1 *> \brief \b DLA_GBRFSX_EXTENDED improves the computed solution to a system of linear equations for general banded matrices by performing extra-precise iterative refinement and provides error bounds and backward error estimates for the solution.
3 * =========== DOCUMENTATION ===========
5 * Online html documentation available at
6 * http://www.netlib.org/lapack/explore-html/
9 *> Download DLA_GBRFSX_EXTENDED + dependencies
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21 * SUBROUTINE DLA_GBRFSX_EXTENDED( PREC_TYPE, TRANS_TYPE, N, KL, KU,
22 * NRHS, AB, LDAB, AFB, LDAFB, IPIV,
23 * COLEQU, C, B, LDB, Y, LDY,
24 * BERR_OUT, N_NORMS, ERR_BNDS_NORM,
25 * ERR_BNDS_COMP, RES, AYB, DY,
26 * Y_TAIL, RCOND, ITHRESH, RTHRESH,
27 * DZ_UB, IGNORE_CWISE, INFO )
29 * .. Scalar Arguments ..
30 * INTEGER INFO, LDAB, LDAFB, LDB, LDY, N, KL, KU, NRHS,
31 * $ PREC_TYPE, TRANS_TYPE, N_NORMS, ITHRESH
32 * LOGICAL COLEQU, IGNORE_CWISE
33 * DOUBLE PRECISION RTHRESH, DZ_UB
35 * .. Array Arguments ..
37 * DOUBLE PRECISION AB( LDAB, * ), AFB( LDAFB, * ), B( LDB, * ),
38 * $ Y( LDY, * ), RES(*), DY(*), Y_TAIL(*)
39 * DOUBLE PRECISION C( * ), AYB(*), RCOND, BERR_OUT(*),
40 * $ ERR_BNDS_NORM( NRHS, * ),
41 * $ ERR_BNDS_COMP( NRHS, * )
51 *> DLA_GBRFSX_EXTENDED improves the computed solution to a system of
52 *> linear equations by performing extra-precise iterative refinement
53 *> and provides error bounds and backward error estimates for the solution.
54 *> This subroutine is called by DGBRFSX to perform iterative refinement.
55 *> In addition to normwise error bound, the code provides maximum
56 *> componentwise error bound if possible. See comments for ERR_BNDS_NORM
57 *> and ERR_BNDS_COMP for details of the error bounds. Note that this
58 *> subroutine is only resonsible for setting the second fields of
59 *> ERR_BNDS_NORM and ERR_BNDS_COMP.
65 *> \param[in] PREC_TYPE
67 *> PREC_TYPE is INTEGER
68 *> Specifies the intermediate precision to be used in refinement.
69 *> The value is defined by ILAPREC(P) where P is a CHARACTER and
76 *> \param[in] TRANS_TYPE
78 *> TRANS_TYPE is INTEGER
79 *> Specifies the transposition operation on A.
80 *> The value is defined by ILATRANS(T) where T is a CHARACTER and
81 *> T = 'N': No transpose
83 *> = 'C': Conjugate transpose
89 *> The number of linear equations, i.e., the order of the
96 *> The number of subdiagonals within the band of A. KL >= 0.
102 *> The number of superdiagonals within the band of A. KU >= 0
108 *> The number of right-hand-sides, i.e., the number of columns of the
114 *> AB is DOUBLE PRECISION array, dimension (LDAB,N)
115 *> On entry, the N-by-N matrix AB.
121 *> The leading dimension of the array AB. LDBA >= max(1,N).
126 *> AFB is DOUBLE PRECISION array, dimension (LDAFB,N)
127 *> The factors L and U from the factorization
128 *> A = P*L*U as computed by DGBTRF.
134 *> The leading dimension of the array AF. LDAFB >= max(1,N).
139 *> IPIV is INTEGER array, dimension (N)
140 *> The pivot indices from the factorization A = P*L*U
141 *> as computed by DGBTRF; row i of the matrix was interchanged
148 *> If .TRUE. then column equilibration was done to A before calling
149 *> this routine. This is needed to compute the solution and error
155 *> C is DOUBLE PRECISION array, dimension (N)
156 *> The column scale factors for A. If COLEQU = .FALSE., C
157 *> is not accessed. If C is input, each element of C should be a power
158 *> of the radix to ensure a reliable solution and error estimates.
159 *> Scaling by powers of the radix does not cause rounding errors unless
160 *> the result underflows or overflows. Rounding errors during scaling
161 *> lead to refining with a matrix that is not equivalent to the
162 *> input matrix, producing error estimates that may not be
168 *> B is DOUBLE PRECISION array, dimension (LDB,NRHS)
169 *> The right-hand-side matrix B.
175 *> The leading dimension of the array B. LDB >= max(1,N).
180 *> Y is DOUBLE PRECISION array, dimension
182 *> On entry, the solution matrix X, as computed by DGBTRS.
183 *> On exit, the improved solution matrix Y.
189 *> The leading dimension of the array Y. LDY >= max(1,N).
192 *> \param[out] BERR_OUT
194 *> BERR_OUT is DOUBLE PRECISION array, dimension (NRHS)
195 *> On exit, BERR_OUT(j) contains the componentwise relative backward
196 *> error for right-hand-side j from the formula
197 *> max(i) ( abs(RES(i)) / ( abs(op(A_s))*abs(Y) + abs(B_s) )(i) )
198 *> where abs(Z) is the componentwise absolute value of the matrix
199 *> or vector Z. This is computed by DLA_LIN_BERR.
202 *> \param[in] N_NORMS
204 *> N_NORMS is INTEGER
205 *> Determines which error bounds to return (see ERR_BNDS_NORM
206 *> and ERR_BNDS_COMP).
207 *> If N_NORMS >= 1 return normwise error bounds.
208 *> If N_NORMS >= 2 return componentwise error bounds.
211 *> \param[in,out] ERR_BNDS_NORM
213 *> ERR_BNDS_NORM is DOUBLE PRECISION array, dimension
214 *> (NRHS, N_ERR_BNDS)
215 *> For each right-hand side, this array contains information about
216 *> various error bounds and condition numbers corresponding to the
217 *> normwise relative error, which is defined as follows:
219 *> Normwise relative error in the ith solution vector:
220 *> max_j (abs(XTRUE(j,i) - X(j,i)))
221 *> ------------------------------
224 *> The array is indexed by the type of error information as described
225 *> below. There currently are up to three pieces of information
228 *> The first index in ERR_BNDS_NORM(i,:) corresponds to the ith
231 *> The second index in ERR_BNDS_NORM(:,err) contains the following
233 *> err = 1 "Trust/don't trust" boolean. Trust the answer if the
234 *> reciprocal condition number is less than the threshold
235 *> sqrt(n) * slamch('Epsilon').
237 *> err = 2 "Guaranteed" error bound: The estimated forward error,
238 *> almost certainly within a factor of 10 of the true error
239 *> so long as the next entry is greater than the threshold
240 *> sqrt(n) * slamch('Epsilon'). This error bound should only
241 *> be trusted if the previous boolean is true.
243 *> err = 3 Reciprocal condition number: Estimated normwise
244 *> reciprocal condition number. Compared with the threshold
245 *> sqrt(n) * slamch('Epsilon') to determine if the error
246 *> estimate is "guaranteed". These reciprocal condition
247 *> numbers are 1 / (norm(Z^{-1},inf) * norm(Z,inf)) for some
248 *> appropriately scaled matrix Z.
249 *> Let Z = S*A, where S scales each row by a power of the
250 *> radix so all absolute row sums of Z are approximately 1.
252 *> This subroutine is only responsible for setting the second field
254 *> See Lapack Working Note 165 for further details and extra
258 *> \param[in,out] ERR_BNDS_COMP
260 *> ERR_BNDS_COMP is DOUBLE PRECISION array, dimension
261 *> (NRHS, N_ERR_BNDS)
262 *> For each right-hand side, this array contains information about
263 *> various error bounds and condition numbers corresponding to the
264 *> componentwise relative error, which is defined as follows:
266 *> Componentwise relative error in the ith solution vector:
267 *> abs(XTRUE(j,i) - X(j,i))
268 *> max_j ----------------------
271 *> The array is indexed by the right-hand side i (on which the
272 *> componentwise relative error depends), and the type of error
273 *> information as described below. There currently are up to three
274 *> pieces of information returned for each right-hand side. If
275 *> componentwise accuracy is not requested (PARAMS(3) = 0.0), then
276 *> ERR_BNDS_COMP is not accessed. If N_ERR_BNDS .LT. 3, then at most
277 *> the first (:,N_ERR_BNDS) entries are returned.
279 *> The first index in ERR_BNDS_COMP(i,:) corresponds to the ith
282 *> The second index in ERR_BNDS_COMP(:,err) contains the following
284 *> err = 1 "Trust/don't trust" boolean. Trust the answer if the
285 *> reciprocal condition number is less than the threshold
286 *> sqrt(n) * slamch('Epsilon').
288 *> err = 2 "Guaranteed" error bound: The estimated forward error,
289 *> almost certainly within a factor of 10 of the true error
290 *> so long as the next entry is greater than the threshold
291 *> sqrt(n) * slamch('Epsilon'). This error bound should only
292 *> be trusted if the previous boolean is true.
294 *> err = 3 Reciprocal condition number: Estimated componentwise
295 *> reciprocal condition number. Compared with the threshold
296 *> sqrt(n) * slamch('Epsilon') to determine if the error
297 *> estimate is "guaranteed". These reciprocal condition
298 *> numbers are 1 / (norm(Z^{-1},inf) * norm(Z,inf)) for some
299 *> appropriately scaled matrix Z.
300 *> Let Z = S*(A*diag(x)), where x is the solution for the
301 *> current right-hand side and S scales each row of
302 *> A*diag(x) by a power of the radix so all absolute row
303 *> sums of Z are approximately 1.
305 *> This subroutine is only responsible for setting the second field
307 *> See Lapack Working Note 165 for further details and extra
313 *> RES is DOUBLE PRECISION array, dimension (N)
314 *> Workspace to hold the intermediate residual.
319 *> AYB is DOUBLE PRECISION array, dimension (N)
320 *> Workspace. This can be the same workspace passed for Y_TAIL.
325 *> DY is DOUBLE PRECISION array, dimension (N)
326 *> Workspace to hold the intermediate solution.
331 *> Y_TAIL is DOUBLE PRECISION array, dimension (N)
332 *> Workspace to hold the trailing bits of the intermediate solution.
337 *> RCOND is DOUBLE PRECISION
338 *> Reciprocal scaled condition number. This is an estimate of the
339 *> reciprocal Skeel condition number of the matrix A after
340 *> equilibration (if done). If this is less than the machine
341 *> precision (in particular, if it is zero), the matrix is singular
342 *> to working precision. Note that the error may still be small even
343 *> if this number is very small and the matrix appears ill-
347 *> \param[in] ITHRESH
349 *> ITHRESH is INTEGER
350 *> The maximum number of residual computations allowed for
351 *> refinement. The default is 10. For 'aggressive' set to 100 to
352 *> permit convergence using approximate factorizations or
353 *> factorizations other than LU. If the factorization uses a
354 *> technique other than Gaussian elimination, the guarantees in
355 *> ERR_BNDS_NORM and ERR_BNDS_COMP may no longer be trustworthy.
358 *> \param[in] RTHRESH
360 *> RTHRESH is DOUBLE PRECISION
361 *> Determines when to stop refinement if the error estimate stops
362 *> decreasing. Refinement will stop when the next solution no longer
363 *> satisfies norm(dx_{i+1}) < RTHRESH * norm(dx_i) where norm(Z) is
364 *> the infinity norm of Z. RTHRESH satisfies 0 < RTHRESH <= 1. The
365 *> default value is 0.5. For 'aggressive' set to 0.9 to permit
366 *> convergence on extremely ill-conditioned matrices. See LAWN 165
372 *> DZ_UB is DOUBLE PRECISION
373 *> Determines when to start considering componentwise convergence.
374 *> Componentwise convergence is only considered after each component
375 *> of the solution Y is stable, which we definte as the relative
376 *> change in each component being less than DZ_UB. The default value
377 *> is 0.25, requiring the first bit to be stable. See LAWN 165 for
381 *> \param[in] IGNORE_CWISE
383 *> IGNORE_CWISE is LOGICAL
384 *> If .TRUE. then ignore componentwise convergence. Default value
391 *> = 0: Successful exit.
392 *> < 0: if INFO = -i, the ith argument to DGBTRS had an illegal
399 *> \author Univ. of Tennessee
400 *> \author Univ. of California Berkeley
401 *> \author Univ. of Colorado Denver
404 *> \date September 2012
406 *> \ingroup doubleGBcomputational
408 * =====================================================================
409 SUBROUTINE DLA_GBRFSX_EXTENDED( PREC_TYPE, TRANS_TYPE, N, KL, KU,
410 $ NRHS, AB, LDAB, AFB, LDAFB, IPIV,
411 $ COLEQU, C, B, LDB, Y, LDY,
412 $ BERR_OUT, N_NORMS, ERR_BNDS_NORM,
413 $ ERR_BNDS_COMP, RES, AYB, DY,
414 $ Y_TAIL, RCOND, ITHRESH, RTHRESH,
415 $ DZ_UB, IGNORE_CWISE, INFO )
417 * -- LAPACK computational routine (version 3.4.2) --
418 * -- LAPACK is a software package provided by Univ. of Tennessee, --
419 * -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
422 * .. Scalar Arguments ..
423 INTEGER INFO, LDAB, LDAFB, LDB, LDY, N, KL, KU, NRHS,
424 $ PREC_TYPE, TRANS_TYPE, N_NORMS, ITHRESH
425 LOGICAL COLEQU, IGNORE_CWISE
426 DOUBLE PRECISION RTHRESH, DZ_UB
428 * .. Array Arguments ..
430 DOUBLE PRECISION AB( LDAB, * ), AFB( LDAFB, * ), B( LDB, * ),
431 $ Y( LDY, * ), RES(*), DY(*), Y_TAIL(*)
432 DOUBLE PRECISION C( * ), AYB(*), RCOND, BERR_OUT(*),
433 $ ERR_BNDS_NORM( NRHS, * ),
434 $ ERR_BNDS_COMP( NRHS, * )
437 * =====================================================================
439 * .. Local Scalars ..
441 INTEGER CNT, I, J, M, X_STATE, Z_STATE, Y_PREC_STATE
442 DOUBLE PRECISION YK, DYK, YMIN, NORMY, NORMX, NORMDX, DXRAT,
443 $ DZRAT, PREVNORMDX, PREV_DZ_Z, DXRATMAX,
444 $ DZRATMAX, DX_X, DZ_Z, FINAL_DX_X, FINAL_DZ_Z,
445 $ EPS, HUGEVAL, INCR_THRESH
449 INTEGER UNSTABLE_STATE, WORKING_STATE, CONV_STATE,
450 $ NOPROG_STATE, BASE_RESIDUAL, EXTRA_RESIDUAL,
452 PARAMETER ( UNSTABLE_STATE = 0, WORKING_STATE = 1,
453 $ CONV_STATE = 2, NOPROG_STATE = 3 )
454 PARAMETER ( BASE_RESIDUAL = 0, EXTRA_RESIDUAL = 1,
456 INTEGER FINAL_NRM_ERR_I, FINAL_CMP_ERR_I, BERR_I
457 INTEGER RCOND_I, NRM_RCOND_I, NRM_ERR_I, CMP_RCOND_I
458 INTEGER CMP_ERR_I, PIV_GROWTH_I
459 PARAMETER ( FINAL_NRM_ERR_I = 1, FINAL_CMP_ERR_I = 2,
461 PARAMETER ( RCOND_I = 4, NRM_RCOND_I = 5, NRM_ERR_I = 6 )
462 PARAMETER ( CMP_RCOND_I = 7, CMP_ERR_I = 8,
464 INTEGER LA_LINRX_ITREF_I, LA_LINRX_ITHRESH_I,
466 PARAMETER ( LA_LINRX_ITREF_I = 1,
467 $ LA_LINRX_ITHRESH_I = 2 )
468 PARAMETER ( LA_LINRX_CWISE_I = 3 )
469 INTEGER LA_LINRX_TRUST_I, LA_LINRX_ERR_I,
471 PARAMETER ( LA_LINRX_TRUST_I = 1, LA_LINRX_ERR_I = 2 )
472 PARAMETER ( LA_LINRX_RCOND_I = 3 )
474 * .. External Subroutines ..
475 EXTERNAL DAXPY, DCOPY, DGBTRS, DGBMV, BLAS_DGBMV_X,
476 $ BLAS_DGBMV2_X, DLA_GBAMV, DLA_WWADDW, DLAMCH,
477 $ CHLA_TRANSTYPE, DLA_LIN_BERR
478 DOUBLE PRECISION DLAMCH
479 CHARACTER CHLA_TRANSTYPE
481 * .. Intrinsic Functions ..
482 INTRINSIC ABS, MAX, MIN
484 * .. Executable Statements ..
486 IF (INFO.NE.0) RETURN
487 TRANS = CHLA_TRANSTYPE(TRANS_TYPE)
488 EPS = DLAMCH( 'Epsilon' )
489 HUGEVAL = DLAMCH( 'Overflow' )
490 * Force HUGEVAL to Inf
491 HUGEVAL = HUGEVAL * HUGEVAL
492 * Using HUGEVAL may lead to spurious underflows.
493 INCR_THRESH = DBLE( N ) * EPS
497 Y_PREC_STATE = EXTRA_RESIDUAL
498 IF ( Y_PREC_STATE .EQ. EXTRA_Y ) THEN
515 X_STATE = WORKING_STATE
516 Z_STATE = UNSTABLE_STATE
521 * Compute residual RES = B_s - op(A_s) * Y,
522 * op(A) = A, A**T, or A**H depending on TRANS (and type).
524 CALL DCOPY( N, B( 1, J ), 1, RES, 1 )
525 IF ( Y_PREC_STATE .EQ. BASE_RESIDUAL ) THEN
526 CALL DGBMV( TRANS, M, N, KL, KU, -1.0D+0, AB, LDAB,
527 $ Y( 1, J ), 1, 1.0D+0, RES, 1 )
528 ELSE IF ( Y_PREC_STATE .EQ. EXTRA_RESIDUAL ) THEN
529 CALL BLAS_DGBMV_X( TRANS_TYPE, N, N, KL, KU,
530 $ -1.0D+0, AB, LDAB, Y( 1, J ), 1, 1.0D+0, RES, 1,
533 CALL BLAS_DGBMV2_X( TRANS_TYPE, N, N, KL, KU, -1.0D+0,
534 $ AB, LDAB, Y( 1, J ), Y_TAIL, 1, 1.0D+0, RES, 1,
538 ! XXX: RES is no longer needed.
539 CALL DCOPY( N, RES, 1, DY, 1 )
540 CALL DGBTRS( TRANS, N, KL, KU, 1, AFB, LDAFB, IPIV, DY, N,
543 * Calculate relative changes DX_X, DZ_Z and ratios DXRAT, DZRAT.
552 YK = ABS( Y( I, J ) )
555 IF ( YK .NE. 0.0D+0 ) THEN
556 DZ_Z = MAX( DZ_Z, DYK / YK )
557 ELSE IF ( DYK .NE. 0.0D+0 ) THEN
561 YMIN = MIN( YMIN, YK )
563 NORMY = MAX( NORMY, YK )
566 NORMX = MAX( NORMX, YK * C( I ) )
567 NORMDX = MAX( NORMDX, DYK * C( I ) )
570 NORMDX = MAX( NORMDX, DYK )
574 IF ( NORMX .NE. 0.0D+0 ) THEN
575 DX_X = NORMDX / NORMX
576 ELSE IF ( NORMDX .EQ. 0.0D+0 ) THEN
582 DXRAT = NORMDX / PREVNORMDX
583 DZRAT = DZ_Z / PREV_DZ_Z
585 * Check termination criteria.
587 IF ( .NOT.IGNORE_CWISE
588 $ .AND. YMIN*RCOND .LT. INCR_THRESH*NORMY
589 $ .AND. Y_PREC_STATE .LT. EXTRA_Y )
592 IF ( X_STATE .EQ. NOPROG_STATE .AND. DXRAT .LE. RTHRESH )
593 $ X_STATE = WORKING_STATE
594 IF ( X_STATE .EQ. WORKING_STATE ) THEN
595 IF ( DX_X .LE. EPS ) THEN
597 ELSE IF ( DXRAT .GT. RTHRESH ) THEN
598 IF ( Y_PREC_STATE .NE. EXTRA_Y ) THEN
601 X_STATE = NOPROG_STATE
604 IF ( DXRAT .GT. DXRATMAX ) DXRATMAX = DXRAT
606 IF ( X_STATE .GT. WORKING_STATE ) FINAL_DX_X = DX_X
609 IF ( Z_STATE .EQ. UNSTABLE_STATE .AND. DZ_Z .LE. DZ_UB )
610 $ Z_STATE = WORKING_STATE
611 IF ( Z_STATE .EQ. NOPROG_STATE .AND. DZRAT .LE. RTHRESH )
612 $ Z_STATE = WORKING_STATE
613 IF ( Z_STATE .EQ. WORKING_STATE ) THEN
614 IF ( DZ_Z .LE. EPS ) THEN
616 ELSE IF ( DZ_Z .GT. DZ_UB ) THEN
617 Z_STATE = UNSTABLE_STATE
620 ELSE IF ( DZRAT .GT. RTHRESH ) THEN
621 IF ( Y_PREC_STATE .NE. EXTRA_Y ) THEN
624 Z_STATE = NOPROG_STATE
627 IF ( DZRAT .GT. DZRATMAX ) DZRATMAX = DZRAT
629 IF ( Z_STATE .GT. WORKING_STATE ) FINAL_DZ_Z = DZ_Z
632 * Exit if both normwise and componentwise stopped working,
633 * but if componentwise is unstable, let it go at least two
636 IF ( X_STATE.NE.WORKING_STATE ) THEN
637 IF ( IGNORE_CWISE ) GOTO 666
638 IF ( Z_STATE.EQ.NOPROG_STATE .OR. Z_STATE.EQ.CONV_STATE )
640 IF ( Z_STATE.EQ.UNSTABLE_STATE .AND. CNT.GT.1 ) GOTO 666
643 IF ( INCR_PREC ) THEN
645 Y_PREC_STATE = Y_PREC_STATE + 1
656 IF (Y_PREC_STATE .LT. EXTRA_Y) THEN
657 CALL DAXPY( N, 1.0D+0, DY, 1, Y(1,J), 1 )
659 CALL DLA_WWADDW( N, Y(1,J), Y_TAIL, DY )
663 * Target of "IF (Z_STOP .AND. X_STOP)". Sun's f77 won't EXIT.
666 * Set final_* when cnt hits ithresh.
668 IF ( X_STATE .EQ. WORKING_STATE ) FINAL_DX_X = DX_X
669 IF ( Z_STATE .EQ. WORKING_STATE ) FINAL_DZ_Z = DZ_Z
671 * Compute error bounds.
673 IF ( N_NORMS .GE. 1 ) THEN
674 ERR_BNDS_NORM( J, LA_LINRX_ERR_I ) =
675 $ FINAL_DX_X / (1 - DXRATMAX)
677 IF (N_NORMS .GE. 2) THEN
678 ERR_BNDS_COMP( J, LA_LINRX_ERR_I ) =
679 $ FINAL_DZ_Z / (1 - DZRATMAX)
682 * Compute componentwise relative backward error from formula
683 * max(i) ( abs(R(i)) / ( abs(op(A_s))*abs(Y) + abs(B_s) )(i) )
684 * where abs(Z) is the componentwise absolute value of the matrix
687 * Compute residual RES = B_s - op(A_s) * Y,
688 * op(A) = A, A**T, or A**H depending on TRANS (and type).
690 CALL DCOPY( N, B( 1, J ), 1, RES, 1 )
691 CALL DGBMV(TRANS, N, N, KL, KU, -1.0D+0, AB, LDAB, Y(1,J),
692 $ 1, 1.0D+0, RES, 1 )
695 AYB( I ) = ABS( B( I, J ) )
698 * Compute abs(op(A_s))*abs(Y) + abs(B_s).
700 CALL DLA_GBAMV( TRANS_TYPE, N, N, KL, KU, 1.0D+0,
701 $ AB, LDAB, Y(1, J), 1, 1.0D+0, AYB, 1 )
703 CALL DLA_LIN_BERR( N, N, 1, RES, AYB, BERR_OUT( J ) )
705 * End of loop for each RHS