SUBROUTINE SLATDF( IJOB, N, Z, LDZ, RHS, RDSUM, RDSCAL, IPIV, $ JPIV ) * * -- LAPACK auxiliary routine (version 3.2) -- * -- LAPACK is a software package provided by Univ. of Tennessee, -- * -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- * November 2006 * * .. Scalar Arguments .. INTEGER IJOB, LDZ, N REAL RDSCAL, RDSUM * .. * .. Array Arguments .. INTEGER IPIV( * ), JPIV( * ) REAL RHS( * ), Z( LDZ, * ) * .. * * Purpose * ======= * * SLATDF uses the LU factorization of the n-by-n matrix Z computed by * SGETC2 and computes a contribution to the reciprocal Dif-estimate * by solving Z * x = b for x, and choosing the r.h.s. b such that * the norm of x is as large as possible. On entry RHS = b holds the * contribution from earlier solved sub-systems, and on return RHS = x. * * The factorization of Z returned by SGETC2 has the form Z = P*L*U*Q, * where P and Q are permutation matrices. L is lower triangular with * unit diagonal elements and U is upper triangular. * * Arguments * ========= * * IJOB (input) INTEGER * IJOB = 2: First compute an approximative null-vector e * of Z using SGECON, e is normalized and solve for * Zx = +-e - f with the sign giving the greater value * of 2-norm(x). About 5 times as expensive as Default. * IJOB .ne. 2: Local look ahead strategy where all entries of * the r.h.s. b is choosen as either +1 or -1 (Default). * * N (input) INTEGER * The number of columns of the matrix Z. * * Z (input) REAL array, dimension (LDZ, N) * On entry, the LU part of the factorization of the n-by-n * matrix Z computed by SGETC2: Z = P * L * U * Q * * LDZ (input) INTEGER * The leading dimension of the array Z. LDA >= max(1, N). * * RHS (input/output) REAL array, dimension N. * On entry, RHS contains contributions from other subsystems. * On exit, RHS contains the solution of the subsystem with * entries acoording to the value of IJOB (see above). * * RDSUM (input/output) REAL * On entry, the sum of squares of computed contributions to * the Dif-estimate under computation by STGSYL, where the * scaling factor RDSCAL (see below) has been factored out. * On exit, the corresponding sum of squares updated with the * contributions from the current sub-system. * If TRANS = 'T' RDSUM is not touched. * NOTE: RDSUM only makes sense when STGSY2 is called by STGSYL. * * RDSCAL (input/output) REAL * On entry, scaling factor used to prevent overflow in RDSUM. * On exit, RDSCAL is updated w.r.t. the current contributions * in RDSUM. * If TRANS = 'T', RDSCAL is not touched. * NOTE: RDSCAL only makes sense when STGSY2 is called by * STGSYL. * * IPIV (input) INTEGER array, dimension (N). * The pivot indices; for 1 <= i <= N, row i of the * matrix has been interchanged with row IPIV(i). * * JPIV (input) INTEGER array, dimension (N). * The pivot indices; for 1 <= j <= N, column j of the * matrix has been interchanged with column JPIV(j). * * Further Details * =============== * * Based on contributions by * Bo Kagstrom and Peter Poromaa, Department of Computing Science, * Umea University, S-901 87 Umea, Sweden. * * This routine is a further developed implementation of algorithm * BSOLVE in [1] using complete pivoting in the LU factorization. * * [1] Bo Kagstrom and Lars Westin, * Generalized Schur Methods with Condition Estimators for * Solving the Generalized Sylvester Equation, IEEE Transactions * on Automatic Control, Vol. 34, No. 7, July 1989, pp 745-751. * * [2] Peter Poromaa, * On Efficient and Robust Estimators for the Separation * between two Regular Matrix Pairs with Applications in * Condition Estimation. Report IMINF-95.05, Departement of * Computing Science, Umea University, S-901 87 Umea, Sweden, 1995. * * ===================================================================== * * .. Parameters .. INTEGER MAXDIM PARAMETER ( MAXDIM = 8 ) REAL ZERO, ONE PARAMETER ( ZERO = 0.0E+0, ONE = 1.0E+0 ) * .. * .. Local Scalars .. INTEGER I, INFO, J, K REAL BM, BP, PMONE, SMINU, SPLUS, TEMP * .. * .. Local Arrays .. INTEGER IWORK( MAXDIM ) REAL WORK( 4*MAXDIM ), XM( MAXDIM ), XP( MAXDIM ) * .. * .. External Subroutines .. EXTERNAL SAXPY, SCOPY, SGECON, SGESC2, SLASSQ, SLASWP, $ SSCAL * .. * .. External Functions .. REAL SASUM, SDOT EXTERNAL SASUM, SDOT * .. * .. Intrinsic Functions .. INTRINSIC ABS, SQRT * .. * .. Executable Statements .. * IF( IJOB.NE.2 ) THEN * * Apply permutations IPIV to RHS * CALL SLASWP( 1, RHS, LDZ, 1, N-1, IPIV, 1 ) * * Solve for L-part choosing RHS either to +1 or -1. * PMONE = -ONE * DO 10 J = 1, N - 1 BP = RHS( J ) + ONE BM = RHS( J ) - ONE SPLUS = ONE * * Look-ahead for L-part RHS(1:N-1) = + or -1, SPLUS and * SMIN computed more efficiently than in BSOLVE [1]. * SPLUS = SPLUS + SDOT( N-J, Z( J+1, J ), 1, Z( J+1, J ), 1 ) SMINU = SDOT( N-J, Z( J+1, J ), 1, RHS( J+1 ), 1 ) SPLUS = SPLUS*RHS( J ) IF( SPLUS.GT.SMINU ) THEN RHS( J ) = BP ELSE IF( SMINU.GT.SPLUS ) THEN RHS( J ) = BM ELSE * * In this case the updating sums are equal and we can * choose RHS(J) +1 or -1. The first time this happens * we choose -1, thereafter +1. This is a simple way to * get good estimates of matrices like Byers well-known * example (see [1]). (Not done in BSOLVE.) * RHS( J ) = RHS( J ) + PMONE PMONE = ONE END IF * * Compute the remaining r.h.s. * TEMP = -RHS( J ) CALL SAXPY( N-J, TEMP, Z( J+1, J ), 1, RHS( J+1 ), 1 ) * 10 CONTINUE * * Solve for U-part, look-ahead for RHS(N) = +-1. This is not done * in BSOLVE and will hopefully give us a better estimate because * any ill-conditioning of the original matrix is transfered to U * and not to L. U(N, N) is an approximation to sigma_min(LU). * CALL SCOPY( N-1, RHS, 1, XP, 1 ) XP( N ) = RHS( N ) + ONE RHS( N ) = RHS( N ) - ONE SPLUS = ZERO SMINU = ZERO DO 30 I = N, 1, -1 TEMP = ONE / Z( I, I ) XP( I ) = XP( I )*TEMP RHS( I ) = RHS( I )*TEMP DO 20 K = I + 1, N XP( I ) = XP( I ) - XP( K )*( Z( I, K )*TEMP ) RHS( I ) = RHS( I ) - RHS( K )*( Z( I, K )*TEMP ) 20 CONTINUE SPLUS = SPLUS + ABS( XP( I ) ) SMINU = SMINU + ABS( RHS( I ) ) 30 CONTINUE IF( SPLUS.GT.SMINU ) $ CALL SCOPY( N, XP, 1, RHS, 1 ) * * Apply the permutations JPIV to the computed solution (RHS) * CALL SLASWP( 1, RHS, LDZ, 1, N-1, JPIV, -1 ) * * Compute the sum of squares * CALL SLASSQ( N, RHS, 1, RDSCAL, RDSUM ) * ELSE * * IJOB = 2, Compute approximate nullvector XM of Z * CALL SGECON( 'I', N, Z, LDZ, ONE, TEMP, WORK, IWORK, INFO ) CALL SCOPY( N, WORK( N+1 ), 1, XM, 1 ) * * Compute RHS * CALL SLASWP( 1, XM, LDZ, 1, N-1, IPIV, -1 ) TEMP = ONE / SQRT( SDOT( N, XM, 1, XM, 1 ) ) CALL SSCAL( N, TEMP, XM, 1 ) CALL SCOPY( N, XM, 1, XP, 1 ) CALL SAXPY( N, ONE, RHS, 1, XP, 1 ) CALL SAXPY( N, -ONE, XM, 1, RHS, 1 ) CALL SGESC2( N, Z, LDZ, RHS, IPIV, JPIV, TEMP ) CALL SGESC2( N, Z, LDZ, XP, IPIV, JPIV, TEMP ) IF( SASUM( N, XP, 1 ).GT.SASUM( N, RHS, 1 ) ) $ CALL SCOPY( N, XP, 1, RHS, 1 ) * * Compute the sum of squares * CALL SLASSQ( N, RHS, 1, RDSCAL, RDSUM ) * END IF * RETURN * * End of SLATDF * END