C++ PetscLogEventEnd函数代码示例

/*@
  TaoComputeObjective - Computes the objective function value at a given point

  Collective on Tao

  Input Parameters:
+ tao - the Tao context
- X - input vector

  Output Parameter:
. f - Objective value at X

  Notes: TaoComputeObjective() is typically used within minimization implementations,
  so most users would not generally call this routine themselves.

  Level: advanced

.seealso: TaoComputeGradient(), TaoComputeObjectiveAndGradient(), TaoSetObjectiveRoutine()
@*/
PetscErrorCode TaoComputeObjective(Tao tao, Vec X, PetscReal *f)
{
  PetscErrorCode ierr;
  Vec            temp;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(tao,TAO_CLASSID,1);
  PetscValidHeaderSpecific(X,VEC_CLASSID,2);
  PetscCheckSameComm(tao,1,X,2);
  if (tao->ops->computeobjective) {
    ierr = PetscLogEventBegin(Tao_ObjectiveEval,tao,X,NULL,NULL);CHKERRQ(ierr);
    PetscStackPush("Tao user objective evaluation routine");
    ierr = (*tao->ops->computeobjective)(tao,X,f,tao->user_objP);CHKERRQ(ierr);
    PetscStackPop;
    ierr = PetscLogEventEnd(Tao_ObjectiveEval,tao,X,NULL,NULL);CHKERRQ(ierr);
    tao->nfuncs++;
  } else if (tao->ops->computeobjectiveandgradient) {
    ierr = PetscInfo(tao,"Duplicating variable vector in order to call func/grad routine\n");CHKERRQ(ierr);
    ierr = VecDuplicate(X,&temp);CHKERRQ(ierr);
    ierr = PetscLogEventBegin(Tao_ObjGradientEval,tao,X,NULL,NULL);CHKERRQ(ierr);
    PetscStackPush("Tao user objective/gradient evaluation routine");
    ierr = (*tao->ops->computeobjectiveandgradient)(tao,X,f,temp,tao->user_objgradP);CHKERRQ(ierr);
    PetscStackPop;
    ierr = PetscLogEventEnd(Tao_ObjGradientEval,tao,X,NULL,NULL);CHKERRQ(ierr);
    ierr = VecDestroy(&temp);CHKERRQ(ierr);
    tao->nfuncgrads++;
  }  else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"TaoSetObjectiveRoutine() has not been called");
  ierr = PetscInfo1(tao,"TAO Function evaluation: %14.12e\n",(double)(*f));CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

/*@
  TaoComputeGradient - Computes the gradient of the objective function

  Collective on Tao

  Input Parameters:
+ tao - the Tao context
- X - input vector

  Output Parameter:
. G - gradient vector

  Notes: TaoComputeGradient() is typically used within minimization implementations,
  so most users would not generally call this routine themselves.

  Level: advanced

.seealso: TaoComputeObjective(), TaoComputeObjectiveAndGradient(), TaoSetGradientRoutine()
@*/
PetscErrorCode TaoComputeGradient(Tao tao, Vec X, Vec G)
{
  PetscErrorCode ierr;
  PetscReal      dummy;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(tao,TAO_CLASSID,1);
  PetscValidHeaderSpecific(X,VEC_CLASSID,2);
  PetscValidHeaderSpecific(G,VEC_CLASSID,2);
  PetscCheckSameComm(tao,1,X,2);
  PetscCheckSameComm(tao,1,G,3);
  if (tao->ops->computegradient) {
    ierr = PetscLogEventBegin(Tao_GradientEval,tao,X,G,NULL);CHKERRQ(ierr);
    PetscStackPush("Tao user gradient evaluation routine");
    ierr = (*tao->ops->computegradient)(tao,X,G,tao->user_gradP);CHKERRQ(ierr);
    PetscStackPop;
    ierr = PetscLogEventEnd(Tao_GradientEval,tao,X,G,NULL);CHKERRQ(ierr);
    tao->ngrads++;
  } else if (tao->ops->computeobjectiveandgradient) {
    ierr = PetscLogEventBegin(Tao_ObjGradientEval,tao,X,G,NULL);CHKERRQ(ierr);
    PetscStackPush("Tao user objective/gradient evaluation routine");
    ierr = (*tao->ops->computeobjectiveandgradient)(tao,X,&dummy,G,tao->user_objgradP);CHKERRQ(ierr);
    PetscStackPop;
    ierr = PetscLogEventEnd(Tao_ObjGradientEval,tao,X,G,NULL);CHKERRQ(ierr);
    tao->nfuncgrads++;
  }  else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"TaoSetGradientRoutine() has not been called");
  PetscFunctionReturn(0);
}

PetscErrorCode PCMGACycle_Private(PC pc,PC_MG_Levels **mglevels)
{
  PetscErrorCode ierr;
  PetscInt       i,l = mglevels[0]->levels;

  PetscFunctionBegin;
  /* compute RHS on each level */
  for (i=l-1; i>0; i--) {
    if (mglevels[i]->eventinterprestrict) {ierr = PetscLogEventBegin(mglevels[i]->eventinterprestrict,0,0,0,0);CHKERRQ(ierr);}
    ierr = MatRestrict(mglevels[i]->restrct,mglevels[i]->b,mglevels[i-1]->b);CHKERRQ(ierr);
    if (mglevels[i]->eventinterprestrict) {ierr = PetscLogEventEnd(mglevels[i]->eventinterprestrict,0,0,0,0);CHKERRQ(ierr);}
  }
  /* solve separately on each level */
  for (i=0; i<l; i++) {
    ierr = VecSet(mglevels[i]->x,0.0);CHKERRQ(ierr);
    if (mglevels[i]->eventsmoothsolve) {ierr = PetscLogEventBegin(mglevels[i]->eventsmoothsolve,0,0,0,0);CHKERRQ(ierr);}
    ierr = KSPSolve(mglevels[i]->smoothd,mglevels[i]->b,mglevels[i]->x);CHKERRQ(ierr);
    ierr = KSPCheckSolve(mglevels[i]->smoothd,pc,mglevels[i]->x);CHKERRQ(ierr);
    if (mglevels[i]->eventsmoothsolve) {ierr = PetscLogEventEnd(mglevels[i]->eventsmoothsolve,0,0,0,0);CHKERRQ(ierr);}
  }
  for (i=1; i<l; i++) {
    if (mglevels[i]->eventinterprestrict) {ierr = PetscLogEventBegin(mglevels[i]->eventinterprestrict,0,0,0,0);CHKERRQ(ierr);}
    ierr = MatInterpolateAdd(mglevels[i]->interpolate,mglevels[i-1]->x,mglevels[i]->x,mglevels[i]->x);CHKERRQ(ierr);
    if (mglevels[i]->eventinterprestrict) {ierr = PetscLogEventEnd(mglevels[i]->eventinterprestrict,0,0,0,0);CHKERRQ(ierr);}
  }
  PetscFunctionReturn(0);
}

PetscErrorCode MatPtAP_SeqAIJ_SeqAIJ(Mat A,Mat P,MatReuse scall,PetscReal fill,Mat *C)
{
  PetscErrorCode ierr;
  const char     *algTypes[2] = {"scalable","nonscalable"};
  PetscInt       alg=0; /* set default algorithm */

  PetscFunctionBegin;
  if (scall == MAT_INITIAL_MATRIX) {
    /* 
     Alg 'scalable' determines which implementations to be used:
       "nonscalable": do dense axpy in MatPtAPNumeric() - fastest, but requires storage of struct A*P;
       "scalable":    do two sparse axpy in MatPtAPNumeric() - might slow, does not store structure of A*P. 
     */
    ierr = PetscObjectOptionsBegin((PetscObject)A);CHKERRQ(ierr);
    ierr = PetscOptionsEList("-matptap_via","Algorithmic approach","MatPtAP",algTypes,2,algTypes[0],&alg,NULL);CHKERRQ(ierr);
    ierr = PetscOptionsEnd();CHKERRQ(ierr);
    ierr = PetscLogEventBegin(MAT_PtAPSymbolic,A,P,0,0);CHKERRQ(ierr);
    switch (alg) {
    case 1:
      ierr = MatPtAPSymbolic_SeqAIJ_SeqAIJ_DenseAxpy(A,P,fill,C);CHKERRQ(ierr);
      break;
    default:
      ierr = MatPtAPSymbolic_SeqAIJ_SeqAIJ_SparseAxpy(A,P,fill,C);CHKERRQ(ierr);
      break;
    }
    ierr = PetscLogEventEnd(MAT_PtAPSymbolic,A,P,0,0);CHKERRQ(ierr);
  }
  ierr = PetscLogEventBegin(MAT_PtAPNumeric,A,P,0,0);CHKERRQ(ierr);
  ierr = (*(*C)->ops->ptapnumeric)(A,P,*C);CHKERRQ(ierr);
  ierr = PetscLogEventEnd(MAT_PtAPNumeric,A,P,0,0);CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

PetscErrorCode PCMGKCycle_Private(PC pc,PC_MG_Levels **mglevels)
{
  PetscErrorCode ierr;
  PetscInt       i,l = mglevels[0]->levels;

  PetscFunctionBegin;
  /* restrict the RHS through all levels to coarsest. */
  for (i=l-1; i>0; i--){
    if (mglevels[i]->eventinterprestrict) {ierr = PetscLogEventBegin(mglevels[i]->eventinterprestrict,0,0,0,0);CHKERRQ(ierr);}
    ierr = MatRestrict(mglevels[i]->restrct,mglevels[i]->b,mglevels[i-1]->b);CHKERRQ(ierr); 
    if (mglevels[i]->eventinterprestrict) {ierr = PetscLogEventEnd(mglevels[i]->eventinterprestrict,0,0,0,0);CHKERRQ(ierr);}
  }
  
  /* work our way up through the levels */
  ierr = VecSet(mglevels[0]->x,0.0);CHKERRQ(ierr); 
  for (i=0; i<l-1; i++) {
    if (mglevels[i]->eventsmoothsolve) {ierr = PetscLogEventBegin(mglevels[i]->eventsmoothsolve,0,0,0,0);CHKERRQ(ierr);}
    ierr = KSPSolve(mglevels[i]->smoothd,mglevels[i]->b,mglevels[i]->x);CHKERRQ(ierr);
    if (mglevels[i]->eventsmoothsolve) {ierr = PetscLogEventEnd(mglevels[i]->eventsmoothsolve,0,0,0,0);CHKERRQ(ierr);}
    if (mglevels[i+1]->eventinterprestrict) {ierr = PetscLogEventBegin(mglevels[i+1]->eventinterprestrict,0,0,0,0);CHKERRQ(ierr);}
    ierr = MatInterpolate(mglevels[i+1]->interpolate,mglevels[i]->x,mglevels[i+1]->x);CHKERRQ(ierr);
    if (mglevels[i+1]->eventinterprestrict) {ierr = PetscLogEventEnd(mglevels[i+1]->eventinterprestrict,0,0,0,0);CHKERRQ(ierr);}
  }
  if (mglevels[l-1]->eventsmoothsolve) {ierr = PetscLogEventBegin(mglevels[l-1]->eventsmoothsolve,0,0,0,0);CHKERRQ(ierr);}
  ierr = KSPSolve(mglevels[l-1]->smoothd,mglevels[l-1]->b,mglevels[l-1]->x);CHKERRQ(ierr);
  if (mglevels[l-1]->eventsmoothsolve) {ierr = PetscLogEventEnd(mglevels[l-1]->eventsmoothsolve,0,0,0,0);CHKERRQ(ierr);}

  PetscFunctionReturn(0);
}

/*

Performs the FAS coarse correction as:

fine problem:   F(x) = b
coarse problem: F^c(x^c) = b^c

b^c = F^c(Rx) - R(F(x) - b)

 */
PetscErrorCode SNESFASCoarseCorrection(SNES snes, Vec X, Vec F, Vec X_new)
{
  PetscErrorCode      ierr;
  Vec                 X_c, Xo_c, F_c, B_c;
  SNESConvergedReason reason;
  SNES                next;
  Mat                 restrct, interpolate;
  SNES_FAS            *fasc;

  PetscFunctionBegin;
  ierr = SNESFASCycleGetCorrection(snes, &next);CHKERRQ(ierr);
  if (next) {
    fasc = (SNES_FAS*)next->data;

    ierr = SNESFASCycleGetRestriction(snes, &restrct);CHKERRQ(ierr);
    ierr = SNESFASCycleGetInterpolation(snes, &interpolate);CHKERRQ(ierr);

    X_c  = next->vec_sol;
    Xo_c = next->work[0];
    F_c  = next->vec_func;
    B_c  = next->vec_rhs;

    if (fasc->eventinterprestrict) {ierr = PetscLogEventBegin(fasc->eventinterprestrict,0,0,0,0);CHKERRQ(ierr);}
    ierr = SNESFASRestrict(snes,X,Xo_c);CHKERRQ(ierr);
    /* restrict the defect: R(F(x) - b) */
    ierr = MatRestrict(restrct, F, B_c);CHKERRQ(ierr);
    if (fasc->eventinterprestrict) {ierr = PetscLogEventEnd(fasc->eventinterprestrict,0,0,0,0);CHKERRQ(ierr);}

    if (fasc->eventresidual) {ierr = PetscLogEventBegin(fasc->eventresidual,0,0,0,0);CHKERRQ(ierr);}
    /* F_c = F^c(Rx) - R(F(x) - b) since the second term was sitting in next->vec_rhs */
    ierr = SNESComputeFunction(next, Xo_c, F_c);CHKERRQ(ierr);
    if (fasc->eventresidual) {ierr = PetscLogEventEnd(fasc->eventresidual,0,0,0,0);CHKERRQ(ierr);}

    /* solve the coarse problem corresponding to F^c(x^c) = b^c = F^c(Rx) - R(F(x) - b) */
    ierr = VecCopy(B_c, X_c);CHKERRQ(ierr);
    ierr = VecCopy(F_c, B_c);CHKERRQ(ierr);
    ierr = VecCopy(X_c, F_c);CHKERRQ(ierr);
    /* set initial guess of the coarse problem to the projected fine solution */
    ierr = VecCopy(Xo_c, X_c);CHKERRQ(ierr);

    /* recurse to the next level */
    ierr = SNESSetInitialFunction(next, F_c);CHKERRQ(ierr);
    ierr = SNESSolve(next, B_c, X_c);CHKERRQ(ierr);
    ierr = SNESGetConvergedReason(next,&reason);CHKERRQ(ierr);
    if (reason < 0 && reason != SNES_DIVERGED_MAX_IT) {
      snes->reason = SNES_DIVERGED_INNER;
      PetscFunctionReturn(0);
    }
    /* correct as x <- x + I(x^c - Rx)*/
    ierr = VecAXPY(X_c, -1.0, Xo_c);CHKERRQ(ierr);

    if (fasc->eventinterprestrict) {ierr = PetscLogEventBegin(fasc->eventinterprestrict,0,0,0,0);CHKERRQ(ierr);}
    ierr = MatInterpolateAdd(interpolate, X_c, X, X_new);CHKERRQ(ierr);
    if (fasc->eventinterprestrict) {ierr = PetscLogEventEnd(fasc->eventinterprestrict,0,0,0,0);CHKERRQ(ierr);}
  }
  PetscFunctionReturn(0);
}

PetscErrorCode PCMGMCycle_Private(PC pc,PC_MG_Levels **mglevelsin,PCRichardsonConvergedReason *reason)
{
  PC_MG          *mg = (PC_MG*)pc->data;
  PC_MG_Levels   *mgc,*mglevels = *mglevelsin;
  PetscErrorCode ierr;
  PetscInt       cycles = (mglevels->level == 1) ? 1 : (PetscInt) mglevels->cycles;
  PC             subpc;
  PCFailedReason pcreason;

  PetscFunctionBegin;
  if (mglevels->eventsmoothsolve) {ierr = PetscLogEventBegin(mglevels->eventsmoothsolve,0,0,0,0);CHKERRQ(ierr);}
  ierr = KSPSolve(mglevels->smoothd,mglevels->b,mglevels->x);CHKERRQ(ierr);  /* pre-smooth */
  ierr = KSPGetPC(mglevels->smoothd,&subpc);CHKERRQ(ierr);
  ierr = PCGetSetUpFailedReason(subpc,&pcreason);CHKERRQ(ierr); 
  if (pcreason) {
    pc->failedreason = PC_SUBPC_ERROR;
  }
  if (mglevels->eventsmoothsolve) {ierr = PetscLogEventEnd(mglevels->eventsmoothsolve,0,0,0,0);CHKERRQ(ierr);}
  if (mglevels->level) {  /* not the coarsest grid */
    if (mglevels->eventresidual) {ierr = PetscLogEventBegin(mglevels->eventresidual,0,0,0,0);CHKERRQ(ierr);}
    ierr = (*mglevels->residual)(mglevels->A,mglevels->b,mglevels->x,mglevels->r);CHKERRQ(ierr);
    if (mglevels->eventresidual) {ierr = PetscLogEventEnd(mglevels->eventresidual,0,0,0,0);CHKERRQ(ierr);}

    /* if on finest level and have convergence criteria set */
    if (mglevels->level == mglevels->levels-1 && mg->ttol && reason) {
      PetscReal rnorm;
      ierr = VecNorm(mglevels->r,NORM_2,&rnorm);CHKERRQ(ierr);
      if (rnorm <= mg->ttol) {
        if (rnorm < mg->abstol) {
          *reason = PCRICHARDSON_CONVERGED_ATOL;
          ierr    = PetscInfo2(pc,"Linear solver has converged. Residual norm %g is less than absolute tolerance %g\n",(double)rnorm,(double)mg->abstol);CHKERRQ(ierr);
        } else {
          *reason = PCRICHARDSON_CONVERGED_RTOL;
          ierr    = PetscInfo2(pc,"Linear solver has converged. Residual norm %g is less than relative tolerance times initial residual norm %g\n",(double)rnorm,(double)mg->ttol);CHKERRQ(ierr);
        }
        PetscFunctionReturn(0);
      }
    }

    mgc = *(mglevelsin - 1);
    if (mglevels->eventinterprestrict) {ierr = PetscLogEventBegin(mglevels->eventinterprestrict,0,0,0,0);CHKERRQ(ierr);}
    ierr = MatRestrict(mglevels->restrct,mglevels->r,mgc->b);CHKERRQ(ierr);
    if (mglevels->eventinterprestrict) {ierr = PetscLogEventEnd(mglevels->eventinterprestrict,0,0,0,0);CHKERRQ(ierr);}
    ierr = VecSet(mgc->x,0.0);CHKERRQ(ierr);
    while (cycles--) {
      ierr = PCMGMCycle_Private(pc,mglevelsin-1,reason);CHKERRQ(ierr);
    }
    if (mglevels->eventinterprestrict) {ierr = PetscLogEventBegin(mglevels->eventinterprestrict,0,0,0,0);CHKERRQ(ierr);}
    ierr = MatInterpolateAdd(mglevels->interpolate,mgc->x,mglevels->x,mglevels->x);CHKERRQ(ierr);
    if (mglevels->eventinterprestrict) {ierr = PetscLogEventEnd(mglevels->eventinterprestrict,0,0,0,0);CHKERRQ(ierr);}
    if (mglevels->eventsmoothsolve) {ierr = PetscLogEventBegin(mglevels->eventsmoothsolve,0,0,0,0);CHKERRQ(ierr);}
    ierr = KSPSolve(mglevels->smoothu,mglevels->b,mglevels->x);CHKERRQ(ierr);    /* post smooth */
    if (mglevels->eventsmoothsolve) {ierr = PetscLogEventEnd(mglevels->eventsmoothsolve,0,0,0,0);CHKERRQ(ierr);}
  }
  PetscFunctionReturn(0);
}

static PetscErrorCode SNESComputeFunction_DMDA(SNES snes,Vec X,Vec F,void *ctx)
{
  PetscErrorCode ierr;
  DM             dm;
  DMSNES_DA      *dmdasnes = (DMSNES_DA*)ctx;
  DMDALocalInfo  info;
  Vec            Xloc;
  void           *x,*f;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(snes,SNES_CLASSID,1);
  PetscValidHeaderSpecific(X,VEC_CLASSID,2);
  PetscValidHeaderSpecific(F,VEC_CLASSID,3);
  if (!dmdasnes->residuallocal) SETERRQ(PetscObjectComm((PetscObject)snes),PETSC_ERR_PLIB,"Corrupt context");
  ierr = SNESGetDM(snes,&dm);CHKERRQ(ierr);
  ierr = DMGetLocalVector(dm,&Xloc);CHKERRQ(ierr);
  ierr = DMGlobalToLocalBegin(dm,X,INSERT_VALUES,Xloc);CHKERRQ(ierr);
  ierr = DMGlobalToLocalEnd(dm,X,INSERT_VALUES,Xloc);CHKERRQ(ierr);
  ierr = DMDAGetLocalInfo(dm,&info);CHKERRQ(ierr);
  ierr = DMDAVecGetArray(dm,Xloc,&x);CHKERRQ(ierr);
  switch (dmdasnes->residuallocalimode) {
  case INSERT_VALUES: {
    ierr = DMDAVecGetArray(dm,F,&f);CHKERRQ(ierr);
    ierr = PetscLogEventBegin(SNES_FunctionEval,snes,X,F,0);CHKERRQ(ierr);
    CHKMEMQ;
    ierr = (*dmdasnes->residuallocal)(&info,x,f,dmdasnes->residuallocalctx);CHKERRQ(ierr);
    CHKMEMQ;
    ierr = PetscLogEventEnd(SNES_FunctionEval,snes,X,F,0);CHKERRQ(ierr);
    ierr = DMDAVecRestoreArray(dm,F,&f);CHKERRQ(ierr);
  } break;
  case ADD_VALUES: {
    Vec Floc;
    ierr = DMGetLocalVector(dm,&Floc);CHKERRQ(ierr);
    ierr = VecZeroEntries(Floc);CHKERRQ(ierr);
    ierr = DMDAVecGetArray(dm,Floc,&f);CHKERRQ(ierr);
    ierr = PetscLogEventBegin(SNES_FunctionEval,snes,X,F,0);CHKERRQ(ierr);
    CHKMEMQ;
    ierr = (*dmdasnes->residuallocal)(&info,x,f,dmdasnes->residuallocalctx);CHKERRQ(ierr);
    CHKMEMQ;
    ierr = PetscLogEventEnd(SNES_FunctionEval,snes,X,F,0);CHKERRQ(ierr);
    ierr = DMDAVecRestoreArray(dm,Floc,&f);CHKERRQ(ierr);
    ierr = VecZeroEntries(F);CHKERRQ(ierr);
    ierr = DMLocalToGlobalBegin(dm,Floc,ADD_VALUES,F);CHKERRQ(ierr);
    ierr = DMLocalToGlobalEnd(dm,Floc,ADD_VALUES,F);CHKERRQ(ierr);
    ierr = DMRestoreLocalVector(dm,&Floc);CHKERRQ(ierr);
  } break;
  default: SETERRQ1(PetscObjectComm((PetscObject)snes),PETSC_ERR_ARG_INCOMP,"Cannot use imode=%d",(int)dmdasnes->residuallocalimode);
  }
  ierr = DMDAVecRestoreArray(dm,Xloc,&x);CHKERRQ(ierr);
  ierr = DMRestoreLocalVector(dm,&Xloc);CHKERRQ(ierr);
  if (snes->domainerror) {
    ierr = VecSetInf(F);CHKERRQ(ierr);
  }
  PetscFunctionReturn(0);
}

/*@
  TaoComputeObjectiveAndGradient - Computes the objective function value at a given point

  Collective on Tao

  Input Parameters:
+ tao - the Tao context
- X - input vector

  Output Parameter:
+ f - Objective value at X
- g - Gradient vector at X

  Notes: TaoComputeObjectiveAndGradient() is typically used within minimization implementations,
  so most users would not generally call this routine themselves.

  Level: advanced

.seealso: TaoComputeGradient(), TaoComputeObjectiveAndGradient(), TaoSetObjectiveRoutine()
@*/
PetscErrorCode TaoComputeObjectiveAndGradient(Tao tao, Vec X, PetscReal *f, Vec G)
{
    PetscErrorCode ierr;

    PetscFunctionBegin;
    PetscValidHeaderSpecific(tao,TAO_CLASSID,1);
    PetscValidHeaderSpecific(X,VEC_CLASSID,2);
    PetscValidHeaderSpecific(G,VEC_CLASSID,4);
    PetscCheckSameComm(tao,1,X,2);
    PetscCheckSameComm(tao,1,G,4);
    if (tao->ops->computeobjectiveandgradient) {
        ierr = PetscLogEventBegin(Tao_ObjGradientEval,tao,X,G,NULL);
        CHKERRQ(ierr);
        PetscStackPush("Tao user objective/gradient evaluation routine");
        ierr = (*tao->ops->computeobjectiveandgradient)(tao,X,f,G,tao->user_objgradP);
        CHKERRQ(ierr);
        PetscStackPop;
        if (tao->ops->computegradient == TaoDefaultComputeGradient) {
            /* Overwrite gradient with finite difference gradient */
            ierr = TaoDefaultComputeGradient(tao,X,G,tao->user_objgradP);
            CHKERRQ(ierr);
        }
        ierr = PetscLogEventEnd(Tao_ObjGradientEval,tao,X,G,NULL);
        CHKERRQ(ierr);
        tao->nfuncgrads++;
    } else if (tao->ops->computeobjective && tao->ops->computegradient) {
        ierr = PetscLogEventBegin(Tao_ObjectiveEval,tao,X,NULL,NULL);
        CHKERRQ(ierr);
        PetscStackPush("Tao user objective evaluation routine");
        ierr = (*tao->ops->computeobjective)(tao,X,f,tao->user_objP);
        CHKERRQ(ierr);
        PetscStackPop;
        ierr = PetscLogEventEnd(Tao_ObjectiveEval,tao,X,NULL,NULL);
        CHKERRQ(ierr);
        tao->nfuncs++;
        ierr = PetscLogEventBegin(Tao_GradientEval,tao,X,G,NULL);
        CHKERRQ(ierr);
        PetscStackPush("Tao user gradient evaluation routine");
        ierr = (*tao->ops->computegradient)(tao,X,G,tao->user_gradP);
        CHKERRQ(ierr);
        PetscStackPop;
        ierr = PetscLogEventEnd(Tao_GradientEval,tao,X,G,NULL);
        CHKERRQ(ierr);
        tao->ngrads++;
    } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"TaoSetObjectiveRoutine() or TaoSetGradientRoutine() not set");
    ierr = PetscInfo1(tao,"TAO Function evaluation: %14.12e\n",(double)(*f));
    CHKERRQ(ierr);
    PetscFunctionReturn(0);
}

PetscErrorCode MatPtAP_SeqAIJ_SeqAIJ(Mat A,Mat P,MatReuse scall,PetscReal fill,Mat *C)
{
  PetscErrorCode ierr;

  PetscFunctionBegin;
  if (scall == MAT_INITIAL_MATRIX) {
    ierr = PetscLogEventBegin(MAT_PtAPSymbolic,A,P,0,0);CHKERRQ(ierr);
    ierr = MatPtAPSymbolic_SeqAIJ_SeqAIJ(A,P,fill,C);CHKERRQ(ierr);
    ierr = PetscLogEventEnd(MAT_PtAPSymbolic,A,P,0,0);CHKERRQ(ierr);
  }
  ierr = PetscLogEventBegin(MAT_PtAPNumeric,A,P,0,0);CHKERRQ(ierr);
  ierr = (*(*C)->ops->ptapnumeric)(A,P,*C);CHKERRQ(ierr);
  ierr = PetscLogEventEnd(MAT_PtAPNumeric,A,P,0,0);CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

PetscErrorCode MatTransposeMatMult_SeqAIJ_SeqDense(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C)
{
  PetscErrorCode ierr;
 
  PetscFunctionBegin;
  if (scall == MAT_INITIAL_MATRIX) {
    ierr = PetscLogEventBegin(MAT_TransposeMatMultSymbolic,A,B,0,0);CHKERRQ(ierr);
    ierr = MatTransposeMatMultSymbolic_SeqAIJ_SeqDense(A,B,fill,C);CHKERRQ(ierr);
    ierr = PetscLogEventEnd(MAT_TransposeMatMultSymbolic,A,B,0,0);CHKERRQ(ierr);
  } 
  ierr = PetscLogEventBegin(MAT_TransposeMatMultNumeric,A,B,0,0);CHKERRQ(ierr);
  ierr = MatTransposeMatMultNumeric_SeqAIJ_SeqDense(A,B,*C);CHKERRQ(ierr);
  ierr = PetscLogEventEnd(MAT_TransposeMatMultNumeric,A,B,0,0);CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

/*@
   MatColoringApply - Apply the coloring to the matrix, producing index
   sets corresponding to a number of independent sets in the induced
   graph.

   Collective on MatColoring

   Input Parameters:
.  mc - the MatColoring context

   Output Parameter:
.  coloring - the ISColoring instance containing the coloring

   Level: beginner

.keywords: Coloring, Apply

.seealso: MatColoring, MatColoringCreate()
@*/
PetscErrorCode MatColoringApply(MatColoring mc,ISColoring *coloring)
{
  PetscErrorCode    ierr;
  PetscBool         flg;
  PetscViewerFormat format;
  PetscViewer       viewer;
  PetscInt          nc,ncolors;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mc,MAT_COLORING_CLASSID,1);
  ierr = PetscLogEventBegin(Mat_Coloring_Apply,mc,0,0,0);CHKERRQ(ierr);
  ierr = (*mc->ops->apply)(mc,coloring);CHKERRQ(ierr);
  ierr = PetscLogEventEnd(Mat_Coloring_Apply,mc,0,0,0);CHKERRQ(ierr);
  /* valid */
  if (mc->valid) {
    ierr = MatColoringTestValid(mc,*coloring);CHKERRQ(ierr);
  }
  /* view */
  ierr = PetscOptionsGetViewer(PetscObjectComm((PetscObject)mc),((PetscObject)mc)->prefix,"-mat_coloring_view",&viewer,&format,&flg);CHKERRQ(ierr);
  if (flg && !PetscPreLoadingOn) {
    ierr = PetscViewerPushFormat(viewer,format);CHKERRQ(ierr);
    ierr = MatColoringView(mc,viewer);CHKERRQ(ierr);
    ierr = MatGetSize(mc->mat,NULL,&nc);CHKERRQ(ierr);
    ierr = ISColoringGetIS(*coloring,&ncolors,NULL);CHKERRQ(ierr);
    ierr = PetscViewerASCIIPrintf(viewer,"  Number of colors %d\n",ncolors);CHKERRQ(ierr);
    ierr = PetscViewerASCIIPrintf(viewer,"  Number of total columns %d\n",nc);CHKERRQ(ierr);
    if (nc <= 1000) {ierr = ISColoringView(*coloring,viewer);CHKERRQ(ierr);}
    ierr = PetscViewerPopFormat(viewer);CHKERRQ(ierr);
    ierr = PetscViewerDestroy(&viewer);CHKERRQ(ierr);
  }
  PetscFunctionReturn(0);
}

/*@
  DMPlexDistributeField - Distribute field data to match a given PetscSF, usually the SF from mesh distribution

  Collective on DM

  Input Parameters:
+ dm - The DMPlex object
. pointSF - The PetscSF describing the communication pattern
. originalSection - The PetscSection for existing data layout
- originalVec - The existing data

  Output Parameters:
+ newSection - The PetscSF describing the new data layout
- newVec - The new data

  Level: developer

.seealso: DMPlexDistribute(), DMPlexDistributeData()
@*/
PetscErrorCode DMPlexDistributeField(DM dm, PetscSF pointSF, PetscSection originalSection, Vec originalVec, PetscSection newSection, Vec newVec)
{
  PetscSF        fieldSF;
  PetscInt      *remoteOffsets, fieldSize;
  PetscScalar   *originalValues, *newValues;
  PetscErrorCode ierr;

  PetscFunctionBegin;
  ierr = PetscLogEventBegin(DMPLEX_DistributeField,dm,0,0,0);CHKERRQ(ierr);
  ierr = PetscSFDistributeSection(pointSF, originalSection, &remoteOffsets, newSection);CHKERRQ(ierr);

  ierr = PetscSectionGetStorageSize(newSection, &fieldSize);CHKERRQ(ierr);
  ierr = VecSetSizes(newVec, fieldSize, PETSC_DETERMINE);CHKERRQ(ierr);
  ierr = VecSetType(newVec,dm->vectype);CHKERRQ(ierr);

  ierr = VecGetArray(originalVec, &originalValues);CHKERRQ(ierr);
  ierr = VecGetArray(newVec, &newValues);CHKERRQ(ierr);
  ierr = PetscSFCreateSectionSF(pointSF, originalSection, remoteOffsets, newSection, &fieldSF);CHKERRQ(ierr);
  ierr = PetscSFBcastBegin(fieldSF, MPIU_SCALAR, originalValues, newValues);CHKERRQ(ierr);
  ierr = PetscSFBcastEnd(fieldSF, MPIU_SCALAR, originalValues, newValues);CHKERRQ(ierr);
  ierr = PetscSFDestroy(&fieldSF);CHKERRQ(ierr);
  ierr = VecRestoreArray(newVec, &newValues);CHKERRQ(ierr);
  ierr = VecRestoreArray(originalVec, &originalValues);CHKERRQ(ierr);
  ierr = PetscLogEventEnd(DMPLEX_DistributeField,dm,0,0,0);CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

/*@
   VecMTDotBegin - Starts a split phase transpose multiple dot product computation.

   Input Parameters:
+  x - the first vector
.  nv - number of vectors
.  y - array of  vectors
-  result - where the result will go (can be PETSC_NULL)

   Level: advanced

   Notes:
   Each call to VecMTDotBegin() should be paired with a call to VecMTDotEnd().

.seealso: VecMTDotEnd(), VecNormBegin(), VecNormEnd(), VecNorm(), VecDot(), VecMDot(), 
         VecDotBegin(), VecDotEnd(), VecMDotBegin(), VecMDotEnd(), PetscCommSplitReductionBegin()

@*/
PetscErrorCode  VecMTDotBegin(Vec x,PetscInt nv,const Vec y[],PetscScalar result[]) 
{
  PetscErrorCode      ierr;
  PetscSplitReduction *sr;
  MPI_Comm            comm;
  int                 i;

  PetscFunctionBegin;
  ierr = PetscObjectGetComm((PetscObject)x,&comm);CHKERRQ(ierr);
  ierr = PetscSplitReductionGet(comm,&sr);CHKERRQ(ierr);
  if (sr->state != STATE_BEGIN) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Called before all VecxxxEnd() called");
  for (i=0;i<nv;i++) {
    if (sr->numopsbegin+i >= sr->maxops) {
      ierr = PetscSplitReductionExtend(sr);CHKERRQ(ierr);
    }
    sr->reducetype[sr->numopsbegin+i] = REDUCE_SUM;
    sr->invecs[sr->numopsbegin+i]     = (void*)x;
  }
  if (!x->ops->mtdot_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Vector does not suppport local mdots");
  ierr = PetscLogEventBegin(VEC_ReduceArithmetic,0,0,0,0);CHKERRQ(ierr);
  ierr = (*x->ops->mdot_local)(x,nv,y,sr->lvalues+sr->numopsbegin);CHKERRQ(ierr);
  ierr = PetscLogEventEnd(VEC_ReduceArithmetic,0,0,0,0);CHKERRQ(ierr);
  sr->numopsbegin += nv;
  PetscFunctionReturn(0);
}

PetscErrorCode  VecLoad_Default(Vec newvec, PetscViewer viewer)
{
  PetscErrorCode ierr;
  PetscBool      isbinary;
#if defined(PETSC_HAVE_HDF5)
  PetscBool      ishdf5;
#endif

  PetscFunctionBegin;
  ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr);
#if defined(PETSC_HAVE_HDF5)
  ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERHDF5,&ishdf5);CHKERRQ(ierr);
#endif

#if defined(PETSC_HAVE_HDF5)
  if (ishdf5) {
    if (!((PetscObject)newvec)->name) {
      SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Since HDF5 format gives ASCII name for each object in file; must use VecLoad() after setting name of Vec with PetscObjectSetName()");
      ierr = PetscLogEventEnd(VEC_Load,viewer,0,0,0);CHKERRQ(ierr);
    }
    ierr = VecLoad_HDF5(newvec, viewer);CHKERRQ(ierr);
  } else
#endif
  {
    ierr = VecLoad_Binary(newvec, viewer);CHKERRQ(ierr);
  }
  PetscFunctionReturn(0);
}