1 // This file is part of Eigen, a lightweight C++ template library
2 // for linear algebra.
3 //
4 // Copyright (C) 2010 Gael Guennebaud <gael.guennebaud@inria.fr>
5 //
6 // This Source Code Form is subject to the terms of the Mozilla
7 // Public License v. 2.0. If a copy of the MPL was not distributed
8 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
9
10 #ifndef EIGEN_PARALLELIZER_H
11 #define EIGEN_PARALLELIZER_H
12
13 #include <atomic>
14
15 namespace Eigen {
16
17 namespace internal {
18
19 /** \internal */
manage_multi_threading(Action action,int * v)20 inline void manage_multi_threading(Action action, int* v)
21 {
22 static EIGEN_UNUSED int m_maxThreads = -1;
23
24 if(action==SetAction)
25 {
26 eigen_internal_assert(v!=0);
27 m_maxThreads = *v;
28 }
29 else if(action==GetAction)
30 {
31 eigen_internal_assert(v!=0);
32 #ifdef EIGEN_HAS_OPENMP
33 if(m_maxThreads>0)
34 *v = m_maxThreads;
35 else
36 *v = omp_get_max_threads();
37 #else
38 *v = 1;
39 #endif
40 }
41 else
42 {
43 eigen_internal_assert(false);
44 }
45 }
46
47 }
48
49 /** Must be call first when calling Eigen from multiple threads */
initParallel()50 inline void initParallel()
51 {
52 int nbt;
53 internal::manage_multi_threading(GetAction, &nbt);
54 std::ptrdiff_t l1, l2, l3;
55 internal::manage_caching_sizes(GetAction, &l1, &l2, &l3);
56 }
57
58 /** \returns the max number of threads reserved for Eigen
59 * \sa setNbThreads */
nbThreads()60 inline int nbThreads()
61 {
62 int ret;
63 internal::manage_multi_threading(GetAction, &ret);
64 return ret;
65 }
66
67 /** Sets the max number of threads reserved for Eigen
68 * \sa nbThreads */
setNbThreads(int v)69 inline void setNbThreads(int v)
70 {
71 internal::manage_multi_threading(SetAction, &v);
72 }
73
74 namespace internal {
75
76 template<typename Index> struct GemmParallelInfo
77 {
GemmParallelInfoGemmParallelInfo78 GemmParallelInfo() : sync(-1), users(0), lhs_start(0), lhs_length(0) {}
79
80 std::atomic<Index> sync;
81 std::atomic<int> users;
82
83 Index lhs_start;
84 Index lhs_length;
85 };
86
87 template<bool Condition, typename Functor, typename Index>
parallelize_gemm(const Functor & func,Index rows,Index cols,Index depth,bool transpose)88 void parallelize_gemm(const Functor& func, Index rows, Index cols, Index depth, bool transpose)
89 {
90 // TODO when EIGEN_USE_BLAS is defined,
91 // we should still enable OMP for other scalar types
92 #if !(defined (EIGEN_HAS_OPENMP)) || defined (EIGEN_USE_BLAS)
93 // FIXME the transpose variable is only needed to properly split
94 // the matrix product when multithreading is enabled. This is a temporary
95 // fix to support row-major destination matrices. This whole
96 // parallelizer mechanism has to be redisigned anyway.
97 EIGEN_UNUSED_VARIABLE(depth);
98 EIGEN_UNUSED_VARIABLE(transpose);
99 func(0,rows, 0,cols);
100 #else
101
102 // Dynamically check whether we should enable or disable OpenMP.
103 // The conditions are:
104 // - the max number of threads we can create is greater than 1
105 // - we are not already in a parallel code
106 // - the sizes are large enough
107
108 // compute the maximal number of threads from the size of the product:
109 // This first heuristic takes into account that the product kernel is fully optimized when working with nr columns at once.
110 Index size = transpose ? rows : cols;
111 Index pb_max_threads = std::max<Index>(1,size / Functor::Traits::nr);
112
113 // compute the maximal number of threads from the total amount of work:
114 double work = static_cast<double>(rows) * static_cast<double>(cols) *
115 static_cast<double>(depth);
116 double kMinTaskSize = 50000; // FIXME improve this heuristic.
117 pb_max_threads = std::max<Index>(1, std::min<Index>(pb_max_threads, work / kMinTaskSize));
118
119 // compute the number of threads we are going to use
120 Index threads = std::min<Index>(nbThreads(), pb_max_threads);
121
122 // if multi-threading is explicitely disabled, not useful, or if we already are in a parallel session,
123 // then abort multi-threading
124 // FIXME omp_get_num_threads()>1 only works for openmp, what if the user does not use openmp?
125 if((!Condition) || (threads==1) || (omp_get_num_threads()>1))
126 return func(0,rows, 0,cols);
127
128 Eigen::initParallel();
129 func.initParallelSession(threads);
130
131 if(transpose)
132 std::swap(rows,cols);
133
134 ei_declare_aligned_stack_constructed_variable(GemmParallelInfo<Index>,info,threads,0);
135
136 #pragma omp parallel num_threads(threads)
137 {
138 Index i = omp_get_thread_num();
139 // Note that the actual number of threads might be lower than the number of request ones.
140 Index actual_threads = omp_get_num_threads();
141
142 Index blockCols = (cols / actual_threads) & ~Index(0x3);
143 Index blockRows = (rows / actual_threads);
144 blockRows = (blockRows/Functor::Traits::mr)*Functor::Traits::mr;
145
146 Index r0 = i*blockRows;
147 Index actualBlockRows = (i+1==actual_threads) ? rows-r0 : blockRows;
148
149 Index c0 = i*blockCols;
150 Index actualBlockCols = (i+1==actual_threads) ? cols-c0 : blockCols;
151
152 info[i].lhs_start = r0;
153 info[i].lhs_length = actualBlockRows;
154
155 if(transpose) func(c0, actualBlockCols, 0, rows, info);
156 else func(0, rows, c0, actualBlockCols, info);
157 }
158 #endif
159 }
160
161 } // end namespace internal
162
163 } // end namespace Eigen
164
165 #endif // EIGEN_PARALLELIZER_H
166