f07bhc returns error bounds for the solution of a real band system of linear equations with multiple right-hand sides, or . It improves the solution by iterative refinement, in order to reduce the backward error as much as possible.
The function may be called by the names: f07bhc, nag_lapacklin_dgbrfs or nag_dgbrfs.
3Description
f07bhc returns the backward errors and estimated bounds on the forward errors for the solution of a real band system of linear equations with multiple right-hand sides or . The function handles each right-hand side vector (stored as a column of the matrix ) independently, so we describe the function of f07bhc in terms of a single right-hand side and solution .
Given a computed solution , the function computes the component-wise backward error
. This is the size of the smallest relative perturbation in each element of and such that is the exact solution of a perturbed system
Then the function estimates a bound for the component-wise forward error in the computed solution, defined by:
Golub G H and Van Loan C F (1996) Matrix Computations (3rd Edition) Johns Hopkins University Press, Baltimore
5Arguments
1: – Nag_OrderTypeInput
On entry: the order argument specifies the two-dimensional storage scheme being used, i.e., row-major ordering or column-major ordering. C language defined storage is specified by . See Section 3.1.3 in the Introduction to the NAG Library CL Interface for a more detailed explanation of the use of this argument.
Constraint:
or .
2: – Nag_TransTypeInput
On entry: indicates the form of the linear equations for which is the computed solution.
The linear equations are of the form .
or
The linear equations are of the form .
Constraint:
, or .
3: – IntegerInput
On entry: , the order of the matrix .
Constraint:
.
4: – IntegerInput
On entry: , the number of subdiagonals within the band of the matrix .
Constraint:
.
5: – IntegerInput
On entry: , the number of superdiagonals within the band of the matrix .
Constraint:
.
6: – IntegerInput
On entry: , the number of right-hand sides.
Constraint:
.
7: – const doubleInput
Note: the dimension, dim, of the array ab
must be at least
.
On entry: the original band matrix as supplied to f07bdc but with reduced requirements since the matrix is not factorized.
This is stored as a notional two-dimensional array with row elements or column elements stored contiguously. The storage of elements , for row and column , depends on the order argument as follows:
On entry: the stride separating row or column elements (depending on the value of order) of the matrix in the array
ab.
Constraint:
.
9: – const doubleInput
Note: the dimension, dim, of the array afb
must be at least
.
On entry: the factorization of , as returned by f07bdc.
10: – IntegerInput
On entry: the stride separating row or column elements (depending on the value of order) of the matrix in the array
afb.
Constraint:
.
11: – const IntegerInput
Note: the dimension, dim, of the array ipiv
must be at least
.
On entry: the pivot indices, as returned by f07bdc.
12: – const doubleInput
Note: the dimension, dim, of the array b
must be at least
when
;
when
.
The th element of the matrix is stored in
when ;
when .
On entry: the right-hand side matrix .
13: – IntegerInput
On entry: the stride separating row or column elements (depending on the value of order) in the array b.
Constraints:
if ,
;
if , .
14: – doubleInput/Output
Note: the dimension, dim, of the array x
must be at least
when
;
when
.
The th element of the matrix is stored in
when ;
when .
On entry: the solution matrix , as returned by f07bec.
On exit: the improved solution matrix .
15: – IntegerInput
On entry: the stride separating row or column elements (depending on the value of order) in the array x.
Constraints:
if ,
;
if , .
16: – doubleOutput
On exit: contains an estimated error bound for the th solution vector, that is, the th column of , for .
17: – doubleOutput
On exit: contains the component-wise backward error bound for the th solution vector, that is, the th column of , for .
18: – NagError *Input/Output
The NAG error argument (see Section 7 in the Introduction to the NAG Library CL Interface).
6Error Indicators and Warnings
NE_ALLOC_FAIL
Dynamic memory allocation failed.
See Section 3.1.2 in the Introduction to the NAG Library CL Interface for further information.
NE_BAD_PARAM
On entry, argument had an illegal value.
NE_INT
On entry, .
Constraint: .
On entry, .
Constraint: .
On entry, .
Constraint: .
On entry, .
Constraint: .
On entry, . Constraint: .
On entry, . Constraint: .
On entry, . Constraint: .
On entry, . Constraint: .
NE_INT_2
On entry, and .
Constraint: .
On entry, and .
Constraint: .
On entry, and .
Constraint: .
On entry, and .
Constraint: .
NE_INT_3
On entry, , and .
Constraint: .
On entry, , and .
Constraint: .
NE_INTERNAL_ERROR
An internal error has occurred in this function. Check the function call and any array sizes. If the call is correct then please contact NAG for assistance.
See Section 7.5 in the Introduction to the NAG Library CL Interface for further information.
NE_NO_LICENCE
Your licence key may have expired or may not have been installed correctly.
See Section 8 in the Introduction to the NAG Library CL Interface for further information.
7Accuracy
The bounds returned in ferr are not rigorous, because they are estimated, not computed exactly; but in practice they almost always overestimate the actual error.
8Parallelism and Performance
Background information to multithreading can be found in the Multithreading documentation.
f07bhc is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.
f07bhc makes calls to BLAS and/or LAPACK routines, which may be threaded within the vendor library used by this implementation. Consult the documentation for the vendor library for further information.
Please consult the X06 Chapter Introduction for information on how to control and interrogate the OpenMP environment used within this function. Please also consult the Users' Note for your implementation for any additional implementation-specific information.
9Further Comments
For each right-hand side, computation of the backward error involves a minimum of floating-point operations. Each step of iterative refinement involves an additional operations. This assumes and . At most five steps of iterative refinement are performed, but usually only one or two steps are required.
Estimating the forward error involves solving a number of systems of linear equations of the form or ; the number is usually or and never more than . Each solution involves approximately operations.