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
>>>>>>>>
>>>>>>>
>>>>>>
>>>>>
>>>>
>>>
>>
>
