NAG CL Interface
f07jvc (zptrfs)

1 Purpose

f07jvc computes error bounds and refines the solution to a complex system of linear equations AX=B , where A is an n by n Hermitian positive definite tridiagonal matrix and X and B are n by r matrices, using the modified Cholesky factorization returned by f07jrc and an initial solution returned by f07jsc. Iterative refinement is used to reduce the backward error as much as possible.

2 Specification

#include <nag.h>
void  f07jvc (Nag_OrderType order, Nag_UploType uplo, Integer n, Integer nrhs, const double d[], const Complex e[], const double df[], const Complex ef[], const Complex b[], Integer pdb, Complex x[], Integer pdx, double ferr[], double berr[], NagError *fail)
The function may be called by the names: f07jvc, nag_lapacklin_zptrfs or nag_zptrfs.

3 Description

f07jvc should normally be preceded by calls to f07jrc and f07jsc. f07jrc computes a modified Cholesky factorization of the matrix A as
A=LDLH ,  
where L is a unit lower bidiagonal matrix and D is a diagonal matrix, with positive diagonal elements. f07jsc then utilizes the factorization to compute a solution, X^ , to the required equations. Letting x^ denote a column of X^ , f07jvc computes a component-wise backward error, β , the smallest relative perturbation in each element of A and b such that x^ is the exact solution of a perturbed system
A+E x^ = b + f , with  eij β aij , and  fj β bj .  
The function also estimates a bound for the component-wise forward error in the computed solution defined by max xi - xi^ / max xi^ , where x is the corresponding column of the exact solution, X .
Note that the modified Cholesky factorization of A can also be expressed as
A=UHDU ,  
where U is unit upper bidiagonal.

4 References

Anderson E, Bai Z, Bischof C, Blackford S, Demmel J, Dongarra J J, Du Croz J J, Greenbaum A, Hammarling S, McKenney A and Sorensen D (1999) LAPACK Users' Guide (3rd Edition) SIAM, Philadelphia https://www.netlib.org/lapack/lug

5 Arguments

1: order Nag_OrderType Input
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 order=Nag_RowMajor. 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: order=Nag_RowMajor or Nag_ColMajor.
2: uplo Nag_UploType Input
On entry: specifies the form of the factorization as follows:
uplo=Nag_Upper
A=UHDU.
uplo=Nag_Lower
A=LDLH.
Constraint: uplo=Nag_Upper or Nag_Lower.
3: n Integer Input
On entry: n, the order of the matrix A.
Constraint: n0.
4: nrhs Integer Input
On entry: r, the number of right-hand sides, i.e., the number of columns of the matrix B.
Constraint: nrhs0.
5: d[dim] const double Input
Note: the dimension, dim, of the array d must be at least max1,n.
On entry: must contain the n diagonal elements of the matrix of A.
6: e[dim] const Complex Input
Note: the dimension, dim, of the array e must be at least max1,n-1.
On entry: if uplo=Nag_Upper, e must contain the n-1 superdiagonal elements of the matrix A.
If uplo=Nag_Lower, e must contain the n-1 subdiagonal elements of the matrix A.
7: df[dim] const double Input
Note: the dimension, dim, of the array df must be at least max1,n.
On entry: must contain the n diagonal elements of the diagonal matrix D from the LDLT factorization of A.
8: ef[dim] const Complex Input
Note: the dimension, dim, of the array ef must be at least max1,n-1.
On entry: if uplo=Nag_Upper, ef must contain the n-1 superdiagonal elements of the unit upper bidiagonal matrix U from the UHDU factorization of A.
If uplo=Nag_Lower, ef must contain the n-1 subdiagonal elements of the unit lower bidiagonal matrix L from the LDLH factorization of A.
9: b[dim] const Complex Input
Note: the dimension, dim, of the array b must be at least
  • max1,pdb×nrhs when order=Nag_ColMajor;
  • max1,n×pdb when order=Nag_RowMajor.
The i,jth element of the matrix B is stored in
  • b[j-1×pdb+i-1] when order=Nag_ColMajor;
  • b[i-1×pdb+j-1] when order=Nag_RowMajor.
On entry: the n by r matrix of right-hand sides B.
10: pdb Integer Input
On entry: the stride separating row or column elements (depending on the value of order) in the array b.
Constraints:
  • if order=Nag_ColMajor, pdbmax1,n;
  • if order=Nag_RowMajor, pdbmax1,nrhs.
11: x[dim] Complex Input/Output
Note: the dimension, dim, of the array x must be at least
  • max1,pdx×nrhs when order=Nag_ColMajor;
  • max1,n×pdx when order=Nag_RowMajor.
The i,jth element of the matrix X is stored in
  • x[j-1×pdx+i-1] when order=Nag_ColMajor;
  • x[i-1×pdx+j-1] when order=Nag_RowMajor.
On entry: the n by r initial solution matrix X.
On exit: the n by r refined solution matrix X.
12: pdx Integer Input
On entry: the stride separating row or column elements (depending on the value of order) in the array x.
Constraints:
  • if order=Nag_ColMajor, pdxmax1,n;
  • if order=Nag_RowMajor, pdxmax1,nrhs.
13: ferr[nrhs] double Output
On exit: estimate of the forward error bound for each computed solution vector, such that x^j-xj/x^jferr[j-1], where x^j is the jth column of the computed solution returned in the array x and xj is the corresponding column of the exact solution X. The estimate is almost always a slight overestimate of the true error.
14: berr[nrhs] double Output
On exit: estimate of the component-wise relative backward error of each computed solution vector x^j (i.e., the smallest relative change in any element of A or B that makes x^j an exact solution).
15: fail NagError * Input/Output
The NAG error argument (see Section 7 in the Introduction to the NAG Library CL Interface).

6 Error 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 value had an illegal value.
NE_INT
On entry, n=value.
Constraint: n0.
On entry, nrhs=value.
Constraint: nrhs0.
On entry, pdb=value.
Constraint: pdb>0.
On entry, pdx=value.
Constraint: pdx>0.
NE_INT_2
On entry, pdb=value and n=value.
Constraint: pdbmax1,n.
On entry, pdb=value and nrhs=value.
Constraint: pdbmax1,nrhs.
On entry, pdx=value and n=value.
Constraint: pdxmax1,n.
On entry, pdx=value and nrhs=value.
Constraint: pdxmax1,nrhs.
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.

7 Accuracy

The computed solution for a single right-hand side, x^ , satisfies an equation of the form
A+E x^=b ,  
where
E=OεA  
and ε is the machine precision. An approximate error bound for the computed solution is given by
x^ - x x κA E A ,  
where κA=A-1 A , the condition number of A with respect to the solution of the linear equations. See Section 4.4 of Anderson et al. (1999) for further details.
Function f07juc can be used to compute the condition number of A .

8 Parallelism and Performance

f07jvc is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.
f07jvc 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.

9 Further Comments

The total number of floating-point operations required to solve the equations AX=B is proportional to nr . At most five steps of iterative refinement are performed, but usually only one or two steps are required.
The real analogue of this function is f07jhc.

10 Example

This example solves the equations
AX=B ,  
where A is the Hermitian positive definite tridiagonal matrix
A = 16.0i+00.0 16.0-16.0i 0.0i+0.0 0.0i+0.0 16.0+16.0i 41.0i+00.0 18.0+9.0i 0.0i+0.0 0.0i+00.0 18.0-09.0i 46.0i+0.0 1.0+4.0i 0.0i+00.0 0.0i+00.0 1.0-4.0i 21.0i+0.0  
and
B = 64.0+16.0i -16.0-32.0i 93.0+62.0i 61.0-66.0i 78.0-80.0i 71.0-74.0i 14.0-27.0i 35.0+15.0i .  
Estimates for the backward errors and forward errors are also output.

10.1 Program Text

Program Text (f07jvce.c)

10.2 Program Data

Program Data (f07jvce.d)

10.3 Program Results

Program Results (f07jvce.r)