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/* Copyright 2013 IST Austria
Contributed by: Jan Reininghaus
This file is part of PHAT.
PHAT is free software: you can redistribute it and/or modify
it under the terms of the GNU Lesser General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
PHAT is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public License
along with PHAT. If not, see <http://www.gnu.org/licenses/>. */
#pragma once
#include <phat/helpers/misc.h>
#include <phat/boundary_matrix.h>
namespace phat {
class spectral_sequence_reduction {
public:
template< typename Representation >
void operator () ( boundary_matrix< Representation >& boundary_matrix ) {
const index nr_columns = boundary_matrix.get_num_cols();
std::vector< index > lowest_one_lookup( nr_columns, -1 );
//const index num_stripes = (index) sqrt( (double)nr_columns );
const index num_stripes = omp_get_max_threads();
index block_size = ( nr_columns % num_stripes == 0 ) ? nr_columns / num_stripes : block_size = nr_columns / num_stripes + 1;
std::vector< std::vector< index > > unreduced_cols_cur_pass( num_stripes );
std::vector< std::vector< index > > unreduced_cols_next_pass( num_stripes );
for( index cur_dim = boundary_matrix.get_max_dim(); cur_dim >= 1 ; cur_dim-- ) {
#pragma omp parallel for schedule( guided, 1 )
for( index cur_stripe = 0; cur_stripe < num_stripes; cur_stripe++ ) {
index col_begin = cur_stripe * block_size;
index col_end = std::min( (cur_stripe+1) * block_size, nr_columns );
for( index cur_col = col_begin; cur_col < col_end; cur_col++ )
if( boundary_matrix.get_dim( cur_col ) == cur_dim && boundary_matrix.get_max_index( cur_col ) != -1 )
unreduced_cols_cur_pass[ cur_stripe ].push_back( cur_col );
}
for( index cur_pass = 0; cur_pass < num_stripes; cur_pass++ ) {
boundary_matrix.sync();
#pragma omp parallel for schedule( guided, 1 )
for( int cur_stripe = 0; cur_stripe < num_stripes; cur_stripe++ ) {
index row_begin = (cur_stripe - cur_pass) * block_size;
index row_end = row_begin + block_size;
unreduced_cols_next_pass[ cur_stripe ].clear();
for( index idx = 0; idx < (index)unreduced_cols_cur_pass[ cur_stripe ].size(); idx++ ) {
index cur_col = unreduced_cols_cur_pass[ cur_stripe ][ idx ];
index lowest_one = boundary_matrix.get_max_index( cur_col );
while( lowest_one != -1 && lowest_one >= row_begin && lowest_one < row_end && lowest_one_lookup[ lowest_one ] != -1 ) {
boundary_matrix.add_to( lowest_one_lookup[ lowest_one ], cur_col );
lowest_one = boundary_matrix.get_max_index( cur_col );
}
if( lowest_one != -1 ) {
if( lowest_one >= row_begin && lowest_one < row_end ) {
lowest_one_lookup[ lowest_one ] = cur_col;
boundary_matrix.clear( lowest_one );
boundary_matrix.finalize( cur_col );
} else {
unreduced_cols_next_pass[ cur_stripe ].push_back( cur_col );
}
}
}
unreduced_cols_next_pass[ cur_stripe ].swap( unreduced_cols_cur_pass[ cur_stripe ] );
}
}
}
}
};
}
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