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

Nag_ColMajor

2: $uplo$ – Nag_UploType Input

On entry: specifies whether the upper or lower triangular part of

A

is stored and how

A

is to be factorized.

$uplo = Nag_Upper$: The upper triangular part of $A$ is stored and $A$ is factorized as $P U D U^{T} P^{T}$ , where $U$ is upper triangular.
$uplo = Nag_Lower$: The lower triangular part of $A$ is stored and $A$ is factorized as $P L D L^{T} P^{T}$ , where $L$ is lower triangular.

Constraint:

uplo = Nag_Upper

Nag_Lower

3: $n$ – Integer Input

On entry:

n

, the order of the matrix

A

Constraint:

n \geq 0

4: $ap [\dim]$ – double Input/Output

Note: the dimension, dim, of the array ap must be at least

\max (1, n \times (n + 1) / 2)

On entry: the

n \times n

symmetric matrix

A

, packed by rows or columns.

The storage of elements

A_{i j}

depends on the order and uplo arguments as follows:

if $order = Nag_ColMajor$ and $uplo = Nag_Upper$ ,: $A_{i j}$ is stored in $ap [(j - 1) \times j / 2 + i - 1]$ , for $i \leq j$ ;
if $order = Nag_ColMajor$ and $uplo = Nag_Lower$ ,: $A_{i j}$ is stored in $ap [(2 n - j) \times (j - 1) / 2 + i - 1]$ , for $i \geq j$ ;
if $order = Nag_RowMajor$ and $uplo = Nag_Upper$ ,: $A_{i j}$ is stored in $ap [(2 n - i) \times (i - 1) / 2 + j - 1]$ , for $i \leq j$ ;
if $order = Nag_RowMajor$ and $uplo = Nag_Lower$ ,: $A_{i j}$ is stored in $ap [(i - 1) \times i / 2 + j - 1]$ , for $i \geq j$ .

On exit:

A

is overwritten by details of the block diagonal matrix

D

and the multipliers used to obtain the factor

U

L

as specified by uplo.

5: $ipiv [n]$ – Integer Output

On exit: details of the interchanges and the block structure of

D

. More precisely,

if $ipiv [i - 1] = k > 0$ , $d_{i i}$ is a $1 \times 1$ pivot block and the $i$ th row and column of $A$ were interchanged with the $k$ th row and column;
if $uplo = Nag_Upper$ and $ipiv [i - 2] = ipiv [i - 1] = - l < 0$ , $(\begin{matrix} d_{i - 1, i - 1} & {\bar{d}}_{i, i - 1} \\ {\bar{d}}_{i, i - 1} & d_{i i} \end{matrix})$ is a $2 \times 2$ pivot block and the $(i - 1)$ th row and column of $A$ were interchanged with the $l$ th row and column;
if $uplo = Nag_Lower$ and $ipiv [i - 1] = ipiv [i] = - m < 0$ , $(\begin{matrix} d_{i i} & d_{i + 1, i} \\ d_{i + 1, i} & d_{i + 1, i + 1} \end{matrix})$ is a $2 \times 2$ pivot block and the $(i + 1)$ th row and column of $A$ were interchanged with the $m$ th row and column.

6: $fail$ – 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: $n \geq 0$ .
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.
NE_SINGULAR: Element $⟨ value ⟩$ of the diagonal is exactly zero. The factorization has been completed, but the block diagonal matrix $D$ is exactly singular, and division by zero will occur if it is used to solve a system of equations.

7 Accuracy

uplo = Nag_Upper

, the computed factors

U

and

D

are the exact factors of a perturbed matrix

A + E

, where

| E | \leq c (n) ε P | U | | D | | U^{T} | P^{T},

c (n)

is a modest linear function of

n

, and

ε

is the machine precision.

uplo = Nag_Lower

, a similar statement holds for the computed factors

L

and

D

8 Parallelism and Performance

Background information to multithreading can be found in the Multithreading documentation.

f07pdc 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 elements of

D

overwrite the corresponding elements of

A

; if

D

has

2 \times 2

blocks, only the upper or lower triangle is stored, as specified by uplo.

The unit diagonal elements of

U

L

and the

2 \times 2

unit diagonal blocks are not stored. The remaining elements of

U

L

overwrite elements in the corresponding columns of

A

, but additional row interchanges must be applied to recover

U

L

explicitly (this is seldom necessary). If

ipiv [i - 1] = i

, for

i = 1, 2, \dots, n

(as is the case when

A

is positive definite), then

U

L

are stored explicitly in packed form (except for their unit diagonal elements which are equal to

1

The total number of floating-point operations is approximately

\frac{1}{3} n^{3}

A call to f07pdc may be followed by calls to the functions:

f07pec to solve $A X = B$ ;
f07pgc to estimate the condition number of $A$ ;
f07pjc to compute the inverse of $A$ .

The complex analogues of this function are f07prc for Hermitian matrices and f07qrc for symmetric matrices.

10 Example

This example computes the Bunch–Kaufman factorization of the matrix

A

, where

A = (\begin{matrix} 2.07 & 3.87 & 4.20 & - 1.15 \\ 3.87 & - 0.21 & 1.87 & 0.63 \\ 4.20 & 1.87 & 1.15 & 2.06 \\ - 1.15 & 0.63 & 2.06 & - 1.81 \end{matrix}),

using packed storage.

f07pd: FL CL CPP AD PY MB

NAG CL Interfacef07pdc (dsptrf)

▸▿ Contents

1 Purpose

2 Specification

3 Description

4 References

5 Arguments

6 Error Indicators and Warnings

7 Accuracy

8 Parallelism and Performance

9 Further Comments

10 Example

10.1 Program Text

10.2 Program Data

10.3 Program Results

NAG CL Interface
f07pdc (dsptrf)