LAPACK 3.12.1
LAPACK: Linear Algebra PACKage
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◆ cposvxx()

subroutine cposvxx ( character fact,
character uplo,
integer n,
integer nrhs,
complex, dimension( lda, * ) a,
integer lda,
complex, dimension( ldaf, * ) af,
integer ldaf,
character equed,
real, dimension( * ) s,
complex, dimension( ldb, * ) b,
integer ldb,
complex, dimension( ldx, * ) x,
integer ldx,
real rcond,
real rpvgrw,
real, dimension( * ) berr,
integer n_err_bnds,
real, dimension( nrhs, * ) err_bnds_norm,
real, dimension( nrhs, * ) err_bnds_comp,
integer nparams,
real, dimension( * ) params,
complex, dimension( * ) work,
real, dimension( * ) rwork,
integer info )

CPOSVXX computes the solution to system of linear equations A * X = B for PO matrices

Download CPOSVXX + dependencies [TGZ] [ZIP] [TXT]

Purpose:
!>
!>    CPOSVXX uses the Cholesky factorization A = U**T*U or A = L*L**T
!>    to compute the solution to a complex system of linear equations
!>    A * X = B, where A is an N-by-N Hermitian positive definite matrix
!>    and X and B are N-by-NRHS matrices.
!>
!>    If requested, both normwise and maximum componentwise error bounds
!>    are returned. CPOSVXX will return a solution with a tiny
!>    guaranteed error (O(eps) where eps is the working machine
!>    precision) unless the matrix is very ill-conditioned, in which
!>    case a warning is returned. Relevant condition numbers also are
!>    calculated and returned.
!>
!>    CPOSVXX accepts user-provided factorizations and equilibration
!>    factors; see the definitions of the FACT and EQUED options.
!>    Solving with refinement and using a factorization from a previous
!>    CPOSVXX call will also produce a solution with either O(eps)
!>    errors or warnings, but we cannot make that claim for general
!>    user-provided factorizations and equilibration factors if they
!>    differ from what CPOSVXX would itself produce.
!>
Description:
!>
!>    The following steps are performed:
!>
!>    1. If FACT = 'E', real scaling factors are computed to equilibrate
!>    the system:
!>
!>      diag(S)*A*diag(S)     *inv(diag(S))*X = diag(S)*B
!>
!>    Whether or not the system will be equilibrated depends on the
!>    scaling of the matrix A, but if equilibration is used, A is
!>    overwritten by diag(S)*A*diag(S) and B by diag(S)*B.
!>
!>    2. If FACT = 'N' or 'E', the Cholesky decomposition is used to
!>    factor the matrix A (after equilibration if FACT = 'E') as
!>       A = U**T* U,  if UPLO = 'U', or
!>       A = L * L**T,  if UPLO = 'L',
!>    where U is an upper triangular matrix and L is a lower triangular
!>    matrix.
!>
!>    3. If the leading principal minor of order i is not positive,
!>    then the routine returns with INFO = i. Otherwise, the factored
!>    form of A is used to estimate the condition number of the matrix
!>    A (see argument RCOND).  If the reciprocal of the condition number
!>    is less than machine precision, the routine still goes on to solve
!>    for X and compute error bounds as described below.
!>
!>    4. The system of equations is solved for X using the factored form
!>    of A.
!>
!>    5. By default (unless PARAMS(LA_LINRX_ITREF_I) is set to zero),
!>    the routine will use iterative refinement to try to get a small
!>    error and error bounds.  Refinement calculates the residual to at
!>    least twice the working precision.
!>
!>    6. If equilibration was used, the matrix X is premultiplied by
!>    diag(S) so that it solves the original system before
!>    equilibration.
!> 
!>     Some optional parameters are bundled in the PARAMS array.  These
!>     settings determine how refinement is performed, but often the
!>     defaults are acceptable.  If the defaults are acceptable, users
!>     can pass NPARAMS = 0 which prevents the source code from accessing
!>     the PARAMS argument.
!>
Parameters
[in]FACT
!>          FACT is CHARACTER*1
!>     Specifies whether or not the factored form of the matrix A is
!>     supplied on entry, and if not, whether the matrix A should be
!>     equilibrated before it is factored.
!>       = 'F':  On entry, AF contains the factored form of A.
!>               If EQUED is not 'N', the matrix A has been
!>               equilibrated with scaling factors given by S.
!>               A and AF are not modified.
!>       = 'N':  The matrix A will be copied to AF and factored.
!>       = 'E':  The matrix A will be equilibrated if necessary, then
!>               copied to AF and factored.
!>
[in]UPLO
!>          UPLO is CHARACTER*1
!>       = 'U':  Upper triangle of A is stored;
!>       = 'L':  Lower triangle of A is stored.
!>
[in]N
!>          N is INTEGER
!>     The number of linear equations, i.e., the order of the
!>     matrix A.  N >= 0.
!>
[in]NRHS
!>          NRHS is INTEGER
!>     The number of right hand sides, i.e., the number of columns
!>     of the matrices B and X.  NRHS >= 0.
!>
[in,out]A
!>          A is COMPLEX array, dimension (LDA,N)
!>     On entry, the Hermitian matrix A, except if FACT = 'F' and EQUED =
!>     'Y', then A must contain the equilibrated matrix
!>     diag(S)*A*diag(S).  If UPLO = 'U', the leading N-by-N upper
!>     triangular part of A contains the upper triangular part of the
!>     matrix A, and the strictly lower triangular part of A is not
!>     referenced.  If UPLO = 'L', the leading N-by-N lower triangular
!>     part of A contains the lower triangular part of the matrix A, and
!>     the strictly upper triangular part of A is not referenced.  A is
!>     not modified if FACT = 'F' or 'N', or if FACT = 'E' and EQUED =
!>     'N' on exit.
!>
!>     On exit, if FACT = 'E' and EQUED = 'Y', A is overwritten by
!>     diag(S)*A*diag(S).
!>
[in]LDA
!>          LDA is INTEGER
!>     The leading dimension of the array A.  LDA >= max(1,N).
!>
[in,out]AF
!>          AF is COMPLEX array, dimension (LDAF,N)
!>     If FACT = 'F', then AF is an input argument and on entry
!>     contains the triangular factor U or L from the Cholesky
!>     factorization A = U**T*U or A = L*L**T, in the same storage
!>     format as A.  If EQUED .ne. 'N', then AF is the factored
!>     form of the equilibrated matrix diag(S)*A*diag(S).
!>
!>     If FACT = 'N', then AF is an output argument and on exit
!>     returns the triangular factor U or L from the Cholesky
!>     factorization A = U**T*U or A = L*L**T of the original
!>     matrix A.
!>
!>     If FACT = 'E', then AF is an output argument and on exit
!>     returns the triangular factor U or L from the Cholesky
!>     factorization A = U**T*U or A = L*L**T of the equilibrated
!>     matrix A (see the description of A for the form of the
!>     equilibrated matrix).
!>
[in]LDAF
!>          LDAF is INTEGER
!>     The leading dimension of the array AF.  LDAF >= max(1,N).
!>
[in,out]EQUED
!>          EQUED is CHARACTER*1
!>     Specifies the form of equilibration that was done.
!>       = 'N':  No equilibration (always true if FACT = 'N').
!>       = 'Y':  Both row and column equilibration, i.e., A has been
!>               replaced by diag(S) * A * diag(S).
!>     EQUED is an input argument if FACT = 'F'; otherwise, it is an
!>     output argument.
!>
[in,out]S
!>          S is REAL array, dimension (N)
!>     The row scale factors for A.  If EQUED = 'Y', A is multiplied on
!>     the left and right by diag(S).  S is an input argument if FACT =
!>     'F'; otherwise, S is an output argument.  If FACT = 'F' and EQUED
!>     = 'Y', each element of S must be positive.  If S is output, each
!>     element of S is a power of the radix. If S is input, each element
!>     of S 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.
!>
[in,out]B
!>          B is COMPLEX array, dimension (LDB,NRHS)
!>     On entry, the N-by-NRHS right hand side matrix B.
!>     On exit,
!>     if EQUED = 'N', B is not modified;
!>     if EQUED = 'Y', B is overwritten by diag(S)*B;
!>
[in]LDB
!>          LDB is INTEGER
!>     The leading dimension of the array B.  LDB >= max(1,N).
!>
[out]X
!>          X is COMPLEX array, dimension (LDX,NRHS)
!>     If INFO = 0, the N-by-NRHS solution matrix X to the original
!>     system of equations.  Note that A and B are modified on exit if
!>     EQUED .ne. 'N', and the solution to the equilibrated system is
!>     inv(diag(S))*X.
!>
[in]LDX
!>          LDX is INTEGER
!>     The leading dimension of the array X.  LDX >= max(1,N).
!>
[out]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.
!>
[out]RPVGRW
!>          RPVGRW is REAL
!>     Reciprocal pivot growth.  On exit, this contains the reciprocal
!>     pivot growth factor norm(A)/norm(U). The 
!>     norm is used.  If this is much less than 1, then the stability of
!>     the LU factorization of the (equilibrated) matrix A could be poor.
!>     This also means that the solution X, estimated condition numbers,
!>     and error bounds could be unreliable. If factorization fails with
!>     0<INFO<=N, then this contains the reciprocal pivot growth factor
!>     for the leading INFO columns of A.
!>
[out]BERR
!>          BERR is REAL array, dimension (NRHS)
!>     Componentwise relative backward error.  This is the
!>     componentwise relative backward error of each solution vector X(j)
!>     (i.e., the smallest relative change in any element of A or B that
!>     makes X(j) an exact solution).
!>
[in]N_ERR_BNDS
!>          N_ERR_BNDS is INTEGER
!>     Number of error bounds to return for each right hand side
!>     and each type (normwise or componentwise).  See ERR_BNDS_NORM and
!>     ERR_BNDS_COMP below.
!>
[out]ERR_BNDS_NORM
!>          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  boolean. Trust the answer if the
!>              reciprocal condition number is less than the threshold
!>              sqrt(n) * slamch('Epsilon').
!>
!>     err = 2  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 . 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.
!>
!>     See Lapack Working Note 165 for further details and extra
!>     cautions.
!>
[out]ERR_BNDS_COMP
!>          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 < 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  boolean. Trust the answer if the
!>              reciprocal condition number is less than the threshold
!>              sqrt(n) * slamch('Epsilon').
!>
!>     err = 2  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 . 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.
!>
!>     See Lapack Working Note 165 for further details and extra
!>     cautions.
!>
[in]NPARAMS
!>          NPARAMS is INTEGER
!>     Specifies the number of parameters set in PARAMS.  If <= 0, the
!>     PARAMS array is never referenced and default values are used.
!>
[in,out]PARAMS
!>          PARAMS is REAL array, dimension NPARAMS
!>     Specifies algorithm parameters.  If an entry is < 0.0, then
!>     that entry will be filled with default value used for that
!>     parameter.  Only positions up to NPARAMS are accessed; defaults
!>     are used for higher-numbered parameters.
!>
!>       PARAMS(LA_LINRX_ITREF_I = 1) : Whether to perform iterative
!>            refinement or not.
!>         Default: 1.0
!>            = 0.0:  No refinement is performed, and no error bounds are
!>                    computed.
!>            = 1.0:  Use the double-precision refinement algorithm,
!>                    possibly with doubled-single computations if the
!>                    compilation environment does not support DOUBLE
!>                    PRECISION.
!>              (other values are reserved for future use)
!>
!>       PARAMS(LA_LINRX_ITHRESH_I = 2) : Maximum number of residual
!>            computations allowed for refinement.
!>         Default: 10
!>         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.
!>
!>       PARAMS(LA_LINRX_CWISE_I = 3) : Flag determining if the code
!>            will attempt to find a solution with small componentwise
!>            relative error in the double-precision algorithm.  Positive
!>            is true, 0.0 is false.
!>         Default: 1.0 (attempt componentwise convergence)
!>
[out]WORK
!>          WORK is COMPLEX array, dimension (2*N)
!>
[out]RWORK
!>          RWORK is REAL array, dimension (2*N)
!>
[out]INFO
!>          INFO is INTEGER
!>       = 0:  Successful exit. The solution to every right-hand side is
!>         guaranteed.
!>       < 0:  If INFO = -i, the i-th argument had an illegal value
!>       > 0 and <= N:  U(INFO,INFO) is exactly zero.  The factorization
!>         has been completed, but the factor U is exactly singular, so
!>         the solution and error bounds could not be computed. RCOND = 0
!>         is returned.
!>       = N+J: The solution corresponding to the Jth right-hand side is
!>         not guaranteed. The solutions corresponding to other right-
!>         hand sides K with K > J may not be guaranteed as well, but
!>         only the first such right-hand side is reported. If a small
!>         componentwise error is not requested (PARAMS(3) = 0.0) then
!>         the Jth right-hand side is the first with a normwise error
!>         bound that is not guaranteed (the smallest J such
!>         that ERR_BNDS_NORM(J,1) = 0.0). By default (PARAMS(3) = 1.0)
!>         the Jth right-hand side is the first with either a normwise or
!>         componentwise error bound that is not guaranteed (the smallest
!>         J such that either ERR_BNDS_NORM(J,1) = 0.0 or
!>         ERR_BNDS_COMP(J,1) = 0.0). See the definition of
!>         ERR_BNDS_NORM(:,1) and ERR_BNDS_COMP(:,1). To get information
!>         about all of the right-hand sides check ERR_BNDS_NORM or
!>         ERR_BNDS_COMP.
!>
Author
Univ. of Tennessee
Univ. of California Berkeley
Univ. of Colorado Denver
NAG Ltd.

Definition at line 490 of file cposvxx.f.

495*
496* -- LAPACK driver routine --
497* -- LAPACK is a software package provided by Univ. of Tennessee, --
498* -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
499*
500* .. Scalar Arguments ..
501 CHARACTER EQUED, FACT, UPLO
502 INTEGER INFO, LDA, LDAF, LDB, LDX, N, NRHS, NPARAMS,
503 $ N_ERR_BNDS
504 REAL RCOND, RPVGRW
505* ..
506* .. Array Arguments ..
507 COMPLEX A( LDA, * ), AF( LDAF, * ), B( LDB, * ),
508 $ WORK( * ), X( LDX, * )
509 REAL S( * ), PARAMS( * ), BERR( * ), RWORK( * ),
510 $ ERR_BNDS_NORM( NRHS, * ),
511 $ ERR_BNDS_COMP( NRHS, * )
512* ..
513*
514* ==================================================================
515*
516* .. Parameters ..
517 REAL ZERO, ONE
518 parameter( zero = 0.0e+0, one = 1.0e+0 )
519 INTEGER FINAL_NRM_ERR_I, FINAL_CMP_ERR_I, BERR_I
520 INTEGER RCOND_I, NRM_RCOND_I, NRM_ERR_I, CMP_RCOND_I
521 INTEGER CMP_ERR_I, PIV_GROWTH_I
522 parameter( final_nrm_err_i = 1, final_cmp_err_i = 2,
523 $ berr_i = 3 )
524 parameter( rcond_i = 4, nrm_rcond_i = 5, nrm_err_i = 6 )
525 parameter( cmp_rcond_i = 7, cmp_err_i = 8,
526 $ piv_growth_i = 9 )
527* ..
528* .. Local Scalars ..
529 LOGICAL EQUIL, NOFACT, RCEQU
530 INTEGER INFEQU, J
531 REAL AMAX, BIGNUM, SMIN, SMAX, SCOND, SMLNUM
532* ..
533* .. External Functions ..
534 EXTERNAL lsame, slamch, cla_porpvgrw
535 LOGICAL LSAME
536 REAL SLAMCH, CLA_PORPVGRW
537* ..
538* .. External Subroutines ..
539 EXTERNAL cpoequb, cpotrf, cpotrs, clacpy,
540 $ claqhe, xerbla, clascl2, cporfsx
541* ..
542* .. Intrinsic Functions ..
543 INTRINSIC max, min
544* ..
545* .. Executable Statements ..
546*
547 info = 0
548 nofact = lsame( fact, 'N' )
549 equil = lsame( fact, 'E' )
550 smlnum = slamch( 'Safe minimum' )
551 bignum = one / smlnum
552 IF( nofact .OR. equil ) THEN
553 equed = 'N'
554 rcequ = .false.
555 ELSE
556 rcequ = lsame( equed, 'Y' )
557 ENDIF
558*
559* Default is failure. If an input parameter is wrong or
560* factorization fails, make everything look horrible. Only the
561* pivot growth is set here, the rest is initialized in CPORFSX.
562*
563 rpvgrw = zero
564*
565* Test the input parameters. PARAMS is not tested until CPORFSX.
566*
567 IF( .NOT.nofact .AND. .NOT.equil .AND. .NOT.
568 $ lsame( fact, 'F' ) ) THEN
569 info = -1
570 ELSE IF( .NOT.lsame( uplo, 'U' ) .AND.
571 $ .NOT.lsame( uplo, 'L' ) ) THEN
572 info = -2
573 ELSE IF( n.LT.0 ) THEN
574 info = -3
575 ELSE IF( nrhs.LT.0 ) THEN
576 info = -4
577 ELSE IF( lda.LT.max( 1, n ) ) THEN
578 info = -6
579 ELSE IF( ldaf.LT.max( 1, n ) ) THEN
580 info = -8
581 ELSE IF( lsame( fact, 'F' ) .AND. .NOT.
582 $ ( rcequ .OR. lsame( equed, 'N' ) ) ) THEN
583 info = -9
584 ELSE
585 IF ( rcequ ) THEN
586 smin = bignum
587 smax = zero
588 DO 10 j = 1, n
589 smin = min( smin, s( j ) )
590 smax = max( smax, s( j ) )
591 10 CONTINUE
592 IF( smin.LE.zero ) THEN
593 info = -10
594 ELSE IF( n.GT.0 ) THEN
595 scond = max( smin, smlnum ) / min( smax, bignum )
596 ELSE
597 scond = one
598 END IF
599 END IF
600 IF( info.EQ.0 ) THEN
601 IF( ldb.LT.max( 1, n ) ) THEN
602 info = -12
603 ELSE IF( ldx.LT.max( 1, n ) ) THEN
604 info = -14
605 END IF
606 END IF
607 END IF
608*
609 IF( info.NE.0 ) THEN
610 CALL xerbla( 'CPOSVXX', -info )
611 RETURN
612 END IF
613*
614 IF( equil ) THEN
615*
616* Compute row and column scalings to equilibrate the matrix A.
617*
618 CALL cpoequb( n, a, lda, s, scond, amax, infequ )
619 IF( infequ.EQ.0 ) THEN
620*
621* Equilibrate the matrix.
622*
623 CALL claqhe( uplo, n, a, lda, s, scond, amax, equed )
624 rcequ = lsame( equed, 'Y' )
625 END IF
626 END IF
627*
628* Scale the right-hand side.
629*
630 IF( rcequ ) CALL clascl2( n, nrhs, s, b, ldb )
631*
632 IF( nofact .OR. equil ) THEN
633*
634* Compute the Cholesky factorization of A.
635*
636 CALL clacpy( uplo, n, n, a, lda, af, ldaf )
637 CALL cpotrf( uplo, n, af, ldaf, info )
638*
639* Return if INFO is non-zero.
640*
641 IF( info.GT.0 ) THEN
642*
643* Pivot in column INFO is exactly 0
644* Compute the reciprocal pivot growth factor of the
645* leading rank-deficient INFO columns of A.
646*
647 rpvgrw = cla_porpvgrw( uplo, n, a, lda, af, ldaf, rwork )
648 RETURN
649 END IF
650 END IF
651*
652* Compute the reciprocal pivot growth factor RPVGRW.
653*
654 rpvgrw = cla_porpvgrw( uplo, n, a, lda, af, ldaf, rwork )
655*
656* Compute the solution matrix X.
657*
658 CALL clacpy( 'Full', n, nrhs, b, ldb, x, ldx )
659 CALL cpotrs( uplo, n, nrhs, af, ldaf, x, ldx, info )
660*
661* Use iterative refinement to improve the computed solution and
662* compute error bounds and backward error estimates for it.
663*
664 CALL cporfsx( uplo, equed, n, nrhs, a, lda, af, ldaf,
665 $ s, b, ldb, x, ldx, rcond, berr, n_err_bnds, err_bnds_norm,
666 $ err_bnds_comp, nparams, params, work, rwork, info )
667
668*
669* Scale solutions.
670*
671 IF ( rcequ ) THEN
672 CALL clascl2( n, nrhs, s, x, ldx )
673 END IF
674*
675 RETURN
676*
677* End of CPOSVXX
678*
xerbla
subroutine xerbla(srname, info)
Definition cblat2.f:3285
cla_porpvgrw
real function cla_porpvgrw(uplo, ncols, a, lda, af, ldaf, work)
CLA_PORPVGRW computes the reciprocal pivot growth factor norm(A)/norm(U) for a symmetric or Hermitian...
Definition cla_porpvgrw.f:104
clacpy
subroutine clacpy(uplo, m, n, a, lda, b, ldb)
CLACPY copies all or part of one two-dimensional array to another.
Definition clacpy.f:101
slamch
real function slamch(cmach)
SLAMCH
Definition slamch.f:68
claqhe
subroutine claqhe(uplo, n, a, lda, s, scond, amax, equed)
CLAQHE scales a Hermitian matrix.
Definition claqhe.f:132
clascl2
subroutine clascl2(m, n, d, x, ldx)
CLASCL2 performs diagonal scaling on a matrix.
Definition clascl2.f:89
lsame
logical function lsame(ca, cb)
LSAME
Definition lsame.f:48
cpoequb
subroutine cpoequb(n, a, lda, s, scond, amax, info)
CPOEQUB
Definition cpoequb.f:117
cporfsx
subroutine cporfsx(uplo, equed, n, nrhs, a, lda, af, ldaf, s, b, ldb, x, ldx, rcond, berr, n_err_bnds, err_bnds_norm, err_bnds_comp, nparams, params, work, rwork, info)
CPORFSX
Definition cporfsx.f:392
cpotrf
subroutine cpotrf(uplo, n, a, lda, info)
CPOTRF
Definition cpotrf.f:105
cpotrs
subroutine cpotrs(uplo, n, nrhs, a, lda, b, ldb, info)
CPOTRS
Definition cpotrs.f:108
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