monolish::vml::alo

Asymmetric linear operation to CRS matrix elements (C[0:nnz] = alpha max(A[0:nnz], 0) + beta min(A[0:nnz], 0)) More...

Functions
void	monolish::vml::alo (const matrix::CRS< double > &A, const double alpha, const double beta, matrix::CRS< double > &C)
	Asymmetric linear operation to CRS matrix elements (C[0:nnz] = alpha max(A[0:nnz], 0) + beta min(A[0:nnz], 0)) More...
void	monolish::vml::alo (const matrix::CRS< float > &A, const float alpha, const float beta, matrix::CRS< float > &C)
void	monolish::vml::alo (const tensor::tensor_CRS< double > &A, const double alpha, const double beta, tensor::tensor_CRS< double > &C)
	Asymmetric linear operation to tensor_CRS matrix elements (C[0:nnz] = alpha max(A[0:nnz], 0) + beta min(A[0:nnz], 0)) More...
void	monolish::vml::alo (const tensor::tensor_CRS< float > &A, const float alpha, const float beta, tensor::tensor_CRS< float > &C)

Detailed Description

Asymmetric linear operation to CRS matrix elements (C[0:nnz] = alpha max(A[0:nnz], 0) + beta min(A[0:nnz], 0))

Asymmetric linear operation to tensor_CRS matrix elements (C[0:nnz] = alpha max(A[0:nnz], 0) + beta min(A[0:nnz], 0))

Function Documentation

alo() [1/4]

void monolish::vml::alo	(	const matrix::CRS< double > &	A,
		const double	alpha,
		const double	beta,
		matrix::CRS< double > &	C
	)

Asymmetric linear operation to CRS matrix elements (C[0:nnz] = alpha max(A[0:nnz], 0) + beta min(A[0:nnz], 0))

Parameters

A	monolish CRS matrix (size M x N)
alpha	linear coefficient in positive range
beta	linear coefficient in negative range
C	monolish CRS matrix (size M x N)

Note

• # of computation: M*N
• Multi-threading: true
• GPU acceleration: true

alo() [2/4]

void monolish::vml::alo	(	const matrix::CRS< float > &	A,
		const float	alpha,
		const float	beta,
		matrix::CRS< float > &	C
	)

alo() [3/4]

void monolish::vml::alo	(	const tensor::tensor_CRS< double > &	A,
		const double	alpha,
		const double	beta,
		tensor::tensor_CRS< double > &	C
	)

Asymmetric linear operation to tensor_CRS matrix elements (C[0:nnz] = alpha max(A[0:nnz], 0) + beta min(A[0:nnz], 0))

Parameters

A	monolish tensor_CRS matrix (size M x N)
alpha	linear coefficient in positive range
beta	linear coefficient in negative range
C	monolish tensor_CRS matrix (size M x N)

Note

• # of computation: M*N
• Multi-threading: true
• GPU acceleration: true

alo() [4/4]

void monolish::vml::alo	(	const tensor::tensor_CRS< float > &	A,
		const float	alpha,
		const float	beta,
		tensor::tensor_CRS< float > &	C
	)