bug #466: better fix for the race condition: this new patch add an initParallel()
function which must be called at the initialization time of any multi-threaded application calling Eigen from multiple threads.
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@ -329,9 +329,9 @@ using std::ptrdiff_t;
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#include "src/Core/GeneralProduct.h"
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#include "src/Core/GeneralProduct.h"
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#include "src/Core/TriangularMatrix.h"
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#include "src/Core/TriangularMatrix.h"
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#include "src/Core/SelfAdjointView.h"
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#include "src/Core/SelfAdjointView.h"
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#include "src/Core/products/GeneralBlockPanelKernel.h"
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#include "src/Core/products/Parallelizer.h"
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#include "src/Core/products/Parallelizer.h"
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#include "src/Core/products/CoeffBasedProduct.h"
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#include "src/Core/products/CoeffBasedProduct.h"
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#include "src/Core/products/GeneralBlockPanelKernel.h"
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#include "src/Core/products/GeneralMatrixVector.h"
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#include "src/Core/products/GeneralMatrixVector.h"
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#include "src/Core/products/GeneralMatrixMatrix.h"
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#include "src/Core/products/GeneralMatrixMatrix.h"
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#include "src/Core/SolveTriangular.h"
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#include "src/Core/SolveTriangular.h"
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@ -26,7 +26,7 @@
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#define EIGEN_GENERAL_BLOCK_PANEL_H
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#define EIGEN_GENERAL_BLOCK_PANEL_H
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namespace Eigen {
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namespace Eigen {
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namespace internal {
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namespace internal {
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template<typename _LhsScalar, typename _RhsScalar, bool _ConjLhs=false, bool _ConjRhs=false>
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template<typename _LhsScalar, typename _RhsScalar, bool _ConjLhs=false, bool _ConjRhs=false>
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@ -44,8 +44,7 @@ inline void manage_caching_sizes(Action action, std::ptrdiff_t* l1=0, std::ptrdi
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{
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{
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static std::ptrdiff_t m_l1CacheSize = 0;
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static std::ptrdiff_t m_l1CacheSize = 0;
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static std::ptrdiff_t m_l2CacheSize = 0;
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static std::ptrdiff_t m_l2CacheSize = 0;
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#pragma omp threadprivate(m_l1CacheSize,m_l2CacheSize)
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if(m_l2CacheSize==0)
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if(m_l1CacheSize==0)
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{
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{
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m_l1CacheSize = manage_caching_sizes_helper(queryL1CacheSize(),8 * 1024);
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m_l1CacheSize = manage_caching_sizes_helper(queryL1CacheSize(),8 * 1024);
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m_l2CacheSize = manage_caching_sizes_helper(queryTopLevelCacheSize(),1*1024*1024);
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m_l2CacheSize = manage_caching_sizes_helper(queryTopLevelCacheSize(),1*1024*1024);
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@ -57,12 +57,23 @@ inline void manage_multi_threading(Action action, int* v)
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}
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}
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}
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}
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}
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/** Must be call first when calling Eigen from multiple threads */
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inline void initParallel()
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{
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int nbt;
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internal::manage_multi_threading(GetAction, &nbt);
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std::ptrdiff_t l1, l2;
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internal::manage_caching_sizes(GetAction, &l1, &l2);
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}
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/** \returns the max number of threads reserved for Eigen
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/** \returns the max number of threads reserved for Eigen
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* \sa setNbThreads */
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* \sa setNbThreads */
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inline int nbThreads()
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inline int nbThreads()
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{
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{
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int ret;
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int ret;
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manage_multi_threading(GetAction, &ret);
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internal::manage_multi_threading(GetAction, &ret);
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return ret;
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return ret;
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}
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}
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@ -70,9 +81,11 @@ inline int nbThreads()
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* \sa nbThreads */
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* \sa nbThreads */
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inline void setNbThreads(int v)
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inline void setNbThreads(int v)
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{
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{
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manage_multi_threading(SetAction, &v);
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internal::manage_multi_threading(SetAction, &v);
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}
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}
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namespace internal {
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template<typename Index> struct GemmParallelInfo
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template<typename Index> struct GemmParallelInfo
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{
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{
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GemmParallelInfo() : sync(-1), users(0), rhs_start(0), rhs_length(0) {}
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GemmParallelInfo() : sync(-1), users(0), rhs_start(0), rhs_length(0) {}
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@ -121,6 +134,7 @@ void parallelize_gemm(const Functor& func, Index rows, Index cols, bool transpos
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if(threads==1)
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if(threads==1)
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return func(0,rows, 0,cols);
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return func(0,rows, 0,cols);
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Eigen::initParallel();
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func.initParallelSession();
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func.initParallelSession();
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if(transpose)
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if(transpose)
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46
doc/TopicMultithreading.dox
Normal file
46
doc/TopicMultithreading.dox
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@ -0,0 +1,46 @@
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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 Eiegn'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 bahavior 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(n);
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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 matrix - matrix products
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* PartialPivLU
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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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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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