ZLA_GERFSX_EXTENDED
Purpose
ZLA_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 ZGERFSX 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 resonsible for setting the second fields of
ERR_BNDS_NORM and ERR_BNDS_COMP.
linear equations by performing extra-precise iterative refinement
and provides error bounds and backward error estimates for the solution.
This subroutine is called by ZGERFSX 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 resonsible for setting the second fields of
ERR_BNDS_NORM and ERR_BNDS_COMP.
Arguments
| PREC_TYPE |
(input) 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', 'E': Extra |
| TRANS_TYPE |
(input) 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 |
| N |
(input) INTEGER
The number of linear equations, i.e., the order of the
matrix A. N >= 0. |
| NRHS |
(input) INTEGER
The number of right-hand-sides, i.e., the number of columns of the
matrix B. |
| A |
(input) COMPLEX*16 array, dimension (LDA,N)
On entry, the N-by-N matrix A.
|
| LDA |
(input) INTEGER
The leading dimension of the array A. LDA >= max(1,N).
|
| AF |
(input) COMPLEX*16 array, dimension (LDAF,N)
The factors L and U from the factorization
|
| A |
= P*L*U as computed by ZGETRF.
|
| LDAF |
(input) INTEGER
The leading dimension of the array AF. LDAF >= max(1,N).
|
| IPIV |
(input) INTEGER array, dimension (N)
The pivot indices from the factorization A = P*L*U
as computed by ZGETRF; row i of the matrix was interchanged with row IPIV(i). |
| COLEQU |
(input) 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. |
| C |
(input) 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. |
| B |
(input) COMPLEX*16 array, dimension (LDB,NRHS)
The right-hand-side matrix B.
|
| LDB |
(input) INTEGER
The leading dimension of the array B. LDB >= max(1,N).
|
| Y |
(input/output) COMPLEX*16 array, dimension (LDY,NRHS)
On entry, the solution matrix X, as computed by ZGETRS.
On exit, the improved solution matrix Y. |
| LDY |
(input) INTEGER
The leading dimension of the array Y. LDY >= max(1,N).
|
| BERR_OUT |
(output) 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 ZLA_LIN_BERR. |
| N_NORMS |
(input) 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. |
| ERR_BNDS_NORM |
(input/output) 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 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. |
| ERR_BNDS_COMP |
(input/output) 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 |
| ERR_BNDS_COMP |
is not accessed. If N_ERR_BNDS .LT. 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. |
| RES |
(input) COMPLEX*16 array, dimension (N)
Workspace to hold the intermediate residual.
|
| AYB |
(input) DOUBLE PRECISION array, dimension (N)
Workspace.
|
| DY |
(input) COMPLEX*16 array, dimension (N)
Workspace to hold the intermediate solution.
|
| Y_TAIL |
(input) COMPLEX*16 array, dimension (N)
Workspace to hold the trailing bits of the intermediate solution.
|
| RCOND |
(input) 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. |
| ITHRESH |
(input) 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.
|
| RTHRESH |
(input) 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. |
| DZ_UB |
(input) 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 definte 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. |
| IGNORE_CWISE |
(input) LOGICAL
If .TRUE. then ignore componentwise convergence. Default value
is .FALSE.. |
| INFO |
(output) INTEGER
= 0: Successful exit.
< 0: if INFO = -i, the ith argument to ZGETRS had an illegal value |