Module: ppl/ppl Branch: MPI Commit: 262fd31e77b59abfafba4ee7b1fb8f4adf5de2ac URL: http://www.cs.unipr.it/git/gitweb.cgi?p=ppl/ppl.git;a=commit;h=262fd31e77b59...

Author: Marco Poletti poletti.marco@gmail.com Date: Fri Sep 10 17:47:07 2010 +0200

Distributed_Sparse_Matrix: optimize compute_working_cost_reducer_functor.

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src/Distributed_Sparse_Matrix.cc | 42 ++++++++++++++++++------------------- 1 files changed, 20 insertions(+), 22 deletions(-)

diff --git a/src/Distributed_Sparse_Matrix.cc b/src/Distributed_Sparse_Matrix.cc index 3b44eaf..9ec2f61 100644 --- a/src/Distributed_Sparse_Matrix.cc +++ b/src/Distributed_Sparse_Matrix.cc @@ -583,21 +583,18 @@ namespace { struct compute_working_cost_reducer_functor { typedef std::pair<std::pair<PPL::Coefficient, PPL::Coefficient>, PPL::Sparse_Row> pair_type; - pair_type - operator()(const pair_type& x, const pair_type& y) const { - pair_type result(x); - const PPL::Coefficient& x_scaling = x.first.first; - const PPL::Coefficient& x_reverse_scaling = x.first.second; + const pair_type& + operator()(pair_type& x, const pair_type& y) const { + PPL::Coefficient& x_scaling = x.first.first; + PPL::Coefficient& x_reverse_scaling = x.first.second; + PPL::Sparse_Row& x_row = x.second; const PPL::Coefficient& y_scaling = y.first.first; const PPL::Coefficient& y_reverse_scaling = y.first.second; + const PPL::Sparse_Row& y_row = y.second; PPL_ASSERT(x_scaling != 0); PPL_ASSERT(x_reverse_scaling != 0); PPL_ASSERT(y_scaling != 0); PPL_ASSERT(y_reverse_scaling != 0); - const PPL::Sparse_Row& y_row = y.second; - PPL::Coefficient& scaling = result.first.first; - PPL::Coefficient& reverse_scaling = result.first.second; - PPL::Sparse_Row& row = result.second;

PPL::Coefficient x_normalized_scaling = x_scaling * y_reverse_scaling; PPL::Coefficient y_normalized_scaling = y_scaling * x_reverse_scaling; @@ -606,19 +603,20 @@ struct compute_working_cost_reducer_functor { PPL::exact_div_assign(x_normalized_scaling, x_normalized_scaling, gcd); PPL::exact_div_assign(y_normalized_scaling, y_normalized_scaling, gcd);

- scaling *= y_scaling; - reverse_scaling = gcd; - PPL_ASSERT(scaling != 0); - PPL_ASSERT(reverse_scaling != 0); - PPL::normalize2(scaling, reverse_scaling, scaling, reverse_scaling); - PPL_ASSERT(scaling != 0); - PPL_ASSERT(reverse_scaling != 0); - - PPL::dimension_type n = x.second.size(); - PPL::Dense_Row tmp(n, PPL::Row_Flags()); - row.linear_combine(y_row, y_normalized_scaling, x_normalized_scaling); - // TODO: Check if the copy can be avoided. - return result; + x_scaling *= y_scaling; + x_reverse_scaling = gcd; + + x_row.linear_combine(y_row, y_normalized_scaling, x_normalized_scaling); + + x_row.normalize(gcd); + x_reverse_scaling *= gcd; + + PPL::normalize2(x_scaling, x_reverse_scaling, + x_scaling, x_reverse_scaling); + + // This return is needed because mpi::reduce() requires it. + // x will be assigned to itself, so the data will not be copied. + return x; } };