!>
!> DPOSVX uses the Cholesky factorization A = U**T*U or A = L*L**T to
!> compute the solution to a real system of linear equations
!>    A * X = B,
!> where A is an N-by-N symmetric positive definite matrix and X and B
!> are N-by-NRHS matrices.
!>
!> Error bounds on the solution and a condition estimate are also
!> provided.
!> 

!>
!> 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.  If the reciprocal of the condition number is less than machine
!>    precision, INFO = N+1 is returned as a warning, but 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. Iterative refinement is applied to improve the computed solution
!>    matrix and calculate error bounds and backward error estimates
!>    for it.
!>
!> 6. If equilibration was used, the matrix X is premultiplied by
!>    diag(S) so that it solves the original system before
!>    equilibration.
!> 

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 = 'Y', the matrix A has been equilibrated
!>                  with scaling factors given by S.  A and AF will not
!>                  be 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.
!> 

UPLO

!>          UPLO is CHARACTER*1
!>          = 'U':  Upper triangle of A is stored;
!>          = 'L':  Lower triangle of A is stored.
!> 

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 matrices B and X.  NRHS >= 0.
!> 

A

!>          A is DOUBLE PRECISION array, dimension (LDA,N)
!>          On entry, the symmetric 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).
!> 

LDA

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

AF

!>          AF is DOUBLE PRECISION 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).
!> 

LDAF

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

EQUED

!>          EQUED is CHARACTER*1
!>          Specifies the form of equilibration that was done.
!>          = 'N':  No equilibration (always true if FACT = 'N').
!>          = 'Y':  Equilibration was done, 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.
!> 

S

!>          S is DOUBLE PRECISION array, dimension (N)
!>          The scale factors for A; not accessed if EQUED = 'N'.  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.
!> 

B

!>          B is DOUBLE PRECISION 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.
!> 

LDB

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

X

!>          X is DOUBLE PRECISION array, dimension (LDX,NRHS)
!>          If INFO = 0 or INFO = N+1, the N-by-NRHS solution matrix X to
!>          the original system of equations.  Note that if EQUED = 'Y',
!>          A and B are modified on exit, and the solution to the
!>          equilibrated system is inv(diag(S))*X.
!> 

LDX

!>          LDX is INTEGER
!>          The leading dimension of the array X.  LDX >= max(1,N).
!> 

RCOND

!>          RCOND is DOUBLE PRECISION
!>          The estimate of the reciprocal condition number of the matrix
!>          A after equilibration (if done).  If RCOND is less than the
!>          machine precision (in particular, if RCOND = 0), the matrix
!>          is singular to working precision.  This condition is
!>          indicated by a return code of INFO > 0.
!> 

FERR

!>          FERR is DOUBLE PRECISION array, dimension (NRHS)
!>          The estimated forward error bound for each solution vector
!>          X(j) (the j-th column of the solution matrix X).
!>          If XTRUE is the true solution corresponding to X(j), FERR(j)
!>          is an estimated upper bound for the magnitude of the largest
!>          element in (X(j) - XTRUE) divided by the magnitude of the
!>          largest element in X(j).  The estimate is as reliable as
!>          the estimate for RCOND, and is almost always a slight
!>          overestimate of the true error.
!> 

BERR

!>          BERR is DOUBLE PRECISION array, dimension (NRHS)
!>          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).
!> 

WORK

!>          WORK is DOUBLE PRECISION array, dimension (3*N)
!> 

IWORK

!>          IWORK is INTEGER array, dimension (N)
!> 

INFO

!>          INFO is INTEGER
!>          = 0: successful exit
!>          < 0: if INFO = -i, the i-th argument had an illegal value
!>          > 0: if INFO = i, and i is
!>                <= N:  the leading principal minor of order i of A
!>                       is not positive, so the factorization could not
!>                       be completed, and the solution has not been
!>                       computed. RCOND = 0 is returned.
!>                = N+1: U is nonsingular, but RCOND is less than machine
!>                       precision, meaning that the matrix is singular
!>                       to working precision.  Nevertheless, the
!>                       solution and error bounds are computed because
!>                       there are a number of situations where the
!>                       computed solution can be more accurate than the
!>                       value of RCOND would suggest.
!> 

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