2.070985084809e+02 ||r(i)||/||b|| 6.933180894527e-01
> 2 KSP preconditioned resid norm 4.585761865240e-04 true resid norm
> 4.702442627021e+01 ||r(i)||/||b|| 1.574269443967e-01
> 28 SNES Function norm 2.987063253277e+02
> 0 KSP preconditioned resid norm 4.785016507221e+05 true resid norm
> 2.987063253277e+02 ||r(i)||/||b|| 1.000000000000e+00
> 1 KSP preconditioned resid norm 4.095374466008e+01 true resid norm
> 3.817886040589e+02 ||r(i)||/||b|| 1.278140339479e+00
> 2 KSP preconditioned resid norm 9.617782709610e-05 true resid norm
> 1.003348221878e+02 ||r(i)||/||b|| 3.358978825700e-01
> 29 SNES Function norm 2.987063197153e+02
> 0 KSP preconditioned resid norm 1.669977278077e+05 true resid norm
> 2.987063197153e+02 ||r(i)||/||b|| 1.000000000000e+00
> 1 KSP preconditioned resid norm 2.767902454807e+01 true resid norm
> 2.821167168096e+02 ||r(i)||/||b|| 9.444618281879e-01
> 2 KSP preconditioned resid norm 6.086718418040e-04 true resid norm
> 1.840415528667e+02 ||r(i)||/||b|| 6.161287549660e-01
> 30 SNES Function norm 2.987063193089e+02
> 0 KSP preconditioned resid norm 3.136061088127e+05 true resid norm
> 2.987063193089e+02 ||r(i)||/||b|| 1.000000000000e+00
> 1 KSP preconditioned resid norm 1.186362823355e+02 true resid norm
> 1.132640635624e+03 ||r(i)||/||b|| 3.791820133718e+00
> 2 KSP preconditioned resid norm 6.719259676319e-04 true resid norm
> 6.778160111686e+02 ||r(i)||/||b|| 2.269171983830e+00
> 31 SNES Function norm 2.987063192061e+02
> 0 KSP preconditioned resid norm 2.691271219294e+05 true resid norm
> 2.987063192061e+02 ||r(i)||/||b|| 1.000000000000e+00
> 1 KSP preconditioned resid norm 4.462251245099e+01 true resid norm
> 4.074982952445e+02 ||r(i)||/||b|| 1.364210493864e+00
> 2 KSP preconditioned resid norm 1.183786013104e-04 true resid norm
> 7.539314959670e+01 ||r(i)||/||b|| 2.523989107331e-01
> 32 SNES Function norm 2.987063094492e+02
> 0 KSP preconditioned resid norm 1.124446369819e+05 true resid norm
> 2.987063094492e+02 ||r(i)||/||b|| 1.000000000000e+00
> 1 KSP preconditioned resid norm 8.973907556421e+01 true resid norm
> 8.420449781516e+02 ||r(i)||/||b|| 2.818972855660e+00
> 2 KSP preconditioned resid norm 7.374208523915e-04 true resid norm
> 2.422646074110e+02 ||r(i)||/||b|| 8.110461672459e-01
> 33 SNES Function norm 2.987063089942e+02
> 0 KSP preconditioned resid norm 1.329193031679e+05 true resid norm
> 2.987063089942e+02 ||r(i)||/||b|| 1.000000000000e+00
> 1 KSP preconditioned resid norm 2.183766435760e+01 true resid norm
> 2.005487212339e+02 ||r(i)||/||b|| 6.713909790161e-01
> 2 KSP preconditioned resid norm 6.941412108263e-05 true resid norm
> 2.615656494311e+01 ||r(i)||/||b|| 8.756616166289e-02
> 34 SNES Function norm 2.987062660109e+02
> 0 KSP preconditioned resid norm 3.096972895505e+05 true resid norm
> 2.987062660109e+02 ||r(i)||/||b|| 1.000000000000e+00
> 1 KSP preconditioned resid norm 3.733316558393e+01 true resid norm
> 3.375691658619e+02 ||r(i)||/||b|| 1.130104066346e+00
> 2 KSP preconditioned resid norm 2.068548659549e-04 true resid norm
> 3.231989034216e+01 ||r(i)||/||b|| 1.081995726898e-01
> 35 SNES Function norm 2.987062107900e+02
> 0 KSP preconditioned resid norm 6.499649833972e+04 true resid norm
> 2.987062107900e+02 ||r(i)||/||b|| 1.000000000000e+00
> 1 KSP preconditioned resid norm 3.096524448730e+01 true resid norm
> 2.899705639690e+02 ||r(i)||/||b|| 9.707550546139e-01
> 2 KSP preconditioned resid norm 1.801709551672e-04 true resid norm
> 7.425681993520e+01 ||r(i)||/||b|| 2.485948308166e-01
> 36 SNES Function norm 2.987062055224e+02
> 0 KSP preconditioned resid norm 8.633609234208e+04 true resid norm
> 2.987062055224e+02 ||r(i)||/||b|| 1.000000000000e+00
> 1 KSP preconditioned resid norm 1.229972441154e+01 true resid norm
> 1.120738026723e+02 ||r(i)||/||b|| 3.751974368137e-01
> 2 KSP preconditioned resid norm 5.664496361269e-05 true resid norm
> 3.120682958584e+01 ||r(i)||/||b|| 1.044733219763e-01
> 37 SNES Function norm 2.987061774798e+02
> 0 KSP preconditioned resid norm 4.344743984989e+05 true resid norm
> 2.987061774798e+02 ||r(i)||/||b|| 1.000000000000e+00
> 1 KSP preconditioned resid norm 2.372624802517e+01 true resid norm
> 2.243904583149e+02 ||r(i)||/||b|| 7.512079603043e-01
> 2 KSP preconditioned resid norm 2.527665232153e-04 true resid norm
> 7.229322099941e+01 ||r(i)||/||b|| 2.420211781669e-01
> 38 SNES Function norm 2.987061715400e+02
> 0 KSP preconditioned resid norm 5.756130938265e+05 true resid norm
> 2.987061715400e+02 ||r(i)||/||b|| 1.000000000000e+00
> 1 KSP preconditioned resid norm 4.629319937995e+01 true resid norm
> 4.389108492088e+02 ||r(i)||/||b|| 1.469373220332e+00
> 2 KSP preconditioned resid norm 8.099878702234e-04 true resid norm
> 1.923430480373e+02 ||r(i)||/||b|| 6.439205693195e-01
> 39 SNES Function norm 2.987061699634e+02
> 0 KSP preconditioned resid norm 2.326428261777e+05 true resid norm
> 2.987061699634e+02 ||r(i)||/||b|| 1.000000000000e+00
> 1 KSP preconditioned resid norm 1.756089168490e+01 true resid norm
> 1.659759863394e+02 ||r(i)||/||b|| 5.556496752635e-01
> 2 KSP preconditioned resid norm 1.956105557949e-04 true resid norm
> 6.351047187913e+01 ||r(i)||/||b|| 2.126185471392e-01
> 40 SNES Function norm 2.987061630064e+02
> 0 KSP preconditioned resid norm 4.133259484912e+07 true resid norm
> 2.987061630064e+02 ||r(i)||/||b|| 1.000000000000e+00
> 1 KSP preconditioned resid norm 3.296568492777e+01 true resid norm
> 3.022811302762e+02 ||r(i)||/||b|| 1.011968173786e+00
> 41 SNES Function norm 2.987061630064e+02
> 0 KSP preconditioned resid norm 4.124224624453e+07 true resid norm
> 2.987061630064e+02 ||r(i)||/||b|| 1.000000000000e+00
> 1 KSP preconditioned resid norm 3.219934148122e+01 true resid norm
> 3.144341309207e+02 ||r(i)||/||b|| 1.052653643822e+00
> 42 SNES Function norm 2.987061630064e+02
> 0 KSP preconditioned resid norm 5.748707463105e+08 true resid norm
> 2.987061630064e+02 ||r(i)||/||b|| 1.000000000000e+00
> 1 KSP preconditioned resid norm 3.291843121908e+01 true resid norm
> 3.293271430969e+02 ||r(i)||/||b|| 1.102512046562e+00
> 43 SNES Function norm 2.987061630064e+02
> 0 KSP preconditioned resid norm 1.022718794881e+09 true resid norm
> 2.987061630064e+02 ||r(i)||/||b|| 1.000000000000e+00
> 1 KSP preconditioned resid norm 3.314705152175e+01 true resid norm
> 3.015751234379e+02 ||r(i)||/||b|| 1.009604624165e+00
> 44 SNES Function norm 2.987061630064e+02
> 0 KSP preconditioned resid norm 5.380361366230e+08 true resid norm
> 2.987061630064e+02 ||r(i)||/||b|| 1.000000000000e+00
> 1 KSP preconditioned resid norm 3.237699578864e+01 true resid norm
> 3.185658867057e+02 ||r(i)||/||b|| 1.066485818369e+00
> 45 SNES Function norm 2.987061630064e+02
> 0 KSP preconditioned resid norm 6.303672864381e+08 true resid norm
> 2.987061630064e+02 ||r(i)||/||b|| 1.000000000000e+00
> 1 KSP preconditioned resid norm 3.789746869236e+01 true resid norm
> 4.518602376852e+02 ||r(i)||/||b|| 1.512724856888e+00
> 46 SNES Function norm 2.987061630064e+02
> 0 KSP preconditioned resid norm 3.428971983722e+09 true resid norm
> 2.987061630064e+02 ||r(i)||/||b|| 1.000000000000e+00
> 1 KSP preconditioned resid norm 3.314776104627e+01 true resid norm
> 2.999404779745e+02 ||r(i)||/||b|| 1.004132204557e+00
> 47 SNES Function norm 2.987061630064e+02
> 0 KSP preconditioned resid norm 5.189185292378e+09 true resid norm
> 2.987061630064e+02 ||r(i)||/||b|| 1.000000000000e+00
> 1 KSP preconditioned resid norm 3.191097159135e+01 true resid norm
> 3.466943097246e+02 ||r(i)||/||b|| 1.160653353233e+00
> Nonlinear solve did not converge due to DIVERGED_LINE_SEARCH iterations 47
>
>
> -gideon
>
>> On Sep 7, 2015, at 9:39 PM, Barry Smith <[email protected]> wrote:
>>
>>
>> This indicates that somewhere in your ComputeJacobian you are setting
>> matrix entries with the first Mat argument when you should always set them
>> with the second matrix argument. For example if you have
>>
>> ComputeJacobian(SNES snes,Vec x, Mat J, Mat jpre,void *ctx)
>>
>> you should call all the MatSetValues() with jpre, no J. Then at the end of
>> the function you should call MatAssemblyBegin/End() on jpre then on J if J
>> is not == jpre see for example src/snes/examples/tutorials/ex1.c
>>
>> This is a minor glitch we'll get past.
>>
>> Barry
>>
>>> On Sep 7, 2015, at 8:32 PM, Gideon Simpson <[email protected]> wrote:
>>>
>>> By the way, I tried using a different petsc installation, and now, rather
>>> than the segmentation fault, I get the following error:
>>>
>>> [0]PETSC ERROR: --------------------- Error Message
>>> --------------------------------------------------------------
>>> [0]PETSC ERROR: No support for this operation for this object type
>>> [0]PETSC ERROR: Mat type mffd
>>> [0]PETSC ERROR: See http://www.mcs.anl.gov/petsc/documentation/faq.html for
>>> trouble shooting.
>>> [0]PETSC ERROR: Petsc Release Version 3.5.4, May, 23, 2015
>>> [0]PETSC ERROR: ./blowup_batch_refine on a arch-darwin-c-debug named gs_air
>>> by gideon Mon Sep 7 21:32:18 2015
>>> [0]PETSC ERROR: Configure options --download-mpich=yes
>>> --download-suitesparse=yes --download-superlu=yes
>>> --download-superlu_dist=yes --download-mumps=yes --download-sprng=yes
>>> --with-cxx=clang++ --with-cc=clang --with-fc=gfortran --download-metis=yes
>>> --download-parmetis=yes --download-scalapack=yes
>>> [0]PETSC ERROR: #3892 MatSetValues() line 1116 in
>>> /opt/petsc-3.5.4/src/mat/interface/matrix.c
>>>
>>> -gideon
>>>
>>>> On Sep 7, 2015, at 9:22 PM, Barry Smith <[email protected]> wrote:
>>>>
>>>>
>>>> Hmm,
>>>>
>>>> Ok you can try running it directly in the debugger since it is one
>>>> process, type
>>>>
>>>> gdb ./blowup_batch_refine
>>>>
>>>> then
>>>>
>>>> when the debugger comes up (if it does not cut and paste all output and
>>>> send it)
>>>>
>>>> run -on_error_abort -snes_mf_operator and any other options you normally
>>>> use
>>>>
>>>>
>>>> Barry
>>>>
>>>>> On Sep 7, 2015, at 8:18 PM, Gideon Simpson <[email protected]>
>>>>> wrote:
>>>>>
>>>>> Running with that flag gives me this:
>>>>>
>>>>> [0]PETSC ERROR: PETSC: Attaching gdb to ./blowup_batch_refine of pid
>>>>> 16111 on gs_air
>>>>> Unable to start debugger: No such file or directory
>>>>>
>>>>>
>>>>>
>>>>> -gideon
>>>>>
>>>>>> On Sep 7, 2015, at 9:11 PM, Barry Smith <[email protected]> wrote:
>>>>>>
>>>>>>
>>>>>> This should not happen. Run with a debug version of PETSc installed and
>>>>>> the option -start_in_debugger noxterm Once the debugger starts up type
>>>>>> cont and when it crashes type where or bt Send all output
>>>>>>
>>>>>>
>>>>>>
>>>>>> Barry
>>>>>>
>>>>>>
>>>>>>> On Sep 7, 2015, at 8:09 PM, Gideon Simpson <[email protected]>
>>>>>>> wrote:
>>>>>>>
>>>>>>> I’m getting an error with -snes_mf_operator,
>>>>>>>
>>>>>>> 0 SNES Function norm 1.421454390131e-02
>>>>>>> [0]PETSC ERROR:
>>>>>>> ------------------------------------------------------------------------
>>>>>>> [0]PETSC ERROR: Caught signal number 11 SEGV: Segmentation Violation,
>>>>>>> probably memory access out of range
>>>>>>> [0]PETSC ERROR: Try option -start_in_debugger or
>>>>>>> -on_error_attach_debugger
>>>>>>> [0]PETSC ERROR: or see
>>>>>>> http://www.mcs.anl.gov/petsc/documentation/faq.html#valgrind
>>>>>>> [0]PETSC ERROR: or try http://valgrind.org on GNU/linux and Apple Mac
>>>>>>> OS X to find memory corruption errors
>>>>>>> [0]PETSC ERROR: configure using --with-debugging=yes, recompile, link,
>>>>>>> and run
>>>>>>> [0]PETSC ERROR: to get more information on the crash.
>>>>>>> [0]PETSC ERROR: --------------------- Error Message
>>>>>>> --------------------------------------------------------------
>>>>>>> [0]PETSC ERROR: Signal received
>>>>>>> [0]PETSC ERROR: See http://www.mcs.anl.gov/petsc/documentation/faq.html
>>>>>>> for trouble shooting.
>>>>>>> [0]PETSC ERROR: Petsc Release Version 3.5.3, unknown
>>>>>>> [0]PETSC ERROR: ./blowup_batch_refine on a arch-macports named gs_air
>>>>>>> by gideon Mon Sep 7 21:08:19 2015
>>>>>>> [0]PETSC ERROR: Configure options --prefix=/opt/local
>>>>>>> --prefix=/opt/local/lib/petsc --with-valgrind=0 --with-shared-libraries
>>>>>>> --with-debugging=0 --with-c2html-dir=/opt/local --with-x=0
>>>>>>> --with-blas-lapack-lib=/System/Library/Frameworks/Accelerate.framework/Versions/Current/Accelerate
>>>>>>> --with-hwloc-dir=/opt/local --with-suitesparse-dir=/opt/local
>>>>>>> --with-superlu-dir=/opt/local --with-metis-dir=/opt/local
>>>>>>> --with-parmetis-dir=/opt/local --with-scalapack-dir=/opt/local
>>>>>>> --with-mumps-dir=/opt/local --with-superlu_dist-dir=/opt/local
>>>>>>> CC=/opt/local/bin/mpicc-mpich-mp CXX=/opt/local/bin/mpicxx-mpich-mp
>>>>>>> FC=/opt/local/bin/mpif90-mpich-mp F77=/opt/local/bin/mpif90-mpich-mp
>>>>>>> F90=/opt/local/bin/mpif90-mpich-mp COPTFLAGS=-Os CXXOPTFLAGS=-Os
>>>>>>> FOPTFLAGS=-Os LDFLAGS="-L/opt/local/lib
>>>>>>> -Wl,-headerpad_max_install_names" CPPFLAGS=-I/opt/local/include
>>>>>>> CFLAGS="-Os -arch x86_64" CXXFLAGS=-Os FFLAGS=-Os FCFLAGS=-Os
>>>>>>> F90FLAGS=-Os PETSC_ARCH=arch-macports --with-mpiexec=mpiexec-mpich-mp
>>>>>>> [0]PETSC ERROR: #1 User provided function() line 0 in unknown file
>>>>>>> application called MPI_Abort(MPI_COMM_WORLD, 59) - process 0
>>>>>>>
>>>>>>> -gideon
>>>>>>>
>>>>>>>> On Sep 7, 2015, at 9:01 PM, Barry Smith <[email protected]> wrote:
>>>>>>>>
>>>>>>>>
>>>>>>>> My guess is the Jacobian is not correct (or correct "enough"), hence
>>>>>>>> PETSc SNES is generating a poor descent direction. You can try
>>>>>>>> -snes_mf_operator -ksp_monitor_true residual as additional arguments.
>>>>>>>> What happens?
>>>>>>>>
>>>>>>>> Barry
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>>> On Sep 7, 2015, at 7:49 PM, Gideon Simpson <[email protected]>
>>>>>>>>> wrote:
>>>>>>>>>
>>>>>>>>> No problem Matt, I don’t think we had previously discussed that
>>>>>>>>> output. Here is a case where things fail.
>>>>>>>>>
>>>>>>>>> 0 SNES Function norm 4.027481756921e-09
>>>>>>>>> 1 SNES Function norm 1.760477878365e-12
>>>>>>>>> Nonlinear solve converged due to CONVERGED_SNORM_RELATIVE iterations 1
>>>>>>>>> 0 SNES Function norm 5.066222213176e+03
>>>>>>>>> 1 SNES Function norm 8.484697184230e+02
>>>>>>>>> 2 SNES Function norm 6.549559723294e+02
>>>>>>>>> 3 SNES Function norm 5.770723278153e+02
>>>>>>>>> 4 SNES Function norm 5.237702240594e+02
>>>>>>>>> 5 SNES Function norm 4.753909019848e+02
>>>>>>>>> 6 SNES Function norm 4.221784590755e+02
>>>>>>>>> 7 SNES Function norm 3.806525080483e+02
>>>>>>>>> 8 SNES Function norm 3.762054656019e+02
>>>>>>>>> 9 SNES Function norm 3.758975226873e+02
>>>>>>>>> 10 SNES Function norm 3.757032042706e+02
>>>>>>>>> 11 SNES Function norm 3.728798164234e+02
>>>>>>>>> 12 SNES Function norm 3.723078741075e+02
>>>>>>>>> 13 SNES Function norm 3.721848059825e+02
>>>>>>>>> 14 SNES Function norm 3.720227575629e+02
>>>>>>>>> 15 SNES Function norm 3.720051998555e+02
>>>>>>>>> 16 SNES Function norm 3.718945430587e+02
>>>>>>>>> 17 SNES Function norm 3.700412694044e+02
>>>>>>>>> 18 SNES Function norm 3.351964889461e+02
>>>>>>>>> 19 SNES Function norm 3.096016086233e+02
>>>>>>>>> 20 SNES Function norm 3.008410789787e+02
>>>>>>>>> 21 SNES Function norm 2.752316716557e+02
>>>>>>>>> 22 SNES Function norm 2.707658474165e+02
>>>>>>>>> 23 SNES Function norm 2.698436736049e+02
>>>>>>>>> 24 SNES Function norm 2.618233857172e+02
>>>>>>>>> 25 SNES Function norm 2.600121920634e+02
>>>>>>>>> 26 SNES Function norm 2.585046423168e+02
>>>>>>>>> 27 SNES Function norm 2.568551090220e+02
>>>>>>>>> 28 SNES Function norm 2.556404537064e+02
>>>>>>>>> 29 SNES Function norm 2.536353523683e+02
>>>>>>>>> 30 SNES Function norm 2.533596070171e+02
>>>>>>>>> 31 SNES Function norm 2.532324379596e+02
>>>>>>>>> 32 SNES Function norm 2.531842335211e+02
>>>>>>>>> 33 SNES Function norm 2.531684527520e+02
>>>>>>>>> 34 SNES Function norm 2.531637604618e+02
>>>>>>>>> 35 SNES Function norm 2.531624767821e+02
>>>>>>>>> 36 SNES Function norm 2.531621359093e+02
>>>>>>>>> 37 SNES Function norm 2.531620504925e+02
>>>>>>>>> 38 SNES Function norm 2.531620350055e+02
>>>>>>>>> 39 SNES Function norm 2.531620310522e+02
>>>>>>>>> 40 SNES Function norm 2.531620300471e+02
>>>>>>>>> 41 SNES Function norm 2.531620298084e+02
>>>>>>>>> 42 SNES Function norm 2.531620297478e+02
>>>>>>>>> 43 SNES Function norm 2.531620297324e+02
>>>>>>>>> 44 SNES Function norm 2.531620297303e+02
>>>>>>>>> 45 SNES Function norm 2.531620297302e+02
>>>>>>>>> Nonlinear solve did not converge due to DIVERGED_LINE_SEARCH
>>>>>>>>> iterations 45
>>>>>>>>> 0 SNES Function norm 9.636339304380e+03
>>>>>>>>> 1 SNES Function norm 8.997731184634e+03
>>>>>>>>> 2 SNES Function norm 8.120498349232e+03
>>>>>>>>> 3 SNES Function norm 7.322379894820e+03
>>>>>>>>> 4 SNES Function norm 6.599581599149e+03
>>>>>>>>> 5 SNES Function norm 6.374872854688e+03
>>>>>>>>> 6 SNES Function norm 6.372518007653e+03
>>>>>>>>> 7 SNES Function norm 6.073996314301e+03
>>>>>>>>> 8 SNES Function norm 5.635965277054e+03
>>>>>>>>> 9 SNES Function norm 5.155389064046e+03
>>>>>>>>> 10 SNES Function norm 5.080567902638e+03
>>>>>>>>> 11 SNES Function norm 5.058878643969e+03
>>>>>>>>> 12 SNES Function norm 5.058835649793e+03
>>>>>>>>> 13 SNES Function norm 5.058491285707e+03
>>>>>>>>> 14 SNES Function norm 5.057452865337e+03
>>>>>>>>> 15 SNES Function norm 5.057226140688e+03
>>>>>>>>> 16 SNES Function norm 5.056651272898e+03
>>>>>>>>> 17 SNES Function norm 5.056575190057e+03
>>>>>>>>> 18 SNES Function norm 5.056574632598e+03
>>>>>>>>> 19 SNES Function norm 5.056574520229e+03
>>>>>>>>> 20 SNES Function norm 5.056574492569e+03
>>>>>>>>> 21 SNES Function norm 5.056574485124e+03
>>>>>>>>> 22 SNES Function norm 5.056574483029e+03
>>>>>>>>> 23 SNES Function norm 5.056574482427e+03
>>>>>>>>> 24 SNES Function norm 5.056574482302e+03
>>>>>>>>> 25 SNES Function norm 5.056574482287e+03
>>>>>>>>> 26 SNES Function norm 5.056574482282e+03
>>>>>>>>> 27 SNES Function norm 5.056574482281e+03
>>>>>>>>> Nonlinear solve did not converge due to DIVERGED_LINE_SEARCH
>>>>>>>>> iterations 27
>>>>>>>>> SNES Object: 1 MPI processes
>>>>>>>>> type: newtonls
>>>>>>>>> maximum iterations=50, maximum function evaluations=10000
>>>>>>>>> tolerances: relative=1e-08, absolute=1e-50, solution=1e-08
>>>>>>>>> total number of linear solver iterations=28
>>>>>>>>> total number of function evaluations=323
>>>>>>>>> total number of grid sequence refinements=2
>>>>>>>>> SNESLineSearch Object: 1 MPI processes
>>>>>>>>> type: bt
>>>>>>>>> interpolation: cubic
>>>>>>>>> alpha=1.000000e-04
>>>>>>>>> maxstep=1.000000e+08, minlambda=1.000000e-12
>>>>>>>>> tolerances: relative=1.000000e-08, absolute=1.000000e-15,
>>>>>>>>> lambda=1.000000e-08
>>>>>>>>> maximum iterations=40
>>>>>>>>> KSP Object: 1 MPI processes
>>>>>>>>> type: gmres
>>>>>>>>> GMRES: restart=30, using Classical (unmodified) Gram-Schmidt
>>>>>>>>> Orthogonalization with no iterative refinement
>>>>>>>>> GMRES: happy breakdown tolerance 1e-30
>>>>>>>>> maximum iterations=10000, initial guess is zero
>>>>>>>>> tolerances: relative=1e-05, absolute=1e-50, divergence=10000
>>>>>>>>> left preconditioning
>>>>>>>>> using PRECONDITIONED norm type for convergence test
>>>>>>>>> PC Object: 1 MPI processes
>>>>>>>>> type: lu
>>>>>>>>> LU: out-of-place factorization
>>>>>>>>> tolerance for zero pivot 2.22045e-14
>>>>>>>>> matrix ordering: nd
>>>>>>>>> factor fill ratio given 0, needed 0
>>>>>>>>> Factored matrix follows:
>>>>>>>>> Mat Object: 1 MPI processes
>>>>>>>>> type: seqaij
>>>>>>>>> rows=15991, cols=15991
>>>>>>>>> package used to perform factorization: mumps
>>>>>>>>> total: nonzeros=255801, allocated nonzeros=255801
>>>>>>>>> total number of mallocs used during MatSetValues calls =0
>>>>>>>>> MUMPS run parameters:
>>>>>>>>> SYM (matrix type): 0
>>>>>>>>> PAR (host participation): 1
>>>>>>>>> ICNTL(1) (output for error): 6
>>>>>>>>> ICNTL(2) (output of diagnostic msg): 0
>>>>>>>>> ICNTL(3) (output for global info): 0
>>>>>>>>> ICNTL(4) (level of printing): 0
>>>>>>>>> ICNTL(5) (input mat struct): 0
>>>>>>>>> ICNTL(6) (matrix prescaling): 7
>>>>>>>>> ICNTL(7) (sequentia matrix ordering):6
>>>>>>>>> ICNTL(8) (scalling strategy): 77
>>>>>>>>> ICNTL(10) (max num of refinements): 0
>>>>>>>>> ICNTL(11) (error analysis): 0
>>>>>>>>> ICNTL(12) (efficiency control): 1
>>>>>>>>> ICNTL(13) (efficiency control): 0
>>>>>>>>> ICNTL(14) (percentage of estimated workspace increase):
>>>>>>>>> 20
>>>>>>>>> ICNTL(18) (input mat struct): 0
>>>>>>>>> ICNTL(19) (Shur complement info): 0
>>>>>>>>> ICNTL(20) (rhs sparse pattern): 0
>>>>>>>>> ICNTL(21) (somumpstion struct):
>>>>>>>>> 0
>>>>>>>>> ICNTL(22) (in-core/out-of-core facility): 0
>>>>>>>>> ICNTL(23) (max size of memory can be allocated locally):0
>>>>>>>>> ICNTL(24) (detection of null pivot rows): 0
>>>>>>>>> ICNTL(25) (computation of a null space basis): 0
>>>>>>>>> ICNTL(26) (Schur options for rhs or solution): 0
>>>>>>>>> ICNTL(27) (experimental parameter):
>>>>>>>>> -8
>>>>>>>>> ICNTL(28) (use parallel or sequential ordering): 1
>>>>>>>>> ICNTL(29) (parallel ordering): 0
>>>>>>>>> ICNTL(30) (user-specified set of entries in inv(A)): 0
>>>>>>>>> ICNTL(31) (factors is discarded in the solve phase): 0
>>>>>>>>> ICNTL(33) (compute determinant): 0
>>>>>>>>> CNTL(1) (relative pivoting threshold): 0.01
>>>>>>>>> CNTL(2) (stopping criterion of refinement): 1.49012e-08
>>>>>>>>> CNTL(3) (absomumpste pivoting threshold): 0
>>>>>>>>> CNTL(4) (vamumpse of static pivoting): -1
>>>>>>>>> CNTL(5) (fixation for null pivots): 0
>>>>>>>>> RINFO(1) (local estimated flops for the elimination after
>>>>>>>>> analysis):
>>>>>>>>> [0] 1.95838e+06
>>>>>>>>> RINFO(2) (local estimated flops for the assembly after
>>>>>>>>> factorization):
>>>>>>>>> [0] 143924
>>>>>>>>> RINFO(3) (local estimated flops for the elimination after
>>>>>>>>> factorization):
>>>>>>>>> [0] 1.95943e+06
>>>>>>>>> INFO(15) (estimated size of (in MB) MUMPS internal data
>>>>>>>>> for running numerical factorization):
>>>>>>>>> [0] 7
>>>>>>>>> INFO(16) (size of (in MB) MUMPS internal data used during
>>>>>>>>> numerical factorization):
>>>>>>>>> [0] 7
>>>>>>>>> INFO(23) (num of pivots eliminated on this processor
>>>>>>>>> after factorization):
>>>>>>>>> [0] 15991
>>>>>>>>> RINFOG(1) (global estimated flops for the elimination
>>>>>>>>> after analysis): 1.95838e+06
>>>>>>>>> RINFOG(2) (global estimated flops for the assembly after
>>>>>>>>> factorization): 143924
>>>>>>>>> RINFOG(3) (global estimated flops for the elimination
>>>>>>>>> after factorization): 1.95943e+06
>>>>>>>>> (RINFOG(12) RINFOG(13))*2^INFOG(34) (determinant):
>>>>>>>>> (0,0)*(2^0)
>>>>>>>>> INFOG(3) (estimated real workspace for factors on all
>>>>>>>>> processors after analysis): 255801
>>>>>>>>> INFOG(4) (estimated integer workspace for factors on all
>>>>>>>>> processors after analysis): 127874
>>>>>>>>> INFOG(5) (estimated maximum front size in the complete
>>>>>>>>> tree): 11
>>>>>>>>> INFOG(6) (number of nodes in the complete tree): 3996
>>>>>>>>> INFOG(7) (ordering option effectively use after
>>>>>>>>> analysis): 6
>>>>>>>>> INFOG(8) (structural symmetry in percent of the permuted
>>>>>>>>> matrix after analysis): 86
>>>>>>>>> INFOG(9) (total real/complex workspace to store the
>>>>>>>>> matrix factors after factorization): 255865
>>>>>>>>> INFOG(10) (total integer space store the matrix factors
>>>>>>>>> after factorization): 127890
>>>>>>>>> INFOG(11) (order of largest frontal matrix after
>>>>>>>>> factorization): 11
>>>>>>>>> INFOG(12) (number of off-diagonal pivots): 19
>>>>>>>>> INFOG(13) (number of delayed pivots after factorization):
>>>>>>>>> 8
>>>>>>>>> INFOG(14) (number of memory compress after
>>>>>>>>> factorization): 0
>>>>>>>>> INFOG(15) (number of steps of iterative refinement after
>>>>>>>>> solution): 0
>>>>>>>>> INFOG(16) (estimated size (in MB) of all MUMPS internal
>>>>>>>>> data for factorization after analysis: value on the most memory
>>>>>>>>> consuming processor): 7
>>>>>>>>> INFOG(17) (estimated size of all MUMPS internal data for
>>>>>>>>> factorization after analysis: sum over all processors): 7
>>>>>>>>> INFOG(18) (size of all MUMPS internal data allocated
>>>>>>>>> during factorization: value on the most memory consuming processor):
>>>>>>>>> 7
>>>>>>>>> INFOG(19) (size of all MUMPS internal data allocated
>>>>>>>>> during factorization: sum over all processors): 7
>>>>>>>>> INFOG(20) (estimated number of entries in the factors):
>>>>>>>>> 255801
>>>>>>>>> INFOG(21) (size in MB of memory effectively used during
>>>>>>>>> factorization - value on the most memory consuming processor): 7
>>>>>>>>> INFOG(22) (size in MB of memory effectively used during
>>>>>>>>> factorization - sum over all processors): 7
>>>>>>>>> INFOG(23) (after analysis: value of ICNTL(6) effectively
>>>>>>>>> used): 0
>>>>>>>>> INFOG(24) (after analysis: value of ICNTL(12) effectively
>>>>>>>>> used): 1
>>>>>>>>> INFOG(25) (after factorization: number of pivots modified
>>>>>>>>> by static pivoting): 0
>>>>>>>>> INFOG(28) (after factorization: number of null pivots
>>>>>>>>> encountered): 0
>>>>>>>>> INFOG(29) (after factorization: effective number of
>>>>>>>>> entries in the factors (sum over all processors)): 255865
>>>>>>>>> INFOG(30, 31) (after solution: size in Mbytes of memory
>>>>>>>>> used during solution phase): 5, 5
>>>>>>>>> INFOG(32) (after analysis: type of analysis done): 1
>>>>>>>>> INFOG(33) (value used for ICNTL(8)): 7
>>>>>>>>> INFOG(34) (exponent of the determinant if determinant is
>>>>>>>>> requested): 0
>>>>>>>>> linear system matrix = precond matrix:
>>>>>>>>> Mat Object: 1 MPI processes
>>>>>>>>> type: seqaij
>>>>>>>>> rows=15991, cols=15991
>>>>>>>>> total: nonzeros=223820, allocated nonzeros=431698
>>>>>>>>> total number of mallocs used during MatSetValues calls =15991
>>>>>>>>> using I-node routines: found 4000 nodes, limit used is 5
>>>>>>>>>
>>>>>>>>>
>>>>>>>>>
>>>>>>>>>
>>>>>>>>> -gideon
>>>>>>>>>
>>>>>>>>>> On Sep 7, 2015, at 8:40 PM, Matthew Knepley <[email protected]>
>>>>>>>>>> wrote:
>>>>>>>>>>
>>>>>>>>>> On Mon, Sep 7, 2015 at 7:32 PM, Gideon Simpson
>>>>>>>>>> <[email protected]> wrote:
>>>>>>>>>> Barry,
>>>>>>>>>>
>>>>>>>>>> I finally got a chance to really try using the grid sequencing
>>>>>>>>>> within my code. I find that, in some cases, even if it can solve
>>>>>>>>>> successfully on the coarsest mesh, the SNES fails, usually due to a
>>>>>>>>>> line search failure, when it tries to compute along the grid
>>>>>>>>>> sequence. Would you have any suggestions?
>>>>>>>>>>
>>>>>>>>>> I apologize if I have asked before, but can you give me -snes_view
>>>>>>>>>> for the solver? I could not find it in the email thread.
>>>>>>>>>>
>>>>>>>>>> I would suggest trying to fiddle with the line search, or
>>>>>>>>>> precondition it with Richardson. It would be nice to see
>>>>>>>>>> -snes_monitor
>>>>>>>>>> for the runs that fail, and then we can break down the residual into
>>>>>>>>>> fields and look at it again (if my custom residual monitor
>>>>>>>>>> does not work we can write one easily). Seeing which part of the
>>>>>>>>>> residual does not converge is key to designing the NASM
>>>>>>>>>> for the problem. I have just seen the virtuoso of this, Xiao-Chuan
>>>>>>>>>> Cai, present it. We need better monitoring in PETSc.
>>>>>>>>>>
>>>>>>>>>> Thanks,
>>>>>>>>>>
>>>>>>>>>> Matt
>>>>>>>>>>
>>>>>>>>>> -gideon
>>>>>>>>>>
>>>>>>>>>>> On Aug 28, 2015, at 4:21 PM, Barry Smith <[email protected]> wrote:
>>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>>>> On Aug 28, 2015, at 3:04 PM, Gideon Simpson
>>>>>>>>>>>> <[email protected]> wrote:
>>>>>>>>>>>>
>>>>>>>>>>>> Yes, if i continue in this parameter on the coarse mesh, I can
>>>>>>>>>>>> generally solve at all values. I do find that I need to do some
>>>>>>>>>>>> amount of continuation to solve near the endpoint. The problem is
>>>>>>>>>>>> that on the coarse mesh, things are not fully resolved at all the
>>>>>>>>>>>> values along the continuation parameter, and I would like to do
>>>>>>>>>>>> refinement.
>>>>>>>>>>>>
>>>>>>>>>>>> One subtlety is that I actually want the intermediate continuation
>>>>>>>>>>>> solutions too. Currently, without doing any grid sequence, I
>>>>>>>>>>>> compute each, write it to disk, and then go on to the next one.
>>>>>>>>>>>> So I now need to go back an refine them. I was thinking that
>>>>>>>>>>>> perhaps I could refine them on the fly, dump them to disk, and use
>>>>>>>>>>>> the coarse solution as the starting guess at the next iteration,
>>>>>>>>>>>> but that would seem to require resetting the snes back to the
>>>>>>>>>>>> coarse grid.
>>>>>>>>>>>>
>>>>>>>>>>>> The alternative would be to just script the mesh refinement in a
>>>>>>>>>>>> post processing stage, where each value of the continuation is
>>>>>>>>>>>> parameter is loaded on the coarse mesh, and refined. Perhaps
>>>>>>>>>>>> that’s the most practical thing to do.
>>>>>>>>>>>
>>>>>>>>>>> I would do the following. Create your DM and create a SNES that
>>>>>>>>>>> will do the continuation
>>>>>>>>>>>
>>>>>>>>>>> loop over continuation parameter
>>>>>>>>>>>
>>>>>>>>>>> SNESSolve(snes,NULL,Ucoarse);
>>>>>>>>>>>
>>>>>>>>>>> if (you decide you want to see the refined solution at this
>>>>>>>>>>> continuation point) {
>>>>>>>>>>> SNESCreate(comm,&snesrefine);
>>>>>>>>>>> SNESSetDM()
>>>>>>>>>>> etc
>>>>>>>>>>> SNESSetGridSequence(snesrefine,)
>>>>>>>>>>> SNESSolve(snesrefine,0,Ucoarse);
>>>>>>>>>>> SNESGetSolution(snesrefine,&Ufine);
>>>>>>>>>>> VecView(Ufine or do whatever you want to do with the Ufine
>>>>>>>>>>> at that continuation point
>>>>>>>>>>> SNESDestroy(snesrefine);
>>>>>>>>>>> end if
>>>>>>>>>>>
>>>>>>>>>>> end loop over continuation parameter.
>>>>>>>>>>>
>>>>>>>>>>> Barry
>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>> -gideon
>>>>>>>>>>>>
>>>>>>>>>>>>> On Aug 28, 2015, at 3:55 PM, Barry Smith <[email protected]>
>>>>>>>>>>>>> wrote:
>>>>>>>>>>>>>
>>>>>>>>>>>>>>
>>>>>>>>>>>>>>
>>>>>>>>>>>>>> 3. This problem is actually part of a continuation problem that
>>>>>>>>>>>>>> roughly looks like this
>>>>>>>>>>>>>>
>>>>>>>>>>>>>> for( continuation parameter p = 0 to 1){
>>>>>>>>>>>>>>
>>>>>>>>>>>>>> solve with parameter p_i using solution from p_{i-1},
>>>>>>>>>>>>>> }
>>>>>>>>>>>>>>
>>>>>>>>>>>>>> What I would like to do is to start the solver, for each value
>>>>>>>>>>>>>> of parameter p_i on the coarse mesh, and then do grid sequencing
>>>>>>>>>>>>>> on that. But it appears that after doing grid sequencing on the
>>>>>>>>>>>>>> initial p_0 = 0, the SNES is set to use the finer mesh.
>>>>>>>>>>>>>
>>>>>>>>>>>>> So you are using continuation to give you a good enough initial
>>>>>>>>>>>>> guess on the coarse level to even get convergence on the coarse
>>>>>>>>>>>>> level? First I would check if you even need the continuation (or
>>>>>>>>>>>>> can you not even solve the coarse problem without it).
>>>>>>>>>>>>>
>>>>>>>>>>>>> If you do need the continuation then you will need to tweak how
>>>>>>>>>>>>> you do the grid sequencing. I think this will work:
>>>>>>>>>>>>>
>>>>>>>>>>>>> Do not use -snes_grid_sequencing
>>>>>>>>>>>>>
>>>>>>>>>>>>> Run SNESSolve() as many times as you want with your continuation
>>>>>>>>>>>>> parameter. This will all happen on the coarse mesh.
>>>>>>>>>>>>>
>>>>>>>>>>>>> Call SNESSetGridSequence()
>>>>>>>>>>>>>
>>>>>>>>>>>>> Then call SNESSolve() again and it will do one solve on the
>>>>>>>>>>>>> coarse level and then interpolate to the next level etc.
>>>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> --
>>>>>>>>>> What most experimenters take for granted before they begin their
>>>>>>>>>> experiments is infinitely more interesting than any results to which
>>>>>>>>>> their experiments lead.
>>>>>>>>>> -- Norbert Wiener
>>>>>>>>>
>>>>>>>>
>>>>>>>
>>>>>>
>>>>>
>>>>
>>>
>>
>
