Improve doc on multi-threading and warn about hyper-threading

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Gael Guennebaud 2018-11-14 14:42:29 +01:00
parent db529ae4ec
commit 4263f23c28

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@ -4,22 +4,25 @@ namespace Eigen {
\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 Eigen's API using the following priority:
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 threads that will be used using either the OpenMP API or %Eigen'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 behavior by calling \code setNbThreads(0); \endcode
Unless `setNbThreads` has been called, %Eigen uses the number of threads specified by OpenMP.
You can restore this behavior by calling `setNbThreads(0);`.
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.
You can disable %Eigen's multi threading at compile time by defining the \link TopicPreprocessorDirectivesPerformance EIGEN_DONT_PARALLELIZE \endlink preprocessor token.
Currently, the following algorithms can make use of multi-threading:
- general dense matrix - matrix products
@ -29,9 +32,17 @@ Currently, the following algorithms can make use of multi-threading:
- BiCGSTAB with a row-major sparse matrix format.
- LeastSquaresConjugateGradient
\warning On most OS it is <strong>very important</strong> to limit the number of threads to the number of physical cores, otherwise significant slowdowns are expected, especially for operations involving dense matrices.
Indeed, the principle of hyper-threading is to run multiple threads (in most cases 2) on a single core in an interleaved manner.
However, %Eigen's matrix-matrix product kernel is fully optimized and already exploits nearly 100% of the CPU capacity.
Consequently, there is no room for running multiple such threads on a single core, and the performance would drops significantly because of cache pollution and other sources of overheads.
At this stage of reading you're probably wondering why %Eigen does not limit itself to the number of physical cores?
This is simply because OpenMP does not allow to know the number of physical cores, and thus %Eigen will launch as many threads as <i>cores</i> reported by OpenMP.
\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:
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>
@ -43,11 +54,12 @@ int main(int argc, char** argv)
}
\endcode
\note With Eigen 3.3, and a fully C++11 compliant compiler (i.e., <a href="http://en.cppreference.com/w/cpp/language/storage_duration#Static_local_variables">thread-safe static local variable initialization</a>), then calling \c initParallel() is optional.
\note With %Eigen 3.3, and a fully C++11 compliant compiler (i.e., <a href="http://en.cppreference.com/w/cpp/language/storage_duration#Static_local_variables">thread-safe static local variable initialization</a>), then calling \c initParallel() is optional.
\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.
\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 c++11 random generators (\link DenseBase::NullaryExpr(Index, const CustomNullaryOp&) example \endlink) or `boost::random`.
In the case your application is parallelized with OpenMP, you might want to disable Eigen's own parallelization as detailed in the previous section.
In the case your application is parallelized with OpenMP, you might want to disable %Eigen's own parallelization as detailed in the previous section.
*/