Actual source code: cheby.c

petsc-master 2017-04-20
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  2:  #include <../src/ksp/ksp/impls/cheby/chebyshevimpl.h>

  4: static PetscErrorCode KSPReset_Chebyshev(KSP ksp)
  5: {
  6:   KSP_Chebyshev  *cheb = (KSP_Chebyshev*)ksp->data;

 10:   KSPReset(cheb->kspest);
 11:   return(0);
 12: }

 14: static PetscErrorCode KSPSetUp_Chebyshev(KSP ksp)
 15: {
 16:   KSP_Chebyshev  *cheb = (KSP_Chebyshev*)ksp->data;

 20:   KSPSetWorkVecs(ksp,3);
 21:   if ((cheb->emin == 0. || cheb->emax == 0.) && !cheb->kspest) { /* We need to estimate eigenvalues */
 22:     KSPChebyshevEstEigSet(ksp,PETSC_DECIDE,PETSC_DECIDE,PETSC_DECIDE,PETSC_DECIDE);
 23:   }
 24:   return(0);
 25: }

 27: static PetscErrorCode KSPChebyshevSetEigenvalues_Chebyshev(KSP ksp,PetscReal emax,PetscReal emin)
 28: {
 29:   KSP_Chebyshev  *chebyshevP = (KSP_Chebyshev*)ksp->data;

 33:   if (emax <= emin) SETERRQ2(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_INCOMP,"Maximum eigenvalue must be larger than minimum: max %g min %g",(double)emax,(double)emin);
 34:   if (emax*emin <= 0.0) SETERRQ2(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_INCOMP,"Both eigenvalues must be of the same sign: max %g min %g",(double)emax,(double)emin);
 35:   chebyshevP->emax = emax;
 36:   chebyshevP->emin = emin;

 38:   KSPChebyshevEstEigSet(ksp,0.,0.,0.,0.); /* Destroy any estimation setup */
 39:   return(0);
 40: }

 42: static PetscErrorCode KSPChebyshevEstEigSet_Chebyshev(KSP ksp,PetscReal a,PetscReal b,PetscReal c,PetscReal d)
 43: {
 44:   KSP_Chebyshev  *cheb = (KSP_Chebyshev*)ksp->data;

 48:   if (a != 0.0 || b != 0.0 || c != 0.0 || d != 0.0) {
 49:     if (!cheb->kspest) { /* should this block of code be moved to KSPSetUp_Chebyshev()? */
 50:       KSPCreate(PetscObjectComm((PetscObject)ksp),&cheb->kspest);
 51:       PetscObjectIncrementTabLevel((PetscObject)cheb->kspest,(PetscObject)ksp,1);
 52:       KSPSetPC(cheb->kspest,ksp->pc);
 53:       /* use PetscObjectSet/AppendOptionsPrefix() instead of KSPSet/AppendOptionsPrefix() so that the PC prefix is not changed */
 54:       PetscObjectSetOptionsPrefix((PetscObject)cheb->kspest,((PetscObject)ksp)->prefix);
 55:       PetscObjectAppendOptionsPrefix((PetscObject)cheb->kspest,"esteig_");
 56:       KSPSetSkipPCSetFromOptions(cheb->kspest,PETSC_TRUE);

 58:       KSPSetComputeEigenvalues(cheb->kspest,PETSC_TRUE);

 60:       /* We cannot turn off convergence testing because GMRES will break down if you attempt to keep iterating after a zero norm is obtained */
 61:       KSPSetTolerances(cheb->kspest,1.e-12,PETSC_DEFAULT,PETSC_DEFAULT,cheb->eststeps);
 62:     }
 63:     if (a >= 0) cheb->tform[0] = a;
 64:     if (b >= 0) cheb->tform[1] = b;
 65:     if (c >= 0) cheb->tform[2] = c;
 66:     if (d >= 0) cheb->tform[3] = d;
 67:     cheb->amatid    = 0;
 68:     cheb->pmatid    = 0;
 69:     cheb->amatstate = -1;
 70:     cheb->pmatstate = -1;
 71:   } else {
 72:     KSPDestroy(&cheb->kspest);
 73:   }
 74:   return(0);
 75: }

 77: static PetscErrorCode KSPChebyshevEstEigSetUseNoisy_Chebyshev(KSP ksp,PetscBool use)
 78: {
 79:   KSP_Chebyshev  *cheb = (KSP_Chebyshev*)ksp->data;

 82:   cheb->usenoisy = use;
 83:   return(0);
 84: }

 86: /*@
 87:    KSPChebyshevSetEigenvalues - Sets estimates for the extreme eigenvalues
 88:    of the preconditioned problem.

 90:    Logically Collective on KSP

 92:    Input Parameters:
 93: +  ksp - the Krylov space context
 94: -  emax, emin - the eigenvalue estimates

 96:   Options Database:
 97: .  -ksp_chebyshev_eigenvalues emin,emax

 99:    Note: Call KSPChebyshevEstEigSet() or use the option -ksp_chebyshev_esteig a,b,c,d to have the KSP
100:          estimate the eigenvalues and use these estimated values automatically

102:    Level: intermediate

104: .keywords: KSP, Chebyshev, set, eigenvalues
105: @*/
106: PetscErrorCode  KSPChebyshevSetEigenvalues(KSP ksp,PetscReal emax,PetscReal emin)
107: {

114:   PetscTryMethod(ksp,"KSPChebyshevSetEigenvalues_C",(KSP,PetscReal,PetscReal),(ksp,emax,emin));
115:   return(0);
116: }

118: /*@
119:    KSPChebyshevEstEigSet - Automatically estimate the eigenvalues to use for Chebyshev

121:    Logically Collective on KSP

123:    Input Parameters:
124: +  ksp - the Krylov space context
125: .  a - multiple of min eigenvalue estimate to use for min Chebyshev bound (or PETSC_DECIDE)
126: .  b - multiple of max eigenvalue estimate to use for min Chebyshev bound (or PETSC_DECIDE)
127: .  c - multiple of min eigenvalue estimate to use for max Chebyshev bound (or PETSC_DECIDE)
128: -  d - multiple of max eigenvalue estimate to use for max Chebyshev bound (or PETSC_DECIDE)

130:   Options Database:
131: .  -ksp_chebyshev_esteig a,b,c,d

133:    Notes:
134:    The Chebyshev bounds are set using
135: .vb
136:    minbound = a*minest + b*maxest
137:    maxbound = c*minest + d*maxest
138: .ve
139:    The default configuration targets the upper part of the spectrum for use as a multigrid smoother, so only the maximum eigenvalue estimate is used.
140:    The minimum eigenvalue estimate obtained by Krylov iteration is typically not accurate until the method has converged.

142:    If 0.0 is passed for all transform arguments (a,b,c,d), eigenvalue estimation is disabled.

144:    The default transform is (0,0.1; 0,1.1) which targets the "upper" part of the spectrum, as desirable for use with multigrid.

146:    The eigenvalues are estimated using the Lanczo (KSPCG) or Arnoldi (KSPGMRES) process using a noisy right hand side vector.

148:    Level: intermediate

150: .keywords: KSP, Chebyshev, set, eigenvalues, PCMG
151: @*/
152: PetscErrorCode KSPChebyshevEstEigSet(KSP ksp,PetscReal a,PetscReal b,PetscReal c,PetscReal d)
153: {

162:   PetscTryMethod(ksp,"KSPChebyshevEstEigSet_C",(KSP,PetscReal,PetscReal,PetscReal,PetscReal),(ksp,a,b,c,d));
163:   return(0);
164: }

166: /*@
167:    KSPChebyshevEstEigSetUseNoisy - use a noisy right hand side in order to do the estimate instead of the given right hand side

169:    Logically Collective

171:    Input Arguments:
172: +  ksp - linear solver context
173: -  use - PETSC_TRUE to use noisy

175:    Options Database:
176: +  -ksp_chebyshev_esteig_noisy <true,false>

178:   Notes: This alledgely works better for multigrid smoothers

180:   Level: intermediate

182: .seealso: KSPChebyshevEstEigSet()
183: @*/
184: PetscErrorCode KSPChebyshevEstEigSetUseNoisy(KSP ksp,PetscBool use)
185: {

190:   PetscTryMethod(ksp,"KSPChebyshevEstEigSetUseNoisy_C",(KSP,PetscBool),(ksp,use));
191:   return(0);
192: }

194: /*@
195:   KSPChebyshevEstEigGetKSP - Get the Krylov method context used to estimate eigenvalues for the Chebyshev method.  If
196:   a Krylov method is not being used for this purpose, NULL is returned.  The reference count of the returned KSP is
197:   not incremented: it should not be destroyed by the user.

199:   Input Parameters:
200: . ksp - the Krylov space context

202:   Output Parameters:
203: . kspest the eigenvalue estimation Krylov space context

205:   Level: intermediate

207: .seealso: KSPChebyshevEstEigSet()
208: @*/
209: PetscErrorCode KSPChebyshevEstEigGetKSP(KSP ksp, KSP *kspest)
210: {

215:   *kspest = NULL;
216:   PetscTryMethod(ksp,"KSPChebyshevEstEigGetKSP_C",(KSP,KSP*),(ksp,kspest));
217:   return(0);
218: }

220: static PetscErrorCode KSPChebyshevEstEigGetKSP_Chebyshev(KSP ksp, KSP *kspest)
221: {
222:   KSP_Chebyshev *cheb = (KSP_Chebyshev*)ksp->data;

225:   *kspest = cheb->kspest;
226:   return(0);
227: }

229: static PetscErrorCode KSPSetFromOptions_Chebyshev(PetscOptionItems *PetscOptionsObject,KSP ksp)
230: {
231:   KSP_Chebyshev  *cheb = (KSP_Chebyshev*)ksp->data;
233:   PetscInt       neigarg = 2, nestarg = 4;
234:   PetscReal      eminmax[2] = {0., 0.};
235:   PetscReal      tform[4] = {PETSC_DECIDE,PETSC_DECIDE,PETSC_DECIDE,PETSC_DECIDE};
236:   PetscBool      flgeig, flgest;

239:   PetscOptionsHead(PetscOptionsObject,"KSP Chebyshev Options");
240:   PetscOptionsInt("-ksp_chebyshev_esteig_steps","Number of est steps in Chebyshev","",cheb->eststeps,&cheb->eststeps,NULL);
241:   PetscOptionsRealArray("-ksp_chebyshev_eigenvalues","extreme eigenvalues","KSPChebyshevSetEigenvalues",eminmax,&neigarg,&flgeig);
242:   if (flgeig) {
243:     if (neigarg != 2) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_INCOMP,"-ksp_chebyshev_eigenvalues: must specify 2 parameters, min and max eigenvalues");
244:     KSPChebyshevSetEigenvalues(ksp, eminmax[1], eminmax[0]);
245:   }
246:   PetscOptionsRealArray("-ksp_chebyshev_esteig","estimate eigenvalues using a Krylov method, then use this transform for Chebyshev eigenvalue bounds","KSPChebyshevEstEigSet",tform,&nestarg,&flgest);
247:   if (flgest) {
248:     switch (nestarg) {
249:     case 0:
250:       KSPChebyshevEstEigSet(ksp,PETSC_DECIDE,PETSC_DECIDE,PETSC_DECIDE,PETSC_DECIDE);
251:       break;
252:     case 2:                     /* Base everything on the max eigenvalues */
253:       KSPChebyshevEstEigSet(ksp,PETSC_DECIDE,tform[0],PETSC_DECIDE,tform[1]);
254:       break;
255:     case 4:                     /* Use the full 2x2 linear transformation */
256:       KSPChebyshevEstEigSet(ksp,tform[0],tform[1],tform[2],tform[3]);
257:       break;
258:     default: SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_INCOMP,"Must specify either 0, 2, or 4 parameters for eigenvalue estimation");
259:     }
260:   }

262:   /* We need to estimate eigenvalues; need to set this here so that KSPSetFromOptions() is called on the estimator */
263:   if ((cheb->emin == 0. || cheb->emax == 0.) && !cheb->kspest) {
264:    KSPChebyshevEstEigSet(ksp,PETSC_DECIDE,PETSC_DECIDE,PETSC_DECIDE,PETSC_DECIDE);
265:   }

267:   if (cheb->kspest) {
268:     PetscOptionsBool("-ksp_chebyshev_esteig_noisy","Use noisy right hand side for estimate","KSPChebyshevEstEigSetUseNoisy",cheb->usenoisy,&cheb->usenoisy,NULL);
269:     KSPSetFromOptions(cheb->kspest);
270:   }
271:   PetscOptionsTail();
272:   return(0);
273: }

275: /*
276:  * Must be passed a KSP solver that has "converged", with KSPSetComputeEigenvalues() called before the solve
277:  */
278: static PetscErrorCode KSPChebyshevComputeExtremeEigenvalues_Private(KSP kspest,PetscReal *emin,PetscReal *emax)
279: {
281:   PetscInt       n,neig;
282:   PetscReal      *re,*im,min,max;

285:   KSPGetIterationNumber(kspest,&n);
286:   PetscMalloc2(n,&re,n,&im);
287:   KSPComputeEigenvalues(kspest,n,re,im,&neig);
288:   min  = PETSC_MAX_REAL;
289:   max  = PETSC_MIN_REAL;
290:   for (n=0; n<neig; n++) {
291:     min = PetscMin(min,re[n]);
292:     max = PetscMax(max,re[n]);
293:   }
294:   PetscFree2(re,im);
295:   *emax = max;
296:   *emin = min;
297:   return(0);
298: }

300: PETSC_STATIC_INLINE PetscScalar chebyhash(PetscInt xx)
301: {
302:   unsigned int x = xx;
303:   x = ((x >> 16) ^ x) * 0x45d9f3b;
304:   x = ((x >> 16) ^ x) * 0x45d9f3b;
305:   x = ((x >> 16) ^ x);
306:   return (PetscScalar)((PetscInt64)x-2147483648)*5.e-10; /* center around zero, scaled about -1. to 1.*/
307: }

309: static PetscErrorCode KSPSolve_Chebyshev(KSP ksp)
310: {
311:   KSP_Chebyshev  *cheb = (KSP_Chebyshev*)ksp->data;
313:   PetscInt       k,kp1,km1,maxit,ktmp,i;
314:   PetscScalar    alpha,omegaprod,mu,omega,Gamma,c[3],scale;
315:   PetscReal      rnorm = 0.0;
316:   Vec            sol_orig,b,p[3],r;
317:   Mat            Amat,Pmat;
318:   PetscBool      diagonalscale;

321:   PCGetDiagonalScale(ksp->pc,&diagonalscale);
322:   if (diagonalscale) SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_SUP,"Krylov method %s does not support diagonal scaling",((PetscObject)ksp)->type_name);

324:   PCGetOperators(ksp->pc,&Amat,&Pmat);
325:   if (cheb->kspest) {
326:     PetscObjectId    amatid,    pmatid;
327:     PetscObjectState amatstate, pmatstate;

329:     PetscObjectGetId((PetscObject)Amat,&amatid);
330:     PetscObjectGetId((PetscObject)Pmat,&pmatid);
331:     PetscObjectStateGet((PetscObject)Amat,&amatstate);
332:     PetscObjectStateGet((PetscObject)Pmat,&pmatstate);
333:     if (amatid != cheb->amatid || pmatid != cheb->pmatid || amatstate != cheb->amatstate || pmatstate != cheb->pmatstate) {
334:       PetscReal          max=0.0,min=0.0;
335:       Vec                B;
336:       KSPConvergedReason reason;

338:       if (cheb->usenoisy) {
339:         B  = ksp->work[1];
340:         {
342:           PetscInt       n,i,istart;
343:           PetscScalar    *xx;
344:           VecGetOwnershipRange(B,&istart,NULL);
345:           VecGetLocalSize(B,&n);
346:           VecGetArray(B,&xx);
347:           for (i=0; i<n; i++) {
348:             PetscScalar v = chebyhash(i+istart);
349:             xx[i] = v;
350:           }
351:           VecRestoreArray(B,&xx);
352:         }
353:       } else {
354:         PC        pc;
355:         PetscBool change;

357:         KSPGetPC(cheb->kspest,&pc);
358:         PCPreSolveChangeRHS(pc,&change);
359:         if (change) {
360:           B = ksp->work[1];
361:           VecCopy(ksp->vec_rhs,B);
362:         } else {
363:           B = ksp->vec_rhs;
364:         }
365:       }
366:       KSPSolve(cheb->kspest,B,ksp->work[0]);

368:       KSPGetConvergedReason(cheb->kspest,&reason);
369:       if (reason < 0) {
370:         if (reason == KSP_DIVERGED_ITS) {
371:           PetscInfo(ksp,"Eigen estimator ran for prescribed number of iterations\n");
372:         } else {
373:           PetscInt its;
374:           KSPGetIterationNumber(cheb->kspest,&its);
375:           if (reason == KSP_DIVERGED_PCSETUP_FAILED) {
376:             PetscInfo(ksp,"Eigen estimator KSP_DIVERGED_PCSETUP_FAILED\n");
377:             ksp->reason = KSP_DIVERGED_PCSETUP_FAILED;
378:             VecSetInf(ksp->vec_sol);
379:           } else {
380:             SETERRQ2(PetscObjectComm((PetscObject)ksp),PETSC_ERR_PLIB,"Eigen estimator failed: %s at iteration %D",KSPConvergedReasons[reason],its);
381:           }
382:         }
383:       } else if (reason==KSP_CONVERGED_RTOL ||reason==KSP_CONVERGED_ATOL) {
384:         PetscInfo(ksp,"Eigen estimator converged prematurely. Should not happen except for small or low rank problem\n");
385:       } else {
386:         PetscInfo1(ksp,"Eigen estimator did not converge by iteration: %s\n",KSPConvergedReasons[reason]);
387:       }

389:       KSPChebyshevComputeExtremeEigenvalues_Private(cheb->kspest,&min,&max);

391:       cheb->emin_computed = min;
392:       cheb->emax_computed = max;
393:       cheb->emin = cheb->tform[0]*min + cheb->tform[1]*max;
394:       cheb->emax = cheb->tform[2]*min + cheb->tform[3]*max;

396:       cheb->amatid    = amatid;
397:       cheb->pmatid    = pmatid;
398:       cheb->amatstate = amatstate;
399:       cheb->pmatstate = pmatstate;
400:     }
401:   }

403:   ksp->its = 0;
404:   maxit    = ksp->max_it;

406:   /* These three point to the three active solutions, we
407:      rotate these three at each solution update */
408:   km1      = 0; k = 1; kp1 = 2;
409:   sol_orig = ksp->vec_sol; /* ksp->vec_sol will be asigned to rotating vector p[k], thus save its address */
410:   b        = ksp->vec_rhs;
411:   p[km1]   = sol_orig;
412:   p[k]     = ksp->work[0];
413:   p[kp1]   = ksp->work[1];
414:   r        = ksp->work[2];

416:   /* use scale*B as our preconditioner */
417:   scale = 2.0/(cheb->emax + cheb->emin);

419:   /*   -alpha <=  scale*lambda(B^{-1}A) <= alpha   */
420:   alpha     = 1.0 - scale*(cheb->emin);
421:   Gamma     = 1.0;
422:   mu        = 1.0/alpha;
423:   omegaprod = 2.0/alpha;

425:   c[km1] = 1.0;
426:   c[k]   = mu;

428:   if (!ksp->guess_zero) {
429:     KSP_MatMult(ksp,Amat,p[km1],r);     /*  r = b - A*p[km1] */
430:     VecAYPX(r,-1.0,b);
431:   } else {
432:     VecCopy(b,r);
433:   }

435:   KSP_PCApply(ksp,r,p[k]);  /* p[k] = scale B^{-1}r + p[km1] */
436:   VecAYPX(p[k],scale,p[km1]);

438:   for (i=0; i<maxit; i++) {
439:     PetscObjectSAWsTakeAccess((PetscObject)ksp);

441:     ksp->its++;
442:     PetscObjectSAWsGrantAccess((PetscObject)ksp);
443:     c[kp1] = 2.0*mu*c[k] - c[km1];
444:     omega  = omegaprod*c[k]/c[kp1];

446:     KSP_MatMult(ksp,Amat,p[k],r);          /*  r = b - Ap[k]    */
447:     VecAYPX(r,-1.0,b);
448:     KSP_PCApply(ksp,r,p[kp1]);             /*  p[kp1] = B^{-1}r  */
449:     ksp->vec_sol = p[k];

451:     /* calculate residual norm if requested */
452:     if (ksp->normtype != KSP_NORM_NONE || ksp->numbermonitors) {
453:       if (ksp->normtype == KSP_NORM_UNPRECONDITIONED) {
454:         VecNorm(r,NORM_2,&rnorm);
455:       } else {
456:         VecNorm(p[kp1],NORM_2,&rnorm);
457:       }
458:       PetscObjectSAWsTakeAccess((PetscObject)ksp);
459:       ksp->rnorm   = rnorm;
460:       PetscObjectSAWsGrantAccess((PetscObject)ksp);
461:       KSPLogResidualHistory(ksp,rnorm);
462:       KSPMonitor(ksp,i,rnorm);
463:       (*ksp->converged)(ksp,i,rnorm,&ksp->reason,ksp->cnvP);
464:       if (ksp->reason) break;
465:     }

467:     /* y^{k+1} = omega(y^{k} - y^{k-1} + Gamma*r^{k}) + y^{k-1} */
468:     VecAXPBYPCZ(p[kp1],1.0-omega,omega,omega*Gamma*scale,p[km1],p[k]);

470:     ktmp = km1;
471:     km1  = k;
472:     k    = kp1;
473:     kp1  = ktmp;
474:   }
475:   if (!ksp->reason) {
476:     if (ksp->normtype != KSP_NORM_NONE) {
477:       KSP_MatMult(ksp,Amat,p[k],r);       /*  r = b - Ap[k]    */
478:       VecAYPX(r,-1.0,b);
479:       if (ksp->normtype == KSP_NORM_UNPRECONDITIONED) {
480:         VecNorm(r,NORM_2,&rnorm);
481:       } else {
482:         KSP_PCApply(ksp,r,p[kp1]); /* p[kp1] = B^{-1}r */
483:         VecNorm(p[kp1],NORM_2,&rnorm);
484:       }
485:       PetscObjectSAWsTakeAccess((PetscObject)ksp);
486:       ksp->rnorm   = rnorm;
487:       PetscObjectSAWsGrantAccess((PetscObject)ksp);
488:       ksp->vec_sol = p[k];
489:       KSPLogResidualHistory(ksp,rnorm);
490:       KSPMonitor(ksp,i,rnorm);
491:     }
492:     if (ksp->its >= ksp->max_it) {
493:       if (ksp->normtype != KSP_NORM_NONE) {
494:         (*ksp->converged)(ksp,i,rnorm,&ksp->reason,ksp->cnvP);
495:         if (!ksp->reason) ksp->reason = KSP_DIVERGED_ITS;
496:       } else ksp->reason = KSP_CONVERGED_ITS;
497:     }
498:   }

500:   /* make sure solution is in vector x */
501:   ksp->vec_sol = sol_orig;
502:   if (k) {
503:     VecCopy(p[k],sol_orig);
504:   }
505:   return(0);
506: }

508: static  PetscErrorCode KSPView_Chebyshev(KSP ksp,PetscViewer viewer)
509: {
510:   KSP_Chebyshev  *cheb = (KSP_Chebyshev*)ksp->data;
512:   PetscBool      iascii;

515:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
516:   if (iascii) {
517:     PetscViewerASCIIPrintf(viewer,"  Chebyshev: eigenvalue estimates used:  min = %g, max = %g\n",(double)cheb->emin,(double)cheb->emax);
518:     if (cheb->kspest) {
519:       PetscViewerASCIIPrintf(viewer,"  Chebyshev: eigenvalues estimate via %s min %g, max %g\n",((PetscObject)(cheb->kspest))->type_name,(double)cheb->emin_computed,(double)cheb->emax_computed);
520:       PetscViewerASCIIPrintf(viewer,"  Chebyshev: eigenvalues estimated using %s with translations  [%g %g; %g %g]\n",((PetscObject) cheb->kspest)->type_name,(double)cheb->tform[0],(double)cheb->tform[1],(double)cheb->tform[2],(double)cheb->tform[3]);
521:       PetscViewerASCIIPushTab(viewer);
522:       KSPView(cheb->kspest,viewer);
523:       PetscViewerASCIIPopTab(viewer);
524:       if (cheb->usenoisy) {
525:         PetscViewerASCIIPrintf(viewer,"  Chebyshev: estimating eigenvalues using noisy right hand side\n");
526:       }
527:     }
528:   }
529:   return(0);
530: }

532: static PetscErrorCode KSPDestroy_Chebyshev(KSP ksp)
533: {
534:   KSP_Chebyshev  *cheb = (KSP_Chebyshev*)ksp->data;

538:   KSPDestroy(&cheb->kspest);
539:   PetscObjectComposeFunction((PetscObject)ksp,"KSPChebyshevSetEigenvalues_C",NULL);
540:   PetscObjectComposeFunction((PetscObject)ksp,"KSPChebyshevEstEigSet_C",NULL);
541:   PetscObjectComposeFunction((PetscObject)ksp,"KSPChebyshevEstEigSetUseNoisy_C",NULL);
542:   PetscObjectComposeFunction((PetscObject)ksp,"KSPChebyshevEstEigGetKSP_C",NULL);
543:   KSPDestroyDefault(ksp);
544:   return(0);
545: }

547: /*MC
548:      KSPCHEBYSHEV - The preconditioned Chebyshev iterative method

550:    Options Database Keys:
551: +   -ksp_chebyshev_eigenvalues <emin,emax> - set approximations to the smallest and largest eigenvalues
552:                   of the preconditioned operator. If these are accurate you will get much faster convergence.
553: .   -ksp_chebyshev_esteig <a,b,c,d> - estimate eigenvalues using a Krylov method, then use this
554:                          transform for Chebyshev eigenvalue bounds (KSPChebyshevEstEigSet())
555: .   -ksp_chebyshev_esteig_steps - number of estimation steps
556: -   -ksp_chebyshev_esteig_noisy - use noisy number generator to create right hand side for eigenvalue estimator

558:    Level: beginner

560:    Notes: The Chebyshev method requires both the matrix and preconditioner to
561:           be symmetric positive (semi) definite.
562:           Only support for left preconditioning.

564:           Chebyshev is configured as a smoother by default, targetting the "upper" part of the spectrum.
565:           The user should call KSPChebyshevSetEigenvalues() if they have eigenvalue estimates.

567: .seealso:  KSPCreate(), KSPSetType(), KSPType (for list of available types), KSP,
568:            KSPChebyshevSetEigenvalues(), KSPChebyshevEstEigSet(), KSPChebyshevEstEigSetUseNoisy()
569:            KSPRICHARDSON, KSPCG, PCMG

571: M*/

573: PETSC_EXTERN PetscErrorCode KSPCreate_Chebyshev(KSP ksp)
574: {
576:   KSP_Chebyshev  *chebyshevP;

579:   PetscNewLog(ksp,&chebyshevP);

581:   ksp->data = (void*)chebyshevP;
582:   KSPSetSupportedNorm(ksp,KSP_NORM_PRECONDITIONED,PC_LEFT,3);
583:   KSPSetSupportedNorm(ksp,KSP_NORM_UNPRECONDITIONED,PC_LEFT,2);
584:   KSPSetSupportedNorm(ksp,KSP_NORM_NONE,PC_LEFT,1);

586:   chebyshevP->emin = 0.;
587:   chebyshevP->emax = 0.;

589:   chebyshevP->tform[0] = 0.0;
590:   chebyshevP->tform[1] = 0.1;
591:   chebyshevP->tform[2] = 0;
592:   chebyshevP->tform[3] = 1.1;
593:   chebyshevP->eststeps = 10;
594:   chebyshevP->usenoisy = PETSC_TRUE;

596:   ksp->ops->setup          = KSPSetUp_Chebyshev;
597:   ksp->ops->solve          = KSPSolve_Chebyshev;
598:   ksp->ops->destroy        = KSPDestroy_Chebyshev;
599:   ksp->ops->buildsolution  = KSPBuildSolutionDefault;
600:   ksp->ops->buildresidual  = KSPBuildResidualDefault;
601:   ksp->ops->setfromoptions = KSPSetFromOptions_Chebyshev;
602:   ksp->ops->view           = KSPView_Chebyshev;
603:   ksp->ops->reset          = KSPReset_Chebyshev;

605:   PetscObjectComposeFunction((PetscObject)ksp,"KSPChebyshevSetEigenvalues_C",KSPChebyshevSetEigenvalues_Chebyshev);
606:   PetscObjectComposeFunction((PetscObject)ksp,"KSPChebyshevEstEigSet_C",KSPChebyshevEstEigSet_Chebyshev);
607:   PetscObjectComposeFunction((PetscObject)ksp,"KSPChebyshevEstEigSetUseNoisy_C",KSPChebyshevEstEigSetUseNoisy_Chebyshev);
608:   PetscObjectComposeFunction((PetscObject)ksp,"KSPChebyshevEstEigGetKSP_C",KSPChebyshevEstEigGetKSP_Chebyshev);
609:   return(0);
610: }