syrk: Symmetric rank k update

\(C = \alpha A A^T + \beta C\) where \(C\) is symmetric More...

Functions
template<typename scalar_t >
void	slate::syrk (scalar_t alpha, Matrix< scalar_t > &A, scalar_t beta, SymmetricMatrix< scalar_t > &C, Options const &opts)
	Distributed parallel symmetric rank k update.

Detailed Description

\(C = \alpha A A^T + \beta C\) where \(C\) is symmetric

Function Documentation

syrk()

template<typename scalar_t >

void slate::syrk	(	scalar_t	alpha,
		Matrix< scalar_t > &	A,
		scalar_t	beta,
		SymmetricMatrix< scalar_t > &	C,
		Options const &	opts
	)

Distributed parallel symmetric rank k update.

Performs the symmetric rank k operation

\[ C = \alpha A A^T + \beta C, \]

where alpha and beta are scalars, C is an n-by-n symmetric matrix, and A is an n-by-k matrix. The matrices can be transposed beforehand, e.g.,

auto AT = slate::transpose( A );
slate::syrk( alpha, AT, beta, C );

Template Parameters

scalar_t

One of float, double, std::complex<float>, std::complex<double>.

Parameters

[in]	alpha	The scalar alpha.
[in]	A	The n-by-k matrix A.
[in]	beta	The scalar beta.
[in,out]	C	On entry, the n-by-n symmetric matrix C. On exit, overwritten by the result \(C = \alpha A A^T + \beta C\).
[in]	opts	Additional options, as map of name = value pairs. Possible options: Option::Lookahead: Number of blocks to overlap communication and computation. lookahead >= 0. Default 1. Option::Target: Implementation to target. Possible values: HostTask: OpenMP tasks on CPU host [default]. HostNest: nested OpenMP parallel for loop on CPU host. HostBatch: batched BLAS on CPU host. Devices: batched BLAS on GPU device.