Added tutorial on for loops.

add_subdirectory( Arrays )

add_subdirectory( Vectors )

add_subdirectory( ReductionAndScan )

add_subdirectory( ForLoops )

IF( BUILD_CUDA )

   CUDA_ADD_EXECUTABLE( ParallelForExample ParallelForExample.cu )

   ADD_CUSTOM_COMMAND( COMMAND ParallelForExample > ${TNL_DOCUMENTATION_OUTPUT_SNIPPETS_PATH}/ParallelForExample.out OUTPUT ParallelForExample.out )

ENDIF()

IF( BUILD_CUDA )

ADD_CUSTOM_TARGET( ForLoops-cuda ALL DEPENDS

   ParallelForExample.out )

ENDIF()

#include <iostream>

#include <cstdlib>

#include <TNL/Containers/Vector.h>

using namespace TNL;

using namespace TNL::Containers;

using namespace TNL::Containers::Algorithms;

template< typename Device >

void vectorSum( const Vector< double, Device >& v1,

                const Vector< double, Device >& v2,

                const double& c,

                Vector< double, Device >& result )

{

   /****

    * Get vectors view which can be captured by lambda.

    */

   auto v1_view = v1.getConstView();

   auto v2_view = v2.getConstView();

   auto result_view = result.getView();

   /****

    * The sum function.

    */

   auto sum = [=] __cuda_callable__  ( int i, const double c ) mutable {

      result_view[ i ] = v1_view[ i ] + v2_view[ i ] + c; };

      ParallelFor< Device >::exec( 0, v1.getSize(), sum, c );

}

int main( int argc, char* argv[] )

{

   /***

    * Firstly, test the vectors sum on CPU.

    */

   Vector< double, Devices::Host > host_v1( 10 ), host_v2( 10 ), host_result( 10 );

   host_v1 = 1.0;

   host_v2.evaluate( []__cuda_callable__ ( int i )->double { return i; } );

   vectorSum( host_v1, host_v2, 2.0, host_result );

   std::cout << "host_v1 = " << host_v1 << std::endl;

   std::cout << "host_v2 = " << host_v2 << std::endl;

   std::cout << "The sum of the vectors on CPU is " << host_result << "." << std::endl;

   /***

    * And then also on GPU.

    */

#ifdef HAVE_CUDA

   Vector< double, Devices::Cuda > cuda_v1( 10 ), cuda_v2( 10 ), cuda_result( 10 );

   cuda_v1 = 1.0;

   cuda_v2.evaluate( []__cuda_callable__ ( int i )->double { return i; } );

   vectorSum( cuda_v1, cuda_v2, 2.0, cuda_result );

   std::cout << "cuda_v1 = " << cuda_v1 << std::endl;

   std::cout << "cuda_v2 = " << cuda_v2 << std::endl;

   std::cout << "The sum of the vectors on GPU is " << cuda_result << "." << std::endl;

#endif

   return EXIT_SUCCESS;

}

ParallelForExample.cpp

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