*> \brief \b CLAQP3RK computes a step of truncated QR factorization with column pivoting of a complex m-by-n matrix A using Level 3 BLAS and overwrites a complex m-by-nrhs matrix B with Q**H * B.
*
* =========== DOCUMENTATION ===========
*
* Online html documentation available at
* http://www.netlib.org/lapack/explore-html/
*
*> \htmlonly
*> Download CLAQP3RK + dependencies
*>
*> [TGZ]
*>
*> [ZIP]
*>
*> [TXT]
*> \endhtmlonly
*
* Definition:
* ===========
*
* SUBROUTINE CLAQP3RK( M, N, NRHS, IOFFSET, NB, ABSTOL,
* $ RELTOL, KP1, MAXC2NRM, A, LDA, DONE, KB,
* $ MAXC2NRMK, RELMAXC2NRMK, JPIV, TAU,
* $ VN1, VN2, AUXV, F, LDF, IWORK, INFO )
* IMPLICIT NONE
* LOGICAL DONE
* INTEGER INFO, IOFFSET, KB, KP1, LDA, LDF, M, N,
* $ NB, NRHS
* REAL ABSTOL, MAXC2NRM, MAXC2NRMK, RELMAXC2NRMK,
* $ RELTOL
* ..
* .. Array Arguments ..
* INTEGER IWORK( * ), JPIV( * )
* REAL VN1( * ), VN2( * )
* COMPLEX*16 A( LDA, * ), AUXV( * ), F( LDF, * ), TAU( * )
* ..
*
*
*> \par Purpose:
* =============
*>
*> \verbatim
*>
*> CLAQP3RK computes a step of truncated QR factorization with column
*> pivoting of a complex M-by-N matrix A block A(IOFFSET+1:M,1:N)
*> by using Level 3 BLAS as
*>
*> A * P(KB) = Q(KB) * R(KB).
*>
*> The routine tries to factorize NB columns from A starting from
*> the row IOFFSET+1 and updates the residual matrix with BLAS 3
*> xGEMM. The number of actually factorized columns is returned
*> is smaller than NB.
*>
*> Block A(1:IOFFSET,1:N) is accordingly pivoted, but not factorized.
*>
*> The routine also overwrites the right-hand-sides B matrix stored
*> in A(IOFFSET+1:M,1:N+1:N+NRHS) with Q(KB)**H * B.
*>
*> Cases when the number of factorized columns KB < NB:
*>
*> (1) In some cases, due to catastrophic cancellations, it cannot
*> factorize all NB columns and need to update the residual matrix.
*> Hence, the actual number of factorized columns in the block returned
*> in KB is smaller than NB. The logical DONE is returned as FALSE.
*> The factorization of the whole original matrix A_orig must proceed
*> with the next block.
*>
*> (2) Whenever the stopping criterion ABSTOL or RELTOL is satisfied,
*> the factorization of the whole original matrix A_orig is stopped,
*> the logical DONE is returned as TRUE. The number of factorized
*> columns which is smaller than NB is returned in KB.
*>
*> (3) In case both stopping criteria ABSTOL or RELTOL are not used,
*> and when the residual matrix is a zero matrix in some factorization
*> step KB, the factorization of the whole original matrix A_orig is
*> stopped, the logical DONE is returned as TRUE. The number of
*> factorized columns which is smaller than NB is returned in KB.
*>
*> (4) Whenever NaN is detected in the matrix A or in the array TAU,
*> the factorization of the whole original matrix A_orig is stopped,
*> the logical DONE is returned as TRUE. The number of factorized
*> columns which is smaller than NB is returned in KB. The INFO
*> parameter is set to the column index of the first NaN occurrence.
*>
*> \endverbatim
*
* Arguments:
* ==========
*
*> \param[in] M
*> \verbatim
*> M is INTEGER
*> The number of rows of the matrix A. M >= 0.
*> \endverbatim
*>
*> \param[in] N
*> \verbatim
*> N is INTEGER
*> The number of columns of the matrix A. N >= 0
*> \endverbatim
*>
*> \param[in] NRHS
*> \verbatim
*> NRHS is INTEGER
*> The number of right hand sides, i.e., the number of
*> columns of the matrix B. NRHS >= 0.
*> \endverbatim
*>
*> \param[in] IOFFSET
*> \verbatim
*> IOFFSET is INTEGER
*> The number of rows of the matrix A that must be pivoted
*> but not factorized. IOFFSET >= 0.
*>
*> IOFFSET also represents the number of columns of the whole
*> original matrix A_orig that have been factorized
*> in the previous steps.
*> \endverbatim
*>
*> \param[in] NB
*> \verbatim
*> NB is INTEGER
*> Factorization block size, i.e the number of columns
*> to factorize in the matrix A. 0 <= NB
*>
*> If NB = 0, then the routine exits immediately.
*> This means that the factorization is not performed,
*> the matrices A and B and the arrays TAU, IPIV
*> are not modified.
*> \endverbatim
*>
*> \param[in] ABSTOL
*> \verbatim
*> ABSTOL is REAL, cannot be NaN.
*>
*> The absolute tolerance (stopping threshold) for
*> maximum column 2-norm of the residual matrix.
*> The algorithm converges (stops the factorization) when
*> the maximum column 2-norm of the residual matrix
*> is less than or equal to ABSTOL.
*>
*> a) If ABSTOL < 0.0, then this stopping criterion is not
*> used, the routine factorizes columns depending
*> on NB and RELTOL.
*> This includes the case ABSTOL = -Inf.
*>
*> b) If 0.0 <= ABSTOL then the input value
*> of ABSTOL is used.
*> \endverbatim
*>
*> \param[in] RELTOL
*> \verbatim
*> RELTOL is REAL, cannot be NaN.
*>
*> The tolerance (stopping threshold) for the ratio of the
*> maximum column 2-norm of the residual matrix to the maximum
*> column 2-norm of the original matrix A_orig. The algorithm
*> converges (stops the factorization), when this ratio is
*> less than or equal to RELTOL.
*>
*> a) If RELTOL < 0.0, then this stopping criterion is not
*> used, the routine factorizes columns depending
*> on NB and ABSTOL.
*> This includes the case RELTOL = -Inf.
*>
*> d) If 0.0 <= RELTOL then the input value of RELTOL
*> is used.
*> \endverbatim
*>
*> \param[in] KP1
*> \verbatim
*> KP1 is INTEGER
*> The index of the column with the maximum 2-norm in
*> the whole original matrix A_orig determined in the
*> main routine CGEQP3RK. 1 <= KP1 <= N_orig.
*> \endverbatim
*>
*> \param[in] MAXC2NRM
*> \verbatim
*> MAXC2NRM is REAL
*> The maximum column 2-norm of the whole original
*> matrix A_orig computed in the main routine CGEQP3RK.
*> MAXC2NRM >= 0.
*> \endverbatim
*>
*> \param[in,out] A
*> \verbatim
*> A is COMPLEX array, dimension (LDA,N+NRHS)
*> On entry:
*> the M-by-N matrix A and M-by-NRHS matrix B, as in
*>
*> N NRHS
*> array_A = M [ mat_A, mat_B ]
*>
*> On exit:
*> 1. The elements in block A(IOFFSET+1:M,1:KB) below
*> the diagonal together with the array TAU represent
*> the unitary matrix Q(KB) as a product of elementary
*> reflectors.
*> 2. The upper triangular block of the matrix A stored
*> in A(IOFFSET+1:M,1:KB) is the triangular factor obtained.
*> 3. The block of the matrix A stored in A(1:IOFFSET,1:N)
*> has been accordingly pivoted, but not factorized.
*> 4. The rest of the array A, block A(IOFFSET+1:M,KB+1:N+NRHS).
*> The left part A(IOFFSET+1:M,KB+1:N) of this block
*> contains the residual of the matrix A, and,
*> if NRHS > 0, the right part of the block
*> A(IOFFSET+1:M,N+1:N+NRHS) contains the block of
*> the right-hand-side matrix B. Both these blocks have been
*> updated by multiplication from the left by Q(KB)**H.
*> \endverbatim
*>
*> \param[in] LDA
*> \verbatim
*> LDA is INTEGER
*> The leading dimension of the array A. LDA >= max(1,M).
*> \endverbatim
*>
*> \param[out] DONE
*> \verbatim
*> DONE is LOGICAL
*> TRUE: a) if the factorization completed before processing
*> all min(M-IOFFSET,NB,N) columns due to ABSTOL
*> or RELTOL criterion,
*> b) if the factorization completed before processing
*> all min(M-IOFFSET,NB,N) columns due to the
*> residual matrix being a ZERO matrix.
*> c) when NaN was detected in the matrix A
*> or in the array TAU.
*> FALSE: otherwise.
*> \endverbatim
*>
*> \param[out] KB
*> \verbatim
*> KB is INTEGER
*> Factorization rank of the matrix A, i.e. the rank of
*> the factor R, which is the same as the number of non-zero
*> rows of the factor R. 0 <= KB <= min(M-IOFFSET,NB,N).
*>
*> KB also represents the number of non-zero Householder
*> vectors.
*> \endverbatim
*>
*> \param[out] MAXC2NRMK
*> \verbatim
*> MAXC2NRMK is REAL
*> The maximum column 2-norm of the residual matrix,
*> when the factorization stopped at rank KB. MAXC2NRMK >= 0.
*> \endverbatim
*>
*> \param[out] RELMAXC2NRMK
*> \verbatim
*> RELMAXC2NRMK is REAL
*> The ratio MAXC2NRMK / MAXC2NRM of the maximum column
*> 2-norm of the residual matrix (when the factorization
*> stopped at rank KB) to the maximum column 2-norm of the
*> original matrix A_orig. RELMAXC2NRMK >= 0.
*> \endverbatim
*>
*> \param[out] JPIV
*> \verbatim
*> JPIV is INTEGER array, dimension (N)
*> Column pivot indices, for 1 <= j <= N, column j
*> of the matrix A was interchanged with column JPIV(j).
*> \endverbatim
*>
*> \param[out] TAU
*> \verbatim
*> TAU is COMPLEX array, dimension (min(M-IOFFSET,N))
*> The scalar factors of the elementary reflectors.
*> \endverbatim
*>
*> \param[in,out] VN1
*> \verbatim
*> VN1 is REAL array, dimension (N)
*> The vector with the partial column norms.
*> \endverbatim
*>
*> \param[in,out] VN2
*> \verbatim
*> VN2 is REAL array, dimension (N)
*> The vector with the exact column norms.
*> \endverbatim
*>
*> \param[out] AUXV
*> \verbatim
*> AUXV is COMPLEX array, dimension (NB)
*> Auxiliary vector.
*> \endverbatim
*>
*> \param[out] F
*> \verbatim
*> F is COMPLEX array, dimension (LDF,NB)
*> Matrix F**H = L*(Y**H)*A.
*> \endverbatim
*>
*> \param[in] LDF
*> \verbatim
*> LDF is INTEGER
*> The leading dimension of the array F. LDF >= max(1,N+NRHS).
*> \endverbatim
*>
*> \param[out] IWORK
*> \verbatim
*> IWORK is INTEGER array, dimension (N-1).
*> Is a work array. ( IWORK is used to store indices
*> of "bad" columns for norm downdating in the residual
*> matrix ).
*> \endverbatim
*>
*> \param[out] INFO
*> \verbatim
*> INFO is INTEGER
*> 1) INFO = 0: successful exit.
*> 2) If INFO = j_1, where 1 <= j_1 <= N, then NaN was
*> detected and the routine stops the computation.
*> The j_1-th column of the matrix A or the j_1-th
*> element of array TAU contains the first occurrence
*> of NaN in the factorization step KB+1 ( when KB columns
*> have been factorized ).
*>
*> On exit:
*> KB is set to the number of
*> factorized columns without
*> exception.
*> MAXC2NRMK is set to NaN.
*> RELMAXC2NRMK is set to NaN.
*> TAU(KB+1:min(M,N)) is not set and contains undefined
*> elements. If j_1=KB+1, TAU(KB+1)
*> may contain NaN.
*> 3) If INFO = j_2, where N+1 <= j_2 <= 2*N, then no NaN
*> was detected, but +Inf (or -Inf) was detected and
*> the routine continues the computation until completion.
*> The (j_2-N)-th column of the matrix A contains the first
*> occurrence of +Inf (or -Inf) in the actorization
*> step KB+1 ( when KB columns have been factorized ).
*> \endverbatim
*
* Authors:
* ========
*
*> \author Univ. of Tennessee
*> \author Univ. of California Berkeley
*> \author Univ. of Colorado Denver
*> \author NAG Ltd.
*
*> \ingroup laqp3rk
*
*> \par References:
* ================
*> [1] A Level 3 BLAS QR factorization algorithm with column pivoting developed in 1996.
*> G. Quintana-Orti, Depto. de Informatica, Universidad Jaime I, Spain.
*> X. Sun, Computer Science Dept., Duke University, USA.
*> C. H. Bischof, Math. and Comp. Sci. Div., Argonne National Lab, USA.
*> A BLAS-3 version of the QR factorization with column pivoting.
*> LAPACK Working Note 114
*> \htmlonly
*> https://www.netlib.org/lapack/lawnspdf/lawn114.pdf
*> \endhtmlonly
*> and in
*> SIAM J. Sci. Comput., 19(5):1486-1494, Sept. 1998.
*> \htmlonly
*> https://doi.org/10.1137/S1064827595296732
*> \endhtmlonly
*>
*> [2] A partial column norm updating strategy developed in 2006.
*> Z. Drmac and Z. Bujanovic, Dept. of Math., University of Zagreb, Croatia.
*> On the failure of rank revealing QR factorization software – a case study.
*> LAPACK Working Note 176.
*> \htmlonly
*> http://www.netlib.org/lapack/lawnspdf/lawn176.pdf
*> \endhtmlonly
*> and in
*> ACM Trans. Math. Softw. 35, 2, Article 12 (July 2008), 28 pages.
*> \htmlonly
*> https://doi.org/10.1145/1377612.1377616
*> \endhtmlonly
*
*> \par Contributors:
* ==================
*>
*> \verbatim
*>
*> November 2023, Igor Kozachenko, James Demmel,
*> EECS Department,
*> University of California, Berkeley, USA.
*>
*> \endverbatim
*
* =====================================================================
SUBROUTINE CLAQP3RK( M, N, NRHS, IOFFSET, NB, ABSTOL,
$ RELTOL, KP1, MAXC2NRM, A, LDA, DONE, KB,
$ MAXC2NRMK, RELMAXC2NRMK, JPIV, TAU,
$ VN1, VN2, AUXV, F, LDF, IWORK, INFO )
IMPLICIT NONE
*
* -- LAPACK auxiliary routine --
* -- LAPACK is a software package provided by Univ. of Tennessee, --
* -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
*
* .. Scalar Arguments ..
LOGICAL DONE
INTEGER INFO, IOFFSET, KB, KP1, LDA, LDF, M, N,
$ NB, NRHS
REAL ABSTOL, MAXC2NRM, MAXC2NRMK, RELMAXC2NRMK,
$ RELTOL
* ..
* .. Array Arguments ..
INTEGER IWORK( * ), JPIV( * )
REAL VN1( * ), VN2( * )
COMPLEX A( LDA, * ), AUXV( * ), F( LDF, * ), TAU( * )
* ..
*
* =====================================================================
*
* .. Parameters ..
REAL ZERO, ONE
PARAMETER ( ZERO = 0.0E+0, ONE = 1.0E+0 )
COMPLEX CZERO, CONE
PARAMETER ( CZERO = ( 0.0E+0, 0.0E+0 ),
$ CONE = ( 1.0E+0, 0.0E+0 ) )
* ..
* .. Local Scalars ..
INTEGER ITEMP, J, K, MINMNFACT, MINMNUPDT,
$ LSTICC, KP, I, IF
REAL HUGEVAL, TAUNAN, TEMP, TEMP2, TOL3Z
COMPLEX AIK
* ..
* .. External Subroutines ..
EXTERNAL CGEMM, CGEMV, CLARFG, CSWAP
* ..
* .. Intrinsic Functions ..
INTRINSIC ABS, REAL, CONJG, AIMAG, MAX, MIN, SQRT
* ..
* .. External Functions ..
LOGICAL SISNAN
INTEGER ISAMAX
REAL SLAMCH, SCNRM2
EXTERNAL SISNAN, SLAMCH, ISAMAX, SCNRM2
* ..
* .. Executable Statements ..
*
* Initialize INFO
*
INFO = 0
*
* MINMNFACT in the smallest dimension of the submatrix
* A(IOFFSET+1:M,1:N) to be factorized.
*
MINMNFACT = MIN( M-IOFFSET, N )
MINMNUPDT = MIN( M-IOFFSET, N+NRHS )
NB = MIN( NB, MINMNFACT )
TOL3Z = SQRT( SLAMCH( 'Epsilon' ) )
HUGEVAL = SLAMCH( 'Overflow' )
*
* Compute factorization in a while loop over NB columns,
* K is the column index in the block A(1:M,1:N).
*
K = 0
LSTICC = 0
DONE = .FALSE.
*
DO WHILE ( K.LT.NB .AND. LSTICC.EQ.0 )
K = K + 1
I = IOFFSET + K
*
IF( I.EQ.1 ) THEN
*
* We are at the first column of the original whole matrix A_orig,
* therefore we use the computed KP1 and MAXC2NRM from the
* main routine.
*
KP = KP1
*
ELSE
*
* Determine the pivot column in K-th step, i.e. the index
* of the column with the maximum 2-norm in the
* submatrix A(I:M,K:N).
*
KP = ( K-1 ) + ISAMAX( N-K+1, VN1( K ), 1 )
*
* Determine the maximum column 2-norm and the relative maximum
* column 2-norm of the submatrix A(I:M,K:N) in step K.
*
MAXC2NRMK = VN1( KP )
*
* ============================================================
*
* Check if the submatrix A(I:M,K:N) contains NaN, set
* INFO parameter to the column number, where the first NaN
* is found and return from the routine.
* We need to check the condition only if the
* column index (same as row index) of the original whole
* matrix is larger than 1, since the condition for whole
* original matrix is checked in the main routine.
*
IF( SISNAN( MAXC2NRMK ) ) THEN
*
DONE = .TRUE.
*
* Set KB, the number of factorized partial columns
* that are non-zero in each step in the block,
* i.e. the rank of the factor R.
* Set IF, the number of processed rows in the block, which
* is the same as the number of processed rows in
* the original whole matrix A_orig.
*
KB = K - 1
IF = I - 1
INFO = KB + KP
*
* Set RELMAXC2NRMK to NaN.
*
RELMAXC2NRMK = MAXC2NRMK
*
* There is no need to apply the block reflector to the
* residual of the matrix A stored in A(KB+1:M,KB+1:N),
* since the submatrix contains NaN and we stop
* the computation.
* But, we need to apply the block reflector to the residual
* right hand sides stored in A(KB+1:M,N+1:N+NRHS), if the
* residual right hand sides exist. This occurs
* when ( NRHS != 0 AND KB <= (M-IOFFSET) ):
*
* A(I+1:M,N+1:N+NRHS) := A(I+1:M,N+1:N+NRHS) -
* A(I+1:M,1:KB) * F(N+1:N+NRHS,1:KB)**H.
IF( NRHS.GT.0 .AND. KB.LT.(M-IOFFSET) ) THEN
CALL CGEMM( 'No transpose', 'Conjugate transpose',
$ M-IF, NRHS, KB, -CONE, A( IF+1, 1 ), LDA,
$ F( N+1, 1 ), LDF, CONE, A( IF+1, N+1 ), LDA )
END IF
*
* There is no need to recompute the 2-norm of the
* difficult columns, since we stop the factorization.
*
* Array TAU(KF+1:MINMNFACT) is not set and contains
* undefined elements.
*
* Return from the routine.
*
RETURN
END IF
*
* Quick return, if the submatrix A(I:M,K:N) is
* a zero matrix. We need to check it only if the column index
* (same as row index) is larger than 1, since the condition
* for the whole original matrix A_orig is checked in the main
* routine.
*
IF( MAXC2NRMK.EQ.ZERO ) THEN
*
DONE = .TRUE.
*
* Set KB, the number of factorized partial columns
* that are non-zero in each step in the block,
* i.e. the rank of the factor R.
* Set IF, the number of processed rows in the block, which
* is the same as the number of processed rows in
* the original whole matrix A_orig.
*
KB = K - 1
IF = I - 1
RELMAXC2NRMK = ZERO
*
* There is no need to apply the block reflector to the
* residual of the matrix A stored in A(KB+1:M,KB+1:N),
* since the submatrix is zero and we stop the computation.
* But, we need to apply the block reflector to the residual
* right hand sides stored in A(KB+1:M,N+1:N+NRHS), if the
* residual right hand sides exist. This occurs
* when ( NRHS != 0 AND KB <= (M-IOFFSET) ):
*
* A(I+1:M,N+1:N+NRHS) := A(I+1:M,N+1:N+NRHS) -
* A(I+1:M,1:KB) * F(N+1:N+NRHS,1:KB)**H.
*
IF( NRHS.GT.0 .AND. KB.LT.(M-IOFFSET) ) THEN
CALL CGEMM( 'No transpose', 'Conjugate transpose',
$ M-IF, NRHS, KB, -CONE, A( IF+1, 1 ), LDA,
$ F( N+1, 1 ), LDF, CONE, A( IF+1, N+1 ), LDA )
END IF
*
* There is no need to recompute the 2-norm of the
* difficult columns, since we stop the factorization.
*
* Set TAUs corresponding to the columns that were not
* factorized to ZERO, i.e. set TAU(KB+1:MINMNFACT) = CZERO,
* which is equivalent to seting TAU(K:MINMNFACT) = CZERO.
*
DO J = K, MINMNFACT
TAU( J ) = CZERO
END DO
*
* Return from the routine.
*
RETURN
*
END IF
*
* ============================================================
*
* Check if the submatrix A(I:M,K:N) contains Inf,
* set INFO parameter to the column number, where
* the first Inf is found plus N, and continue
* the computation.
* We need to check the condition only if the
* column index (same as row index) of the original whole
* matrix is larger than 1, since the condition for whole
* original matrix is checked in the main routine.
*
IF( INFO.EQ.0 .AND. MAXC2NRMK.GT.HUGEVAL ) THEN
INFO = N + K - 1 + KP
END IF
*
* ============================================================
*
* Test for the second and third tolerance stopping criteria.
* NOTE: There is no need to test for ABSTOL.GE.ZERO, since
* MAXC2NRMK is non-negative. Similarly, there is no need
* to test for RELTOL.GE.ZERO, since RELMAXC2NRMK is
* non-negative.
* We need to check the condition only if the
* column index (same as row index) of the original whole
* matrix is larger than 1, since the condition for whole
* original matrix is checked in the main routine.
*
RELMAXC2NRMK = MAXC2NRMK / MAXC2NRM
*
IF( MAXC2NRMK.LE.ABSTOL .OR. RELMAXC2NRMK.LE.RELTOL ) THEN
*
DONE = .TRUE.
*
* Set KB, the number of factorized partial columns
* that are non-zero in each step in the block,
* i.e. the rank of the factor R.
* Set IF, the number of processed rows in the block, which
* is the same as the number of processed rows in
* the original whole matrix A_orig;
*
KB = K - 1
IF = I - 1
*
* Apply the block reflector to the residual of the
* matrix A and the residual of the right hand sides B, if
* the residual matrix and and/or the residual of the right
* hand sides exist, i.e. if the submatrix
* A(I+1:M,KB+1:N+NRHS) exists. This occurs when
* KB < MINMNUPDT = min( M-IOFFSET, N+NRHS ):
*
* A(IF+1:M,K+1:N+NRHS) := A(IF+1:M,KB+1:N+NRHS) -
* A(IF+1:M,1:KB) * F(KB+1:N+NRHS,1:KB)**H.
*
IF( KB.LT.MINMNUPDT ) THEN
CALL CGEMM( 'No transpose', 'Conjugate transpose',
$ M-IF, N+NRHS-KB, KB,-CONE, A( IF+1, 1 ), LDA,
$ F( KB+1, 1 ), LDF, CONE, A( IF+1, KB+1 ), LDA )
END IF
*
* There is no need to recompute the 2-norm of the
* difficult columns, since we stop the factorization.
*
* Set TAUs corresponding to the columns that were not
* factorized to ZERO, i.e. set TAU(KB+1:MINMNFACT) = CZERO,
* which is equivalent to seting TAU(K:MINMNFACT) = CZERO.
*
DO J = K, MINMNFACT
TAU( J ) = CZERO
END DO
*
* Return from the routine.
*
RETURN
*
END IF
*
* ============================================================
*
* End ELSE of IF(I.EQ.1)
*
END IF
*
* ===============================================================
*
* If the pivot column is not the first column of the
* subblock A(1:M,K:N):
* 1) swap the K-th column and the KP-th pivot column
* in A(1:M,1:N);
* 2) swap the K-th row and the KP-th row in F(1:N,1:K-1)
* 3) copy the K-th element into the KP-th element of the partial
* and exact 2-norm vectors VN1 and VN2. (Swap is not needed
* for VN1 and VN2 since we use the element with the index
* larger than K in the next loop step.)
* 4) Save the pivot interchange with the indices relative to the
* the original matrix A_orig, not the block A(1:M,1:N).
*
IF( KP.NE.K ) THEN
CALL CSWAP( M, A( 1, KP ), 1, A( 1, K ), 1 )
CALL CSWAP( K-1, F( KP, 1 ), LDF, F( K, 1 ), LDF )
VN1( KP ) = VN1( K )
VN2( KP ) = VN2( K )
ITEMP = JPIV( KP )
JPIV( KP ) = JPIV( K )
JPIV( K ) = ITEMP
END IF
*
* Apply previous Householder reflectors to column K:
* A(I:M,K) := A(I:M,K) - A(I:M,1:K-1)*F(K,1:K-1)**H.
*
IF( K.GT.1 ) THEN
DO J = 1, K - 1
F( K, J ) = CONJG( F( K, J ) )
END DO
CALL CGEMV( 'No transpose', M-I+1, K-1, -CONE, A( I, 1 ),
$ LDA, F( K, 1 ), LDF, CONE, A( I, K ), 1 )
DO J = 1, K - 1
F( K, J ) = CONJG( F( K, J ) )
END DO
END IF
*
* Generate elementary reflector H(k) using the column A(I:M,K).
*
IF( I.LT.M ) THEN
CALL CLARFG( M-I+1, A( I, K ), A( I+1, K ), 1, TAU( K ) )
ELSE
TAU( K ) = CZERO
END IF
*
* Check if TAU(K) contains NaN, set INFO parameter
* to the column number where NaN is found and return from
* the routine.
* NOTE: There is no need to check TAU(K) for Inf,
* since CLARFG cannot produce TAU(KK) or Householder vector
* below the diagonal containing Inf. Only BETA on the diagonal,
* returned by CLARFG can contain Inf, which requires
* TAU(K) to contain NaN. Therefore, this case of generating Inf
* by CLARFG is covered by checking TAU(K) for NaN.
*
IF( SISNAN( REAL( TAU(K) ) ) ) THEN
TAUNAN = REAL( TAU(K) )
ELSE IF( SISNAN( AIMAG( TAU(K) ) ) ) THEN
TAUNAN = AIMAG( TAU(K) )
ELSE
TAUNAN = ZERO
END IF
*
IF( SISNAN( TAUNAN ) ) THEN
*
DONE = .TRUE.
*
* Set KB, the number of factorized partial columns
* that are non-zero in each step in the block,
* i.e. the rank of the factor R.
* Set IF, the number of processed rows in the block, which
* is the same as the number of processed rows in
* the original whole matrix A_orig.
*
KB = K - 1
IF = I - 1
INFO = K
*
* Set MAXC2NRMK and RELMAXC2NRMK to NaN.
*
MAXC2NRMK = TAUNAN
RELMAXC2NRMK = TAUNAN
*
* There is no need to apply the block reflector to the
* residual of the matrix A stored in A(KB+1:M,KB+1:N),
* since the submatrix contains NaN and we stop
* the computation.
* But, we need to apply the block reflector to the residual
* right hand sides stored in A(KB+1:M,N+1:N+NRHS), if the
* residual right hand sides exist. This occurs
* when ( NRHS != 0 AND KB <= (M-IOFFSET) ):
*
* A(I+1:M,N+1:N+NRHS) := A(I+1:M,N+1:N+NRHS) -
* A(I+1:M,1:KB) * F(N+1:N+NRHS,1:KB)**H.
*
IF( NRHS.GT.0 .AND. KB.LT.(M-IOFFSET) ) THEN
CALL CGEMM( 'No transpose', 'Conjugate transpose',
$ M-IF, NRHS, KB, -CONE, A( IF+1, 1 ), LDA,
$ F( N+1, 1 ), LDF, CONE, A( IF+1, N+1 ), LDA )
END IF
*
* There is no need to recompute the 2-norm of the
* difficult columns, since we stop the factorization.
*
* Array TAU(KF+1:MINMNFACT) is not set and contains
* undefined elements.
*
* Return from the routine.
*
RETURN
END IF
*
* ===============================================================
*
AIK = A( I, K )
A( I, K ) = CONE
*
* ===============================================================
*
* Compute the current K-th column of F:
* 1) F(K+1:N,K) := tau(K) * A(I:M,K+1:N)**H * A(I:M,K).
*
IF( K.LT.N+NRHS ) THEN
CALL CGEMV( 'Conjugate transpose', M-I+1, N+NRHS-K,
$ TAU( K ), A( I, K+1 ), LDA, A( I, K ), 1,
$ CZERO, F( K+1, K ), 1 )
END IF
*
* 2) Zero out elements above and on the diagonal of the
* column K in matrix F, i.e elements F(1:K,K).
*
DO J = 1, K
F( J, K ) = CZERO
END DO
*
* 3) Incremental updating of the K-th column of F:
* F(1:N,K) := F(1:N,K) - tau(K) * F(1:N,1:K-1) * A(I:M,1:K-1)**H
* * A(I:M,K).
*
IF( K.GT.1 ) THEN
CALL CGEMV( 'Conjugate Transpose', M-I+1, K-1, -TAU( K ),
$ A( I, 1 ), LDA, A( I, K ), 1, CZERO,
$ AUXV( 1 ), 1 )
*
CALL CGEMV( 'No transpose', N+NRHS, K-1, CONE,
$ F( 1, 1 ), LDF, AUXV( 1 ), 1, CONE,
$ F( 1, K ), 1 )
END IF
*
* ===============================================================
*
* Update the current I-th row of A:
* A(I,K+1:N+NRHS) := A(I,K+1:N+NRHS)
* - A(I,1:K)*F(K+1:N+NRHS,1:K)**H.
*
IF( K.LT.N+NRHS ) THEN
CALL CGEMM( 'No transpose', 'Conjugate transpose',
$ 1, N+NRHS-K, K, -CONE, A( I, 1 ), LDA,
$ F( K+1, 1 ), LDF, CONE, A( I, K+1 ), LDA )
END IF
*
A( I, K ) = AIK
*
* Update the partial column 2-norms for the residual matrix,
* only if the residual matrix A(I+1:M,K+1:N) exists, i.e.
* when K < MINMNFACT = min( M-IOFFSET, N ).
*
IF( K.LT.MINMNFACT ) THEN
*
DO J = K + 1, N
IF( VN1( J ).NE.ZERO ) THEN
*
* NOTE: The following lines follow from the analysis in
* Lapack Working Note 176.
*
TEMP = ABS( A( I, J ) ) / VN1( J )
TEMP = MAX( ZERO, ( ONE+TEMP )*( ONE-TEMP ) )
TEMP2 = TEMP*( VN1( J ) / VN2( J ) )**2
IF( TEMP2.LE.TOL3Z ) THEN
*
* At J-index, we have a difficult column for the
* update of the 2-norm. Save the index of the previous
* difficult column in IWORK(J-1).
* NOTE: ILSTCC > 1, threfore we can use IWORK only
* with N-1 elements, where the elements are
* shifted by 1 to the left.
*
IWORK( J-1 ) = LSTICC
*
* Set the index of the last difficult column LSTICC.
*
LSTICC = J
*
ELSE
VN1( J ) = VN1( J )*SQRT( TEMP )
END IF
END IF
END DO
*
END IF
*
* End of while loop.
*
END DO
*
* Now, afler the loop:
* Set KB, the number of factorized columns in the block;
* Set IF, the number of processed rows in the block, which
* is the same as the number of processed rows in
* the original whole matrix A_orig, IF = IOFFSET + KB.
*
KB = K
IF = I
*
* Apply the block reflector to the residual of the matrix A
* and the residual of the right hand sides B, if the residual
* matrix and and/or the residual of the right hand sides
* exist, i.e. if the submatrix A(I+1:M,KB+1:N+NRHS) exists.
* This occurs when KB < MINMNUPDT = min( M-IOFFSET, N+NRHS ):
*
* A(IF+1:M,K+1:N+NRHS) := A(IF+1:M,KB+1:N+NRHS) -
* A(IF+1:M,1:KB) * F(KB+1:N+NRHS,1:KB)**H.
*
IF( KB.LT.MINMNUPDT ) THEN
CALL CGEMM( 'No transpose', 'Conjugate transpose',
$ M-IF, N+NRHS-KB, KB, -CONE, A( IF+1, 1 ), LDA,
$ F( KB+1, 1 ), LDF, CONE, A( IF+1, KB+1 ), LDA )
END IF
*
* Recompute the 2-norm of the difficult columns.
* Loop over the index of the difficult columns from the largest
* to the smallest index.
*
DO WHILE( LSTICC.GT.0 )
*
* LSTICC is the index of the last difficult column is greater
* than 1.
* ITEMP is the index of the previous difficult column.
*
ITEMP = IWORK( LSTICC-1 )
*
* Compute the 2-norm explicilty for the last difficult column and
* save it in the partial and exact 2-norm vectors VN1 and VN2.
*
* NOTE: The computation of VN1( LSTICC ) relies on the fact that
* SCNRM2 does not fail on vectors with norm below the value of
* SQRT(SLAMCH('S'))
*
VN1( LSTICC ) = SCNRM2( M-IF, A( IF+1, LSTICC ), 1 )
VN2( LSTICC ) = VN1( LSTICC )
*
* Downdate the index of the last difficult column to
* the index of the previous difficult column.
*
LSTICC = ITEMP
*
END DO
*
RETURN
*
* End of CLAQP3RK
*
END