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|
*> \brief \b SLA_GBRFSX_EXTENDED improves the computed solution to a system of linear equations for general banded matrices by performing extra-precise iterative refinement and provides error bounds and backward error estimates for the solution.
*
* =========== DOCUMENTATION ===========
*
* Online html documentation available at
* http://www.netlib.org/lapack/explore-html/
*
*> \htmlonly
*> Download SLA_GBRFSX_EXTENDED + dependencies
*> <a href="http://www.netlib.org/cgi-bin/netlibfiles.tgz?format=tgz&filename=/lapack/lapack_routine/sla_gbrfsx_extended.f">
*> [TGZ]</a>
*> <a href="http://www.netlib.org/cgi-bin/netlibfiles.zip?format=zip&filename=/lapack/lapack_routine/sla_gbrfsx_extended.f">
*> [ZIP]</a>
*> <a href="http://www.netlib.org/cgi-bin/netlibfiles.txt?format=txt&filename=/lapack/lapack_routine/sla_gbrfsx_extended.f">
*> [TXT]</a>
*> \endhtmlonly
*
* Definition:
* ===========
*
* SUBROUTINE SLA_GBRFSX_EXTENDED( PREC_TYPE, TRANS_TYPE, N, KL, KU,
* NRHS, AB, LDAB, AFB, LDAFB, IPIV,
* COLEQU, C, B, LDB, Y, LDY,
* BERR_OUT, N_NORMS, ERR_BNDS_NORM,
* ERR_BNDS_COMP, RES, AYB, DY,
* Y_TAIL, RCOND, ITHRESH, RTHRESH,
* DZ_UB, IGNORE_CWISE, INFO )
*
* .. Scalar Arguments ..
* INTEGER INFO, LDAB, LDAFB, LDB, LDY, N, KL, KU, NRHS,
* $ PREC_TYPE, TRANS_TYPE, N_NORMS, ITHRESH
* LOGICAL COLEQU, IGNORE_CWISE
* REAL RTHRESH, DZ_UB
* ..
* .. Array Arguments ..
* INTEGER IPIV( * )
* REAL AB( LDAB, * ), AFB( LDAFB, * ), B( LDB, * ),
* $ Y( LDY, * ), RES(*), DY(*), Y_TAIL(*)
* REAL C( * ), AYB(*), RCOND, BERR_OUT(*),
* $ ERR_BNDS_NORM( NRHS, * ),
* $ ERR_BNDS_COMP( NRHS, * )
* ..
*
*
*> \par Purpose:
* =============
*>
*> \verbatim
*>
*> SLA_GBRFSX_EXTENDED improves the computed solution to a system of
*> linear equations by performing extra-precise iterative refinement
*> and provides error bounds and backward error estimates for the solution.
*> This subroutine is called by SGBRFSX to perform iterative refinement.
*> In addition to normwise error bound, the code provides maximum
*> componentwise error bound if possible. See comments for ERR_BNDS_NORM
*> and ERR_BNDS_COMP for details of the error bounds. Note that this
*> subroutine is only resonsible for setting the second fields of
*> ERR_BNDS_NORM and ERR_BNDS_COMP.
*> \endverbatim
*
* Arguments:
* ==========
*
*> \param[in] PREC_TYPE
*> \verbatim
*> PREC_TYPE is INTEGER
*> Specifies the intermediate precision to be used in refinement.
*> The value is defined by ILAPREC(P) where P is a CHARACTER and
*> P = 'S': Single
*> = 'D': Double
*> = 'I': Indigenous
*> = 'X', 'E': Extra
*> \endverbatim
*>
*> \param[in] TRANS_TYPE
*> \verbatim
*> TRANS_TYPE is INTEGER
*> Specifies the transposition operation on A.
*> The value is defined by ILATRANS(T) where T is a CHARACTER and
*> T = 'N': No transpose
*> = 'T': Transpose
*> = 'C': Conjugate transpose
*> \endverbatim
*>
*> \param[in] N
*> \verbatim
*> N is INTEGER
*> The number of linear equations, i.e., the order of the
*> matrix A. N >= 0.
*> \endverbatim
*>
*> \param[in] KL
*> \verbatim
*> KL is INTEGER
*> The number of subdiagonals within the band of A. KL >= 0.
*> \endverbatim
*>
*> \param[in] KU
*> \verbatim
*> KU is INTEGER
*> The number of superdiagonals within the band of A. KU >= 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.
*> \endverbatim
*>
*> \param[in] AB
*> \verbatim
*> AB is REAL array, dimension (LDAB,N)
*> On entry, the N-by-N matrix AB.
*> \endverbatim
*>
*> \param[in] LDAB
*> \verbatim
*> LDAB is INTEGER
*> The leading dimension of the array AB. LDAB >= max(1,N).
*> \endverbatim
*>
*> \param[in] AFB
*> \verbatim
*> AFB is REAL array, dimension (LDAFB,N)
*> The factors L and U from the factorization
*> A = P*L*U as computed by SGBTRF.
*> \endverbatim
*>
*> \param[in] LDAFB
*> \verbatim
*> LDAFB is INTEGER
*> The leading dimension of the array AF. LDAFB >= max(1,N).
*> \endverbatim
*>
*> \param[in] IPIV
*> \verbatim
*> IPIV is INTEGER array, dimension (N)
*> The pivot indices from the factorization A = P*L*U
*> as computed by SGBTRF; row i of the matrix was interchanged
*> with row IPIV(i).
*> \endverbatim
*>
*> \param[in] COLEQU
*> \verbatim
*> COLEQU is LOGICAL
*> If .TRUE. then column equilibration was done to A before calling
*> this routine. This is needed to compute the solution and error
*> bounds correctly.
*> \endverbatim
*>
*> \param[in] C
*> \verbatim
*> C is REAL array, dimension (N)
*> The column scale factors for A. If COLEQU = .FALSE., C
*> is not accessed. If C is input, each element of C should be a power
*> of the radix to ensure a reliable solution and error estimates.
*> Scaling by powers of the radix does not cause rounding errors unless
*> the result underflows or overflows. Rounding errors during scaling
*> lead to refining with a matrix that is not equivalent to the
*> input matrix, producing error estimates that may not be
*> reliable.
*> \endverbatim
*>
*> \param[in] B
*> \verbatim
*> B is REAL array, dimension (LDB,NRHS)
*> The right-hand-side matrix B.
*> \endverbatim
*>
*> \param[in] LDB
*> \verbatim
*> LDB is INTEGER
*> The leading dimension of the array B. LDB >= max(1,N).
*> \endverbatim
*>
*> \param[in,out] Y
*> \verbatim
*> Y is REAL array, dimension (LDY,NRHS)
*> On entry, the solution matrix X, as computed by SGBTRS.
*> On exit, the improved solution matrix Y.
*> \endverbatim
*>
*> \param[in] LDY
*> \verbatim
*> LDY is INTEGER
*> The leading dimension of the array Y. LDY >= max(1,N).
*> \endverbatim
*>
*> \param[out] BERR_OUT
*> \verbatim
*> BERR_OUT is REAL array, dimension (NRHS)
*> On exit, BERR_OUT(j) contains the componentwise relative backward
*> error for right-hand-side j from the formula
*> max(i) ( abs(RES(i)) / ( abs(op(A_s))*abs(Y) + abs(B_s) )(i) )
*> where abs(Z) is the componentwise absolute value of the matrix
*> or vector Z. This is computed by SLA_LIN_BERR.
*> \endverbatim
*>
*> \param[in] N_NORMS
*> \verbatim
*> N_NORMS is INTEGER
*> Determines which error bounds to return (see ERR_BNDS_NORM
*> and ERR_BNDS_COMP).
*> If N_NORMS >= 1 return normwise error bounds.
*> If N_NORMS >= 2 return componentwise error bounds.
*> \endverbatim
*>
*> \param[in,out] ERR_BNDS_NORM
*> \verbatim
*> ERR_BNDS_NORM is REAL array, dimension
*> (NRHS, N_ERR_BNDS)
*> For each right-hand side, this array contains information about
*> various error bounds and condition numbers corresponding to the
*> normwise relative error, which is defined as follows:
*>
*> Normwise relative error in the ith solution vector:
*> max_j (abs(XTRUE(j,i) - X(j,i)))
*> ------------------------------
*> max_j abs(X(j,i))
*>
*> The array is indexed by the type of error information as described
*> below. There currently are up to three pieces of information
*> returned.
*>
*> The first index in ERR_BNDS_NORM(i,:) corresponds to the ith
*> right-hand side.
*>
*> The second index in ERR_BNDS_NORM(:,err) contains the following
*> three fields:
*> err = 1 "Trust/don't trust" boolean. Trust the answer if the
*> reciprocal condition number is less than the threshold
*> sqrt(n) * slamch('Epsilon').
*>
*> err = 2 "Guaranteed" error bound: The estimated forward error,
*> almost certainly within a factor of 10 of the true error
*> so long as the next entry is greater than the threshold
*> sqrt(n) * slamch('Epsilon'). This error bound should only
*> be trusted if the previous boolean is true.
*>
*> err = 3 Reciprocal condition number: Estimated normwise
*> reciprocal condition number. Compared with the threshold
*> sqrt(n) * slamch('Epsilon') to determine if the error
*> estimate is "guaranteed". These reciprocal condition
*> numbers are 1 / (norm(Z^{-1},inf) * norm(Z,inf)) for some
*> appropriately scaled matrix Z.
*> Let Z = S*A, where S scales each row by a power of the
*> radix so all absolute row sums of Z are approximately 1.
*>
*> This subroutine is only responsible for setting the second field
*> above.
*> See Lapack Working Note 165 for further details and extra
*> cautions.
*> \endverbatim
*>
*> \param[in,out] ERR_BNDS_COMP
*> \verbatim
*> ERR_BNDS_COMP is REAL array, dimension
*> (NRHS, N_ERR_BNDS)
*> For each right-hand side, this array contains information about
*> various error bounds and condition numbers corresponding to the
*> componentwise relative error, which is defined as follows:
*>
*> Componentwise relative error in the ith solution vector:
*> abs(XTRUE(j,i) - X(j,i))
*> max_j ----------------------
*> abs(X(j,i))
*>
*> The array is indexed by the right-hand side i (on which the
*> componentwise relative error depends), and the type of error
*> information as described below. There currently are up to three
*> pieces of information returned for each right-hand side. If
*> componentwise accuracy is not requested (PARAMS(3) = 0.0), then
*> ERR_BNDS_COMP is not accessed. If N_ERR_BNDS .LT. 3, then at most
*> the first (:,N_ERR_BNDS) entries are returned.
*>
*> The first index in ERR_BNDS_COMP(i,:) corresponds to the ith
*> right-hand side.
*>
*> The second index in ERR_BNDS_COMP(:,err) contains the following
*> three fields:
*> err = 1 "Trust/don't trust" boolean. Trust the answer if the
*> reciprocal condition number is less than the threshold
*> sqrt(n) * slamch('Epsilon').
*>
*> err = 2 "Guaranteed" error bound: The estimated forward error,
*> almost certainly within a factor of 10 of the true error
*> so long as the next entry is greater than the threshold
*> sqrt(n) * slamch('Epsilon'). This error bound should only
*> be trusted if the previous boolean is true.
*>
*> err = 3 Reciprocal condition number: Estimated componentwise
*> reciprocal condition number. Compared with the threshold
*> sqrt(n) * slamch('Epsilon') to determine if the error
*> estimate is "guaranteed". These reciprocal condition
*> numbers are 1 / (norm(Z^{-1},inf) * norm(Z,inf)) for some
*> appropriately scaled matrix Z.
*> Let Z = S*(A*diag(x)), where x is the solution for the
*> current right-hand side and S scales each row of
*> A*diag(x) by a power of the radix so all absolute row
*> sums of Z are approximately 1.
*>
*> This subroutine is only responsible for setting the second field
*> above.
*> See Lapack Working Note 165 for further details and extra
*> cautions.
*> \endverbatim
*>
*> \param[in] RES
*> \verbatim
*> RES is REAL array, dimension (N)
*> Workspace to hold the intermediate residual.
*> \endverbatim
*>
*> \param[in] AYB
*> \verbatim
*> AYB is REAL array, dimension (N)
*> Workspace. This can be the same workspace passed for Y_TAIL.
*> \endverbatim
*>
*> \param[in] DY
*> \verbatim
*> DY is REAL array, dimension (N)
*> Workspace to hold the intermediate solution.
*> \endverbatim
*>
*> \param[in] Y_TAIL
*> \verbatim
*> Y_TAIL is REAL array, dimension (N)
*> Workspace to hold the trailing bits of the intermediate solution.
*> \endverbatim
*>
*> \param[in] RCOND
*> \verbatim
*> RCOND is REAL
*> Reciprocal scaled condition number. This is an estimate of the
*> reciprocal Skeel condition number of the matrix A after
*> equilibration (if done). If this is less than the machine
*> precision (in particular, if it is zero), the matrix is singular
*> to working precision. Note that the error may still be small even
*> if this number is very small and the matrix appears ill-
*> conditioned.
*> \endverbatim
*>
*> \param[in] ITHRESH
*> \verbatim
*> ITHRESH is INTEGER
*> The maximum number of residual computations allowed for
*> refinement. The default is 10. For 'aggressive' set to 100 to
*> permit convergence using approximate factorizations or
*> factorizations other than LU. If the factorization uses a
*> technique other than Gaussian elimination, the guarantees in
*> ERR_BNDS_NORM and ERR_BNDS_COMP may no longer be trustworthy.
*> \endverbatim
*>
*> \param[in] RTHRESH
*> \verbatim
*> RTHRESH is REAL
*> Determines when to stop refinement if the error estimate stops
*> decreasing. Refinement will stop when the next solution no longer
*> satisfies norm(dx_{i+1}) < RTHRESH * norm(dx_i) where norm(Z) is
*> the infinity norm of Z. RTHRESH satisfies 0 < RTHRESH <= 1. The
*> default value is 0.5. For 'aggressive' set to 0.9 to permit
*> convergence on extremely ill-conditioned matrices. See LAWN 165
*> for more details.
*> \endverbatim
*>
*> \param[in] DZ_UB
*> \verbatim
*> DZ_UB is REAL
*> Determines when to start considering componentwise convergence.
*> Componentwise convergence is only considered after each component
*> of the solution Y is stable, which we definte as the relative
*> change in each component being less than DZ_UB. The default value
*> is 0.25, requiring the first bit to be stable. See LAWN 165 for
*> more details.
*> \endverbatim
*>
*> \param[in] IGNORE_CWISE
*> \verbatim
*> IGNORE_CWISE is LOGICAL
*> If .TRUE. then ignore componentwise convergence. Default value
*> is .FALSE..
*> \endverbatim
*>
*> \param[out] INFO
*> \verbatim
*> INFO is INTEGER
*> = 0: Successful exit.
*> < 0: if INFO = -i, the ith argument to SGBTRS had an illegal
*> value
*> \endverbatim
*
* Authors:
* ========
*
*> \author Univ. of Tennessee
*> \author Univ. of California Berkeley
*> \author Univ. of Colorado Denver
*> \author NAG Ltd.
*
*> \date September 2012
*
*> \ingroup realGBcomputational
*
* =====================================================================
SUBROUTINE SLA_GBRFSX_EXTENDED( PREC_TYPE, TRANS_TYPE, N, KL, KU,
$ NRHS, AB, LDAB, AFB, LDAFB, IPIV,
$ COLEQU, C, B, LDB, Y, LDY,
$ BERR_OUT, N_NORMS, ERR_BNDS_NORM,
$ ERR_BNDS_COMP, RES, AYB, DY,
$ Y_TAIL, RCOND, ITHRESH, RTHRESH,
$ DZ_UB, IGNORE_CWISE, INFO )
*
* -- LAPACK computational routine (version 3.4.2) --
* -- LAPACK is a software package provided by Univ. of Tennessee, --
* -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
* September 2012
*
* .. Scalar Arguments ..
INTEGER INFO, LDAB, LDAFB, LDB, LDY, N, KL, KU, NRHS,
$ PREC_TYPE, TRANS_TYPE, N_NORMS, ITHRESH
LOGICAL COLEQU, IGNORE_CWISE
REAL RTHRESH, DZ_UB
* ..
* .. Array Arguments ..
INTEGER IPIV( * )
REAL AB( LDAB, * ), AFB( LDAFB, * ), B( LDB, * ),
$ Y( LDY, * ), RES(*), DY(*), Y_TAIL(*)
REAL C( * ), AYB(*), RCOND, BERR_OUT(*),
$ ERR_BNDS_NORM( NRHS, * ),
$ ERR_BNDS_COMP( NRHS, * )
* ..
*
* =====================================================================
*
* .. Local Scalars ..
CHARACTER TRANS
INTEGER CNT, I, J, M, X_STATE, Z_STATE, Y_PREC_STATE
REAL YK, DYK, YMIN, NORMY, NORMX, NORMDX, DXRAT,
$ DZRAT, PREVNORMDX, PREV_DZ_Z, DXRATMAX,
$ DZRATMAX, DX_X, DZ_Z, FINAL_DX_X, FINAL_DZ_Z,
$ EPS, HUGEVAL, INCR_THRESH
LOGICAL INCR_PREC
* ..
* .. Parameters ..
INTEGER UNSTABLE_STATE, WORKING_STATE, CONV_STATE,
$ NOPROG_STATE, BASE_RESIDUAL, EXTRA_RESIDUAL,
$ EXTRA_Y
PARAMETER ( UNSTABLE_STATE = 0, WORKING_STATE = 1,
$ CONV_STATE = 2, NOPROG_STATE = 3 )
PARAMETER ( BASE_RESIDUAL = 0, EXTRA_RESIDUAL = 1,
$ EXTRA_Y = 2 )
INTEGER FINAL_NRM_ERR_I, FINAL_CMP_ERR_I, BERR_I
INTEGER RCOND_I, NRM_RCOND_I, NRM_ERR_I, CMP_RCOND_I
INTEGER CMP_ERR_I, PIV_GROWTH_I
PARAMETER ( FINAL_NRM_ERR_I = 1, FINAL_CMP_ERR_I = 2,
$ BERR_I = 3 )
PARAMETER ( RCOND_I = 4, NRM_RCOND_I = 5, NRM_ERR_I = 6 )
PARAMETER ( CMP_RCOND_I = 7, CMP_ERR_I = 8,
$ PIV_GROWTH_I = 9 )
INTEGER LA_LINRX_ITREF_I, LA_LINRX_ITHRESH_I,
$ LA_LINRX_CWISE_I
PARAMETER ( LA_LINRX_ITREF_I = 1,
$ LA_LINRX_ITHRESH_I = 2 )
PARAMETER ( LA_LINRX_CWISE_I = 3 )
INTEGER LA_LINRX_TRUST_I, LA_LINRX_ERR_I,
$ LA_LINRX_RCOND_I
PARAMETER ( LA_LINRX_TRUST_I = 1, LA_LINRX_ERR_I = 2 )
PARAMETER ( LA_LINRX_RCOND_I = 3 )
* ..
* .. External Subroutines ..
EXTERNAL SAXPY, SCOPY, SGBTRS, SGBMV, BLAS_SGBMV_X,
$ BLAS_SGBMV2_X, SLA_GBAMV, SLA_WWADDW, SLAMCH,
$ CHLA_TRANSTYPE, SLA_LIN_BERR
REAL SLAMCH
CHARACTER CHLA_TRANSTYPE
* ..
* .. Intrinsic Functions ..
INTRINSIC ABS, MAX, MIN
* ..
* .. Executable Statements ..
*
IF (INFO.NE.0) RETURN
TRANS = CHLA_TRANSTYPE(TRANS_TYPE)
EPS = SLAMCH( 'Epsilon' )
HUGEVAL = SLAMCH( 'Overflow' )
* Force HUGEVAL to Inf
HUGEVAL = HUGEVAL * HUGEVAL
* Using HUGEVAL may lead to spurious underflows.
INCR_THRESH = REAL( N ) * EPS
M = KL+KU+1
DO J = 1, NRHS
Y_PREC_STATE = EXTRA_RESIDUAL
IF ( Y_PREC_STATE .EQ. EXTRA_Y ) THEN
DO I = 1, N
Y_TAIL( I ) = 0.0
END DO
END IF
DXRAT = 0.0
DXRATMAX = 0.0
DZRAT = 0.0
DZRATMAX = 0.0
FINAL_DX_X = HUGEVAL
FINAL_DZ_Z = HUGEVAL
PREVNORMDX = HUGEVAL
PREV_DZ_Z = HUGEVAL
DZ_Z = HUGEVAL
DX_X = HUGEVAL
X_STATE = WORKING_STATE
Z_STATE = UNSTABLE_STATE
INCR_PREC = .FALSE.
DO CNT = 1, ITHRESH
*
* Compute residual RES = B_s - op(A_s) * Y,
* op(A) = A, A**T, or A**H depending on TRANS (and type).
*
CALL SCOPY( N, B( 1, J ), 1, RES, 1 )
IF ( Y_PREC_STATE .EQ. BASE_RESIDUAL ) THEN
CALL SGBMV( TRANS, M, N, KL, KU, -1.0, AB, LDAB,
$ Y( 1, J ), 1, 1.0, RES, 1 )
ELSE IF ( Y_PREC_STATE .EQ. EXTRA_RESIDUAL ) THEN
CALL BLAS_SGBMV_X( TRANS_TYPE, N, N, KL, KU,
$ -1.0, AB, LDAB, Y( 1, J ), 1, 1.0, RES, 1,
$ PREC_TYPE )
ELSE
CALL BLAS_SGBMV2_X( TRANS_TYPE, N, N, KL, KU, -1.0,
$ AB, LDAB, Y( 1, J ), Y_TAIL, 1, 1.0, RES, 1,
$ PREC_TYPE )
END IF
! XXX: RES is no longer needed.
CALL SCOPY( N, RES, 1, DY, 1 )
CALL SGBTRS( TRANS, N, KL, KU, 1, AFB, LDAFB, IPIV, DY, N,
$ INFO )
*
* Calculate relative changes DX_X, DZ_Z and ratios DXRAT, DZRAT.
*
NORMX = 0.0
NORMY = 0.0
NORMDX = 0.0
DZ_Z = 0.0
YMIN = HUGEVAL
DO I = 1, N
YK = ABS( Y( I, J ) )
DYK = ABS( DY( I ) )
IF ( YK .NE. 0.0 ) THEN
DZ_Z = MAX( DZ_Z, DYK / YK )
ELSE IF ( DYK .NE. 0.0 ) THEN
DZ_Z = HUGEVAL
END IF
YMIN = MIN( YMIN, YK )
NORMY = MAX( NORMY, YK )
IF ( COLEQU ) THEN
NORMX = MAX( NORMX, YK * C( I ) )
NORMDX = MAX( NORMDX, DYK * C( I ) )
ELSE
NORMX = NORMY
NORMDX = MAX( NORMDX, DYK )
END IF
END DO
IF ( NORMX .NE. 0.0 ) THEN
DX_X = NORMDX / NORMX
ELSE IF ( NORMDX .EQ. 0.0 ) THEN
DX_X = 0.0
ELSE
DX_X = HUGEVAL
END IF
DXRAT = NORMDX / PREVNORMDX
DZRAT = DZ_Z / PREV_DZ_Z
*
* Check termination criteria.
*
IF ( .NOT.IGNORE_CWISE
$ .AND. YMIN*RCOND .LT. INCR_THRESH*NORMY
$ .AND. Y_PREC_STATE .LT. EXTRA_Y )
$ INCR_PREC = .TRUE.
IF ( X_STATE .EQ. NOPROG_STATE .AND. DXRAT .LE. RTHRESH )
$ X_STATE = WORKING_STATE
IF ( X_STATE .EQ. WORKING_STATE ) THEN
IF ( DX_X .LE. EPS ) THEN
X_STATE = CONV_STATE
ELSE IF ( DXRAT .GT. RTHRESH ) THEN
IF ( Y_PREC_STATE .NE. EXTRA_Y ) THEN
INCR_PREC = .TRUE.
ELSE
X_STATE = NOPROG_STATE
END IF
ELSE
IF ( DXRAT .GT. DXRATMAX ) DXRATMAX = DXRAT
END IF
IF ( X_STATE .GT. WORKING_STATE ) FINAL_DX_X = DX_X
END IF
IF ( Z_STATE .EQ. UNSTABLE_STATE .AND. DZ_Z .LE. DZ_UB )
$ Z_STATE = WORKING_STATE
IF ( Z_STATE .EQ. NOPROG_STATE .AND. DZRAT .LE. RTHRESH )
$ Z_STATE = WORKING_STATE
IF ( Z_STATE .EQ. WORKING_STATE ) THEN
IF ( DZ_Z .LE. EPS ) THEN
Z_STATE = CONV_STATE
ELSE IF ( DZ_Z .GT. DZ_UB ) THEN
Z_STATE = UNSTABLE_STATE
DZRATMAX = 0.0
FINAL_DZ_Z = HUGEVAL
ELSE IF ( DZRAT .GT. RTHRESH ) THEN
IF ( Y_PREC_STATE .NE. EXTRA_Y ) THEN
INCR_PREC = .TRUE.
ELSE
Z_STATE = NOPROG_STATE
END IF
ELSE
IF ( DZRAT .GT. DZRATMAX ) DZRATMAX = DZRAT
END IF
IF ( Z_STATE .GT. WORKING_STATE ) FINAL_DZ_Z = DZ_Z
END IF
*
* Exit if both normwise and componentwise stopped working,
* but if componentwise is unstable, let it go at least two
* iterations.
*
IF ( X_STATE.NE.WORKING_STATE ) THEN
IF ( IGNORE_CWISE ) GOTO 666
IF ( Z_STATE.EQ.NOPROG_STATE .OR. Z_STATE.EQ.CONV_STATE )
$ GOTO 666
IF ( Z_STATE.EQ.UNSTABLE_STATE .AND. CNT.GT.1 ) GOTO 666
END IF
IF ( INCR_PREC ) THEN
INCR_PREC = .FALSE.
Y_PREC_STATE = Y_PREC_STATE + 1
DO I = 1, N
Y_TAIL( I ) = 0.0
END DO
END IF
PREVNORMDX = NORMDX
PREV_DZ_Z = DZ_Z
*
* Update soluton.
*
IF (Y_PREC_STATE .LT. EXTRA_Y) THEN
CALL SAXPY( N, 1.0, DY, 1, Y(1,J), 1 )
ELSE
CALL SLA_WWADDW( N, Y(1,J), Y_TAIL, DY )
END IF
END DO
* Target of "IF (Z_STOP .AND. X_STOP)". Sun's f77 won't EXIT.
666 CONTINUE
*
* Set final_* when cnt hits ithresh.
*
IF ( X_STATE .EQ. WORKING_STATE ) FINAL_DX_X = DX_X
IF ( Z_STATE .EQ. WORKING_STATE ) FINAL_DZ_Z = DZ_Z
*
* Compute error bounds.
*
IF ( N_NORMS .GE. 1 ) THEN
ERR_BNDS_NORM( J, LA_LINRX_ERR_I ) =
$ FINAL_DX_X / (1 - DXRATMAX)
END IF
IF (N_NORMS .GE. 2) THEN
ERR_BNDS_COMP( J, LA_LINRX_ERR_I ) =
$ FINAL_DZ_Z / (1 - DZRATMAX)
END IF
*
* Compute componentwise relative backward error from formula
* max(i) ( abs(R(i)) / ( abs(op(A_s))*abs(Y) + abs(B_s) )(i) )
* where abs(Z) is the componentwise absolute value of the matrix
* or vector Z.
*
* Compute residual RES = B_s - op(A_s) * Y,
* op(A) = A, A**T, or A**H depending on TRANS (and type).
*
CALL SCOPY( N, B( 1, J ), 1, RES, 1 )
CALL SGBMV(TRANS, N, N, KL, KU, -1.0, AB, LDAB, Y(1,J),
$ 1, 1.0, RES, 1 )
DO I = 1, N
AYB( I ) = ABS( B( I, J ) )
END DO
*
* Compute abs(op(A_s))*abs(Y) + abs(B_s).
*
CALL SLA_GBAMV( TRANS_TYPE, N, N, KL, KU, 1.0,
$ AB, LDAB, Y(1, J), 1, 1.0, AYB, 1 )
CALL SLA_LIN_BERR( N, N, 1, RES, AYB, BERR_OUT( J ) )
*
* End of loop for each RHS
*
END DO
*
RETURN
END
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