*> \brief \b SLASD3 finds all square roots of the roots of the secular equation, as defined by the values in D and Z, and then updates the singular vectors by matrix multiplication. Used by sbdsdc. * * =========== DOCUMENTATION =========== * * Online html documentation available at * http://www.netlib.org/lapack/explore-html/ * *> \htmlonly *> Download SLASD3 + dependencies *> *> [TGZ] *> *> [ZIP] *> *> [TXT] *> \endhtmlonly * * Definition: * =========== * * SUBROUTINE SLASD3( NL, NR, SQRE, K, D, Q, LDQ, DSIGMA, U, LDU, U2, * LDU2, VT, LDVT, VT2, LDVT2, IDXC, CTOT, Z, * INFO ) * * .. Scalar Arguments .. * INTEGER INFO, K, LDQ, LDU, LDU2, LDVT, LDVT2, NL, NR, * \$ SQRE * .. * .. Array Arguments .. * INTEGER CTOT( * ), IDXC( * ) * REAL D( * ), DSIGMA( * ), Q( LDQ, * ), U( LDU, * ), * \$ U2( LDU2, * ), VT( LDVT, * ), VT2( LDVT2, * ), * \$ Z( * ) * .. * * *> \par Purpose: * ============= *> *> \verbatim *> *> SLASD3 finds all the square roots of the roots of the secular *> equation, as defined by the values in D and Z. It makes the *> appropriate calls to SLASD4 and then updates the singular *> vectors by matrix multiplication. *> *> This code makes very mild assumptions about floating point *> arithmetic. It will work on machines with a guard digit in *> add/subtract, or on those binary machines without guard digits *> which subtract like the Cray XMP, Cray YMP, Cray C 90, or Cray 2. *> It could conceivably fail on hexadecimal or decimal machines *> without guard digits, but we know of none. *> *> SLASD3 is called from SLASD1. *> \endverbatim * * Arguments: * ========== * *> \param[in] NL *> \verbatim *> NL is INTEGER *> The row dimension of the upper block. NL >= 1. *> \endverbatim *> *> \param[in] NR *> \verbatim *> NR is INTEGER *> The row dimension of the lower block. NR >= 1. *> \endverbatim *> *> \param[in] SQRE *> \verbatim *> SQRE is INTEGER *> = 0: the lower block is an NR-by-NR square matrix. *> = 1: the lower block is an NR-by-(NR+1) rectangular matrix. *> *> The bidiagonal matrix has N = NL + NR + 1 rows and *> M = N + SQRE >= N columns. *> \endverbatim *> *> \param[in] K *> \verbatim *> K is INTEGER *> The size of the secular equation, 1 =< K = < N. *> \endverbatim *> *> \param[out] D *> \verbatim *> D is REAL array, dimension(K) *> On exit the square roots of the roots of the secular equation, *> in ascending order. *> \endverbatim *> *> \param[out] Q *> \verbatim *> Q is REAL array, dimension (LDQ,K) *> \endverbatim *> *> \param[in] LDQ *> \verbatim *> LDQ is INTEGER *> The leading dimension of the array Q. LDQ >= K. *> \endverbatim *> *> \param[in,out] DSIGMA *> \verbatim *> DSIGMA is REAL array, dimension(K) *> The first K elements of this array contain the old roots *> of the deflated updating problem. These are the poles *> of the secular equation. *> \endverbatim *> *> \param[out] U *> \verbatim *> U is REAL array, dimension (LDU, N) *> The last N - K columns of this matrix contain the deflated *> left singular vectors. *> \endverbatim *> *> \param[in] LDU *> \verbatim *> LDU is INTEGER *> The leading dimension of the array U. LDU >= N. *> \endverbatim *> *> \param[in] U2 *> \verbatim *> U2 is REAL array, dimension (LDU2, N) *> The first K columns of this matrix contain the non-deflated *> left singular vectors for the split problem. *> \endverbatim *> *> \param[in] LDU2 *> \verbatim *> LDU2 is INTEGER *> The leading dimension of the array U2. LDU2 >= N. *> \endverbatim *> *> \param[out] VT *> \verbatim *> VT is REAL array, dimension (LDVT, M) *> The last M - K columns of VT**T contain the deflated *> right singular vectors. *> \endverbatim *> *> \param[in] LDVT *> \verbatim *> LDVT is INTEGER *> The leading dimension of the array VT. LDVT >= N. *> \endverbatim *> *> \param[in,out] VT2 *> \verbatim *> VT2 is REAL array, dimension (LDVT2, N) *> The first K columns of VT2**T contain the non-deflated *> right singular vectors for the split problem. *> \endverbatim *> *> \param[in] LDVT2 *> \verbatim *> LDVT2 is INTEGER *> The leading dimension of the array VT2. LDVT2 >= N. *> \endverbatim *> *> \param[in] IDXC *> \verbatim *> IDXC is INTEGER array, dimension (N) *> The permutation used to arrange the columns of U (and rows of *> VT) into three groups: the first group contains non-zero *> entries only at and above (or before) NL +1; the second *> contains non-zero entries only at and below (or after) NL+2; *> and the third is dense. The first column of U and the row of *> VT are treated separately, however. *> *> The rows of the singular vectors found by SLASD4 *> must be likewise permuted before the matrix multiplies can *> take place. *> \endverbatim *> *> \param[in] CTOT *> \verbatim *> CTOT is INTEGER array, dimension (4) *> A count of the total number of the various types of columns *> in U (or rows in VT), as described in IDXC. The fourth column *> type is any column which has been deflated. *> \endverbatim *> *> \param[in,out] Z *> \verbatim *> Z is REAL array, dimension (K) *> The first K elements of this array contain the components *> of the deflation-adjusted updating row vector. *> \endverbatim *> *> \param[out] INFO *> \verbatim *> INFO is INTEGER *> = 0: successful exit. *> < 0: if INFO = -i, the i-th argument had an illegal value. *> > 0: if INFO = 1, a singular value did not converge *> \endverbatim * * Authors: * ======== * *> \author Univ. of Tennessee *> \author Univ. of California Berkeley *> \author Univ. of Colorado Denver *> \author NAG Ltd. * *> \date June 2017 * *> \ingroup OTHERauxiliary * *> \par Contributors: * ================== *> *> Ming Gu and Huan Ren, Computer Science Division, University of *> California at Berkeley, USA *> * ===================================================================== SUBROUTINE SLASD3( NL, NR, SQRE, K, D, Q, LDQ, DSIGMA, U, LDU, U2, \$ LDU2, VT, LDVT, VT2, LDVT2, IDXC, CTOT, Z, \$ INFO ) * * -- LAPACK auxiliary routine (version 3.7.1) -- * -- LAPACK is a software package provided by Univ. of Tennessee, -- * -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- * June 2017 * * .. Scalar Arguments .. INTEGER INFO, K, LDQ, LDU, LDU2, LDVT, LDVT2, NL, NR, \$ SQRE * .. * .. Array Arguments .. INTEGER CTOT( * ), IDXC( * ) REAL D( * ), DSIGMA( * ), Q( LDQ, * ), U( LDU, * ), \$ U2( LDU2, * ), VT( LDVT, * ), VT2( LDVT2, * ), \$ Z( * ) * .. * * ===================================================================== * * .. Parameters .. REAL ONE, ZERO, NEGONE PARAMETER ( ONE = 1.0E+0, ZERO = 0.0E+0, \$ NEGONE = -1.0E+0 ) * .. * .. Local Scalars .. INTEGER CTEMP, I, J, JC, KTEMP, M, N, NLP1, NLP2, NRP1 REAL RHO, TEMP * .. * .. External Functions .. REAL SLAMC3, SNRM2 EXTERNAL SLAMC3, SNRM2 * .. * .. External Subroutines .. EXTERNAL SCOPY, SGEMM, SLACPY, SLASCL, SLASD4, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC ABS, SIGN, SQRT * .. * .. Executable Statements .. * * Test the input parameters. * INFO = 0 * IF( NL.LT.1 ) THEN INFO = -1 ELSE IF( NR.LT.1 ) THEN INFO = -2 ELSE IF( ( SQRE.NE.1 ) .AND. ( SQRE.NE.0 ) ) THEN INFO = -3 END IF * N = NL + NR + 1 M = N + SQRE NLP1 = NL + 1 NLP2 = NL + 2 * IF( ( K.LT.1 ) .OR. ( K.GT.N ) ) THEN INFO = -4 ELSE IF( LDQ.LT.K ) THEN INFO = -7 ELSE IF( LDU.LT.N ) THEN INFO = -10 ELSE IF( LDU2.LT.N ) THEN INFO = -12 ELSE IF( LDVT.LT.M ) THEN INFO = -14 ELSE IF( LDVT2.LT.M ) THEN INFO = -16 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'SLASD3', -INFO ) RETURN END IF * * Quick return if possible * IF( K.EQ.1 ) THEN D( 1 ) = ABS( Z( 1 ) ) CALL SCOPY( M, VT2( 1, 1 ), LDVT2, VT( 1, 1 ), LDVT ) IF( Z( 1 ).GT.ZERO ) THEN CALL SCOPY( N, U2( 1, 1 ), 1, U( 1, 1 ), 1 ) ELSE DO 10 I = 1, N U( I, 1 ) = -U2( I, 1 ) 10 CONTINUE END IF RETURN END IF * * Modify values DSIGMA(i) to make sure all DSIGMA(i)-DSIGMA(j) can * be computed with high relative accuracy (barring over/underflow). * This is a problem on machines without a guard digit in * add/subtract (Cray XMP, Cray YMP, Cray C 90 and Cray 2). * The following code replaces DSIGMA(I) by 2*DSIGMA(I)-DSIGMA(I), * which on any of these machines zeros out the bottommost * bit of DSIGMA(I) if it is 1; this makes the subsequent * subtractions DSIGMA(I)-DSIGMA(J) unproblematic when cancellation * occurs. On binary machines with a guard digit (almost all * machines) it does not change DSIGMA(I) at all. On hexadecimal * and decimal machines with a guard digit, it slightly * changes the bottommost bits of DSIGMA(I). It does not account * for hexadecimal or decimal machines without guard digits * (we know of none). We use a subroutine call to compute * 2*DSIGMA(I) to prevent optimizing compilers from eliminating * this code. * DO 20 I = 1, K DSIGMA( I ) = SLAMC3( DSIGMA( I ), DSIGMA( I ) ) - DSIGMA( I ) 20 CONTINUE * * Keep a copy of Z. * CALL SCOPY( K, Z, 1, Q, 1 ) * * Normalize Z. * RHO = SNRM2( K, Z, 1 ) CALL SLASCL( 'G', 0, 0, RHO, ONE, K, 1, Z, K, INFO ) RHO = RHO*RHO * * Find the new singular values. * DO 30 J = 1, K CALL SLASD4( K, J, DSIGMA, Z, U( 1, J ), RHO, D( J ), \$ VT( 1, J ), INFO ) * * If the zero finder fails, report the convergence failure. * IF( INFO.NE.0 ) THEN RETURN END IF 30 CONTINUE * * Compute updated Z. * DO 60 I = 1, K Z( I ) = U( I, K )*VT( I, K ) DO 40 J = 1, I - 1 Z( I ) = Z( I )*( U( I, J )*VT( I, J ) / \$ ( DSIGMA( I )-DSIGMA( J ) ) / \$ ( DSIGMA( I )+DSIGMA( J ) ) ) 40 CONTINUE DO 50 J = I, K - 1 Z( I ) = Z( I )*( U( I, J )*VT( I, J ) / \$ ( DSIGMA( I )-DSIGMA( J+1 ) ) / \$ ( DSIGMA( I )+DSIGMA( J+1 ) ) ) 50 CONTINUE Z( I ) = SIGN( SQRT( ABS( Z( I ) ) ), Q( I, 1 ) ) 60 CONTINUE * * Compute left singular vectors of the modified diagonal matrix, * and store related information for the right singular vectors. * DO 90 I = 1, K VT( 1, I ) = Z( 1 ) / U( 1, I ) / VT( 1, I ) U( 1, I ) = NEGONE DO 70 J = 2, K VT( J, I ) = Z( J ) / U( J, I ) / VT( J, I ) U( J, I ) = DSIGMA( J )*VT( J, I ) 70 CONTINUE TEMP = SNRM2( K, U( 1, I ), 1 ) Q( 1, I ) = U( 1, I ) / TEMP DO 80 J = 2, K JC = IDXC( J ) Q( J, I ) = U( JC, I ) / TEMP 80 CONTINUE 90 CONTINUE * * Update the left singular vector matrix. * IF( K.EQ.2 ) THEN CALL SGEMM( 'N', 'N', N, K, K, ONE, U2, LDU2, Q, LDQ, ZERO, U, \$ LDU ) GO TO 100 END IF IF( CTOT( 1 ).GT.0 ) THEN CALL SGEMM( 'N', 'N', NL, K, CTOT( 1 ), ONE, U2( 1, 2 ), LDU2, \$ Q( 2, 1 ), LDQ, ZERO, U( 1, 1 ), LDU ) IF( CTOT( 3 ).GT.0 ) THEN KTEMP = 2 + CTOT( 1 ) + CTOT( 2 ) CALL SGEMM( 'N', 'N', NL, K, CTOT( 3 ), ONE, U2( 1, KTEMP ), \$ LDU2, Q( KTEMP, 1 ), LDQ, ONE, U( 1, 1 ), LDU ) END IF ELSE IF( CTOT( 3 ).GT.0 ) THEN KTEMP = 2 + CTOT( 1 ) + CTOT( 2 ) CALL SGEMM( 'N', 'N', NL, K, CTOT( 3 ), ONE, U2( 1, KTEMP ), \$ LDU2, Q( KTEMP, 1 ), LDQ, ZERO, U( 1, 1 ), LDU ) ELSE CALL SLACPY( 'F', NL, K, U2, LDU2, U, LDU ) END IF CALL SCOPY( K, Q( 1, 1 ), LDQ, U( NLP1, 1 ), LDU ) KTEMP = 2 + CTOT( 1 ) CTEMP = CTOT( 2 ) + CTOT( 3 ) CALL SGEMM( 'N', 'N', NR, K, CTEMP, ONE, U2( NLP2, KTEMP ), LDU2, \$ Q( KTEMP, 1 ), LDQ, ZERO, U( NLP2, 1 ), LDU ) * * Generate the right singular vectors. * 100 CONTINUE DO 120 I = 1, K TEMP = SNRM2( K, VT( 1, I ), 1 ) Q( I, 1 ) = VT( 1, I ) / TEMP DO 110 J = 2, K JC = IDXC( J ) Q( I, J ) = VT( JC, I ) / TEMP 110 CONTINUE 120 CONTINUE * * Update the right singular vector matrix. * IF( K.EQ.2 ) THEN CALL SGEMM( 'N', 'N', K, M, K, ONE, Q, LDQ, VT2, LDVT2, ZERO, \$ VT, LDVT ) RETURN END IF KTEMP = 1 + CTOT( 1 ) CALL SGEMM( 'N', 'N', K, NLP1, KTEMP, ONE, Q( 1, 1 ), LDQ, \$ VT2( 1, 1 ), LDVT2, ZERO, VT( 1, 1 ), LDVT ) KTEMP = 2 + CTOT( 1 ) + CTOT( 2 ) IF( KTEMP.LE.LDVT2 ) \$ CALL SGEMM( 'N', 'N', K, NLP1, CTOT( 3 ), ONE, Q( 1, KTEMP ), \$ LDQ, VT2( KTEMP, 1 ), LDVT2, ONE, VT( 1, 1 ), \$ LDVT ) * KTEMP = CTOT( 1 ) + 1 NRP1 = NR + SQRE IF( KTEMP.GT.1 ) THEN DO 130 I = 1, K Q( I, KTEMP ) = Q( I, 1 ) 130 CONTINUE DO 140 I = NLP2, M VT2( KTEMP, I ) = VT2( 1, I ) 140 CONTINUE END IF CTEMP = 1 + CTOT( 2 ) + CTOT( 3 ) CALL SGEMM( 'N', 'N', K, NRP1, CTEMP, ONE, Q( 1, KTEMP ), LDQ, \$ VT2( KTEMP, NLP2 ), LDVT2, ZERO, VT( 1, NLP2 ), LDVT ) * RETURN * * End of SLASD3 * END