Actual source code: fcg.c

petsc-3.10.5 2019-03-28
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  1: /*
  2:     This file implements the FCG (Flexible Conjugate Gradient) method

  4: */

  6:  #include <../src/ksp/ksp/impls/fcg/fcgimpl.h>
  7: extern PetscErrorCode KSPComputeExtremeSingularValues_CG(KSP,PetscReal*,PetscReal*);
  8: extern PetscErrorCode KSPComputeEigenvalues_CG(KSP,PetscInt,PetscReal*,PetscReal*,PetscInt*);

 10: #define KSPFCG_DEFAULT_MMAX 30          /* maximum number of search directions to keep */
 11: #define KSPFCG_DEFAULT_NPREALLOC 10     /* number of search directions to preallocate */
 12: #define KSPFCG_DEFAULT_VECB 5           /* number of search directions to allocate each time new direction vectors are needed */
 13: #define KSPFCG_DEFAULT_TRUNCSTRAT KSP_FCD_TRUNC_TYPE_NOTAY

 15: static PetscErrorCode KSPAllocateVectors_FCG(KSP ksp, PetscInt nvecsneeded, PetscInt chunksize)
 16: {
 17:   PetscErrorCode  ierr;
 18:   PetscInt        i;
 19:   KSP_FCG         *fcg = (KSP_FCG*)ksp->data;
 20:   PetscInt        nnewvecs, nvecsprev;

 23:   /* Allocate enough new vectors to add chunksize new vectors, reach nvecsneedtotal, or to reach mmax+1, whichever is smallest */
 24:   if (fcg->nvecs < PetscMin(fcg->mmax+1,nvecsneeded)){
 25:     nvecsprev = fcg->nvecs;
 26:     nnewvecs = PetscMin(PetscMax(nvecsneeded-fcg->nvecs,chunksize),fcg->mmax+1-fcg->nvecs);
 27:     KSPCreateVecs(ksp,nnewvecs,&fcg->pCvecs[fcg->nchunks],0,NULL);
 28:     PetscLogObjectParents((PetscObject)ksp,nnewvecs,fcg->pCvecs[fcg->nchunks]);
 29:     KSPCreateVecs(ksp,nnewvecs,&fcg->pPvecs[fcg->nchunks],0,NULL);
 30:     PetscLogObjectParents((PetscObject)ksp,nnewvecs,fcg->pPvecs[fcg->nchunks]);
 31:     fcg->nvecs += nnewvecs;
 32:     for (i=0;i<nnewvecs;++i){
 33:       fcg->Cvecs[nvecsprev + i] = fcg->pCvecs[fcg->nchunks][i];
 34:       fcg->Pvecs[nvecsprev + i] = fcg->pPvecs[fcg->nchunks][i];
 35:     }
 36:     fcg->chunksizes[fcg->nchunks] = nnewvecs;
 37:     ++fcg->nchunks;
 38:   }
 39:   return(0);
 40: }

 42: static PetscErrorCode    KSPSetUp_FCG(KSP ksp)
 43: {
 45:   KSP_FCG        *fcg = (KSP_FCG*)ksp->data;
 46:   PetscInt       maxit = ksp->max_it;
 47:   const PetscInt nworkstd = 2;


 51:   /* Allocate "standard" work vectors (not including the basis and transformed basis vectors) */
 52:   KSPSetWorkVecs(ksp,nworkstd);

 54:   /* Allocated space for pointers to additional work vectors
 55:    note that mmax is the number of previous directions, so we add 1 for the current direction,
 56:    and an extra 1 for the prealloc (which might be empty) */
 57:   PetscMalloc5(fcg->mmax+1,&fcg->Pvecs,fcg->mmax+1,&fcg->Cvecs,fcg->mmax+1,&fcg->pPvecs,fcg->mmax+1,&fcg->pCvecs,fcg->mmax+2,&fcg->chunksizes);
 58:   PetscLogObjectMemory((PetscObject)ksp,2*(fcg->mmax+1)*sizeof(Vec*) + 2*(fcg->mmax + 1)*sizeof(Vec**) + (fcg->mmax + 2)*sizeof(PetscInt));

 60:   /* If the requested number of preallocated vectors is greater than mmax reduce nprealloc */
 61:   if(fcg->nprealloc > fcg->mmax+1){
 62:     PetscInfo2(NULL,"Requested nprealloc=%d is greater than m_max+1=%d. Resetting nprealloc = m_max+1.\n",fcg->nprealloc, fcg->mmax+1);
 63:   }

 65:   /* Preallocate additional work vectors */
 66:   KSPAllocateVectors_FCG(ksp,fcg->nprealloc,fcg->nprealloc);
 67:   /*
 68:   If user requested computations of eigenvalues then allocate work
 69:   work space needed
 70:   */
 71:   if (ksp->calc_sings) {
 72:     /* get space to store tridiagonal matrix for Lanczos */
 73:     PetscMalloc4(maxit,&fcg->e,maxit,&fcg->d,maxit,&fcg->ee,maxit,&fcg->dd);
 74:     PetscLogObjectMemory((PetscObject)ksp,2*(maxit+1)*(sizeof(PetscScalar)+sizeof(PetscReal)));

 76:     ksp->ops->computeextremesingularvalues = KSPComputeExtremeSingularValues_CG;
 77:     ksp->ops->computeeigenvalues           = KSPComputeEigenvalues_CG;
 78:   }
 79:   return(0);
 80: }

 82: static PetscErrorCode KSPSolve_FCG(KSP ksp)
 83: {
 85:   PetscInt       i,k,idx,mi;
 86:   KSP_FCG        *fcg = (KSP_FCG*)ksp->data;
 87:   PetscScalar    alpha=0.0,beta = 0.0,dpi,s;
 88:   PetscReal      dp=0.0;
 89:   Vec            B,R,Z,X,Pcurr,Ccurr;
 90:   Mat            Amat,Pmat;
 91:   PetscInt       eigs = ksp->calc_sings; /* Variables for eigen estimation - START*/
 92:   PetscInt       stored_max_it = ksp->max_it;
 93:   PetscScalar    alphaold = 0,betaold = 1.0,*e = 0,*d = 0;/* Variables for eigen estimation  - FINISH */


 97: #define VecXDot(x,y,a) (((fcg->type) == (KSP_CG_HERMITIAN)) ? VecDot(x,y,a) : VecTDot(x,y,a))
 98: #define VecXMDot(a,b,c,d) (((fcg->type) == (KSP_CG_HERMITIAN)) ? VecMDot(a,b,c,d) : VecMTDot(a,b,c,d))

100:   X             = ksp->vec_sol;
101:   B             = ksp->vec_rhs;
102:   R             = ksp->work[0];
103:   Z             = ksp->work[1];

105:   PCGetOperators(ksp->pc,&Amat,&Pmat);
106:   if (eigs) {e = fcg->e; d = fcg->d; e[0] = 0.0; }
107:   /* Compute initial residual needed for convergence check*/
108:   ksp->its = 0;
109:   if (!ksp->guess_zero) {
110:     KSP_MatMult(ksp,Amat,X,R);
111:     VecAYPX(R,-1.0,B);                    /*   r <- b - Ax     */
112:   } else {
113:     VecCopy(B,R);                         /*   r <- b (x is 0) */
114:   }
115:   switch (ksp->normtype) {
116:     case KSP_NORM_PRECONDITIONED:
117:       KSP_PCApply(ksp,R,Z);               /*   z <- Br         */
118:       VecNorm(Z,NORM_2,&dp);              /*   dp <- dqrt(z'*z) = sqrt(e'*A'*B'*B*A*e)     */
119:       break;
120:     case KSP_NORM_UNPRECONDITIONED:
121:       VecNorm(R,NORM_2,&dp);              /*   dp <- sqrt(r'*r) = sqrt(e'*A'*A*e)     */
122:       break;
123:     case KSP_NORM_NATURAL:
124:       KSP_PCApply(ksp,R,Z);               /*   z <- Br         */
125:       VecXDot(R,Z,&s);
126:       dp = PetscSqrtReal(PetscAbsScalar(s));                   /*   dp <- sqrt(r'*z) = sqrt(e'*A'*B*A*e)  */
127:       break;
128:     case KSP_NORM_NONE:
129:       dp = 0.0;
130:       break;
131:     default: SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_SUP,"%s",KSPNormTypes[ksp->normtype]);
132:   }

134:   /* Initial Convergence Check */
135:   KSPLogResidualHistory(ksp,dp);
136:   KSPMonitor(ksp,0,dp);
137:   ksp->rnorm = dp;
138:   if (ksp->normtype == KSP_NORM_NONE) {
139:     KSPConvergedSkip(ksp,0,dp,&ksp->reason,ksp->cnvP);
140:   } else {
141:     (*ksp->converged)(ksp,0,dp,&ksp->reason,ksp->cnvP);
142:   }
143:   if (ksp->reason) return(0);

145:   /* Apply PC if not already done for convergence check */
146:   if(ksp->normtype == KSP_NORM_UNPRECONDITIONED || ksp->normtype == KSP_NORM_NONE){
147:     KSP_PCApply(ksp,R,Z);               /*   z <- Br         */
148:   }

150:   i = 0;
151:   do {
152:     ksp->its = i+1;

154:     /*  If needbe, allocate a new chunk of vectors in P and C */
155:     KSPAllocateVectors_FCG(ksp,i+1,fcg->vecb);

157:     /* Note that we wrap around and start clobbering old vectors */
158:     idx = i % (fcg->mmax+1);
159:     Pcurr = fcg->Pvecs[idx];
160:     Ccurr = fcg->Cvecs[idx];

162:     /* number of old directions to orthogonalize against */
163:     switch(fcg->truncstrat){
164:       case KSP_FCD_TRUNC_TYPE_STANDARD:
165:         mi = fcg->mmax;
166:         break;
167:       case KSP_FCD_TRUNC_TYPE_NOTAY:
168:         mi = ((i-1) % fcg->mmax)+1;
169:         break;
170:       default:
171:         SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Unrecognized Truncation Strategy");
172:     }

174:     /* Compute a new column of P (Currently does not support modified G-S or iterative refinement)*/
175:     VecCopy(Z,Pcurr);

177:     {
178:       PetscInt l,ndots;

180:       l = PetscMax(0,i-mi);
181:       ndots = i-l;
182:       if (ndots){
183:         PetscInt    j;
184:         Vec         *Pold,  *Cold;
185:         PetscScalar *dots;

187:         PetscMalloc3(ndots,&dots,ndots,&Cold,ndots,&Pold);
188:         for(k=l,j=0;j<ndots;++k,++j){
189:           idx = k % (fcg->mmax+1);
190:           Cold[j] = fcg->Cvecs[idx];
191:           Pold[j] = fcg->Pvecs[idx];
192:         }
193:         VecXMDot(Z,ndots,Cold,dots);
194:         for(k=0;k<ndots;++k){
195:           dots[k] = -dots[k];
196:         }
197:         VecMAXPY(Pcurr,ndots,dots,Pold);
198:         PetscFree3(dots,Cold,Pold);
199:       }
200:     }

202:     /* Update X and R */
203:     betaold = beta;
204:     VecXDot(Pcurr,R,&beta);                 /*  beta <- pi'*r       */
205:     KSP_MatMult(ksp,Amat,Pcurr,Ccurr);      /*  w <- A*pi (stored in ci)   */
206:     VecXDot(Pcurr,Ccurr,&dpi);              /*  dpi <- pi'*w        */
207:     alphaold = alpha;
208:     alpha = beta / dpi;                                          /*  alpha <- beta/dpi    */
209:     VecAXPY(X,alpha,Pcurr);                 /*  x <- x + alpha * pi  */
210:     VecAXPY(R,-alpha,Ccurr);                /*  r <- r - alpha * wi  */

212:     /* Compute norm for convergence check */
213:     switch (ksp->normtype) {
214:       case KSP_NORM_PRECONDITIONED:
215:         KSP_PCApply(ksp,R,Z);               /*   z <- Br             */
216:         VecNorm(Z,NORM_2,&dp);              /*   dp <- sqrt(z'*z) = sqrt(e'*A'*B'*B*A*e)  */
217:         break;
218:       case KSP_NORM_UNPRECONDITIONED:
219:         VecNorm(R,NORM_2,&dp);              /*   dp <- sqrt(r'*r) = sqrt(e'*A'*A*e)   */
220:         break;
221:       case KSP_NORM_NATURAL:
222:         KSP_PCApply(ksp,R,Z);               /*   z <- Br             */
223:         VecXDot(R,Z,&s);
224:         dp = PetscSqrtReal(PetscAbsScalar(s));                   /*   dp <- sqrt(r'*z) = sqrt(e'*A'*B*A*e)  */
225:         break;
226:       case KSP_NORM_NONE:
227:         dp = 0.0;
228:         break;
229:       default: SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_SUP,"%s",KSPNormTypes[ksp->normtype]);
230:     }

232:     /* Check for convergence */
233:     ksp->rnorm = dp;
234:     KSPLogResidualHistory(ksp,dp);
235:     KSPMonitor(ksp,i+1,dp);
236:     (*ksp->converged)(ksp,i+1,dp,&ksp->reason,ksp->cnvP);
237:     if (ksp->reason) break;

239:     /* Apply PC if not already done for convergence check */
240:     if(ksp->normtype == KSP_NORM_UNPRECONDITIONED || ksp->normtype == KSP_NORM_NONE){
241:       KSP_PCApply(ksp,R,Z);               /*   z <- Br         */
242:     }

244:     /* Compute current C (which is W/dpi) */
245:     VecScale(Ccurr,1.0/dpi);              /*   w <- ci/dpi   */

247:     if (eigs) {
248:       if (i > 0) {
249:         if (ksp->max_it != stored_max_it) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_SUP,"Can not change maxit AND calculate eigenvalues");
250:         e[i] = PetscSqrtReal(PetscAbsScalar(beta/betaold))/alphaold;
251:         d[i] = PetscSqrtReal(PetscAbsScalar(beta/betaold))*e[i] + 1.0/alpha;
252:       } else {
253:         d[i] = PetscSqrtReal(PetscAbsScalar(beta))*e[i] + 1.0/alpha;
254:       }
255:       fcg->ned = ksp->its-1;
256:     }
257:     ++i;
258:   } while (i<ksp->max_it);
259:   if (i >= ksp->max_it) ksp->reason = KSP_DIVERGED_ITS;
260:   return(0);
261: }

263: static PetscErrorCode KSPDestroy_FCG(KSP ksp)
264: {
266:   PetscInt       i;
267:   KSP_FCG        *fcg = (KSP_FCG*)ksp->data;


271:   /* Destroy "standard" work vecs */
272:   VecDestroyVecs(ksp->nwork,&ksp->work);

274:   /* Destroy P and C vectors and the arrays that manage pointers to them */
275:   if (fcg->nvecs){
276:     for (i=0;i<fcg->nchunks;++i){
277:       VecDestroyVecs(fcg->chunksizes[i],&fcg->pPvecs[i]);
278:       VecDestroyVecs(fcg->chunksizes[i],&fcg->pCvecs[i]);
279:     }
280:   }
281:   PetscFree5(fcg->Pvecs,fcg->Cvecs,fcg->pPvecs,fcg->pCvecs,fcg->chunksizes);
282:   /* free space used for singular value calculations */
283:   if (ksp->calc_sings) {
284:     PetscFree4(fcg->e,fcg->d,fcg->ee,fcg->dd);
285:   }
286:   KSPDestroyDefault(ksp);
287:   return(0);
288: }

290: static PetscErrorCode KSPView_FCG(KSP ksp,PetscViewer viewer)
291: {
292:   KSP_FCG        *fcg = (KSP_FCG*)ksp->data;
294:   PetscBool      iascii,isstring;
295:   const char     *truncstr;

298:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
299:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSTRING,&isstring);

301:   if (fcg->truncstrat == KSP_FCD_TRUNC_TYPE_STANDARD) truncstr = "Using standard truncation strategy";
302:   else if (fcg->truncstrat == KSP_FCD_TRUNC_TYPE_NOTAY) truncstr = "Using Notay's truncation strategy";
303:   else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Undefined FCG truncation strategy");

305:   if (iascii) {
306:     PetscViewerASCIIPrintf(viewer,"  m_max=%D\n",fcg->mmax);
307:     PetscViewerASCIIPrintf(viewer,"  preallocated %D directions\n",PetscMin(fcg->nprealloc,fcg->mmax+1));
308:     PetscViewerASCIIPrintf(viewer,"  %s\n",truncstr);
309:   } else if (isstring) {
310:     PetscViewerStringSPrintf(viewer,"m_max %D nprealloc %D %s",fcg->mmax,fcg->nprealloc,truncstr);
311:   }
312:   return(0);
313: }

315: /*@
316:   KSPFCGSetMmax - set the maximum number of previous directions FCG will store for orthogonalization

318:   Note: mmax + 1 directions are stored (mmax previous ones along with a current one)
319:   and whether all are used in each iteration also depends on the truncation strategy
320:   (see KSPFCGSetTruncationType())

322:   Logically Collective on KSP

324:   Input Parameters:
325: +  ksp - the Krylov space context
326: -  mmax - the maximum number of previous directions to orthogonalize againt

328:   Level: intermediate

330:   Options Database:
331: . -ksp_fcg_mmax <N>

333: .seealso: KSPFCG, KSPFCGGetTruncationType(), KSPFCGGetNprealloc()
334: @*/
335: PetscErrorCode KSPFCGSetMmax(KSP ksp,PetscInt mmax)
336: {
337:   KSP_FCG *fcg = (KSP_FCG*)ksp->data;

342:   fcg->mmax = mmax;
343:   return(0);
344: }

346: /*@
347:   KSPFCGGetMmax - get the maximum number of previous directions FCG will store

349:   Note: FCG stores mmax+1 directions at most (mmax previous ones, and one current one)

351:    Not Collective

353:    Input Parameter:
354: .  ksp - the Krylov space context

356:    Output Parameter:
357: .  mmax - the maximum number of previous directons allowed for orthogonalization

359:   Options Database:
360: . -ksp_fcg_mmax <N>

362:    Level: intermediate

364: .keywords: KSP, FCG, truncation

366: .seealso: KSPFCG, KSPFCGGetTruncationType(), KSPFCGGetNprealloc(), KSPFCGSetMmax()
367: @*/

369: PetscErrorCode KSPFCGGetMmax(KSP ksp,PetscInt *mmax)
370: {
371:   KSP_FCG *fcg=(KSP_FCG*)ksp->data;

375:   *mmax = fcg->mmax;
376:   return(0);
377: }

379: /*@
380:   KSPFCGSetNprealloc - set the number of directions to preallocate with FCG

382:   Logically Collective on KSP

384:   Input Parameters:
385: +  ksp - the Krylov space context
386: -  nprealloc - the number of vectors to preallocate

388:   Level: advanced

390:   Options Database:
391: . -ksp_fcg_nprealloc <N> - number of directions to preallocate

393: .seealso: KSPFCG, KSPFCGGetTruncationType(), KSPFCGGetNprealloc()
394: @*/
395: PetscErrorCode KSPFCGSetNprealloc(KSP ksp,PetscInt nprealloc)
396: {
397:   KSP_FCG *fcg=(KSP_FCG*)ksp->data;

402:   if(nprealloc > fcg->mmax+1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Cannot preallocate more than m_max+1 vectors");
403:   fcg->nprealloc = nprealloc;
404:   return(0);
405: }

407: /*@
408:   KSPFCGGetNprealloc - get the number of directions preallocate by FCG

410:    Not Collective

412:    Input Parameter:
413: .  ksp - the Krylov space context

415:    Output Parameter:
416: .  nprealloc - the number of directions preallocated

418:    Level: advanced

420: .keywords: KSP, FCG, truncation

422: .seealso: KSPFCG, KSPFCGGetTruncationType(), KSPFCGSetNprealloc()
423: @*/
424: PetscErrorCode KSPFCGGetNprealloc(KSP ksp,PetscInt *nprealloc)
425: {
426:   KSP_FCG *fcg=(KSP_FCG*)ksp->data;

430:   *nprealloc = fcg->nprealloc;
431:   return(0);
432: }

434: /*@
435:   KSPFCGSetTruncationType - specify how many of its stored previous directions FCG uses during orthoganalization

437:   Logically Collective on KSP

439:   KSP_FCD_TRUNC_TYPE_STANDARD uses all (up to mmax) stored directions
440:   KSP_FCD_TRUNC_TYPE_NOTAY uses the last max(1,mod(i,mmax)) stored directions at iteration i=0,1,..

442:   Input Parameters:
443: +  ksp - the Krylov space context
444: -  truncstrat - the choice of strategy

446:   Level: intermediate

448:   Options Database:
449: . -ksp_fcg_truncation_type <standard, notay> - specify how many of its stored previous directions FCG uses during orthoganalization

451:   .seealso: KSPFCDTruncationType, KSPFCGGetTruncationType
452: @*/
453: PetscErrorCode KSPFCGSetTruncationType(KSP ksp,KSPFCDTruncationType truncstrat)
454: {
455:   KSP_FCG *fcg=(KSP_FCG*)ksp->data;

460:   fcg->truncstrat=truncstrat;
461:   return(0);
462: }

464: /*@
465:   KSPFCGGetTruncationType - get the truncation strategy employed by FCG

467:    Not Collective

469:    Input Parameter:
470: .  ksp - the Krylov space context

472:    Output Parameter:
473: .  truncstrat - the strategy type

475:    Level: intermediate

477: .keywords: KSP, FCG, truncation

479: .seealso: KSPFCG, KSPFCGSetTruncationType, KSPFCDTruncationType
480: @*/
481: PetscErrorCode KSPFCGGetTruncationType(KSP ksp,KSPFCDTruncationType *truncstrat)
482: {
483:   KSP_FCG *fcg=(KSP_FCG*)ksp->data;

487:   *truncstrat=fcg->truncstrat;
488:   return(0);
489: }

491: static PetscErrorCode KSPSetFromOptions_FCG(PetscOptionItems *PetscOptionsObject,KSP ksp)
492: {
494:   KSP_FCG        *fcg=(KSP_FCG*)ksp->data;
495:   PetscInt       mmax,nprealloc;
496:   PetscBool      flg;

499:   PetscOptionsHead(PetscOptionsObject,"KSP FCG Options");
500:   PetscOptionsInt("-ksp_fcg_mmax","Maximum number of search directions to store","KSPFCGSetMmax",fcg->mmax,&mmax,&flg);
501:   if (flg) {
502:     KSPFCGSetMmax(ksp,mmax);
503:   }
504:   PetscOptionsInt("-ksp_fcg_nprealloc","Number of directions to preallocate","KSPFCGSetNprealloc",fcg->nprealloc,&nprealloc,&flg);
505:   if (flg) {
506:     KSPFCGSetNprealloc(ksp,nprealloc);
507:   }
508:   PetscOptionsEnum("-ksp_fcg_truncation_type","Truncation approach for directions","KSPFCGSetTruncationType",KSPFCDTruncationTypes,(PetscEnum)fcg->truncstrat,(PetscEnum*)&fcg->truncstrat,NULL);
509:   PetscOptionsTail();
510:   return(0);
511: }

513: /*MC
514:       KSPFCG - Implements the Flexible Conjugate Gradient method (FCG)

516:   Options Database Keys:
517: +   -ksp_fcg_mmax <N>  - maximum number of search directions
518: .   -ksp_fcg_nprealloc <N> - number of directions to preallocate
519: -   -ksp_fcg_truncation_type <standard,notay> - truncation approach for directions

521:     Contributed by Patrick Sanan

523:    Notes:
524:    Supports left preconditioning only.

526:    Level: beginner

528:   References:
529: +    1. - Notay, Y."Flexible Conjugate Gradients", SIAM J. Sci. Comput. 22:4, 2000
530: -    2. - Axelsson, O. and Vassilevski, P. S. "A Black Box Generalized Conjugate Gradient Solver with Inner Iterations and Variable step Preconditioning",
531:     SIAM J. Matrix Anal. Appl. 12:4, 1991

533:  .seealso : KSPGCR, KSPFGMRES, KSPCG, KSPFCGSetMmax(), KSPFCGGetMmax(), KSPFCGSetNprealloc(), KSPFCGGetNprealloc(), KSPFCGSetTruncationType(), KSPFCGGetTruncationType()

535: M*/
536: PETSC_EXTERN PetscErrorCode KSPCreate_FCG(KSP ksp)
537: {
539:   KSP_FCG        *fcg;

542:   PetscNewLog(ksp,&fcg);
543: #if !defined(PETSC_USE_COMPLEX)
544:   fcg->type       = KSP_CG_SYMMETRIC;
545: #else
546:   fcg->type       = KSP_CG_HERMITIAN;
547: #endif
548:   fcg->mmax       = KSPFCG_DEFAULT_MMAX;
549:   fcg->nprealloc  = KSPFCG_DEFAULT_NPREALLOC;
550:   fcg->nvecs      = 0;
551:   fcg->vecb       = KSPFCG_DEFAULT_VECB;
552:   fcg->nchunks    = 0;
553:   fcg->truncstrat = KSPFCG_DEFAULT_TRUNCSTRAT;

555:   ksp->data = (void*)fcg;

557:   KSPSetSupportedNorm(ksp,KSP_NORM_PRECONDITIONED,PC_LEFT,2);
558:   KSPSetSupportedNorm(ksp,KSP_NORM_UNPRECONDITIONED,PC_LEFT,1);
559:   KSPSetSupportedNorm(ksp,KSP_NORM_NATURAL,PC_LEFT,1);
560:   KSPSetSupportedNorm(ksp,KSP_NORM_NONE,PC_LEFT,1);

562:   ksp->ops->setup          = KSPSetUp_FCG;
563:   ksp->ops->solve          = KSPSolve_FCG;
564:   ksp->ops->destroy        = KSPDestroy_FCG;
565:   ksp->ops->view           = KSPView_FCG;
566:   ksp->ops->setfromoptions = KSPSetFromOptions_FCG;
567:   ksp->ops->buildsolution  = KSPBuildSolutionDefault;
568:   ksp->ops->buildresidual  = KSPBuildResidualDefault;
569:   return(0);
570: }