Module: ppl/ppl Branch: MPI Commit: 6c3d9cd541493017fbe0f813f3edbb721c8fa094 URL: http://www.cs.unipr.it/git/gitweb.cgi?p=ppl/ppl.git;a=commit;h=6c3d9cd541493...

Author: Marco Poletti poletti.marco@gmail.com Date: Sun Sep 12 09:11:49 2010 +0200

Distributed_Sparse_Matrix: move some code.

---

src/Distributed_Sparse_Matrix.cc | 154 +++++++++++++++++++------------------- 1 files changed, 77 insertions(+), 77 deletions(-)

diff --git a/src/Distributed_Sparse_Matrix.cc b/src/Distributed_Sparse_Matrix.cc index ddf67fe..f25675c 100644 --- a/src/Distributed_Sparse_Matrix.cc +++ b/src/Distributed_Sparse_Matrix.cc @@ -1661,83 +1661,6 @@ PPL::Distributed_Sparse_Matrix return entering_index; }

-namespace { - -class exact_entering_index_reducer_functor2 { -public: - const std::vectorPPL::Coefficient& - operator()(std::vectorPPL::Coefficient& x, - const std::vectorPPL::Coefficient& y) const { - PPL_ASSERT(x.size() == y.size()); - for (PPL::dimension_type i = x.size(); i-- > 0; ) - x[i] += y[i]; - return x; - } -}; - -} // namespace - -PPL::dimension_type -PPL::Distributed_Sparse_Matrix -::exact_entering_index(const Dense_Row& working_cost) const { - broadcast_operation(EXACT_ENTERING_INDEX_OPERATION, id); - - // Contains the list of the (column) indexes of challengers. - std::vector<dimension_type> columns; - // This is only an upper bound. - columns.reserve(num_columns() - 1); - - const int cost_sign = sgn(working_cost[working_cost.size() - 1]); - for (dimension_type column = 1; column < num_columns() - 1; ++column) - if (sgn(working_cost[column]) == cost_sign) { - columns.push_back(column); - } - - mpi::broadcast(comm(), columns, 0); - - // For each i, challenger_values[i] contains the challenger value for the - // columns[i] column. - std::vector<Coefficient> challenger_values(columns.size()); - PPL_DIRTY_TEMP_COEFFICIENT(squared_lcm_basis); - exact_entering_index__common(columns, challenger_values, local_rows, base, - squared_lcm_basis); - - std::vector<Coefficient> global_challenger_values; - mpi::reduce(comm(), challenger_values, global_challenger_values, - exact_entering_index_reducer_functor2(), 0); - - PPL_DIRTY_TEMP_COEFFICIENT(challenger_num); - PPL_DIRTY_TEMP_COEFFICIENT(current_num); - PPL_DIRTY_TEMP_COEFFICIENT(current_den); - PPL_DIRTY_TEMP_COEFFICIENT(challenger_value); - PPL_DIRTY_TEMP_COEFFICIENT(current_value); - dimension_type entering_index = 0; - for (dimension_type k = 0; k < columns.size(); ++k) { - global_challenger_values[k] += squared_lcm_basis; - Coefficient_traits::const_reference cost_j = working_cost[columns[k]]; - // We cannot compute the (exact) square root of abs(\Delta x_j). - // The workaround is to compute the square of `cost[j]'. - challenger_num = cost_j * cost_j; - // Initialization during the first loop. - if (entering_index == 0) { - std::swap(current_num, challenger_num); - std::swap(current_den, global_challenger_values[k]); - entering_index = columns[k]; - continue; - } - challenger_value = challenger_num * current_den; - current_value = current_num * global_challenger_values[k]; - // Update the values, if the challenger wins. - if (challenger_value > current_value) { - std::swap(current_num, challenger_num); - std::swap(current_den, global_challenger_values[k]); - entering_index = columns[k]; - } - } - - return entering_index; -} - void PPL::Distributed_Sparse_Matrix ::set_artificial_indexes_for_new_rows(dimension_type old_num_rows, @@ -1839,6 +1762,83 @@ PPL::Distributed_Sparse_Matrix } }

+namespace { + +class exact_entering_index_reducer_functor2 { +public: + const std::vectorPPL::Coefficient& + operator()(std::vectorPPL::Coefficient& x, + const std::vectorPPL::Coefficient& y) const { + PPL_ASSERT(x.size() == y.size()); + for (PPL::dimension_type i = x.size(); i-- > 0; ) + x[i] += y[i]; + return x; + } +}; + +} // namespace + +PPL::dimension_type +PPL::Distributed_Sparse_Matrix +::exact_entering_index(const Dense_Row& working_cost) const { + broadcast_operation(EXACT_ENTERING_INDEX_OPERATION, id); + + // Contains the list of the (column) indexes of challengers. + std::vector<dimension_type> columns; + // This is only an upper bound. + columns.reserve(num_columns() - 1); + + const int cost_sign = sgn(working_cost[working_cost.size() - 1]); + for (dimension_type column = 1; column < num_columns() - 1; ++column) + if (sgn(working_cost[column]) == cost_sign) { + columns.push_back(column); + } + + mpi::broadcast(comm(), columns, 0); + + // For each i, challenger_values[i] contains the challenger value for the + // columns[i] column. + std::vector<Coefficient> challenger_values(columns.size()); + PPL_DIRTY_TEMP_COEFFICIENT(squared_lcm_basis); + exact_entering_index__common(columns, challenger_values, local_rows, base, + squared_lcm_basis); + + std::vector<Coefficient> global_challenger_values; + mpi::reduce(comm(), challenger_values, global_challenger_values, + exact_entering_index_reducer_functor2(), 0); + + PPL_DIRTY_TEMP_COEFFICIENT(challenger_num); + PPL_DIRTY_TEMP_COEFFICIENT(current_num); + PPL_DIRTY_TEMP_COEFFICIENT(current_den); + PPL_DIRTY_TEMP_COEFFICIENT(challenger_value); + PPL_DIRTY_TEMP_COEFFICIENT(current_value); + dimension_type entering_index = 0; + for (dimension_type k = 0; k < columns.size(); ++k) { + global_challenger_values[k] += squared_lcm_basis; + Coefficient_traits::const_reference cost_j = working_cost[columns[k]]; + // We cannot compute the (exact) square root of abs(\Delta x_j). + // The workaround is to compute the square of `cost[j]'. + challenger_num = cost_j * cost_j; + // Initialization during the first loop. + if (entering_index == 0) { + std::swap(current_num, challenger_num); + std::swap(current_den, global_challenger_values[k]); + entering_index = columns[k]; + continue; + } + challenger_value = challenger_num * current_den; + current_value = current_num * global_challenger_values[k]; + // Update the values, if the challenger wins. + if (challenger_value > current_value) { + std::swap(current_num, challenger_num); + std::swap(current_den, global_challenger_values[k]); + entering_index = columns[k]; + } + } + + return entering_index; +} + PPL::dimension_type PPL::Distributed_Sparse_Matrix::get_unique_id() { static dimension_type next_id = 0;