Dear authors, I tried -pc_type game -pc_gamg_parallel_coarse_grid_solver and -pc_type field split -pc_fieldsplit_detect_saddle_point -fieldsplit_0_ksp_type pronely -fieldsplit_0_pc_type game -fieldsplit_0_mg_coarse_pc_type sad -fieldsplit_1_ksp_type pronely -fieldsplit_1_pc_type Jacobi _fieldsplit_1_sub_pc_type for , both options got the KSP_DIVERGE_PC_FAILED error.
Thanks, Xiaofeng > On Jun 12, 2025, at 20:50, Mark Adams <mfad...@lbl.gov> wrote: > > > > On Thu, Jun 12, 2025 at 8:44 AM Matthew Knepley <knep...@gmail.com > <mailto:knep...@gmail.com>> wrote: >> On Thu, Jun 12, 2025 at 4:58 AM Mark Adams <mfad...@lbl.gov >> <mailto:mfad...@lbl.gov>> wrote: >>> Adding this to the PETSc mailing list, >>> >>> On Thu, Jun 12, 2025 at 3:43 AM hexioafeng <hexiaof...@buaa.edu.cn >>> <mailto:hexiaof...@buaa.edu.cn>> wrote: >>>> >>>> Dear Professor, >>>> >>>> I hope this message finds you well. >>>> >>>> I am an employee at a CAE company and a heavy user of the PETSc library. I >>>> would like to thank you for your contributions to PETSc and express my >>>> deep appreciation for your work. >>>> >>>> Recently, I encountered some difficulties when using PETSc to solve >>>> structural mechanics problems with Lagrange multiplier constraints. After >>>> searching extensively online and reviewing several papers, I found your >>>> previous paper titled "Algebraic multigrid methods for constrained linear >>>> systems with applications to contact problems in solid mechanics" seems to >>>> be the most relevant and helpful. >>>> >>>> The stiffness matrix I'm working with, K, is a block saddle-point matrix >>>> of the form (A00 A01; A10 0), where A00 is singular—just as described in >>>> your paper, and different from many other articles . I have a few >>>> questions regarding your work and would greatly appreciate your insights: >>>> >>>> 1. Is the AMG/KKT method presented in your paper available in PETSc? I >>>> tried using CG+GAMG directly but received a KSP_DIVERGED_PC_FAILED error. >>>> I also attempted to use CG+PCFIELDSPLIT with the following options: >>> >>> No >>> >>>> >>>> -pc_type fieldsplit -pc_fieldsplit_detect_saddle_point >>>> -pc_fieldsplit_type schur -pc_fieldsplit_schur_precondition selfp >>>> -pc_fieldsplit_schur_fact_type full -fieldsplit_0_ksp_type preonly >>>> -fieldsplit_0_pc_type gamg -fieldsplit_1_ksp_type preonly >>>> -fieldsplit_1_pc_type bjacobi >>>> >>>> Unfortunately, this also resulted in a KSP_DIVERGED_PC_FAILED error. Do >>>> you have any suggestions? >>>> >>>> 2. In your paper, you compare the method with Uzawa-type approaches. To my >>>> understanding, Uzawa methods typically require A00 to be invertible. How >>>> did you handle the singularity of A00 to construct an M-matrix that is >>>> invertible? >>>> >>> >>> You add a regularization term like A01 * A10 (like springs). See the paper >>> or any reference to augmented lagrange or Uzawa >>> >>> >>>> 3. Can i implement the AMG/KKT method in your paper using existing AMG >>>> APIs? Implementing a production-level AMG solver from scratch would be >>>> quite challenging for me, so I’m hoping to utilize existing AMG interfaces >>>> within PETSc or other packages. >>>> >>> >>> You can do Uzawa and make the regularization matrix with matrix-matrix >>> products. Just use AMG for the A00 block. >>> >>> >>>> 4. For saddle-point systems where A00 is singular, can you recommend any >>>> more robust or efficient solutions? Alternatively, are you aware of any >>>> open-source software packages that can handle such cases out-of-the-box? >>>> >>> >>> No, and I don't think PETSc can do this out-of-the-box, but others may be >>> able to give you a better idea of what PETSc can do. >>> I think PETSc can do Uzawa or other similar algorithms but it will not do >>> the regularization automatically (it is a bit more complicated than just >>> A01 * A10) >> >> One other trick you can use is to have >> >> -fieldsplit_0_mg_coarse_pc_type svd >> >> This will use SVD on the coarse grid of GAMG, which can handle the null >> space in A00 as long as the prolongation does not put it back in. I have >> used this for the Laplacian with Neumann conditions and for freely floating >> elastic problems. >> > > Good point. > You can also use -pc_gamg_parallel_coarse_grid_solver to get GAMG to use a on > level iterative solver for the coarse grid. > >> Thanks, >> >> Matt >> >>> Thanks, >>> Mark >>>> >>>> Thank you very much for taking the time to read my email. Looking forward >>>> to hearing from you. >>>> >>>> >>>> >>>> Sincerely, >>>> >>>> Xiaofeng He >>>> ----------------------------------------------------- >>>> >>>> Research Engineer >>>> >>>> Internet Based Engineering, Beijing, China >>>> >> >> >> >> -- >> 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 >> >> https://urldefense.us/v3/__https://www.cse.buffalo.edu/*knepley/__;fg!!G_uCfscf7eWS!YnpI8yJI5A6InOexOleRZqZzYOiuR4sw1PSdo040lUsJmZvbh-i6AWIkRtbavv78rzOsshSHnj3REra61DB188ztbxlYbg$ >> >> <https://urldefense.us/v3/__http://www.cse.buffalo.edu/*knepley/__;fg!!G_uCfscf7eWS!YnpI8yJI5A6InOexOleRZqZzYOiuR4sw1PSdo040lUsJmZvbh-i6AWIkRtbavv78rzOsshSHnj3REra61DB188yxPXfiRQ$ >> >
