NAG CL Interface
f16ycc (dsymm)

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1 Purpose

f16ycc performs matrix-matrix multiplication for a real symmetric matrix.

2 Specification

#include <nag.h>
void  f16ycc (Nag_OrderType order, Nag_SideType side, Nag_UploType uplo, Integer m, Integer n, double alpha, const double a[], Integer pda, const double b[], Integer pdb, double beta, double c[], Integer pdc, NagError *fail)
The function may be called by the names: f16ycc, nag_blast_dsymm or nag_dsymm.

3 Description

f16ycc performs one of the matrix-matrix operations
CαAB + βC   or   CαBA + βC ,  
where A is a real symmetric matrix, B and C are m×n real matrices, and α and β are real scalars.

4 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

5 Arguments

1: order Nag_OrderType Input
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 or Nag_ColMajor.
2: side Nag_SideType Input
On entry: specifies whether B is operated on from the left or the right.
side=Nag_LeftSide
B is pre-multiplied from the left.
side=Nag_RightSide
B is post-multiplied from the right.
Constraint: side=Nag_LeftSide or Nag_RightSide.
3: uplo Nag_UploType Input
On entry: specifies whether the upper or lower triangular part of A is stored.
uplo=Nag_Upper
The upper triangular part of A is stored.
uplo=Nag_Lower
The lower triangular part of A is stored.
Constraint: uplo=Nag_Upper or Nag_Lower.
4: m Integer Input
On entry: m, the number of rows of the matrices B and C; the order of A if side=Nag_LeftSide.
Constraint: m0.
5: n Integer Input
On entry: n, the number of columns of the matrices B and C; the order of A if side=Nag_RightSide.
Constraint: n0.
6: alpha double Input
On entry: the scalar α.
7: a[dim] const double Input
Note: the dimension, dim, of the array a must be at least
  • max(1,pda×m) when side=Nag_LeftSide;
  • max(1,pda×n) when side=Nag_RightSide.
On entry: the symmetric matrix A; A is m×m if side=Nag_LeftSide, or n×n if side=Nag_RightSide.
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].
If uplo=Nag_Upper, the upper triangular part of A must be stored and the elements of the array below the diagonal are not referenced.
If uplo=Nag_Lower, the lower triangular part of A must be stored and the elements of the array above the diagonal are not referenced.
8: pda Integer Input
On entry: the stride separating row or column elements (depending on the value of order) of the matrix A in the array a.
Constraints:
  • if side=Nag_LeftSide, pda max(1,m) ;
  • if side=Nag_RightSide, pda max(1,n) .
9: b[dim] const double Input
Note: the dimension, dim, of the array b must be at least
  • max(1,pdb×n) when order=Nag_ColMajor;
  • max(1,m×pdb) when order=Nag_RowMajor.
If order=Nag_ColMajor, Bij is stored in b[(j-1)×pdb+i-1].
If order=Nag_RowMajor, Bij is stored in b[(i-1)×pdb+j-1].
On entry: the m×n matrix B.
10: pdb Integer Input
On entry: the stride separating row or column elements (depending on the value of order) in the array b.
Constraints:
  • if order=Nag_ColMajor, pdbmax(1,m);
  • if order=Nag_RowMajor, pdbmax(1,n).
11: beta double Input
On entry: the scalar β.
12: c[dim] double Input/Output
Note: the dimension, dim, of the array c must be at least
  • max(1,pdc×n) when order=Nag_ColMajor;
  • max(1,m×pdc) when order=Nag_RowMajor.
If order=Nag_ColMajor, Cij is stored in c[(j-1)×pdc+i-1].
If order=Nag_RowMajor, Cij is stored in c[(i-1)×pdc+j-1].
On entry: the m×n matrix C.
If beta=0, c need not be set.
On exit: the updated matrix C.
13: pdc Integer Input
On entry: the stride separating row or column elements (depending on the value of order) in the array c.
Constraints:
  • if order=Nag_ColMajor, pdcmax(1,m);
  • if order=Nag_RowMajor, pdcmax(1,n).
14: 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_ENUM_INT_2
On entry, side=value, m=value, pda=value.
Constraint: if side=Nag_LeftSide, pda max(1,m) .
On entry, side=value, n=value, pda=value.
Constraint: if side=Nag_RightSide, pda max(1,n) .
NE_INT
On entry, m=value.
Constraint: m0.
On entry, n=value.
Constraint: n0.
NE_INT_2
On entry, pdb=value, m=value.
Constraint: pdbmax(1,m).
On entry, pdb=value and n=value.
Constraint: pdbmax(1,n).
On entry, pdc=value, m=value.
Constraint: pdcmax(1,m).
On entry, pdc=value and n=value.
Constraint: pdcmax(1,n).
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.
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.

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

f16ycc 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 function. Please also consult the Users' Note for your implementation for any additional implementation-specific information.

9 Further Comments

None.

10 Example

This example computes the matrix-matrix product
C=αAB+βC  
where
A = ( 1.0 2.0 3.0 2.0 3.0 4.0 3.0 4.0 1.0 ) ,  
B = ( 1.0 2.0 -2.0 1.0 3.0 -1.0 ) ,  
C = ( -2.0 1.0 1.0 3.0 2.0 -1.0 ) ,  
α=1.5   and   β=1.0 .  

10.1 Program Text

Program Text (f16ycce.c)

10.2 Program Data

Program Data (f16ycce.d)

10.3 Program Results

Program Results (f16ycce.r)