Hi all,

I'm working on a project using uBlas. I'm using dense vector and dense matrix, the dimensions of these structures are very big.

So, I was thinking about the opportunity to modify some algorithms of uBlas using multi-thread programming.

I've tried to do this using openMP. Below, you find my first attempt.

This is a piece of the original code in vector_assign.hpp

// Explicitly indexing

template<template <class T1, class T2> class F, class V, class E>

// BOOST_UBLAS_INLINE This function seems to be big. So we do not let the compiler inline it.

void indexing_vector_assign (V &v, const vector_expression<E> &e) {

typedef F<typename V::reference, typename E::value_type> functor_type;

typedef typename V::size_type size_type;

size_type size (BOOST_UBLAS_SAME (v.size (), e ().size ()));

#ifndef BOOST_UBLAS_USE_DUFF_DEVICE

for (size_type i = 0; i < size; ++ i)

functor_type::apply (v (i), e () (i));

#else

size_type i (0);

DD (size, 2, r, (functor_type::apply (v (i), e () (i)), ++ i));

#endif

}

And I modified the inner for in this way:

int i;

#pragma omp parallel private(i) shared(v, e)

{

#pragma omp for

for (i = 0; i < size; ++ i)

functor_type::apply (v (i), e () (i));

}

I tried the code and it run.

Yes I know that it's better if I use the clause schedule in the pragma for, but the real question is: do you think that this code is enough general? Can I extend it with the operations?

Thank you in advance

Mirko

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