static char help[] = "Poisson Problem with finite elements.\n\ This example supports automatic convergence estimation for multilevel solvers\n\ and solver adaptivity.\n\n\n"; #include #include #include #include /* Next steps: - Show lowest eigenmodes using SLEPc code from my ex6 - Run CR example from Brannick's slides that looks like semicoarsening - Show lowest modes - Show CR convergence rate - Show CR solution to show non-convergence - Refine coarse grid around non-converged dofs - Maybe use Barry's "more then Z% above the average" monitor to label bad dofs - Mark coarse cells that contain bad dofs - Run SBR on coarse grid - Run Helmholtz example from Gander's writeup - Run Low Mach example? - Run subduction example? */ typedef struct { PetscBool cr; /* Use compatible relaxation */ } AppCtx; static PetscErrorCode trig_u(PetscInt dim, PetscReal time, const PetscReal x[], PetscInt Nc, PetscScalar *u, void *ctx) { PetscInt d; u[0] = 0.0; for (d = 0; d < dim; ++d) u[0] += PetscSinReal(2.0*PETSC_PI*x[d]); return 0; } static void f0_trig_u(PetscInt dim, PetscInt Nf, PetscInt NfAux, const PetscInt uOff[], const PetscInt uOff_x[], const PetscScalar u[], const PetscScalar u_t[], const PetscScalar u_x[], const PetscInt aOff[], const PetscInt aOff_x[], const PetscScalar a[], const PetscScalar a_t[], const PetscScalar a_x[], PetscReal t, const PetscReal x[], PetscInt numConstants, const PetscScalar constants[], PetscScalar f0[]) { PetscInt d; for (d = 0; d < dim; ++d) f0[0] += -4.0*PetscSqr(PETSC_PI)*PetscSinReal(2.0*PETSC_PI*x[d]); } static void f1_u(PetscInt dim, PetscInt Nf, PetscInt NfAux, const PetscInt uOff[], const PetscInt uOff_x[], const PetscScalar u[], const PetscScalar u_t[], const PetscScalar u_x[], const PetscInt aOff[], const PetscInt aOff_x[], const PetscScalar a[], const PetscScalar a_t[], const PetscScalar a_x[], PetscReal t, const PetscReal x[], PetscInt numConstants, const PetscScalar constants[], PetscScalar f1[]) { PetscInt d; for (d = 0; d < dim; ++d) f1[d] = u_x[d]; } static void g3_uu(PetscInt dim, PetscInt Nf, PetscInt NfAux, const PetscInt uOff[], const PetscInt uOff_x[], const PetscScalar u[], const PetscScalar u_t[], const PetscScalar u_x[], const PetscInt aOff[], const PetscInt aOff_x[], const PetscScalar a[], const PetscScalar a_t[], const PetscScalar a_x[], PetscReal t, PetscReal u_tShift, const PetscReal x[], PetscInt numConstants, const PetscScalar constants[], PetscScalar g3[]) { PetscInt d; for (d = 0; d < dim; ++d) g3[d*dim+d] = 1.0; } static PetscErrorCode ProcessOptions(MPI_Comm comm, AppCtx *options) { PetscErrorCode ierr; PetscFunctionBeginUser; options->cr = PETSC_FALSE; ierr = PetscOptionsBegin(comm, "", "Poisson Problem Options", "DMPLEX");CHKERRQ(ierr); ierr = PetscOptionsBool("-cr", "Use compatible relaxarion", "ex20.c", options->cr, &options->cr, NULL);CHKERRQ(ierr); ierr = PetscOptionsEnd(); PetscFunctionReturn(0); } static PetscErrorCode CreateMesh(MPI_Comm comm, AppCtx *user, DM *dm) { PetscErrorCode ierr; PetscFunctionBeginUser; ierr = DMPlexCreateBoxMesh(comm, 2, PETSC_TRUE, NULL, NULL, NULL, NULL, PETSC_TRUE, dm);CHKERRQ(ierr); ierr = DMLocalizeCoordinates(*dm);CHKERRQ(ierr); ierr = PetscObjectSetName((PetscObject) *dm, "Mesh");CHKERRQ(ierr); ierr = DMSetApplicationContext(*dm, user);CHKERRQ(ierr); ierr = DMSetFromOptions(*dm);CHKERRQ(ierr); ierr = DMViewFromOptions(*dm, NULL, "-dm_view");CHKERRQ(ierr); PetscFunctionReturn(0); } static PetscErrorCode SetupPrimalProblem(DM dm, AppCtx *user) { PetscDS prob; const PetscInt id = 1; PetscErrorCode ierr; PetscFunctionBeginUser; ierr = DMGetDS(dm, &prob);CHKERRQ(ierr); ierr = PetscDSSetResidual(prob, 0, f0_trig_u, f1_u);CHKERRQ(ierr); ierr = PetscDSSetJacobian(prob, 0, 0, NULL, NULL, NULL, g3_uu);CHKERRQ(ierr); ierr = PetscDSSetExactSolution(prob, 0, trig_u, user);CHKERRQ(ierr); ierr = DMAddBoundary(dm, DM_BC_ESSENTIAL, "wall", "marker", 0, 0, NULL, (void (*)(void)) trig_u, NULL, 1, &id, user);CHKERRQ(ierr); PetscFunctionReturn(0); } static PetscErrorCode SetupDiscretization(DM dm, const char name[], PetscErrorCode (*setup)(DM, AppCtx *), AppCtx *user) { DM cdm = dm; PetscFE fe; DMPolytopeType ct; PetscBool simplex; PetscInt dim, cStart; char prefix[PETSC_MAX_PATH_LEN]; PetscErrorCode ierr; PetscFunctionBeginUser; ierr = DMGetDimension(dm, &dim);CHKERRQ(ierr); ierr = DMPlexGetHeightStratum(dm, 0, &cStart, NULL);CHKERRQ(ierr); ierr = DMPlexGetCellType(dm, cStart, &ct);CHKERRQ(ierr); simplex = DMPolytopeTypeGetNumVertices(ct) == DMPolytopeTypeGetDim(ct)+1 ? PETSC_TRUE : PETSC_FALSE; ierr = PetscSNPrintf(prefix, PETSC_MAX_PATH_LEN, "%s_", name);CHKERRQ(ierr); ierr = PetscFECreateDefault(PetscObjectComm((PetscObject) dm), dim, 1, simplex, name ? prefix : NULL, -1, &fe);CHKERRQ(ierr); ierr = PetscObjectSetName((PetscObject) fe, name);CHKERRQ(ierr); ierr = DMSetField(dm, 0, NULL, (PetscObject) fe);CHKERRQ(ierr); ierr = DMCreateDS(dm);CHKERRQ(ierr); ierr = (*setup)(dm, user);CHKERRQ(ierr); while (cdm) { ierr = DMCopyDisc(dm,cdm);CHKERRQ(ierr); ierr = DMGetCoarseDM(cdm, &cdm);CHKERRQ(ierr); } ierr = PetscFEDestroy(&fe);CHKERRQ(ierr); PetscFunctionReturn(0); } /* How to do CR in PETSc: Loop over PCMG levels, coarse to fine: Run smoother for 5 iterates At each iterate, solve Inj u_f = u_c with LSQR to 1e-15 Suppose that e_k = c^k e_0, which means log e_k = log e_0 + k log c Fit log of error to look at log c, the slope Check R^2 for linearity (1 - square residual / variance) Solve exactly Prolong to next level */ int main(int argc, char **argv) { DM dm; /* Problem specification */ SNES snes; /* Nonlinear solver */ Vec u; /* Solutions */ AppCtx user; /* User-defined work context */ PetscErrorCode ierr; ierr = PetscInitialize(&argc, &argv, NULL,help);if (ierr) return ierr; ierr = ProcessOptions(PETSC_COMM_WORLD, &user);CHKERRQ(ierr); /* Primal system */ ierr = SNESCreate(PETSC_COMM_WORLD, &snes);CHKERRQ(ierr); ierr = CreateMesh(PETSC_COMM_WORLD, &user, &dm);CHKERRQ(ierr); ierr = SNESSetDM(snes, dm);CHKERRQ(ierr); ierr = SetupDiscretization(dm, "potential", SetupPrimalProblem, &user);CHKERRQ(ierr); ierr = DMCreateGlobalVector(dm, &u);CHKERRQ(ierr); ierr = VecSet(u, 0.0);CHKERRQ(ierr); ierr = PetscObjectSetName((PetscObject) u, "potential");CHKERRQ(ierr); ierr = DMPlexSetSNESLocalFEM(dm, &user, &user, &user);CHKERRQ(ierr); ierr = SNESSetFromOptions(snes);CHKERRQ(ierr); ierr = SNESSolve(snes, NULL, u);CHKERRQ(ierr); ierr = SNESGetSolution(snes, &u);CHKERRQ(ierr); ierr = VecViewFromOptions(u, NULL, "-potential_view");CHKERRQ(ierr); /* Cleanup */ ierr = VecDestroy(&u);CHKERRQ(ierr); ierr = SNESDestroy(&snes);CHKERRQ(ierr); ierr = DMDestroy(&dm);CHKERRQ(ierr); ierr = PetscFinalize(); return ierr; } /*TEST test: suffix: 2d_p1_gmg_vcycle_rate requires: triangle args: -potential_petscspace_degree 1 -dm_plex_box_faces 2,2 -dm_refine_hierarchy 3 \ -ksp_rtol 5e-10 -ksp_converged_rate -pc_type mg \ -mg_levels_ksp_max_it 5 -mg_levels_ksp_norm_type preconditioned -mg_levels_ksp_converged_rate \ -mg_levels_esteig_ksp_type cg \ -mg_levels_esteig_ksp_max_it 10 \ -mg_levels_ksp_chebyshev_esteig 0,0.05,0,1.05 \ -mg_levels_pc_type jacobi test: suffix: 2d_p1_gmg_vcycle_cr requires: triangle args: -potential_petscspace_degree 1 -dm_plex_box_faces 2,2 -dm_refine_hierarchy 3 \ -ksp_rtol 5e-10 -pc_type mg -pc_mg_adapt_cr \ -mg_levels_ksp_max_it 5 -mg_levels_ksp_norm_type preconditioned \ -mg_levels_esteig_ksp_type cg \ -mg_levels_esteig_ksp_max_it 10 \ -mg_levels_ksp_chebyshev_esteig 0,0.05,0,1.05 \ -mg_levels_cr_ksp_max_it 5 -mg_levels_cr_ksp_converged_rate -mg_levels_cr_ksp_converged_rate_type error test: suffix: 2d_p1_gmg_fcycle_rate requires: triangle args: -potential_petscspace_degree 1 -dm_plex_box_faces 2,2 -dm_refine_hierarchy 3 \ -ksp_rtol 5e-10 -ksp_converged_rate -pc_type mg -pc_mg_type full \ -mg_levels_ksp_max_it 5 -mg_levels_ksp_norm_type preconditioned -mg_levels_ksp_converged_rate \ -mg_levels_esteig_ksp_type cg \ -mg_levels_esteig_ksp_max_it 10 \ -mg_levels_ksp_chebyshev_esteig 0,0.05,0,1.05 \ -mg_levels_pc_type jacobi test: suffix: 2d_p1_gmg_vcycle_adapt_rate requires: triangle bamg args: -potential_petscspace_degree 1 -dm_plex_box_faces 2,2 -dm_refine_hierarchy 3 \ -ksp_rtol 5e-10 -ksp_converged_rate -pc_type mg \ -pc_mg_galerkin -pc_mg_adapt_interp -pc_mg_adapt_interp_coarse_space harmonic -pc_mg_adapt_interp_n 8 \ -mg_levels_ksp_max_it 5 -mg_levels_ksp_norm_type preconditioned -mg_levels_ksp_converged_rate \ -mg_levels_esteig_ksp_type cg \ -mg_levels_esteig_ksp_max_it 10 \ -mg_levels_ksp_chebyshev_esteig 0,0.05,0,1.05 \ -mg_levels_pc_type jacobi test: suffix: 2d_p1_scalable_rate requires: triangle args: -potential_petscspace_degree 1 -dm_refine 3 \ -ksp_type cg -ksp_rtol 1.e-11 -ksp_norm_type unpreconditioned -ksp_converged_rate \ -pc_type gamg \ -pc_gamg_type agg -pc_gamg_agg_nsmooths 1 \ -pc_gamg_coarse_eq_limit 1000 \ -pc_gamg_square_graph 1 \ -pc_gamg_threshold 0.05 \ -pc_gamg_threshold_scale .0 \ -mg_levels_ksp_type chebyshev -mg_levels_ksp_norm_type preconditioned -mg_levels_ksp_converged_rate \ -mg_levels_ksp_max_it 5 \ -mg_levels_esteig_ksp_type cg \ -mg_levels_esteig_ksp_max_it 10 \ -mg_levels_ksp_chebyshev_esteig 0,0.05,0,1.05 \ -mg_levels_pc_type jacobi \ -matptap_via scalable TEST*/