Date: 2024-04-26T10:22:57+00:00

Actual source code: bvglobal.c
slepc-3.21.1 2024-04-26
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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:    BV operations involving global communication
     12: */

     14: #include <slepc/private/bvimpl.h>

     16: /*
     17:   BVDot for the particular case of non-standard inner product with
     18:   matrix B, which is assumed to be symmetric (or complex Hermitian)
     19: */
     20: static inline PetscErrorCode BVDot_Private(BV X,BV Y,Mat M)
     21: {
     22:   PetscObjectId  idx,idy;
     23:   PetscInt       i,j,jend,m;
     24:   PetscScalar    *marray;
     25:   PetscBool      symm=PETSC_FALSE;
     26:   Mat            B;
     27:   Vec            z;

     29:   PetscFunctionBegin;
     30:   BVCheckOp(Y,1,dotvec);
     31:   PetscCall(MatGetSize(M,&m,NULL));
     32:   PetscCall(MatDenseGetArray(M,&marray));
     33:   PetscCall(PetscObjectGetId((PetscObject)X,&idx));
     34:   PetscCall(PetscObjectGetId((PetscObject)Y,&idy));
     35:   B = Y->matrix;
     36:   Y->matrix = NULL;
     37:   if (idx==idy) symm=PETSC_TRUE;  /* M=X'BX is symmetric */
     38:   jend = X->k;
     39:   for (j=X->l;j<jend;j++) {
     40:     if (symm) Y->k = j+1;
     41:     PetscCall(BVGetColumn(X->cached,j,&z));
     42:     PetscUseTypeMethod(Y,dotvec,z,marray+j*m+Y->l);
     43:     PetscCall(BVRestoreColumn(X->cached,j,&z));
     44:     if (symm) {
     45:       for (i=X->l;i<j;i++)
     46:         marray[j+i*m] = PetscConj(marray[i+j*m]);
     47:     }
     48:   }
     49:   PetscCall(MatDenseRestoreArray(M,&marray));
     50:   Y->matrix = B;
     51:   PetscFunctionReturn(PETSC_SUCCESS);
     52: }

     54: /*@
     55:    BVDot - Computes the 'block-dot' product of two basis vectors objects.

     57:    Collective

     59:    Input Parameters:
     60: +  X - first basis vectors
     61: -  Y - second basis vectors

     63:    Output Parameter:
     64: .  M - the resulting matrix

     66:    Notes:
     67:    This is the generalization of VecDot() for a collection of vectors, M = Y^H*X.
     68:    The result is a matrix M whose entry m_ij is equal to y_i^H x_j (where y_i^H
     69:    denotes the conjugate transpose of y_i).

     71:    If a non-standard inner product has been specified with BVSetMatrix(),
     72:    then the result is M = Y^H*B*X. In this case, both X and Y must have
     73:    the same associated matrix.

     75:    On entry, M must be a sequential dense Mat with dimensions m,n at least, where
     76:    m is the number of active columns of Y and n is the number of active columns of X.
     77:    Only rows (resp. columns) of M starting from ly (resp. lx) are computed,
     78:    where ly (resp. lx) is the number of leading columns of Y (resp. X).

     80:    X and Y need not be different objects.

     82:    Level: intermediate

     84: .seealso: BVDotVec(), BVDotColumn(), BVSetActiveColumns(), BVSetMatrix()
     85: @*/
     86: PetscErrorCode BVDot(BV X,BV Y,Mat M)
     87: {
     88:   PetscInt       m,n;

     90:   PetscFunctionBegin;
     95:   BVCheckSizes(X,1);
     97:   BVCheckSizes(Y,2);
     99:   PetscCheckSameTypeAndComm(X,1,Y,2);
    100:   PetscCheckTypeNames(M,MATSEQDENSE,MATSEQDENSECUDA);

    102:   PetscCall(MatGetSize(M,&m,&n));
    103:   PetscCheck(m>=Y->k,PetscObjectComm((PetscObject)X),PETSC_ERR_ARG_SIZ,"Mat argument has %" PetscInt_FMT " rows, should have at least %" PetscInt_FMT,m,Y->k);
    104:   PetscCheck(n>=X->k,PetscObjectComm((PetscObject)X),PETSC_ERR_ARG_SIZ,"Mat argument has %" PetscInt_FMT " columns, should have at least %" PetscInt_FMT,n,X->k);
    105:   PetscCheck(X->n==Y->n,PetscObjectComm((PetscObject)X),PETSC_ERR_ARG_INCOMP,"Mismatching local dimension X %" PetscInt_FMT ", Y %" PetscInt_FMT,X->n,Y->n);
    106:   PetscCheck(X->matrix==Y->matrix,PetscObjectComm((PetscObject)X),PETSC_ERR_ARG_WRONGSTATE,"X and Y must have the same inner product matrix");
    107:   if (X->l==X->k || Y->l==Y->k) PetscFunctionReturn(PETSC_SUCCESS);

    109:   PetscCall(PetscLogEventBegin(BV_Dot,X,Y,0,0));
    110:   if (X->matrix) { /* non-standard inner product */
    111:     /* compute BX first */
    112:     PetscCall(BV_IPMatMultBV(X));
    113:     if (X->vmm==BV_MATMULT_VECS) {
    114:       /* perform computation column by column */
    115:       PetscCall(BVDot_Private(X,Y,M));
    116:     } else PetscUseTypeMethod(X->cached,dot,Y,M);
    117:   } else PetscUseTypeMethod(X,dot,Y,M);
    118:   PetscCall(PetscLogEventEnd(BV_Dot,X,Y,0,0));
    119:   PetscFunctionReturn(PETSC_SUCCESS);
    120: }

    122: /*@
    123:    BVDotVec - Computes multiple dot products of a vector against all the
    124:    column vectors of a BV.

    126:    Collective

    128:    Input Parameters:
    129: +  X - basis vectors
    130: -  y - a vector

    132:    Output Parameter:
    133: .  m - an array where the result must be placed

    135:    Notes:
    136:    This is analogue to VecMDot(), but using BV to represent a collection
    137:    of vectors. The result is m = X^H*y, so m_i is equal to x_j^H y. Note
    138:    that here X is transposed as opposed to BVDot().

    140:    If a non-standard inner product has been specified with BVSetMatrix(),
    141:    then the result is m = X^H*B*y.

    143:    The length of array m must be equal to the number of active columns of X
    144:    minus the number of leading columns, i.e. the first entry of m is the
    145:    product of the first non-leading column with y.

    147:    Level: intermediate

    149: .seealso: BVDot(), BVDotColumn(), BVSetActiveColumns(), BVSetMatrix()
    150: @*/
    151: PetscErrorCode BVDotVec(BV X,Vec y,PetscScalar m[])
    152: {
    153:   PetscInt       n;

    155:   PetscFunctionBegin;
    159:   BVCheckSizes(X,1);
    160:   BVCheckOp(X,1,dotvec);
    162:   PetscCheckSameTypeAndComm(X,1,y,2);

    164:   PetscCall(VecGetLocalSize(y,&n));
    165:   PetscCheck(X->n==n,PetscObjectComm((PetscObject)X),PETSC_ERR_ARG_INCOMP,"Mismatching local dimension X %" PetscInt_FMT ", y %" PetscInt_FMT,X->n,n);

    167:   PetscCall(PetscLogEventBegin(BV_DotVec,X,y,0,0));
    168:   PetscUseTypeMethod(X,dotvec,y,m);
    169:   PetscCall(PetscLogEventEnd(BV_DotVec,X,y,0,0));
    170:   PetscFunctionReturn(PETSC_SUCCESS);
    171: }

    173: /*@
    174:    BVDotVecBegin - Starts a split phase dot product computation.

    176:    Input Parameters:
    177: +  X - basis vectors
    178: .  y - a vector
    179: -  m - an array where the result will go (can be NULL)

    181:    Note:
    182:    Each call to BVDotVecBegin() should be paired with a call to BVDotVecEnd().

    184:    Level: advanced

    186: .seealso: BVDotVecEnd(), BVDotVec()
    187: @*/
    188: PetscErrorCode BVDotVecBegin(BV X,Vec y,PetscScalar *m)
    189: {
    190:   PetscInt            i,n,nv;
    191:   PetscSplitReduction *sr;
    192:   MPI_Comm            comm;

    194:   PetscFunctionBegin;
    198:   BVCheckSizes(X,1);
    200:   PetscCheckSameTypeAndComm(X,1,y,2);

    202:   PetscCall(VecGetLocalSize(y,&n));
    203:   PetscCheck(X->n==n,PetscObjectComm((PetscObject)X),PETSC_ERR_ARG_INCOMP,"Mismatching local dimension X %" PetscInt_FMT ", y %" PetscInt_FMT,X->n,n);

    205:   if (X->ops->dotvec_begin) PetscUseTypeMethod(X,dotvec_begin,y,m);
    206:   else {
    207:     BVCheckOp(X,1,dotvec_local);
    208:     nv = X->k-X->l;
    209:     PetscCall(PetscObjectGetComm((PetscObject)X,&comm));
    210:     PetscCall(PetscSplitReductionGet(comm,&sr));
    211:     PetscCheck(sr->state==STATE_BEGIN,PetscObjectComm((PetscObject)X),PETSC_ERR_ORDER,"Called before all VecxxxEnd() called");
    212:     for (i=0;i<nv;i++) {
    213:       if (sr->numopsbegin+i >= sr->maxops) PetscCall(PetscSplitReductionExtend(sr));
    214:       sr->reducetype[sr->numopsbegin+i] = PETSC_SR_REDUCE_SUM;
    215:       sr->invecs[sr->numopsbegin+i]     = (void*)X;
    216:     }
    217:     PetscCall(PetscLogEventBegin(BV_DotVec,X,y,0,0));
    218:     PetscUseTypeMethod(X,dotvec_local,y,sr->lvalues+sr->numopsbegin);
    219:     sr->numopsbegin += nv;
    220:     PetscCall(PetscLogEventEnd(BV_DotVec,X,y,0,0));
    221:   }
    222:   PetscFunctionReturn(PETSC_SUCCESS);
    223: }

    225: /*@
    226:    BVDotVecEnd - Ends a split phase dot product computation.

    228:    Input Parameters:
    229: +  X - basis vectors
    230: .  y - a vector
    231: -  m - an array where the result will go

    233:    Note:
    234:    Each call to BVDotVecBegin() should be paired with a call to BVDotVecEnd().

    236:    Level: advanced

    238: .seealso: BVDotVecBegin(), BVDotVec()
    239: @*/
    240: PetscErrorCode BVDotVecEnd(BV X,Vec y,PetscScalar *m)
    241: {
    242:   PetscInt            i,nv;
    243:   PetscSplitReduction *sr;
    244:   MPI_Comm            comm;

    246:   PetscFunctionBegin;
    249:   BVCheckSizes(X,1);

    251:   if (X->ops->dotvec_end) PetscUseTypeMethod(X,dotvec_end,y,m);
    252:   else {
    253:     nv = X->k-X->l;
    254:     PetscCall(PetscObjectGetComm((PetscObject)X,&comm));
    255:     PetscCall(PetscSplitReductionGet(comm,&sr));
    256:     PetscCall(PetscSplitReductionEnd(sr));

    258:     PetscCheck(sr->numopsend<sr->numopsbegin,PetscObjectComm((PetscObject)X),PETSC_ERR_ARG_WRONGSTATE,"Called VecxxxEnd() more times than VecxxxBegin()");
    259:     PetscCheck((void*)X==sr->invecs[sr->numopsend],PetscObjectComm((PetscObject)X),PETSC_ERR_ARG_WRONGSTATE,"Called BVxxxEnd() in a different order or with a different BV than BVxxxBegin()");
    260:     PetscCheck(sr->reducetype[sr->numopsend]==PETSC_SR_REDUCE_SUM,PetscObjectComm((PetscObject)X),PETSC_ERR_ARG_WRONGSTATE,"Wrong type of reduction");
    261:     for (i=0;i<nv;i++) m[i] = sr->gvalues[sr->numopsend++];

    263:     /* Finished getting all the results so reset to no outstanding requests */
    264:     if (sr->numopsend == sr->numopsbegin) {
    265:       sr->state       = STATE_BEGIN;
    266:       sr->numopsend   = 0;
    267:       sr->numopsbegin = 0;
    268:     }
    269:   }
    270:   PetscFunctionReturn(PETSC_SUCCESS);
    271: }

    273: /*@
    274:    BVDotColumn - Computes multiple dot products of a column against all the
    275:    previous columns of a BV.

    277:    Collective

    279:    Input Parameters:
    280: +  X - basis vectors
    281: -  j - the column index

    283:    Output Parameter:
    284: .  q - an array where the result must be placed

    286:    Notes:
    287:    This operation is equivalent to BVDotVec() but it uses column j of X
    288:    rather than taking a Vec as an argument. The number of active columns of
    289:    X is set to j before the computation, and restored afterwards.
    290:    If X has leading columns specified, then these columns do not participate
    291:    in the computation. Therefore, the length of array q must be equal to j
    292:    minus the number of leading columns.

    294:    Developer Notes:
    295:    If q is NULL, then the result is written in position nc+l of the internal
    296:    buffer vector, see BVGetBufferVec().

    298:    Level: advanced

    300: .seealso: BVDot(), BVDotVec(), BVSetActiveColumns(), BVSetMatrix()
    301: @*/
    302: PetscErrorCode BVDotColumn(BV X,PetscInt j,PetscScalar *q)
    303: {
    304:   PetscInt       ksave;
    305:   Vec            y;

    307:   PetscFunctionBegin;
    311:   BVCheckSizes(X,1);
    312:   BVCheckOp(X,1,dotvec);

    314:   PetscCheck(j>=0,PetscObjectComm((PetscObject)X),PETSC_ERR_ARG_OUTOFRANGE,"Index j must be non-negative");
    315:   PetscCheck(j<X->m,PetscObjectComm((PetscObject)X),PETSC_ERR_ARG_OUTOFRANGE,"Index j=%" PetscInt_FMT " but BV only has %" PetscInt_FMT " columns",j,X->m);

    317:   PetscCall(PetscLogEventBegin(BV_DotVec,X,0,0,0));
    318:   ksave = X->k;
    319:   X->k = j;
    320:   if (!q && !X->buffer) PetscCall(BVGetBufferVec(X,&X->buffer));
    321:   PetscCall(BVGetColumn(X,j,&y));
    322:   PetscUseTypeMethod(X,dotvec,y,q);
    323:   PetscCall(BVRestoreColumn(X,j,&y));
    324:   X->k = ksave;
    325:   PetscCall(PetscLogEventEnd(BV_DotVec,X,0,0,0));
    326:   PetscFunctionReturn(PETSC_SUCCESS);
    327: }

    329: /*@
    330:    BVDotColumnBegin - Starts a split phase dot product computation.

    332:    Input Parameters:
    333: +  X - basis vectors
    334: .  j - the column index
    335: -  m - an array where the result will go (can be NULL)

    337:    Note:
    338:    Each call to BVDotColumnBegin() should be paired with a call to BVDotColumnEnd().

    340:    Level: advanced

    342: .seealso: BVDotColumnEnd(), BVDotColumn()
    343: @*/
    344: PetscErrorCode BVDotColumnBegin(BV X,PetscInt j,PetscScalar *m)
    345: {
    346:   PetscInt            i,nv,ksave;
    347:   PetscSplitReduction *sr;
    348:   MPI_Comm            comm;
    349:   Vec                 y;

    351:   PetscFunctionBegin;
    355:   BVCheckSizes(X,1);

    357:   PetscCheck(j>=0,PetscObjectComm((PetscObject)X),PETSC_ERR_ARG_OUTOFRANGE,"Index j must be non-negative");
    358:   PetscCheck(j<X->m,PetscObjectComm((PetscObject)X),PETSC_ERR_ARG_OUTOFRANGE,"Index j=%" PetscInt_FMT " but BV only has %" PetscInt_FMT " columns",j,X->m);
    359:   ksave = X->k;
    360:   X->k = j;
    361:   PetscCall(BVGetColumn(X,j,&y));

    363:   if (X->ops->dotvec_begin) PetscUseTypeMethod(X,dotvec_begin,y,m);
    364:   else {
    365:     BVCheckOp(X,1,dotvec_local);
    366:     nv = X->k-X->l;
    367:     PetscCall(PetscObjectGetComm((PetscObject)X,&comm));
    368:     PetscCall(PetscSplitReductionGet(comm,&sr));
    369:     PetscCheck(sr->state==STATE_BEGIN,PetscObjectComm((PetscObject)X),PETSC_ERR_ORDER,"Called before all VecxxxEnd() called");
    370:     for (i=0;i<nv;i++) {
    371:       if (sr->numopsbegin+i >= sr->maxops) PetscCall(PetscSplitReductionExtend(sr));
    372:       sr->reducetype[sr->numopsbegin+i] = PETSC_SR_REDUCE_SUM;
    373:       sr->invecs[sr->numopsbegin+i]     = (void*)X;
    374:     }
    375:     PetscCall(PetscLogEventBegin(BV_DotVec,X,0,0,0));
    376:     PetscUseTypeMethod(X,dotvec_local,y,sr->lvalues+sr->numopsbegin);
    377:     sr->numopsbegin += nv;
    378:     PetscCall(PetscLogEventEnd(BV_DotVec,X,0,0,0));
    379:   }
    380:   PetscCall(BVRestoreColumn(X,j,&y));
    381:   X->k = ksave;
    382:   PetscFunctionReturn(PETSC_SUCCESS);
    383: }

    385: /*@
    386:    BVDotColumnEnd - Ends a split phase dot product computation.

    388:    Input Parameters:
    389: +  X - basis vectors
    390: .  j - the column index
    391: -  m - an array where the result will go

    393:    Notes:
    394:    Each call to BVDotColumnBegin() should be paired with a call to BVDotColumnEnd().

    396:    Level: advanced

    398: .seealso: BVDotColumnBegin(), BVDotColumn()
    399: @*/
    400: PetscErrorCode BVDotColumnEnd(BV X,PetscInt j,PetscScalar *m)
    401: {
    402:   PetscInt            i,nv,ksave;
    403:   PetscSplitReduction *sr;
    404:   MPI_Comm            comm;
    405:   Vec                 y;

    407:   PetscFunctionBegin;
    411:   BVCheckSizes(X,1);

    413:   PetscCheck(j>=0,PetscObjectComm((PetscObject)X),PETSC_ERR_ARG_OUTOFRANGE,"Index j must be non-negative");
    414:   PetscCheck(j<X->m,PetscObjectComm((PetscObject)X),PETSC_ERR_ARG_OUTOFRANGE,"Index j=%" PetscInt_FMT " but BV only has %" PetscInt_FMT " columns",j,X->m);
    415:   ksave = X->k;
    416:   X->k = j;

    418:   if (X->ops->dotvec_end) {
    419:     PetscCall(BVGetColumn(X,j,&y));
    420:     PetscUseTypeMethod(X,dotvec_end,y,m);
    421:     PetscCall(BVRestoreColumn(X,j,&y));
    422:   } else {
    423:     nv = X->k-X->l;
    424:     PetscCall(PetscObjectGetComm((PetscObject)X,&comm));
    425:     PetscCall(PetscSplitReductionGet(comm,&sr));
    426:     PetscCall(PetscSplitReductionEnd(sr));

    428:     PetscCheck(sr->numopsend<sr->numopsbegin,PetscObjectComm((PetscObject)X),PETSC_ERR_ARG_WRONGSTATE,"Called VecxxxEnd() more times than VecxxxBegin()");
    429:     PetscCheck((void*)X==sr->invecs[sr->numopsend],PetscObjectComm((PetscObject)X),PETSC_ERR_ARG_WRONGSTATE,"Called BVxxxEnd() in a different order or with a different BV than BVxxxBegin()");
    430:     PetscCheck(sr->reducetype[sr->numopsend]==PETSC_SR_REDUCE_SUM,PetscObjectComm((PetscObject)X),PETSC_ERR_ARG_WRONGSTATE,"Wrong type of reduction");
    431:     for (i=0;i<nv;i++) m[i] = sr->gvalues[sr->numopsend++];

    433:     /* Finished getting all the results so reset to no outstanding requests */
    434:     if (sr->numopsend == sr->numopsbegin) {
    435:       sr->state       = STATE_BEGIN;
    436:       sr->numopsend   = 0;
    437:       sr->numopsbegin = 0;
    438:     }
    439:   }
    440:   X->k = ksave;
    441:   PetscFunctionReturn(PETSC_SUCCESS);
    442: }

    444: static inline PetscErrorCode BVNorm_Private(BV bv,Vec z,NormType type,PetscReal *val)
    445: {
    446:   PetscScalar    p;

    448:   PetscFunctionBegin;
    449:   PetscCall(BV_IPMatMult(bv,z));
    450:   PetscCall(VecDot(bv->Bx,z,&p));
    451:   PetscCall(BV_SafeSqrt(bv,p,val));
    452:   PetscFunctionReturn(PETSC_SUCCESS);
    453: }

    455: static inline PetscErrorCode BVNorm_Begin_Private(BV bv,Vec z,NormType type,PetscReal *val)
    456: {
    457:   PetscScalar    p;

    459:   PetscFunctionBegin;
    460:   PetscCall(BV_IPMatMult(bv,z));
    461:   PetscCall(VecDotBegin(bv->Bx,z,&p));
    462:   PetscFunctionReturn(PETSC_SUCCESS);
    463: }

    465: static inline PetscErrorCode BVNorm_End_Private(BV bv,Vec z,NormType type,PetscReal *val)
    466: {
    467:   PetscScalar    p;

    469:   PetscFunctionBegin;
    470:   PetscCall(VecDotEnd(bv->Bx,z,&p));
    471:   PetscCall(BV_SafeSqrt(bv,p,val));
    472:   PetscFunctionReturn(PETSC_SUCCESS);
    473: }

    475: /*@
    476:    BVNorm - Computes the matrix norm of the BV.

    478:    Collective

    480:    Input Parameters:
    481: +  bv   - basis vectors
    482: -  type - the norm type

    484:    Output Parameter:
    485: .  val  - the norm

    487:    Notes:
    488:    All active columns (except the leading ones) are considered as a matrix.
    489:    The allowed norms are NORM_1, NORM_FROBENIUS, and NORM_INFINITY.

    491:    This operation fails if a non-standard inner product has been
    492:    specified with BVSetMatrix().

    494:    Level: intermediate

    496: .seealso: BVNormVec(), BVNormColumn(), BVNormalize(), BVSetActiveColumns(), BVSetMatrix()
    497: @*/
    498: PetscErrorCode BVNorm(BV bv,NormType type,PetscReal *val)
    499: {
    500:   PetscFunctionBegin;
    503:   PetscAssertPointer(val,3);
    505:   BVCheckSizes(bv,1);

    507:   PetscCheck(type!=NORM_2 && type!=NORM_1_AND_2,PetscObjectComm((PetscObject)bv),PETSC_ERR_SUP,"Requested norm not available");
    508:   PetscCheck(!bv->matrix,PetscObjectComm((PetscObject)bv),PETSC_ERR_SUP,"Matrix norm not available for non-standard inner product");

    510:   PetscCall(PetscLogEventBegin(BV_Norm,bv,0,0,0));
    511:   PetscUseTypeMethod(bv,norm,-1,type,val);
    512:   PetscCall(PetscLogEventEnd(BV_Norm,bv,0,0,0));
    513:   PetscFunctionReturn(PETSC_SUCCESS);
    514: }

    516: /*@
    517:    BVNormVec - Computes the norm of a given vector.

    519:    Collective

    521:    Input Parameters:
    522: +  bv   - basis vectors
    523: .  v    - the vector
    524: -  type - the norm type

    526:    Output Parameter:
    527: .  val  - the norm

    529:    Notes:
    530:    This is the analogue of BVNormColumn() but for a vector that is not in the BV.
    531:    If a non-standard inner product has been specified with BVSetMatrix(),
    532:    then the returned value is sqrt(v'*B*v), where B is the inner product
    533:    matrix (argument 'type' is ignored). Otherwise, VecNorm() is called.

    535:    Level: developer

    537: .seealso: BVNorm(), BVNormColumn(), BVSetMatrix()
    538: @*/
    539: PetscErrorCode BVNormVec(BV bv,Vec v,NormType type,PetscReal *val)
    540: {
    541:   PetscInt       n;

    543:   PetscFunctionBegin;
    547:   PetscAssertPointer(val,4);
    549:   BVCheckSizes(bv,1);
    551:   PetscCheckSameComm(bv,1,v,2);

    553:   PetscCheck(type!=NORM_1_AND_2 || bv->matrix,PetscObjectComm((PetscObject)bv),PETSC_ERR_SUP,"Requested norm not available");

    555:   PetscCall(PetscLogEventBegin(BV_NormVec,bv,0,0,0));
    556:   if (bv->matrix) { /* non-standard inner product */
    557:     PetscCall(VecGetLocalSize(v,&n));
    558:     PetscCheck(bv->n==n,PetscObjectComm((PetscObject)bv),PETSC_ERR_ARG_INCOMP,"Mismatching local dimension bv %" PetscInt_FMT ", v %" PetscInt_FMT,bv->n,n);
    559:     PetscCall(BVNorm_Private(bv,v,type,val));
    560:   } else PetscCall(VecNorm(v,type,val));
    561:   PetscCall(PetscLogEventEnd(BV_NormVec,bv,0,0,0));
    562:   PetscFunctionReturn(PETSC_SUCCESS);
    563: }

    565: /*@
    566:    BVNormVecBegin - Starts a split phase norm computation.

    568:    Input Parameters:
    569: +  bv   - basis vectors
    570: .  v    - the vector
    571: .  type - the norm type
    572: -  val  - the norm

    574:    Note:
    575:    Each call to BVNormVecBegin() should be paired with a call to BVNormVecEnd().

    577:    Level: advanced

    579: .seealso: BVNormVecEnd(), BVNormVec()
    580: @*/
    581: PetscErrorCode BVNormVecBegin(BV bv,Vec v,NormType type,PetscReal *val)
    582: {
    583:   PetscInt       n;

    585:   PetscFunctionBegin;
    589:   PetscAssertPointer(val,4);
    591:   BVCheckSizes(bv,1);
    593:   PetscCheckSameTypeAndComm(bv,1,v,2);

    595:   PetscCheck(type!=NORM_1_AND_2 || bv->matrix,PetscObjectComm((PetscObject)bv),PETSC_ERR_SUP,"Requested norm not available");

    597:   PetscCall(PetscLogEventBegin(BV_NormVec,bv,0,0,0));
    598:   if (bv->matrix) { /* non-standard inner product */
    599:     PetscCall(VecGetLocalSize(v,&n));
    600:     PetscCheck(bv->n==n,PetscObjectComm((PetscObject)bv),PETSC_ERR_ARG_INCOMP,"Mismatching local dimension bv %" PetscInt_FMT ", v %" PetscInt_FMT,bv->n,n);
    601:     PetscCall(BVNorm_Begin_Private(bv,v,type,val));
    602:   } else PetscCall(VecNormBegin(v,type,val));
    603:   PetscCall(PetscLogEventEnd(BV_NormVec,bv,0,0,0));
    604:   PetscFunctionReturn(PETSC_SUCCESS);
    605: }

    607: /*@
    608:    BVNormVecEnd - Ends a split phase norm computation.

    610:    Input Parameters:
    611: +  bv   - basis vectors
    612: .  v    - the vector
    613: .  type - the norm type
    614: -  val  - the norm

    616:    Note:
    617:    Each call to BVNormVecBegin() should be paired with a call to BVNormVecEnd().

    619:    Level: advanced

    621: .seealso: BVNormVecBegin(), BVNormVec()
    622: @*/
    623: PetscErrorCode BVNormVecEnd(BV bv,Vec v,NormType type,PetscReal *val)
    624: {
    625:   PetscFunctionBegin;
    628:   PetscAssertPointer(val,4);
    630:   BVCheckSizes(bv,1);

    632:   PetscCheck(type!=NORM_1_AND_2,PetscObjectComm((PetscObject)bv),PETSC_ERR_SUP,"Requested norm not available");

    634:   if (bv->matrix) PetscCall(BVNorm_End_Private(bv,v,type,val));  /* non-standard inner product */
    635:   else PetscCall(VecNormEnd(v,type,val));
    636:   PetscFunctionReturn(PETSC_SUCCESS);
    637: }

    639: /*@
    640:    BVNormColumn - Computes the vector norm of a selected column.

    642:    Collective

    644:    Input Parameters:
    645: +  bv   - basis vectors
    646: .  j    - column number to be used
    647: -  type - the norm type

    649:    Output Parameter:
    650: .  val  - the norm

    652:    Notes:
    653:    The norm of V[j] is computed (NORM_1, NORM_2, or NORM_INFINITY).
    654:    If a non-standard inner product has been specified with BVSetMatrix(),
    655:    then the returned value is sqrt(V[j]'*B*V[j]),
    656:    where B is the inner product matrix (argument 'type' is ignored).

    658:    Level: intermediate

    660: .seealso: BVNorm(), BVNormVec(), BVNormalize(), BVSetActiveColumns(), BVSetMatrix()
    661: @*/
    662: PetscErrorCode BVNormColumn(BV bv,PetscInt j,NormType type,PetscReal *val)
    663: {
    664:   Vec            z;

    666:   PetscFunctionBegin;
    670:   PetscAssertPointer(val,4);
    672:   BVCheckSizes(bv,1);

    674:   PetscCheck(j>=0 && j<bv->m,PetscObjectComm((PetscObject)bv),PETSC_ERR_ARG_OUTOFRANGE,"Argument j has wrong value %" PetscInt_FMT ", the number of columns is %" PetscInt_FMT,j,bv->m);
    675:   PetscCheck(type!=NORM_1_AND_2 || bv->matrix,PetscObjectComm((PetscObject)bv),PETSC_ERR_SUP,"Requested norm not available");

    677:   PetscCall(PetscLogEventBegin(BV_NormVec,bv,0,0,0));
    678:   if (bv->matrix) { /* non-standard inner product */
    679:     PetscCall(BVGetColumn(bv,j,&z));
    680:     PetscCall(BVNorm_Private(bv,z,type,val));
    681:     PetscCall(BVRestoreColumn(bv,j,&z));
    682:   } else PetscUseTypeMethod(bv,norm,j,type,val);
    683:   PetscCall(PetscLogEventEnd(BV_NormVec,bv,0,0,0));
    684:   PetscFunctionReturn(PETSC_SUCCESS);
    685: }

    687: /*@
    688:    BVNormColumnBegin - Starts a split phase norm computation.

    690:    Input Parameters:
    691: +  bv   - basis vectors
    692: .  j    - column number to be used
    693: .  type - the norm type
    694: -  val  - the norm

    696:    Note:
    697:    Each call to BVNormColumnBegin() should be paired with a call to BVNormColumnEnd().

    699:    Level: advanced

    701: .seealso: BVNormColumnEnd(), BVNormColumn()
    702: @*/
    703: PetscErrorCode BVNormColumnBegin(BV bv,PetscInt j,NormType type,PetscReal *val)
    704: {
    705:   PetscSplitReduction *sr;
    706:   PetscReal           lresult;
    707:   MPI_Comm            comm;
    708:   Vec                 z;

    710:   PetscFunctionBegin;
    714:   PetscAssertPointer(val,4);
    716:   BVCheckSizes(bv,1);

    718:   PetscCheck(j>=0 && j<bv->m,PetscObjectComm((PetscObject)bv),PETSC_ERR_ARG_OUTOFRANGE,"Argument j has wrong value %" PetscInt_FMT ", the number of columns is %" PetscInt_FMT,j,bv->m);
    719:   PetscCheck(type!=NORM_1_AND_2 || bv->matrix,PetscObjectComm((PetscObject)bv),PETSC_ERR_SUP,"Requested norm not available");

    721:   PetscCall(PetscLogEventBegin(BV_NormVec,bv,0,0,0));
    722:   PetscCall(BVGetColumn(bv,j,&z));
    723:   if (bv->matrix) PetscCall(BVNorm_Begin_Private(bv,z,type,val)); /* non-standard inner product */
    724:   else if (bv->ops->norm_begin) PetscUseTypeMethod(bv,norm_begin,j,type,val);
    725:   else {
    726:     BVCheckOp(bv,1,norm_local);
    727:     PetscCall(PetscObjectGetComm((PetscObject)z,&comm));
    728:     PetscCall(PetscSplitReductionGet(comm,&sr));
    729:     PetscCheck(sr->state==STATE_BEGIN,PetscObjectComm((PetscObject)bv),PETSC_ERR_ORDER,"Called before all VecxxxEnd() called");
    730:     if (sr->numopsbegin >= sr->maxops) PetscCall(PetscSplitReductionExtend(sr));
    731:     sr->invecs[sr->numopsbegin] = (void*)bv;
    732:     PetscUseTypeMethod(bv,norm_local,j,type,&lresult);
    733:     if (type == NORM_2) lresult = lresult*lresult;
    734:     if (type == NORM_MAX) sr->reducetype[sr->numopsbegin] = PETSC_SR_REDUCE_MAX;
    735:     else sr->reducetype[sr->numopsbegin] = PETSC_SR_REDUCE_SUM;
    736:     sr->lvalues[sr->numopsbegin++] = lresult;
    737:   }
    738:   PetscCall(BVRestoreColumn(bv,j,&z));
    739:   PetscCall(PetscLogEventEnd(BV_NormVec,bv,0,0,0));
    740:   PetscFunctionReturn(PETSC_SUCCESS);
    741: }

    743: /*@
    744:    BVNormColumnEnd - Ends a split phase norm computation.

    746:    Input Parameters:
    747: +  bv   - basis vectors
    748: .  j    - column number to be used
    749: .  type - the norm type
    750: -  val  - the norm

    752:    Note:
    753:    Each call to BVNormColumnBegin() should be paired with a call to BVNormColumnEnd().

    755:    Level: advanced

    757: .seealso: BVNormColumnBegin(), BVNormColumn()
    758: @*/
    759: PetscErrorCode BVNormColumnEnd(BV bv,PetscInt j,NormType type,PetscReal *val)
    760: {
    761:   PetscSplitReduction *sr;
    762:   MPI_Comm            comm;
    763:   Vec                 z;

    765:   PetscFunctionBegin;
    769:   PetscAssertPointer(val,4);
    771:   BVCheckSizes(bv,1);

    773:   PetscCheck(type!=NORM_1_AND_2,PetscObjectComm((PetscObject)bv),PETSC_ERR_SUP,"Requested norm not available");

    775:   PetscCall(BVGetColumn(bv,j,&z));
    776:   if (bv->matrix) PetscCall(BVNorm_End_Private(bv,z,type,val)); /* non-standard inner product */
    777:   else if (bv->ops->norm_end) PetscUseTypeMethod(bv,norm_end,j,type,val);
    778:   else {
    779:     PetscCall(PetscObjectGetComm((PetscObject)z,&comm));
    780:     PetscCall(PetscSplitReductionGet(comm,&sr));
    781:     PetscCall(PetscSplitReductionEnd(sr));

    783:     PetscCheck(sr->numopsend<sr->numopsbegin,PetscObjectComm((PetscObject)bv),PETSC_ERR_ARG_WRONGSTATE,"Called VecxxxEnd() more times then VecxxxBegin()");
    784:     PetscCheck((void*)bv==sr->invecs[sr->numopsend],PetscObjectComm((PetscObject)bv),PETSC_ERR_ARG_WRONGSTATE,"Called VecxxxEnd() in a different order or with a different vector than VecxxxBegin()");
    785:     PetscCheck(sr->reducetype[sr->numopsend]==PETSC_SR_REDUCE_MAX || type!=NORM_MAX,PetscObjectComm((PetscObject)bv),PETSC_ERR_ARG_WRONGSTATE,"Called BVNormEnd(,NORM_MAX,) on a reduction started with VecDotBegin() or NORM_1 or NORM_2");
    786:     *val = PetscRealPart(sr->gvalues[sr->numopsend++]);
    787:     if (type == NORM_2) *val = PetscSqrtReal(*val);
    788:     if (sr->numopsend == sr->numopsbegin) {
    789:       sr->state       = STATE_BEGIN;
    790:       sr->numopsend   = 0;
    791:       sr->numopsbegin = 0;
    792:     }
    793:   }
    794:   PetscCall(BVRestoreColumn(bv,j,&z));
    795:   PetscFunctionReturn(PETSC_SUCCESS);
    796: }

    798: /*@
    799:    BVNormalize - Normalize all columns (starting from the leading ones).

    801:    Collective

    803:    Input Parameters:
    804: +  bv   - basis vectors
    805: -  eigi - (optional) imaginary parts of eigenvalues

    807:    Notes:
    808:    On output, all columns will have unit norm. The normalization is done with
    809:    respect to the 2-norm, or to the B-norm if a non-standard inner product has
    810:    been specified with BVSetMatrix(), see BVNormColumn().

    812:    If the optional argument eigi is passed (taken into account only in real
    813:    scalars) it is interpreted as the imaginary parts of the eigenvalues and
    814:    the BV is supposed to contain the corresponding eigenvectors. Suppose the
    815:    first three values are eigi = { 0, alpha, -alpha }, then the first column
    816:    is normalized as usual, but the second and third ones are normalized assuming
    817:    that they contain the real and imaginary parts of a complex conjugate pair of
    818:    eigenvectors.

    820:    If eigi is passed, the inner-product matrix is ignored.

    822:    If there are leading columns, they are not modified (are assumed to be already
    823:    normalized).

    825:    Level: intermediate

    827: .seealso: BVNormColumn()
    828: @*/
    829: PetscErrorCode BVNormalize(BV bv,PetscScalar *eigi)
    830: {
    831:   PetscReal      norm;
    832:   PetscInt       i;

    834:   PetscFunctionBegin;
    837:   BVCheckSizes(bv,1);

    839:   PetscCall(PetscLogEventBegin(BV_Normalize,bv,0,0,0));
    840:   if (bv->matrix && !eigi) {
    841:     for (i=bv->l;i<bv->k;i++) {
    842:       PetscCall(BVNormColumn(bv,i,NORM_2,&norm));
    843:       PetscCall(BVScaleColumn(bv,i,1.0/norm));
    844:     }
    845:   } else PetscTryTypeMethod(bv,normalize,eigi);
    846:   PetscCall(PetscLogEventEnd(BV_Normalize,bv,0,0,0));
    847:   PetscCall(PetscObjectStateIncrease((PetscObject)bv));
    848:   PetscFunctionReturn(PETSC_SUCCESS);
    849: }

    851: /*
    852:   Compute Y^H*A*X: right part column by column (with MatMult) and bottom
    853:   part row by row (with MatMultHermitianTranspose); result placed in marray[*,ldm]
    854: */
    855: static inline PetscErrorCode BVMatProject_Vec(BV X,Mat A,BV Y,PetscScalar *marray,PetscInt ldm,PetscBool symm)
    856: {
    857:   PetscInt       i,j,lx,ly,kx,ky,ulim;
    858:   Vec            z,f;

    860:   PetscFunctionBegin;
    861:   lx = X->l; kx = X->k;
    862:   ly = Y->l; ky = Y->k;
    863:   PetscCall(BVCreateVec(X,&f));
    864:   BVCheckOp(Y,3,dotvec);
    865:   for (j=lx;j<kx;j++) {
    866:     PetscCall(BVGetColumn(X,j,&z));
    867:     PetscCall(MatMult(A,z,f));
    868:     PetscCall(BVRestoreColumn(X,j,&z));
    869:     ulim = PetscMin(ly+(j-lx)+1,ky);
    870:     Y->l = 0; Y->k = ulim;
    871:     PetscUseTypeMethod(Y,dotvec,f,marray+j*ldm);
    872:     if (symm) {
    873:       for (i=0;i<j;i++) marray[j+i*ldm] = PetscConj(marray[i+j*ldm]);
    874:     }
    875:   }
    876:   if (!symm) {
    877:     BVCheckOp(X,1,dotvec);
    878:     PetscCall(BV_AllocateCoeffs(Y));
    879:     for (j=ly;j<ky;j++) {
    880:       PetscCall(BVGetColumn(Y,j,&z));
    881:       PetscCall(MatMultHermitianTranspose(A,z,f));
    882:       PetscCall(BVRestoreColumn(Y,j,&z));
    883:       ulim = PetscMin(lx+(j-ly),kx);
    884:       X->l = 0; X->k = ulim;
    885:       PetscUseTypeMethod(X,dotvec,f,Y->h);
    886:       for (i=0;i<ulim;i++) marray[j+i*ldm] = PetscConj(Y->h[i]);
    887:     }
    888:   }
    889:   PetscCall(VecDestroy(&f));
    890:   X->l = lx; X->k = kx;
    891:   Y->l = ly; Y->k = ky;
    892:   PetscFunctionReturn(PETSC_SUCCESS);
    893: }

    895: /*
    896:   Compute Y^H*A*X= [   --   | Y0'*W1 ]
    897:                    [ Y1'*W0 | Y1'*W1 ]
    898:   Allocates auxiliary BV to store the result of A*X, then one BVDot
    899:   call for top-right part and another one for bottom part;
    900:   result placed in marray[*,ldm]
    901: */
    902: static inline PetscErrorCode BVMatProject_MatMult(BV X,Mat A,BV Y,PetscScalar *marray,PetscInt ldm)
    903: {
    904:   PetscInt          j,lx,ly,kx,ky;
    905:   const PetscScalar *harray;
    906:   Mat               H;
    907:   BV                W;

    909:   PetscFunctionBegin;
    910:   lx = X->l; kx = X->k;
    911:   ly = Y->l; ky = Y->k;
    912:   PetscCall(BVDuplicate(X,&W));
    913:   X->l = 0; X->k = kx;
    914:   W->l = 0; W->k = kx;
    915:   PetscCall(BVMatMult(X,A,W));

    917:   /* top-right part, Y0'*AX1 */
    918:   if (ly>0 && lx<kx) {
    919:     PetscCall(MatCreateSeqDense(PETSC_COMM_SELF,ly,kx,NULL,&H));
    920:     W->l = lx; W->k = kx;
    921:     Y->l = 0;  Y->k = ly;
    922:     PetscCall(BVDot(W,Y,H));
    923:     PetscCall(MatDenseGetArrayRead(H,&harray));
    924:     for (j=lx;j<kx;j++) PetscCall(PetscArraycpy(marray+j*ldm,harray+j*ly,ly));
    925:     PetscCall(MatDenseRestoreArrayRead(H,&harray));
    926:     PetscCall(MatDestroy(&H));
    927:   }

    929:   /* bottom part, Y1'*AX */
    930:   if (kx>0 && ly<ky) {
    931:     PetscCall(MatCreateSeqDense(PETSC_COMM_SELF,ky,kx,NULL,&H));
    932:     W->l = 0;  W->k = kx;
    933:     Y->l = ly; Y->k = ky;
    934:     PetscCall(BVDot(W,Y,H));
    935:     PetscCall(MatDenseGetArrayRead(H,&harray));
    936:     for (j=0;j<kx;j++) PetscCall(PetscArraycpy(marray+j*ldm+ly,harray+j*ky+ly,ky-ly));
    937:     PetscCall(MatDenseRestoreArrayRead(H,&harray));
    938:     PetscCall(MatDestroy(&H));
    939:   }
    940:   PetscCall(BVDestroy(&W));
    941:   X->l = lx; X->k = kx;
    942:   Y->l = ly; Y->k = ky;
    943:   PetscFunctionReturn(PETSC_SUCCESS);
    944: }

    946: /*
    947:   Compute Y^H*A*X= [   --   | Y0'*W1 ]
    948:                    [ Y1'*W0 | Y1'*W1 ]
    949:   First stage: allocate auxiliary BV to store A*X1, one BVDot for right part;
    950:   Second stage: resize BV to accommodate A'*Y1, then call BVDot for transpose of
    951:   bottom-left part; result placed in marray[*,ldm]
    952: */
    953: static inline PetscErrorCode BVMatProject_MatMult_2(BV X,Mat A,BV Y,PetscScalar *marray,PetscInt ldm,PetscBool symm)
    954: {
    955:   PetscInt          i,j,lx,ly,kx,ky;
    956:   const PetscScalar *harray;
    957:   Mat               H;
    958:   BV                W;

    960:   PetscFunctionBegin;
    961:   lx = X->l; kx = X->k;
    962:   ly = Y->l; ky = Y->k;

    964:   /* right part, Y'*AX1 */
    965:   PetscCall(BVDuplicateResize(X,kx-lx,&W));
    966:   if (ky>0 && lx<kx) {
    967:     PetscCall(BVMatMult(X,A,W));
    968:     PetscCall(MatCreateSeqDense(PETSC_COMM_SELF,ky,kx-lx,NULL,&H));
    969:     Y->l = 0; Y->k = ky;
    970:     PetscCall(BVDot(W,Y,H));
    971:     PetscCall(MatDenseGetArrayRead(H,&harray));
    972:     for (j=lx;j<kx;j++) PetscCall(PetscArraycpy(marray+j*ldm,harray+(j-lx)*ky,ky));
    973:     PetscCall(MatDenseRestoreArrayRead(H,&harray));
    974:     PetscCall(MatDestroy(&H));
    975:   }

    977:   /* bottom-left part, Y1'*AX0 */
    978:   if (lx>0 && ly<ky) {
    979:     if (symm) {
    980:       /* do not compute, just copy symmetric elements */
    981:       for (i=ly;i<ky;i++) {
    982:         for (j=0;j<lx;j++) marray[i+j*ldm] = PetscConj(marray[j+i*ldm]);
    983:       }
    984:     } else {
    985:       PetscCall(BVResize(W,ky-ly,PETSC_FALSE));
    986:       Y->l = ly; Y->k = ky;
    987:       PetscCall(BVMatMultHermitianTranspose(Y,A,W));
    988:       PetscCall(MatCreateSeqDense(PETSC_COMM_SELF,lx,ky-ly,NULL,&H));
    989:       X->l = 0; X->k = lx;
    990:       PetscCall(BVDot(W,X,H));
    991:       PetscCall(MatDenseGetArrayRead(H,&harray));
    992:       for (i=0;i<ky-ly;i++) {
    993:         for (j=0;j<lx;j++) {
    994:           marray[i+j*ldm+ly] = PetscConj(harray[j+i*(ky-ly)]);
    995:         }
    996:       }
    997:       PetscCall(MatDenseRestoreArrayRead(H,&harray));
    998:       PetscCall(MatDestroy(&H));
    999:     }
    1000:   }
    1001:   PetscCall(BVDestroy(&W));
    1002:   X->l = lx; X->k = kx;
    1003:   Y->l = ly; Y->k = ky;
    1004:   PetscFunctionReturn(PETSC_SUCCESS);
    1005: }

    1007: /*
    1008:   Compute Y^H*X = [   --   | Y0'*X1 ]     (X contains A*X):
    1009:                   [ Y1'*X0 | Y1'*X1 ]
    1010:   one BVDot call for top-right part and another one for bottom part;
    1011:   result placed in marray[*,ldm]
    1012: */
    1013: static inline PetscErrorCode BVMatProject_Dot(BV X,BV Y,PetscScalar *marray,PetscInt ldm)
    1014: {
    1015:   PetscInt          j,lx,ly,kx,ky;
    1016:   const PetscScalar *harray;
    1017:   Mat               H;

    1019:   PetscFunctionBegin;
    1020:   lx = X->l; kx = X->k;
    1021:   ly = Y->l; ky = Y->k;

    1023:   /* top-right part, Y0'*X1 */
    1024:   if (ly>0 && lx<kx) {
    1025:     PetscCall(MatCreateSeqDense(PETSC_COMM_SELF,ly,kx,NULL,&H));
    1026:     X->l = lx; X->k = kx;
    1027:     Y->l = 0;  Y->k = ly;
    1028:     PetscCall(BVDot(X,Y,H));
    1029:     PetscCall(MatDenseGetArrayRead(H,&harray));
    1030:     for (j=lx;j<kx;j++) PetscCall(PetscArraycpy(marray+j*ldm,harray+j*ly,ly));
    1031:     PetscCall(MatDenseRestoreArrayRead(H,&harray));
    1032:     PetscCall(MatDestroy(&H));
    1033:   }

    1035:   /* bottom part, Y1'*X */
    1036:   if (kx>0 && ly<ky) {
    1037:     PetscCall(MatCreateSeqDense(PETSC_COMM_SELF,ky,kx,NULL,&H));
    1038:     X->l = 0;  X->k = kx;
    1039:     Y->l = ly; Y->k = ky;
    1040:     PetscCall(BVDot(X,Y,H));
    1041:     PetscCall(MatDenseGetArrayRead(H,&harray));
    1042:     for (j=0;j<kx;j++) PetscCall(PetscArraycpy(marray+j*ldm+ly,harray+j*ky+ly,ky-ly));
    1043:     PetscCall(MatDenseRestoreArrayRead(H,&harray));
    1044:     PetscCall(MatDestroy(&H));
    1045:   }
    1046:   X->l = lx; X->k = kx;
    1047:   Y->l = ly; Y->k = ky;
    1048:   PetscFunctionReturn(PETSC_SUCCESS);
    1049: }

    1051: /*@
    1052:    BVMatProject - Computes the projection of a matrix onto a subspace.

    1054:    Collective

    1056:    Input Parameters:
    1057: +  X - basis vectors
    1058: .  A - (optional) matrix to be projected
    1059: -  Y - left basis vectors, can be equal to X

    1061:    Output Parameter:
    1062: .  M - the resulting matrix

    1064:    Notes:
    1065:    If A=NULL, then it is assumed that X already contains A*X.

    1067:    This operation is similar to BVDot(), with important differences.
    1068:    The goal is to compute the matrix resulting from the orthogonal projection
    1069:    of A onto the subspace spanned by the columns of X, M = X^H*A*X, or the
    1070:    oblique projection onto X along Y, M = Y^H*A*X.

    1072:    A difference with respect to BVDot() is that the standard inner product
    1073:    is always used, regardless of a non-standard inner product being specified
    1074:    with BVSetMatrix().

    1076:    On entry, M must be a sequential dense Mat with dimensions ky,kx at least,
    1077:    where ky (resp. kx) is the number of active columns of Y (resp. X).
    1078:    Another difference with respect to BVDot() is that all entries of M are
    1079:    computed except the leading ly,lx part, where ly (resp. lx) is the
    1080:    number of leading columns of Y (resp. X). Hence, the leading columns of
    1081:    X and Y participate in the computation, as opposed to BVDot().
    1082:    The leading part of M is assumed to be already available from previous
    1083:    computations.

    1085:    In the orthogonal projection case, Y=X, some computation can be saved if
    1086:    A is real symmetric (or complex Hermitian). In order to exploit this
    1087:    property, the symmetry flag of A must be set with MatSetOption().

    1089:    Level: intermediate

    1091: .seealso: BVDot(), BVSetActiveColumns(), BVSetMatrix()
    1092: @*/
    1093: PetscErrorCode BVMatProject(BV X,Mat A,BV Y,Mat M)
    1094: {
    1095:   PetscBool      set,flg,symm=PETSC_FALSE;
    1096:   PetscInt       m,n,ldm;
    1097:   PetscScalar    *marray;
    1098:   Mat            Xmatrix,Ymatrix;
    1099:   PetscObjectId  idx,idy;

    1101:   PetscFunctionBegin;
    1107:   BVCheckSizes(X,1);
    1108:   if (A) {
    1110:     PetscCheckSameComm(X,1,A,2);
    1111:   }
    1113:   BVCheckSizes(Y,3);
    1115:   PetscCheckSameTypeAndComm(X,1,Y,3);
    1116:   PetscCheckTypeNames(M,MATSEQDENSE,MATSEQDENSECUDA);

    1118:   PetscCall(MatGetSize(M,&m,&n));
    1119:   PetscCall(MatDenseGetLDA(M,&ldm));
    1120:   PetscCheck(m>=Y->k,PetscObjectComm((PetscObject)X),PETSC_ERR_ARG_SIZ,"Matrix M has %" PetscInt_FMT " rows, should have at least %" PetscInt_FMT,m,Y->k);
    1121:   PetscCheck(n>=X->k,PetscObjectComm((PetscObject)X),PETSC_ERR_ARG_SIZ,"Matrix M has %" PetscInt_FMT " columns, should have at least %" PetscInt_FMT,n,X->k);
    1122:   PetscCheck(X->n==Y->n,PetscObjectComm((PetscObject)X),PETSC_ERR_ARG_INCOMP,"Mismatching local dimension X %" PetscInt_FMT ", Y %" PetscInt_FMT,X->n,Y->n);

    1124:   PetscCall(PetscLogEventBegin(BV_MatProject,X,A,Y,0));
    1125:   /* temporarily set standard inner product */
    1126:   Xmatrix = X->matrix;
    1127:   Ymatrix = Y->matrix;
    1128:   X->matrix = Y->matrix = NULL;

    1130:   PetscCall(PetscObjectGetId((PetscObject)X,&idx));
    1131:   PetscCall(PetscObjectGetId((PetscObject)Y,&idy));
    1132:   if (A && idx==idy) { /* check symmetry of M=X'AX */
    1133:     PetscCall(MatIsHermitianKnown(A,&set,&flg));
    1134:     symm = set? flg: PETSC_FALSE;
    1135:   }

    1137:   PetscCall(MatDenseGetArray(M,&marray));

    1139:   if (A) {
    1140:     if (X->vmm==BV_MATMULT_VECS) {
    1141:       /* perform computation column by column */
    1142:       PetscCall(BVMatProject_Vec(X,A,Y,marray,ldm,symm));
    1143:     } else {
    1144:       /* use BVMatMult, then BVDot */
    1145:       PetscCall(MatHasOperation(A,MATOP_MULT_TRANSPOSE,&flg));
    1146:       if (symm || (flg && X->l>=X->k/2 && Y->l>=Y->k/2)) PetscCall(BVMatProject_MatMult_2(X,A,Y,marray,ldm,symm));
    1147:       else PetscCall(BVMatProject_MatMult(X,A,Y,marray,ldm));
    1148:     }
    1149:   } else {
    1150:     /* use BVDot on subblocks */
    1151:     PetscCall(BVMatProject_Dot(X,Y,marray,ldm));
    1152:   }

    1154:   PetscCall(MatDenseRestoreArray(M,&marray));
    1155:   PetscCall(PetscLogEventEnd(BV_MatProject,X,A,Y,0));
    1156:   /* restore non-standard inner product */
    1157:   X->matrix = Xmatrix;
    1158:   Y->matrix = Ymatrix;
    1159:   PetscFunctionReturn(PETSC_SUCCESS);
    1160: }