Пример #1
0
void createOuterPC(OuterContext* ctx) {
  PCCreate(((ctx->data)->commAll), &(ctx->outerPC));
  PCSetType(ctx->outerPC, PCSHELL);
  PCShellSetName(ctx->outerPC, "RSD");
  PCShellSetContext(ctx->outerPC, ctx);
  PCShellSetApply(ctx->outerPC, &outerPCapply);
}
Пример #2
0
void PetscNonlinearSolver<T>::init ()
{
  // Initialize the data structures if not done so already.
  if (!this->initialized())
    {
      this->_is_initialized = true;

      PetscErrorCode ierr=0;

#if PETSC_VERSION_LESS_THAN(2,1,2)
      // At least until Petsc 2.1.1, the SNESCreate had a different calling syntax.
      // The second argument was of type SNESProblemType, and could have a value of
      // either SNES_NONLINEAR_EQUATIONS or SNES_UNCONSTRAINED_MINIMIZATION.
      ierr = SNESCreate(this->comm().get(), SNES_NONLINEAR_EQUATIONS, &_snes);
             LIBMESH_CHKERRABORT(ierr);

#else

      ierr = SNESCreate(this->comm().get(),&_snes);
             LIBMESH_CHKERRABORT(ierr);

#endif


#if PETSC_VERSION_LESS_THAN(2,3,3)
      ierr = SNESSetMonitor (_snes, __libmesh_petsc_snes_monitor,
			     this, PETSC_NULL);
#else
      // API name change in PETSc 2.3.3
      ierr = SNESMonitorSet (_snes, __libmesh_petsc_snes_monitor,
			     this, PETSC_NULL);
#endif
      LIBMESH_CHKERRABORT(ierr);

#if PETSC_VERSION_LESS_THAN(3,1,0)
      // Cannot call SNESSetOptions before SNESSetFunction when using
      // any matrix free options with PETSc 3.1.0+
      ierr = SNESSetFromOptions(_snes);
             LIBMESH_CHKERRABORT(ierr);
#endif

      if(this->_preconditioner)
      {
        KSP ksp;
        ierr = SNESGetKSP (_snes, &ksp);
               LIBMESH_CHKERRABORT(ierr);
        PC pc;
        ierr = KSPGetPC(ksp,&pc);
               LIBMESH_CHKERRABORT(ierr);

        this->_preconditioner->init();

        PCSetType(pc, PCSHELL);
        PCShellSetContext(pc,(void*)this->_preconditioner);

        //Re-Use the shell functions from petsc_linear_solver
        PCShellSetSetUp(pc,__libmesh_petsc_preconditioner_setup);
        PCShellSetApply(pc,__libmesh_petsc_preconditioner_apply);
      }
    }
}
Пример #3
0
static int TaoSolve_BNLS(TAO_SOLVER tao, void*solver){

  TAO_BNLS *bnls = (TAO_BNLS *)solver;
  int info;
  TaoInt lsflag,iter=0;
  TaoTerminateReason reason=TAO_CONTINUE_ITERATING;
  double f,f_full,gnorm,gdx,stepsize=1.0;
  TaoTruth success;
  TaoVec *XU, *XL;
  TaoVec *X,  *G=bnls->G, *PG=bnls->PG;
  TaoVec *R=bnls->R, *DXFree=bnls->DXFree;
  TaoVec *DX=bnls->DX, *Work=bnls->Work;
  TaoMat *H, *Hsub=bnls->Hsub;
  TaoIndexSet *FreeVariables = bnls->FreeVariables;

  TaoFunctionBegin;

  /* Check if upper bound greater than lower bound. */
  info = TaoGetSolution(tao,&X);CHKERRQ(info); bnls->X=X;
  info = TaoGetVariableBounds(tao,&XL,&XU);CHKERRQ(info);
  info = TaoEvaluateVariableBounds(tao,XL,XU); CHKERRQ(info);
  info = TaoGetHessian(tao,&H);CHKERRQ(info); bnls->H=H;

  /*   Project the current point onto the feasible set */
  info = X->Median(XL,X,XU); CHKERRQ(info);
  
  TaoLinearSolver *tls;
  // Modify the linear solver to a conjugate gradient method
  info = TaoGetLinearSolver(tao, &tls); CHKERRQ(info);
  TaoLinearSolverPetsc *pls;
  pls  = dynamic_cast <TaoLinearSolverPetsc *> (tls);
  // set trust radius to zero 
  // PETSc ignores this case and should return the negative curvature direction
  // at its current default length
  pls->SetTrustRadius(0.0);

  if(!bnls->M) bnls->M = new TaoLMVMMat(X);
  TaoLMVMMat *M = bnls->M;
  KSP pksp = pls->GetKSP();
  // we will want to provide an initial guess in case neg curvature on the first iteration
  info = KSPSetInitialGuessNonzero(pksp,PETSC_TRUE); CHKERRQ(info);
  PC ppc;
  // Modify the preconditioner to use the bfgs approximation
  info = KSPGetPC(pksp, &ppc); CHKERRQ(info);
  PetscTruth  BFGSPreconditioner=PETSC_FALSE;// debug flag
  info = PetscOptionsGetTruth(PETSC_NULL,"-bnls_pc_bfgs",
                              &BFGSPreconditioner,PETSC_NULL); CHKERRQ(info);
  if( BFGSPreconditioner) 
    { 
     info=PetscInfo(tao,"TaoSolve_BNLS:  using bfgs preconditioner\n");
     info = KSPSetNormType(pksp, KSP_NORM_PRECONDITIONED); CHKERRQ(info);
     info = PCSetType(ppc, PCSHELL); CHKERRQ(info);
     info = PCShellSetName(ppc, "bfgs"); CHKERRQ(info);
     info = PCShellSetContext(ppc, M); CHKERRQ(info);
     info = PCShellSetApply(ppc, bfgs_apply); CHKERRQ(info);
    }
  else
    {// default to none
     info=PetscInfo(tao,"TaoSolve_BNLS:  using no preconditioner\n");
     info = PCSetType(ppc, PCNONE); CHKERRQ(info);
    }

  info = TaoComputeMeritFunctionGradient(tao,X,&f,G);CHKERRQ(info);
  info = PG->BoundGradientProjection(G,XL,X,XU);CHKERRQ(info);
  info = PG->Norm2(&gnorm); CHKERRQ(info);
  
  // Set initial scaling for the function
  if (f != 0.0) {
    info = M->SetDelta(2.0 * TaoAbsDouble(f) / (gnorm*gnorm)); CHKERRQ(info);
  }
  else {
    info = M->SetDelta(2.0 / (gnorm*gnorm)); CHKERRQ(info);
  }
  
  while (reason==TAO_CONTINUE_ITERATING){
    
    /* Project the gradient and calculate the norm */
    info = PG->BoundGradientProjection(G,XL,X,XU);CHKERRQ(info);
    info = PG->Norm2(&gnorm); CHKERRQ(info);
    
    info = M->Update(X, PG); CHKERRQ(info);

    PetscScalar ewAtol  = PetscMin(0.5,gnorm)*gnorm;
    info = KSPSetTolerances(pksp,PETSC_DEFAULT,ewAtol,
                            PETSC_DEFAULT, PETSC_DEFAULT); CHKERRQ(info);
    info=PetscInfo1(tao,"TaoSolve_BNLS: gnorm =%g\n",gnorm);
    pksp->printreason = PETSC_TRUE;
    info = KSPView(pksp,PETSC_VIEWER_STDOUT_WORLD);CHKERRQ(info);
    M->View();

    info = TaoMonitor(tao,iter++,f,gnorm,0.0,stepsize,&reason);
    CHKERRQ(info);
    if (reason!=TAO_CONTINUE_ITERATING) break;

    info = FreeVariables->WhichEqual(PG,G); CHKERRQ(info);

    info = TaoComputeHessian(tao,X,H);CHKERRQ(info);
    
    /* Create a reduced linear system */

    info = R->SetReducedVec(G,FreeVariables);CHKERRQ(info);
    info = R->Negate();CHKERRQ(info);

    /* Use gradient as initial guess */
    PetscTruth  UseGradientIG=PETSC_FALSE;// debug flag
    info = PetscOptionsGetTruth(PETSC_NULL,"-bnls_use_gradient_ig",
                                &UseGradientIG,PETSC_NULL); CHKERRQ(info);
    if(UseGradientIG)
      info = DX->CopyFrom(G);
    else
     {
      info=PetscInfo(tao,"TaoSolve_BNLS: use bfgs init guess \n");
      info = M->Solve(G, DX, &success);
     }
    CHKERRQ(info);
    info = DXFree->SetReducedVec(DX,FreeVariables);CHKERRQ(info);
    info = DXFree->Negate(); CHKERRQ(info);
    
    info = Hsub->SetReducedMatrix(H,FreeVariables,FreeVariables);CHKERRQ(info);

    bnls->gamma_factor /= 2;
    success = TAO_FALSE;

    while (success==TAO_FALSE) {
      
      /* Approximately solve the reduced linear system */
      info = TaoPreLinearSolve(tao,Hsub);CHKERRQ(info);
      info = TaoLinearSolve(tao,Hsub,R,DXFree,&success);CHKERRQ(info);

      info = DX->SetToZero(); CHKERRQ(info);
      info = DX->ReducedXPY(DXFree,FreeVariables);CHKERRQ(info);
      info = DX->Dot(G,&gdx); CHKERRQ(info);

      if (gdx>=0 || success==TAO_FALSE) { /* use bfgs direction */
        info = M->Solve(G, DX, &success); CHKERRQ(info);
        info = DX->BoundGradientProjection(DX,XL,X,XU); CHKERRQ(info);
        info = DX->Negate(); CHKERRQ(info);
        // Check for success (descent direction)
        info = DX->Dot(G,&gdx); CHKERRQ(info);
        if (gdx >= 0) {
          // Step is not descent or solve was not successful
          // Use steepest descent direction (scaled)
          if (f != 0.0) {
            info = M->SetDelta(2.0 * TaoAbsDouble(f) / (gnorm*gnorm)); CHKERRQ(info);
          }
          else {
            info = M->SetDelta(2.0 / (gnorm*gnorm)); CHKERRQ(info);
          }
          info = M->Reset(); CHKERRQ(info);
          info = M->Update(X, G); CHKERRQ(info);
          info = DX->CopyFrom(G);
          info = DX->Negate(); CHKERRQ(info);
          info = DX->Dot(G,&gdx); CHKERRQ(info);
          info=PetscInfo1(tao,"LMVM Solve Fail use steepest descent, gdx %22.12e \n",gdx);
        } 
        else {
          info=PetscInfo1(tao,"Newton Solve Fail use BFGS direction, gdx %22.12e \n",gdx);
        } 
	success = TAO_TRUE;
//        bnls->gamma_factor *= 2; 
//        bnls->gamma = bnls->gamma_factor*(gnorm); 
//#if !defined(PETSC_USE_COMPLEX)
//        info=PetscInfo2(tao,"TaoSolve_NLS:  modify diagonal (assume same nonzero structure), gamma_factor=%g, gamma=%g\n",bnls->gamma_factor,bnls->gamma);
//	CHKERRQ(info);
//#else
//        info=PetscInfo3(tao,"TaoSolve_NLS:  modify diagonal (asuume same nonzero structure), gamma_factor=%g, gamma=%g, gdx %22.12e \n",
//	     bnls->gamma_factor,PetscReal(bnls->gamma),gdx);CHKERRQ(info);
//#endif
//        info = Hsub->ShiftDiagonal(bnls->gamma);CHKERRQ(info);
//        if (f != 0.0) {
//          info = M->SetDelta(2.0 * TaoAbsDouble(f) / (gnorm*gnorm)); CHKERRQ(info);
//        }
//        else {
//          info = M->SetDelta(2.0 / (gnorm*gnorm)); CHKERRQ(info);
//        }
//        info = M->Reset(); CHKERRQ(info);
//        info = M->Update(X, G); CHKERRQ(info);
//        success = TAO_FALSE;
      } else {
        info=PetscInfo1(tao,"Newton Solve is descent direction, gdx %22.12e \n",gdx);
	success = TAO_TRUE;
      }

    }
    
    stepsize=1.0;	
    info = TaoLineSearchApply(tao,X,G,DX,Work,
			      &f,&f_full,&stepsize,&lsflag);
    CHKERRQ(info);

    
  }  /* END MAIN LOOP  */

  TaoFunctionReturn(0);
}
Пример #4
0
int main(int argc, char **argv)
{
  PetscErrorCode ierr;
  PetscInt       n=10000,its,dfid=1;
  Vec            x,b,u;
  Mat            A;
  KSP            ksp;
  PC             pc,pcnoise;
  PCNoise_Ctx    ctx={0,NULL};
  PetscReal      eta=0.1,norm;
  PetscScalar(*diagfunc)(PetscInt,PetscInt);

  ierr = PetscInitialize(&argc,&argv,(char*)0,help);CHKERRQ(ierr);

  /* Process command line options */
  ierr = PetscOptionsGetInt(NULL,"-n",&n,NULL);CHKERRQ(ierr);
  ierr = PetscOptionsGetReal(NULL,"-eta",&eta,NULL);CHKERRQ(ierr);
  ierr = PetscOptionsGetInt(NULL,"-diagfunc",&dfid,NULL);CHKERRQ(ierr);
  switch(dfid){
    case 1:
      diagfunc = diagFunc1;
      break;
    case 2:
      diagfunc = diagFunc2;
      break;
    case 3:
      diagfunc = diagFunc3;
      break;
    default:
      SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Unrecognized diagfunc option");
  }

  /* Create a diagonal matrix with a given distribution of diagonal elements */
  ierr = MatCreate(PETSC_COMM_WORLD,&A);CHKERRQ(ierr);
  ierr = MatSetSizes(A,PETSC_DECIDE,PETSC_DECIDE,n,n);CHKERRQ(ierr);
  ierr = MatSetFromOptions(A);CHKERRQ(ierr);
  ierr = MatSetUp(A);CHKERRQ(ierr);
  ierr = AssembleDiagonalMatrix(A,diagfunc);CHKERRQ(ierr);

  /* Allocate vectors and manufacture an exact solution and rhs */
  ierr = MatCreateVecs(A,&x,NULL);CHKERRQ(ierr);
  ierr = PetscObjectSetName((PetscObject)x,"Computed Solution");CHKERRQ(ierr);
  ierr = MatCreateVecs(A,&b,NULL);CHKERRQ(ierr);
  ierr = PetscObjectSetName((PetscObject)b,"RHS");CHKERRQ(ierr);
  ierr = MatCreateVecs(A,&u,NULL);CHKERRQ(ierr);
  ierr = PetscObjectSetName((PetscObject)u,"Reference Solution");CHKERRQ(ierr);
  ierr = VecSet(u,1.0);CHKERRQ(ierr);
  ierr = MatMult(A,u,b);CHKERRQ(ierr);

  /* Create a KSP object */
  ierr = KSPCreate(PETSC_COMM_WORLD,&ksp);CHKERRQ(ierr);
  ierr = KSPSetOperators(ksp,A,A);CHKERRQ(ierr);

  /* Set up a composite preconditioner */
  ierr = KSPGetPC(ksp,&pc);CHKERRQ(ierr);
  ierr = PCSetType(pc,PCCOMPOSITE);CHKERRQ(ierr); /* default composite with single Identity PC */
  ierr = PCCompositeSetType(pc,PC_COMPOSITE_ADDITIVE);CHKERRQ(ierr);
  ierr = PCCompositeAddPC(pc,PCNONE);CHKERRQ(ierr);
  if(eta > 0){
    ierr = PCCompositeAddPC(pc,PCSHELL);CHKERRQ(ierr);
    ierr = PCCompositeGetPC(pc,1,&pcnoise);CHKERRQ(ierr);
    ctx.eta = eta;
    ierr = PCShellSetContext(pcnoise,&ctx);CHKERRQ(ierr);
    ierr = PCShellSetApply(pcnoise,PCApply_Noise);CHKERRQ(ierr);
    ierr = PCShellSetSetUp(pcnoise,PCSetup_Noise);CHKERRQ(ierr);
    ierr = PCShellSetDestroy(pcnoise,PCDestroy_Noise);CHKERRQ(ierr);
    ierr = PCShellSetName(pcnoise,"Noise PC");CHKERRQ(ierr);
  }

  /* Set KSP from options (this can override the PC just defined) */
  ierr = KSPSetFromOptions(ksp);CHKERRQ(ierr);

  /* Solve */
  ierr = KSPSolve(ksp,b,x);CHKERRQ(ierr);

  /* Compute error */
  ierr = VecAXPY(x,-1.0,u);CHKERRQ(ierr);
  ierr = PetscObjectSetName((PetscObject)x,"Error");CHKERRQ(ierr);
  ierr = VecNorm(x,NORM_2,&norm);CHKERRQ(ierr);
  ierr = KSPGetIterationNumber(ksp,&its);CHKERRQ(ierr);
  ierr = PetscPrintf(PETSC_COMM_WORLD,"Norm of error %g, Iterations %D\n",(double)norm,its);CHKERRQ(ierr);

  /* Destroy objects and finalize */
  ierr = KSPDestroy(&ksp);CHKERRQ(ierr);
  ierr = MatDestroy(&A);CHKERRQ(ierr);
  ierr = VecDestroy(&x);CHKERRQ(ierr);
  ierr = VecDestroy(&b);CHKERRQ(ierr);
  ierr = VecDestroy(&u);CHKERRQ(ierr);
  PetscFinalize();

  return 0;
}
Пример #5
0
PetscErrorCode PCBDDCNullSpaceAssembleCorrection(PC pc, PetscBool isdir, IS local_dofs)
{
  PC_BDDC        *pcbddc = (PC_BDDC*)pc->data;
  PC_IS          *pcis = (PC_IS*)pc->data;
  Mat_IS*        matis = (Mat_IS*)pc->pmat->data;
  KSP            local_ksp;
  PC             newpc;
  NullSpaceCorrection_ctx  shell_ctx;
  Mat            local_mat,local_pmat,small_mat,inv_small_mat;
  Vec            work1,work2;
  const Vec      *nullvecs;
  VecScatter     scatter_ctx;
  IS             is_aux;
  MatFactorInfo  matinfo;
  PetscScalar    *basis_mat,*Kbasis_mat,*array,*array_mat;
  PetscScalar    one = 1.0,zero = 0.0, m_one = -1.0;
  PetscInt       basis_dofs,basis_size,nnsp_size,i,k;
  PetscBool      nnsp_has_cnst;
  PetscErrorCode ierr;

  PetscFunctionBegin;
  /* Infer the local solver */
  ierr = ISGetSize(local_dofs,&basis_dofs);CHKERRQ(ierr);
  if (isdir) {
    /* Dirichlet solver */
    local_ksp = pcbddc->ksp_D;
  } else {
    /* Neumann solver */
    local_ksp = pcbddc->ksp_R;
  }
  ierr = KSPGetOperators(local_ksp,&local_mat,&local_pmat);CHKERRQ(ierr);

  /* Get null space vecs */
  ierr = MatNullSpaceGetVecs(pcbddc->NullSpace,&nnsp_has_cnst,&nnsp_size,&nullvecs);CHKERRQ(ierr);
  basis_size = nnsp_size;
  if (nnsp_has_cnst) {
    basis_size++;
  }

  if (basis_dofs) {
     /* Create shell ctx */
    ierr = PetscNew(&shell_ctx);CHKERRQ(ierr);

    /* Create work vectors in shell context */
    ierr = VecCreate(PETSC_COMM_SELF,&shell_ctx->work_small_1);CHKERRQ(ierr);
    ierr = VecSetSizes(shell_ctx->work_small_1,basis_size,basis_size);CHKERRQ(ierr);
    ierr = VecSetType(shell_ctx->work_small_1,VECSEQ);CHKERRQ(ierr);
    ierr = VecDuplicate(shell_ctx->work_small_1,&shell_ctx->work_small_2);CHKERRQ(ierr);
    ierr = VecCreate(PETSC_COMM_SELF,&shell_ctx->work_full_1);CHKERRQ(ierr);
    ierr = VecSetSizes(shell_ctx->work_full_1,basis_dofs,basis_dofs);CHKERRQ(ierr);
    ierr = VecSetType(shell_ctx->work_full_1,VECSEQ);CHKERRQ(ierr);
    ierr = VecDuplicate(shell_ctx->work_full_1,&shell_ctx->work_full_2);CHKERRQ(ierr);

    /* Allocate workspace */
    ierr = MatCreateSeqDense(PETSC_COMM_SELF,basis_dofs,basis_size,NULL,&shell_ctx->basis_mat );CHKERRQ(ierr);
    ierr = MatCreateSeqDense(PETSC_COMM_SELF,basis_dofs,basis_size,NULL,&shell_ctx->Kbasis_mat);CHKERRQ(ierr);
    ierr = MatDenseGetArray(shell_ctx->basis_mat,&basis_mat);CHKERRQ(ierr);
    ierr = MatDenseGetArray(shell_ctx->Kbasis_mat,&Kbasis_mat);CHKERRQ(ierr);

    /* Restrict local null space on selected dofs (Dirichlet or Neumann)
       and compute matrices N and K*N */
    ierr = VecDuplicate(shell_ctx->work_full_1,&work1);CHKERRQ(ierr);
    ierr = VecDuplicate(shell_ctx->work_full_1,&work2);CHKERRQ(ierr);
    ierr = VecScatterCreate(pcis->vec1_N,local_dofs,work1,(IS)0,&scatter_ctx);CHKERRQ(ierr);
  }

  for (k=0;k<nnsp_size;k++) {
    ierr = VecScatterBegin(matis->rctx,nullvecs[k],pcis->vec1_N,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
    ierr = VecScatterEnd(matis->rctx,nullvecs[k],pcis->vec1_N,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
    if (basis_dofs) {
      ierr = VecPlaceArray(work1,(const PetscScalar*)&basis_mat[k*basis_dofs]);CHKERRQ(ierr);
      ierr = VecScatterBegin(scatter_ctx,pcis->vec1_N,work1,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
      ierr = VecScatterEnd(scatter_ctx,pcis->vec1_N,work1,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
      ierr = VecPlaceArray(work2,(const PetscScalar*)&Kbasis_mat[k*basis_dofs]);CHKERRQ(ierr);
      ierr = MatMult(local_mat,work1,work2);CHKERRQ(ierr);
      ierr = VecResetArray(work1);CHKERRQ(ierr);
      ierr = VecResetArray(work2);CHKERRQ(ierr);
    }
  }

  if (basis_dofs) {
    if (nnsp_has_cnst) {
      ierr = VecPlaceArray(work1,(const PetscScalar*)&basis_mat[k*basis_dofs]);CHKERRQ(ierr);
      ierr = VecSet(work1,one);CHKERRQ(ierr);
      ierr = VecPlaceArray(work2,(const PetscScalar*)&Kbasis_mat[k*basis_dofs]);CHKERRQ(ierr);
      ierr = MatMult(local_mat,work1,work2);CHKERRQ(ierr);
      ierr = VecResetArray(work1);CHKERRQ(ierr);
      ierr = VecResetArray(work2);CHKERRQ(ierr);
    }
    ierr = VecDestroy(&work1);CHKERRQ(ierr);
    ierr = VecDestroy(&work2);CHKERRQ(ierr);
    ierr = VecScatterDestroy(&scatter_ctx);CHKERRQ(ierr);
    ierr = MatDenseRestoreArray(shell_ctx->basis_mat,&basis_mat);CHKERRQ(ierr);
    ierr = MatDenseRestoreArray(shell_ctx->Kbasis_mat,&Kbasis_mat);CHKERRQ(ierr);

    /* Assemble another Mat object in shell context */
    ierr = MatTransposeMatMult(shell_ctx->basis_mat,shell_ctx->Kbasis_mat,MAT_INITIAL_MATRIX,PETSC_DEFAULT,&small_mat);CHKERRQ(ierr);
    ierr = MatFactorInfoInitialize(&matinfo);CHKERRQ(ierr);
    ierr = ISCreateStride(PETSC_COMM_SELF,basis_size,0,1,&is_aux);CHKERRQ(ierr);
    ierr = MatLUFactor(small_mat,is_aux,is_aux,&matinfo);CHKERRQ(ierr);
    ierr = ISDestroy(&is_aux);CHKERRQ(ierr);
    ierr = PetscMalloc1(basis_size*basis_size,&array_mat);CHKERRQ(ierr);
    for (k=0;k<basis_size;k++) {
      ierr = VecSet(shell_ctx->work_small_1,zero);CHKERRQ(ierr);
      ierr = VecSetValue(shell_ctx->work_small_1,k,one,INSERT_VALUES);CHKERRQ(ierr);
      ierr = VecAssemblyBegin(shell_ctx->work_small_1);CHKERRQ(ierr);
      ierr = VecAssemblyEnd(shell_ctx->work_small_1);CHKERRQ(ierr);
      ierr = MatSolve(small_mat,shell_ctx->work_small_1,shell_ctx->work_small_2);CHKERRQ(ierr);
      ierr = VecGetArrayRead(shell_ctx->work_small_2,(const PetscScalar**)&array);CHKERRQ(ierr);
      for (i=0;i<basis_size;i++) {
        array_mat[i*basis_size+k]=array[i];
      }
      ierr = VecRestoreArrayRead(shell_ctx->work_small_2,(const PetscScalar**)&array);CHKERRQ(ierr);
    }
    ierr = MatCreateSeqDense(PETSC_COMM_SELF,basis_size,basis_size,array_mat,&inv_small_mat);CHKERRQ(ierr);
    ierr = MatMatMult(shell_ctx->basis_mat,inv_small_mat,MAT_INITIAL_MATRIX,PETSC_DEFAULT,&shell_ctx->Lbasis_mat);CHKERRQ(ierr);
    ierr = PetscFree(array_mat);CHKERRQ(ierr);
    ierr = MatDestroy(&inv_small_mat);CHKERRQ(ierr);
    ierr = MatDestroy(&small_mat);CHKERRQ(ierr);
    ierr = MatScale(shell_ctx->Kbasis_mat,m_one);CHKERRQ(ierr);

    /* Rebuild local PC */
    ierr = KSPGetPC(local_ksp,&shell_ctx->local_pc);CHKERRQ(ierr);
    ierr = PetscObjectReference((PetscObject)shell_ctx->local_pc);CHKERRQ(ierr);
    ierr = PCCreate(PETSC_COMM_SELF,&newpc);CHKERRQ(ierr);
    ierr = PCSetOperators(newpc,local_mat,local_mat);CHKERRQ(ierr);
    ierr = PCSetType(newpc,PCSHELL);CHKERRQ(ierr);
    ierr = PCShellSetContext(newpc,shell_ctx);CHKERRQ(ierr);
    ierr = PCShellSetApply(newpc,PCBDDCApplyNullSpaceCorrectionPC);CHKERRQ(ierr);
    ierr = PCShellSetDestroy(newpc,PCBDDCDestroyNullSpaceCorrectionPC);CHKERRQ(ierr);
    ierr = PCSetUp(newpc);CHKERRQ(ierr);
    ierr = KSPSetPC(local_ksp,newpc);CHKERRQ(ierr);
    ierr = PCDestroy(&newpc);CHKERRQ(ierr);
    ierr = KSPSetUp(local_ksp);CHKERRQ(ierr);
  }
  /* test */
  if (pcbddc->dbg_flag && basis_dofs) {
    KSP         check_ksp;
    PC          check_pc;
    Mat         test_mat;
    Vec         work3;
    PetscReal   test_err,lambda_min,lambda_max;
    PetscBool   setsym,issym=PETSC_FALSE;
    PetscInt    tabs;

    ierr = PetscViewerASCIIGetTab(pcbddc->dbg_viewer,&tabs);CHKERRQ(ierr);
    ierr = KSPGetPC(local_ksp,&check_pc);CHKERRQ(ierr);
    ierr = VecDuplicate(shell_ctx->work_full_1,&work1);CHKERRQ(ierr);
    ierr = VecDuplicate(shell_ctx->work_full_1,&work2);CHKERRQ(ierr);
    ierr = VecDuplicate(shell_ctx->work_full_1,&work3);CHKERRQ(ierr);
    ierr = VecSetRandom(shell_ctx->work_small_1,NULL);CHKERRQ(ierr);
    ierr = MatMult(shell_ctx->basis_mat,shell_ctx->work_small_1,work1);CHKERRQ(ierr);
    ierr = VecCopy(work1,work2);CHKERRQ(ierr);
    ierr = MatMult(local_mat,work1,work3);CHKERRQ(ierr);
    ierr = PCApply(check_pc,work3,work1);CHKERRQ(ierr);
    ierr = VecAXPY(work1,m_one,work2);CHKERRQ(ierr);
    ierr = VecNorm(work1,NORM_INFINITY,&test_err);CHKERRQ(ierr);
    ierr = PetscViewerASCIISynchronizedPrintf(pcbddc->dbg_viewer,"Subdomain %04d error for nullspace correction for ",PetscGlobalRank);CHKERRQ(ierr);
    ierr = PetscViewerASCIIUseTabs(pcbddc->dbg_viewer,PETSC_FALSE);CHKERRQ(ierr);
    if (isdir) {
      ierr = PetscViewerASCIISynchronizedPrintf(pcbddc->dbg_viewer,"Dirichlet ");CHKERRQ(ierr);
    } else {
      ierr = PetscViewerASCIISynchronizedPrintf(pcbddc->dbg_viewer,"Neumann ");CHKERRQ(ierr);
    }
    ierr = PetscViewerASCIISynchronizedPrintf(pcbddc->dbg_viewer,"solver is :%1.14e\n",test_err);CHKERRQ(ierr);
    ierr = PetscViewerASCIISetTab(pcbddc->dbg_viewer,tabs);CHKERRQ(ierr);
    ierr = PetscViewerASCIIUseTabs(pcbddc->dbg_viewer,PETSC_TRUE);CHKERRQ(ierr);

    ierr = MatTransposeMatMult(shell_ctx->Lbasis_mat,shell_ctx->Kbasis_mat,MAT_INITIAL_MATRIX,PETSC_DEFAULT,&test_mat);CHKERRQ(ierr);
    ierr = MatShift(test_mat,one);CHKERRQ(ierr);
    ierr = MatNorm(test_mat,NORM_INFINITY,&test_err);CHKERRQ(ierr);
    ierr = MatDestroy(&test_mat);CHKERRQ(ierr);
    ierr = PetscViewerASCIISynchronizedPrintf(pcbddc->dbg_viewer,"Subdomain %04d error for nullspace matrices is :%1.14e\n",PetscGlobalRank,test_err);CHKERRQ(ierr);

    /* Create ksp object suitable for extreme eigenvalues' estimation */
    ierr = KSPCreate(PETSC_COMM_SELF,&check_ksp);CHKERRQ(ierr);
    ierr = KSPSetErrorIfNotConverged(check_ksp,pc->erroriffailure);CHKERRQ(ierr);
    ierr = KSPSetOperators(check_ksp,local_mat,local_mat);CHKERRQ(ierr);
    ierr = KSPSetTolerances(check_ksp,1.e-8,1.e-8,PETSC_DEFAULT,basis_dofs);CHKERRQ(ierr);
    ierr = KSPSetComputeSingularValues(check_ksp,PETSC_TRUE);CHKERRQ(ierr);
    ierr = MatIsSymmetricKnown(pc->pmat,&setsym,&issym);CHKERRQ(ierr);
    if (issym) {
      ierr = KSPSetType(check_ksp,KSPCG);CHKERRQ(ierr);
    }
    ierr = KSPSetPC(check_ksp,check_pc);CHKERRQ(ierr);
    ierr = KSPSetUp(check_ksp);CHKERRQ(ierr);
    ierr = VecSetRandom(work1,NULL);CHKERRQ(ierr);
    ierr = MatMult(local_mat,work1,work2);CHKERRQ(ierr);
    ierr = KSPSolve(check_ksp,work2,work2);CHKERRQ(ierr);
    ierr = VecAXPY(work2,m_one,work1);CHKERRQ(ierr);
    ierr = VecNorm(work2,NORM_INFINITY,&test_err);CHKERRQ(ierr);
    ierr = KSPComputeExtremeSingularValues(check_ksp,&lambda_max,&lambda_min);CHKERRQ(ierr);
    ierr = KSPGetIterationNumber(check_ksp,&k);CHKERRQ(ierr);
    ierr = PetscViewerASCIISynchronizedPrintf(pcbddc->dbg_viewer,"Subdomain %04d error for adapted KSP %1.14e (it %d, eigs %1.6e %1.6e)\n",PetscGlobalRank,test_err,k,lambda_min,lambda_max);CHKERRQ(ierr);
    ierr = KSPDestroy(&check_ksp);CHKERRQ(ierr);
    ierr = VecDestroy(&work1);CHKERRQ(ierr);
    ierr = VecDestroy(&work2);CHKERRQ(ierr);
    ierr = VecDestroy(&work3);CHKERRQ(ierr);
  }
  /* all processes shoud call this, even the void ones */
  if (pcbddc->dbg_flag) {
    ierr = PetscViewerFlush(pcbddc->dbg_viewer);CHKERRQ(ierr);
  }
  PetscFunctionReturn(0);
}
Пример #6
0
int main(int argc,char **argv)
{
    DMMG           *dmmg;               /* multilevel grid structure */
    PetscErrorCode ierr;
    DA             da;
    AppCtx         app;
    PC             pc;
    KSP            ksp;
    PetscTruth     isshell;
    PetscViewer    v1;

    PetscInitialize(&argc,&argv,(char *)0,help);

    PreLoadBegin(PETSC_TRUE,"SetUp");

    app.comm = PETSC_COMM_WORLD;
    app.nxv  = 6;
    app.nyvf = 3;
    app.nyv  = app.nyvf + 2;
    ierr = PetscOptionsBegin(app.comm,PETSC_NULL,"Options for Grid Sizes",PETSC_NULL);
    ierr = PetscOptionsInt("-nxv","Grid spacing in X direction",PETSC_NULL,app.nxv,&app.nxv,PETSC_NULL);
    CHKERRQ(ierr);
    ierr = PetscOptionsInt("-nyvf","Grid spacing in Y direction of Fuel",PETSC_NULL,app.nyvf,&app.nyvf,PETSC_NULL);
    CHKERRQ(ierr);
    ierr = PetscOptionsInt("-nyv","Total Grid spacing in Y direction of",PETSC_NULL,app.nyv,&app.nyv,PETSC_NULL);
    CHKERRQ(ierr);
    ierr = PetscOptionsEnd();

    ierr = PetscViewerDrawOpen(app.comm,PETSC_NULL,"",-1,-1,-1,-1,&v1);
    CHKERRQ(ierr);

    /*
       Create the DMComposite object to manage the three grids/physics.
       We use a 1d decomposition along the y direction (since one of the grids is 1d).

    */
    ierr = DMCompositeCreate(app.comm,&app.pack);
    CHKERRQ(ierr);

    /* 6 fluid unknowns, 3 ghost points on each end for either periodicity or simply boundary conditions */
    ierr = DACreate1d(app.comm,DA_XPERIODIC,app.nxv,6,3,0,&da);
    CHKERRQ(ierr);
    ierr = DASetFieldName(da,0,"prss");
    CHKERRQ(ierr);
    ierr = DASetFieldName(da,1,"ergg");
    CHKERRQ(ierr);
    ierr = DASetFieldName(da,2,"ergf");
    CHKERRQ(ierr);
    ierr = DASetFieldName(da,3,"alfg");
    CHKERRQ(ierr);
    ierr = DASetFieldName(da,4,"velg");
    CHKERRQ(ierr);
    ierr = DASetFieldName(da,5,"velf");
    CHKERRQ(ierr);
    ierr = DMCompositeAddDM(app.pack,(DM)da);
    CHKERRQ(ierr);
    ierr = DADestroy(da);
    CHKERRQ(ierr);

    ierr = DACreate2d(app.comm,DA_YPERIODIC,DA_STENCIL_STAR,app.nxv,app.nyv,PETSC_DETERMINE,1,1,1,0,0,&da);
    CHKERRQ(ierr);
    ierr = DASetFieldName(da,0,"Tempature");
    CHKERRQ(ierr);
    ierr = DMCompositeAddDM(app.pack,(DM)da);
    CHKERRQ(ierr);
    ierr = DADestroy(da);
    CHKERRQ(ierr);

    ierr = DACreate2d(app.comm,DA_XYPERIODIC,DA_STENCIL_STAR,app.nxv,app.nyvf,PETSC_DETERMINE,1,2,1,0,0,&da);
    CHKERRQ(ierr);
    ierr = DASetFieldName(da,0,"Phi");
    CHKERRQ(ierr);
    ierr = DASetFieldName(da,1,"Pre");
    CHKERRQ(ierr);
    ierr = DMCompositeAddDM(app.pack,(DM)da);
    CHKERRQ(ierr);
    ierr = DADestroy(da);
    CHKERRQ(ierr);

    app.pri = 1.0135e+5;
    app.ugi = 2.5065e+6;
    app.ufi = 4.1894e+5;
    app.agi = 1.00e-1;
    app.vgi = 1.0e-1 ;
    app.vfi = 1.0e-1;

    app.prin = 1.0135e+5;
    app.ugin = 2.5065e+6;
    app.ufin = 4.1894e+5;
    app.agin = 1.00e-1;
    app.vgin = 1.0e-1 ;
    app.vfin = 1.0e-1;

    app.prout = 1.0135e+5;
    app.ugout = 2.5065e+6;
    app.ufout = 4.1894e+5;
    app.agout = 3.0e-1;

    app.twi = 373.15e+0;

    app.phii = 1.0e+0;
    app.prei = 1.0e-5;

    /*
       Create the solver object and attach the grid/physics info
    */
    ierr = DMMGCreate(app.comm,1,0,&dmmg);
    CHKERRQ(ierr);
    ierr = DMMGSetDM(dmmg,(DM)app.pack);
    CHKERRQ(ierr);
    ierr = DMMGSetUser(dmmg,0,&app);
    CHKERRQ(ierr);
    ierr = DMMGSetISColoringType(dmmg,IS_COLORING_GLOBAL);
    CHKERRQ(ierr);
    CHKMEMQ;


    ierr = DMMGSetInitialGuess(dmmg,FormInitialGuess);
    CHKERRQ(ierr);
    ierr = DMMGSetSNES(dmmg,FormFunction,0);
    CHKERRQ(ierr);
    ierr = DMMGSetFromOptions(dmmg);
    CHKERRQ(ierr);

    /* Supply custom shell preconditioner if requested */
    ierr = SNESGetKSP(DMMGGetSNES(dmmg),&ksp);
    CHKERRQ(ierr);
    ierr = KSPGetPC(ksp,&pc);
    CHKERRQ(ierr);
    ierr = PetscTypeCompare((PetscObject)pc,PCSHELL,&isshell);
    CHKERRQ(ierr);
    if (isshell) {
        ierr = PCShellSetContext(pc,&app);
        CHKERRQ(ierr);
        ierr = PCShellSetSetUp(pc,MyPCSetUp);
        CHKERRQ(ierr);
        ierr = PCShellSetApply(pc,MyPCApply);
        CHKERRQ(ierr);
        ierr = PCShellSetDestroy(pc,MyPCDestroy);
        CHKERRQ(ierr);
    }

    /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
       Solve the nonlinear system
       - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

    PreLoadStage("Solve");
    ierr = DMMGSolve(dmmg);
    CHKERRQ(ierr);


    ierr = VecView(DMMGGetx(dmmg),v1);
    CHKERRQ(ierr);

    /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
       Free work space.  All PETSc objects should be destroyed when they
       are no longer needed.
       - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

    ierr = PetscViewerDestroy(v1);
    CHKERRQ(ierr);
    ierr = DMCompositeDestroy(app.pack);
    CHKERRQ(ierr);
    ierr = DMMGDestroy(dmmg);
    CHKERRQ(ierr);
    PreLoadEnd();

    ierr = PetscFinalize();
    CHKERRQ(ierr);
    return 0;
}
Пример #7
0
PETSC_EXTERN void PETSC_STDCALL  pcshellsetcontext_(PC pc,void*ctx, int *__ierr ){
*__ierr = PCShellSetContext(
	(PC)PetscToPointer((pc) ),ctx);
}
Пример #8
0
static PetscErrorCode TaoSolve_NTR(Tao tao)
{
  TAO_NTR            *tr = (TAO_NTR *)tao->data;
  PC                 pc;
  KSPConvergedReason ksp_reason;
  TaoConvergedReason reason;
  PetscReal          fmin, ftrial, prered, actred, kappa, sigma, beta;
  PetscReal          tau, tau_1, tau_2, tau_max, tau_min, max_radius;
  PetscReal          f, gnorm;

  PetscReal          delta;
  PetscReal          norm_d;
  PetscErrorCode     ierr;
  PetscInt           iter = 0;
  PetscInt           bfgsUpdates = 0;
  PetscInt           needH;

  PetscInt           i_max = 5;
  PetscInt           j_max = 1;
  PetscInt           i, j, N, n, its;

  PetscFunctionBegin;
  if (tao->XL || tao->XU || tao->ops->computebounds) {
    ierr = PetscPrintf(((PetscObject)tao)->comm,"WARNING: Variable bounds have been set but will be ignored by ntr algorithm\n");CHKERRQ(ierr);
  }

  tao->trust = tao->trust0;

  /* Modify the radius if it is too large or small */
  tao->trust = PetscMax(tao->trust, tr->min_radius);
  tao->trust = PetscMin(tao->trust, tr->max_radius);


  if (NTR_PC_BFGS == tr->pc_type && !tr->M) {
    ierr = VecGetLocalSize(tao->solution,&n);CHKERRQ(ierr);
    ierr = VecGetSize(tao->solution,&N);CHKERRQ(ierr);
    ierr = MatCreateLMVM(((PetscObject)tao)->comm,n,N,&tr->M);CHKERRQ(ierr);
    ierr = MatLMVMAllocateVectors(tr->M,tao->solution);CHKERRQ(ierr);
  }

  /* Check convergence criteria */
  ierr = TaoComputeObjectiveAndGradient(tao, tao->solution, &f, tao->gradient);CHKERRQ(ierr);
  ierr = VecNorm(tao->gradient,NORM_2,&gnorm);CHKERRQ(ierr);
  if (PetscIsInfOrNanReal(f) || PetscIsInfOrNanReal(gnorm)) SETERRQ(PETSC_COMM_SELF,1, "User provided compute function generated Inf or NaN");
  needH = 1;

  ierr = TaoMonitor(tao, iter, f, gnorm, 0.0, 1.0, &reason);CHKERRQ(ierr);
  if (reason != TAO_CONTINUE_ITERATING) PetscFunctionReturn(0);

  /* Create vectors for the limited memory preconditioner */
  if ((NTR_PC_BFGS == tr->pc_type) &&
      (BFGS_SCALE_BFGS != tr->bfgs_scale_type)) {
    if (!tr->Diag) {
        ierr = VecDuplicate(tao->solution, &tr->Diag);CHKERRQ(ierr);
    }
  }

  switch(tr->ksp_type) {
  case NTR_KSP_NASH:
    ierr = KSPSetType(tao->ksp, KSPNASH);CHKERRQ(ierr);
    if (tao->ksp->ops->setfromoptions) {
      (*tao->ksp->ops->setfromoptions)(tao->ksp);
    }
    break;

  case NTR_KSP_STCG:
    ierr = KSPSetType(tao->ksp, KSPSTCG);CHKERRQ(ierr);
    if (tao->ksp->ops->setfromoptions) {
      (*tao->ksp->ops->setfromoptions)(tao->ksp);
    }
    break;

  default:
    ierr = KSPSetType(tao->ksp, KSPGLTR);CHKERRQ(ierr);
    if (tao->ksp->ops->setfromoptions) {
      (*tao->ksp->ops->setfromoptions)(tao->ksp);
    }
    break;
  }

  /*  Modify the preconditioner to use the bfgs approximation */
  ierr = KSPGetPC(tao->ksp, &pc);CHKERRQ(ierr);
  switch(tr->pc_type) {
  case NTR_PC_NONE:
    ierr = PCSetType(pc, PCNONE);CHKERRQ(ierr);
    if (pc->ops->setfromoptions) {
      (*pc->ops->setfromoptions)(pc);
    }
    break;

  case NTR_PC_AHESS:
    ierr = PCSetType(pc, PCJACOBI);CHKERRQ(ierr);
    if (pc->ops->setfromoptions) {
      (*pc->ops->setfromoptions)(pc);
    }
    ierr = PCJacobiSetUseAbs(pc);CHKERRQ(ierr);
    break;

  case NTR_PC_BFGS:
    ierr = PCSetType(pc, PCSHELL);CHKERRQ(ierr);
    if (pc->ops->setfromoptions) {
      (*pc->ops->setfromoptions)(pc);
    }
    ierr = PCShellSetName(pc, "bfgs");CHKERRQ(ierr);
    ierr = PCShellSetContext(pc, tr->M);CHKERRQ(ierr);
    ierr = PCShellSetApply(pc, MatLMVMSolveShell);CHKERRQ(ierr);
    break;

  default:
    /*  Use the pc method set by pc_type */
    break;
  }

  /*  Initialize trust-region radius */
  switch(tr->init_type) {
  case NTR_INIT_CONSTANT:
    /*  Use the initial radius specified */
    break;

  case NTR_INIT_INTERPOLATION:
    /*  Use the initial radius specified */
    max_radius = 0.0;

    for (j = 0; j < j_max; ++j) {
      fmin = f;
      sigma = 0.0;

      if (needH) {
        ierr = TaoComputeHessian(tao,tao->solution,tao->hessian,tao->hessian_pre);CHKERRQ(ierr);
        needH = 0;
      }

      for (i = 0; i < i_max; ++i) {

        ierr = VecCopy(tao->solution, tr->W);CHKERRQ(ierr);
        ierr = VecAXPY(tr->W, -tao->trust/gnorm, tao->gradient);CHKERRQ(ierr);
        ierr = TaoComputeObjective(tao, tr->W, &ftrial);CHKERRQ(ierr);

        if (PetscIsInfOrNanReal(ftrial)) {
          tau = tr->gamma1_i;
        }
        else {
          if (ftrial < fmin) {
            fmin = ftrial;
            sigma = -tao->trust / gnorm;
          }

          ierr = MatMult(tao->hessian, tao->gradient, tao->stepdirection);CHKERRQ(ierr);
          ierr = VecDot(tao->gradient, tao->stepdirection, &prered);CHKERRQ(ierr);

          prered = tao->trust * (gnorm - 0.5 * tao->trust * prered / (gnorm * gnorm));
          actred = f - ftrial;
          if ((PetscAbsScalar(actred) <= tr->epsilon) &&
              (PetscAbsScalar(prered) <= tr->epsilon)) {
            kappa = 1.0;
          }
          else {
            kappa = actred / prered;
          }

          tau_1 = tr->theta_i * gnorm * tao->trust / (tr->theta_i * gnorm * tao->trust + (1.0 - tr->theta_i) * prered - actred);
          tau_2 = tr->theta_i * gnorm * tao->trust / (tr->theta_i * gnorm * tao->trust - (1.0 + tr->theta_i) * prered + actred);
          tau_min = PetscMin(tau_1, tau_2);
          tau_max = PetscMax(tau_1, tau_2);

          if (PetscAbsScalar(kappa - 1.0) <= tr->mu1_i) {
            /*  Great agreement */
            max_radius = PetscMax(max_radius, tao->trust);

            if (tau_max < 1.0) {
              tau = tr->gamma3_i;
            }
            else if (tau_max > tr->gamma4_i) {
              tau = tr->gamma4_i;
            }
            else {
              tau = tau_max;
            }
          }
          else if (PetscAbsScalar(kappa - 1.0) <= tr->mu2_i) {
            /*  Good agreement */
            max_radius = PetscMax(max_radius, tao->trust);

            if (tau_max < tr->gamma2_i) {
              tau = tr->gamma2_i;
            }
            else if (tau_max > tr->gamma3_i) {
              tau = tr->gamma3_i;
            }
            else {
              tau = tau_max;
            }
          }
          else {
            /*  Not good agreement */
            if (tau_min > 1.0) {
              tau = tr->gamma2_i;
            }
            else if (tau_max < tr->gamma1_i) {
              tau = tr->gamma1_i;
            }
            else if ((tau_min < tr->gamma1_i) && (tau_max >= 1.0)) {
              tau = tr->gamma1_i;
            }
            else if ((tau_1 >= tr->gamma1_i) && (tau_1 < 1.0) &&
                     ((tau_2 < tr->gamma1_i) || (tau_2 >= 1.0))) {
              tau = tau_1;
            }
            else if ((tau_2 >= tr->gamma1_i) && (tau_2 < 1.0) &&
                     ((tau_1 < tr->gamma1_i) || (tau_2 >= 1.0))) {
              tau = tau_2;
            }
            else {
              tau = tau_max;
            }
          }
        }
        tao->trust = tau * tao->trust;
      }

      if (fmin < f) {
        f = fmin;
        ierr = VecAXPY(tao->solution, sigma, tao->gradient);CHKERRQ(ierr);
        ierr = TaoComputeGradient(tao,tao->solution, tao->gradient);CHKERRQ(ierr);

        ierr = VecNorm(tao->gradient, NORM_2, &gnorm);CHKERRQ(ierr);

        if (PetscIsInfOrNanReal(f) || PetscIsInfOrNanReal(gnorm)) SETERRQ(PETSC_COMM_SELF,1, "User provided compute function generated Inf or NaN");
        needH = 1;

        ierr = TaoMonitor(tao, iter, f, gnorm, 0.0, 1.0, &reason);CHKERRQ(ierr);
        if (reason != TAO_CONTINUE_ITERATING) {
          PetscFunctionReturn(0);
        }
      }
    }
    tao->trust = PetscMax(tao->trust, max_radius);

    /*  Modify the radius if it is too large or small */
    tao->trust = PetscMax(tao->trust, tr->min_radius);
    tao->trust = PetscMin(tao->trust, tr->max_radius);
    break;

  default:
    /*  Norm of the first direction will initialize radius */
    tao->trust = 0.0;
    break;
  }

  /* Set initial scaling for the BFGS preconditioner
     This step is done after computing the initial trust-region radius
     since the function value may have decreased */
  if (NTR_PC_BFGS == tr->pc_type) {
    if (f != 0.0) {
      delta = 2.0 * PetscAbsScalar(f) / (gnorm*gnorm);
    }
    else {
      delta = 2.0 / (gnorm*gnorm);
    }
    ierr = MatLMVMSetDelta(tr->M,delta);CHKERRQ(ierr);
  }

  /* Have not converged; continue with Newton method */
  while (reason == TAO_CONTINUE_ITERATING) {
    ++iter;
    tao->ksp_its=0;
    /* Compute the Hessian */
    if (needH) {
      ierr = TaoComputeHessian(tao,tao->solution,tao->hessian,tao->hessian_pre);CHKERRQ(ierr);
      needH = 0;
    }

    if (NTR_PC_BFGS == tr->pc_type) {
      if (BFGS_SCALE_AHESS == tr->bfgs_scale_type) {
        /* Obtain diagonal for the bfgs preconditioner */
        ierr = MatGetDiagonal(tao->hessian, tr->Diag);CHKERRQ(ierr);
        ierr = VecAbs(tr->Diag);CHKERRQ(ierr);
        ierr = VecReciprocal(tr->Diag);CHKERRQ(ierr);
        ierr = MatLMVMSetScale(tr->M,tr->Diag);CHKERRQ(ierr);
      }

      /* Update the limited memory preconditioner */
      ierr = MatLMVMUpdate(tr->M, tao->solution, tao->gradient);CHKERRQ(ierr);
      ++bfgsUpdates;
    }

    while (reason == TAO_CONTINUE_ITERATING) {
      ierr = KSPSetOperators(tao->ksp, tao->hessian, tao->hessian_pre);CHKERRQ(ierr);

      /* Solve the trust region subproblem */
      if (NTR_KSP_NASH == tr->ksp_type) {
        ierr = KSPNASHSetRadius(tao->ksp,tao->trust);CHKERRQ(ierr);
        ierr = KSPSolve(tao->ksp, tao->gradient, tao->stepdirection);CHKERRQ(ierr);
        ierr = KSPGetIterationNumber(tao->ksp,&its);CHKERRQ(ierr);
        tao->ksp_its+=its;
        tao->ksp_tot_its+=its;
        ierr = KSPNASHGetNormD(tao->ksp, &norm_d);CHKERRQ(ierr);
      } else if (NTR_KSP_STCG == tr->ksp_type) {
        ierr = KSPSTCGSetRadius(tao->ksp,tao->trust);CHKERRQ(ierr);
        ierr = KSPSolve(tao->ksp, tao->gradient, tao->stepdirection);CHKERRQ(ierr);
        ierr = KSPGetIterationNumber(tao->ksp,&its);CHKERRQ(ierr);
        tao->ksp_its+=its;
        tao->ksp_tot_its+=its;
        ierr = KSPSTCGGetNormD(tao->ksp, &norm_d);CHKERRQ(ierr);
      } else { /* NTR_KSP_GLTR */
        ierr = KSPGLTRSetRadius(tao->ksp,tao->trust);CHKERRQ(ierr);
        ierr = KSPSolve(tao->ksp, tao->gradient, tao->stepdirection);CHKERRQ(ierr);
        ierr = KSPGetIterationNumber(tao->ksp,&its);CHKERRQ(ierr);
        tao->ksp_its+=its;
        tao->ksp_tot_its+=its;
        ierr = KSPGLTRGetNormD(tao->ksp, &norm_d);CHKERRQ(ierr);
      }

      if (0.0 == tao->trust) {
        /* Radius was uninitialized; use the norm of the direction */
        if (norm_d > 0.0) {
          tao->trust = norm_d;

          /* Modify the radius if it is too large or small */
          tao->trust = PetscMax(tao->trust, tr->min_radius);
          tao->trust = PetscMin(tao->trust, tr->max_radius);
        }
        else {
          /* The direction was bad; set radius to default value and re-solve
             the trust-region subproblem to get a direction */
          tao->trust = tao->trust0;

          /* Modify the radius if it is too large or small */
          tao->trust = PetscMax(tao->trust, tr->min_radius);
          tao->trust = PetscMin(tao->trust, tr->max_radius);

          if (NTR_KSP_NASH == tr->ksp_type) {
            ierr = KSPNASHSetRadius(tao->ksp,tao->trust);CHKERRQ(ierr);
            ierr = KSPSolve(tao->ksp, tao->gradient, tao->stepdirection);CHKERRQ(ierr);
            ierr = KSPGetIterationNumber(tao->ksp,&its);CHKERRQ(ierr);
            tao->ksp_its+=its;
            tao->ksp_tot_its+=its;
            ierr = KSPNASHGetNormD(tao->ksp, &norm_d);CHKERRQ(ierr);
          } else if (NTR_KSP_STCG == tr->ksp_type) {
            ierr = KSPSTCGSetRadius(tao->ksp,tao->trust);CHKERRQ(ierr);
            ierr = KSPSolve(tao->ksp, tao->gradient, tao->stepdirection);CHKERRQ(ierr);
            ierr = KSPGetIterationNumber(tao->ksp,&its);CHKERRQ(ierr);
            tao->ksp_its+=its;
            tao->ksp_tot_its+=its;
            ierr = KSPSTCGGetNormD(tao->ksp, &norm_d);CHKERRQ(ierr);
          } else { /* NTR_KSP_GLTR */
            ierr = KSPGLTRSetRadius(tao->ksp,tao->trust);CHKERRQ(ierr);
            ierr = KSPSolve(tao->ksp, tao->gradient, tao->stepdirection);CHKERRQ(ierr);
            ierr = KSPGetIterationNumber(tao->ksp,&its);CHKERRQ(ierr);
            tao->ksp_its+=its;
            tao->ksp_tot_its+=its;
            ierr = KSPGLTRGetNormD(tao->ksp, &norm_d);CHKERRQ(ierr);
          }

          if (norm_d == 0.0) SETERRQ(PETSC_COMM_SELF,1, "Initial direction zero");
        }
      }
      ierr = VecScale(tao->stepdirection, -1.0);CHKERRQ(ierr);
      ierr = KSPGetConvergedReason(tao->ksp, &ksp_reason);CHKERRQ(ierr);
      if ((KSP_DIVERGED_INDEFINITE_PC == ksp_reason) &&
          (NTR_PC_BFGS == tr->pc_type) && (bfgsUpdates > 1)) {
        /* Preconditioner is numerically indefinite; reset the
           approximate if using BFGS preconditioning. */

        if (f != 0.0) {
          delta = 2.0 * PetscAbsScalar(f) / (gnorm*gnorm);
        }
        else {
          delta = 2.0 / (gnorm*gnorm);
        }
        ierr = MatLMVMSetDelta(tr->M, delta);CHKERRQ(ierr);
        ierr = MatLMVMReset(tr->M);CHKERRQ(ierr);
        ierr = MatLMVMUpdate(tr->M, tao->solution, tao->gradient);CHKERRQ(ierr);
        bfgsUpdates = 1;
      }

      if (NTR_UPDATE_REDUCTION == tr->update_type) {
        /* Get predicted reduction */
        if (NTR_KSP_NASH == tr->ksp_type) {
          ierr = KSPNASHGetObjFcn(tao->ksp,&prered);CHKERRQ(ierr);
        } else if (NTR_KSP_STCG == tr->ksp_type) {
          ierr = KSPSTCGGetObjFcn(tao->ksp,&prered);CHKERRQ(ierr);
        } else { /* gltr */
          ierr = KSPGLTRGetObjFcn(tao->ksp,&prered);CHKERRQ(ierr);
        }

        if (prered >= 0.0) {
          /* The predicted reduction has the wrong sign.  This cannot
             happen in infinite precision arithmetic.  Step should
             be rejected! */
          tao->trust = tr->alpha1 * PetscMin(tao->trust, norm_d);
        }
        else {
          /* Compute trial step and function value */
          ierr = VecCopy(tao->solution,tr->W);CHKERRQ(ierr);
          ierr = VecAXPY(tr->W, 1.0, tao->stepdirection);CHKERRQ(ierr);
          ierr = TaoComputeObjective(tao, tr->W, &ftrial);CHKERRQ(ierr);

          if (PetscIsInfOrNanReal(ftrial)) {
            tao->trust = tr->alpha1 * PetscMin(tao->trust, norm_d);
          } else {
            /* Compute and actual reduction */
            actred = f - ftrial;
            prered = -prered;
            if ((PetscAbsScalar(actred) <= tr->epsilon) &&
                (PetscAbsScalar(prered) <= tr->epsilon)) {
              kappa = 1.0;
            }
            else {
              kappa = actred / prered;
            }

            /* Accept or reject the step and update radius */
            if (kappa < tr->eta1) {
              /* Reject the step */
              tao->trust = tr->alpha1 * PetscMin(tao->trust, norm_d);
            }
            else {
              /* Accept the step */
              if (kappa < tr->eta2) {
                /* Marginal bad step */
                tao->trust = tr->alpha2 * PetscMin(tao->trust, norm_d);
              }
              else if (kappa < tr->eta3) {
                /* Reasonable step */
                tao->trust = tr->alpha3 * tao->trust;
              }
              else if (kappa < tr->eta4) {
                /* Good step */
                tao->trust = PetscMax(tr->alpha4 * norm_d, tao->trust);
              }
              else {
                /* Very good step */
                tao->trust = PetscMax(tr->alpha5 * norm_d, tao->trust);
              }
              break;
            }
          }
        }
      }
      else {
        /* Get predicted reduction */
        if (NTR_KSP_NASH == tr->ksp_type) {
          ierr = KSPNASHGetObjFcn(tao->ksp,&prered);CHKERRQ(ierr);
        } else if (NTR_KSP_STCG == tr->ksp_type) {
          ierr = KSPSTCGGetObjFcn(tao->ksp,&prered);CHKERRQ(ierr);
        } else { /* gltr */
          ierr = KSPGLTRGetObjFcn(tao->ksp,&prered);CHKERRQ(ierr);
        }

        if (prered >= 0.0) {
          /* The predicted reduction has the wrong sign.  This cannot
             happen in infinite precision arithmetic.  Step should
             be rejected! */
          tao->trust = tr->gamma1 * PetscMin(tao->trust, norm_d);
        }
        else {
          ierr = VecCopy(tao->solution, tr->W);CHKERRQ(ierr);
          ierr = VecAXPY(tr->W, 1.0, tao->stepdirection);CHKERRQ(ierr);
          ierr = TaoComputeObjective(tao, tr->W, &ftrial);CHKERRQ(ierr);
          if (PetscIsInfOrNanReal(ftrial)) {
            tao->trust = tr->gamma1 * PetscMin(tao->trust, norm_d);
          }
          else {
            ierr = VecDot(tao->gradient, tao->stepdirection, &beta);CHKERRQ(ierr);
            actred = f - ftrial;
            prered = -prered;
            if ((PetscAbsScalar(actred) <= tr->epsilon) &&
                (PetscAbsScalar(prered) <= tr->epsilon)) {
              kappa = 1.0;
            }
            else {
              kappa = actred / prered;
            }

            tau_1 = tr->theta * beta / (tr->theta * beta - (1.0 - tr->theta) * prered + actred);
            tau_2 = tr->theta * beta / (tr->theta * beta + (1.0 + tr->theta) * prered - actred);
            tau_min = PetscMin(tau_1, tau_2);
            tau_max = PetscMax(tau_1, tau_2);

            if (kappa >= 1.0 - tr->mu1) {
              /* Great agreement; accept step and update radius */
              if (tau_max < 1.0) {
                tao->trust = PetscMax(tao->trust, tr->gamma3 * norm_d);
              }
              else if (tau_max > tr->gamma4) {
                tao->trust = PetscMax(tao->trust, tr->gamma4 * norm_d);
              }
              else {
                tao->trust = PetscMax(tao->trust, tau_max * norm_d);
              }
              break;
            }
            else if (kappa >= 1.0 - tr->mu2) {
              /* Good agreement */

              if (tau_max < tr->gamma2) {
                tao->trust = tr->gamma2 * PetscMin(tao->trust, norm_d);
              }
              else if (tau_max > tr->gamma3) {
                tao->trust = PetscMax(tao->trust, tr->gamma3 * norm_d);
              }
              else if (tau_max < 1.0) {
                tao->trust = tau_max * PetscMin(tao->trust, norm_d);
              }
              else {
                tao->trust = PetscMax(tao->trust, tau_max * norm_d);
              }
              break;
            }
            else {
              /* Not good agreement */
              if (tau_min > 1.0) {
                tao->trust = tr->gamma2 * PetscMin(tao->trust, norm_d);
              }
              else if (tau_max < tr->gamma1) {
                tao->trust = tr->gamma1 * PetscMin(tao->trust, norm_d);
              }
              else if ((tau_min < tr->gamma1) && (tau_max >= 1.0)) {
                tao->trust = tr->gamma1 * PetscMin(tao->trust, norm_d);
              }
              else if ((tau_1 >= tr->gamma1) && (tau_1 < 1.0) &&
                       ((tau_2 < tr->gamma1) || (tau_2 >= 1.0))) {
                tao->trust = tau_1 * PetscMin(tao->trust, norm_d);
              }
              else if ((tau_2 >= tr->gamma1) && (tau_2 < 1.0) &&
                       ((tau_1 < tr->gamma1) || (tau_2 >= 1.0))) {
                tao->trust = tau_2 * PetscMin(tao->trust, norm_d);
              }
              else {
                tao->trust = tau_max * PetscMin(tao->trust, norm_d);
              }
            }
          }
        }
      }

      /* The step computed was not good and the radius was decreased.
         Monitor the radius to terminate. */
      ierr = TaoMonitor(tao, iter, f, gnorm, 0.0, tao->trust, &reason);CHKERRQ(ierr);
    }

    /* The radius may have been increased; modify if it is too large */
    tao->trust = PetscMin(tao->trust, tr->max_radius);

    if (reason == TAO_CONTINUE_ITERATING) {
      ierr = VecCopy(tr->W, tao->solution);CHKERRQ(ierr);
      f = ftrial;
      ierr = TaoComputeGradient(tao, tao->solution, tao->gradient);
      ierr = VecNorm(tao->gradient, NORM_2, &gnorm);CHKERRQ(ierr);
      if (PetscIsInfOrNanReal(f) || PetscIsInfOrNanReal(gnorm)) SETERRQ(PETSC_COMM_SELF,1, "User provided compute function generated Inf or NaN");
      needH = 1;
      ierr = TaoMonitor(tao, iter, f, gnorm, 0.0, tao->trust, &reason);CHKERRQ(ierr);
    }
  }
  PetscFunctionReturn(0);
}
Пример #9
0
krylov_petsc_info_t
krylov_petsc_solve
(
 p4est_t* p4est,
 problem_data_t* vecs,
 weakeqn_ptrs_t* fcns,
 p4est_ghost_t** ghost,
 element_data_t** ghost_data, 
 dgmath_jit_dbase_t* dgmath_jit_dbase,
 krylov_petsc_params_t* krylov_params
)
{
  krylov_petsc_info_t info;
  KSP ksp;
  Vec x,b;
  PC             pc;
  /* double* u_temp; */
  /* double* rhs_temp; */

  KSPCreate(PETSC_COMM_WORLD,&ksp);  
  VecCreate(PETSC_COMM_WORLD,&x);//CHKERRQ(ierr);
  VecSetSizes(x, vecs->local_nodes, PETSC_DECIDE);//CHKERRQ(ierr);
  VecSetFromOptions(x);//CHKERRQ(ierr);
  VecDuplicate(x,&b);//CHKERRQ(ierr);
  /* VecGetArray(x,&u_temp); */
  /* VecGetArray(b,&rhs_temp); */

  krylov_pc_ctx_t kct;
  kct.p4est = p4est;
  kct.vecs = vecs;
  kct.fcns = fcns;
  kct.ghost = ghost;
  kct.ghost_data = ghost_data;
  kct.dgmath_jit_dbase = dgmath_jit_dbase;
  kct.pc_data = krylov_params->pc_data;
  if (krylov_params->ksp_monitor)
    PetscOptionsSetValue(NULL,"-ksp_monitor","");
  if (krylov_params->ksp_monitor)
    PetscOptionsSetValue(NULL,"-ksp_view","");
    /* KSPMonitorSet(ksp, KSPMonitorDefault, NULL, NULL); */

  /* PetscOptionsSetValue(NULL,"-ksp_converged_reason",""); */
  PetscOptionsSetValue(NULL,"-ksp_atol","1e-20");
  /* PetscOptionsSetValue(NULL,"-with-debugging","1"); */
  PetscOptionsSetValue(NULL,"-ksp_rtol","1e-20");
  PetscOptionsSetValue(NULL,"-ksp_max_it","1000000");

  KSPGetPC(ksp,&pc);
  krylov_pc_t* kp = NULL;
  if (krylov_params != NULL && krylov_params->user_defined_pc) {
    PCSetType(pc,PCSHELL);//CHKERRQ(ierr);
    kp = krylov_params->pc_create(&kct);
    PCShellSetApply(pc, krylov_petsc_pc_apply);//CHKERRQ(ierr);
    PCShellSetSetUp(pc, krylov_petsc_pc_setup);
    PCShellSetContext(pc, kp);//CHKERRQ(ierr);
  }
  else {
    PCSetType(pc,PCNONE);//CHKERRQ(ierr);
  }

  KSPSetType(ksp, krylov_params->krylov_type);
  KSPSetFromOptions(ksp);

  /* Create matrix-free shell for Aij */
  Mat A;
  MatCreateShell
    (
     PETSC_COMM_WORLD,
     vecs->local_nodes,
     vecs->local_nodes,
     PETSC_DETERMINE,
     PETSC_DETERMINE,
     (void*)&kct,
     &A
    ); 
  MatShellSetOperation(A,MATOP_MULT,(void(*)())krylov_petsc_apply_aij);

  /* Set Amat and Pmat, where Pmat is the matrix the Preconditioner needs */
  KSPSetOperators(ksp,A,A);

  /* linalg_copy_1st_to_2nd(vecs->u, u_temp, vecs->local_nodes); */
  /* linalg_copy_1st_to_2nd(vecs->rhs, rhs_temp, vecs->local_nodes); */

  VecPlaceArray(b, vecs->rhs);
  VecPlaceArray(x, vecs->u);
  
  KSPSolve(ksp,b,x);

  if (krylov_params != NULL && krylov_params->user_defined_pc) {
    krylov_params->pc_destroy(kp);
  }
  
  KSPGetIterationNumber(ksp, &(info.iterations));
  KSPGetResidualNorm(ksp, &(info.residual_norm));
  
  /* linalg_copy_1st_to_2nd(u_temp, vecs->u, vecs->local_nodes); */

  /* VecRestoreArray(x,&u_temp); */
  /* VecRestoreArray(b,&rhs_temp); */
  VecResetArray(b);
  VecResetArray(x);
  VecDestroy(&x);
  VecDestroy(&b);
  KSPDestroy(&ksp);

  return info;
}
Пример #10
0
void SolverLinearPetsc<T>::init ()
{
    // Initialize the data structures if not done so already.
    if ( !this->initialized() )
    {
        this->setInitialized(  true );

        int ierr=0;

        // 2.1.x & earlier style
#if (PETSC_VERSION_MAJOR == 2) && (PETSC_VERSION_MINOR <= 1)

        // Create the linear solver context
        ierr = SLESCreate ( this->worldComm().globalComm(), &M_sles );
        CHKERRABORT( this->worldComm().globalComm(),ierr );

        // Create the Krylov subspace & preconditioner contexts
        ierr = SLESGetKSP       ( M_sles, &M_ksp );
        CHKERRABORT( this->worldComm().globalComm(),ierr );
        ierr = SLESGetPC        ( M_sles, &M_pc );
        CHKERRABORT( this->worldComm().globalComm(),ierr );

        // Have the Krylov subspace method use our good initial guess rather than 0
        ierr = KSPSetInitialGuessNonzero ( M_ksp, PETSC_TRUE );
        CHKERRABORT( this->worldComm().globalComm(),ierr );

        // Set user-specified  solver and preconditioner types
        this->setPetscSolverType();
        this->setPetscPreconditionerType();
        this->setPetscConstantNullSpace();

        // Set the options from user-input
        // Set runtime options, e.g.,
        //      -ksp_type <type> -pc_type <type> -ksp_monitor -ksp_rtol <rtol>
        //  These options will override those specified above as long as
        //  SLESSetFromOptions() is called _after_ any other customization
        //  routines.

        ierr = SLESSetFromOptions ( M_sles );
        CHKERRABORT( this->worldComm().globalComm(),ierr );

        // 2.2.0 & newer style
#else

        // Create the linear solver context
        ierr = KSPCreate ( this->worldComm().globalComm(), &M_ksp );
        CHKERRABORT( this->worldComm().globalComm(),ierr );

        // Create the preconditioner context
        ierr = KSPGetPC        ( M_ksp, &M_pc );
        CHKERRABORT( this->worldComm().globalComm(),ierr );

        // Have the Krylov subspace method use our good initial guess rather than 0
        ierr = KSPSetInitialGuessNonzero ( M_ksp, PETSC_TRUE );
        CHKERRABORT( this->worldComm().globalComm(),ierr );

        // Set user-specified  solver and preconditioner types
        this->setPetscSolverType();
        this->setPetscConstantNullSpace();


        // Set the options from user-input
        // Set runtime options, e.g.,
        //      -ksp_type <type> -pc_type <type> -ksp_monitor -ksp_rtol <rtol>
        //  These options will override those specified above as long as
        //  KSPSetFromOptions() is called _after_ any other customization
        //  routines.
        //ierr = PCSetFromOptions ( M_pc );
        //CHKERRABORT( this->worldComm().globalComm(),ierr );
        ierr = KSPSetFromOptions ( M_ksp );
        CHKERRABORT( this->worldComm().globalComm(),ierr );


#endif

        // Have the Krylov subspace method use our good initial guess
        // rather than 0, unless the user requested a KSPType of
        // preonly, which complains if asked to use initial guesses.
#if PETSC_VERSION_LESS_THAN(3,0,0)
        KSPType ksp_type;
#else
#if PETSC_VERSION_LESS_THAN(3,4,0)
        const KSPType ksp_type;
#else
        KSPType ksp_type;
#endif
#endif

        ierr = KSPGetType ( M_ksp, &ksp_type );
        CHKERRABORT( this->worldComm().globalComm(),ierr );

        if ( std::string((char*)ksp_type) == std::string( ( char* )KSPPREONLY ) )
        {
            ierr = KSPSetInitialGuessNonzero ( M_ksp, PETSC_FALSE );
            CHKERRABORT( this->worldComm().globalComm(),ierr );
        }

        if ( std::string((char*)ksp_type) == std::string( ( char* )KSPGMRES ) )
        {
            int nRestartGMRES = option(_name="gmres-restart", _prefix=this->prefix() ).template as<int>();
            ierr = KSPGMRESSetRestart( M_ksp, nRestartGMRES );
            CHKERRABORT( this->worldComm().globalComm(),ierr );
        }
        // Notify PETSc of location to store residual history.
        // This needs to be called before any solves, since
        // it sets the residual history length to zero.  The default
        // behavior is for PETSc to allocate (internally) an array
        // of size 1000 to hold the residual norm history.
        ierr = KSPSetResidualHistory( M_ksp,
                                      PETSC_NULL,   // pointer to the array which holds the history
                                      PETSC_DECIDE, // size of the array holding the history
                                      PETSC_TRUE ); // Whether or not to reset the history for each solve.
        CHKERRABORT( this->worldComm().globalComm(),ierr );

        //If there is a preconditioner object we need to set the internal setup and apply routines
        if ( this->M_preconditioner )
        {
            VLOG(2) << "preconditioner: "  << this->M_preconditioner << "\n";

            PCSetType(M_pc, PCSHELL);
            PCShellSetName( M_pc, this->M_preconditioner->name().c_str() );
            PCShellSetContext( M_pc,( void* )this->M_preconditioner.get() );
            PCShellSetSetUp( M_pc,__feel_petsc_preconditioner_setup );
            PCShellSetApply( M_pc,__feel_petsc_preconditioner_apply );
            PCShellSetView( M_pc,__feel_petsc_preconditioner_view );
#if PETSC_VERSION_LESS_THAN(3,4,0)
            const PCType pc_type;
#else
            PCType pc_type;
#endif
            ierr = PCGetType ( M_pc, &pc_type );
            CHKERRABORT( this->worldComm().globalComm(),ierr );

            VLOG(2) << "preconditioner set as "  << pc_type << "\n";
        }
        else
        {
            this->setPetscPreconditionerType();
            // sets the software that is used to perform the factorization
            PetscPCFactorSetMatSolverPackage( M_pc,this->matSolverPackageType() );
        }

        if ( Environment::vm(_name="ksp-monitor",_prefix=this->prefix()).template as<bool>() )
        {
            KSPMonitorSet( M_ksp,KSPMonitorDefault,PETSC_NULL,PETSC_NULL );
        }

    }
}
void IBImplicitStaggeredHierarchyIntegrator::integrateHierarchy(const double current_time,
                                                                const double new_time,
                                                                const int cycle_num)
{
    IBHierarchyIntegrator::integrateHierarchy(current_time, new_time, cycle_num);

    Pointer<INSStaggeredHierarchyIntegrator> ins_hier_integrator = d_ins_hier_integrator;
    TBOX_ASSERT(ins_hier_integrator);

    PetscErrorCode ierr;
    int n_local;

    const int coarsest_ln = 0;
    const int finest_ln = d_hierarchy->getFinestLevelNumber();
    //  const double half_time = current_time+0.5*(new_time-current_time);

    VariableDatabase<NDIM>* var_db = VariableDatabase<NDIM>::getDatabase();
    Pointer<VariableContext> current_ctx = ins_hier_integrator->getCurrentContext();
    Pointer<VariableContext> scratch_ctx = ins_hier_integrator->getScratchContext();
    Pointer<VariableContext> new_ctx = ins_hier_integrator->getNewContext();

    const int wgt_cc_idx = d_hier_math_ops->getCellWeightPatchDescriptorIndex();
    const int wgt_sc_idx = d_hier_math_ops->getSideWeightPatchDescriptorIndex();

    Pointer<Variable<NDIM> > u_var = ins_hier_integrator->getVelocityVariable();
    //  const int u_current_idx = var_db->mapVariableAndContextToIndex(u_var, current_ctx);
    const int u_scratch_idx = var_db->mapVariableAndContextToIndex(u_var, scratch_ctx);
    //  const int u_new_idx     = var_db->mapVariableAndContextToIndex(u_var, new_ctx);

    Pointer<Variable<NDIM> > p_var = ins_hier_integrator->getPressureVariable();
    //  const int p_current_idx = var_db->mapVariableAndContextToIndex(p_var, current_ctx);
    const int p_scratch_idx = var_db->mapVariableAndContextToIndex(p_var, scratch_ctx);
    //  const int p_new_idx     = var_db->mapVariableAndContextToIndex(p_var, new_ctx);

    // Skip all cycles in the INS solver --- we advance the state data here.
    ins_hier_integrator->skipCycle(current_time, new_time, cycle_num);

    // Setup Eulerian vectors used in solving the implicit IB equations.
    Pointer<SAMRAIVectorReal<NDIM, double> > eul_sol_vec = new SAMRAIVectorReal<NDIM, double>(
        d_object_name + "::eulerian_sol_vec", d_hierarchy, coarsest_ln, finest_ln);
    eul_sol_vec->addComponent(u_var, u_scratch_idx, wgt_sc_idx, d_hier_velocity_data_ops);
    eul_sol_vec->addComponent(p_var, p_scratch_idx, wgt_cc_idx, d_hier_pressure_data_ops);

    Pointer<SAMRAIVectorReal<NDIM, double> > eul_rhs_vec =
        eul_sol_vec->cloneVector(d_object_name + "::eulerian_rhs_vec");
    eul_rhs_vec->allocateVectorData(current_time);

    d_u_scratch_vec = eul_sol_vec->cloneVector(d_object_name + "::u_scratch_vec");
    d_f_scratch_vec = eul_rhs_vec->cloneVector(d_object_name + "::f_scratch_vec");
    d_u_scratch_vec->allocateVectorData(current_time);
    d_f_scratch_vec->allocateVectorData(current_time);

    ins_hier_integrator->setupSolverVectors(
        eul_sol_vec, eul_rhs_vec, current_time, new_time, cycle_num);

    d_stokes_solver = ins_hier_integrator->getStokesSolver();
    Pointer<KrylovLinearSolver> p_stokes_solver = d_stokes_solver;
    TBOX_ASSERT(p_stokes_solver);
    d_stokes_op = p_stokes_solver->getOperator();
    TBOX_ASSERT(d_stokes_op);

    // Setup Lagrangian vectors used in solving the implicit IB equations.
    Vec lag_sol_petsc_vec, lag_rhs_petsc_vec;
    d_ib_implicit_ops->createSolverVecs(lag_sol_petsc_vec, lag_rhs_petsc_vec);
    d_ib_implicit_ops->setupSolverVecs(lag_sol_petsc_vec, lag_rhs_petsc_vec);

    // Indicate that the current approximation to position of the structure
    // should be used for Lagrangian-Eulerian coupling.
    d_ib_implicit_ops->updateFixedLEOperators();

    // Setup multi-vec objects to store the composite solution and
    // right-hand-side vectors.
    Vec eul_sol_petsc_vec =
        PETScSAMRAIVectorReal::createPETScVector(eul_sol_vec, PETSC_COMM_WORLD);
    Vec eul_rhs_petsc_vec =
        PETScSAMRAIVectorReal::createPETScVector(eul_rhs_vec, PETSC_COMM_WORLD);

    Vec sol_petsc_vecs[] = { eul_sol_petsc_vec, lag_sol_petsc_vec };
    Vec rhs_petsc_vecs[] = { eul_rhs_petsc_vec, lag_rhs_petsc_vec };

    Vec composite_sol_petsc_vec, composite_rhs_petsc_vec, composite_res_petsc_vec;
    ierr = VecCreateMultiVec(PETSC_COMM_WORLD, 2, sol_petsc_vecs, &composite_sol_petsc_vec);
    IBTK_CHKERRQ(ierr);
    ierr = VecCreateMultiVec(PETSC_COMM_WORLD, 2, rhs_petsc_vecs, &composite_rhs_petsc_vec);
    IBTK_CHKERRQ(ierr);
    ierr = VecDuplicate(composite_rhs_petsc_vec, &composite_res_petsc_vec);
    IBTK_CHKERRQ(ierr);

    // Solve the implicit IB equations.
    d_ib_implicit_ops->preprocessSolveFluidEquations(current_time, new_time, cycle_num);

    SNES snes;
    ierr = SNESCreate(PETSC_COMM_WORLD, &snes);
    IBTK_CHKERRQ(ierr);
    ierr = SNESSetFunction(snes, composite_res_petsc_vec, compositeIBFunction_SAMRAI, this);
    IBTK_CHKERRQ(ierr);
    ierr = SNESSetOptionsPrefix(snes, "ib_");
    IBTK_CHKERRQ(ierr);

    Mat jac;
    ierr = VecGetLocalSize(composite_sol_petsc_vec, &n_local);
    IBTK_CHKERRQ(ierr);
    ierr = MatCreateShell(
        PETSC_COMM_WORLD, n_local, n_local, PETSC_DETERMINE, PETSC_DETERMINE, this, &jac);
    IBTK_CHKERRQ(ierr);
    ierr = MatShellSetOperation(
        jac, MATOP_MULT, reinterpret_cast<void (*)(void)>(compositeIBJacobianApply_SAMRAI));
    IBTK_CHKERRQ(ierr);
    ierr = SNESSetJacobian(snes, jac, jac, compositeIBJacobianSetup_SAMRAI, this);
    IBTK_CHKERRQ(ierr);

    Mat schur;
    ierr = VecGetLocalSize(lag_sol_petsc_vec, &n_local);
    IBTK_CHKERRQ(ierr);
    ierr = MatCreateShell(
        PETSC_COMM_WORLD, n_local, n_local, PETSC_DETERMINE, PETSC_DETERMINE, this, &schur);
    IBTK_CHKERRQ(ierr);
    ierr = MatShellSetOperation(
        schur, MATOP_MULT, reinterpret_cast<void (*)(void)>(lagrangianSchurApply_SAMRAI));
    IBTK_CHKERRQ(ierr);
    ierr = KSPCreate(PETSC_COMM_WORLD, &d_schur_solver);
    IBTK_CHKERRQ(ierr);
    ierr = KSPSetOptionsPrefix(d_schur_solver, "ib_schur_");
    IBTK_CHKERRQ(ierr);
    ierr = KSPSetOperators(d_schur_solver, schur, schur, SAME_PRECONDITIONER);
    IBTK_CHKERRQ(ierr);
    PC schur_pc;
    ierr = KSPGetPC(d_schur_solver, &schur_pc);
    IBTK_CHKERRQ(ierr);
    ierr = PCSetType(schur_pc, PCNONE);
    IBTK_CHKERRQ(ierr);
    ierr = KSPSetFromOptions(d_schur_solver);
    IBTK_CHKERRQ(ierr);

    KSP snes_ksp;
    ierr = SNESGetKSP(snes, &snes_ksp);
    IBTK_CHKERRQ(ierr);
    ierr = KSPSetType(snes_ksp, KSPFGMRES);
    IBTK_CHKERRQ(ierr);
    PC snes_pc;
    ierr = KSPGetPC(snes_ksp, &snes_pc);
    IBTK_CHKERRQ(ierr);
    ierr = PCSetType(snes_pc, PCSHELL);
    IBTK_CHKERRQ(ierr);
    ierr = PCShellSetContext(snes_pc, this);
    IBTK_CHKERRQ(ierr);
    ierr = PCShellSetApply(snes_pc, compositeIBPCApply_SAMRAI);
    IBTK_CHKERRQ(ierr);

    ierr = SNESSetFromOptions(snes);
    IBTK_CHKERRQ(ierr);
    ierr = SNESSolve(snes, composite_rhs_petsc_vec, composite_sol_petsc_vec);
    IBTK_CHKERRQ(ierr);
    ierr = SNESDestroy(&snes);
    IBTK_CHKERRQ(ierr);
    ierr = MatDestroy(&jac);
    IBTK_CHKERRQ(ierr);
    ierr = MatDestroy(&schur);
    IBTK_CHKERRQ(ierr);
    ierr = KSPDestroy(&d_schur_solver);
    IBTK_CHKERRQ(ierr);

    d_ib_implicit_ops->postprocessSolveFluidEquations(current_time, new_time, cycle_num);

    // Reset Eulerian solver vectors and Eulerian state data.
    ins_hier_integrator->resetSolverVectors(
        eul_sol_vec, eul_rhs_vec, current_time, new_time, cycle_num);

    // Interpolate the Eulerian velocity to the curvilinear mesh.
    d_ib_implicit_ops->setUpdatedPosition(lag_sol_petsc_vec);
#if 0
    d_hier_velocity_data_ops->linearSum(d_u_idx, 0.5, u_current_idx, 0.5, u_new_idx);
    if (d_enable_logging) plog << d_object_name << "::integrateHierarchy(): interpolating Eulerian velocity to the Lagrangian mesh\n";
    d_ib_implicit_ops->interpolateVelocity(d_u_idx, getCoarsenSchedules(d_object_name+"::u::CONSERVATIVE_COARSEN"), getGhostfillRefineSchedules(d_object_name+"::u"), half_time);

    // Compute the final value of the updated positions of the Lagrangian
    // structure.
    d_ib_implicit_ops->midpointStep(current_time, new_time);
#endif

    // Deallocate temporary data.
    ierr = VecDestroy(&composite_sol_petsc_vec);
    IBTK_CHKERRQ(ierr);
    ierr = VecDestroy(&composite_rhs_petsc_vec);
    IBTK_CHKERRQ(ierr);
    ierr = VecDestroy(&composite_res_petsc_vec);
    IBTK_CHKERRQ(ierr);
    PETScSAMRAIVectorReal::destroyPETScVector(eul_sol_petsc_vec);
    PETScSAMRAIVectorReal::destroyPETScVector(eul_rhs_petsc_vec);
    eul_rhs_vec->freeVectorComponents();
    d_u_scratch_vec->freeVectorComponents();
    d_f_scratch_vec->freeVectorComponents();
    ierr = VecDestroy(&lag_sol_petsc_vec);
    IBTK_CHKERRQ(ierr);
    ierr = VecDestroy(&lag_rhs_petsc_vec);
    IBTK_CHKERRQ(ierr);

    // Execute any registered callbacks.
    executeIntegrateHierarchyCallbackFcns(current_time, new_time, cycle_num);
    return;
} // integrateHierarchy