Actual source code: ex50.c

  1: /*   DMDA/KSP solving a system of linear equations.
  2:      Poisson equation in 2D:

  4:      div(grad p) = f,  0 < x,y < 1
  5:      with
  6:        forcing function f = -cos(m*pi*x)*cos(n*pi*y),
  7:        Neumann boundary conditions
  8:         dp/dx = 0 for x = 0, x = 1.
  9:         dp/dy = 0 for y = 0, y = 1.

 11:      Contributed by Michael Boghosian <boghmic@iit.edu>, 2008,
 12:          based on petsc/src/ksp/ksp/tutorials/ex29.c and ex32.c

 14:      Compare to ex66.c

 16:      Example of Usage:
 17:           ./ex50 -da_grid_x 3 -da_grid_y 3 -pc_type mg -da_refine 3 -ksp_monitor -ksp_view -dm_view draw -draw_pause -1
 18:           ./ex50 -da_grid_x 100 -da_grid_y 100 -pc_type mg  -pc_mg_levels 1 -mg_levels_0_pc_type ilu -mg_levels_0_pc_factor_levels 1 -ksp_monitor -ksp_view
 19:           ./ex50 -da_grid_x 100 -da_grid_y 100 -pc_type mg -pc_mg_levels 1 -mg_levels_0_pc_type lu -mg_levels_0_pc_factor_shift_type NONZERO -ksp_monitor
 20:           mpiexec -n 4 ./ex50 -da_grid_x 3 -da_grid_y 3 -pc_type mg -da_refine 10 -ksp_monitor -ksp_view -log_view
 21: */

 23: static char help[] = "Solves 2D Poisson equation using multigrid.\n\n";

 25: #include <petscdm.h>
 26: #include <petscdmda.h>
 27: #include <petscksp.h>
 28: #include <petscsys.h>
 29: #include <petscvec.h>

 31: extern PetscErrorCode ComputeJacobian(KSP, Mat, Mat, void *);
 32: extern PetscErrorCode ComputeRHS(KSP, Vec, void *);

 34: typedef struct {
 35:   PetscScalar uu, tt;
 36: } UserContext;

 38: int main(int argc, char **argv)
 39: {
 40:   KSP         ksp;
 41:   DM          da;
 42:   UserContext user;

 44:   PetscFunctionBeginUser;
 45:   PetscCall(PetscInitialize(&argc, &argv, (char *)0, help));
 46:   PetscCall(KSPCreate(PETSC_COMM_WORLD, &ksp));
 47:   PetscCall(DMDACreate2d(PETSC_COMM_WORLD, DM_BOUNDARY_NONE, DM_BOUNDARY_NONE, DMDA_STENCIL_STAR, 11, 11, PETSC_DECIDE, PETSC_DECIDE, 1, 1, NULL, NULL, &da));
 48:   PetscCall(DMSetFromOptions(da));
 49:   PetscCall(DMSetUp(da));
 50:   PetscCall(KSPSetDM(ksp, (DM)da));
 51:   PetscCall(DMSetApplicationContext(da, &user));

 53:   user.uu = 1.0;
 54:   user.tt = 1.0;

 56:   PetscCall(KSPSetComputeRHS(ksp, ComputeRHS, &user));
 57:   PetscCall(KSPSetComputeOperators(ksp, ComputeJacobian, &user));
 58:   PetscCall(KSPSetFromOptions(ksp));
 59:   PetscCall(KSPSolve(ksp, NULL, NULL));

 61:   PetscCall(DMDestroy(&da));
 62:   PetscCall(KSPDestroy(&ksp));
 63:   PetscCall(PetscFinalize());
 64:   return 0;
 65: }

 67: PetscErrorCode ComputeRHS(KSP ksp, Vec b, void *ctx)
 68: {
 69:   UserContext  *user = (UserContext *)ctx;
 70:   PetscInt      i, j, M, N, xm, ym, xs, ys;
 71:   PetscScalar   Hx, Hy, pi, uu, tt;
 72:   PetscScalar **array;
 73:   DM            da;
 74:   MatNullSpace  nullspace;

 76:   PetscFunctionBeginUser;
 77:   PetscCall(KSPGetDM(ksp, &da));
 78:   PetscCall(DMDAGetInfo(da, 0, &M, &N, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0));
 79:   uu = user->uu;
 80:   tt = user->tt;
 81:   pi = 4 * atan(1.0);
 82:   Hx = 1.0 / (PetscReal)(M);
 83:   Hy = 1.0 / (PetscReal)(N);

 85:   PetscCall(DMDAGetCorners(da, &xs, &ys, 0, &xm, &ym, 0)); /* Fine grid */
 86:   PetscCall(DMDAVecGetArray(da, b, &array));
 87:   for (j = ys; j < ys + ym; j++) {
 88:     for (i = xs; i < xs + xm; i++) array[j][i] = -PetscCosScalar(uu * pi * ((PetscReal)i + 0.5) * Hx) * PetscCosScalar(tt * pi * ((PetscReal)j + 0.5) * Hy) * Hx * Hy;
 89:   }
 90:   PetscCall(DMDAVecRestoreArray(da, b, &array));
 91:   PetscCall(VecAssemblyBegin(b));
 92:   PetscCall(VecAssemblyEnd(b));

 94:   /* force right-hand side to be consistent for singular matrix */
 95:   /* note this is really a hack, normally the model would provide you with a consistent right handside */
 96:   PetscCall(MatNullSpaceCreate(PETSC_COMM_WORLD, PETSC_TRUE, 0, 0, &nullspace));
 97:   PetscCall(MatNullSpaceRemove(nullspace, b));
 98:   PetscCall(MatNullSpaceDestroy(&nullspace));
 99:   PetscFunctionReturn(PETSC_SUCCESS);
100: }

102: PetscErrorCode ComputeJacobian(KSP ksp, Mat J, Mat jac, void *ctx)
103: {
104:   PetscInt     i, j, M, N, xm, ym, xs, ys, num, numi, numj;
105:   PetscScalar  v[5], Hx, Hy, HydHx, HxdHy;
106:   MatStencil   row, col[5];
107:   DM           da;
108:   MatNullSpace nullspace;

110:   PetscFunctionBeginUser;
111:   PetscCall(KSPGetDM(ksp, &da));
112:   PetscCall(DMDAGetInfo(da, 0, &M, &N, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0));
113:   Hx    = 1.0 / (PetscReal)(M);
114:   Hy    = 1.0 / (PetscReal)(N);
115:   HxdHy = Hx / Hy;
116:   HydHx = Hy / Hx;
117:   PetscCall(DMDAGetCorners(da, &xs, &ys, 0, &xm, &ym, 0));
118:   for (j = ys; j < ys + ym; j++) {
119:     for (i = xs; i < xs + xm; i++) {
120:       row.i = i;
121:       row.j = j;

123:       if (i == 0 || j == 0 || i == M - 1 || j == N - 1) {
124:         num  = 0;
125:         numi = 0;
126:         numj = 0;
127:         if (j != 0) {
128:           v[num]     = -HxdHy;
129:           col[num].i = i;
130:           col[num].j = j - 1;
131:           num++;
132:           numj++;
133:         }
134:         if (i != 0) {
135:           v[num]     = -HydHx;
136:           col[num].i = i - 1;
137:           col[num].j = j;
138:           num++;
139:           numi++;
140:         }
141:         if (i != M - 1) {
142:           v[num]     = -HydHx;
143:           col[num].i = i + 1;
144:           col[num].j = j;
145:           num++;
146:           numi++;
147:         }
148:         if (j != N - 1) {
149:           v[num]     = -HxdHy;
150:           col[num].i = i;
151:           col[num].j = j + 1;
152:           num++;
153:           numj++;
154:         }
155:         v[num]     = ((PetscReal)(numj)*HxdHy + (PetscReal)(numi)*HydHx);
156:         col[num].i = i;
157:         col[num].j = j;
158:         num++;
159:         PetscCall(MatSetValuesStencil(jac, 1, &row, num, col, v, INSERT_VALUES));
160:       } else {
161:         v[0]     = -HxdHy;
162:         col[0].i = i;
163:         col[0].j = j - 1;
164:         v[1]     = -HydHx;
165:         col[1].i = i - 1;
166:         col[1].j = j;
167:         v[2]     = 2.0 * (HxdHy + HydHx);
168:         col[2].i = i;
169:         col[2].j = j;
170:         v[3]     = -HydHx;
171:         col[3].i = i + 1;
172:         col[3].j = j;
173:         v[4]     = -HxdHy;
174:         col[4].i = i;
175:         col[4].j = j + 1;
176:         PetscCall(MatSetValuesStencil(jac, 1, &row, 5, col, v, INSERT_VALUES));
177:       }
178:     }
179:   }
180:   PetscCall(MatAssemblyBegin(jac, MAT_FINAL_ASSEMBLY));
181:   PetscCall(MatAssemblyEnd(jac, MAT_FINAL_ASSEMBLY));

183:   PetscCall(MatNullSpaceCreate(PETSC_COMM_WORLD, PETSC_TRUE, 0, 0, &nullspace));
184:   PetscCall(MatSetNullSpace(J, nullspace));
185:   PetscCall(MatNullSpaceDestroy(&nullspace));
186:   PetscFunctionReturn(PETSC_SUCCESS);
187: }

189: /*TEST

191:    build:
192:       requires: !complex !single

194:    test:
195:       args: -pc_type mg -pc_mg_type full -ksp_type cg -ksp_monitor_short -da_refine 3 -mg_coarse_pc_type svd -ksp_view

197:    test:
198:       suffix: 2
199:       nsize: 4
200:       args: -pc_type mg -pc_mg_type full -ksp_type cg -ksp_monitor_short -da_refine 3 -mg_coarse_pc_type redundant -mg_coarse_redundant_pc_type svd -ksp_view

202:    test:
203:       suffix: 3
204:       nsize: 2
205:       args: -pc_type mg -pc_mg_type full -ksp_monitor_short -da_refine 5 -mg_coarse_ksp_type cg -mg_coarse_ksp_converged_reason -mg_coarse_ksp_rtol 1e-2 -mg_coarse_ksp_max_it 5 -mg_coarse_pc_type none -pc_mg_levels 2 -ksp_type pipefgmres -ksp_pipefgmres_shift 1.5

207:    test:
208:       suffix: tut_1
209:       nsize: 1
210:       args: -da_grid_x 4 -da_grid_y 4 -mat_view

212:    test:
213:       suffix: tut_2
214:       requires: superlu_dist parmetis
215:       nsize: 4
216:       args: -da_grid_x 120 -da_grid_y 120 -pc_type lu -pc_factor_mat_solver_type superlu_dist -ksp_monitor -ksp_view

218:    test:
219:       suffix: tut_3
220:       nsize: 4
221:       args: -da_grid_x 1025 -da_grid_y 1025 -pc_type mg -pc_mg_levels 9 -ksp_monitor

223: TEST*/