Would you be able to share your code? I'm at a loss as to why we are seeing this behavior and can much more quickly figure it out by running the code in a debugger.
Barry You can send the code [email protected] <mailto:[email protected]> if you don't want to share the code with everyone, > On Sep 30, 2025, at 5:05 AM, Moral Sanchez, Elena > <[email protected]> wrote: > > This is what I get: > Residual norms for mg_levels_1_ solve. > 0 KSP Residual norm 2.249726733143e+00 > Residual norms for mg_levels_1_ solve. > 0 KSP unpreconditioned resid norm 2.249726733143e+00 true resid norm > 2.249726733143e+00 ||r(i)||/||b|| 1.000000000000e+00 > 1 KSP Residual norm 1.433120400946e+00 > 1 KSP unpreconditioned resid norm 1.433120400946e+00 true resid norm > 1.433120400946e+00 ||r(i)||/||b|| 6.370197677051e-01 > 2 KSP Residual norm 1.169262560123e+00 > 2 KSP unpreconditioned resid norm 1.169262560123e+00 true resid norm > 1.169262560123e+00 ||r(i)||/||b|| 5.197353718108e-01 > 3 KSP Residual norm 1.323528716607e+00 > 3 KSP unpreconditioned resid norm 1.323528716607e+00 true resid norm > 1.323528716607e+00 ||r(i)||/||b|| 5.883064361148e-01 > 4 KSP Residual norm 5.006323254234e-01 > 4 KSP unpreconditioned resid norm 5.006323254234e-01 true resid norm > 5.006323254234e-01 ||r(i)||/||b|| 2.225302824775e-01 > 5 KSP Residual norm 3.569836784785e-01 > 5 KSP unpreconditioned resid norm 3.569836784785e-01 true resid norm > 3.569836784785e-01 ||r(i)||/||b|| 1.586786844906e-01 > 6 KSP Residual norm 2.493182937513e-01 > 6 KSP unpreconditioned resid norm 2.493182937513e-01 true resid norm > 2.493182937513e-01 ||r(i)||/||b|| 1.108215900529e-01 > 7 KSP Residual norm 3.038202502298e-01 > 7 KSP unpreconditioned resid norm 3.038202502298e-01 true resid norm > 3.038202502298e-01 ||r(i)||/||b|| 1.350476241198e-01 > 8 KSP Residual norm 2.780214194402e-01 > 8 KSP unpreconditioned resid norm 2.780214194402e-01 true resid norm > 2.780214194402e-01 ||r(i)||/||b|| 1.235800843473e-01 > 9 KSP Residual norm 1.676826341491e-01 > 9 KSP unpreconditioned resid norm 1.676826341491e-01 true resid norm > 1.676826341491e-01 ||r(i)||/||b|| 7.453466755710e-02 > 10 KSP Residual norm 1.209985378713e-01 > 10 KSP unpreconditioned resid norm 1.209985378713e-01 true resid norm > 1.209985378713e-01 ||r(i)||/||b|| 5.378366007245e-02 > 11 KSP Residual norm 9.445076689969e-02 > 11 KSP unpreconditioned resid norm 9.445076689969e-02 true resid norm > 9.445076689969e-02 ||r(i)||/||b|| 4.198321756516e-02 > 12 KSP Residual norm 8.308555284580e-02 > 12 KSP unpreconditioned resid norm 8.308555284580e-02 true resid norm > 8.308555284580e-02 ||r(i)||/||b|| 3.693139776569e-02 > 13 KSP Residual norm 5.472865592585e-02 > 13 KSP unpreconditioned resid norm 5.472865592585e-02 true resid norm > 5.472865592585e-02 ||r(i)||/||b|| 2.432680161532e-02 > 14 KSP Residual norm 4.357870564398e-02 > 14 KSP unpreconditioned resid norm 4.357870564398e-02 true resid norm > 4.357870564398e-02 ||r(i)||/||b|| 1.937066622447e-02 > 15 KSP Residual norm 5.079681292439e-02 > 15 KSP unpreconditioned resid norm 5.079681292439e-02 true resid norm > 5.079681292439e-02 ||r(i)||/||b|| 2.257910357558e-02 > Linear mg_levels_1_ solve converged due to CONVERGED_ITS iterations 15 > Residual norms for mg_levels_1_ solve. > 0 KSP Residual norm 5.079681292439e-02 > Residual norms for mg_levels_1_ solve. > 0 KSP unpreconditioned resid norm 5.079681292439e-02 true resid norm > 5.079681292439e-02 ||r(i)||/||b|| 2.257910357559e-02 > 1 KSP Residual norm 2.934938644003e-02 > 1 KSP unpreconditioned resid norm 2.934938644003e-02 true resid norm > 2.934938644003e-02 ||r(i)||/||b|| 1.304575618348e-02 > 2 KSP Residual norm 3.257065831294e-02 > 2 KSP unpreconditioned resid norm 3.257065831294e-02 true resid norm > 3.257065831294e-02 ||r(i)||/||b|| 1.447760647243e-02 > 3 KSP Residual norm 4.143063876867e-02 > 3 KSP unpreconditioned resid norm 4.143063876867e-02 true resid norm > 4.143063876867e-02 ||r(i)||/||b|| 1.841585387164e-02 > 4 KSP Residual norm 4.822471409489e-02 > 4 KSP unpreconditioned resid norm 4.822471409489e-02 true resid norm > 4.822471409489e-02 ||r(i)||/||b|| 2.143580968499e-02 > 5 KSP Residual norm 3.197538246153e-02 > 5 KSP unpreconditioned resid norm 3.197538246153e-02 true resid norm > 3.197538246153e-02 ||r(i)||/||b|| 1.421300729127e-02 > 6 KSP Residual norm 3.461217019835e-02 > 6 KSP unpreconditioned resid norm 3.461217019835e-02 true resid norm > 3.461217019835e-02 ||r(i)||/||b|| 1.538505529958e-02 > 7 KSP Residual norm 3.410193775327e-02 > 7 KSP unpreconditioned resid norm 3.410193775327e-02 true resid norm > 3.410193775327e-02 ||r(i)||/||b|| 1.515825777899e-02 > 8 KSP Residual norm 4.690424294464e-02 > 8 KSP unpreconditioned resid norm 4.690424294464e-02 true resid norm > 4.690424294464e-02 ||r(i)||/||b|| 2.084886233233e-02 > 9 KSP Residual norm 3.366148892800e-02 > 9 KSP unpreconditioned resid norm 3.366148892800e-02 true resid norm > 3.366148892800e-02 ||r(i)||/||b|| 1.496247896783e-02 > 10 KSP Residual norm 4.068015727689e-02 > 10 KSP unpreconditioned resid norm 4.068015727689e-02 true resid norm > 4.068015727689e-02 ||r(i)||/||b|| 1.808226602707e-02 > 11 KSP Residual norm 2.658836123104e-02 > 11 KSP unpreconditioned resid norm 2.658836123104e-02 true resid norm > 2.658836123104e-02 ||r(i)||/||b|| 1.181848481389e-02 > 12 KSP Residual norm 2.826244186003e-02 > 12 KSP unpreconditioned resid norm 2.826244186003e-02 true resid norm > 2.826244186003e-02 ||r(i)||/||b|| 1.256261102456e-02 > 13 KSP Residual norm 2.981793619508e-02 > 13 KSP unpreconditioned resid norm 2.981793619508e-02 true resid norm > 2.981793619508e-02 ||r(i)||/||b|| 1.325402581380e-02 > 14 KSP Residual norm 3.525455091450e-02 > 14 KSP unpreconditioned resid norm 3.525455091450e-02 true resid norm > 3.525455091450e-02 ||r(i)||/||b|| 1.567059251914e-02 > 15 KSP Residual norm 2.331539121838e-02 > 15 KSP unpreconditioned resid norm 2.331539121838e-02 true resid norm > 2.331539121838e-02 ||r(i)||/||b|| 1.036365478300e-02 > Linear mg_levels_1_ solve converged due to CONVERGED_ITS iterations 15 > Residual norms for mg_levels_1_ solve. > 0 KSP Residual norm 2.421498365806e-02 > Residual norms for mg_levels_1_ solve. > 0 KSP unpreconditioned resid norm 2.421498365806e-02 true resid norm > 2.421498365806e-02 ||r(i)||/||b|| 1.000000000000e+00 > 1 KSP Residual norm 1.761072112362e-02 > 1 KSP unpreconditioned resid norm 1.761072112362e-02 true resid norm > 1.761072112362e-02 ||r(i)||/||b|| 7.272654556492e-01 > 2 KSP Residual norm 1.400842489042e-02 > 2 KSP unpreconditioned resid norm 1.400842489042e-02 true resid norm > 1.400842489042e-02 ||r(i)||/||b|| 5.785023474818e-01 > 3 KSP Residual norm 1.419665483348e-02 > 3 KSP unpreconditioned resid norm 1.419665483348e-02 true resid norm > 1.419665483348e-02 ||r(i)||/||b|| 5.862756314004e-01 > 4 KSP Residual norm 1.617590701667e-02 > 4 KSP unpreconditioned resid norm 1.617590701667e-02 true resid norm > 1.617590701667e-02 ||r(i)||/||b|| 6.680123036665e-01 > 5 KSP Residual norm 1.354824081005e-02 > 5 KSP unpreconditioned resid norm 1.354824081005e-02 true resid norm > 1.354824081005e-02 ||r(i)||/||b|| 5.594982429624e-01 > 6 KSP Residual norm 1.387252917475e-02 > 6 KSP unpreconditioned resid norm 1.387252917475e-02 true resid norm > 1.387252917475e-02 ||r(i)||/||b|| 5.728902967950e-01 > 7 KSP Residual norm 1.514043102087e-02 > 7 KSP unpreconditioned resid norm 1.514043102087e-02 true resid norm > 1.514043102087e-02 ||r(i)||/||b|| 6.252505157414e-01 > 8 KSP Residual norm 1.275811124745e-02 > 8 KSP unpreconditioned resid norm 1.275811124745e-02 true resid norm > 1.275811124745e-02 ||r(i)||/||b|| 5.268684640721e-01 > 9 KSP Residual norm 1.241039155981e-02 > 9 KSP unpreconditioned resid norm 1.241039155981e-02 true resid norm > 1.241039155981e-02 ||r(i)||/||b|| 5.125087728764e-01 > 10 KSP Residual norm 9.585207801652e-03 > 10 KSP unpreconditioned resid norm 9.585207801652e-03 true resid norm > 9.585207801652e-03 ||r(i)||/||b|| 3.958378802565e-01 > 11 KSP Residual norm 9.022641230732e-03 > 11 KSP unpreconditioned resid norm 9.022641230732e-03 true resid norm > 9.022641230732e-03 ||r(i)||/||b|| 3.726057121550e-01 > 12 KSP Residual norm 1.187709152046e-02 > 12 KSP unpreconditioned resid norm 1.187709152046e-02 true resid norm > 1.187709152046e-02 ||r(i)||/||b|| 4.904852172597e-01 > 13 KSP Residual norm 1.084880112494e-02 > 13 KSP unpreconditioned resid norm 1.084880112494e-02 true resid norm > 1.084880112494e-02 ||r(i)||/||b|| 4.480201712351e-01 > 14 KSP Residual norm 8.194750346781e-03 > 14 KSP unpreconditioned resid norm 8.194750346781e-03 true resid norm > 8.194750346781e-03 ||r(i)||/||b|| 3.384165136140e-01 > 15 KSP Residual norm 7.614246199165e-03 > 15 KSP unpreconditioned resid norm 7.614246199165e-03 true resid norm > 7.614246199165e-03 ||r(i)||/||b|| 3.144435819857e-01 > Linear mg_levels_1_ solve converged due to CONVERGED_ITS iterations 15 > Residual norms for mg_levels_1_ solve. > 0 KSP Residual norm 7.614246199165e-03 > Residual norms for mg_levels_1_ solve. > 0 KSP unpreconditioned resid norm 7.614246199165e-03 true resid norm > 7.614246199165e-03 ||r(i)||/||b|| 3.144435819857e-01 > 1 KSP Residual norm 5.620014684145e-03 > 1 KSP unpreconditioned resid norm 5.620014684145e-03 true resid norm > 5.620014684145e-03 ||r(i)||/||b|| 2.320883120759e-01 > 2 KSP Residual norm 6.643368363907e-03 > 2 KSP unpreconditioned resid norm 6.643368363907e-03 true resid norm > 6.643368363907e-03 ||r(i)||/||b|| 2.743494878096e-01 > 3 KSP Residual norm 8.708642393659e-03 > 3 KSP unpreconditioned resid norm 8.708642393659e-03 true resid norm > 8.708642393659e-03 ||r(i)||/||b|| 3.596385823189e-01 > 4 KSP Residual norm 6.401852907459e-03 > 4 KSP unpreconditioned resid norm 6.401852907459e-03 true resid norm > 6.401852907459e-03 ||r(i)||/||b|| 2.643756856440e-01 > 5 KSP Residual norm 7.230576215262e-03 > 5 KSP unpreconditioned resid norm 7.230576215262e-03 true resid norm > 7.230576215262e-03 ||r(i)||/||b|| 2.985992605803e-01 > 6 KSP Residual norm 6.204081601285e-03 > 6 KSP unpreconditioned resid norm 6.204081601285e-03 true resid norm > 6.204081601285e-03 ||r(i)||/||b|| 2.562083744880e-01 > 7 KSP Residual norm 7.038656665944e-03 > 7 KSP unpreconditioned resid norm 7.038656665944e-03 true resid norm > 7.038656665944e-03 ||r(i)||/||b|| 2.906736079337e-01 > 8 KSP Residual norm 7.194079694050e-03 > 8 KSP unpreconditioned resid norm 7.194079694050e-03 true resid norm > 7.194079694050e-03 ||r(i)||/||b|| 2.970920730585e-01 > 9 KSP Residual norm 6.353576889135e-03 > 9 KSP unpreconditioned resid norm 6.353576889135e-03 true resid norm > 6.353576889135e-03 ||r(i)||/||b|| 2.623820432363e-01 > 10 KSP Residual norm 7.313589502731e-03 > 10 KSP unpreconditioned resid norm 7.313589502731e-03 true resid norm > 7.313589502731e-03 ||r(i)||/||b|| 3.020274391264e-01 > 11 KSP Residual norm 6.643320423193e-03 > 11 KSP unpreconditioned resid norm 6.643320423193e-03 true resid norm > 6.643320423193e-03 ||r(i)||/||b|| 2.743475080142e-01 > 12 KSP Residual norm 7.235443182108e-03 > 12 KSP unpreconditioned resid norm 7.235443182108e-03 true resid norm > 7.235443182108e-03 ||r(i)||/||b|| 2.988002504681e-01 > 13 KSP Residual norm 4.971292307201e-03 > 13 KSP unpreconditioned resid norm 4.971292307201e-03 true resid norm > 4.971292307201e-03 ||r(i)||/||b|| 2.052981896416e-01 > 14 KSP Residual norm 5.357933842147e-03 > 14 KSP unpreconditioned resid norm 5.357933842147e-03 true resid norm > 5.357933842147e-03 ||r(i)||/||b|| 2.212652264320e-01 > 15 KSP Residual norm 5.841682994497e-03 > 15 KSP unpreconditioned resid norm 5.841682994497e-03 true resid norm > 5.841682994497e-03 ||r(i)||/||b|| 2.412424917146e-01 > Linear mg_levels_1_ solve converged due to CONVERGED_ITS iterations 15 > Cheers, > Elena > From: Barry Smith <[email protected] <mailto:[email protected]>> > Sent: 29 September 2025 20:31:26 > To: Moral Sanchez, Elena > Cc: Mark Adams; petsc-users > Subject: Re: [petsc-users] setting correct tolerances for MG smoother CG at > the finest level > > > Thanks. I missed something earlier in the KSPView > >>> using UNPRECONDITIONED norm type for convergence test > > Please add the options > >>>>> -ksp_monitor_true_residual -mg_levels_ksp_monitor_true_residual > > It is using the unpreconditioned residual norms for convergence testing but > we are printing the preconditioned norms. > > Barry > > >> On Sep 29, 2025, at 11:12 AM, Moral Sanchez, Elena >> <[email protected] <mailto:[email protected]>> >> wrote: >> >> This is the output: >> Residual norms for mg_levels_1_ solve. >> 0 KSP Residual norm 2.249726733143e+00 >> 1 KSP Residual norm 1.433120400946e+00 >> 2 KSP Residual norm 1.169262560123e+00 >> 3 KSP Residual norm 1.323528716607e+00 >> 4 KSP Residual norm 5.006323254234e-01 >> 5 KSP Residual norm 3.569836784785e-01 >> 6 KSP Residual norm 2.493182937513e-01 >> 7 KSP Residual norm 3.038202502298e-01 >> 8 KSP Residual norm 2.780214194402e-01 >> 9 KSP Residual norm 1.676826341491e-01 >> 10 KSP Residual norm 1.209985378713e-01 >> 11 KSP Residual norm 9.445076689969e-02 >> 12 KSP Residual norm 8.308555284580e-02 >> 13 KSP Residual norm 5.472865592585e-02 >> 14 KSP Residual norm 4.357870564398e-02 >> 15 KSP Residual norm 5.079681292439e-02 >> Linear mg_levels_1_ solve converged due to CONVERGED_ITS iterations 15 >> Residual norms for mg_levels_1_ solve. >> 0 KSP Residual norm 5.079681292439e-02 >> 1 KSP Residual norm 2.934938644003e-02 >> 2 KSP Residual norm 3.257065831294e-02 >> 3 KSP Residual norm 4.143063876867e-02 >> 4 KSP Residual norm 4.822471409489e-02 >> 5 KSP Residual norm 3.197538246153e-02 >> 6 KSP Residual norm 3.461217019835e-02 >> 7 KSP Residual norm 3.410193775327e-02 >> 8 KSP Residual norm 4.690424294464e-02 >> 9 KSP Residual norm 3.366148892800e-02 >> 10 KSP Residual norm 4.068015727689e-02 >> 11 KSP Residual norm 2.658836123104e-02 >> 12 KSP Residual norm 2.826244186003e-02 >> 13 KSP Residual norm 2.981793619508e-02 >> 14 KSP Residual norm 3.525455091450e-02 >> 15 KSP Residual norm 2.331539121838e-02 >> Linear mg_levels_1_ solve converged due to CONVERGED_ITS iterations 15 >> Residual norms for mg_levels_1_ solve. >> 0 KSP Residual norm 2.421498365806e-02 >> 1 KSP Residual norm 1.761072112362e-02 >> 2 KSP Residual norm 1.400842489042e-02 >> 3 KSP Residual norm 1.419665483348e-02 >> 4 KSP Residual norm 1.617590701667e-02 >> 5 KSP Residual norm 1.354824081005e-02 >> 6 KSP Residual norm 1.387252917475e-02 >> 7 KSP Residual norm 1.514043102087e-02 >> 8 KSP Residual norm 1.275811124745e-02 >> 9 KSP Residual norm 1.241039155981e-02 >> 10 KSP Residual norm 9.585207801652e-03 >> 11 KSP Residual norm 9.022641230732e-03 >> 12 KSP Residual norm 1.187709152046e-02 >> 13 KSP Residual norm 1.084880112494e-02 >> 14 KSP Residual norm 8.194750346781e-03 >> 15 KSP Residual norm 7.614246199165e-03 >> Linear mg_levels_1_ solve converged due to CONVERGED_ITS iterations 15 >> Residual norms for mg_levels_1_ solve. >> 0 KSP Residual norm 7.614246199165e-03 >> 1 KSP Residual norm 5.620014684145e-03 >> 2 KSP Residual norm 6.643368363907e-03 >> 3 KSP Residual norm 8.708642393659e-03 >> 4 KSP Residual norm 6.401852907459e-03 >> 5 KSP Residual norm 7.230576215262e-03 >> 6 KSP Residual norm 6.204081601285e-03 >> 7 KSP Residual norm 7.038656665944e-03 >> 8 KSP Residual norm 7.194079694050e-03 >> 9 KSP Residual norm 6.353576889135e-03 >> 10 KSP Residual norm 7.313589502731e-03 >> 11 KSP Residual norm 6.643320423193e-03 >> 12 KSP Residual norm 7.235443182108e-03 >> 13 KSP Residual norm 4.971292307201e-03 >> 14 KSP Residual norm 5.357933842147e-03 >> 15 KSP Residual norm 5.841682994497e-03 >> Linear mg_levels_1_ solve converged due to CONVERGED_ITS iterations 15 >> >> From: Barry Smith <[email protected] <mailto:[email protected]>> >> Sent: 29 September 2025 15:56:33 >> To: Moral Sanchez, Elena >> Cc: Mark Adams; petsc-users >> Subject: Re: [petsc-users] setting correct tolerances for MG smoother CG at >> the finest level >> >> >> I asked you to run with >> >>>>> -ksp_monitor -mg_levels_ksp_monitor -ksp_converged_reason >>>>> -mg_levels_ksp_converged_reason >> >> you chose not to, delaying the process of understanding what is happening. >> >> Please run with those options and send the output. My guess is that you >> are computing the "residual norms" in your own monitor code, and it is doing >> so differently than what PETSc does, thus resulting in the appearance of a >> sufficiently small residual norm, whereas PETSc may not have calculated >> something that small. >> >> Barry >> >> >>> On Sep 29, 2025, at 8:39 AM, Moral Sanchez, Elena >>> <[email protected] <mailto:[email protected]>> >>> wrote: >>> >>> Thanks for the hint. I agree that the coarse solve should be much more >>> "accurate". However, for the moment I am just trying to understand what the >>> MG is doing exactly. >>> >>> I am puzzled to see that the fine grid smoother ("lvl 0") does not stop >>> when the residual becomes less than 1e-1. It should converge due to the >>> atol. >>> >>> From: Mark Adams <[email protected] <mailto:[email protected]>> >>> Sent: 29 September 2025 14:20:56 >>> To: Moral Sanchez, Elena >>> Cc: Barry Smith; petsc-users >>> Subject: Re: [petsc-users] setting correct tolerances for MG smoother CG at >>> the finest level >>> >>> Oh I see the coarse grid solver in your full solver output now. >>> You still want an accurate coarse grid solve. Usually (the default in GAMG) >>> you use a direct solver on one process, and cousin until the coarse grid is >>> small enough to make that cheap. >>> >>> On Mon, Sep 29, 2025 at 8:07 AM Moral Sanchez, Elena >>> <[email protected] <mailto:[email protected]>> >>> wrote: >>>> Hi, I doubled the system size and changed the tolerances just to show a >>>> better example of the problem. This is the output of the callbacks in the >>>> first iteration: >>>> CG Iter 0/1 | res = 2.25e+00/1.00e-09 | 0.1 s >>>> MG lvl 0 (s=884): CG Iter 0/15 | res = 2.25e+00/1.00e-01 | 0.3 s >>>> MG lvl 0 (s=884): CG Iter 1/15 | res = 1.43e+00/1.00e-01 | 0.2 s >>>> MG lvl 0 (s=884): CG Iter 2/15 | res = 1.17e+00/1.00e-01 | 0.2 s >>>> MG lvl 0 (s=884): CG Iter 3/15 | res = 1.32e+00/1.00e-01 | 0.1 s >>>> MG lvl 0 (s=884): CG Iter 4/15 | res = 5.01e-01/1.00e-01 | 0.2 s >>>> MG lvl 0 (s=884): CG Iter 5/15 | res = 3.57e-01/1.00e-01 | 0.2 s >>>> MG lvl 0 (s=884): CG Iter 6/15 | res = 2.49e-01/1.00e-01 | 0.2 s >>>> MG lvl 0 (s=884): CG Iter 7/15 | res = 3.04e-01/1.00e-01 | 0.2 s >>>> MG lvl 0 (s=884): CG Iter 8/15 | res = 2.78e-01/1.00e-01 | 0.2 s >>>> MG lvl 0 (s=884): CG Iter 9/15 | res = 1.68e-01/1.00e-01 | 0.2 s >>>> MG lvl 0 (s=884): CG Iter 10/15 | res = 1.21e-01/1.00e-01 | 0.1 s >>>> MG lvl 0 (s=884): CG Iter 11/15 | res = 9.45e-02/1.00e-01 | 0.2 s >>>> MG lvl 0 (s=884): CG Iter 12/15 | res = 8.31e-02/1.00e-01 | 0.2 s >>>> MG lvl 0 (s=884): CG Iter 13/15 | res = 5.47e-02/1.00e-01 | 0.2 s >>>> MG lvl 0 (s=884): CG Iter 14/15 | res = 4.36e-02/1.00e-01 | 0.2 s >>>> MG lvl 0 (s=884): CG Iter 15/15 | res = 5.08e-02/1.00e-01 | 0.1 s >>>> ConvergedReason MG lvl 0: 4 >>>> MG lvl -1 (s=524): CG Iter 0/15 | res = 8.15e-02/1.00e-01 | 3.0 s >>>> ConvergedReason MG lvl -1: 3 >>>> MG lvl 0 (s=884): CG Iter 0/15 | res = 5.08e-02/1.00e-01 | 0.3 s >>>> MG lvl 0 (s=884): CG Iter 1/15 | res = 2.93e-02/1.00e-01 | 0.2 s >>>> MG lvl 0 (s=884): CG Iter 2/15 | res = 3.26e-02/1.00e-01 | 0.2 s >>>> MG lvl 0 (s=884): CG Iter 3/15 | res = 4.14e-02/1.00e-01 | 0.2 s >>>> MG lvl 0 (s=884): CG Iter 4/15 | res = 4.82e-02/1.00e-01 | 0.2 s >>>> MG lvl 0 (s=884): CG Iter 5/15 | res = 3.20e-02/1.00e-01 | 0.2 s >>>> MG lvl 0 (s=884): CG Iter 6/15 | res = 3.46e-02/1.00e-01 | 0.3 s >>>> MG lvl 0 (s=884): CG Iter 7/15 | res = 3.41e-02/1.00e-01 | 0.2 s >>>> MG lvl 0 (s=884): CG Iter 8/15 | res = 4.69e-02/1.00e-01 | 0.2 s >>>> MG lvl 0 (s=884): CG Iter 9/15 | res = 3.37e-02/1.00e-01 | 0.2 s >>>> MG lvl 0 (s=884): CG Iter 10/15 | res = 4.07e-02/1.00e-01 | 0.2 s >>>> MG lvl 0 (s=884): CG Iter 11/15 | res = 2.66e-02/1.00e-01 | 0.1 s >>>> MG lvl 0 (s=884): CG Iter 12/15 | res = 2.83e-02/1.00e-01 | 0.1 s >>>> MG lvl 0 (s=884): CG Iter 13/15 | res = 2.98e-02/1.00e-01 | 0.2 s >>>> MG lvl 0 (s=884): CG Iter 14/15 | res = 3.53e-02/1.00e-01 | 0.1 s >>>> MG lvl 0 (s=884): CG Iter 15/15 | res = 2.33e-02/1.00e-01 | 0.2 s >>>> ConvergedReason MG lvl 0: 4 >>>> CG Iter 1/1 | res = 2.42e-02/1.00e-09 | 5.6 s >>>> MG lvl 0 (s=884): CG Iter 0/15 | res = 2.42e-02/1.00e-01 | 0.2 s >>>> MG lvl 0 (s=884): CG Iter 1/15 | res = 1.76e-02/1.00e-01 | 0.2 s >>>> MG lvl 0 (s=884): CG Iter 2/15 | res = 1.40e-02/1.00e-01 | 0.2 s >>>> MG lvl 0 (s=884): CG Iter 3/15 | res = 1.42e-02/1.00e-01 | 0.1 s >>>> MG lvl 0 (s=884): CG Iter 4/15 | res = 1.62e-02/1.00e-01 | 0.2 s >>>> MG lvl 0 (s=884): CG Iter 5/15 | res = 1.35e-02/1.00e-01 | 0.1 s >>>> MG lvl 0 (s=884): CG Iter 6/15 | res = 1.39e-02/1.00e-01 | 0.1 s >>>> MG lvl 0 (s=884): CG Iter 7/15 | res = 1.51e-02/1.00e-01 | 0.2 s >>>> MG lvl 0 (s=884): CG Iter 8/15 | res = 1.28e-02/1.00e-01 | 0.2 s >>>> MG lvl 0 (s=884): CG Iter 9/15 | res = 1.24e-02/1.00e-01 | 0.2 s >>>> MG lvl 0 (s=884): CG Iter 10/15 | res = 9.59e-03/1.00e-01 | 0.1 s >>>> MG lvl 0 (s=884): CG Iter 11/15 | res = 9.02e-03/1.00e-01 | 0.1 s >>>> MG lvl 0 (s=884): CG Iter 12/15 | res = 1.19e-02/1.00e-01 | 0.1 s >>>> MG lvl 0 (s=884): CG Iter 13/15 | res = 1.08e-02/1.00e-01 | 0.1 s >>>> MG lvl 0 (s=884): CG Iter 14/15 | res = 8.19e-03/1.00e-01 | 0.1 s >>>> MG lvl 0 (s=884): CG Iter 15/15 | res = 7.61e-03/1.00e-01 | 0.1 s >>>> ConvergedReason MG lvl 0: 4 >>>> MG lvl -1 (s=524): CG Iter 0/15 | res = 1.38e-02/1.00e-01 | 5.2 s >>>> ConvergedReason MG lvl -1: 3 >>>> MG lvl 0 (s=884): CG Iter 0/15 | res = 7.61e-03/1.00e-01 | 0.2 s >>>> MG lvl 0 (s=884): CG Iter 1/15 | res = 5.62e-03/1.00e-01 | 0.1 s >>>> MG lvl 0 (s=884): CG Iter 2/15 | res = 6.64e-03/1.00e-01 | 0.1 s >>>> MG lvl 0 (s=884): CG Iter 3/15 | res = 8.71e-03/1.00e-01 | 0.1 s >>>> MG lvl 0 (s=884): CG Iter 4/15 | res = 6.40e-03/1.00e-01 | 0.1 s >>>> MG lvl 0 (s=884): CG Iter 5/15 | res = 7.23e-03/1.00e-01 | 0.1 s >>>> MG lvl 0 (s=884): CG Iter 6/15 | res = 6.20e-03/1.00e-01 | 0.1 s >>>> MG lvl 0 (s=884): CG Iter 7/15 | res = 7.04e-03/1.00e-01 | 0.1 s >>>> MG lvl 0 (s=884): CG Iter 8/15 | res = 7.19e-03/1.00e-01 | 0.1 s >>>> MG lvl 0 (s=884): CG Iter 9/15 | res = 6.35e-03/1.00e-01 | 0.1 s >>>> MG lvl 0 (s=884): CG Iter 10/15 | res = 7.31e-03/1.00e-01 | 0.1 s >>>> MG lvl 0 (s=884): CG Iter 11/15 | res = 6.64e-03/1.00e-01 | 0.1 s >>>> MG lvl 0 (s=884): CG Iter 12/15 | res = 7.24e-03/1.00e-01 | 0.1 s >>>> MG lvl 0 (s=884): CG Iter 13/15 | res = 4.97e-03/1.00e-01 | 0.1 s >>>> MG lvl 0 (s=884): CG Iter 14/15 | res = 5.36e-03/1.00e-01 | 0.1 s >>>> MG lvl 0 (s=884): CG Iter 15/15 | res = 5.84e-03/1.00e-01 | 0.1 s >>>> ConvergedReason MG lvl 0: 4 >>>> CG ConvergedReason: -3 >>>> >>>> For completeness, I add here the -ksp_view of the whole solver: >>>> KSP Object: 1 MPI process >>>> type: cg >>>> variant HERMITIAN >>>> maximum iterations=1, nonzero initial guess >>>> tolerances: relative=1e-08, absolute=1e-09, divergence=10000. >>>> left preconditioning >>>> using UNPRECONDITIONED norm type for convergence test >>>> PC Object: 1 MPI process >>>> type: mg >>>> type is MULTIPLICATIVE, levels=2 cycles=v >>>> Cycles per PCApply=1 >>>> Not using Galerkin computed coarse grid matrices >>>> Coarse grid solver -- level 0 ------------------------------- >>>> KSP Object: (mg_coarse_) 1 MPI process >>>> type: cg >>>> variant HERMITIAN >>>> maximum iterations=15, nonzero initial guess >>>> tolerances: relative=0.1, absolute=0.1, divergence=1e+30 >>>> left preconditioning >>>> using UNPRECONDITIONED norm type for convergence test >>>> PC Object: (mg_coarse_) 1 MPI process >>>> type: none >>>> linear system matrix = precond matrix: >>>> Mat Object: 1 MPI process >>>> type: python >>>> rows=524, cols=524 >>>> Python: Solver_petsc.LeastSquaresOperator >>>> Down solver (pre-smoother) on level 1 ------------------------------- >>>> KSP Object: (mg_levels_1_) 1 MPI process >>>> type: cg >>>> variant HERMITIAN >>>> maximum iterations=15, nonzero initial guess >>>> tolerances: relative=0.1, absolute=0.1, divergence=1e+30 >>>> left preconditioning >>>> using UNPRECONDITIONED norm type for convergence test >>>> PC Object: (mg_levels_1_) 1 MPI process >>>> type: none >>>> linear system matrix = precond matrix: >>>> Mat Object: 1 MPI process >>>> type: python >>>> rows=884, cols=884 >>>> Python: Solver_petsc.LeastSquaresOperator >>>> Up solver (post-smoother) same as down solver (pre-smoother) >>>> linear system matrix = precond matrix: >>>> Mat Object: 1 MPI process >>>> type: python >>>> rows=884, cols=884 >>>> Python: Solver_petsc.LeastSquaresOperator >>>> >>>> Regarding Mark's Email: What do you mean with "the whole solver doesn't >>>> have a coarse grid"? I am using my own Restriction and Interpolation >>>> operators. >>>> Thanks for the help, >>>> Elena >>>> >>>> From: Mark Adams <[email protected] <mailto:[email protected]>> >>>> Sent: 28 September 2025 20:13:54 >>>> To: Barry Smith >>>> Cc: Moral Sanchez, Elena; petsc-users >>>> Subject: Re: [petsc-users] setting correct tolerances for MG smoother CG >>>> at the finest level >>>> >>>> Not sure why your "whole"solver does not have a coarse grid but this is >>>> wrong: >>>> >>>>> KSP Object: (mg_coarse_) 1 MPI process >>>>> type: cg >>>>> variant HERMITIAN >>>>> maximum iterations=100, initial guess is zero >>>>> tolerances: relative=0.1, absolute=0.1, divergence=1e+30 >>>>> >>>>> The coarse grid has to be accurate. The defaults are a good place to >>>>> start: max_it=10.000, rtol=1e-5, atol=1e-30 (ish) >>>> >>>> On Fri, Sep 26, 2025 at 3:21 PM Barry Smith <[email protected] >>>> <mailto:[email protected]>> wrote: >>>>> Looks reasonable. Send the output running with >>>>> >>>>> -ksp_monitor -mg_levels_ksp_monitor -ksp_converged_reason >>>>> -mg_levels_ksp_converged_reason >>>>> >>>>>> On Sep 26, 2025, at 1:19 PM, Moral Sanchez, Elena >>>>>> <[email protected] <mailto:[email protected]>> >>>>>> wrote: >>>>>> >>>>>> Dear Barry, >>>>>> >>>>>> This is -ksp_view for the smoother at the finest level: >>>>>> KSP Object: (mg_levels_1_) 1 MPI process >>>>>> type: cg >>>>>> variant HERMITIAN >>>>>> maximum iterations=10, nonzero initial guess >>>>>> tolerances: relative=0.1, absolute=0.1, divergence=1e+30 >>>>>> left preconditioning >>>>>> using UNPRECONDITIONED norm type for convergence test >>>>>> PC Object: (mg_levels_1_) 1 MPI process >>>>>> type: none >>>>>> linear system matrix = precond matrix: >>>>>> Mat Object: 1 MPI process >>>>>> type: python >>>>>> rows=524, cols=524 >>>>>> Python: Solver_petsc.LeastSquaresOperator >>>>>> And at the coarsest level: >>>>>> KSP Object: (mg_coarse_) 1 MPI process >>>>>> type: cg >>>>>> variant HERMITIAN >>>>>> maximum iterations=100, initial guess is zero >>>>>> tolerances: relative=0.1, absolute=0.1, divergence=1e+30 >>>>>> left preconditioning >>>>>> using UNPRECONDITIONED norm type for convergence test >>>>>> PC Object: (mg_coarse_) 1 MPI process >>>>>> type: none >>>>>> linear system matrix = precond matrix: >>>>>> Mat Object: 1 MPI process >>>>>> type: python >>>>>> rows=344, cols=344 >>>>>> Python: Solver_petsc.LeastSquaresOperator >>>>>> And for the whole solver: >>>>>> KSP Object: 1 MPI process >>>>>> type: cg >>>>>> variant HERMITIAN >>>>>> maximum iterations=100, nonzero initial guess >>>>>> tolerances: relative=1e-08, absolute=1e-09, divergence=10000. >>>>>> left preconditioning >>>>>> using UNPRECONDITIONED norm type for convergence test >>>>>> PC Object: 1 MPI process >>>>>> type: mg >>>>>> type is MULTIPLICATIVE, levels=2 cycles=v >>>>>> Cycles per PCApply=1 >>>>>> Not using Galerkin computed coarse grid matrices >>>>>> Coarse grid solver -- level 0 ------------------------------- >>>>>> KSP Object: (mg_coarse_) 1 MPI process >>>>>> type: cg >>>>>> variant HERMITIAN >>>>>> maximum iterations=100, initial guess is zero >>>>>> tolerances: relative=0.1, absolute=0.1, divergence=1e+30 >>>>>> left preconditioning >>>>>> using UNPRECONDITIONED norm type for convergence test >>>>>> PC Object: (mg_coarse_) 1 MPI process >>>>>> type: none >>>>>> linear system matrix = precond matrix: >>>>>> Mat Object: 1 MPI process >>>>>> type: python >>>>>> rows=344, cols=344 >>>>>> Python: Solver_petsc.LeastSquaresOperator >>>>>> Down solver (pre-smoother) on level 1 ------------------------------- >>>>>> KSP Object: (mg_levels_1_) 1 MPI process >>>>>> type: cg >>>>>> variant HERMITIAN >>>>>> maximum iterations=10, nonzero initial guess >>>>>> tolerances: relative=0.1, absolute=0.1, divergence=1e+30 >>>>>> left preconditioning >>>>>> using UNPRECONDITIONED norm type for convergence test >>>>>> PC Object: (mg_levels_1_) 1 MPI process >>>>>> type: none >>>>>> linear system matrix = precond matrix: >>>>>> Mat Object: 1 MPI process >>>>>> type: python >>>>>> rows=524, cols=524 >>>>>> Python: Solver_petsc.LeastSquaresOperator >>>>>> Up solver (post-smoother) same as down solver (pre-smoother) >>>>>> linear system matrix = precond matrix: >>>>>> Mat Object: 1 MPI process >>>>>> type: python >>>>>> rows=524, cols=524 >>>>>> Python: Solver_petsc.LeastSquaresOperator >>>>>> Best, >>>>>> Elena >>>>>> >>>>>> >>>>>> From: Barry Smith <[email protected] <mailto:[email protected]>> >>>>>> Sent: 26 September 2025 19:05:02 >>>>>> To: Moral Sanchez, Elena >>>>>> Cc: [email protected] <mailto:[email protected]> >>>>>> Subject: Re: [petsc-users] setting correct tolerances for MG smoother CG >>>>>> at the finest level >>>>>> >>>>>> >>>>>> Send the output using -ksp_view >>>>>> >>>>>> Normally one uses a fixed number of iterations of smoothing on level >>>>>> with multigrid rather than a tolerance, but yes PETSc should respect >>>>>> such a tolerance. >>>>>> >>>>>> Barry >>>>>> >>>>>> >>>>>>> On Sep 26, 2025, at 12:49 PM, Moral Sanchez, Elena >>>>>>> <[email protected] >>>>>>> <mailto:[email protected]>> wrote: >>>>>>> >>>>>>> Hi, >>>>>>> I am using multigrid (multiplicative) as a preconditioner with a >>>>>>> V-cycle of two levels. At each level, I am setting CG as the smoother >>>>>>> with certain tolerance. >>>>>>> >>>>>>> What I observe is that in the finest level the CG continues iterating >>>>>>> after the residual norm reaches the tolerance (atol) and it only stops >>>>>>> when reaching the maximum number of iterations at that level. At the >>>>>>> coarsest level this does not occur and the CG stops when the tolerance >>>>>>> is reached. >>>>>>> >>>>>>> I double-checked that the smoother at the finest level has the right >>>>>>> tolerance. And I am using a Monitor function to track the residual. >>>>>>> >>>>>>> Do you know how to make the smoother at the finest level stop when >>>>>>> reaching the tolerance? >>>>>>> >>>>>>> Cheers, >>>>>>> Elena.
