/*
    This file implements PGMRES (a Pipelined Generalized Minimal Residual method)
*/

#include <../src/ksp/ksp/impls/gmres/pgmres/pgmresimpl.h> /*I  "petscksp.h"  I*/

static PetscErrorCode KSPPGMRESUpdateHessenberg(KSP, PetscInt, PetscBool *, PetscReal *);
static PetscErrorCode KSPPGMRESBuildSoln(PetscScalar *, Vec, Vec, KSP, PetscInt);

static PetscErrorCode KSPSetUp_PGMRES(KSP ksp)
{
  PetscFunctionBegin;
  PetscCall(KSPSetUp_GMRES(ksp));
  PetscFunctionReturn(PETSC_SUCCESS);
}

static PetscErrorCode KSPPGMRESCycle(PetscInt *itcount, KSP ksp)
{
  KSP_PGMRES *pgmres = (KSP_PGMRES *)ksp->data;
  PetscReal   res_norm, res, newnorm;
  PetscInt    it     = 0, j, k;
  PetscBool   hapend = PETSC_FALSE;

  PetscFunctionBegin;
  if (itcount) *itcount = 0;
  PetscCall(VecNormalize(VEC_VV(0), &res_norm));
  KSPCheckNorm(ksp, res_norm);
  res    = res_norm;
  *RS(0) = res_norm;

  /* check for the convergence */
  PetscCall(PetscObjectSAWsTakeAccess((PetscObject)ksp));
  if (ksp->normtype != KSP_NORM_NONE) ksp->rnorm = res;
  else ksp->rnorm = 0;
  PetscCall(PetscObjectSAWsGrantAccess((PetscObject)ksp));
  pgmres->it = it - 2;
  PetscCall(KSPLogResidualHistory(ksp, ksp->rnorm));
  PetscCall(KSPMonitor(ksp, ksp->its, ksp->rnorm));
  if (!res) {
    ksp->reason = KSP_CONVERGED_ATOL;
    PetscCall(PetscInfo(ksp, "Converged due to zero residual norm on entry\n"));
    PetscFunctionReturn(PETSC_SUCCESS);
  }

  PetscCall((*ksp->converged)(ksp, ksp->its, ksp->rnorm, &ksp->reason, ksp->cnvP));
  for (; !ksp->reason; it++) {
    Vec Zcur, Znext;
    if (pgmres->vv_allocated <= it + VEC_OFFSET + 1) PetscCall(KSPGMRESGetNewVectors(ksp, it + 1));
    /* VEC_VV(it-1) is orthogonal, it will be normalized once the VecNorm arrives. */
    Zcur  = VEC_VV(it);     /* Zcur is not yet orthogonal, but the VecMDot to orthogonalize it has been started. */
    Znext = VEC_VV(it + 1); /* This iteration will compute Znext, update with a deferred correction once we know how
                               Zcur relates to the previous vectors, and start the reduction to orthogonalize it. */

    if (it < pgmres->max_k + 1 && ksp->its + 1 < PetscMax(2, ksp->max_it)) { /* We don't know whether what we have computed is enough, so apply the matrix. */
      PetscCall(KSP_PCApplyBAorAB(ksp, Zcur, Znext, VEC_TEMP_MATOP));
    }

    if (it > 1) { /* Complete the pending reduction */
      PetscCall(VecNormEnd(VEC_VV(it - 1), NORM_2, &newnorm));
      *HH(it - 1, it - 2) = newnorm;
    }
    if (it > 0) { /* Finish the reduction computing the latest column of H */
      PetscCall(VecMDotEnd(Zcur, it, &(VEC_VV(0)), HH(0, it - 1)));
    }

    if (it > 1) {
      /* normalize the base vector from two iterations ago, basis is complete up to here */
      PetscCall(VecScale(VEC_VV(it - 1), 1. / *HH(it - 1, it - 2)));

      PetscCall(KSPPGMRESUpdateHessenberg(ksp, it - 2, &hapend, &res));
      pgmres->it = it - 2;
      ksp->its++;
      if (ksp->normtype != KSP_NORM_NONE) ksp->rnorm = res;
      else ksp->rnorm = 0;

      PetscCall((*ksp->converged)(ksp, ksp->its, ksp->rnorm, &ksp->reason, ksp->cnvP));
      if (ksp->reason) break;
      if (it < pgmres->max_k + 1) { /* Monitor if we are not done or still iterating, but not before a restart. */
        PetscCall(KSPLogResidualHistory(ksp, ksp->rnorm));
        PetscCall(KSPMonitor(ksp, ksp->its, ksp->rnorm));
      }
      /* Catch error in happy breakdown and signal convergence and break from loop */
      if (hapend) {
        PetscCheck(!ksp->errorifnotconverged, PetscObjectComm((PetscObject)ksp), PETSC_ERR_NOT_CONVERGED, "Reached happy break down, but convergence was not indicated. Residual norm = %g", (double)res);
        ksp->reason = KSP_DIVERGED_BREAKDOWN;
        break;
      }

      if (!(it < pgmres->max_k + 1 && ksp->its < ksp->max_it)) break;

      /* The it-2 column of H was not scaled when we computed Zcur, apply correction */
      PetscCall(VecScale(Zcur, 1. / *HH(it - 1, it - 2)));
      /* And Znext computed in this iteration was computed using the under-scaled Zcur */
      PetscCall(VecScale(Znext, 1. / *HH(it - 1, it - 2)));

      /* In the previous iteration, we projected an unnormalized Zcur against the Krylov basis, so we need to fix the column of H resulting from that projection. */
      for (k = 0; k < it; k++) *HH(k, it - 1) /= *HH(it - 1, it - 2);
      /* When Zcur was projected against the Krylov basis, VV(it-1) was still not normalized, so fix that too. This
       * column is complete except for HH(it,it-1) which we won't know until the next iteration. */
      *HH(it - 1, it - 1) /= *HH(it - 1, it - 2);
    }

    if (it > 0) {
      PetscScalar *work;
      if (!pgmres->orthogwork) PetscCall(PetscMalloc1(pgmres->max_k + 2, &pgmres->orthogwork));
      work = pgmres->orthogwork;
      /* Apply correction computed by the VecMDot in the last iteration to Znext. The original form is
       *
       *   Znext -= sum_{j=0}^{i-1} Z[j+1] * H[j,i-1]
       *
       * where
       *
       *   Z[j] = sum_{k=0}^j V[k] * H[k,j-1]
       *
       * substituting
       *
       *   Znext -= sum_{j=0}^{i-1} sum_{k=0}^{j+1} V[k] * H[k,j] * H[j,i-1]
       *
       * rearranging the iteration space from row-column to column-row
       *
       *   Znext -= sum_{k=0}^i sum_{j=k-1}^{i-1} V[k] * H[k,j] * H[j,i-1]
       *
       * Note that column it-1 of HH is correct. For all previous columns, we must look at HES because HH has already
       * been transformed to upper triangular form.
       */
      for (k = 0; k < it + 1; k++) {
        work[k] = 0;
        for (j = PetscMax(0, k - 1); j < it - 1; j++) work[k] -= *HES(k, j) * *HH(j, it - 1);
      }
      PetscCall(VecMAXPY(Znext, it + 1, work, &VEC_VV(0)));
      PetscCall(VecAXPY(Znext, -*HH(it - 1, it - 1), Zcur));

      /* Orthogonalize Zcur against existing basis vectors. */
      for (k = 0; k < it; k++) work[k] = -*HH(k, it - 1);
      PetscCall(VecMAXPY(Zcur, it, work, &VEC_VV(0)));
      /* Zcur is now orthogonal, and will be referred to as VEC_VV(it) again, though it is still not normalized. */
      /* Begin computing the norm of the new vector, will be normalized after the MatMult in the next iteration. */
      PetscCall(VecNormBegin(VEC_VV(it), NORM_2, &newnorm));
    }

    /* Compute column of H (to the diagonal, but not the subdiagonal) to be able to orthogonalize the newest vector. */
    PetscCall(VecMDotBegin(Znext, it + 1, &VEC_VV(0), HH(0, it)));

    /* Start an asynchronous split-mode reduction, the result of the MDot and Norm will be collected on the next iteration. */
    PetscCall(PetscCommSplitReductionBegin(PetscObjectComm((PetscObject)Znext)));
  }
  if (itcount) *itcount = it - 1; /* Number of iterations actually completed. */

  /*
    Solve for the "best" coefficients of the Krylov
    columns, add the solution values together, and possibly unwind the preconditioning from the solution
   */
  /* Form the solution (or the solution so far) */
  PetscCall(KSPPGMRESBuildSoln(RS(0), ksp->vec_sol, ksp->vec_sol, ksp, it - 2));

  if (ksp->reason == KSP_CONVERGED_ITERATING && ksp->its == ksp->max_it) ksp->reason = KSP_DIVERGED_ITS;
  if (ksp->reason) {
    PetscCall(KSPLogResidualHistory(ksp, ksp->rnorm));
    PetscCall(KSPMonitor(ksp, ksp->its, ksp->rnorm));
  }
  PetscFunctionReturn(PETSC_SUCCESS);
}

static PetscErrorCode KSPSolve_PGMRES(KSP ksp)
{
  PetscInt    its, itcount;
  KSP_PGMRES *pgmres     = (KSP_PGMRES *)ksp->data;
  PetscBool   guess_zero = ksp->guess_zero;

  PetscFunctionBegin;
  PetscCheck(!ksp->calc_sings || pgmres->Rsvd, PetscObjectComm((PetscObject)ksp), PETSC_ERR_ORDER, "Must call KSPSetComputeSingularValues() before KSPSetUp() is called");
  PetscCall(PetscObjectSAWsTakeAccess((PetscObject)ksp));
  ksp->its = 0;
  PetscCall(PetscObjectSAWsGrantAccess((PetscObject)ksp));

  itcount     = 0;
  ksp->reason = KSP_CONVERGED_ITERATING;
  while (!ksp->reason) {
    PetscCall(KSPInitialResidual(ksp, ksp->vec_sol, VEC_TEMP, VEC_TEMP_MATOP, VEC_VV(0), ksp->vec_rhs));
    PetscCall(KSPPGMRESCycle(&its, ksp));
    itcount += its;
    if (itcount >= ksp->max_it) {
      if (!ksp->reason) ksp->reason = KSP_DIVERGED_ITS;
      break;
    }
    ksp->guess_zero = PETSC_FALSE; /* every future call to KSPInitialResidual() will have nonzero guess */
  }
  ksp->guess_zero = guess_zero; /* restore if user provided nonzero initial guess */
  PetscFunctionReturn(PETSC_SUCCESS);
}

static PetscErrorCode KSPDestroy_PGMRES(KSP ksp)
{
  PetscFunctionBegin;
  PetscCall(KSPDestroy_GMRES(ksp));
  PetscFunctionReturn(PETSC_SUCCESS);
}

static PetscErrorCode KSPPGMRESBuildSoln(PetscScalar *nrs, Vec vguess, Vec vdest, KSP ksp, PetscInt it)
{
  PetscScalar tt;
  PetscInt    k, j;
  KSP_PGMRES *pgmres = (KSP_PGMRES *)ksp->data;

  PetscFunctionBegin;
  /* Solve for solution vector that minimizes the residual */

  if (it < 0) {                        /* no pgmres steps have been performed */
    PetscCall(VecCopy(vguess, vdest)); /* VecCopy() is smart, exits immediately if vguess == vdest */
    PetscFunctionReturn(PETSC_SUCCESS);
  }

  /* solve the upper triangular system - RS is the right side and HH is
     the upper triangular matrix  - put soln in nrs */
  if (*HH(it, it) != 0.0) nrs[it] = *RS(it) / *HH(it, it);
  else nrs[it] = 0.0;

  for (k = it - 1; k >= 0; k--) {
    tt = *RS(k);
    for (j = k + 1; j <= it; j++) tt -= *HH(k, j) * nrs[j];
    nrs[k] = tt / *HH(k, k);
  }

  /* Accumulate the correction to the solution of the preconditioned problem in TEMP */
  PetscCall(VecMAXPBY(VEC_TEMP, it + 1, nrs, 0, &VEC_VV(0)));
  PetscCall(KSPUnwindPreconditioner(ksp, VEC_TEMP, VEC_TEMP_MATOP));
  /* add solution to previous solution */
  if (vdest == vguess) {
    PetscCall(VecAXPY(vdest, 1.0, VEC_TEMP));
  } else {
    PetscCall(VecWAXPY(vdest, 1.0, VEC_TEMP, vguess));
  }
  PetscFunctionReturn(PETSC_SUCCESS);
}

static PetscErrorCode KSPPGMRESUpdateHessenberg(KSP ksp, PetscInt it, PetscBool *hapend, PetscReal *res)
{
  PetscScalar *hh, *cc, *ss, *rs;
  PetscInt     j;
  PetscReal    hapbnd;
  KSP_PGMRES  *pgmres = (KSP_PGMRES *)ksp->data;

  PetscFunctionBegin;
  hh = HH(0, it); /* pointer to beginning of column to update */
  cc = CC(0);     /* beginning of cosine rotations */
  ss = SS(0);     /* beginning of sine rotations */
  rs = RS(0);     /* right-hand side of least squares system */

  /* The Hessenberg matrix is now correct through column it, save that form for possible spectral analysis */
  for (j = 0; j <= it + 1; j++) *HES(j, it) = hh[j];

  /* check for the happy breakdown */
  hapbnd = PetscMin(PetscAbsScalar(hh[it + 1] / rs[it]), pgmres->haptol);
  if (PetscAbsScalar(hh[it + 1]) < hapbnd) {
    PetscCall(PetscInfo(ksp, "Detected happy breakdown, current hapbnd = %14.12e H(%" PetscInt_FMT ",%" PetscInt_FMT ") = %14.12e\n", (double)hapbnd, it + 1, it, (double)PetscAbsScalar(*HH(it + 1, it))));
    *hapend = PETSC_TRUE;
  }

  /* Apply all the previously computed plane rotations to the new column of the Hessenberg matrix */
  /* Note: this uses the rotation [conj(c)  s ; -s   c], c= cos(theta), s= sin(theta),
     and some refs have [c   s ; -conj(s)  c] (don't be confused!) */

  for (j = 0; j < it; j++) {
    PetscScalar hhj = hh[j];
    hh[j]           = PetscConj(cc[j]) * hhj + ss[j] * hh[j + 1];
    hh[j + 1]       = -ss[j] * hhj + cc[j] * hh[j + 1];
  }

  /*
    compute the new plane rotation, and apply it to:
     1) the right-hand side of the Hessenberg system (RS)
        note: it affects RS(it) and RS(it+1)
     2) the new column of the Hessenberg matrix
        note: it affects HH(it,it) which is currently pointed to
        by hh and HH(it+1, it) (*(hh+1))
    thus obtaining the updated value of the residual...
  */

  /* compute new plane rotation */

  if (!*hapend) {
    PetscReal delta = PetscSqrtReal(PetscSqr(PetscAbsScalar(hh[it])) + PetscSqr(PetscAbsScalar(hh[it + 1])));
    if (delta == 0.0) {
      ksp->reason = KSP_DIVERGED_NULL;
      PetscFunctionReturn(PETSC_SUCCESS);
    }

    cc[it] = hh[it] / delta;     /* new cosine value */
    ss[it] = hh[it + 1] / delta; /* new sine value */

    hh[it]     = PetscConj(cc[it]) * hh[it] + ss[it] * hh[it + 1];
    rs[it + 1] = -ss[it] * rs[it];
    rs[it]     = PetscConj(cc[it]) * rs[it];
    *res       = PetscAbsScalar(rs[it + 1]);
  } else { /* happy breakdown: HH(it+1, it) = 0, therefore we don't need to apply
            another rotation matrix (so RH doesn't change).  The new residual is
            always the new sine term times the residual from last time (RS(it)),
            but now the new sine rotation would be zero...so the residual should
            be zero...so we will multiply "zero" by the last residual.  This might
            not be exactly what we want to do here -could just return "zero". */
    *res = 0.0;
  }
  PetscFunctionReturn(PETSC_SUCCESS);
}

static PetscErrorCode KSPBuildSolution_PGMRES(KSP ksp, Vec ptr, Vec *result)
{
  KSP_PGMRES *pgmres = (KSP_PGMRES *)ksp->data;

  PetscFunctionBegin;
  if (!ptr) {
    if (!pgmres->sol_temp) PetscCall(VecDuplicate(ksp->vec_sol, &pgmres->sol_temp));
    ptr = pgmres->sol_temp;
  }
  if (!pgmres->nrs) {
    /* allocate the work area */
    PetscCall(PetscMalloc1(pgmres->max_k, &pgmres->nrs));
  }

  PetscCall(KSPPGMRESBuildSoln(pgmres->nrs, ksp->vec_sol, ptr, ksp, pgmres->it));
  if (result) *result = ptr;
  PetscFunctionReturn(PETSC_SUCCESS);
}

static PetscErrorCode KSPSetFromOptions_PGMRES(KSP ksp, PetscOptionItems *PetscOptionsObject)
{
  PetscFunctionBegin;
  PetscCall(KSPSetFromOptions_GMRES(ksp, PetscOptionsObject));
  PetscOptionsHeadBegin(PetscOptionsObject, "KSP pipelined GMRES Options");
  PetscOptionsHeadEnd();
  PetscFunctionReturn(PETSC_SUCCESS);
}

static PetscErrorCode KSPReset_PGMRES(KSP ksp)
{
  PetscFunctionBegin;
  PetscCall(KSPReset_GMRES(ksp));
  PetscFunctionReturn(PETSC_SUCCESS);
}

/*MC
   KSPPGMRES - Implements the Pipelined Generalized Minimal Residual method {cite}`ghyselsashbymeerbergenvanroose2013`. [](sec_pipelineksp)

   Options Database Keys:
+   -ksp_gmres_restart <restart>                                                - the number of Krylov directions to orthogonalize against
.   -ksp_gmres_haptol <tol>                                                     - sets the tolerance for "happy ending" (exact convergence)
.   -ksp_gmres_preallocate                                                      - preallocate all the Krylov search directions initially
                                                                                (otherwise groups of vectors are allocated as needed)
.   -ksp_gmres_classicalgramschmidt                                             - use classical (unmodified) Gram-Schmidt to orthogonalize
                                                                                against the Krylov space (fast) (the default)
.   -ksp_gmres_modifiedgramschmidt                                              - use modified Gram-Schmidt in the orthogonalization (more stable, but slower)
.   -ksp_gmres_cgs_refinement_type <refine_never,refine_ifneeded,refine_always> - determine if iterative refinement is used to increase the
                                                                                stability of the classical Gram-Schmidt  orthogonalization.
-   -ksp_gmres_krylov_monitor                                                   - plot the Krylov space generated

   Level: beginner

   Note:
   MPI configuration may be necessary for reductions to make asynchronous progress, which is important for performance of pipelined methods.
   See [](doc_faq_pipelined)

   Developer Note:
   This object is subclassed off of `KSPGMRES`, see the source code in src/ksp/ksp/impls/gmres for comments on the structure of the code

.seealso: [](ch_ksp), [](sec_pipelineksp), [](doc_faq_pipelined), `KSPCreate()`, `KSPSetType()`, `KSPType`, `KSP`, `KSPGMRES`, `KSPLGMRES`, `KSPPIPECG`, `KSPPIPECR`,
          `KSPGMRESSetRestart()`, `KSPGMRESSetHapTol()`, `KSPGMRESSetPreAllocateVectors()`, `KSPGMRESSetOrthogonalization()`, `KSPGMRESGetOrthogonalization()`,
          `KSPGMRESClassicalGramSchmidtOrthogonalization()`, `KSPGMRESModifiedGramSchmidtOrthogonalization()`,
          `KSPGMRESCGSRefinementType`, `KSPGMRESSetCGSRefinementType()`, `KSPGMRESGetCGSRefinementType()`, `KSPGMRESMonitorKrylov()`
M*/

PETSC_EXTERN PetscErrorCode KSPCreate_PGMRES(KSP ksp)
{
  KSP_PGMRES *pgmres;

  PetscFunctionBegin;
  PetscCall(PetscNew(&pgmres));

  ksp->data                              = (void *)pgmres;
  ksp->ops->buildsolution                = KSPBuildSolution_PGMRES;
  ksp->ops->setup                        = KSPSetUp_PGMRES;
  ksp->ops->solve                        = KSPSolve_PGMRES;
  ksp->ops->reset                        = KSPReset_PGMRES;
  ksp->ops->destroy                      = KSPDestroy_PGMRES;
  ksp->ops->view                         = KSPView_GMRES;
  ksp->ops->setfromoptions               = KSPSetFromOptions_PGMRES;
  ksp->ops->computeextremesingularvalues = KSPComputeExtremeSingularValues_GMRES;
  ksp->ops->computeeigenvalues           = KSPComputeEigenvalues_GMRES;

  PetscCall(KSPSetSupportedNorm(ksp, KSP_NORM_PRECONDITIONED, PC_LEFT, 3));
  PetscCall(KSPSetSupportedNorm(ksp, KSP_NORM_UNPRECONDITIONED, PC_RIGHT, 2));
  PetscCall(KSPSetSupportedNorm(ksp, KSP_NORM_NONE, PC_RIGHT, 1));

  PetscCall(PetscObjectComposeFunction((PetscObject)ksp, "KSPGMRESSetPreAllocateVectors_C", KSPGMRESSetPreAllocateVectors_GMRES));
  PetscCall(PetscObjectComposeFunction((PetscObject)ksp, "KSPGMRESSetOrthogonalization_C", KSPGMRESSetOrthogonalization_GMRES));
  PetscCall(PetscObjectComposeFunction((PetscObject)ksp, "KSPGMRESGetOrthogonalization_C", KSPGMRESGetOrthogonalization_GMRES));
  PetscCall(PetscObjectComposeFunction((PetscObject)ksp, "KSPGMRESSetRestart_C", KSPGMRESSetRestart_GMRES));
  PetscCall(PetscObjectComposeFunction((PetscObject)ksp, "KSPGMRESGetRestart_C", KSPGMRESGetRestart_GMRES));
  PetscCall(PetscObjectComposeFunction((PetscObject)ksp, "KSPGMRESSetCGSRefinementType_C", KSPGMRESSetCGSRefinementType_GMRES));
  PetscCall(PetscObjectComposeFunction((PetscObject)ksp, "KSPGMRESGetCGSRefinementType_C", KSPGMRESGetCGSRefinementType_GMRES));

  pgmres->nextra_vecs    = 1;
  pgmres->haptol         = 1.0e-30;
  pgmres->q_preallocate  = 0;
  pgmres->delta_allocate = PGMRES_DELTA_DIRECTIONS;
  pgmres->orthog         = KSPGMRESClassicalGramSchmidtOrthogonalization;
  pgmres->nrs            = NULL;
  pgmres->sol_temp       = NULL;
  pgmres->max_k          = PGMRES_DEFAULT_MAXK;
  pgmres->Rsvd           = NULL;
  pgmres->orthogwork     = NULL;
  pgmres->cgstype        = KSP_GMRES_CGS_REFINE_NEVER;
  PetscFunctionReturn(PETSC_SUCCESS);
}
