Date: 2023-09-05T10:19:15+00:00

Actual source code: stsles.c
slepc-3.19.2 2023-09-05
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      1: /*
      2:    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
      3:    SLEPc - Scalable Library for Eigenvalue Problem Computations
      4:    Copyright (c) 2002-, 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>

     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: {
     23:   PetscFunctionBegin;
     26:   if (!st->ksp) PetscCall(STGetKSP(st,&st->ksp));
     27:   PetscTryTypeMethod(st,setdefaultksp);
     28:   PetscFunctionReturn(PETSC_SUCCESS);
     29: }

     31: /*
     32:    This is done by all ST types except PRECOND.
     33:    The default is an LU direct solver, or GMRES+Jacobi if matmode=shell.
     34: */
     35: PetscErrorCode STSetDefaultKSP_Default(ST st)
     36: {
     37:   PC             pc;
     38:   PCType         pctype;
     39:   KSPType        ksptype;

     41:   PetscFunctionBegin;
     42:   PetscCall(KSPGetPC(st->ksp,&pc));
     43:   PetscCall(KSPGetType(st->ksp,&ksptype));
     44:   PetscCall(PCGetType(pc,&pctype));
     45:   if (!pctype && !ksptype) {
     46:     if (st->Pmat || st->Psplit) {
     47:       PetscCall(KSPSetType(st->ksp,KSPBCGS));
     48:       PetscCall(PCSetType(pc,PCBJACOBI));
     49:     } else if (st->matmode == ST_MATMODE_SHELL) {
     50:       PetscCall(KSPSetType(st->ksp,KSPGMRES));
     51:       PetscCall(PCSetType(pc,PCJACOBI));
     52:     } else {
     53:       PetscCall(KSPSetType(st->ksp,KSPPREONLY));
     54:       PetscCall(PCSetType(pc,st->asymm?PCCHOLESKY:PCLU));
     55:     }
     56:   }
     57:   PetscCall(KSPSetErrorIfNotConverged(st->ksp,PETSC_TRUE));
     58:   PetscFunctionReturn(PETSC_SUCCESS);
     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:    Neighbor-wise Collective

     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: {
     81:   PetscFunctionBegin;
     86:   STCheckMatrices(st,1);
     87:   PetscCheck(k>=0 && k<PetscMax(2,st->nmat),PetscObjectComm((PetscObject)st),PETSC_ERR_ARG_OUTOFRANGE,"k must be between 0 and %" PetscInt_FMT,st->nmat);
     88:   PetscCheck(x!=y,PetscObjectComm((PetscObject)st),PETSC_ERR_ARG_IDN,"x and y must be different vectors");
     89:   PetscCall(VecSetErrorIfLocked(y,3));

     91:   if (st->state!=ST_STATE_SETUP) PetscCall(STSetUp(st));
     92:   PetscCall(VecLockReadPush(x));
     93:   PetscCall(PetscLogEventBegin(ST_MatMult,st,x,y,0));
     94:   if (!st->T[k]) PetscCall(VecCopy(x,y)); /* T[k]=NULL means identity matrix */
     95:   else PetscCall(MatMult(st->T[k],x,y));
     96:   PetscCall(PetscLogEventEnd(ST_MatMult,st,x,y,0));
     97:   PetscCall(VecLockReadPop(x));
     98:   PetscFunctionReturn(PETSC_SUCCESS);
     99: }

    101: /*@
    102:    STMatMultTranspose - Computes the matrix-vector product y = T[k]' x, where T[k] is
    103:    the k-th matrix of the spectral transformation.

    105:    Neighbor-wise Collective

    107:    Input Parameters:
    108: +  st - the spectral transformation context
    109: .  k  - index of matrix to use
    110: -  x  - the vector to be multiplied

    112:    Output Parameter:
    113: .  y - the result

    115:    Level: developer

    117: .seealso: STMatMult()
    118: @*/
    119: PetscErrorCode STMatMultTranspose(ST st,PetscInt k,Vec x,Vec y)
    120: {
    121:   PetscFunctionBegin;
    126:   STCheckMatrices(st,1);
    127:   PetscCheck(k>=0 && k<PetscMax(2,st->nmat),PetscObjectComm((PetscObject)st),PETSC_ERR_ARG_OUTOFRANGE,"k must be between 0 and %" PetscInt_FMT,st->nmat);
    128:   PetscCheck(x!=y,PetscObjectComm((PetscObject)st),PETSC_ERR_ARG_IDN,"x and y must be different vectors");
    129:   PetscCall(VecSetErrorIfLocked(y,3));

    131:   if (st->state!=ST_STATE_SETUP) PetscCall(STSetUp(st));
    132:   PetscCall(VecLockReadPush(x));
    133:   PetscCall(PetscLogEventBegin(ST_MatMultTranspose,st,x,y,0));
    134:   if (!st->T[k]) PetscCall(VecCopy(x,y)); /* T[k]=NULL means identity matrix */
    135:   else PetscCall(MatMultTranspose(st->T[k],x,y));
    136:   PetscCall(PetscLogEventEnd(ST_MatMultTranspose,st,x,y,0));
    137:   PetscCall(VecLockReadPop(x));
    138:   PetscFunctionReturn(PETSC_SUCCESS);
    139: }

    141: /*@
    142:    STMatSolve - Solves P x = b, where P is the preconditioner matrix of
    143:    the spectral transformation, using a KSP object stored internally.

    145:    Collective

    147:    Input Parameters:
    148: +  st - the spectral transformation context
    149: -  b  - right hand side vector

    151:    Output Parameter:
    152: .  x - computed solution

    154:    Level: developer

    156: .seealso: STMatSolveTranspose()
    157: @*/
    158: PetscErrorCode STMatSolve(ST st,Vec b,Vec x)
    159: {
    160:   PetscFunctionBegin;
    164:   STCheckMatrices(st,1);
    165:   PetscCheck(x!=b,PetscObjectComm((PetscObject)st),PETSC_ERR_ARG_IDN,"x and b must be different vectors");
    166:   PetscCall(VecSetErrorIfLocked(x,3));

    168:   if (st->state!=ST_STATE_SETUP) PetscCall(STSetUp(st));
    169:   PetscCall(VecLockReadPush(b));
    170:   PetscCall(PetscLogEventBegin(ST_MatSolve,st,b,x,0));
    171:   if (!st->P) PetscCall(VecCopy(b,x)); /* P=NULL means identity matrix */
    172:   else PetscCall(KSPSolve(st->ksp,b,x));
    173:   PetscCall(PetscLogEventEnd(ST_MatSolve,st,b,x,0));
    174:   PetscCall(VecLockReadPop(b));
    175:   PetscFunctionReturn(PETSC_SUCCESS);
    176: }

    178: /*@
    179:    STMatMatSolve - Solves P X = B, where P is the preconditioner matrix of
    180:    the spectral transformation, using a KSP object stored internally.

    182:    Collective

    184:    Input Parameters:
    185: +  st - the spectral transformation context
    186: -  B  - right hand side vectors

    188:    Output Parameter:
    189: .  X - computed solutions

    191:    Level: developer

    193: .seealso: STMatSolve()
    194: @*/
    195: PetscErrorCode STMatMatSolve(ST st,Mat B,Mat X)
    196: {
    197:   PetscFunctionBegin;
    201:   STCheckMatrices(st,1);

    203:   if (st->state!=ST_STATE_SETUP) PetscCall(STSetUp(st));
    204:   PetscCall(PetscLogEventBegin(ST_MatSolve,st,B,X,0));
    205:   if (!st->P) PetscCall(MatCopy(B,X,SAME_NONZERO_PATTERN)); /* P=NULL means identity matrix */
    206:   else PetscCall(KSPMatSolve(st->ksp,B,X));
    207:   PetscCall(PetscLogEventEnd(ST_MatSolve,st,B,X,0));
    208:   PetscFunctionReturn(PETSC_SUCCESS);
    209: }

    211: /*@
    212:    STMatSolveTranspose - Solves P' x = b, where P is the preconditioner matrix of
    213:    the spectral transformation, using a KSP object stored internally.

    215:    Collective

    217:    Input Parameters:
    218: +  st - the spectral transformation context
    219: -  b  - right hand side vector

    221:    Output Parameter:
    222: .  x - computed solution

    224:    Level: developer

    226: .seealso: STMatSolve()
    227: @*/
    228: PetscErrorCode STMatSolveTranspose(ST st,Vec b,Vec x)
    229: {
    230:   PetscFunctionBegin;
    234:   STCheckMatrices(st,1);
    235:   PetscCheck(x!=b,PetscObjectComm((PetscObject)st),PETSC_ERR_ARG_IDN,"x and b must be different vectors");
    236:   PetscCall(VecSetErrorIfLocked(x,3));

    238:   if (st->state!=ST_STATE_SETUP) PetscCall(STSetUp(st));
    239:   PetscCall(VecLockReadPush(b));
    240:   PetscCall(PetscLogEventBegin(ST_MatSolveTranspose,st,b,x,0));
    241:   if (!st->P) PetscCall(VecCopy(b,x)); /* P=NULL means identity matrix */
    242:   else PetscCall(KSPSolveTranspose(st->ksp,b,x));
    243:   PetscCall(PetscLogEventEnd(ST_MatSolveTranspose,st,b,x,0));
    244:   PetscCall(VecLockReadPop(b));
    245:   PetscFunctionReturn(PETSC_SUCCESS);
    246: }

    248: PetscErrorCode STCheckFactorPackage(ST st)
    249: {
    250:   PC             pc;
    251:   PetscMPIInt    size;
    252:   PetscBool      flg;
    253:   MatSolverType  stype;

    255:   PetscFunctionBegin;
    256:   PetscCallMPI(MPI_Comm_size(PetscObjectComm((PetscObject)st),&size));
    257:   if (size==1) PetscFunctionReturn(PETSC_SUCCESS);
    258:   PetscCall(KSPGetPC(st->ksp,&pc));
    259:   PetscCall(PCFactorGetMatSolverType(pc,&stype));
    260:   if (stype) {   /* currently selected PC is a factorization */
    261:     PetscCall(PetscStrcmp(stype,MATSOLVERPETSC,&flg));
    262:     PetscCheck(!flg,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");
    263:   }
    264:   PetscFunctionReturn(PETSC_SUCCESS);
    265: }

    267: /*@
    268:    STSetKSP - Sets the KSP object associated with the spectral
    269:    transformation.

    271:    Collective

    273:    Input Parameters:
    274: +  st   - the spectral transformation context
    275: -  ksp  - the linear system context

    277:    Level: advanced

    279: .seealso: STGetKSP()
    280: @*/
    281: PetscErrorCode STSetKSP(ST st,KSP ksp)
    282: {
    283:   PetscFunctionBegin;
    286:   PetscCheckSameComm(st,1,ksp,2);
    287:   STCheckNotSeized(st,1);
    288:   PetscCall(PetscObjectReference((PetscObject)ksp));
    289:   PetscCall(KSPDestroy(&st->ksp));
    290:   st->ksp = ksp;
    291:   PetscFunctionReturn(PETSC_SUCCESS);
    292: }

    294: /*@
    295:    STGetKSP - Gets the KSP object associated with the spectral
    296:    transformation.

    298:    Collective

    300:    Input Parameter:
    301: .  st - the spectral transformation context

    303:    Output Parameter:
    304: .  ksp  - the linear system context

    306:    Level: intermediate

    308: .seealso: STSetKSP()
    309: @*/
    310: PetscErrorCode STGetKSP(ST st,KSP* ksp)
    311: {
    312:   PetscFunctionBegin;
    315:   if (!st->ksp) {
    316:     PetscCall(KSPCreate(PetscObjectComm((PetscObject)st),&st->ksp));
    317:     PetscCall(PetscObjectIncrementTabLevel((PetscObject)st->ksp,(PetscObject)st,1));
    318:     PetscCall(KSPSetOptionsPrefix(st->ksp,((PetscObject)st)->prefix));
    319:     PetscCall(KSPAppendOptionsPrefix(st->ksp,"st_"));
    320:     PetscCall(PetscObjectSetOptions((PetscObject)st->ksp,((PetscObject)st)->options));
    321:     PetscCall(KSPSetTolerances(st->ksp,SLEPC_DEFAULT_TOL,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT));
    322:   }
    323:   *ksp = st->ksp;
    324:   PetscFunctionReturn(PETSC_SUCCESS);
    325: }

    327: PetscErrorCode STCheckNullSpace_Default(ST st,BV V)
    328: {
    329:   PetscInt       nc,i,c;
    330:   PetscReal      norm;
    331:   Vec            *T,w,vi;
    332:   Mat            A;
    333:   PC             pc;
    334:   MatNullSpace   nullsp;

    336:   PetscFunctionBegin;
    337:   PetscCall(BVGetNumConstraints(V,&nc));
    338:   PetscCall(PetscMalloc1(nc,&T));
    339:   if (!st->ksp) PetscCall(STGetKSP(st,&st->ksp));
    340:   PetscCall(KSPGetPC(st->ksp,&pc));
    341:   PetscCall(PCGetOperators(pc,&A,NULL));
    342:   PetscCall(MatCreateVecs(A,NULL,&w));
    343:   c = 0;
    344:   for (i=0;i<nc;i++) {
    345:     PetscCall(BVGetColumn(V,-nc+i,&vi));
    346:     PetscCall(MatMult(A,vi,w));
    347:     PetscCall(VecNorm(w,NORM_2,&norm));
    348:     if (norm < 10.0*PETSC_SQRT_MACHINE_EPSILON) {
    349:       PetscCall(PetscInfo(st,"Vector %" PetscInt_FMT " included in the nullspace of OP, norm=%g\n",i,(double)norm));
    350:       PetscCall(BVCreateVec(V,T+c));
    351:       PetscCall(VecCopy(vi,T[c]));
    352:       PetscCall(VecNormalize(T[c],NULL));
    353:       c++;
    354:     } else PetscCall(PetscInfo(st,"Vector %" PetscInt_FMT " discarded as possible nullspace of OP, norm=%g\n",i,(double)norm));
    355:     PetscCall(BVRestoreColumn(V,-nc+i,&vi));
    356:   }
    357:   PetscCall(VecDestroy(&w));
    358:   if (c>0) {
    359:     PetscCall(MatNullSpaceCreate(PetscObjectComm((PetscObject)st),PETSC_FALSE,c,T,&nullsp));
    360:     PetscCall(MatSetNullSpace(A,nullsp));
    361:     PetscCall(MatNullSpaceDestroy(&nullsp));
    362:     PetscCall(VecDestroyVecs(c,&T));
    363:   } else PetscCall(PetscFree(T));
    364:   PetscFunctionReturn(PETSC_SUCCESS);
    365: }

    367: /*@
    368:    STCheckNullSpace - Tests if constraint vectors are nullspace vectors.

    370:    Collective

    372:    Input Parameters:
    373: +  st - the spectral transformation context
    374: -  V  - basis vectors to be checked

    376:    Notes:
    377:    Given a basis vectors object, this function tests each of its constraint
    378:    vectors to be a nullspace vector of the coefficient matrix of the
    379:    associated KSP object. All these nullspace vectors are passed to the KSP
    380:    object.

    382:    This function allows handling singular pencils and solving some problems
    383:    in which the nullspace is important (see the users guide for details).

    385:    Level: developer

    387: .seealso: EPSSetDeflationSpace()
    388: @*/
    389: PetscErrorCode STCheckNullSpace(ST st,BV V)
    390: {
    391:   PetscInt       nc;

    393:   PetscFunctionBegin;
    397:   PetscCheckSameComm(st,1,V,2);
    398:   PetscCheck(st->state,PetscObjectComm((PetscObject)st),PETSC_ERR_ARG_WRONGSTATE,"Must call STSetUp() first");

    400:   PetscCall(BVGetNumConstraints(V,&nc));
    401:   if (nc) PetscTryTypeMethod(st,checknullspace,V);
    402:   PetscFunctionReturn(PETSC_SUCCESS);
    403: }