1namespace Eigen {
2
3/** \page TopicMultiThreading Eigen and multi-threading
4
5\section TopicMultiThreading_MakingEigenMT Make Eigen run in parallel
6
7Some 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:
8 * GCC: \c -fopenmp
9 * ICC: \c -openmp
10 * MSVC: check the respective option in the build properties.
11You can control the number of thread that will be used using either the OpenMP API or Eiegn's API using the following priority:
12\code
13 OMP_NUM_THREADS=n ./my_program
14 omp_set_num_threads(n);
15 Eigen::setNbThreads(n);
16\endcode
17Unless setNbThreads has been called, Eigen uses the number of threads specified by OpenMP. You can restore this bahavior by calling \code setNbThreads(0); \endcode
18You can query the number of threads that will be used with:
19\code
20n = Eigen::nbThreads( );
21\endcode
22You can disable Eigen's multi threading at compile time by defining the EIGEN_DONT_PARALLELIZE preprocessor token.
23
24Currently, the following algorithms can make use of multi-threading:
25 * general matrix - matrix products
26 * PartialPivLU
27
28\section TopicMultiThreading_UsingEigenWithMT Using Eigen in a multi-threaded application
29
30In 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:
31\code
32#include <Eigen/Core>
33
34int main(int argc, char** argv)
35{
36  Eigen::initParallel();
37  
38  ...
39}
40\endcode
41
42In the case your application is parallelized with OpenMP, you might want to disable Eigen's own parallization as detailed in the previous section.
43
44*/
45
46}
47