\(B = \alpha A + \beta B\) More...

Functions
template<typename scalar_t >
void	slate::add (scalar_t alpha, Matrix< scalar_t > &A, scalar_t beta, Matrix< scalar_t > &B, Options const &opts)
	Distributed parallel general matrix-matrix addition.

template<typename scalar_t >
void	slate::add (scalar_t alpha, BaseTrapezoidMatrix< scalar_t > &A, scalar_t beta, BaseTrapezoidMatrix< scalar_t > &B, Options const &opts)
	Distributed parallel matrix-matrix addition.

Detailed Description

\(B = \alpha A + \beta B\)

Function Documentation

◆ add() [1/2]

template<typename scalar_t >

void slate::add	(	scalar_t	alpha,
		BaseTrapezoidMatrix< scalar_t > &	A,
		scalar_t	beta,
		BaseTrapezoidMatrix< scalar_t > &	B,
		Options const &	opts
	)

Distributed parallel matrix-matrix addition.

Performs the matrix-matrix operation

\[ B = \alpha A + \beta B, \]

where alpha and beta are scalars, and \(A\) and \(B\) are matrices, with \(A\) an m-by-n matrix and \(B\) a m-by-n matrix. Transposition is currently not supported. TODO: Support transposition.

Template Parameters

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

Parameters

[in]	alpha	The scalar alpha.
[in]	A	The m-by-n matrix A.
[in]	beta	The scalar beta.
[in,out]	B	On entry, the m-by-n matrix B. On exit, overwritten by the result \(\alpha A + \beta B\).
[in]	opts	Additional options, as map of name = value pairs. Possible options: 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.

◆ add() [2/2]