Date: 2026-03-31T13:23:11+00:00

Actual source code: bvlapack.c

      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 private kernels that use the LAPACK
     12: */

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

     17: /*
     18:     Reduction operation to compute sqrt(x**2+y**2) when normalizing vectors
     19: */
     20: SLEPC_EXTERN void MPIAPI SlepcPythag(void *in,void *inout,PetscMPIInt *len,MPI_Datatype *datatype)
     21: {
     22:   PetscBLASInt i,n=*len;
     23:   PetscReal    *x = (PetscReal*)in,*y = (PetscReal*)inout;

     25:   PetscFunctionBegin;
     26:   if (PetscUnlikely(*datatype!=MPIU_REAL)) {
     27:     (void)(*PetscErrorPrintf)("Only implemented for MPIU_REAL data type");
     28:     MPI_Abort(PETSC_COMM_WORLD,1);
     29:   }
     30:   for (i=0;i<n;i++) y[i] = SlepcAbs(x[i],y[i]);
     31:   PetscFunctionReturnVoid();
     32: }

     34: /*
     35:     Compute ||A|| for an mxn matrix
     36: */
     37: PetscErrorCode BVNorm_LAPACK_Private(BV bv,PetscInt m_,PetscInt n_,const PetscScalar *A,PetscInt lda_,NormType type,PetscReal *nrm,PetscBool mpi)
     38: {
     39:   PetscBLASInt   m,n,lda,i,j;
     40:   PetscMPIInt    len;
     41:   PetscReal      lnrm,*rwork=NULL,*rwork2=NULL;

     43:   PetscFunctionBegin;
     44:   PetscCall(PetscFPTrapPush(PETSC_FP_TRAP_OFF));
     45:   PetscCall(PetscBLASIntCast(m_,&m));
     46:   PetscCall(PetscBLASIntCast(n_,&n));
     47:   PetscCall(PetscBLASIntCast(lda_,&lda));
     48:   if (type==NORM_FROBENIUS || type==NORM_2) {
     49:     lnrm = LAPACKlange_("F",&m,&n,(PetscScalar*)A,&lda,rwork);
     50:     if (mpi) PetscCallMPI(MPIU_Allreduce(&lnrm,nrm,1,MPIU_REAL,MPIU_LAPY2,PetscObjectComm((PetscObject)bv)));
     51:     else *nrm = lnrm;
     52:     PetscCall(PetscLogFlops(2.0*m*n));
     53:   } else if (type==NORM_1) {
     54:     if (mpi) {
     55:       PetscCall(BVAllocateWork_Private(bv,2*n_));
     56:       rwork = (PetscReal*)bv->work;
     57:       rwork2 = rwork+n_;
     58:       PetscCall(PetscArrayzero(rwork,n_));
     59:       PetscCall(PetscArrayzero(rwork2,n_));
     60:       for (j=0;j<n_;j++) {
     61:         for (i=0;i<m_;i++) {
     62:           rwork[j] += PetscAbsScalar(A[i+j*lda_]);
     63:         }
     64:       }
     65:       PetscCall(PetscMPIIntCast(n_,&len));
     66:       PetscCallMPI(MPIU_Allreduce(rwork,rwork2,len,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)bv)));
     67:       *nrm = 0.0;
     68:       for (j=0;j<n_;j++) if (rwork2[j] > *nrm) *nrm = rwork2[j];
     69:     } else {
     70:       *nrm = LAPACKlange_("O",&m,&n,(PetscScalar*)A,&lda,rwork);
     71:     }
     72:     PetscCall(PetscLogFlops(1.0*m*n));
     73:   } else if (type==NORM_INFINITY) {
     74:     PetscCall(BVAllocateWork_Private(bv,m_));
     75:     rwork = (PetscReal*)bv->work;
     76:     lnrm = LAPACKlange_("I",&m,&n,(PetscScalar*)A,&lda,rwork);
     77:     if (mpi) PetscCallMPI(MPIU_Allreduce(&lnrm,nrm,1,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)bv)));
     78:     else *nrm = lnrm;
     79:     PetscCall(PetscLogFlops(1.0*m*n));
     80:   }
     81:   PetscCall(PetscFPTrapPop());
     82:   PetscFunctionReturn(PETSC_SUCCESS);
     83: }

     85: /*
     86:     Normalize the columns of an mxn matrix A
     87: */
     88: PetscErrorCode BVNormalize_LAPACK_Private(BV bv,PetscInt m_,PetscInt n_,const PetscScalar *A,PetscInt lda_,PetscScalar *eigi,PetscBool mpi)
     89: {
     90:   PetscBLASInt   m,lda,j,k,info,zero=0;
     91:   PetscMPIInt    len;
     92:   PetscReal      *norms,*rwork=NULL,*rwork2=NULL,done=1.0;

     94:   PetscFunctionBegin;
     95:   PetscCall(PetscFPTrapPush(PETSC_FP_TRAP_OFF));
     96:   PetscCall(PetscBLASIntCast(m_,&m));
     97:   PetscCall(PetscBLASIntCast(lda_,&lda));
     98:   PetscCall(BVAllocateWork_Private(bv,2*n_));
     99:   rwork = (PetscReal*)bv->work;
    100:   rwork2 = rwork+n_;
    101:   /* compute local norms */
    102:   for (j=0;j<n_;j++) {
    103:     k = 1;
    104:     if (!PetscDefined(USE_COMPLEX) && eigi && eigi[j] != 0.0) k = 2;
    105:     rwork[j] = LAPACKlange_("F",&m,&k,(PetscScalar*)(A+j*lda_),&lda,rwork2);
    106:     if (k==2) { rwork[j+1] = rwork[j]; j++; }
    107:   }
    108:   /* reduction to get global norms */
    109:   if (mpi) {
    110:     PetscCall(PetscMPIIntCast(n_,&len));
    111:     PetscCall(PetscArrayzero(rwork2,n_));
    112:     PetscCallMPI(MPIU_Allreduce(rwork,rwork2,len,MPIU_REAL,MPIU_LAPY2,PetscObjectComm((PetscObject)bv)));
    113:     norms = rwork2;
    114:   } else norms = rwork;
    115:   /* scale columns */
    116:   for (j=0;j<n_;j++) {
    117:     k = 1;
    118: #if !defined(PETSC_USE_COMPLEX)
    119:     if (eigi && eigi[j] != 0.0) k = 2;
    120: #endif
    121:     PetscCallBLAS("LAPACKlascl",LAPACKlascl_("G",&zero,&zero,norms+j,&done,&m,&k,(PetscScalar*)(A+j*lda_),&lda,&info));
    122:     SlepcCheckLapackInfo("lascl",info);
    123:     if (k==2) j++;
    124:   }
    125:   PetscCall(PetscLogFlops(3.0*m*n_));
    126:   PetscCall(PetscFPTrapPop());
    127:   PetscFunctionReturn(PETSC_SUCCESS);
    128: }

    130: /*
    131:    Compute the upper Cholesky factor in R and its inverse in S.
    132:    If S == R then the inverse overwrites the Cholesky factor.
    133:  */
    134: PetscErrorCode BVMatCholInv_LAPACK_Private(BV bv,Mat R,Mat S)
    135: {
    136:   PetscInt       i,k,l,n,m,ld,lds;
    137:   PetscScalar    *pR,*pS;
    138:   PetscBLASInt   info,n_ = 0,m_ = 0,ld_,lds_;

    140:   PetscFunctionBegin;
    141:   l = bv->l;
    142:   k = bv->k;
    143:   PetscCall(MatGetSize(R,&m,NULL));
    144:   n = k-l;
    145:   PetscCall(PetscBLASIntCast(m,&m_));
    146:   PetscCall(PetscBLASIntCast(n,&n_));
    147:   ld  = m;
    148:   ld_ = m_;
    149:   PetscCall(MatDenseGetArray(R,&pR));

    151:   if (S==R) {
    152:     PetscCall(BVAllocateWork_Private(bv,m*k));
    153:     pS = bv->work;
    154:     lds = ld;
    155:     lds_ = ld_;
    156:   } else {
    157:     PetscCall(MatDenseGetArray(S,&pS));
    158:     PetscCall(MatGetSize(S,&lds,NULL));
    159:     PetscCall(PetscBLASIntCast(lds,&lds_));
    160:   }

    162:   /* save a copy of matrix in S */
    163:   for (i=l;i<k;i++) PetscCall(PetscArraycpy(pS+i*lds+l,pR+i*ld+l,n));

    165:   /* compute upper Cholesky factor in R */
    166:   PetscCall(PetscFPTrapPush(PETSC_FP_TRAP_OFF));
    167:   PetscCallBLAS("LAPACKpotrf",LAPACKpotrf_("U",&n_,pR+l*ld+l,&ld_,&info));
    168:   PetscCall(PetscLogFlops((1.0*n*n*n)/3.0));

    170:   if (info) {  /* LAPACKpotrf failed, retry on diagonally perturbed matrix */
    171:     for (i=l;i<k;i++) {
    172:       PetscCall(PetscArraycpy(pR+i*ld+l,pS+i*lds+l,n));
    173:       pR[i+i*ld] += 50.0*PETSC_MACHINE_EPSILON;
    174:     }
    175:     PetscCallBLAS("LAPACKpotrf",LAPACKpotrf_("U",&n_,pR+l*ld+l,&ld_,&info));
    176:     SlepcCheckLapackInfo("potrf",info);
    177:     PetscCall(PetscLogFlops((1.0*n*n*n)/3.0));
    178:   }

    180:   /* compute S = inv(R) */
    181:   if (S==R) {
    182:     PetscCallBLAS("LAPACKtrtri",LAPACKtrtri_("U","N",&n_,pR+l*ld+l,&ld_,&info));
    183:   } else {
    184:     PetscCall(PetscArrayzero(pS+l*lds,(k-l)*k));
    185:     for (i=l;i<k;i++) PetscCall(PetscArraycpy(pS+i*lds+l,pR+i*ld+l,n));
    186:     PetscCallBLAS("LAPACKtrtri",LAPACKtrtri_("U","N",&n_,pS+l*lds+l,&lds_,&info));
    187:   }
    188:   SlepcCheckLapackInfo("trtri",info);
    189:   PetscCall(PetscFPTrapPop());
    190:   PetscCall(PetscLogFlops(0.33*n*n*n));

    192:   /* Zero out entries below the diagonal */
    193:   for (i=l;i<k-1;i++) {
    194:     PetscCall(PetscArrayzero(pR+i*ld+i+1,(k-i-1)));
    195:     if (S!=R) PetscCall(PetscArrayzero(pS+i*lds+i+1,(k-i-1)));
    196:   }
    197:   PetscCall(MatDenseRestoreArray(R,&pR));
    198:   if (S!=R) PetscCall(MatDenseRestoreArray(S,&pS));
    199:   PetscFunctionReturn(PETSC_SUCCESS);
    200: }

    202: /*
    203:    Compute the inverse of an upper triangular matrix R, store it in S.
    204:    If S == R then the inverse overwrites R.
    205:  */
    206: PetscErrorCode BVMatTriInv_LAPACK_Private(BV bv,Mat R,Mat S)
    207: {
    208:   PetscInt       i,k,l,n,m,ld,lds;
    209:   PetscScalar    *pR,*pS;
    210:   PetscBLASInt   info,n_,m_ = 0,ld_,lds_;

    212:   PetscFunctionBegin;
    213:   l = bv->l;
    214:   k = bv->k;
    215:   PetscCall(MatGetSize(R,&m,NULL));
    216:   n = k-l;
    217:   PetscCall(PetscBLASIntCast(m,&m_));
    218:   PetscCall(PetscBLASIntCast(n,&n_));
    219:   ld  = m;
    220:   ld_ = m_;
    221:   PetscCall(MatDenseGetArray(R,&pR));

    223:   if (S==R) {
    224:     PetscCall(BVAllocateWork_Private(bv,m*k));
    225:     pS = bv->work;
    226:     lds = ld;
    227:     lds_ = ld_;
    228:   } else {
    229:     PetscCall(MatDenseGetArray(S,&pS));
    230:     PetscCall(MatGetSize(S,&lds,NULL));
    231:     PetscCall(PetscBLASIntCast(lds,&lds_));
    232:   }

    234:   /* compute S = inv(R) */
    235:   PetscCall(PetscFPTrapPush(PETSC_FP_TRAP_OFF));
    236:   if (S==R) {
    237:     PetscCallBLAS("LAPACKtrtri",LAPACKtrtri_("U","N",&n_,pR+l*ld+l,&ld_,&info));
    238:   } else {
    239:     PetscCall(PetscArrayzero(pS+l*lds,(k-l)*k));
    240:     for (i=l;i<k;i++) PetscCall(PetscArraycpy(pS+i*lds+l,pR+i*ld+l,n));
    241:     PetscCallBLAS("LAPACKtrtri",LAPACKtrtri_("U","N",&n_,pS+l*lds+l,&lds_,&info));
    242:   }
    243:   SlepcCheckLapackInfo("trtri",info);
    244:   PetscCall(PetscFPTrapPop());
    245:   PetscCall(PetscLogFlops(0.33*n*n*n));

    247:   PetscCall(MatDenseRestoreArray(R,&pR));
    248:   if (S!=R) PetscCall(MatDenseRestoreArray(S,&pS));
    249:   PetscFunctionReturn(PETSC_SUCCESS);
    250: }

    252: /*
    253:    Compute the matrix to be used for post-multiplying the basis in the SVQB
    254:    block orthogonalization method.
    255:    On input R = V'*V, on output S = D*U*Lambda^{-1/2} where (U,Lambda) is
    256:    the eigendecomposition of D*R*D with D=diag(R)^{-1/2}.
    257:    If S == R then the result overwrites R.
    258:  */
    259: PetscErrorCode BVMatSVQB_LAPACK_Private(BV bv,Mat R,Mat S)
    260: {
    261:   PetscInt       i,j,k,l,n,m,ld,lds;
    262:   PetscScalar    *pR,*pS,*D,*work,a;
    263:   PetscReal      *eig,dummy;
    264:   PetscBLASInt   info,lwork,n_,m_ = 0,ld_,lds_;
    265: #if defined(PETSC_USE_COMPLEX)
    266:   PetscReal      *rwork,rdummy;
    267: #endif

    269:   PetscFunctionBegin;
    270:   l = bv->l;
    271:   k = bv->k;
    272:   PetscCall(MatGetSize(R,&m,NULL));
    273:   PetscCall(MatDenseGetLDA(R,&ld));
    274:   n = k-l;
    275:   PetscCall(PetscBLASIntCast(m,&m_));
    276:   PetscCall(PetscBLASIntCast(n,&n_));
    277:   ld_ = m_;
    278:   PetscCall(MatDenseGetArray(R,&pR));

    280:   if (S==R) {
    281:     pS = pR;
    282:     lds = ld;
    283:     lds_ = ld_;
    284:   } else {
    285:     PetscCall(MatDenseGetArray(S,&pS));
    286:     PetscCall(MatDenseGetLDA(S,&lds));
    287:     PetscCall(PetscBLASIntCast(lds,&lds_));
    288:   }
    289:   PetscCall(PetscFPTrapPush(PETSC_FP_TRAP_OFF));

    291:   /* workspace query and memory allocation */
    292:   lwork = -1;
    293: #if defined(PETSC_USE_COMPLEX)
    294:   PetscCallBLAS("LAPACKsyev",LAPACKsyev_("V","L",&n_,pS,&lds_,&dummy,&a,&lwork,&rdummy,&info));
    295:   PetscCall(PetscBLASIntCast((PetscInt)PetscRealPart(a),&lwork));
    296:   PetscCall(PetscMalloc4(n,&eig,n,&D,lwork,&work,PetscMax(1,3*n-2),&rwork));
    297: #else
    298:   PetscCallBLAS("LAPACKsyev",LAPACKsyev_("V","L",&n_,pS,&lds_,&dummy,&a,&lwork,&info));
    299:   PetscCall(PetscBLASIntCast((PetscInt)a,&lwork));
    300:   PetscCall(PetscMalloc3(n,&eig,n,&D,lwork,&work));
    301: #endif

    303:   /* copy and scale matrix */
    304:   for (i=l;i<k;i++) D[i-l] = 1.0/PetscSqrtReal(PetscRealPart(pR[i+i*ld]));
    305:   for (i=l;i<k;i++) for (j=l;j<k;j++) pS[i+j*lds] = pR[i+j*ld]*D[i-l];
    306:   for (j=l;j<k;j++) for (i=l;i<k;i++) pS[i+j*lds] *= D[j-l];

    308:   /* compute eigendecomposition */
    309: #if defined(PETSC_USE_COMPLEX)
    310:   PetscCallBLAS("LAPACKsyev",LAPACKsyev_("V","L",&n_,pS+l*lds+l,&lds_,eig,work,&lwork,rwork,&info));
    311: #else
    312:   PetscCallBLAS("LAPACKsyev",LAPACKsyev_("V","L",&n_,pS+l*lds+l,&lds_,eig,work,&lwork,&info));
    313: #endif
    314:   SlepcCheckLapackInfo("syev",info);

    316:   if (S!=R) {   /* R = U' */
    317:     for (i=l;i<k;i++) for (j=l;j<k;j++) pR[i+j*ld] = pS[j+i*lds];
    318:   }

    320:   /* compute S = D*U*Lambda^{-1/2} */
    321:   for (i=l;i<k;i++) for (j=l;j<k;j++) pS[i+j*lds] *= D[i-l];
    322:   for (j=l;j<k;j++) for (i=l;i<k;i++) pS[i+j*lds] /= PetscSqrtReal(eig[j-l]);

    324:   if (S!=R) {   /* compute R = inv(S) = Lambda^{1/2}*U'/D */
    325:     for (i=l;i<k;i++) for (j=l;j<k;j++) pR[i+j*ld] *= PetscSqrtReal(eig[i-l]);
    326:     for (j=l;j<k;j++) for (i=l;i<k;i++) pR[i+j*ld] /= D[j-l];
    327:   }

    329: #if defined(PETSC_USE_COMPLEX)
    330:   PetscCall(PetscFree4(eig,D,work,rwork));
    331: #else
    332:   PetscCall(PetscFree3(eig,D,work));
    333: #endif
    334:   PetscCall(PetscLogFlops(9.0*n*n*n));
    335:   PetscCall(PetscFPTrapPop());

    337:   PetscCall(MatDenseRestoreArray(R,&pR));
    338:   if (S!=R) PetscCall(MatDenseRestoreArray(S,&pS));
    339:   PetscFunctionReturn(PETSC_SUCCESS);
    340: }

    342: /*
    343:     QR factorization of an mxn matrix via parallel TSQR
    344: */
    345: PetscErrorCode BVOrthogonalize_LAPACK_TSQR(BV bv,PetscInt m_,PetscInt n_,PetscScalar *Q,PetscInt ldq_,PetscScalar *R,PetscInt ldr)
    346: {
    347:   PetscInt       level,plevel,nlevels,lda,worklen;
    348:   PetscBLASInt   m,n,ldq,i,j,k,l,nb,sz,lwork,info;
    349:   PetscScalar    *tau,*work,*A=NULL,*QQ=NULL,*Qhalf,*C=NULL,one=1.0,zero=0.0;
    350:   PetscMPIInt    rank,size,count,stride,powtwo,s = 0;
    351:   MPI_Datatype   tmat;

    353:   PetscFunctionBegin;
    354:   PetscCall(PetscFPTrapPush(PETSC_FP_TRAP_OFF));
    355:   PetscCall(PetscBLASIntCast(m_,&m));
    356:   PetscCall(PetscBLASIntCast(n_,&n));
    357:   PetscCall(PetscBLASIntCast(ldq_,&ldq));
    358:   k  = PetscMin(m,n);
    359:   nb = 16;
    360:   lda = 2*n;
    361:   PetscCallMPI(MPI_Comm_size(PetscObjectComm((PetscObject)bv),&size));
    362:   PetscCallMPI(MPI_Comm_rank(PetscObjectComm((PetscObject)bv),&rank));
    363:   nlevels = (PetscInt)PetscCeilReal(PetscLog2Real((PetscReal)size));
    364:   PetscCall(PetscMPIIntCast(PetscPowInt(2,(PetscInt)PetscFloorReal(PetscLog2Real((PetscReal)size))),&powtwo));
    365:   worklen = n+n*nb;
    366:   if (nlevels) worklen += n*lda+n*lda*nlevels+n*lda;
    367:   PetscCall(BVAllocateWork_Private(bv,worklen));
    368:   tau  = bv->work;
    369:   work = bv->work+n;
    370:   PetscCall(PetscBLASIntCast(n*nb,&lwork));
    371:   if (nlevels) {
    372:     A  = bv->work+n+n*nb;
    373:     QQ = bv->work+n+n*nb+n*lda;
    374:     C  = bv->work+n+n*nb+n*lda+n*lda*nlevels;
    375:   }

    377:   /* Compute QR */
    378:   PetscCallBLAS("LAPACKgeqrf",LAPACKgeqrf_(&m,&n,Q,&ldq,tau,work,&lwork,&info));
    379:   SlepcCheckLapackInfo("geqrf",info);

    381:   /* Extract R */
    382:   if (R || nlevels) {
    383:     for (j=0;j<n;j++) {
    384:       for (i=0;i<=PetscMin(j,m-1);i++) {
    385:         if (nlevels) A[i+j*lda] = Q[i+j*ldq];
    386:         else R[i+j*ldr] = Q[i+j*ldq];
    387:       }
    388:       for (i=PetscMin(j,m-1)+1;i<n;i++) {
    389:         if (nlevels) A[i+j*lda] = 0.0;
    390:         else R[i+j*ldr] = 0.0;
    391:       }
    392:     }
    393:   }

    395:   /* Compute orthogonal matrix in Q */
    396:   PetscCallBLAS("LAPACKorgqr",LAPACKorgqr_(&m,&k,&k,Q,&ldq,tau,work,&lwork,&info));
    397:   SlepcCheckLapackInfo("orgqr",info);

    399:   if (nlevels) {

    401:     PetscCall(PetscMPIIntCast(n,&count));
    402:     PetscCall(PetscMPIIntCast(lda,&stride));
    403:     PetscCall(PetscBLASIntCast(lda,&l));
    404:     PetscCallMPI(MPI_Type_vector(count,count,stride,MPIU_SCALAR,&tmat));
    405:     PetscCallMPI(MPI_Type_commit(&tmat));

    407:     for (level=nlevels;level>=1;level--) {

    409:       plevel = PetscPowInt(2,level);
    410:       PetscCall(PetscMPIIntCast(plevel*PetscFloorReal(rank/(PetscReal)plevel)+(rank+PetscPowInt(2,level-1))%plevel,&s));

    412:       /* Stack triangular matrices */
    413:       if (rank<s && s<size) {  /* send top part, receive bottom part */
    414:         PetscCallMPI(MPI_Sendrecv(A,1,tmat,s,111,A+n,1,tmat,s,111,PetscObjectComm((PetscObject)bv),MPI_STATUS_IGNORE));
    415:       } else if (s<size) {  /* copy top to bottom, receive top part */
    416:         PetscCallMPI(MPI_Sendrecv(A,1,tmat,rank,111,A+n,1,tmat,rank,111,PetscObjectComm((PetscObject)bv),MPI_STATUS_IGNORE));
    417:         PetscCallMPI(MPI_Sendrecv(A+n,1,tmat,s,111,A,1,tmat,s,111,PetscObjectComm((PetscObject)bv),MPI_STATUS_IGNORE));
    418:       }
    419:       if (level<nlevels && size!=powtwo) {  /* for cases when size is not a power of 2 */
    420:         if (rank<size-powtwo) {  /* send bottom part */
    421:           PetscCallMPI(MPI_Send(A+n,1,tmat,rank+powtwo,111,PetscObjectComm((PetscObject)bv)));
    422:         } else if (rank>=powtwo) {  /* receive bottom part */
    423:           PetscCallMPI(MPI_Recv(A+n,1,tmat,rank-powtwo,111,PetscObjectComm((PetscObject)bv),MPI_STATUS_IGNORE));
    424:         }
    425:       }
    426:       /* Compute QR and build orthogonal matrix */
    427:       if (level<nlevels || (level==nlevels && s<size)) {
    428:         PetscCallBLAS("LAPACKgeqrf",LAPACKgeqrf_(&l,&n,A,&l,tau,work,&lwork,&info));
    429:         SlepcCheckLapackInfo("geqrf",info);
    430:         PetscCall(PetscArraycpy(QQ+(level-1)*n*lda,A,n*lda));
    431:         PetscCallBLAS("LAPACKorgqr",LAPACKorgqr_(&l,&n,&n,QQ+(level-1)*n*lda,&l,tau,work,&lwork,&info));
    432:         SlepcCheckLapackInfo("orgqr",info);
    433:         for (j=0;j<n;j++) {
    434:           for (i=j+1;i<n;i++) A[i+j*lda] = 0.0;
    435:         }
    436:       } else if (level==nlevels) {  /* only one triangular matrix, set Q=I */
    437:         PetscCall(PetscArrayzero(QQ+(level-1)*n*lda,n*lda));
    438:         for (j=0;j<n;j++) QQ[j+j*lda+(level-1)*n*lda] = 1.0;
    439:       }
    440:     }

    442:     /* Extract R */
    443:     if (R) {
    444:       for (j=0;j<n;j++) {
    445:         for (i=0;i<=j;i++) R[i+j*ldr] = A[i+j*lda];
    446:         for (i=j+1;i<n;i++) R[i+j*ldr] = 0.0;
    447:       }
    448:     }

    450:     /* Accumulate orthogonal matrices */
    451:     for (level=1;level<=nlevels;level++) {
    452:       plevel = PetscPowInt(2,level);
    453:       PetscCall(PetscMPIIntCast(plevel*PetscFloorReal(rank/(PetscReal)plevel)+(rank+PetscPowInt(2,level-1))%plevel,&s));
    454:       Qhalf = (rank<s)? QQ+(level-1)*n*lda: QQ+(level-1)*n*lda+n;
    455:       if (level<nlevels) {
    456:         PetscCallBLAS("BLASgemm",BLASgemm_("N","N",&l,&n,&n,&one,QQ+level*n*lda,&l,Qhalf,&l,&zero,C,&l));
    457:         PetscCall(PetscArraycpy(QQ+level*n*lda,C,n*lda));
    458:       } else {
    459:         for (i=0;i<m/l;i++) {
    460:           PetscCallBLAS("BLASgemm",BLASgemm_("N","N",&l,&n,&n,&one,Q+i*l,&ldq,Qhalf,&l,&zero,C,&l));
    461:           for (j=0;j<n;j++) PetscCall(PetscArraycpy(Q+i*l+j*ldq,C+j*l,l));
    462:         }
    463:         sz = m%l;
    464:         if (sz) {
    465:           PetscCallBLAS("BLASgemm",BLASgemm_("N","N",&sz,&n,&n,&one,Q+(m/l)*l,&ldq,Qhalf,&l,&zero,C,&l));
    466:           for (j=0;j<n;j++) PetscCall(PetscArraycpy(Q+(m/l)*l+j*ldq,C+j*l,sz));
    467:         }
    468:       }
    469:     }

    471:     PetscCallMPI(MPI_Type_free(&tmat));
    472:   }

    474:   PetscCall(PetscLogFlops(3.0*m*n*n));
    475:   PetscCall(PetscFPTrapPop());
    476:   PetscFunctionReturn(PETSC_SUCCESS);
    477: }

    479: /*
    480:     Reduction operation to compute [~,Rout]=qr([Rin1;Rin2]) in the TSQR algorithm;
    481:     all matrices are upper triangular stored in packed format
    482: */
    483: SLEPC_EXTERN void MPIAPI SlepcGivensPacked(void *in,void *inout,PetscMPIInt *len,MPI_Datatype *datatype)
    484: {
    485:   PetscBLASInt   n,i,j,k,one=1;
    486:   PetscMPIInt    tsize;
    487:   PetscScalar    v,s,*R2=(PetscScalar*)in,*R1=(PetscScalar*)inout;
    488:   PetscReal      c;

    490:   PetscFunctionBegin;
    491:   PetscCallMPIAbort(PETSC_COMM_SELF,MPI_Type_size(*datatype,&tsize));  /* we assume len=1 */
    492:   tsize /= sizeof(PetscScalar);
    493:   n = (-1+(PetscBLASInt)PetscSqrtReal(1+8*tsize))/2;
    494:   for (j=0;j<n;j++) {
    495:     for (i=0;i<=j;i++) {
    496:       LAPACKlartg_(R1+(2*n-j-1)*j/2+j,R2+(2*n-i-1)*i/2+j,&c,&s,&v);
    497:       R1[(2*n-j-1)*j/2+j] = v;
    498:       k = n-j-1;
    499:       if (k) BLASrot_(&k,R1+(2*n-j-1)*j/2+j+1,&one,R2+(2*n-i-1)*i/2+j+1,&one,&c,&s);
    500:     }
    501:   }
    502:   PetscFunctionReturnVoid();
    503: }

    505: /*
    506:     Computes the R factor of the QR factorization of an mxn matrix via parallel TSQR
    507: */
    508: PetscErrorCode BVOrthogonalize_LAPACK_TSQR_OnlyR(BV bv,PetscInt m_,PetscInt n_,PetscScalar *Q,PetscInt ldq_,PetscScalar *R,PetscInt ldr)
    509: {
    510:   PetscInt       worklen;
    511:   PetscBLASInt   m,n,ldq,i,j,s,nb,lwork,info;
    512:   PetscScalar    *tau,*work,*A=NULL,*R1=NULL,*R2=NULL;
    513:   PetscMPIInt    size,count;
    514:   MPI_Datatype   tmat;

    516:   PetscFunctionBegin;
    517:   PetscCall(PetscFPTrapPush(PETSC_FP_TRAP_OFF));
    518:   PetscCall(PetscBLASIntCast(m_,&m));
    519:   PetscCall(PetscBLASIntCast(n_,&n));
    520:   PetscCall(PetscBLASIntCast(ldq_,&ldq));
    521:   nb = 16;
    522:   s  = n+n*(n-1)/2;  /* length of packed triangular matrix */
    523:   PetscCallMPI(MPI_Comm_size(PetscObjectComm((PetscObject)bv),&size));
    524:   worklen = n+n*nb+2*s+ldq*n;
    525:   PetscCall(BVAllocateWork_Private(bv,worklen));
    526:   tau  = bv->work;
    527:   work = bv->work+n;
    528:   R1   = bv->work+n+n*nb;
    529:   R2   = bv->work+n+n*nb+s;
    530:   A    = bv->work+n+n*nb+2*s;
    531:   PetscCall(PetscBLASIntCast(n*nb,&lwork));
    532:   PetscCall(PetscArraycpy(A,Q,ldq*n));

    534:   /* Compute QR */
    535:   PetscCallBLAS("LAPACKgeqrf",LAPACKgeqrf_(&m,&n,A,&ldq,tau,work,&lwork,&info));
    536:   SlepcCheckLapackInfo("geqrf",info);

    538:   if (size==1) {
    539:     /* Extract R */
    540:     for (j=0;j<n;j++) {
    541:       for (i=0;i<=PetscMin(j,m-1);i++) R[i+j*ldr] = A[i+j*ldq];
    542:       for (i=PetscMin(j,m-1)+1;i<n;i++) R[i+j*ldr] = 0.0;
    543:     }
    544:   } else {
    545:     /* Use MPI reduction operation to obtain global R */
    546:     PetscCall(PetscMPIIntCast(s,&count));
    547:     PetscCallMPI(MPI_Type_contiguous(count,MPIU_SCALAR,&tmat));
    548:     PetscCallMPI(MPI_Type_commit(&tmat));
    549:     for (i=0;i<n;i++) {
    550:       for (j=i;j<n;j++) R1[(2*n-i-1)*i/2+j] = (i<m)?A[i+j*ldq]:0.0;
    551:     }
    552:     PetscCallMPI(MPIU_Allreduce(R1,R2,1,tmat,MPIU_TSQR,PetscObjectComm((PetscObject)bv)));
    553:     for (i=0;i<n;i++) {
    554:       for (j=0;j<i;j++) R[i+j*ldr] = 0.0;
    555:       for (j=i;j<n;j++) R[i+j*ldr] = R2[(2*n-i-1)*i/2+j];
    556:     }
    557:     PetscCallMPI(MPI_Type_free(&tmat));
    558:   }

    560:   PetscCall(PetscLogFlops(3.0*m*n*n));
    561:   PetscCall(PetscFPTrapPop());
    562:   PetscFunctionReturn(PETSC_SUCCESS);
    563: }