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cla_gerfsx_extended.f(3)	    LAPACK	      cla_gerfsx_extended.f(3)

NAME
       cla_gerfsx_extended.f -

SYNOPSIS
   Functions/Subroutines
       subroutine cla_gerfsx_extended (PREC_TYPE, TRANS_TYPE, N, NRHS, A, LDA,
	   AF, LDAF, IPIV, COLEQU, C, B, LDB, Y, LDY, BERR_OUT, N_NORMS,
	   ERRS_N, ERRS_C, RES, AYB, DY, Y_TAIL, RCOND, ITHRESH, RTHRESH,
	   DZ_UB, IGNORE_CWISE, INFO)
	   CLA_GERFSX_EXTENDED

Function/Subroutine Documentation
   subroutine cla_gerfsx_extended (integerPREC_TYPE, integerTRANS_TYPE,
       integerN, integerNRHS, complex, dimension( lda, * )A, integerLDA,
       complex, dimension( ldaf, * )AF, integerLDAF, integer, dimension( *
       )IPIV, logicalCOLEQU, real, dimension( * )C, complex, dimension( ldb, *
       )B, integerLDB, complex, dimension( ldy, * )Y, integerLDY, real,
       dimension( * )BERR_OUT, integerN_NORMS, real, dimension( nrhs, *
       )ERRS_N, real, dimension( nrhs, * )ERRS_C, complex, dimension( * )RES,
       real, dimension( * )AYB, complex, dimension( * )DY, complex, dimension(
       * )Y_TAIL, realRCOND, integerITHRESH, realRTHRESH, realDZ_UB,
       logicalIGNORE_CWISE, integerINFO)
       CLA_GERFSX_EXTENDED

       Purpose:

	    CLA_GERFSX_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 CGERFSX to perform iterative refinement.
	    In addition to normwise error bound, the code provides maximum
	    componentwise error bound if possible. See comments for ERRS_N
	    and ERRS_C for details of the error bounds. Note that this
	    subroutine is only resonsible for setting the second fields of
	    ERRS_N and ERRS_C.

       Parameters:
	   PREC_TYPE

		     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

	   TRANS_TYPE

		     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

	   N

		     N is INTEGER
		The number of linear equations, i.e., the order of the
		matrix A.  N >= 0.

	   NRHS

		     NRHS is INTEGER
		The number of right-hand-sides, i.e., the number of columns of the
		matrix B.

	   A

		     A is COMPLEX array, dimension (LDA,N)
		On entry, the N-by-N matrix A.

	   LDA

		     LDA is INTEGER
		The leading dimension of the array A.  LDA >= max(1,N).

	   AF

		     AF is COMPLEX array, dimension (LDAF,N)
		The factors L and U from the factorization
		A = P*L*U as computed by CGETRF.

	   LDAF

		     LDAF is INTEGER
		The leading dimension of the array AF.	LDAF >= max(1,N).

	   IPIV

		     IPIV is INTEGER array, dimension (N)
		The pivot indices from the factorization A = P*L*U
		as computed by CGETRF; row i of the matrix was interchanged
		with row IPIV(i).

	   COLEQU

		     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.

	   C

		     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.

	   B

		     B is COMPLEX array, dimension (LDB,NRHS)
		The right-hand-side matrix B.

	   LDB

		     LDB is INTEGER
		The leading dimension of the array B.  LDB >= max(1,N).

	   Y

		     Y is COMPLEX array, dimension (LDY,NRHS)
		On entry, the solution matrix X, as computed by CGETRS.
		On exit, the improved solution matrix Y.

	   LDY

		     LDY is INTEGER
		The leading dimension of the array Y.  LDY >= max(1,N).

	   BERR_OUT

		     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 CLA_LIN_BERR.

	   N_NORMS

		     N_NORMS is INTEGER
		Determines which error bounds to return (see ERRS_N
		and ERRS_C).
		If N_NORMS >= 1 return normwise error bounds.
		If N_NORMS >= 2 return componentwise error bounds.

	   ERRS_N

		     ERRS_N 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 ERRS_N(i,:) corresponds to the ith
		right-hand side.

		The second index in ERRS_N(:,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.

	   ERRS_C

		     ERRS_C 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
		ERRS_C is not accessed.	 If N_ERR_BNDS .LT. 3, then at most
		the first (:,N_ERR_BNDS) entries are returned.

		The first index in ERRS_C(i,:) corresponds to the ith
		right-hand side.

		The second index in ERRS_C(:,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.

	   RES

		     RES is COMPLEX array, dimension (N)
		Workspace to hold the intermediate residual.

	   AYB

		     AYB is REAL array, dimension (N)
		Workspace.

	   DY

		     DY is COMPLEX array, dimension (N)
		Workspace to hold the intermediate solution.

	   Y_TAIL

		     Y_TAIL is COMPLEX array, dimension (N)
		Workspace to hold the trailing bits of the intermediate solution.

	   RCOND

		     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.

	   ITHRESH

		     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
		ERRS_N and ERRS_C may no longer be trustworthy.

	   RTHRESH

		     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.

	   DZ_UB

		     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.

	   IGNORE_CWISE

		     IGNORE_CWISE is LOGICAL
		If .TRUE. then ignore componentwise convergence. Default value
		is .FALSE..

	   INFO

		     INFO is INTEGER
		  = 0:	Successful exit.
		  < 0:	if INFO = -i, the ith argument to CGETRS had an illegal
			value

       Author:
	   Univ. of Tennessee

	   Univ. of California Berkeley

	   Univ. of Colorado Denver

	   NAG Ltd.

       Date:
	   November 2011

       Definition at line 393 of file cla_gerfsx_extended.f.

Author
       Generated automatically by Doxygen for LAPACK from the source code.

Version 3.4.2			Sat Nov 16 2013	      cla_gerfsx_extended.f(3)
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