NAG FL Interface
f08nef (dgehrd)

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1 Purpose

f08nef reduces a real general matrix to Hessenberg form.

2 Specification

Fortran Interface
Subroutine f08nef ( n, ilo, ihi, a, lda, tau, work, lwork, info)
Integer, Intent (In) :: n, ilo, ihi, lda, lwork
Integer, Intent (Out) :: info
Real (Kind=nag_wp), Intent (Inout) :: a(lda,*), tau(*)
Real (Kind=nag_wp), Intent (Out) :: work(max(1,lwork))
C Header Interface
#include <nag.h>
void  f08nef_ (const Integer *n, const Integer *ilo, const Integer *ihi, double a[], const Integer *lda, double tau[], double work[], const Integer *lwork, Integer *info)
The routine may be called by the names f08nef, nagf_lapackeig_dgehrd or its LAPACK name dgehrd.

3 Description

f08nef reduces a real general matrix A to upper Hessenberg form H by an orthogonal similarity transformation: A=QHQT.
The matrix Q is not formed explicitly, but is represented as a product of elementary reflectors (see the F08 Chapter Introduction for details). Routines are provided to work with Q in this representation (see Section 9).
The routine can take advantage of a previous call to f08nhf, which may produce a matrix with the structure:
( A11 A12 A13 A22 A23 A33 )  
where A11 and A33 are upper triangular. If so, only the central diagonal block A22, in rows and columns ilo to ihi, needs to be reduced to Hessenberg form (the blocks A12 and A23 will also be affected by the reduction). Therefore, the values of ilo and ihi determined by f08nhf can be supplied to the routine directly. If f08nhf has not previously been called however, then ilo must be set to 1 and ihi to n.

4 References

Golub G H and Van Loan C F (1996) Matrix Computations (3rd Edition) Johns Hopkins University Press, Baltimore

5 Arguments

1: n Integer Input
On entry: n, the order of the matrix A.
Constraint: n0.
2: ilo Integer Input
3: ihi Integer Input
On entry: if A has been output by f08nhf, ilo and ihi must contain the values returned by that routine. Otherwise, ilo must be set to 1 and ihi to n.
Constraints:
  • if n>0, 1 ilo ihi n ;
  • if n=0, ilo=1 and ihi=0.
4: a(lda,*) Real (Kind=nag_wp) array Input/Output
Note: the second dimension of the array a must be at least max(1,n).
On entry: the n×n general matrix A.
On exit: a is overwritten by the upper Hessenberg matrix H and details of the orthogonal matrix Q.
5: lda Integer Input
On entry: the first dimension of the array a as declared in the (sub)program from which f08nef is called.
Constraint: ldamax(1,n).
6: tau(*) Real (Kind=nag_wp) array Output
Note: the dimension of the array tau must be at least max(1,n-1).
On exit: further details of the orthogonal matrix Q.
7: work(max(1,lwork)) Real (Kind=nag_wp) array Workspace
On exit: if info=0, work(1) contains the minimum value of lwork required for optimal performance.
8: lwork Integer Input
On entry: the dimension of the array work as declared in the (sub)program from which f08nef is called.
If lwork=−1, a workspace query is assumed; the routine only calculates the optimal size of the work array, returns this value as the first entry of the work array, and no error message related to lwork is issued.
Suggested value: for optimal performance, lworkn×nb, where nb is the optimal block size.
Constraint: lworkmax(1,n) or lwork=−1.
9: info Integer Output
On exit: info=0 unless the routine detects an error (see Section 6).

6 Error Indicators and Warnings

-999<info<0
If info=-i, argument i had an illegal value. An explanatory message is output, and execution of the program is terminated.
info=-999
Dynamic memory allocation failed.
See Section 9 in the Introduction to the NAG Library FL Interface for further information.
An explanatory message is output, and execution of the program is terminated.

7 Accuracy

The computed Hessenberg matrix H is exactly similar to a nearby matrix (A+E), where
E2 c (n) ε A2 ,  
c(n) is a modestly increasing function of n, and ε is the machine precision.
The elements of H themselves may be sensitive to small perturbations in A or to rounding errors in the computation, but this does not affect the stability of the eigenvalues, eigenvectors or Schur factorization.

8 Parallelism and Performance

Background information to multithreading can be found in the Multithreading documentation.
f08nef is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.
f08nef 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 routine. 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 is approximately 23q2(2q+3n), where q=ihi-ilo; if ilo=1 and ihi=n, the number is approximately 103n3.
To form the orthogonal matrix Q f08nef may be followed by a call to f08nff :
Call dorghr(n,ilo,ihi,a,lda,tau,work,lwork,info)
To apply Q to an m×n real matrix C f08nef may be followed by a call to f08ngf. For example,
Call dormhr('Left','No Transpose',m,n,ilo,ihi,a,lda,tau,c,ldc, &
              work,lwork,info)
forms the matrix product QC.
The complex analogue of this routine is f08nsf.

10 Example

This example computes the upper Hessenberg form of the matrix A, where
A = ( 0.35 0.45 -0.14 -0.17 0.09 0.07 -0.54 0.35 -0.44 -0.33 -0.03 0.17 0.25 -0.32 -0.13 0.11 ) .  

10.1 Program Text

Program Text (f08nefe.f90)

10.2 Program Data

Program Data (f08nefe.d)

10.3 Program Results

Program Results (f08nefe.r)