f11mkf computes a matrix-matrix or transposed matrix-matrix product involving a real, square, sparse nonsymmetric matrix stored in compressed column (Harwell–Boeing) format.

2 Specification

Fortran Interface

Subroutine f11mkf (

trans, n, m, alpha, icolzp, irowix, a, b, ldb, beta, c, ldc, ifail)

Integer, Intent (In)	::	n, m, icolzp(), irowix(), ldb, ldc
Integer, Intent (Inout)	::	ifail
Real (Kind=nag_wp), Intent (In)	::	alpha, a(), b(ldb,), beta
Real (Kind=nag_wp), Intent (Inout)	::	c(ldc,*)
Character (1), Intent (In)	::	trans

C Header Interface

#include <nag.h>

void	f11mkf_ (const char trans, const Integer n, const Integer m, const double alpha, const Integer icolzp[], const Integer irowix[], const double a[], const double b[], const Integer ldb, const double beta, double c[], const Integer ldc, Integer ifail, const Charlen length_trans)

The routine may be called by the names f11mkf or nagf_sparse_direct_real_gen_matmul.

3 Description

f11mkf computes either the matrix-matrix product

C \leftarrow α A B + β C

, or the transposed matrix-matrix product

C \leftarrow α A^{T} B + β C

, according to the value of the argument trans, where

A

is a real

n \times n

sparse nonsymmetric matrix, of arbitrary sparsity pattern with

nnz

nonzero elements,

B

and

C

are

n \times m

real dense matrices. The matrix

A

is stored in compressed column (Harwell–Boeing) storage format. The array a stores all nonzero elements of

A

, while arrays icolzp and irowix store the compressed column indices and row indices of

A

respectively.

4 References

None.

5 Arguments

1: $trans$ – Character(1) Input

On entry: specifies whether or not the matrix

A

is transposed.

$trans ='N'$: $α A B + β C$ is computed.
$trans ='T'$: $α A^{T} B + β C$ is computed.

Constraint:

trans ='N'

'T'

2: $n$ – Integer Input

On entry:

n

, the order of the matrix

A

Constraint:

n \geq 0

3: $m$ – Integer Input

On entry:

m

, the number of columns of matrices

B

and

C

Constraint:

m \geq 0

4: $alpha$ – Real (Kind=nag_wp) Input

On entry:

α

, the scalar factor in the matrix multiplication.

5: $icolzp (*)$ – Integer array Input

Note: the dimension of the array icolzp must be at least

n + 1

On entry: the new column index array of sparse matrix

A

. See Section 2.1.3 in the F11 Chapter Introduction.

6: $irowix (*)$ – Integer array Input

Note: the dimension of the array irowix must be at least

icolzp (n + 1) - 1

, the number of nonzeros of the sparse matrix

A

On entry: the row index array of sparse matrix

A

. See Section 2.1.3 in the F11 Chapter Introduction.

7: $a (*)$ – Real (Kind=nag_wp) array Input

Note: the dimension of the array a must be at least

icolzp (n + 1) - 1

, the number of nonzeros of the sparse matrix

A

On entry: the array of nonzero values in the sparse matrix

A

8: $b (ldb, *)$ – Real (Kind=nag_wp) array Input

Note: the second dimension of the array b must be at least

\max (1, m)

On entry: the

n \times m

matrix

B

9: $ldb$ – Integer Input

On entry: the first dimension of the array b as declared in the (sub)program from which f11mkf is called.

Constraint:

ldb \geq \max (1, n)

10: $beta$ – Real (Kind=nag_wp) Input

On entry: the scalar factor

β

11: $c (ldc, *)$ – Real (Kind=nag_wp) array Input/Output

Note: the second dimension of the array c must be at least

\max (1, m)

On entry: the

n \times m

matrix

C

On exit:

C

is overwritten by

α A B + β C

α A^{T} B + β C

depending on the value of trans.

12: $ldc$ – Integer Input

On entry: the first dimension of the array c as declared in the (sub)program from which f11mkf is called.

Constraint:

ldc \geq \max (1, n)

13: $ifail$ – Integer Input/Output

On entry: ifail must be set to

0

−1

1

to set behaviour on detection of an error; these values have no effect when no error is detected.

A value of

0

causes the printing of an error message and program execution will be halted; otherwise program execution continues. A value of

−1

means that an error message is printed while a value of

1

means that it is not.

If halting is not appropriate, the value

−1

1

is recommended. If message printing is undesirable, then the value

1

is recommended. Otherwise, the value

0

is recommended. When the value $- 1$ or $1$ is used it is essential to test the value of ifail on exit.

On exit:

ifail = 0

unless the routine detects an error or a warning has been flagged (see Section 6).

6 Error Indicators and Warnings

If on entry

ifail = 0

−1

, explanatory error messages are output on the current error message unit (as defined by x04aaf).

Errors or warnings detected by the routine:

$ifail = 1$: On entry, $ldb = ⟨ value ⟩$ and $n = ⟨ value ⟩$ .
Constraint: $ldb \geq \max (1, n)$ .

On entry, $ldc = ⟨ value ⟩$ and $n = ⟨ value ⟩$ .
Constraint: $ldc \geq \max (1, n)$ .

On entry, $m = ⟨ value ⟩$ .
Constraint: $m \geq 0$ .

On entry, $n = ⟨ value ⟩$ .
Constraint: $n \geq 0$ .

On entry, $trans = ⟨ value ⟩$ .
Constraint: $trans ='N'$ or $'T'$ .

$ifail = - 99$: An unexpected error has been triggered by this routine. Please contact NAG.
See Section 7 in the Introduction to the NAG Library FL Interface for further information.

$ifail = - 399$: Your licence key may have expired or may not have been installed correctly.
See Section 8 in the Introduction to the NAG Library FL Interface for further information.

$ifail = - 999$: Dynamic memory allocation failed.
See Section 9 in the Introduction to the NAG Library FL Interface for further information.

7 Accuracy

Not applicable.

8 Parallelism and Performance

f11mkf is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.

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

None.

10 Example

This example reads in a sparse matrix

A

and a dense matrix

B

. It then calls f11mkf to compute the matrix-matrix product

C = A B

and the transposed matrix-matrix product

C = A^{T} B

, where

A = (\begin{matrix} 2.00 & 1.00 & 0 & 0 & 0 \\ 0 & 0 & 1.00 & - 1.00 & 0 \\ 4.00 & 0 & 1.00 & 0 & 1.00 \\ 0 & 0 & 0 & 1.00 & 2.00 \\ 0 & - 2.00 & 0 & 0 & 3.00 \end{matrix}) and B = (\begin{matrix} 0.70 & 1.40 \\ 0.16 & 0.32 \\ 0.52 & 1.04 \\ 0.77 & 1.54 \\ 0.28 & 0.56 \end{matrix}) .

f11mk: FL CL CPP AD

NAG FL Interfacef11mkf (direct_​real_​gen_​matmul)

▸▿ 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 FL Interface
f11mkf (direct_real_gen_matmul)