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// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2010 Gael Guennebaud <g.gael@free.fr>
//
// Eigen 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.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen 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 or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_PARALLELIZER_H
#define EIGEN_PARALLELIZER_H
template<bool Parallelize,typename Functor>
void ei_run_parallel_1d(const Functor& func, int size)
{
#ifndef EIGEN_HAS_OPENMP
func(0,size);
#else
if(!Parallelize)
return func(0,size);
int threads = omp_get_num_procs();
int blockSize = size / threads;
#pragma omp parallel for schedule(static,1)
for(int i=0; i<threads; ++i)
{
int blockStart = i*blockSize;
int actualBlockSize = std::min(blockSize, size - blockStart);
func(blockStart, actualBlockSize);
}
#endif
}
template<bool Parallelize,typename Functor>
void ei_run_parallel_2d(const Functor& func, int size1, int size2)
{
#ifndef EIGEN_HAS_OPENMP
func(0,size1, 0,size2);
#else
if(!Parallelize)
return func(0,size1, 0,size2);
// 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16
static const int divide1[17] = { 0, 1, 2, 3, 2, 5, 3, 7, 4, 3, 5, 11, 4, 13, 7, 5, 4};
static const int divide2[17] = { 0, 1, 1, 1, 2, 1, 2, 1, 2, 3, 2, 1, 3, 1, 2, 3, 4};
int threads = omp_get_num_procs();
ei_assert(threads<=16 && "too many threads !");
int blockSize1 = size1 / divide1[threads];
int blockSize2 = size2 / divide2[threads];
Matrix<int,4,Dynamic> ranges(4,threads);
int k = 0;
for(int i1=0; i1<divide1[threads]; ++i1)
{
int blockStart1 = i1*blockSize1;
int actualBlockSize1 = std::min(blockSize1, size1 - blockStart1);
for(int i2=0; i2<divide2[threads]; ++i2)
{
int blockStart2 = i2*blockSize2;
int actualBlockSize2 = std::min(blockSize2, size2 - blockStart2);
ranges.col(k++) << blockStart1, actualBlockSize1, blockStart2, actualBlockSize2;
}
}
#pragma omp parallel for schedule(static,1)
for(int i=0; i<threads; ++i)
{
func(ranges.col(i)[0],ranges.col(i)[1],ranges.col(i)[2],ranges.col(i)[3]);
}
#endif
}
#endif // EIGEN_GENERAL_MATRIX_MATRIX_H
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