1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
|
/* Copyright 2013 IST Austria
Contributed by: Ulrich Bauer, Michael Kerber, 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/representations/vector_vector.h>
namespace phat {
// Note: We could even make the rep generic in the underlying Const representation
// But I cannot imagine that anything else than vector<vector<index>> would
// make sense
template< typename PivotColumn >
class abstract_pivot_column : public vector_vector {
protected:
typedef vector_vector Base;
typedef PivotColumn pivot_col;
// For parallization purposes, it could be more than one full column
mutable thread_local_storage< pivot_col > pivot_cols;
mutable thread_local_storage< index > idx_of_pivot_cols;
pivot_col& get_pivot_col() const {
return pivot_cols();
}
bool is_pivot_col( index idx ) const {
return idx_of_pivot_cols() == idx;
}
void release_pivot_col() {
index idx = idx_of_pivot_cols();
if( idx != -1 ) {
this->matrix[ idx ].clear();
pivot_cols().get_col_and_clear( this->matrix[ idx ] );
}
idx_of_pivot_cols() = -1;
}
void make_pivot_col( index idx ) {
release_pivot_col();
idx_of_pivot_cols() = idx;
get_pivot_col().add_col( matrix[ idx ] );
}
public:
void _set_num_cols( index nr_of_cols ) {
#pragma omp parallel for
for( int tid = 0; tid < omp_get_num_threads(); tid++ ) {
pivot_cols[ tid ].init( nr_of_cols );
idx_of_pivot_cols[ tid ] = -1;
}
Base::_set_num_cols( nr_of_cols );
}
void _add_to( index source, index target ) {
if( !is_pivot_col( target ) )
make_pivot_col( target );
get_pivot_col().add_col( matrix[source] );
}
void _sync() {
#pragma omp parallel for
for( int tid = 0; tid < omp_get_num_threads(); tid++ )
release_pivot_col();
}
void _get_col( index idx, column& col ) const { is_pivot_col( idx ) ? get_pivot_col().get_col( col ) : Base::_get_col( idx, col ); }
bool _is_empty( index idx ) const { return is_pivot_col( idx ) ? get_pivot_col().is_empty() : Base::_is_empty( idx ); }
index _get_max_index( index idx ) const { return is_pivot_col( idx ) ? get_pivot_col().get_max_index() : Base::_get_max_index( idx ); }
void _clear( index idx ) { is_pivot_col( idx ) ? get_pivot_col().clear() : Base::_clear( idx ); }
void _set_col( index idx, const column& col ) { is_pivot_col( idx ) ? get_pivot_col().set_col( col ) : Base::_set_col( idx, col ); }
void _remove_max( index idx ) { is_pivot_col( idx ) ? get_pivot_col().remove_max() : Base::_remove_max( idx ); }
};
}
|