nag_dgemv (f16pac) (PDF version)
f16 Chapter Contents
f16 Chapter Introduction
NAG Library Manual

NAG Library Function Document

nag_dgemv (f16pac)

+ Contents

    1  Purpose
    7  Accuracy

1  Purpose

nag_dgemv (f16pac) performs matrix-vector multiplication for a real general matrix.

2  Specification

#include <nag.h>
#include <nagf16.h>
void  nag_dgemv (Nag_OrderType order, Nag_TransType trans, Integer m, Integer n, double alpha, const double a[], Integer pda, const double x[], Integer incx, double beta, double y[], Integer incy, NagError *fail)

3  Description

nag_dgemv (f16pac) performs one of the matrix-vector operations
yαAx + βy ,   or   yαATx + βy ,
where A is an m by n real matrix, x and y are real vectors, and α and β are real scalars.
If m=0 or n=0, no operation is performed.

4  References

Basic Linear Algebra Subprograms Technical (BLAST) Forum (2001) Basic Linear Algebra Subprograms Technical (BLAST) Forum Standard University of Tennessee, Knoxville, Tennessee http://www.netlib.org/blas/blast-forum/blas-report.pdf

5  Arguments

1:     orderNag_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 order=Nag_RowMajor. See Section 3.2.1.3 in the Essential Introduction for a more detailed explanation of the use of this argument.
Constraint: order=Nag_RowMajor or Nag_ColMajor.
2:     transNag_TransTypeInput
On entry: specifies the operation to be performed.
trans=Nag_NoTrans
yαAx+βy.
trans=Nag_Trans or Nag_ConjTrans
yαATx+βy.
Constraint: trans=Nag_NoTrans, Nag_Trans or Nag_ConjTrans.
3:     mIntegerInput
On entry: m, the number of rows of the matrix A.
Constraint: m0.
4:     nIntegerInput
On entry: n, the number of columns of the matrix A.
Constraint: n0.
5:     alphadoubleInput
On entry: the scalar α.
6:     a[dim]const doubleInput
Note: the dimension, dim, of the array a must be at least
  • max1,pda×n when order=Nag_ColMajor;
  • max1,m×pda when order=Nag_RowMajor.
If order=Nag_ColMajor, Aij is stored in a[j-1×pda+i-1].
If order=Nag_RowMajor, Aij is stored in a[i-1×pda+j-1].
On entry: the m by n matrix A.
7:     pdaIntegerInput
On entry: the stride separating row or column elements (depending on the value of order) in the array a.
Constraints:
  • if order=Nag_ColMajor, pdamax1,m;
  • if order=Nag_RowMajor, pdan.
8:     x[dim]const doubleInput
Note: the dimension, dim, of the array x must be at least
  • max1,1+n-1incx when trans=Nag_NoTrans;
  • max1,1+m-1incx when trans=Nag_Trans or Nag_ConjTrans.
On entry: the vector x.
9:     incxIntegerInput
On entry: the increment in the subscripts of x between successive elements of x.
Constraint: incx0.
10:   betadoubleInput
On entry: the scalar β.
11:   y[dim]doubleInput/Output
Note: the dimension, dim, of the array y must be at least
  • max1,1+m-1incy when trans=Nag_NoTrans;
  • max1,1+n-1incy when trans=Nag_Trans or Nag_ConjTrans.
On entry: the vector y.
If beta=0, y need not be set.
On exit: the updated vector y.
12:   incyIntegerInput
On entry: the increment in the subscripts of y between successive elements of y.
Constraint: incy0.
13:   failNagError *Input/Output
The NAG error argument (see Section 3.6 in the Essential Introduction).

6  Error Indicators and Warnings

NE_ALLOC_FAIL
Dynamic memory allocation failed.
NE_BAD_PARAM
On entry, argument value had an illegal value.
NE_INT
On entry, incx=value.
Constraint: incx0.
On entry, incy=value.
Constraint: incy0.
On entry, m=value.
Constraint: m0.
On entry, n=value.
Constraint: n0.
NE_INT_2
On entry, pda=value, m=value.
Constraint: pdamax1,m.
On entry, pda=value and n=value.
Constraint: pdan.
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.

7  Accuracy

The BLAS standard requires accurate implementations which avoid unnecessary over/underflow (see Section 2.7 of Basic Linear Algebra Subprograms Technical (BLAST) Forum (2001)).

8  Parallelism and Performance

Not applicable.

9  Further Comments

None.

10  Example

This example computes the matrix-vector product
y = αAx+βy
where
A= 1.0 2.0 3.0 4.0 5.0 6.0 ,
x = -1.0 2.0 ,
y= 1.0 2.0 3.0 ,
α=1.5 ​ and ​ β=1.0 .

10.1  Program Text

Program Text (f16pace.c)

10.2  Program Data

Program Data (f16pace.d)

10.3  Program Results

Program Results (f16pace.r)


nag_dgemv (f16pac) (PDF version)
f16 Chapter Contents
f16 Chapter Introduction
NAG Library Manual

© The Numerical Algorithms Group Ltd, Oxford, UK. 2014