Function

# cblas_ssyrk(_:_:_:_:_:_:_:_:_:_:_:)

Rank-k update—multiplies a symmetric matrix by its transpose and adds a second matrix (single precision).

## Parameters

`Order`

Specifies row-major (C) or column-major (Fortran) data ordering.

`Uplo`

Specifies whether to use the upper or lower triangle from the matrix. Valid values are `'U'` or `'L'`.

`Trans`

Specifies whether to use matrix A (`'N'` or `'n'`) or the transpose of A (`'T'`, `'t'`, `'C'`, or `'c'`).

`N`

Order of matrix `C`.

`K`

Number of columns in matrix `A` (or number of rows if matrix `A` is transposed).

`alpha`

Scaling factor for matrix `A`.

`A`

Matrix `A`.

`lda`

Leading dimension of array containing matrix `A`.

`beta`

Scaling factor for matrix `C`.

`C`

Matrix `C`.

`ldc`

Leading dimension of array containing matrix `C`.

## Discussion

Calculates `alpha*A*AT + beta*C`; if transposed, calculates `alpha*AT*A + beta*C`.

### Single-Precision Float Matrix Functions

`func cblas_sasum(Int32, UnsafePointer<Float>!, Int32) -> Float`

Computes the sum of the absolute values of elements in a vector (single-precision).

`func cblas_snrm2(Int32, UnsafePointer<Float>!, Int32) -> Float`

Computes the L2 norm (Euclidian length) of a vector (single precision).

`func cblas_sscal(Int32, Float, UnsafeMutablePointer<Float>!, Int32)`

Multiplies each element of a vector by a constant (single-precision).

`func cblas_sspmv(CBLAS_ORDER, CBLAS_UPLO, Int32, Float, UnsafePointer<Float>!, UnsafePointer<Float>!, Int32, Float, UnsafeMutablePointer<Float>!, Int32)`

Scales a packed symmetric matrix, then multiplies by a vector, then scales and adds another vector (single precision).

`func cblas_sspr(CBLAS_ORDER, CBLAS_UPLO, Int32, Float, UnsafePointer<Float>!, Int32, UnsafeMutablePointer<Float>!)`

Rank one update: adds a packed symmetric matrix to the product of a scaling factor, a vector, and its transpose (single precision).

`func cblas_ssyr(CBLAS_ORDER, CBLAS_UPLO, Int32, Float, UnsafePointer<Float>!, Int32, UnsafeMutablePointer<Float>!, Int32)`

Rank one update: adds a symmetric matrix to the product of a scaling factor, a vector, and its transpose (single precision).