source: pacpussensors/trunk/Vislab/lib3dv-1.2.0/lib3dv/eigen/doc/TopicMultithreading.dox

namespace Eigen {

/** \page TopicMultiThreading Eigen and multi-threading

\section TopicMultiThreading_MakingEigenMT Make Eigen run in parallel

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:
 * GCC: \c -fopenmp
 * ICC: \c -openmp
 * MSVC: check the respective option in the build properties.
You can control the number of thread that will be used using either the OpenMP API or Eiegn's API using the following priority:
\code
 OMP_NUM_THREADS=n ./my_program
 omp_set_num_threads(n);
 Eigen::setNbThreads(n);
\endcode
Unless setNbThreads has been called, Eigen uses the number of threads specified by OpenMP. You can restore this bahavior by calling \code setNbThreads(0); \endcode
You can query the number of threads that will be used with:
\code
n = Eigen::nbThreads( );
\endcode
You can disable Eigen's multi threading at compile time by defining the EIGEN_DONT_PARALLELIZE preprocessor token.

Currently, the following algorithms can make use of multi-threading:
 * general matrix - matrix products
 * PartialPivLU

\section TopicMultiThreading_UsingEigenWithMT Using Eigen in a multi-threaded application

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:
\code
#include <Eigen/Core>

int main(int argc, char** argv)
{
  Eigen::initParallel();
  
  ...
}
\endcode

In the case your application is parallelized with OpenMP, you might want to disable Eigen's own parallization as detailed in the previous section.

*/

}