Actual source code: stsles.c

slepc-3.8.2 2017-12-01
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  1: /*
  2:    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
  3:    SLEPc - Scalable Library for Eigenvalue Problem Computations
  4:    Copyright (c) 2002-2017, Universitat Politecnica de Valencia, Spain

  6:    This file is part of SLEPc.
  7:    SLEPc is distributed under a 2-clause BSD license (see LICENSE).
  8:    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
  9: */
 10: /*
 11:    ST interface routines related to the KSP object associated with it
 12: */

 14: #include <slepc/private/stimpl.h>            /*I "slepcst.h" I*/

 16: /*
 17:    This is used to set a default type for the KSP and PC objects.
 18:    It is called at STSetFromOptions (before KSPSetFromOptions)
 19:    and also at STSetUp (in case STSetFromOptions was not called).
 20: */
 21: PetscErrorCode STSetDefaultKSP(ST st)
 22: {

 28:   if (!st->ksp) { STGetKSP(st,&st->ksp); }
 29:   if (st->ops->setdefaultksp) { (*st->ops->setdefaultksp)(st); }
 30:   return(0);
 31: }

 33: /*
 34:    This is done by all ST types except PRECOND.
 35:    The default is an LU direct solver, or GMRES+Jacobi if matmode=shell.
 36: */
 37: PetscErrorCode STSetDefaultKSP_Default(ST st)
 38: {
 40:   PC             pc;
 41:   PCType         pctype;
 42:   KSPType        ksptype;

 45:   KSPGetPC(st->ksp,&pc);
 46:   KSPGetType(st->ksp,&ksptype);
 47:   PCGetType(pc,&pctype);
 48:   if (!pctype && !ksptype) {
 49:     if (st->shift_matrix == ST_MATMODE_SHELL) {
 50:       KSPSetType(st->ksp,KSPGMRES);
 51:       PCSetType(pc,PCJACOBI);
 52:     } else {
 53:       KSPSetType(st->ksp,KSPPREONLY);
 54:       PCSetType(pc,PCLU);
 55:     }
 56:   }
 57:   KSPSetErrorIfNotConverged(st->ksp,PETSC_TRUE);
 58:   return(0);
 59: }

 61: /*@
 62:    STMatMult - Computes the matrix-vector product y = T[k] x, where T[k] is
 63:    the k-th matrix of the spectral transformation.

 65:    Collective on ST

 67:    Input Parameters:
 68: +  st - the spectral transformation context
 69: .  k  - index of matrix to use
 70: -  x  - the vector to be multiplied

 72:    Output Parameter:
 73: .  y - the result

 75:    Level: developer

 77: .seealso: STMatMultTranspose()
 78: @*/
 79: PetscErrorCode STMatMult(ST st,PetscInt k,Vec x,Vec y)
 80: {

 88:   STCheckMatrices(st,1);
 89:   if (k<0 || k>=PetscMax(2,st->nmat)) SETERRQ1(PetscObjectComm((PetscObject)st),PETSC_ERR_ARG_OUTOFRANGE,"k must be between 0 and %D",st->nmat);
 90:   if (x == y) SETERRQ(PetscObjectComm((PetscObject)st),PETSC_ERR_ARG_IDN,"x and y must be different vectors");
 91:   VecLocked(y,3);

 93:   if (st->state!=ST_STATE_SETUP) { STSetUp(st); }
 94:   VecLockPush(x);
 95:   PetscLogEventBegin(ST_MatMult,st,x,y,0);
 96:   if (!st->T[k]) {
 97:     /* T[k]=NULL means identity matrix */
 98:     VecCopy(x,y);
 99:   } else {
100:     MatMult(st->T[k],x,y);
101:   }
102:   PetscLogEventEnd(ST_MatMult,st,x,y,0);
103:   VecLockPop(x);
104:   return(0);
105: }

107: /*@
108:    STMatMultTranspose - Computes the matrix-vector product y = T[k]' x, where T[k] is
109:    the k-th matrix of the spectral transformation.

111:    Collective on ST

113:    Input Parameters:
114: +  st - the spectral transformation context
115: .  k  - index of matrix to use
116: -  x  - the vector to be multiplied

118:    Output Parameter:
119: .  y - the result

121:    Level: developer

123: .seealso: STMatMult()
124: @*/
125: PetscErrorCode STMatMultTranspose(ST st,PetscInt k,Vec x,Vec y)
126: {

134:   STCheckMatrices(st,1);
135:   if (k<0 || k>=PetscMax(2,st->nmat)) SETERRQ1(PetscObjectComm((PetscObject)st),PETSC_ERR_ARG_OUTOFRANGE,"k must be between 0 and %D",st->nmat);
136:   if (x == y) SETERRQ(PetscObjectComm((PetscObject)st),PETSC_ERR_ARG_IDN,"x and y must be different vectors");
137:   VecLocked(y,3);

139:   if (st->state!=ST_STATE_SETUP) { STSetUp(st); }
140:   VecLockPush(x);
141:   PetscLogEventBegin(ST_MatMultTranspose,st,x,y,0);
142:   if (!st->T[k]) {
143:     /* T[k]=NULL means identity matrix */
144:     VecCopy(x,y);
145:   } else {
146:     MatMultTranspose(st->T[k],x,y);
147:   }
148:   PetscLogEventEnd(ST_MatMultTranspose,st,x,y,0);
149:   VecLockPop(x);
150:   return(0);
151: }

153: /*@
154:    STMatSolve - Solves P x = b, where P is the preconditioner matrix of
155:    the spectral transformation, using a KSP object stored internally.

157:    Collective on ST

159:    Input Parameters:
160: +  st - the spectral transformation context
161: -  b  - right hand side vector

163:    Output Parameter:
164: .  x - computed solution

166:    Level: developer

168: .seealso: STMatSolveTranspose()
169: @*/
170: PetscErrorCode STMatSolve(ST st,Vec b,Vec x)
171: {
173:   PetscInt       its;
174:   PetscBool      flg;

180:   STCheckMatrices(st,1);
181:   if (x == b) SETERRQ(PetscObjectComm((PetscObject)st),PETSC_ERR_ARG_IDN,"x and b must be different vectors");
182:   VecLocked(x,3);

184:   if (st->state!=ST_STATE_SETUP) { STSetUp(st); }
185:   VecLockPush(b);
186:   PetscLogEventBegin(ST_MatSolve,st,b,x,0);
187:   PetscObjectTypeCompareAny((PetscObject)st,&flg,STPRECOND,STSHELL,"");
188:   if (!flg && !st->P) {
189:     /* P=NULL means identity matrix */
190:     VecCopy(b,x);
191:     return(0);
192:   }
193:   if (!st->ksp) { STGetKSP(st,&st->ksp); }
194:   KSPSolve(st->ksp,b,x);
195:   KSPGetIterationNumber(st->ksp,&its);
196:   PetscInfo1(st,"Linear solve iterations=%D\n",its);
197:   PetscLogEventEnd(ST_MatSolve,st,b,x,0);
198:   VecLockPop(b);
199:   return(0);
200: }

202: /*@
203:    STMatSolveTranspose - Solves P' x = b, where P is the preconditioner matrix of
204:    the spectral transformation, using a KSP object stored internally.

206:    Collective on ST

208:    Input Parameters:
209: .  st - the spectral transformation context
210: .  b  - right hand side vector

212:    Output Parameter:
213: .  x - computed solution

215:    Level: developer

217: .seealso: STMatSolve()
218: @*/
219: PetscErrorCode STMatSolveTranspose(ST st,Vec b,Vec x)
220: {
222:   PetscInt       its;
223:   PetscBool      flg;

229:   STCheckMatrices(st,1);
230:   if (x == b) SETERRQ(PetscObjectComm((PetscObject)st),PETSC_ERR_ARG_IDN,"x and b must be different vectors");
231:   VecLocked(x,3);

233:   if (st->state!=ST_STATE_SETUP) { STSetUp(st); }
234:   VecLockPush(b);
235:   PetscLogEventBegin(ST_MatSolveTranspose,st,b,x,0);
236:   PetscObjectTypeCompareAny((PetscObject)st,&flg,STPRECOND,STSHELL,"");
237:   if (!flg && !st->P) {
238:     /* P=NULL means identity matrix */
239:     VecCopy(b,x);
240:     return(0);
241:   }
242:   if (!st->ksp) { STGetKSP(st,&st->ksp); }
243:   KSPSolveTranspose(st->ksp,b,x);
244:   KSPGetIterationNumber(st->ksp,&its);
245:   PetscInfo1(st,"Linear solve iterations=%D\n",its);
246:   PetscLogEventEnd(ST_MatSolveTranspose,st,b,x,0);
247:   VecLockPop(b);
248:   return(0);
249: }

251: /*
252:    STMatSetHermitian - Sets the Hermitian flag to the ST matrix.

254:    Input Parameters:
255: .  st - the spectral transformation context
256: .  M  - matrix
257: */
258: PetscErrorCode STMatSetHermitian(ST st,Mat M)
259: {
260: #if defined(PETSC_USE_COMPLEX)
262:   PetscBool      set,aherm,mherm;
263:   PetscInt       i;
264: #endif

267: #if defined(PETSC_USE_COMPLEX)
268:   mherm = PETSC_FALSE;
269:   for (i=0;i<st->nmat;i++) {
270:     MatIsHermitianKnown(st->A[i],&set,&aherm);
271:     if (!set) aherm = PETSC_FALSE;
272:     mherm = (mherm && aherm)? PETSC_TRUE: PETSC_FALSE;
273:     if (PetscRealPart(st->sigma)==0.0) break;
274:   }
275:   mherm = (mherm && PetscImaginaryPart(st->sigma)==0.0)? PETSC_TRUE: PETSC_FALSE;
276:   MatSetOption(M,MAT_HERMITIAN,mherm);
277: #endif
278:   return(0);
279: }

281: PetscErrorCode STCheckFactorPackage(ST st)
282: {
283:   PetscErrorCode         ierr;
284:   PC                     pc;
285:   PetscMPIInt            size;
286:   PetscBool              flg;
287:   const MatSolverPackage stype;

290:   MPI_Comm_size(PetscObjectComm((PetscObject)st),&size);
291:   if (size==1) return(0);
292:   KSPGetPC(st->ksp,&pc);
293:   PCFactorGetMatSolverPackage(pc,&stype);
294:   if (stype) {   /* currently selected PC is a factorization */
295:     PetscStrcmp(stype,MATSOLVERPETSC,&flg);
296:     if (flg) SETERRQ(PetscObjectComm((PetscObject)st),PETSC_ERR_SUP,"You chose to solve linear systems with a factorization, but in parallel runs you need to select an external package; see the users guide for details");
297:   }
298:   return(0);
299: }

301: /*@
302:    STSetKSP - Sets the KSP object associated with the spectral
303:    transformation.

305:    Collective on ST

307:    Input Parameters:
308: +  st   - the spectral transformation context
309: -  ksp  - the linear system context

311:    Level: advanced
312: @*/
313: PetscErrorCode STSetKSP(ST st,KSP ksp)
314: {

321:   PetscObjectReference((PetscObject)ksp);
322:   KSPDestroy(&st->ksp);
323:   st->ksp = ksp;
324:   PetscLogObjectParent((PetscObject)st,(PetscObject)st->ksp);
325:   return(0);
326: }

328: /*@
329:    STGetKSP - Gets the KSP object associated with the spectral
330:    transformation.

332:    Not Collective

334:    Input Parameter:
335: .  st - the spectral transformation context

337:    Output Parameter:
338: .  ksp  - the linear system context

340:    Level: intermediate
341: @*/
342: PetscErrorCode STGetKSP(ST st,KSP* ksp)
343: {

349:   if (!st->ksp) {
350:     KSPCreate(PetscObjectComm((PetscObject)st),&st->ksp);
351:     KSPSetOptionsPrefix(st->ksp,((PetscObject)st)->prefix);
352:     KSPAppendOptionsPrefix(st->ksp,"st_");
353:     PetscObjectIncrementTabLevel((PetscObject)st->ksp,(PetscObject)st,1);
354:     PetscLogObjectParent((PetscObject)st,(PetscObject)st->ksp);
355:     KSPSetTolerances(st->ksp,SLEPC_DEFAULT_TOL,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT);
356:   }
357:   *ksp = st->ksp;
358:   return(0);
359: }

361: PetscErrorCode STCheckNullSpace_Default(ST st,BV V)
362: {
364:   PetscInt       nc,i,c;
365:   PetscReal      norm;
366:   Vec            *T,w,vi;
367:   Mat            A;
368:   PC             pc;
369:   MatNullSpace   nullsp;

372:   BVGetNumConstraints(V,&nc);
373:   PetscMalloc1(nc,&T);
374:   if (!st->ksp) { STGetKSP(st,&st->ksp); }
375:   KSPGetPC(st->ksp,&pc);
376:   PCGetOperators(pc,&A,NULL);
377:   MatCreateVecs(A,NULL,&w);
378:   c = 0;
379:   for (i=0;i<nc;i++) {
380:     BVGetColumn(V,-nc+i,&vi);
381:     MatMult(A,vi,w);
382:     VecNorm(w,NORM_2,&norm);
383:     if (norm < 1e-8) {
384:       PetscInfo2(st,"Vector %D norm=%g\n",i,(double)norm);
385:       BVCreateVec(V,T+c);
386:       VecCopy(vi,T[c]);
387:       c++;
388:     }
389:     BVRestoreColumn(V,-nc+i,&vi);
390:   }
391:   VecDestroy(&w);
392:   if (c>0) {
393:     MatNullSpaceCreate(PetscObjectComm((PetscObject)st),PETSC_FALSE,c,T,&nullsp);
394:     MatSetNullSpace(A,nullsp);
395:     MatNullSpaceDestroy(&nullsp);
396:     VecDestroyVecs(c,&T);
397:   } else {
398:     PetscFree(T);
399:   }
400:   return(0);
401: }

403: /*@
404:    STCheckNullSpace - Given a basis vectors object, this function tests each
405:    of its constraint vectors to be a nullspace vector of the coefficient
406:    matrix of the associated KSP object. All these nullspace vectors are passed
407:    to the KSP object.

409:    Collective on ST

411:    Input Parameters:
412: +  st - the spectral transformation context
413: -  V  - basis vectors to be checked

415:    Note:
416:    This function allows to handle singular pencils and to solve some problems
417:    in which the nullspace is important (see the users guide for details).

419:    Level: developer

421: .seealso: EPSSetDeflationSpace()
422: @*/
423: PetscErrorCode STCheckNullSpace(ST st,BV V)
424: {
426:   PetscInt       nc;

433:   if (!st->state) SETERRQ(PetscObjectComm((PetscObject)st),PETSC_ERR_ARG_WRONGSTATE,"Must call STSolve() first");

435:   BVGetNumConstraints(V,&nc);
436:   if (nc && st->ops->checknullspace) {
437:     (*st->ops->checknullspace)(st,V);
438:   }
439:   return(0);
440: }