LAPACK 3.12.0
LAPACK: Linear Algebra PACKage
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◆ sla_syrfsx_extended()

subroutine sla_syrfsx_extended ( integer  prec_type,
character  uplo,
integer  n,
integer  nrhs,
real, dimension( lda, * )  a,
integer  lda,
real, dimension( ldaf, * )  af,
integer  ldaf,
integer, dimension( * )  ipiv,
logical  colequ,
real, dimension( * )  c,
real, dimension( ldb, * )  b,
integer  ldb,
real, dimension( ldy, * )  y,
integer  ldy,
real, dimension( * )  berr_out,
integer  n_norms,
real, dimension( nrhs, * )  err_bnds_norm,
real, dimension( nrhs, * )  err_bnds_comp,
real, dimension( * )  res,
real, dimension( * )  ayb,
real, dimension( * )  dy,
real, dimension( * )  y_tail,
real  rcond,
integer  ithresh,
real  rthresh,
real  dz_ub,
logical  ignore_cwise,
integer  info 
)

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

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

Purpose:
 SLA_SYRFSX_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 SSYRFSX to perform iterative refinement.
 In addition to normwise error bound, the code provides maximum
 componentwise error bound if possible. See comments for ERR_BNDS_NORM
 and ERR_BNDS_COMP for details of the error bounds. Note that this
 subroutine is only responsible for setting the second fields of
 ERR_BNDS_NORM and ERR_BNDS_COMP.
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]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
     matrix B.
[in]A
          A is REAL 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 REAL array, dimension (LDAF,N)
     The block diagonal matrix D and the multipliers used to
     obtain the factor U or L as computed by SSYTRF.
[in]LDAF
          LDAF is INTEGER
     The leading dimension of the array AF.  LDAF >= max(1,N).
[in]IPIV
          IPIV is INTEGER array, dimension (N)
     Details of the interchanges and the block structure of D
     as determined by SSYTRF.
[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 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.
[in]B
          B is REAL 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 REAL array, dimension (LDY,NRHS)
     On entry, the solution matrix X, as computed by SSYTRS.
     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 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 SLA_LIN_BERR.
[in]N_NORMS
          N_NORMS is INTEGER
     Determines which error bounds to return (see ERR_BNDS_NORM
     and ERR_BNDS_COMP).
     If N_NORMS >= 1 return normwise error bounds.
     If N_NORMS >= 2 return componentwise error bounds.
[in,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 "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]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 "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 REAL array, dimension (N)
     Workspace to hold the intermediate residual.
[in]AYB
          AYB is REAL array, dimension (N)
     Workspace. This can be the same workspace passed for Y_TAIL.
[in]DY
          DY is REAL array, dimension (N)
     Workspace to hold the intermediate solution.
[in]Y_TAIL
          Y_TAIL is REAL array, dimension (N)
     Workspace to hold the trailing bits of the intermediate solution.
[in]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.
[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
     ERR_BNDS_NORM and ERR_BNDS_COMP may no longer be trustworthy.
[in]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.
[in]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 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 SLA_SYRFSX_EXTENDED had an illegal
             value
Author
Univ. of Tennessee
Univ. of California Berkeley
Univ. of Colorado Denver
NAG Ltd.

Definition at line 389 of file sla_syrfsx_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 $ N_NORMS, ITHRESH
404 CHARACTER UPLO
405 LOGICAL COLEQU, IGNORE_CWISE
406 REAL RTHRESH, DZ_UB
407* ..
408* .. Array Arguments ..
409 INTEGER IPIV( * )
410 REAL A( LDA, * ), AF( LDAF, * ), B( LDB, * ),
411 $ Y( LDY, * ), RES( * ), DY( * ), Y_TAIL( * )
412 REAL C( * ), AYB( * ), RCOND, BERR_OUT( * ),
413 $ ERR_BNDS_NORM( NRHS, * ),
414 $ ERR_BNDS_COMP( NRHS, * )
415* ..
416*
417* =====================================================================
418*
419* .. Local Scalars ..
420 INTEGER UPLO2, CNT, I, J, X_STATE, Z_STATE
421 REAL YK, DYK, YMIN, NORMY, NORMX, NORMDX, DXRAT,
422 $ DZRAT, PREVNORMDX, PREV_DZ_Z, DXRATMAX,
423 $ DZRATMAX, DX_X, DZ_Z, FINAL_DX_X, FINAL_DZ_Z,
424 $ EPS, HUGEVAL, INCR_THRESH
425 LOGICAL INCR_PREC, UPPER
426* ..
427* .. Parameters ..
428 INTEGER UNSTABLE_STATE, WORKING_STATE, CONV_STATE,
429 $ NOPROG_STATE, Y_PREC_STATE, BASE_RESIDUAL,
430 $ EXTRA_RESIDUAL, EXTRA_Y
431 parameter( unstable_state = 0, working_state = 1,
432 $ conv_state = 2, noprog_state = 3 )
433 parameter( base_residual = 0, extra_residual = 1,
434 $ extra_y = 2 )
435 INTEGER FINAL_NRM_ERR_I, FINAL_CMP_ERR_I, BERR_I
436 INTEGER RCOND_I, NRM_RCOND_I, NRM_ERR_I, CMP_RCOND_I
437 INTEGER CMP_ERR_I, PIV_GROWTH_I
438 parameter( final_nrm_err_i = 1, final_cmp_err_i = 2,
439 $ berr_i = 3 )
440 parameter( rcond_i = 4, nrm_rcond_i = 5, nrm_err_i = 6 )
441 parameter( cmp_rcond_i = 7, cmp_err_i = 8,
442 $ piv_growth_i = 9 )
443 INTEGER LA_LINRX_ITREF_I, LA_LINRX_ITHRESH_I,
444 $ LA_LINRX_CWISE_I
445 parameter( la_linrx_itref_i = 1,
446 $ la_linrx_ithresh_i = 2 )
447 parameter( la_linrx_cwise_i = 3 )
448 INTEGER LA_LINRX_TRUST_I, LA_LINRX_ERR_I,
449 $ LA_LINRX_RCOND_I
450 parameter( la_linrx_trust_i = 1, la_linrx_err_i = 2 )
451 parameter( la_linrx_rcond_i = 3 )
452* ..
453* .. External Functions ..
454 LOGICAL LSAME
455 EXTERNAL ilauplo
456 INTEGER ILAUPLO
457* ..
458* .. External Subroutines ..
459 EXTERNAL saxpy, scopy, ssytrs, ssymv, blas_ssymv_x,
460 $ blas_ssymv2_x, sla_syamv, sla_wwaddw,
462 REAL SLAMCH
463* ..
464* .. Intrinsic Functions ..
465 INTRINSIC abs, max, min
466* ..
467* .. Executable Statements ..
468*
469 info = 0
470 upper = lsame( uplo, 'U' )
471 IF( .NOT.upper .AND. .NOT.lsame( uplo, 'L' ) ) THEN
472 info = -2
473 ELSE IF( n.LT.0 ) THEN
474 info = -3
475 ELSE IF( nrhs.LT.0 ) THEN
476 info = -4
477 ELSE IF( lda.LT.max( 1, n ) ) THEN
478 info = -6
479 ELSE IF( ldaf.LT.max( 1, n ) ) THEN
480 info = -8
481 ELSE IF( ldb.LT.max( 1, n ) ) THEN
482 info = -13
483 ELSE IF( ldy.LT.max( 1, n ) ) THEN
484 info = -15
485 END IF
486 IF( info.NE.0 ) THEN
487 CALL xerbla( 'SLA_SYRFSX_EXTENDED', -info )
488 RETURN
489 END IF
490 eps = slamch( 'Epsilon' )
491 hugeval = slamch( 'Overflow' )
492* Force HUGEVAL to Inf
493 hugeval = hugeval * hugeval
494* Using HUGEVAL may lead to spurious underflows.
495 incr_thresh = real( n )*eps
496
497 IF ( lsame( uplo, 'L' ) ) THEN
498 uplo2 = ilauplo( 'L' )
499 ELSE
500 uplo2 = ilauplo( 'U' )
501 ENDIF
502
503 DO j = 1, nrhs
504 y_prec_state = extra_residual
505 IF ( y_prec_state .EQ. extra_y ) THEN
506 DO i = 1, n
507 y_tail( i ) = 0.0
508 END DO
509 END IF
510
511 dxrat = 0.0
512 dxratmax = 0.0
513 dzrat = 0.0
514 dzratmax = 0.0
515 final_dx_x = hugeval
516 final_dz_z = hugeval
517 prevnormdx = hugeval
518 prev_dz_z = hugeval
519 dz_z = hugeval
520 dx_x = hugeval
521
522 x_state = working_state
523 z_state = unstable_state
524 incr_prec = .false.
525
526 DO cnt = 1, ithresh
527*
528* Compute residual RES = B_s - op(A_s) * Y,
529* op(A) = A, A**T, or A**H depending on TRANS (and type).
530*
531 CALL scopy( n, b( 1, j ), 1, res, 1 )
532 IF (y_prec_state .EQ. base_residual) THEN
533 CALL ssymv( uplo, n, -1.0, a, lda, y(1,j), 1,
534 $ 1.0, res, 1 )
535 ELSE IF (y_prec_state .EQ. extra_residual) THEN
536 CALL blas_ssymv_x( uplo2, n, -1.0, a, lda,
537 $ y( 1, j ), 1, 1.0, res, 1, prec_type )
538 ELSE
539 CALL blas_ssymv2_x(uplo2, n, -1.0, a, lda,
540 $ y(1, j), y_tail, 1, 1.0, res, 1, prec_type)
541 END IF
542
543! XXX: RES is no longer needed.
544 CALL scopy( n, res, 1, dy, 1 )
545 CALL ssytrs( uplo, n, 1, af, ldaf, ipiv, dy, n, info )
546*
547* Calculate relative changes DX_X, DZ_Z and ratios DXRAT, DZRAT.
548*
549 normx = 0.0
550 normy = 0.0
551 normdx = 0.0
552 dz_z = 0.0
553 ymin = hugeval
554
555 DO i = 1, n
556 yk = abs( y( i, j ) )
557 dyk = abs( dy( i ) )
558
559 IF ( yk .NE. 0.0 ) THEN
560 dz_z = max( dz_z, dyk / yk )
561 ELSE IF ( dyk .NE. 0.0 ) THEN
562 dz_z = hugeval
563 END IF
564
565 ymin = min( ymin, yk )
566
567 normy = max( normy, yk )
568
569 IF ( colequ ) THEN
570 normx = max( normx, yk * c( i ) )
571 normdx = max( normdx, dyk * c( i ) )
572 ELSE
573 normx = normy
574 normdx = max(normdx, dyk)
575 END IF
576 END DO
577
578 IF ( normx .NE. 0.0 ) THEN
579 dx_x = normdx / normx
580 ELSE IF ( normdx .EQ. 0.0 ) THEN
581 dx_x = 0.0
582 ELSE
583 dx_x = hugeval
584 END IF
585
586 dxrat = normdx / prevnormdx
587 dzrat = dz_z / prev_dz_z
588*
589* Check termination criteria.
590*
591 IF ( ymin*rcond .LT. incr_thresh*normy
592 $ .AND. y_prec_state .LT. extra_y )
593 $ incr_prec = .true.
594
595 IF ( x_state .EQ. noprog_state .AND. dxrat .LE. rthresh )
596 $ x_state = working_state
597 IF ( x_state .EQ. working_state ) THEN
598 IF ( dx_x .LE. eps ) THEN
599 x_state = conv_state
600 ELSE IF ( dxrat .GT. rthresh ) THEN
601 IF ( y_prec_state .NE. extra_y ) THEN
602 incr_prec = .true.
603 ELSE
604 x_state = noprog_state
605 END IF
606 ELSE
607 IF ( dxrat .GT. dxratmax ) dxratmax = dxrat
608 END IF
609 IF ( x_state .GT. working_state ) final_dx_x = dx_x
610 END IF
611
612 IF ( z_state .EQ. unstable_state .AND. dz_z .LE. dz_ub )
613 $ z_state = working_state
614 IF ( z_state .EQ. noprog_state .AND. dzrat .LE. rthresh )
615 $ z_state = working_state
616 IF ( z_state .EQ. working_state ) THEN
617 IF ( dz_z .LE. eps ) THEN
618 z_state = conv_state
619 ELSE IF ( dz_z .GT. dz_ub ) THEN
620 z_state = unstable_state
621 dzratmax = 0.0
622 final_dz_z = hugeval
623 ELSE IF ( dzrat .GT. rthresh ) THEN
624 IF ( y_prec_state .NE. extra_y ) THEN
625 incr_prec = .true.
626 ELSE
627 z_state = noprog_state
628 END IF
629 ELSE
630 IF ( dzrat .GT. dzratmax ) dzratmax = dzrat
631 END IF
632 IF ( z_state .GT. working_state ) final_dz_z = dz_z
633 END IF
634
635 IF ( x_state.NE.working_state.AND.
636 $ ( ignore_cwise.OR.z_state.NE.working_state ) )
637 $ GOTO 666
638
639 IF ( incr_prec ) THEN
640 incr_prec = .false.
641 y_prec_state = y_prec_state + 1
642 DO i = 1, n
643 y_tail( i ) = 0.0
644 END DO
645 END IF
646
647 prevnormdx = normdx
648 prev_dz_z = dz_z
649*
650* Update solution.
651*
652 IF (y_prec_state .LT. extra_y) THEN
653 CALL saxpy( n, 1.0, dy, 1, y(1,j), 1 )
654 ELSE
655 CALL sla_wwaddw( n, y(1,j), y_tail, dy )
656 END IF
657
658 END DO
659* Target of "IF (Z_STOP .AND. X_STOP)". Sun's f77 won't EXIT.
660 666 CONTINUE
661*
662* Set final_* when cnt hits ithresh.
663*
664 IF ( x_state .EQ. working_state ) final_dx_x = dx_x
665 IF ( z_state .EQ. working_state ) final_dz_z = dz_z
666*
667* Compute error bounds.
668*
669 IF ( n_norms .GE. 1 ) THEN
670 err_bnds_norm( j, la_linrx_err_i ) =
671 $ final_dx_x / (1 - dxratmax)
672 END IF
673 IF ( n_norms .GE. 2 ) THEN
674 err_bnds_comp( j, la_linrx_err_i ) =
675 $ final_dz_z / (1 - dzratmax)
676 END IF
677*
678* Compute componentwise relative backward error from formula
679* max(i) ( abs(R(i)) / ( abs(op(A_s))*abs(Y) + abs(B_s) )(i) )
680* where abs(Z) is the componentwise absolute value of the matrix
681* or vector Z.
682*
683* Compute residual RES = B_s - op(A_s) * Y,
684* op(A) = A, A**T, or A**H depending on TRANS (and type).
685 CALL scopy( n, b( 1, j ), 1, res, 1 )
686 CALL ssymv( uplo, n, -1.0, a, lda, y(1,j), 1, 1.0, res, 1 )
687
688 DO i = 1, n
689 ayb( i ) = abs( b( i, j ) )
690 END DO
691*
692* Compute abs(op(A_s))*abs(Y) + abs(B_s).
693*
694 CALL sla_syamv( uplo2, n, 1.0,
695 $ a, lda, y(1, j), 1, 1.0, ayb, 1 )
696
697 CALL sla_lin_berr( n, n, 1, res, ayb, berr_out( j ) )
698*
699* End of loop for each RHS.
700*
701 END DO
702*
703 RETURN
704*
705* End of SLA_SYRFSX_EXTENDED
706*
subroutine xerbla(srname, info)
Definition cblat2.f:3285
subroutine saxpy(n, sa, sx, incx, sy, incy)
SAXPY
Definition saxpy.f:89
subroutine scopy(n, sx, incx, sy, incy)
SCOPY
Definition scopy.f:82
subroutine ssymv(uplo, n, alpha, a, lda, x, incx, beta, y, incy)
SSYMV
Definition ssymv.f:152
subroutine ssytrs(uplo, n, nrhs, a, lda, ipiv, b, ldb, info)
SSYTRS
Definition ssytrs.f:120
integer function ilauplo(uplo)
ILAUPLO
Definition ilauplo.f:58
subroutine sla_syamv(uplo, n, alpha, a, lda, x, incx, beta, y, incy)
SLA_SYAMV computes a matrix-vector product using a symmetric indefinite matrix to calculate error bou...
Definition sla_syamv.f:177
subroutine sla_lin_berr(n, nz, nrhs, res, ayb, berr)
SLA_LIN_BERR computes a component-wise relative backward error.
subroutine sla_wwaddw(n, x, y, w)
SLA_WWADDW adds a vector into a doubled-single vector.
Definition sla_wwaddw.f:81
real function slamch(cmach)
SLAMCH
Definition slamch.f:68
logical function lsame(ca, cb)
LSAME
Definition lsame.f:48
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