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53 lines
2.2 KiB
Plaintext
53 lines
2.2 KiB
Plaintext
namespace Eigen {
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/** \page TopicMultiThreading Eigen and multi-threading
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\section TopicMultiThreading_MakingEigenMT Make Eigen run in parallel
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Some Eigen's algorithms can exploit the multiple cores present in your hardware. To this end, it is enough to enable OpenMP on your compiler, for instance:
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* GCC: \c -fopenmp
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* ICC: \c -openmp
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* MSVC: check the respective option in the build properties.
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You can control the number of thread that will be used using either the OpenMP API or Eigen's API using the following priority:
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\code
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OMP_NUM_THREADS=n ./my_program
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omp_set_num_threads(n);
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Eigen::setNbThreads(n);
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\endcode
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Unless setNbThreads has been called, Eigen uses the number of threads specified by OpenMP. You can restore this behavior by calling \code setNbThreads(0); \endcode
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You can query the number of threads that will be used with:
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\code
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n = Eigen::nbThreads( );
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\endcode
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You can disable Eigen's multi threading at compile time by defining the EIGEN_DONT_PARALLELIZE preprocessor token.
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Currently, the following algorithms can make use of multi-threading:
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- general dense matrix - matrix products
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- PartialPivLU
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- row-major-sparse * dense vector/matrix products
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- ConjugateGradient with \c Lower|Upper as the \c UpLo template parameter.
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- BiCGSTAB with a row-major sparse matrix format.
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- LeastSquaresConjugateGradient
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\section TopicMultiThreading_UsingEigenWithMT Using Eigen in a multi-threaded application
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In the case your own application is multithreaded, and multiple threads make calls to Eigen, then you have to initialize Eigen by calling the following routine \b before creating the threads:
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\code
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#include <Eigen/Core>
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int main(int argc, char** argv)
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{
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Eigen::initParallel();
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...
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}
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\endcode
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\warning note that all functions generating random matrices are \b not re-entrant nor thread-safe. Those include DenseBase::Random(), and DenseBase::setRandom() despite a call to Eigen::initParallel(). This is because these functions are based on std::rand which is not re-entrant. For thread-safe random generator, we recommend the use of boost::random or c++11 random feature.
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In the case your application is parallelized with OpenMP, you might want to disable Eigen's own parallization as detailed in the previous section.
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*/
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}
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