Special Products

Functions

template<class V, class E1, class E2> BOOST_UBLAS_INLINE V &

axpy_prod (const matrix_expression< E1 > &e1, const vector_expression< E2 > &e2, V &v, bool init=true) computes v += A x or v = A x in an optimized fashion.

template<class V, class E1, class E2> BOOST_UBLAS_INLINE V &

axpy_prod (const vector_expression< E1 > &e1, const matrix_expression< E2 > &e2, V &v, bool init=true) computes v += AT x or v = AT x in an optimized fashion.

template<class M, class E1, class E2> BOOST_UBLAS_INLINE M &

axpy_prod (const matrix_expression< E1 > &e1, const matrix_expression< E2 > &e2, M &m, bool init=true) computes M += A X or M = A X in an optimized fashion.

template<class M, class E1, class E2> BOOST_UBLAS_INLINE M &

opb_prod (const matrix_expression< E1 > &e1, const matrix_expression< E2 > &e2, M &m, bool init=true) computes M += A X or M = A X in an optimized fashion.

1.

BOOST_UBLAS_INLINE V& axpy_prod

(

const matrix_expression< E1 > &

e1,

const vector_expression< E2 > &

e2,

V &

v,

bool

init = true

)

computes v += A x or v = A x in an optimized fashion.

Parameters:

e1 the matrix expression A, e2 the vector expression x, v the result vector v, init a boolean parameter

axpy_prod(A, x, v, init) implements the well known axpy-product. Setting init to true is equivalent to call v.clear() before axpy_prod. Currently init defaults to true, but this may change in the future.

Up to now there are some specialisation for compressed matrices that give a large speed up compared to prod.

2.

BOOST_UBLAS_INLINE V& axpy_prod

(

const vector_expression< E1 > &

e1,

const matrix_expression< E2 > &

e2,

V &

v,

bool

init = true

)

computes v += AT x or v = AT x in an optimized fashion.

Parameters:

e1 the vector expression x, e2 the matrix expression A, v the result vector v, init a boolean parameter

axpy_prod(x, A, v, init) implements the well known axpy-product. Setting init to true is equivalent to call v.clear() before axpy_prod. Currently init defaults to true, but this may change in the future.

Up to now there are some specialisation for compressed matrices that give a large speed up compared to prod.

3.

BOOST_UBLAS_INLINE M& axpy_prod

(

const matrix_expression< E1 > &

e1,

const matrix_expression< E2 > &

e2,

M &

m,

bool

init = true

)

computes M += A X or M = A X in an optimized fashion.

Parameters:

e1 !the matrix expression A, e2 !the matrix expression X, m !the result matrix M, init !a boolean parameter

axpy_prod(A, X, M, init) implements the well known axpy-product. Setting init to true is equivalent to call M.clear() before axpy_prod. Currently init defaults to true, but this may change in the future.

Up to now there are no specialisations.

4.

BOOST_UBLAS_INLINE M& opb_prod

(

const matrix_expression< E1 > &

e1,

const matrix_expression< E2 > &

e2,

M &

m,

bool

init = true

)

computes M += A X or M = A X in an optimized fashion.

Parameters:

e1 the matrix expression A e2 the matrix expression X m the result matrix M init a boolean parameter

opb_prod(A, X, M, init) implements the well known axpy-product. Setting init to true is equivalent to call M.clear() before opb_prod. Currently init defaults to true, but this may change in the future.

This function may give a speedup if A has less columns than rows, because the product is computed as a sum of outer products.

Copyright (©) 2000-2004 Michael Stevens, Mathias Koch, Joerg Walter, Gunter Winkler
Copyright (©) 2021 Shikhar Vashistha
Use, modification and distribution are subject to the Boost Software License, Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt ).