LAPACK  3.10.1
LAPACK: Linear Algebra PACKage

◆ dla_gerfsx_extended()

subroutine dla_gerfsx_extended ( integer  PREC_TYPE,
integer  TRANS_TYPE,
integer  N,
integer  NRHS,
double precision, dimension( lda, * )  A,
integer  LDA,
double precision, dimension( ldaf, * )  AF,
integer  LDAF,
integer, dimension( * )  IPIV,
logical  COLEQU,
double precision, dimension( * )  C,
double precision, dimension( ldb, * )  B,
integer  LDB,
double precision, dimension( ldy, * )  Y,
integer  LDY,
double precision, dimension( * )  BERR_OUT,
integer  N_NORMS,
double precision, dimension( nrhs, * )  ERRS_N,
double precision, dimension( nrhs, * )  ERRS_C,
double precision, dimension( * )  RES,
double precision, dimension( * )  AYB,
double precision, dimension( * )  DY,
double precision, dimension( * )  Y_TAIL,
double precision  RCOND,
integer  ITHRESH,
double precision  RTHRESH,
double precision  DZ_UB,
logical  IGNORE_CWISE,
integer  INFO 
)

DLA_GERFSX_EXTENDED improves the computed solution to a system of linear equations for general matrices by performing extra-precise iterative refinement and provides error bounds and backward error estimates for the solution.

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Purpose:
 DLA_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 DGERFSX 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 responsible for setting the second fields of
 ERRS_N and ERRS_C.
Parameters
[in]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' or 'E':  Extra
[in]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
[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
     matrix B.
[in]A
          A is DOUBLE PRECISION array, dimension (LDA,N)
     On entry, the N-by-N matrix A.
[in]LDA
          LDA is INTEGER
     The leading dimension of the array A.  LDA >= max(1,N).
[in]AF
          AF is DOUBLE PRECISION array, dimension (LDAF,N)
     The factors L and U from the factorization
     A = P*L*U as computed by DGETRF.
[in]LDAF
          LDAF is INTEGER
     The leading dimension of the array AF.  LDAF >= max(1,N).
[in]IPIV
          IPIV is INTEGER array, dimension (N)
     The pivot indices from the factorization A = P*L*U
     as computed by DGETRF; row i of the matrix was interchanged
     with row IPIV(i).
[in]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.
[in]C
          C is DOUBLE PRECISION 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.
[in]B
          B is DOUBLE PRECISION array, dimension (LDB,NRHS)
     The right-hand-side matrix B.
[in]LDB
          LDB is INTEGER
     The leading dimension of the array B.  LDB >= max(1,N).
[in,out]Y
          Y is DOUBLE PRECISION array, dimension (LDY,NRHS)
     On entry, the solution matrix X, as computed by DGETRS.
     On exit, the improved solution matrix Y.
[in]LDY
          LDY is INTEGER
     The leading dimension of the array Y.  LDY >= max(1,N).
[out]BERR_OUT
          BERR_OUT is DOUBLE PRECISION 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 DLA_LIN_BERR.
[in]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.
[in,out]ERRS_N
          ERRS_N is DOUBLE PRECISION 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.
[in,out]ERRS_C
          ERRS_C is DOUBLE PRECISION 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 < 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.
[in]RES
          RES is DOUBLE PRECISION array, dimension (N)
     Workspace to hold the intermediate residual.
[in]AYB
          AYB is DOUBLE PRECISION array, dimension (N)
     Workspace. This can be the same workspace passed for Y_TAIL.
[in]DY
          DY is DOUBLE PRECISION array, dimension (N)
     Workspace to hold the intermediate solution.
[in]Y_TAIL
          Y_TAIL is DOUBLE PRECISION array, dimension (N)
     Workspace to hold the trailing bits of the intermediate solution.
[in]RCOND
          RCOND is DOUBLE PRECISION
     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.
[in]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.
[in]RTHRESH
          RTHRESH is DOUBLE PRECISION
     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.
[in]DZ_UB
          DZ_UB is DOUBLE PRECISION
     Determines when to start considering componentwise convergence.
     Componentwise convergence is only considered after each component
     of the solution Y is stable, which we define 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.
[in]IGNORE_CWISE
          IGNORE_CWISE is LOGICAL
     If .TRUE. then ignore componentwise convergence. Default value
     is .FALSE..
[out]INFO
          INFO is INTEGER
       = 0:  Successful exit.
       < 0:  if INFO = -i, the ith argument to DGETRS had an illegal
             value
Author
Univ. of Tennessee
Univ. of California Berkeley
Univ. of Colorado Denver
NAG Ltd.

Definition at line 390 of file dla_gerfsx_extended.f.

396 *
397 * -- LAPACK computational routine --
398 * -- LAPACK is a software package provided by Univ. of Tennessee, --
399 * -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
400 *
401 * .. Scalar Arguments ..
402  INTEGER INFO, LDA, LDAF, LDB, LDY, N, NRHS, PREC_TYPE,
403  $ TRANS_TYPE, N_NORMS, ITHRESH
404  LOGICAL COLEQU, IGNORE_CWISE
405  DOUBLE PRECISION RTHRESH, DZ_UB
406 * ..
407 * .. Array Arguments ..
408  INTEGER IPIV( * )
409  DOUBLE PRECISION A( LDA, * ), AF( LDAF, * ), B( LDB, * ),
410  $ Y( LDY, * ), RES( * ), DY( * ), Y_TAIL( * )
411  DOUBLE PRECISION C( * ), AYB( * ), RCOND, BERR_OUT( * ),
412  $ ERRS_N( NRHS, * ), ERRS_C( NRHS, * )
413 * ..
414 *
415 * =====================================================================
416 *
417 * .. Local Scalars ..
418  CHARACTER TRANS
419  INTEGER CNT, I, J, X_STATE, Z_STATE, Y_PREC_STATE
420  DOUBLE PRECISION YK, DYK, YMIN, NORMY, NORMX, NORMDX, DXRAT,
421  $ DZRAT, PREVNORMDX, PREV_DZ_Z, DXRATMAX,
422  $ DZRATMAX, DX_X, DZ_Z, FINAL_DX_X, FINAL_DZ_Z,
423  $ EPS, HUGEVAL, INCR_THRESH
424  LOGICAL INCR_PREC
425 * ..
426 * .. Parameters ..
427  INTEGER UNSTABLE_STATE, WORKING_STATE, CONV_STATE,
428  $ NOPROG_STATE, BASE_RESIDUAL, EXTRA_RESIDUAL,
429  $ EXTRA_Y
430  parameter( unstable_state = 0, working_state = 1,
431  $ conv_state = 2, noprog_state = 3 )
432  parameter( base_residual = 0, extra_residual = 1,
433  $ extra_y = 2 )
434  INTEGER FINAL_NRM_ERR_I, FINAL_CMP_ERR_I, BERR_I
435  INTEGER RCOND_I, NRM_RCOND_I, NRM_ERR_I, CMP_RCOND_I
436  INTEGER CMP_ERR_I, PIV_GROWTH_I
437  parameter( final_nrm_err_i = 1, final_cmp_err_i = 2,
438  $ berr_i = 3 )
439  parameter( rcond_i = 4, nrm_rcond_i = 5, nrm_err_i = 6 )
440  parameter( cmp_rcond_i = 7, cmp_err_i = 8,
441  $ piv_growth_i = 9 )
442  INTEGER LA_LINRX_ITREF_I, LA_LINRX_ITHRESH_I,
443  $ LA_LINRX_CWISE_I
444  parameter( la_linrx_itref_i = 1,
445  $ la_linrx_ithresh_i = 2 )
446  parameter( la_linrx_cwise_i = 3 )
447  INTEGER LA_LINRX_TRUST_I, LA_LINRX_ERR_I,
448  $ LA_LINRX_RCOND_I
449  parameter( la_linrx_trust_i = 1, la_linrx_err_i = 2 )
450  parameter( la_linrx_rcond_i = 3 )
451 * ..
452 * .. External Subroutines ..
453  EXTERNAL daxpy, dcopy, dgetrs, dgemv, blas_dgemv_x,
454  $ blas_dgemv2_x, dla_geamv, dla_wwaddw, dlamch,
456  DOUBLE PRECISION DLAMCH
457  CHARACTER CHLA_TRANSTYPE
458 * ..
459 * .. Intrinsic Functions ..
460  INTRINSIC abs, max, min
461 * ..
462 * .. Executable Statements ..
463 *
464  IF ( info.NE.0 ) RETURN
465  trans = chla_transtype(trans_type)
466  eps = dlamch( 'Epsilon' )
467  hugeval = dlamch( 'Overflow' )
468 * Force HUGEVAL to Inf
469  hugeval = hugeval * hugeval
470 * Using HUGEVAL may lead to spurious underflows.
471  incr_thresh = dble( n ) * eps
472 *
473  DO j = 1, nrhs
474  y_prec_state = extra_residual
475  IF ( y_prec_state .EQ. extra_y ) THEN
476  DO i = 1, n
477  y_tail( i ) = 0.0d+0
478  END DO
479  END IF
480 
481  dxrat = 0.0d+0
482  dxratmax = 0.0d+0
483  dzrat = 0.0d+0
484  dzratmax = 0.0d+0
485  final_dx_x = hugeval
486  final_dz_z = hugeval
487  prevnormdx = hugeval
488  prev_dz_z = hugeval
489  dz_z = hugeval
490  dx_x = hugeval
491 
492  x_state = working_state
493  z_state = unstable_state
494  incr_prec = .false.
495 
496  DO cnt = 1, ithresh
497 *
498 * Compute residual RES = B_s - op(A_s) * Y,
499 * op(A) = A, A**T, or A**H depending on TRANS (and type).
500 *
501  CALL dcopy( n, b( 1, j ), 1, res, 1 )
502  IF ( y_prec_state .EQ. base_residual ) THEN
503  CALL dgemv( trans, n, n, -1.0d+0, a, lda, y( 1, j ), 1,
504  $ 1.0d+0, res, 1 )
505  ELSE IF ( y_prec_state .EQ. extra_residual ) THEN
506  CALL blas_dgemv_x( trans_type, n, n, -1.0d+0, a, lda,
507  $ y( 1, j ), 1, 1.0d+0, res, 1, prec_type )
508  ELSE
509  CALL blas_dgemv2_x( trans_type, n, n, -1.0d+0, a, lda,
510  $ y( 1, j ), y_tail, 1, 1.0d+0, res, 1, prec_type )
511  END IF
512 
513 ! XXX: RES is no longer needed.
514  CALL dcopy( n, res, 1, dy, 1 )
515  CALL dgetrs( trans, n, 1, af, ldaf, ipiv, dy, n, info )
516 *
517 * Calculate relative changes DX_X, DZ_Z and ratios DXRAT, DZRAT.
518 *
519  normx = 0.0d+0
520  normy = 0.0d+0
521  normdx = 0.0d+0
522  dz_z = 0.0d+0
523  ymin = hugeval
524 *
525  DO i = 1, n
526  yk = abs( y( i, j ) )
527  dyk = abs( dy( i ) )
528 
529  IF ( yk .NE. 0.0d+0 ) THEN
530  dz_z = max( dz_z, dyk / yk )
531  ELSE IF ( dyk .NE. 0.0d+0 ) THEN
532  dz_z = hugeval
533  END IF
534 
535  ymin = min( ymin, yk )
536 
537  normy = max( normy, yk )
538 
539  IF ( colequ ) THEN
540  normx = max( normx, yk * c( i ) )
541  normdx = max( normdx, dyk * c( i ) )
542  ELSE
543  normx = normy
544  normdx = max( normdx, dyk )
545  END IF
546  END DO
547 
548  IF ( normx .NE. 0.0d+0 ) THEN
549  dx_x = normdx / normx
550  ELSE IF ( normdx .EQ. 0.0d+0 ) THEN
551  dx_x = 0.0d+0
552  ELSE
553  dx_x = hugeval
554  END IF
555 
556  dxrat = normdx / prevnormdx
557  dzrat = dz_z / prev_dz_z
558 *
559 * Check termination criteria
560 *
561  IF (.NOT.ignore_cwise
562  $ .AND. ymin*rcond .LT. incr_thresh*normy
563  $ .AND. y_prec_state .LT. extra_y)
564  $ incr_prec = .true.
565 
566  IF ( x_state .EQ. noprog_state .AND. dxrat .LE. rthresh )
567  $ x_state = working_state
568  IF ( x_state .EQ. working_state ) THEN
569  IF ( dx_x .LE. eps ) THEN
570  x_state = conv_state
571  ELSE IF ( dxrat .GT. rthresh ) THEN
572  IF ( y_prec_state .NE. extra_y ) THEN
573  incr_prec = .true.
574  ELSE
575  x_state = noprog_state
576  END IF
577  ELSE
578  IF ( dxrat .GT. dxratmax ) dxratmax = dxrat
579  END IF
580  IF ( x_state .GT. working_state ) final_dx_x = dx_x
581  END IF
582 
583  IF ( z_state .EQ. unstable_state .AND. dz_z .LE. dz_ub )
584  $ z_state = working_state
585  IF ( z_state .EQ. noprog_state .AND. dzrat .LE. rthresh )
586  $ z_state = working_state
587  IF ( z_state .EQ. working_state ) THEN
588  IF ( dz_z .LE. eps ) THEN
589  z_state = conv_state
590  ELSE IF ( dz_z .GT. dz_ub ) THEN
591  z_state = unstable_state
592  dzratmax = 0.0d+0
593  final_dz_z = hugeval
594  ELSE IF ( dzrat .GT. rthresh ) THEN
595  IF ( y_prec_state .NE. extra_y ) THEN
596  incr_prec = .true.
597  ELSE
598  z_state = noprog_state
599  END IF
600  ELSE
601  IF ( dzrat .GT. dzratmax ) dzratmax = dzrat
602  END IF
603  IF ( z_state .GT. working_state ) final_dz_z = dz_z
604  END IF
605 *
606 * Exit if both normwise and componentwise stopped working,
607 * but if componentwise is unstable, let it go at least two
608 * iterations.
609 *
610  IF ( x_state.NE.working_state ) THEN
611  IF ( ignore_cwise) GOTO 666
612  IF ( z_state.EQ.noprog_state .OR. z_state.EQ.conv_state )
613  $ GOTO 666
614  IF ( z_state.EQ.unstable_state .AND. cnt.GT.1 ) GOTO 666
615  END IF
616 
617  IF ( incr_prec ) THEN
618  incr_prec = .false.
619  y_prec_state = y_prec_state + 1
620  DO i = 1, n
621  y_tail( i ) = 0.0d+0
622  END DO
623  END IF
624 
625  prevnormdx = normdx
626  prev_dz_z = dz_z
627 *
628 * Update soluton.
629 *
630  IF ( y_prec_state .LT. extra_y ) THEN
631  CALL daxpy( n, 1.0d+0, dy, 1, y( 1, j ), 1 )
632  ELSE
633  CALL dla_wwaddw( n, y( 1, j ), y_tail, dy )
634  END IF
635 
636  END DO
637 * Target of "IF (Z_STOP .AND. X_STOP)". Sun's f77 won't EXIT.
638  666 CONTINUE
639 *
640 * Set final_* when cnt hits ithresh.
641 *
642  IF ( x_state .EQ. working_state ) final_dx_x = dx_x
643  IF ( z_state .EQ. working_state ) final_dz_z = dz_z
644 *
645 * Compute error bounds
646 *
647  IF (n_norms .GE. 1) THEN
648  errs_n( j, la_linrx_err_i ) = final_dx_x / (1 - dxratmax)
649  END IF
650  IF ( n_norms .GE. 2 ) THEN
651  errs_c( j, la_linrx_err_i ) = final_dz_z / (1 - dzratmax)
652  END IF
653 *
654 * Compute componentwise relative backward error from formula
655 * max(i) ( abs(R(i)) / ( abs(op(A_s))*abs(Y) + abs(B_s) )(i) )
656 * where abs(Z) is the componentwise absolute value of the matrix
657 * or vector Z.
658 *
659 * Compute residual RES = B_s - op(A_s) * Y,
660 * op(A) = A, A**T, or A**H depending on TRANS (and type).
661 *
662  CALL dcopy( n, b( 1, j ), 1, res, 1 )
663  CALL dgemv( trans, n, n, -1.0d+0, a, lda, y(1,j), 1, 1.0d+0,
664  $ res, 1 )
665 
666  DO i = 1, n
667  ayb( i ) = abs( b( i, j ) )
668  END DO
669 *
670 * Compute abs(op(A_s))*abs(Y) + abs(B_s).
671 *
672  CALL dla_geamv ( trans_type, n, n, 1.0d+0,
673  $ a, lda, y(1, j), 1, 1.0d+0, ayb, 1 )
674 
675  CALL dla_lin_berr ( n, n, 1, res, ayb, berr_out( j ) )
676 *
677 * End of loop for each RHS.
678 *
679  END DO
680 *
681  RETURN
682 *
683 * End of DLA_GERFSX_EXTENDED
684 *
double precision function dlamch(CMACH)
DLAMCH
Definition: dlamch.f:69
character *1 function chla_transtype(TRANS)
CHLA_TRANSTYPE
subroutine dcopy(N, DX, INCX, DY, INCY)
DCOPY
Definition: dcopy.f:82
subroutine daxpy(N, DA, DX, INCX, DY, INCY)
DAXPY
Definition: daxpy.f:89
subroutine dgemv(TRANS, M, N, ALPHA, A, LDA, X, INCX, BETA, Y, INCY)
DGEMV
Definition: dgemv.f:156
subroutine dgetrs(TRANS, N, NRHS, A, LDA, IPIV, B, LDB, INFO)
DGETRS
Definition: dgetrs.f:121
subroutine dla_geamv(TRANS, M, N, ALPHA, A, LDA, X, INCX, BETA, Y, INCY)
DLA_GEAMV computes a matrix-vector product using a general matrix to calculate error bounds.
Definition: dla_geamv.f:174
subroutine dla_lin_berr(N, NZ, NRHS, RES, AYB, BERR)
DLA_LIN_BERR computes a component-wise relative backward error.
Definition: dla_lin_berr.f:101
subroutine dla_wwaddw(N, X, Y, W)
DLA_WWADDW adds a vector into a doubled-single vector.
Definition: dla_wwaddw.f:81
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