Date: 2013-07-02T14:48:16+00:00

Actual source code: pgmres.c
petsc-3.4.2 2013-07-02

      2: /*
      3:     This file implements PGMRES (a Pipelined Generalized Minimal Residual method)
      4: */

      6: #include <../src/ksp/ksp/impls/gmres/pgmres/pgmresimpl.h>       /*I  "petscksp.h"  I*/
      7: #define PGMRES_DELTA_DIRECTIONS 10
      8: #define PGMRES_DEFAULT_MAXK     30

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

     13: /*

     15:     KSPSetUp_PGMRES - Sets up the workspace needed by pgmres.

     17:     This is called once, usually automatically by KSPSolve() or KSPSetUp(),
     18:     but can be called directly by KSPSetUp().

     20: */
     23: static PetscErrorCode KSPSetUp_PGMRES(KSP ksp)
     24: {

     28:   KSPSetUp_GMRES(ksp);
     29:   return(0);
     30: }

     32: /*

     34:     KSPPGMRESCycle - Run pgmres, possibly with restart.  Return residual
     35:                   history if requested.

     37:     input parameters:
     38: .        pgmres  - structure containing parameters and work areas

     40:     output parameters:
     41: .        itcount - number of iterations used.  If null, ignored.
     42: .        converged - 0 if not converged

     44:     Notes:
     45:     On entry, the value in vector VEC_VV(0) should be
     46:     the initial residual.

     49:  */
     52: static PetscErrorCode KSPPGMRESCycle(PetscInt *itcount,KSP ksp)
     53: {
     54:   KSP_PGMRES     *pgmres = (KSP_PGMRES*)(ksp->data);
     55:   PetscReal      res_norm,res,newnorm;
     57:   PetscInt       it     = 0,j,k;
     58:   PetscBool      hapend = PETSC_FALSE;

     61:   if (itcount) *itcount = 0;
     62:   VecNormalize(VEC_VV(0),&res_norm);
     63:   res    = res_norm;
     64:   *RS(0) = res_norm;

     66:   /* check for the convergence */
     67:   PetscObjectAMSTakeAccess((PetscObject)ksp);
     68:   ksp->rnorm = res;
     69:   PetscObjectAMSGrantAccess((PetscObject)ksp);
     70:   pgmres->it = it-2;
     71:   KSPLogResidualHistory(ksp,res);
     72:   KSPMonitor(ksp,ksp->its,res);
     73:   if (!res) {
     74:     ksp->reason = KSP_CONVERGED_ATOL;
     75:     PetscInfo(ksp,"Converged due to zero residual norm on entry\n");
     76:     return(0);
     77:   }

     79:   (*ksp->converged)(ksp,ksp->its,res,&ksp->reason,ksp->cnvP);
     80:   for (; !ksp->reason; it++) {
     81:     Vec Zcur,Znext;
     82:     if (pgmres->vv_allocated <= it + VEC_OFFSET + 1) {
     83:       KSPGMRESGetNewVectors(ksp,it+1);
     84:     }
     85:     /* VEC_VV(it-1) is orthogonal, it will be normalized once the VecNorm arrives. */
     86:     Zcur  = VEC_VV(it);         /* Zcur is not yet orthogonal, but the VecMDot to orthogonalize it has been started. */
     87:     Znext = VEC_VV(it+1);       /* This iteration will compute Znext, update with a deferred correction once we know how
     88:                                  * Zcur relates to the previous vectors, and start the reduction to orthogonalize it. */

     90:     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. */
     91:       KSP_PCApplyBAorAB(ksp,Zcur,Znext,VEC_TEMP_MATOP);
     92:     }

     94:     if (it > 1) {               /* Complete the pending reduction */
     95:       VecNormEnd(VEC_VV(it-1),NORM_2,&newnorm);
     96:       *HH(it-1,it-2) = newnorm;
     97:     }
     98:     if (it > 0) {               /* Finish the reduction computing the latest column of H */
     99:       VecMDotEnd(Zcur,it,&(VEC_VV(0)),HH(0,it-1));
    100:     }

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

    106:       KSPPGMRESUpdateHessenberg(ksp,it-2,&hapend,&res);
    107:       pgmres->it = it-2;
    108:       ksp->its++;
    109:       ksp->rnorm = res;

    111:       (*ksp->converged)(ksp,ksp->its,res,&ksp->reason,ksp->cnvP);
    112:       if (it < pgmres->max_k+1 || ksp->reason || ksp->its == ksp->max_it) {  /* Monitor if we are done or still iterating, but not before a restart. */
    113:         KSPLogResidualHistory(ksp,res);
    114:         KSPMonitor(ksp,ksp->its,res);
    115:       }
    116:       if (ksp->reason) break;
    117:       /* Catch error in happy breakdown and signal convergence and break from loop */
    118:       if (hapend) {
    119:         if (ksp->errorifnotconverged) SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_NOT_CONVERGED,"You reached the happy break down, but convergence was not indicated. Residual norm = %G",res);
    120:         else {
    121:           ksp->reason = KSP_DIVERGED_BREAKDOWN;
    122:           break;
    123:         }
    124:       }

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

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

    133:       /* 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. */
    134:       for (k=0; k<it; k++) *HH(k,it-1) /= *HH(it-1,it-2);
    135:       /* When Zcur was projected against the Krylov basis, VV(it-1) was still not normalized, so fix that too. This
    136:        * column is complete except for HH(it,it-1) which we won't know until the next iteration. */
    137:       *HH(it-1,it-1) /= *HH(it-1,it-2);
    138:     }

    140:     if (it > 0) {
    141:       PetscScalar *work;
    142:       if (!pgmres->orthogwork) {PetscMalloc((pgmres->max_k + 2)*sizeof(PetscScalar),&pgmres->orthogwork);}
    143:       work = pgmres->orthogwork;
    144:       /* Apply correction computed by the VecMDot in the last iteration to Znext. The original form is
    145:        *
    146:        *   Znext -= sum_{j=0}^{i-1} Z[j+1] * H[j,i-1]
    147:        *
    148:        * where
    149:        *
    150:        *   Z[j] = sum_{k=0}^j V[k] * H[k,j-1]
    151:        *
    152:        * substituting
    153:        *
    154:        *   Znext -= sum_{j=0}^{i-1} sum_{k=0}^{j+1} V[k] * H[k,j] * H[j,i-1]
    155:        *
    156:        * rearranging the iteration space from row-column to column-row
    157:        *
    158:        *   Znext -= sum_{k=0}^i sum_{j=k-1}^{i-1} V[k] * H[k,j] * H[j,i-1]
    159:        *
    160:        * Note that column it-1 of HH is correct. For all previous columns, we must look at HES because HH has already
    161:        * been transformed to upper triangular form.
    162:        */
    163:       for (k=0; k<it+1; k++) {
    164:         work[k] = 0;
    165:         for (j=PetscMax(0,k-1); j<it-1; j++) work[k] -= *HES(k,j) * *HH(j,it-1);
    166:       }
    167:       VecMAXPY(Znext,it+1,work,&VEC_VV(0));
    168:       VecAXPY(Znext,-*HH(it-1,it-1),Zcur);

    170:       /* Orthogonalize Zcur against existing basis vectors. */
    171:       for (k=0; k<it; k++) work[k] = -*HH(k,it-1);
    172:       VecMAXPY(Zcur,it,work,&VEC_VV(0));
    173:       /* Zcur is now orthogonal, and will be referred to as VEC_VV(it) again, though it is still not normalized. */
    174:       /* Begin computing the norm of the new vector, will be normalized after the MatMult in the next iteration. */
    175:       VecNormBegin(VEC_VV(it),NORM_2,&newnorm);
    176:     }

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

    181:     /* Start an asynchronous split-mode reduction, the result of the MDot and Norm will be collected on the next iteration. */
    182:     PetscCommSplitReductionBegin(PetscObjectComm((PetscObject)Znext));
    183:   }

    185:   if (itcount) *itcount = it-1; /* Number of iterations actually completed. */

    187:   /*
    188:     Down here we have to solve for the "best" coefficients of the Krylov
    189:     columns, add the solution values together, and possibly unwind the
    190:     preconditioning from the solution
    191:    */
    192:   /* Form the solution (or the solution so far) */
    193:   KSPPGMRESBuildSoln(RS(0),ksp->vec_sol,ksp->vec_sol,ksp,it-2);
    194:   return(0);
    195: }

    197: /*
    198:     KSPSolve_PGMRES - This routine applies the PGMRES method.

    201:    Input Parameter:
    202: .     ksp - the Krylov space object that was set to use pgmres

    204:    Output Parameter:
    205: .     outits - number of iterations used

    207: */
    210: static PetscErrorCode KSPSolve_PGMRES(KSP ksp)
    211: {
    213:   PetscInt       its,itcount;
    214:   KSP_PGMRES     *pgmres    = (KSP_PGMRES*)ksp->data;
    215:   PetscBool      guess_zero = ksp->guess_zero;

    218:   if (ksp->calc_sings && !pgmres->Rsvd) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ORDER,"Must call KSPSetComputeSingularValues() before KSPSetUp() is called");
    219:   PetscObjectAMSTakeAccess((PetscObject)ksp);
    220:   ksp->its = 0;
    221:   PetscObjectAMSGrantAccess((PetscObject)ksp);

    223:   itcount     = 0;
    224:   ksp->reason = KSP_CONVERGED_ITERATING;
    225:   while (!ksp->reason) {
    226:     KSPInitialResidual(ksp,ksp->vec_sol,VEC_TEMP,VEC_TEMP_MATOP,VEC_VV(0),ksp->vec_rhs);
    227:     KSPPGMRESCycle(&its,ksp);
    228:     itcount += its;
    229:     if (itcount >= ksp->max_it) {
    230:       if (!ksp->reason) ksp->reason = KSP_DIVERGED_ITS;
    231:       break;
    232:     }
    233:     ksp->guess_zero = PETSC_FALSE; /* every future call to KSPInitialResidual() will have nonzero guess */
    234:   }
    235:   ksp->guess_zero = guess_zero; /* restore if user provided nonzero initial guess */
    236:   return(0);
    237: }

    241: static PetscErrorCode KSPDestroy_PGMRES(KSP ksp)
    242: {

    246:   KSPDestroy_GMRES(ksp);
    247:   return(0);
    248: }

    250: /*
    251:     KSPPGMRESBuildSoln - create the solution from the starting vector and the
    252:                       current iterates.

    254:     Input parameters:
    255:         nrs - work area of size it + 1.
    256:         vguess  - index of initial guess
    257:         vdest - index of result.  Note that vguess may == vdest (replace
    258:                 guess with the solution).
    259:         it - HH upper triangular part is a block of size (it+1) x (it+1)

    261:      This is an internal routine that knows about the PGMRES internals.
    262:  */
    265: static PetscErrorCode KSPPGMRESBuildSoln(PetscScalar *nrs,Vec vguess,Vec vdest,KSP ksp,PetscInt it)
    266: {
    267:   PetscScalar    tt;
    269:   PetscInt       k,j;
    270:   KSP_PGMRES     *pgmres = (KSP_PGMRES*)(ksp->data);

    273:   /* Solve for solution vector that minimizes the residual */

    275:   if (it < 0) {                                 /* no pgmres steps have been performed */
    276:     VecCopy(vguess,vdest); /* VecCopy() is smart, exits immediately if vguess == vdest */
    277:     return(0);
    278:   }

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

    285:   for (k=it-1; k>=0; k--) {
    286:     tt = *RS(k);
    287:     for (j=k+1; j<=it; j++) tt -= *HH(k,j) * nrs[j];
    288:     nrs[k] = tt / *HH(k,k);
    289:   }

    291:   /* Accumulate the correction to the solution of the preconditioned problem in TEMP */
    292:   VecZeroEntries(VEC_TEMP);
    293:   VecMAXPY(VEC_TEMP,it+1,nrs,&VEC_VV(0));
    294:   KSPUnwindPreconditioner(ksp,VEC_TEMP,VEC_TEMP_MATOP);
    295:   /* add solution to previous solution */
    296:   if (vdest == vguess) {
    297:     VecAXPY(vdest,1.0,VEC_TEMP);
    298:   } else {
    299:     VecWAXPY(vdest,1.0,VEC_TEMP,vguess);
    300:   }
    301:   return(0);
    302: }

    304: /*

    306:     KSPPGMRESUpdateHessenberg - Do the scalar work for the orthogonalization.
    307:                             Return new residual.

    309:     input parameters:

    311: .        ksp -    Krylov space object
    312: .        it  -    plane rotations are applied to the (it+1)th column of the
    313:                   modified hessenberg (i.e. HH(:,it))
    314: .        hapend - PETSC_FALSE not happy breakdown ending.

    316:     output parameters:
    317: .        res - the new residual

    319:  */
    322: /*
    323: .  it - column of the Hessenberg that is complete, PGMRES is actually computing two columns ahead of this
    324:  */
    325: static PetscErrorCode KSPPGMRESUpdateHessenberg(KSP ksp,PetscInt it,PetscBool *hapend,PetscReal *res)
    326: {
    327:   PetscScalar    *hh,*cc,*ss,*rs;
    328:   PetscInt       j;
    329:   PetscReal      hapbnd;
    330:   KSP_PGMRES     *pgmres = (KSP_PGMRES*)(ksp->data);

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

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

    342:   /* check for the happy breakdown */
    343:   hapbnd = PetscMin(PetscAbsScalar(hh[it+1] / rs[it]),pgmres->haptol);
    344:   if (PetscAbsScalar(hh[it+1]) < hapbnd) {
    345:     PetscInfo4(ksp,"Detected happy breakdown, current hapbnd = %14.12e H(%D,%D) = %14.12e\n",(double)hapbnd,it+1,it,(double)PetscAbsScalar(*HH(it+1,it)));
    346:     *hapend = PETSC_TRUE;
    347:   }

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

    354:   for (j=0; j<it; j++) {
    355:     PetscScalar hhj = hh[j];
    356:     hh[j]   = PetscConj(cc[j])*hhj + ss[j]*hh[j+1];
    357:     hh[j+1] =          -ss[j] *hhj + cc[j]*hh[j+1];
    358:   }

    360:   /*
    361:     compute the new plane rotation, and apply it to:
    362:      1) the right-hand-side of the Hessenberg system (RS)
    363:         note: it affects RS(it) and RS(it+1)
    364:      2) the new column of the Hessenberg matrix
    365:         note: it affects HH(it,it) which is currently pointed to
    366:         by hh and HH(it+1, it) (*(hh+1))
    367:     thus obtaining the updated value of the residual...
    368:   */

    370:   /* compute new plane rotation */

    372:   if (!*hapend) {
    373:     PetscReal delta = PetscSqrtReal(PetscSqr(PetscAbsScalar(hh[it])) + PetscSqr(PetscAbsScalar(hh[it+1])));
    374:     if (delta == 0.0) {
    375:       ksp->reason = KSP_DIVERGED_NULL;
    376:       return(0);
    377:     }

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

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

    393:     *res = 0.0;
    394:   }
    395:   return(0);
    396: }

    398: /*
    399:    KSPBuildSolution_PGMRES

    401:      Input Parameter:
    402: .     ksp - the Krylov space object
    403: .     ptr-

    405:    Output Parameter:
    406: .     result - the solution

    408:    Note: this calls KSPPGMRESBuildSoln - the same function that KSPPGMRESCycle
    409:    calls directly.

    411: */
    414: PetscErrorCode KSPBuildSolution_PGMRES(KSP ksp,Vec ptr,Vec *result)
    415: {
    416:   KSP_PGMRES     *pgmres = (KSP_PGMRES*)ksp->data;

    420:   if (!ptr) {
    421:     if (!pgmres->sol_temp) {
    422:       VecDuplicate(ksp->vec_sol,&pgmres->sol_temp);
    423:       PetscLogObjectParent(ksp,pgmres->sol_temp);
    424:     }
    425:     ptr = pgmres->sol_temp;
    426:   }
    427:   if (!pgmres->nrs) {
    428:     /* allocate the work area */
    429:     PetscMalloc(pgmres->max_k*sizeof(PetscScalar),&pgmres->nrs);
    430:     PetscLogObjectMemory(ksp,pgmres->max_k*sizeof(PetscScalar));
    431:   }

    433:   KSPPGMRESBuildSoln(pgmres->nrs,ksp->vec_sol,ptr,ksp,pgmres->it);
    434:   if (result) *result = ptr;
    435:   return(0);
    436: }

    440: PetscErrorCode KSPSetFromOptions_PGMRES(KSP ksp)
    441: {

    445:   KSPSetFromOptions_GMRES(ksp);
    446:   PetscOptionsHead("KSP pipelined GMRES Options");
    447:   PetscOptionsTail();
    448:   return(0);
    449: }

    453: PetscErrorCode KSPReset_PGMRES(KSP ksp)
    454: {

    458:   KSPReset_GMRES(ksp);
    459:   return(0);
    460: }

    462: /*MC
    463:      KSPPGMRES - Implements the Pipelined Generalized Minimal Residual method.

    465:    Options Database Keys:
    466: +   -ksp_gmres_restart <restart> - the number of Krylov directions to orthogonalize against
    467: .   -ksp_gmres_haptol <tol> - sets the tolerance for "happy ending" (exact convergence)
    468: .   -ksp_gmres_preallocate - preallocate all the Krylov search directions initially (otherwise groups of
    469:                              vectors are allocated as needed)
    470: .   -ksp_gmres_classicalgramschmidt - use classical (unmodified) Gram-Schmidt to orthogonalize against the Krylov space (fast) (the default)
    471: .   -ksp_gmres_modifiedgramschmidt - use modified Gram-Schmidt in the orthogonalization (more stable, but slower)
    472: .   -ksp_gmres_cgs_refinement_type <never,ifneeded,always> - determine if iterative refinement is used to increase the
    473:                                    stability of the classical Gram-Schmidt  orthogonalization.
    474: -   -ksp_gmres_krylov_monitor - plot the Krylov space generated

    476:    Level: beginner

    478:    Notes:
    479:    MPI configuration may be necessary for reductions to make asynchronous progress, which is important for performance of pipelined methods.
    480:    See the FAQ on the PETSc website for details.

    482:    Reference:
    483:    Ghysels, Ashby, Meerbergen, Vanroose, Hiding global communication latencies in the GMRES algorithm on massively parallel machines, 2012.

    485:    Developer Notes: This object is subclassed off of KSPGMRES

    487: .seealso:  KSPCreate(), KSPSetType(), KSPType (for list of available types), KSP, KSPGMRES, KSPLGMRES, KSPPIPECG, KSPPIPECR,
    488:            KSPGMRESSetRestart(), KSPGMRESSetHapTol(), KSPGMRESSetPreAllocateVectors(), KSPGMRESSetOrthogonalization(), KSPGMRESGetOrthogonalization(),
    489:            KSPGMRESClassicalGramSchmidtOrthogonalization(), KSPGMRESModifiedGramSchmidtOrthogonalization(),
    490:            KSPGMRESCGSRefinementType, KSPGMRESSetCGSRefinementType(),  KSPGMRESGetCGSRefinementType(), KSPGMRESMonitorKrylov()
    491: M*/

    495: PETSC_EXTERN PetscErrorCode KSPCreate_PGMRES(KSP ksp)
    496: {
    497:   KSP_PGMRES     *pgmres;

    501:   PetscNewLog(ksp,KSP_PGMRES,&pgmres);

    503:   ksp->data                              = (void*)pgmres;
    504:   ksp->ops->buildsolution                = KSPBuildSolution_PGMRES;
    505:   ksp->ops->setup                        = KSPSetUp_PGMRES;
    506:   ksp->ops->solve                        = KSPSolve_PGMRES;
    507:   ksp->ops->reset                        = KSPReset_PGMRES;
    508:   ksp->ops->destroy                      = KSPDestroy_PGMRES;
    509:   ksp->ops->view                         = KSPView_GMRES;
    510:   ksp->ops->setfromoptions               = KSPSetFromOptions_PGMRES;
    511:   ksp->ops->computeextremesingularvalues = KSPComputeExtremeSingularValues_GMRES;
    512:   ksp->ops->computeeigenvalues           = KSPComputeEigenvalues_GMRES;

    514:   KSPSetSupportedNorm(ksp,KSP_NORM_PRECONDITIONED,PC_LEFT,2);
    515:   KSPSetSupportedNorm(ksp,KSP_NORM_UNPRECONDITIONED,PC_RIGHT,1);

    517:   PetscObjectComposeFunction((PetscObject)ksp,"KSPGMRESSetPreAllocateVectors_C",KSPGMRESSetPreAllocateVectors_GMRES);
    518:   PetscObjectComposeFunction((PetscObject)ksp,"KSPGMRESSetOrthogonalization_C",KSPGMRESSetOrthogonalization_GMRES);
    519:   PetscObjectComposeFunction((PetscObject)ksp,"KSPGMRESGetOrthogonalization_C",KSPGMRESGetOrthogonalization_GMRES);
    520:   PetscObjectComposeFunction((PetscObject)ksp,"KSPGMRESSetRestart_C",KSPGMRESSetRestart_GMRES);
    521:   PetscObjectComposeFunction((PetscObject)ksp,"KSPGMRESGetRestart_C",KSPGMRESGetRestart_GMRES);
    522:   PetscObjectComposeFunction((PetscObject)ksp,"KSPGMRESSetCGSRefinementType_C",KSPGMRESSetCGSRefinementType_GMRES);
    523:   PetscObjectComposeFunction((PetscObject)ksp,"KSPGMRESGetCGSRefinementType_C",KSPGMRESGetCGSRefinementType_GMRES);

    525:   pgmres->nextra_vecs    = 1;
    526:   pgmres->haptol         = 1.0e-30;
    527:   pgmres->q_preallocate  = 0;
    528:   pgmres->delta_allocate = PGMRES_DELTA_DIRECTIONS;
    529:   pgmres->orthog         = KSPGMRESClassicalGramSchmidtOrthogonalization;
    530:   pgmres->nrs            = 0;
    531:   pgmres->sol_temp       = 0;
    532:   pgmres->max_k          = PGMRES_DEFAULT_MAXK;
    533:   pgmres->Rsvd           = 0;
    534:   pgmres->orthogwork     = 0;
    535:   pgmres->cgstype        = KSP_GMRES_CGS_REFINE_NEVER;
    536:   return(0);
    537: }