F16 (Blast)
Chapter Introduction
FL CL
NAG CL Interface
F16 (Blast)
NAG Interface to BLAS
F16 (Blast)
Chapter Introduction
FL CL
1
Scope of the Chapter
This chapter is concerned with basic linear algebra functions which perform elementary algebraic operations involving scalars, vectors and matrices. Most functions for such operations conform either to the specifications of the BLAS (Basic Linear Algebra Subprograms) or to the specifications of the BLAST (Basic Linear Algebra Subprograms Technical) Forum. This chapter includes functions conforming to both specifications. Two additional functions for such operations are available in
Chapter F06.
2
Background to the Problems
They are called extensively by functions in other chapters of the NAG Library, especially in the linear algebra chapters. They are intended to be useful building-blocks for users of the Library who are developing their own applications. The functions fall into four main groups (following the definitions introduced by the BLAS):
- Level 1: vector operations;
- Level 2: matrix-vector operations and matrix operations which includes single matrix operations;
- Level 3: matrix-matrix operations.
The terminology reflects the number of operations involved, so for example a Level 2 function involves operations, for vectors and matrices of order .
In many implementations of the NAG Library, the BLAS functions in this chapter serve as interfaces to an efficient machine-specific implementation of the BLAS, usually provided by the vendor of the machine. Such implementations are stringently tested before being used with the NAG Library, to ensure that they correctly meet the specifications of the BLAS, and that they return the desired accuracy.
2.1
The Use of BLAS Names
Many of the functions in other chapters of the Library call the functions in this chapter, and in particular a number of the BLAS are called. These functions are usually called by the BLAS name and so, for correct operation of the Library, it is essential that you do not attempt to link your own versions of these functions. If you are in any doubt about how to avoid this, please consult the NAG Technical Support Service.
The BLAS names are used in order to make use of efficient implementations of the functions when these exist. Such implementations are stringently tested before being used, to ensure that they correctly meet the specification of the BLAS, and that they return the desired accuracy (see, for example,
Dodson et al. (1991),
Dongarra et al. (1988) and
Dongarra et al. (1990)).
3
Recommendations on Choice and Use of Available Functions
3.1
Naming Scheme
3.1.1
NAG names
Table 1 shows the naming scheme for the functions in this chapter.
Table 1
|
| Level-1 |
Level-2 |
Level-3 |
integer |
Chapter F16 function |
f16d_c |
– |
– |
‘real’ |
BLAS function |
– |
f16p_c |
f16y_c |
‘real’ |
Chapter F16 function |
f16f_c |
f16q_c f16r_c |
– |
‘real’ |
BLAST function |
f16e_c f16j_c |
f16q_c f16r_c |
– |
‘complex’ |
BLAS function |
– |
f16s_c |
f16z_c |
‘complex’ |
Chapter F16 function |
f16h_c |
f16t_c f16u_c |
– |
‘complex’ |
BLAST function |
f16g_c |
f16t_c f16u_c |
– |
‘mixed type’ |
BLAS function |
f16j_c |
– |
– |
The heading ‘mixed type’ is for functions where a mixture of data types is involved, such as a function that returns the real norm of a complex vector. In future marks of the Library, functions may be included in categories that are currently empty and further categories may be introduced.
3.2
The Level-1 Vector Functions
The Level-1 functions perform operations either on a single vector or on a pair of vectors.
3.3
The Level-2 Matrix-vector and Matrix Functions
The Level-2 functions perform operations involving either a matrix on its own, or a matrix and one or more vectors.
3.4
The Level-3 Matrix-matrix Functions
The Level-3 functions perform operations involving matrix-matrix products.
3.5
Vector Arguments
Vector arguments are represented by a one-dimensional array, immediately followed by an
increment argument whose name consists of the three characters INC followed by the name of the array. For example, a vector
is represented by the two arguments
x and
incx. The length of the vector,
say, is passed as a separate argument,
n.
The increment argument is the spacing (stride) in the array between the elements of the vector. For instance, if
,
then the elements of
are in locations
of the array
x
and the intermediate locations
are not referenced.
When
, the vector element
is in the array element
. When
, the elements are stored in the reverse order so that the vector element
is in the array element
and hence, in particular, the element
is in
. The declared length of the array
x in the calling function must be at least
.
Negative increments are permitted only for:
- Level-1 functions which have more than one vector argument;
- Level-2 BLAS functions (but not for other Level-2 functions)
Zero increments are formally permitted for Level-1 functions with more than one argument (in which case the element is accessed repeatedly), but their use is strongly discouraged since the effect may be implementation-dependent. There is usually an alternative function in this chapter, with a simplified argument list, to achieve the required purpose. Zero increments are not permitted in the Level-2 BLAS.
3.6
Matrix Arguments and Storage Schemes
In this chapter the following different storage schemes are used for matrices:
-
–conventional storage in a two-dimensional array;
-
–packed and RFP storage for symmetric, Hermitian or triangular matrices;
-
–band storage for band matrices;
These storage schemes are compatible with those used in
Chapters F07 and
F08. (Different schemes for packed or band storage are used in a few older functions in
Chapters F01,
F02,
F03 and
F04.)
Chapter F01 provides some utility functions for conversion between storage schemes.
3.6.1
Conventional storage
Please see
Section 3.4.1 in the
F07 Chapter Introduction for full details.
3.6.2
Packed storage
Please see
Section 3.4.2 in the
F07 Chapter Introduction for full details.
3.6.3
Rectangular Full Packed (RFP) storage
Please see
Section 3.4.3 in the
F07 Chapter Introduction for full details.
3.6.4
Band storage
Please see
Section 3.4.4 in the
F07 Chapter Introduction for full details.
3.6.5
Unit triangular matrices
Please see
Section 3.4.5 in the
F07 Chapter Introduction for full details.
3.6.6
Real diagonal elements of complex Hermitian matrices
Please see
Section 3.4.6 in the
F07 Chapter Introduction for full details.
3.7
Option Arguments
In addition to the order argument of type Nag_OrderType, most functions in this Chapter have one or more option arguments of various types; only options of the correct type may be supplied.
The following option arguments are used in this chapter:
- If , operate with the matrix (Not transposed);
- if , operate with the Transpose of the matrix;
- if , operate with the Conjugate transpose of the matrix.
- If , upper triangle or trapezoid of matrix;
- if , lower triangle or trapezoid of matrix.
- If , unit triangular;
- if , nonunit triangular.
- If , operate from the left-hand side;
- if , operate from the right-hand side.
- If , -norm of a matrix;
- if , -norm of a matrix;
- if , Frobenius or Euclidean norm of a matrix;
- if , maximum absolute value of the elements of a matrix (not strictly a norm).
3.7.1
Matrix norms
The option argument
norm
specifies different matrix norms whose definitions are given here for reference (for a general
matrix
):
- One-norm ():
- Infinity-norm ():
- Frobenius or Euclidean norm ():
If is symmetric or Hermitian, .
The argument
norm
can also be used to specify the maximum absolute value
(if
),
but this is not a norm in the strict mathematical sense.
3.8
Error Handling
Functions in this chapter use the usual NAG Library error-handling.
4
Functionality Index
of a Hermitian matrix, RFP format
|
|
f16zqc
|
solution of triangular systems of equations
|
|
f16zjc
|
solution of triangular systems of equations, RFP format
|
|
f16zlc
|
rank- update of a symmetric matrix
|
|
f16yrc
|
of a symmetric matrix, RFP format
|
|
f16yqc
|
solution of triangular systems of equations
|
|
f16yjc
|
solution of triangular systems of equations, RFP format
|
|
f16ylc
|
Matrix-vector operations,
|
|
|
complex matrix and vector(s),
|
|
|
compute a norm or the element of largest absolute value,
|
|
|
Hermitian matrix, RFP format
|
|
f16ukc
|
Hermitian packed matrix
|
|
f16udc
|
symmetric packed matrix
|
|
f16ugc
|
Hermitian packed matrix
|
|
f16sec
|
rectangular band matrix
|
|
f16sbc
|
symmetric packed matrix
|
|
f16tcc
|
triangular packed matrix
|
|
f16shc
|
Hermitian packed matrix
|
|
f16sqc
|
rectangular matrix, unconjugated vector
|
|
f16smc
|
Hermitian packed matrix
|
|
f16ssc
|
solution of a system of equations,
|
|
|
triangular packed matrix
|
|
f16slc
|
real matrix and vector(s),
|
|
|
compute a norm or the element of largest absolute value,
|
|
|
symmetric matrix, RFP format
|
|
f16rkc
|
symmetric packed matrix
|
|
f16rdc
|
rectangular band matrix
|
|
f16pbc
|
symmetric packed matrix
|
|
f16pec
|
triangular packed matrix
|
|
f16phc
|
symmetric packed matrix
|
|
f16pqc
|
symmetric packed matrix
|
|
f16psc
|
solution of a system of equations,
|
|
|
triangular packed matrix
|
|
f16plc
|
Scalar and vector operations,
|
|
|
broadcast a scalar into a vector
|
|
f16hbc
|
maximum absolute value and location
|
|
f16jsc
|
minimum absolute value and location
|
|
f16jtc
|
sum of two scaled vectors
|
|
f16gcc
|
sum of two scaled vectors preserving input
|
|
f16ghc
|
broadcast a scalar into a vector
|
|
f16dbc
|
maximum absolute value and location
|
|
f16dqc
|
maximum value and location
|
|
f16dnc
|
minimum absolute value and location
|
|
f16drc
|
minimum value and location
|
|
f16dpc
|
broadcast a scalar into a vector
|
|
f16fbc
|
dot product of two vectors with optional scaling and accumulation
|
|
f16eac
|
maximum absolute value and location
|
|
f16jqc
|
maximum value and location
|
|
f16jnc
|
minimum absolute value and location
|
|
f16jrc
|
minimum value and location
|
|
f16jpc
|
sum of two scaled vectors
|
|
f16ecc
|
sum of two scaled vectors preserving input
|
|
f16ehc
|
5
Auxiliary Functions Associated with Library Function Arguments
None.
6
Withdrawn or Deprecated Functions
None.
7
References
Basic Linear Algebra Subprograms Technical (BLAST) Forum (2001)
Basic Linear Algebra Subprograms Technical (BLAST) Forum Standard University of Tennessee, Knoxville, Tennessee
https://www.netlib.org/blas/blast-forum/blas-report.pdf
Dodson D S and Grimes R G (1982) Remark on Algorithm 539 ACM Trans. Math. Software 8 403–404
Dongarra J J, Du Croz J J, Duff I S and Hammarling S (1990) A set of Level 3 basic linear algebra subprograms ACM Trans. Math. Software 16 1–28
Dongarra J J, Du Croz J J, Hammarling S and Hanson R J (1988) An extended set of FORTRAN basic linear algebra subprograms ACM Trans. Math. Software 14 1–32
Dongarra J J, Moler C B, Bunch J R and Stewart G W (1979) LINPACK Users' Guide SIAM, Philadelphia
Golub G H and Van Loan C F (1996) Matrix Computations (3rd Edition) Johns Hopkins University Press, Baltimore
Lawson C L, Hanson R J, Kincaid D R and Krogh F T (1979) Basic linear algebra supbrograms for Fortran usage ACM Trans. Math. Software 5 308–325
F16 (Blast)
Chapter Introduction
FL CL