Date: 2025-03-29T05:58:50+00:00

Actual source code: ex5adj.c

      1: static char help[] = "Demonstrates adjoint sensitivity analysis for Reaction-Diffusion Equations.\n";

      3: /*
      4:   See ex5.c for details on the equation.
      5:   This code demonestrates the TSAdjoint interface to a system of time-dependent partial differential equations.
      6:   It computes the sensitivity of a component in the final solution, which locates in the center of the 2D domain, w.r.t. the initial conditions.
      7:   The user does not need to provide any additional functions. The required functions in the original simulation are reused in the adjoint run.

      9:   Runtime options:
     10:     -forwardonly  - run the forward simulation without adjoint
     11:     -implicitform - provide IFunction and IJacobian to TS, if not set, RHSFunction and RHSJacobian will be used
     12:     -aijpc        - set the preconditioner matrix to be aij (the Jacobian matrix can be of a different type such as ELL)
     13: */
     14: #include "reaction_diffusion.h"
     15: #include <petscdm.h>
     16: #include <petscdmda.h>

     18: PetscErrorCode InitialConditions(DM, Vec);

     20: PetscErrorCode InitializeLambda(DM da, Vec lambda, PetscReal x, PetscReal y)
     21: {
     22:   PetscInt i, j, Mx, My, xs, ys, xm, ym;
     23:   Field  **l;

     25:   PetscFunctionBegin;
     26:   PetscCall(DMDAGetInfo(da, PETSC_IGNORE, &Mx, &My, PETSC_IGNORE, PETSC_IGNORE, PETSC_IGNORE, PETSC_IGNORE, PETSC_IGNORE, PETSC_IGNORE, PETSC_IGNORE, PETSC_IGNORE, PETSC_IGNORE, PETSC_IGNORE));
     27:   /* locate the global i index for x and j index for y */
     28:   i = (PetscInt)(x * (Mx - 1));
     29:   j = (PetscInt)(y * (My - 1));
     30:   PetscCall(DMDAGetCorners(da, &xs, &ys, NULL, &xm, &ym, NULL));

     32:   if (xs <= i && i < xs + xm && ys <= j && j < ys + ym) {
     33:     /* the i,j vertex is on this process */
     34:     PetscCall(DMDAVecGetArray(da, lambda, &l));
     35:     l[j][i].u = 1.0;
     36:     l[j][i].v = 1.0;
     37:     PetscCall(DMDAVecRestoreArray(da, lambda, &l));
     38:   }
     39:   PetscFunctionReturn(PETSC_SUCCESS);
     40: }

     42: int main(int argc, char **argv)
     43: {
     44:   TS        ts; /* ODE integrator */
     45:   Vec       x;  /* solution */
     46:   DM        da;
     47:   AppCtx    appctx;
     48:   Vec       lambda[1];
     49:   PetscBool forwardonly = PETSC_FALSE, implicitform = PETSC_TRUE;

     51:   PetscFunctionBeginUser;
     52:   PetscCall(PetscInitialize(&argc, &argv, NULL, help));
     53:   PetscCall(PetscOptionsGetBool(NULL, NULL, "-forwardonly", &forwardonly, NULL));
     54:   PetscCall(PetscOptionsGetBool(NULL, NULL, "-implicitform", &implicitform, NULL));
     55:   appctx.aijpc = PETSC_FALSE;
     56:   PetscCall(PetscOptionsGetBool(NULL, NULL, "-aijpc", &appctx.aijpc, NULL));

     58:   appctx.D1    = 8.0e-5;
     59:   appctx.D2    = 4.0e-5;
     60:   appctx.gamma = .024;
     61:   appctx.kappa = .06;

     63:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     64:      Create distributed array (DMDA) to manage parallel grid and vectors
     65:   - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
     66:   PetscCall(DMDACreate2d(PETSC_COMM_WORLD, DM_BOUNDARY_PERIODIC, DM_BOUNDARY_PERIODIC, DMDA_STENCIL_STAR, 64, 64, PETSC_DECIDE, PETSC_DECIDE, 2, 1, NULL, NULL, &da));
     67:   PetscCall(DMSetFromOptions(da));
     68:   PetscCall(DMSetUp(da));
     69:   PetscCall(DMDASetFieldName(da, 0, "u"));
     70:   PetscCall(DMDASetFieldName(da, 1, "v"));

     72:   /*  - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     73:      Extract global vectors from DMDA; then duplicate for remaining
     74:      vectors that are the same types
     75:    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
     76:   PetscCall(DMCreateGlobalVector(da, &x));

     78:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     79:      Create timestepping solver context
     80:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
     81:   PetscCall(TSCreate(PETSC_COMM_WORLD, &ts));
     82:   PetscCall(TSSetDM(ts, da));
     83:   PetscCall(TSSetProblemType(ts, TS_NONLINEAR));
     84:   PetscCall(TSSetEquationType(ts, TS_EQ_ODE_EXPLICIT)); /* less Jacobian evaluations when adjoint BEuler is used, otherwise no effect */
     85:   if (!implicitform) {
     86:     PetscCall(TSSetType(ts, TSRK));
     87:     PetscCall(TSSetRHSFunction(ts, NULL, RHSFunction, &appctx));
     88:     PetscCall(TSSetRHSJacobian(ts, NULL, NULL, RHSJacobian, &appctx));
     89:   } else {
     90:     PetscCall(TSSetType(ts, TSCN));
     91:     PetscCall(TSSetIFunction(ts, NULL, IFunction, &appctx));
     92:     if (appctx.aijpc) {
     93:       Mat A, B;

     95:       PetscCall(DMSetMatType(da, MATSELL));
     96:       PetscCall(DMCreateMatrix(da, &A));
     97:       PetscCall(MatConvert(A, MATAIJ, MAT_INITIAL_MATRIX, &B));
     98:       /* FIXME do we need to change viewer to display matrix in natural ordering as DMCreateMatrix_DA does? */
     99:       PetscCall(TSSetIJacobian(ts, A, B, IJacobian, &appctx));
    100:       PetscCall(MatDestroy(&A));
    101:       PetscCall(MatDestroy(&B));
    102:     } else {
    103:       PetscCall(TSSetIJacobian(ts, NULL, NULL, IJacobian, &appctx));
    104:     }
    105:   }

    107:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    108:      Set initial conditions
    109:    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
    110:   PetscCall(InitialConditions(da, x));
    111:   PetscCall(TSSetSolution(ts, x));

    113:   /*
    114:     Have the TS save its trajectory so that TSAdjointSolve() may be used
    115:   */
    116:   if (!forwardonly) PetscCall(TSSetSaveTrajectory(ts));

    118:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    119:      Set solver options
    120:    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
    121:   PetscCall(TSSetMaxTime(ts, 200.0));
    122:   PetscCall(TSSetTimeStep(ts, 0.5));
    123:   PetscCall(TSSetExactFinalTime(ts, TS_EXACTFINALTIME_MATCHSTEP));
    124:   PetscCall(TSSetFromOptions(ts));

    126:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    127:      Solve ODE system
    128:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
    129:   PetscCall(TSSolve(ts, x));
    130:   if (!forwardonly) {
    131:     /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    132:        Start the Adjoint model
    133:        - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
    134:     PetscCall(VecDuplicate(x, &lambda[0]));
    135:     /*   Reset initial conditions for the adjoint integration */
    136:     PetscCall(InitializeLambda(da, lambda[0], 0.5, 0.5));
    137:     PetscCall(TSSetCostGradients(ts, 1, lambda, NULL));
    138:     PetscCall(TSAdjointSolve(ts));
    139:     PetscCall(VecDestroy(&lambda[0]));
    140:   }
    141:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    142:      Free work space.  All PETSc objects should be destroyed when they
    143:      are no longer needed.
    144:    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
    145:   PetscCall(VecDestroy(&x));
    146:   PetscCall(TSDestroy(&ts));
    147:   PetscCall(DMDestroy(&da));
    148:   PetscCall(PetscFinalize());
    149:   return 0;
    150: }

    152: /* ------------------------------------------------------------------- */
    153: PetscErrorCode InitialConditions(DM da, Vec U)
    154: {
    155:   PetscInt  i, j, xs, ys, xm, ym, Mx, My;
    156:   Field   **u;
    157:   PetscReal hx, hy, x, y;

    159:   PetscFunctionBegin;
    160:   PetscCall(DMDAGetInfo(da, PETSC_IGNORE, &Mx, &My, PETSC_IGNORE, PETSC_IGNORE, PETSC_IGNORE, PETSC_IGNORE, PETSC_IGNORE, PETSC_IGNORE, PETSC_IGNORE, PETSC_IGNORE, PETSC_IGNORE, PETSC_IGNORE));

    162:   hx = 2.5 / (PetscReal)Mx;
    163:   hy = 2.5 / (PetscReal)My;

    165:   /*
    166:      Get pointers to vector data
    167:   */
    168:   PetscCall(DMDAVecGetArray(da, U, &u));

    170:   /*
    171:      Get local grid boundaries
    172:   */
    173:   PetscCall(DMDAGetCorners(da, &xs, &ys, NULL, &xm, &ym, NULL));

    175:   /*
    176:      Compute function over the locally owned part of the grid
    177:   */
    178:   for (j = ys; j < ys + ym; j++) {
    179:     y = j * hy;
    180:     for (i = xs; i < xs + xm; i++) {
    181:       x = i * hx;
    182:       if (PetscApproximateGTE(x, 1.0) && PetscApproximateLTE(x, 1.5) && PetscApproximateGTE(y, 1.0) && PetscApproximateLTE(y, 1.5))
    183:         u[j][i].v = PetscPowReal(PetscSinReal(4.0 * PETSC_PI * x), 2.0) * PetscPowReal(PetscSinReal(4.0 * PETSC_PI * y), 2.0) / 4.0;
    184:       else u[j][i].v = 0.0;

    186:       u[j][i].u = 1.0 - 2.0 * u[j][i].v;
    187:     }
    188:   }

    190:   /*
    191:      Restore vectors
    192:   */
    193:   PetscCall(DMDAVecRestoreArray(da, U, &u));
    194:   PetscFunctionReturn(PETSC_SUCCESS);
    195: }

    197: /*TEST

    199:    build:
    200:       depends: reaction_diffusion.c
    201:       requires: !complex !single

    203:    test:
    204:       args: -ts_max_steps 10 -ts_monitor -ts_adjoint_monitor -da_grid_x 20 -da_grid_y 20
    205:       output_file: output/ex5adj_1.out

    207:    test:
    208:       suffix: 2
    209:       nsize: 2
    210:       args: -ts_max_steps 10 -ts_dt 10 -ts_monitor -ts_adjoint_monitor -ksp_monitor_short -da_grid_x 20 -da_grid_y 20 -ts_trajectory_dirname Test-dir -ts_trajectory_file_template test-%06D.cp

    212:    test:
    213:       suffix: 3
    214:       nsize: 2
    215:       args: -ts_max_steps 10 -ts_dt 10 -ts_adjoint_monitor_draw_sensi

    217:    test:
    218:       suffix: 4
    219:       nsize: 2
    220:       args: -ts_max_steps 10 -ts_dt 10 -ts_monitor -ts_adjoint_monitor -ksp_monitor_short -da_grid_x 20 -da_grid_y 20 -snes_fd_color
    221:       output_file: output/ex5adj_2.out

    223:    test:
    224:       suffix: 5
    225:       nsize: 2
    226:       args: -ts_max_steps 10 -implicitform 0 -ts_type rk -ts_rk_type 4 -ts_monitor -ts_adjoint_monitor -da_grid_x 20 -da_grid_y 20 -snes_fd_color
    227:       output_file: output/ex5adj_1.out

    229:    test:
    230:       suffix: knl
    231:       args: -ts_max_steps 10 -ts_monitor -ts_adjoint_monitor -ts_trajectory_type memory -ts_trajectory_solution_only 0 -malloc_hbw -ts_trajectory_use_dram 1
    232:       output_file: output/ex5adj_3.out
    233:       requires: knl

    235:    test:
    236:       suffix: sell
    237:       nsize: 4
    238:       args: -forwardonly -ts_max_steps 10 -ts_monitor -snes_monitor_short -dm_mat_type sell -pc_type none
    239:       output_file: output/ex5adj_sell_1.out

    241:    test:
    242:       suffix: aijsell
    243:       nsize: 4
    244:       args: -forwardonly -ts_max_steps 10 -ts_monitor -snes_monitor_short -dm_mat_type aijsell -pc_type none
    245:       output_file: output/ex5adj_sell_1.out

    247:    test:
    248:       suffix: sell2
    249:       nsize: 4
    250:       args: -forwardonly -ts_max_steps 10 -ts_monitor -snes_monitor_short -dm_mat_type sell -pc_type mg -pc_mg_levels 2 -mg_coarse_pc_type sor
    251:       output_file: output/ex5adj_sell_2.out

    253:    test:
    254:       suffix: aijsell2
    255:       nsize: 4
    256:       args: -forwardonly -ts_max_steps 10 -ts_monitor -snes_monitor_short -dm_mat_type aijsell -pc_type mg -pc_mg_levels 2 -mg_coarse_pc_type sor
    257:       output_file: output/ex5adj_sell_2.out

    259:    test:
    260:       suffix: sell3
    261:       nsize: 4
    262:       args: -forwardonly -ts_max_steps 10 -ts_monitor -snes_monitor_short -dm_mat_type sell -pc_type mg -pc_mg_levels 2 -mg_coarse_pc_type bjacobi -mg_levels_pc_type bjacobi
    263:       output_file: output/ex5adj_sell_3.out

    265:    test:
    266:       suffix: sell4
    267:       nsize: 4
    268:       args: -forwardonly -implicitform -ts_max_steps 10 -ts_monitor -snes_monitor_short -dm_mat_type sell -pc_type mg -pc_mg_levels 2 -mg_coarse_pc_type bjacobi -mg_levels_pc_type bjacobi
    269:       output_file: output/ex5adj_sell_4.out

    271:    test:
    272:       suffix: sell5
    273:       nsize: 4
    274:       args: -forwardonly -ts_max_steps 10 -ts_monitor -snes_monitor_short -dm_mat_type sell -aijpc
    275:       output_file: output/ex5adj_sell_5.out

    277:    test:
    278:       suffix: aijsell5
    279:       nsize: 4
    280:       args: -forwardonly -ts_max_steps 10 -ts_monitor -snes_monitor_short -dm_mat_type aijsell
    281:       output_file: output/ex5adj_sell_5.out

    283:    test:
    284:       suffix: sell6
    285:       args: -ts_max_steps 10 -ts_monitor -ts_adjoint_monitor -ts_trajectory_type memory -ts_trajectory_solution_only 0 -dm_mat_type sell -pc_type jacobi
    286:       output_file: output/ex5adj_sell_6.out

    288:    test:
    289:       suffix: sell7
    290:       args: -ts_max_steps 10 -ts_monitor -ts_adjoint_monitor -ts_trajectory_type memory -ts_trajectory_solution_only 0 -dm_mat_type sellcuda -dm_vec_type cuda -pc_type jacobi
    291:       output_file: output/ex5adj_sell_6.out
    292:       requires: cuda

    294:    test:
    295:       suffix: gamg1
    296:       args: -pc_type gamg -pc_gamg_esteig_ksp_type gmres -pc_gamg_esteig_ksp_max_it 10 -ksp_monitor_short -ts_max_steps 2 -ts_monitor -ts_adjoint_monitor -ts_trajectory_type memory -ksp_rtol 1e-2 -pc_gamg_use_sa_esteig 0
    297:       output_file: output/ex5adj_gamg.out

    299:    test:
    300:       suffix: gamg2
    301:       args: -pc_type gamg -pc_gamg_esteig_ksp_type gmres -pc_gamg_esteig_ksp_max_it 10 -ksp_monitor_short -ts_max_steps 2 -ts_monitor -ts_adjoint_monitor -ts_trajectory_type memory -ksp_use_explicittranspose -ksp_rtol 1e-2 -pc_gamg_use_sa_esteig 0
    302:       output_file: output/ex5adj_gamg.out
    303: TEST*/