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## dla_lin_berr()

subroutine dla_lin_berr | ( | integer | n,
|  | integer | nz,
|  | integer | nrhs,
|  | double precision, dimension( n, nrhs ) | res,
|  | double precision, dimension( n, nrhs ) | ayb,
|  | double precision, dimension( nrhs ) | berr )

DLA_LIN_BERR computes a component-wise relative backward error.

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

Purpose:

      !>
      !>    DLA_LIN_BERR computes component-wise relative backward error from
      !>    the formula
      !>        max(i) ( abs(R(i)) / ( abs(op(A_s))*abs(Y) + abs(B_s) )(i) )
      !>    where abs(Z) is the component-wise absolute value of the matrix
      !>    or vector Z.
      !>

Parameters

  [in]

  N

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

  [in]

  NZ

      !>          NZ is INTEGER
      !>     We add (NZ+1)*SLAMCH( 'Safe minimum' ) to R(i) in the numerator to
      !>     guard against spuriously zero residuals. Default value is N.
      !>

  [in]

  NRHS

      !>          NRHS is INTEGER
      !>     The number of right hand sides, i.e., the number of columns
      !>     of the matrices AYB, RES, and BERR.  NRHS >= 0.
      !>

  [in]

  RES

      !>          RES is DOUBLE PRECISION array, dimension (N,NRHS)
      !>     The residual matrix, i.e., the matrix R in the relative backward
      !>     error formula above.
      !>

  [in]

  AYB

      !>          AYB is DOUBLE PRECISION array, dimension (N, NRHS)
      !>     The denominator in the relative backward error formula above, i.e.,
      !>     the matrix abs(op(A_s))*abs(Y) + abs(B_s). The matrices A, Y, and B
      !>     are from iterative refinement (see dla_gerfsx_extended.f).
      !>

  [out]

  BERR

      !>          BERR is DOUBLE PRECISION array, dimension (NRHS)
      !>     The component-wise relative backward error from the formula above.
      !>

Author
  Univ. of Tennessee
  Univ. of California Berkeley
  Univ. of Colorado Denver
  NAG Ltd.