1c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// This file is part of Eigen, a lightweight C++ template library
2c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// for linear algebra.
3c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//
4c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Copyright (C) 2010 Gael Guennebaud <gael.guennebaud@inria.fr>
5c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//
6c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// This Source Code Form is subject to the terms of the Mozilla
7c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Public License v. 2.0. If a copy of the MPL was not distributed
8c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
9c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
10c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#ifndef EIGEN_PARALLELIZER_H
11c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#define EIGEN_PARALLELIZER_H
12c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
13c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathnamespace Eigen {
14c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
15c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathnamespace internal {
16c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
17c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \internal */
18c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathinline void manage_multi_threading(Action action, int* v)
19c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
20c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  static EIGEN_UNUSED int m_maxThreads = -1;
21c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
22c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  if(action==SetAction)
23c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
24c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    eigen_internal_assert(v!=0);
25c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    m_maxThreads = *v;
26c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
27c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  else if(action==GetAction)
28c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
29c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    eigen_internal_assert(v!=0);
30c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    #ifdef EIGEN_HAS_OPENMP
31c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    if(m_maxThreads>0)
32c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      *v = m_maxThreads;
33c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    else
34c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      *v = omp_get_max_threads();
35c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    #else
36c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    *v = 1;
37c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    #endif
38c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
39c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  else
40c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
41c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    eigen_internal_assert(false);
42c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
43c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
44c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
45c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
46c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
47c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** Must be call first when calling Eigen from multiple threads */
48c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathinline void initParallel()
49c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
50c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  int nbt;
51c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  internal::manage_multi_threading(GetAction, &nbt);
52c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  std::ptrdiff_t l1, l2;
53c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  internal::manage_caching_sizes(GetAction, &l1, &l2);
54c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
55c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
56c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \returns the max number of threads reserved for Eigen
57c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \sa setNbThreads */
58c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathinline int nbThreads()
59c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
60c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  int ret;
61c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  internal::manage_multi_threading(GetAction, &ret);
62c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  return ret;
63c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
64c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
65c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** Sets the max number of threads reserved for Eigen
66c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \sa nbThreads */
67c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathinline void setNbThreads(int v)
68c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
69c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  internal::manage_multi_threading(SetAction, &v);
70c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
71c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
72c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathnamespace internal {
73c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
74c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Index> struct GemmParallelInfo
75c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
76c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  GemmParallelInfo() : sync(-1), users(0), rhs_start(0), rhs_length(0) {}
77c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
78c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  int volatile sync;
79c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  int volatile users;
80c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
81c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  Index rhs_start;
82c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  Index rhs_length;
83c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
84c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
85c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<bool Condition, typename Functor, typename Index>
86c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathvoid parallelize_gemm(const Functor& func, Index rows, Index cols, bool transpose)
87c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
88c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  // TODO when EIGEN_USE_BLAS is defined,
89c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  // we should still enable OMP for other scalar types
90c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#if !(defined (EIGEN_HAS_OPENMP)) || defined (EIGEN_USE_BLAS)
91c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  // FIXME the transpose variable is only needed to properly split
92c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  // the matrix product when multithreading is enabled. This is a temporary
93c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  // fix to support row-major destination matrices. This whole
94c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  // parallelizer mechanism has to be redisigned anyway.
95c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_UNUSED_VARIABLE(transpose);
96c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  func(0,rows, 0,cols);
97c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#else
98c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
99c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  // Dynamically check whether we should enable or disable OpenMP.
100c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  // The conditions are:
101c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  // - the max number of threads we can create is greater than 1
102c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  // - we are not already in a parallel code
103c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  // - the sizes are large enough
104c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
105c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  // 1- are we already in a parallel session?
106c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  // FIXME omp_get_num_threads()>1 only works for openmp, what if the user does not use openmp?
107c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  if((!Condition) || (omp_get_num_threads()>1))
108c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    return func(0,rows, 0,cols);
109c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
110c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  Index size = transpose ? cols : rows;
111c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
112c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  // 2- compute the maximal number of threads from the size of the product:
113c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  // FIXME this has to be fine tuned
114c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  Index max_threads = std::max<Index>(1,size / 32);
115c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
116c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  // 3 - compute the number of threads we are going to use
117c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  Index threads = std::min<Index>(nbThreads(), max_threads);
118c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
119c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  if(threads==1)
120c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    return func(0,rows, 0,cols);
121c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
122c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  Eigen::initParallel();
123c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  func.initParallelSession();
124c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
125c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  if(transpose)
126c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    std::swap(rows,cols);
127c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
128c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  Index blockCols = (cols / threads) & ~Index(0x3);
129c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  Index blockRows = (rows / threads) & ~Index(0x7);
130c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
131c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  GemmParallelInfo<Index>* info = new GemmParallelInfo<Index>[threads];
132c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
133c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  #pragma omp parallel for schedule(static,1) num_threads(threads)
134c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  for(Index i=0; i<threads; ++i)
135c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
136c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Index r0 = i*blockRows;
137c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Index actualBlockRows = (i+1==threads) ? rows-r0 : blockRows;
138c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
139c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Index c0 = i*blockCols;
140c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Index actualBlockCols = (i+1==threads) ? cols-c0 : blockCols;
141c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
142c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    info[i].rhs_start = c0;
143c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    info[i].rhs_length = actualBlockCols;
144c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
145c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    if(transpose)
146c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      func(0, cols, r0, actualBlockRows, info);
147c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    else
148c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      func(r0, actualBlockRows, 0,cols, info);
149c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
150c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
151c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  delete[] info;
152c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#endif
153c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
154c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
155c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} // end namespace internal
156c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
157c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} // end namespace Eigen
158c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
159c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#endif // EIGEN_PARALLELIZER_H
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