xref: /petsc/src/ts/tutorials/autodiff/adr_ex5adj_mf.cxx (revision 4e8208cbcbc709572b8abe32f33c78b69c819375)

static char help[] = "Demonstrates automatic, matrix-free Jacobian generation using ADOL-C for a time-dependent PDE in 2d, solved using implicit timestepping.\n";

/*
   REQUIRES configuration of PETSc with option --download-adolc.

   For documentation on ADOL-C, see
     $PETSC_ARCH/externalpackages/ADOL-C-2.6.0/ADOL-C/doc/adolc-manual.pdf
*/
/* ------------------------------------------------------------------------
  See ../advection-diffusion-reaction/ex5 for a description of the problem
  ------------------------------------------------------------------------- */

#include <petscdmda.h>
#include <petscts.h>
#include "adolc-utils/init.cxx"
#include "adolc-utils/matfree.cxx"
#include <adolc/adolc.h>

/* (Passive) field for the two variables */
typedef struct {
  PetscScalar u, v;
} Field;

/* Active field for the two variables */
typedef struct {
  adouble u, v;
} AField;

/* Application context */
typedef struct {
  PetscReal D1, D2, gamma, kappa;
  AField  **u_a, **f_a;
  AdolcCtx *adctx; /* Automatic differentation support */
} AppCtx;

extern PetscErrorCode InitialConditions(DM da, Vec U);
extern PetscErrorCode InitializeLambda(DM da, Vec lambda, PetscReal x, PetscReal y);
extern PetscErrorCode IFunctionLocalPassive(DMDALocalInfo *info, PetscReal t, Field **u, Field **udot, Field **f, void *ptr);
extern PetscErrorCode IFunctionActive(TS ts, PetscReal ftime, Vec U, Vec Udot, Vec F, void *ptr);
extern PetscErrorCode IJacobianMatFree(TS ts, PetscReal t, Vec X, Vec Xdot, PetscReal a, Mat A_shell, Mat B, PetscCtx ctx);

int main(int argc, char **argv)
{
  TS          ts;   /* ODE integrator */
  Vec         x, r; /* solution, residual */
  DM          da;
  AppCtx      appctx; /* Application context */
  AdolcMatCtx matctx; /* Matrix (free) context */
  Vec         lambda[1];
  PetscBool   forwardonly = PETSC_FALSE;
  Mat         A; /* (Matrix free) Jacobian matrix */
  PetscInt    gxm, gym;

  /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     Initialize program
     - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
  PetscFunctionBeginUser;
  PetscCall(PetscInitialize(&argc, &argv, NULL, help));
  PetscCall(PetscOptionsGetBool(NULL, NULL, "-forwardonly", &forwardonly, NULL));
  appctx.D1    = 8.0e-5;
  appctx.D2    = 4.0e-5;
  appctx.gamma = .024;
  appctx.kappa = .06;
  PetscCall(PetscLogEventRegister("df/dx forward", MAT_CLASSID, &matctx.event1));
  PetscCall(PetscLogEventRegister("df/d(xdot) forward", MAT_CLASSID, &matctx.event2));
  PetscCall(PetscLogEventRegister("df/dx reverse", MAT_CLASSID, &matctx.event3));
  PetscCall(PetscLogEventRegister("df/d(xdot) reverse", MAT_CLASSID, &matctx.event4));

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

  /*  - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     Extract global vectors from DMDA; then duplicate for remaining
     vectors that are the same types
   - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
  PetscCall(DMCreateGlobalVector(da, &x));
  PetscCall(VecDuplicate(x, &r));

  /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    Create matrix-free context and specify usage of PETSc-ADOL-C drivers
    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
  PetscCall(DMSetMatType(da, MATSHELL));
  PetscCall(DMCreateMatrix(da, &A));
  PetscCall(MatShellSetContext(A, &matctx));
  PetscCall(MatShellSetOperation(A, MATOP_MULT, (PetscErrorCodeFn *)PetscAdolcIJacobianVectorProductIDMass));
  PetscCall(MatShellSetOperation(A, MATOP_MULT_TRANSPOSE, (PetscErrorCodeFn *)PetscAdolcIJacobianTransposeVectorProductIDMass));
  PetscCall(VecDuplicate(x, &matctx.X));
  PetscCall(VecDuplicate(x, &matctx.Xdot));
  PetscCall(DMGetLocalVector(da, &matctx.localX0));

  /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     Create timestepping solver context
     - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
  PetscCall(TSCreate(PETSC_COMM_WORLD, &ts));
  PetscCall(TSSetType(ts, TSCN));
  PetscCall(TSSetDM(ts, da));
  PetscCall(TSSetProblemType(ts, TS_NONLINEAR));
  PetscCall(DMDATSSetIFunctionLocal(da, INSERT_VALUES, (DMDATSIFunctionLocalFn *)IFunctionLocalPassive, &appctx));

  /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    Some data required for matrix-free context
     - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
  PetscCall(DMDAGetGhostCorners(da, NULL, NULL, NULL, &gxm, &gym, NULL));
  matctx.m    = 2 * gxm * gym;
  matctx.n    = 2 * gxm * gym; /* Number of dependent and independent variables */
  matctx.flg  = PETSC_FALSE;   /* Flag for reverse mode */
  matctx.tag1 = 1;             /* Tape identifier */

  /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     Trace function just once
   - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
  PetscCall(PetscNew(&appctx.adctx));
  PetscCall(IFunctionActive(ts, 1., x, matctx.Xdot, r, &appctx));
  PetscCall(PetscFree(appctx.adctx));

  /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     Set Jacobian. In this case, IJacobian simply acts to pass context
     information to the matrix-free Jacobian vector product.
   - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
  PetscCall(TSSetIJacobian(ts, A, A, IJacobianMatFree, &appctx));

  /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     Set initial conditions
   - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
  PetscCall(InitialConditions(da, x));
  PetscCall(TSSetSolution(ts, x));

  /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    Have the TS save its trajectory so that TSAdjointSolve() may be used
    and set solver options
   - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
  if (!forwardonly) {
    PetscCall(TSSetSaveTrajectory(ts));
    PetscCall(TSSetMaxTime(ts, 200.0));
    PetscCall(TSSetTimeStep(ts, 0.5));
  } else {
    PetscCall(TSSetMaxTime(ts, 2000.0));
    PetscCall(TSSetTimeStep(ts, 10));
  }
  PetscCall(TSSetExactFinalTime(ts, TS_EXACTFINALTIME_STEPOVER));
  PetscCall(TSSetFromOptions(ts));

  /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     Solve ODE system
     - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
  PetscCall(TSSolve(ts, x));
  if (!forwardonly) {
    /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
       Start the Adjoint model
       - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
    PetscCall(VecDuplicate(x, &lambda[0]));
    /*   Reset initial conditions for the adjoint integration */
    PetscCall(InitializeLambda(da, lambda[0], 0.5, 0.5));
    PetscCall(TSSetCostGradients(ts, 1, lambda, NULL));
    PetscCall(TSAdjointSolve(ts));
    PetscCall(VecDestroy(&lambda[0]));
  }

  /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     Free work space.  All PETSc objects should be destroyed when they
     are no longer needed.
   - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
  PetscCall(DMRestoreLocalVector(da, &matctx.localX0));
  PetscCall(VecDestroy(&r));
  PetscCall(VecDestroy(&matctx.X));
  PetscCall(VecDestroy(&matctx.Xdot));
  PetscCall(MatDestroy(&A));
  PetscCall(VecDestroy(&x));
  PetscCall(TSDestroy(&ts));
  PetscCall(DMDestroy(&da));

  PetscCall(PetscFinalize());
  return 0;
}

PetscErrorCode InitialConditions(DM da, Vec U)
{
  PetscInt  i, j, xs, ys, xm, ym, Mx, My;
  Field   **u;
  PetscReal hx, hy, x, y;

  PetscFunctionBegin;
  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));

  hx = 2.5 / (PetscReal)Mx;
  hy = 2.5 / (PetscReal)My;

  /*
     Get pointers to vector data
  */
  PetscCall(DMDAVecGetArray(da, U, &u));

  /*
     Get local grid boundaries
  */
  PetscCall(DMDAGetCorners(da, &xs, &ys, NULL, &xm, &ym, NULL));

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

      u[j][i].u = 1.0 - 2.0 * u[j][i].v;
    }
  }

  /*
     Restore vectors
  */
  PetscCall(DMDAVecRestoreArray(da, U, &u));
  PetscFunctionReturn(PETSC_SUCCESS);
}

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

  PetscFunctionBegin;
  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));
  /* locate the global i index for x and j index for y */
  i = (PetscInt)(x * (Mx - 1));
  j = (PetscInt)(y * (My - 1));
  PetscCall(DMDAGetCorners(da, &xs, &ys, NULL, &xm, &ym, NULL));

  if (xs <= i && i < xs + xm && ys <= j && j < ys + ym) {
    /* the i,j vertex is on this process */
    PetscCall(DMDAVecGetArray(da, lambda, &l));
    l[j][i].u = 1.0;
    l[j][i].v = 1.0;
    PetscCall(DMDAVecRestoreArray(da, lambda, &l));
  }
  PetscFunctionReturn(PETSC_SUCCESS);
}

PetscErrorCode IFunctionLocalPassive(DMDALocalInfo *info, PetscReal t, Field **u, Field **udot, Field **f, void *ptr)
{
  AppCtx     *appctx = (AppCtx *)ptr;
  PetscInt    i, j, xs, ys, xm, ym;
  PetscReal   hx, hy, sx, sy;
  PetscScalar uc, uxx, uyy, vc, vxx, vyy;

  PetscFunctionBegin;
  hx = 2.50 / (PetscReal)info->mx;
  sx = 1.0 / (hx * hx);
  hy = 2.50 / (PetscReal)info->my;
  sy = 1.0 / (hy * hy);

  /* Get local grid boundaries */
  xs = info->xs;
  xm = info->xm;
  ys = info->ys;
  ym = info->ym;

  /* Compute function over the locally owned part of the grid */
  for (j = ys; j < ys + ym; j++) {
    for (i = xs; i < xs + xm; i++) {
      uc        = u[j][i].u;
      uxx       = (-2.0 * uc + u[j][i - 1].u + u[j][i + 1].u) * sx;
      uyy       = (-2.0 * uc + u[j - 1][i].u + u[j + 1][i].u) * sy;
      vc        = u[j][i].v;
      vxx       = (-2.0 * vc + u[j][i - 1].v + u[j][i + 1].v) * sx;
      vyy       = (-2.0 * vc + u[j - 1][i].v + u[j + 1][i].v) * sy;
      f[j][i].u = udot[j][i].u - appctx->D1 * (uxx + uyy) + uc * vc * vc - appctx->gamma * (1.0 - uc);
      f[j][i].v = udot[j][i].v - appctx->D2 * (vxx + vyy) - uc * vc * vc + (appctx->gamma + appctx->kappa) * vc;
    }
  }
  PetscCall(PetscLogFlops(16.0 * xm * ym));
  PetscFunctionReturn(PETSC_SUCCESS);
}

PetscErrorCode IFunctionActive(TS ts, PetscReal ftime, Vec U, Vec Udot, Vec F, void *ptr)
{
  AppCtx       *appctx = (AppCtx *)ptr;
  DM            da;
  DMDALocalInfo info;
  Field       **u, **f, **udot;
  Vec           localU;
  PetscInt      i, j, xs, ys, xm, ym, gxs, gys, gxm, gym;
  PetscReal     hx, hy, sx, sy;
  adouble       uc, uxx, uyy, vc, vxx, vyy;
  AField      **f_a, *f_c, **u_a, *u_c;
  PetscScalar   dummy;

  PetscFunctionBegin;
  PetscCall(TSGetDM(ts, &da));
  PetscCall(DMDAGetLocalInfo(da, &info));
  PetscCall(DMGetLocalVector(da, &localU));
  hx  = 2.50 / (PetscReal)info.mx;
  sx  = 1.0 / (hx * hx);
  hy  = 2.50 / (PetscReal)info.my;
  sy  = 1.0 / (hy * hy);
  xs  = info.xs;
  xm  = info.xm;
  gxs = info.gxs;
  gxm = info.gxm;
  ys  = info.ys;
  ym  = info.ym;
  gys = info.gys;
  gym = info.gym;

  /*
     Scatter ghost points to local vector,using the 2-step process
        DMGlobalToLocalBegin(),DMGlobalToLocalEnd().
     By placing code between these two statements, computations can be
     done while messages are in transition.
  */
  PetscCall(DMGlobalToLocalBegin(da, U, INSERT_VALUES, localU));
  PetscCall(DMGlobalToLocalEnd(da, U, INSERT_VALUES, localU));

  /*
     Get pointers to vector data
  */
  PetscCall(DMDAVecGetArrayRead(da, localU, &u));
  PetscCall(DMDAVecGetArray(da, F, &f));
  PetscCall(DMDAVecGetArrayRead(da, Udot, &udot));

  /*
    Create contiguous 1-arrays of AFields

    NOTE: Memory for ADOL-C active variables (such as adouble and AField)
          cannot be allocated using PetscMalloc, as this does not call the
          relevant class constructor. Instead, we use the C++ keyword `new`.
  */
  u_c = new AField[info.gxm * info.gym];
  f_c = new AField[info.gxm * info.gym];

  /* Create corresponding 2-arrays of AFields */
  u_a = new AField *[info.gym];
  f_a = new AField *[info.gym];

  /* Align indices between array types to endow 2d array with ghost points */
  PetscCall(GiveGhostPoints(da, u_c, &u_a));
  PetscCall(GiveGhostPoints(da, f_c, &f_a));

  trace_on(1); /* Start of active section on tape 1 */

  /*
    Mark independence

    NOTE: Ghost points are marked as independent, in place of the points they represent on
          other processors / on other boundaries.
  */
  for (j = gys; j < gys + gym; j++) {
    for (i = gxs; i < gxs + gxm; i++) {
      u_a[j][i].u <<= u[j][i].u;
      u_a[j][i].v <<= u[j][i].v;
    }
  }

  /* Compute function over the locally owned part of the grid */
  for (j = ys; j < ys + ym; j++) {
    for (i = xs; i < xs + xm; i++) {
      uc          = u_a[j][i].u;
      uxx         = (-2.0 * uc + u_a[j][i - 1].u + u_a[j][i + 1].u) * sx;
      uyy         = (-2.0 * uc + u_a[j - 1][i].u + u_a[j + 1][i].u) * sy;
      vc          = u_a[j][i].v;
      vxx         = (-2.0 * vc + u_a[j][i - 1].v + u_a[j][i + 1].v) * sx;
      vyy         = (-2.0 * vc + u_a[j - 1][i].v + u_a[j + 1][i].v) * sy;
      f_a[j][i].u = udot[j][i].u - appctx->D1 * (uxx + uyy) + uc * vc * vc - appctx->gamma * (1.0 - uc);
      f_a[j][i].v = udot[j][i].v - appctx->D2 * (vxx + vyy) - uc * vc * vc + (appctx->gamma + appctx->kappa) * vc;
    }
  }

  /*
    Mark dependence

    NOTE: Marking dependence of dummy variables makes the index notation much simpler when forming
          the Jacobian later.
  */
  for (j = gys; j < gys + gym; j++) {
    for (i = gxs; i < gxs + gxm; i++) {
      if ((i < xs) || (i >= xs + xm) || (j < ys) || (j >= ys + ym)) {
        f_a[j][i].u >>= dummy;
        f_a[j][i].v >>= dummy;
      } else {
        f_a[j][i].u >>= f[j][i].u;
        f_a[j][i].v >>= f[j][i].v;
      }
    }
  }
  trace_off(); /* End of active section */
  PetscCall(PetscLogFlops(16.0 * xm * ym));

  /* Restore vectors */
  PetscCall(DMDAVecRestoreArray(da, F, &f));
  PetscCall(DMDAVecRestoreArrayRead(da, localU, &u));
  PetscCall(DMDAVecRestoreArrayRead(da, Udot, &udot));

  PetscCall(DMRestoreLocalVector(da, &localU));

  /* Destroy AFields appropriately */
  f_a += info.gys;
  u_a += info.gys;
  delete[] f_a;
  delete[] u_a;
  delete[] f_c;
  delete[] u_c;
  PetscFunctionReturn(PETSC_SUCCESS);
}

/*
  Simply acts to pass TS information to the AdolcMatCtx
*/
PetscErrorCode IJacobianMatFree(TS ts, PetscReal t, Vec X, Vec Xdot, PetscReal a, Mat A_shell, Mat B, PetscCtx ctx)
{
  AdolcMatCtx *mctx;
  DM           da;

  PetscFunctionBeginUser;
  PetscCall(MatShellGetContext(A_shell, &mctx));

  mctx->time  = t;
  mctx->shift = a;
  if (mctx->ts != ts) mctx->ts = ts;
  PetscCall(VecCopy(X, mctx->X));
  PetscCall(VecCopy(Xdot, mctx->Xdot));
  PetscCall(TSGetDM(ts, &da));
  PetscCall(DMGlobalToLocalBegin(da, mctx->X, INSERT_VALUES, mctx->localX0));
  PetscCall(DMGlobalToLocalEnd(da, mctx->X, INSERT_VALUES, mctx->localX0));
  PetscFunctionReturn(PETSC_SUCCESS);
}

/*TEST

  build:
    requires: double !complex adolc

  test:
    suffix: 1
    args: -ts_max_steps 1 -da_grid_x 12 -da_grid_y 12 -snes_test_jacobian
    output_file: output/adr_ex5adj_mf_1.out

  test:
    suffix: 2
    nsize: 4
    args: -ts_max_steps 10 -da_grid_x 12 -da_grid_y 12 -ts_monitor -ts_adjoint_monitor
    output_file: output/adr_ex5adj_mf_2.out

TEST*/