Commit b6491b23 authored by Tomáš Oberhuber's avatar Tomáš Oberhuber Committed by Tomáš Oberhuber
Browse files

Tutorials on reduction.

parent 206aa116

Documentation/Tutorials/Reduction/CMakeLists.txt

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@@ -11,6 +11,14 @@ IF( BUILD_CUDA ) 
   ADD_CUSTOM_COMMAND( COMMAND ComparisonExample > ComparisonExample.out OUTPUT ComparisonExample.out )

   CUDA_ADD_EXECUTABLE( UpdateAndResidueExample UpdateAndResidueExample.cu )

   ADD_CUSTOM_COMMAND( COMMAND UpdateAndResidueExample > UpdateAndResidueExample.out OUTPUT UpdateAndResidueExample.out )

   CUDA_ADD_EXECUTABLE( MaskAndReduceExample-1 MaskAndReduceExample-1.cu )

   ADD_CUSTOM_COMMAND( COMMAND MaskAndReduceExample-1 > MaskAndReduceExample-1.out OUTPUT MaskAndReduceExample-1.out )

   CUDA_ADD_EXECUTABLE( MaskAndReduceExample-2 MaskAndReduceExample-2.cu )

   ADD_CUSTOM_COMMAND( COMMAND MaskAndReduceExample-2 > MaskAndReduceExample-2.out OUTPUT MaskAndReduceExample-2.out )

   CUDA_ADD_EXECUTABLE( MaskAndReduceExample-3 MaskAndReduceExample-3.cu )

   ADD_CUSTOM_COMMAND( COMMAND MaskAndReduceExample-3 > MaskAndReduceExample-3.out OUTPUT MaskAndReduceExample-3.out )

   ADD_EXECUTABLE( ReductionInMethodsExample ReductionInMethodsExample.cpp )

   ADD_CUSTOM_COMMAND( COMMAND ReductionInMethodsExample > ReductionInMethodsExample.out OUTPUT ReductionInMethodsExample.out )

ENDIF()



IF( BUILD_CUDA )
@@ -20,5 +28,9 @@ ADD_CUSTOM_TARGET( TutorialsReduction-cuda ALL DEPENDS 
   ScalarProductExample.out

   MaximumNormExample.out 

   ComparisonExample.out

   UpdateAndResidueExample.out )

   UpdateAndResidueExample.out

   MaskAndReduceExample-1.out

   MaskAndReduceExample-2.out

   MaskAndReduceExample-3.out

   ReductionInMethodsExample.out )

ENDIF()

Documentation/Tutorials/Reduction/MaskAndReduceExample-1.cpp

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#include <iostream>

#include <cstdlib>

#include <TNL/Containers/Vector.h>

#include <TNL/Containers/Algorithms/Reduction.h>

#include <TNL/Timer.h>



using namespace TNL;

using namespace TNL::Containers;

using namespace TNL::Containers::Algorithms;



template< typename Device >

double maskAndReduce( Vector< double, Device >& u )

{

   auto u_view = u.getView();

   auto fetch = [=] __cuda_callable__ ( int i )->double {

      return u_view[ i ] > 0 ? u_view[ i ] : 0.0; };

   auto reduce = [] __cuda_callable__ ( double& a, const double& b ) { a += b; };

   auto volatileReduce = [=] __cuda_callable__ ( volatile double& a, const volatile double& b ) { a += b; };

   return Reduction< Device >::reduce( u_view.getSize(), reduce, volatileReduce, fetch, 0.0 );

}



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

{

   Timer timer;

   Vector< double, Devices::Host > host_u( 10 );

   host_u.evaluate( [] __cuda_callable__ ( int i ) { return sin( ( double ) i ); } );

   double result = maskAndReduce( host_u );

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

   std::cout << "Sum of the positive numbers is:" << result << std::endl;

#ifdef HAVE_CUDA

   Vector< double, Devices::Cuda > cuda_u( 10 );

   cuda_u = host_u;

   result = maskAndReduce( cuda_u );

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

   std::cout << "Sum of the positive numbers is:" << result << std::endl;

#endif

   return EXIT_SUCCESS;

}

Documentation/Tutorials/Reduction/MaskAndReduceExample-1.cu

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MaskAndReduceExample-1.cpp
 
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Documentation/Tutorials/Reduction/MaskAndReduceExample-2.cpp

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#include <iostream>

#include <cstdlib>

#include <TNL/Containers/Vector.h>

#include <TNL/Containers/Algorithms/Reduction.h>

#include <TNL/Timer.h>



using namespace TNL;

using namespace TNL::Containers;

using namespace TNL::Containers::Algorithms;



template< typename Device >

double maskAndReduce( Vector< double, Device >& u )

{

   auto u_view = u.getView();

   auto fetch = [=] __cuda_callable__ ( int i )->double {

      if( i % 2 == 0 ) return u_view[ i ];

      return 0.0; };

   auto reduce = [] __cuda_callable__ ( double& a, const double& b ) { a += b; };

   auto volatileReduce = [=] __cuda_callable__ ( volatile double& a, const volatile double& b ) { a += b; };

   return Reduction< Device >::reduce( u_view.getSize(), reduce, volatileReduce, fetch, 0.0 );

}



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

{

   Timer timer;

   Vector< double, Devices::Host > host_u( 100000 );

   host_u = 1.0;

   timer.start();

   double result = maskAndReduce( host_u );

   timer.stop();

   std::cout << "Host tesult is:" << result << ". It took " << timer.getRealTime() << "seconds." << std::endl;

#ifdef HAVE_CUDA

   Vector< double, Devices::Cuda > cuda_u( 100000 );

   cuda_u = 1.0;

   timer.reset();

   timer.start();

   result = maskAndReduce( cuda_u );

   timer.stop();

   std::cout << "CUDA result is:" << result << ". It took " << timer.getRealTime() << "seconds." << std::endl;

#endif

   return EXIT_SUCCESS;

}

Documentation/Tutorials/Reduction/MaskAndReduceExample-2.cu

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MaskAndReduceExample-2.cpp
 
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