Commit ad664515 authored by Jakub Klinkovský's avatar Jakub Klinkovský
Browse files

Added MultireductionTest

parent c6391559

src/UnitTests/Containers/CMakeLists.txt

+15 −0
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@@ -66,6 +66,20 @@ ELSE( BUILD_CUDA ) 
                              tnl )

ENDIF( BUILD_CUDA )



IF( BUILD_CUDA )

   CUDA_ADD_EXECUTABLE( MultireductionTest MultireductionTest.cu

                        OPTIONS ${CXX_TESTS_FLAGS} )

   TARGET_LINK_LIBRARIES( MultireductionTest

                              ${GTEST_BOTH_LIBRARIES}

                              tnl )

ELSE(  BUILD_CUDA )

   ADD_EXECUTABLE( MultireductionTest MultireductionTest.cpp )

   TARGET_COMPILE_OPTIONS( MultireductionTest PRIVATE ${CXX_TESTS_FLAGS} )

   TARGET_LINK_LIBRARIES( MultireductionTest

                              ${GTEST_BOTH_LIBRARIES}

                              tnl )

ENDIF( BUILD_CUDA )



ADD_EXECUTABLE( StaticVectorTest StaticVectorTest.cpp )

TARGET_COMPILE_OPTIONS( StaticVectorTest PRIVATE ${CXX_TESTS_FLAGS} )

TARGET_LINK_LIBRARIES( StaticVectorTest
@@ -93,6 +107,7 @@ ADD_TEST( ArrayTest ${EXECUTABLE_OUTPUT_PATH}/ArrayTest${CMAKE_EXECUTABLE_SUFFIX 
ADD_TEST( ArrayViewTest ${EXECUTABLE_OUTPUT_PATH}/ArrayViewTest${CMAKE_EXECUTABLE_SUFFIX} )

ADD_TEST( StaticArrayTest ${EXECUTABLE_OUTPUT_PATH}/StaticArrayTest${CMAKE_EXECUTABLE_SUFFIX} )

ADD_TEST( VectorTest ${EXECUTABLE_OUTPUT_PATH}/VectorTest${CMAKE_EXECUTABLE_SUFFIX} )

ADD_TEST( MultireductionTest ${EXECUTABLE_OUTPUT_PATH}/MultireductionTest${CMAKE_EXECUTABLE_SUFFIX} )

ADD_TEST( StaticVectorTest ${EXECUTABLE_OUTPUT_PATH}/StaticVectorTest${CMAKE_EXECUTABLE_SUFFIX} )

#ADD_TEST( MultiArrayTest ${EXECUTABLE_OUTPUT_PATH}/MultiArrayTest${CMAKE_EXECUTABLE_SUFFIX} )

src/UnitTests/Containers/MultireductionTest.cpp

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#include "MultireductionTest.h"

src/UnitTests/Containers/MultireductionTest.cu

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#include "MultireductionTest.h"

src/UnitTests/Containers/MultireductionTest.h

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/***************************************************************************

                          MultireductionTest.h  -  description

                             -------------------

    begin                : Oct 1, 2018

    copyright            : (C) 2018 by Tomas Oberhuber et al.

    email                : tomas.oberhuber@fjfi.cvut.cz

 ***************************************************************************/



/* See Copyright Notice in tnl/Copyright */



#pragma once



#ifdef HAVE_GTEST

#include "gtest/gtest.h"



#include <TNL/Containers/Vector.h>

#include <TNL/Containers/VectorView.h>

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



using namespace TNL;

using namespace TNL::Containers;

using namespace TNL::Containers::Algorithms;



template< typename View >

void setLinearSequence( View& deviceVector )

{

   using HostVector = Containers::Vector< typename View::RealType, Devices::Host, typename View::IndexType >;

   HostVector a;

   a.setLike( deviceVector );

   for( int i = 0; i < a.getSize(); i++ )

      a[ i ] = i;

   deviceVector = a;

}



template< typename View >

void setNegativeLinearSequence( View& deviceVector )

{

   using HostVector = Containers::Vector< typename View::RealType, Devices::Host, typename View::IndexType >;

   HostVector a;

   a.setLike( deviceVector );

   for( int i = 0; i < a.getSize(); i++ )

      a[ i ] = -i;

   deviceVector = a;

}



// test fixture for typed tests

template< typename Vector >

class MultireductionTest : public ::testing::Test

{

protected:

   using DeviceVector = Vector;

   using DeviceView = VectorView< typename Vector::RealType, typename Vector::DeviceType, typename Vector::IndexType >;

   using HostVector = typename DeviceVector::HostType;

   using HostView = typename DeviceView::HostType;



   // should be small enough to have fast tests, but larger than minGPUReductionDataSize

   // and large enough to require multiple CUDA blocks for reduction

   static constexpr int size = 5000;



   // number of vectors which are reduced together

   static constexpr int n = 4;



   DeviceVector V;

   DeviceVector y;

   HostVector result;



   MultireductionTest()

   {

      V.setSize( size * n );

      y.setSize( size );

      result.setSize( n );



      for( int i = 0; i < n; i++ ) {

         DeviceView v( &V[ i * size ], size );

         if( i % 2 == 0 )

            setLinearSequence( v );

         else

            setNegativeLinearSequence( v );

      }

      y.setValue( 1 );

   }

};



// types for which MultireductionTest is instantiated

using VectorTypes = ::testing::Types<

   Vector< int,   Devices::Host >,

   Vector< float, Devices::Host >

#ifdef HAVE_CUDA

   ,

   Vector< int,   Devices::Cuda >,

   Vector< float, Devices::Cuda >

#endif

>;



TYPED_TEST_CASE( MultireductionTest, VectorTypes );



TYPED_TEST( MultireductionTest, scalarProduct )

{

   using RealType = typename TestFixture::DeviceVector::RealType;

   using DeviceType = typename TestFixture::DeviceVector::DeviceType;



   ParallelReductionScalarProduct< RealType, RealType > scalarProduct;

   Multireduction< DeviceType >::reduce

               ( scalarProduct,

                 this->n,

                 this->size,

                 this->V.getData(),

                 this->size,

                 this->y.getData(),

                 this->result.getData() );



   for( int i = 0; i < this->n; i++ ) {

      if( i % 2 == 0 )

         EXPECT_EQ( this->result[ i ], 0.5 * this->size * ( this->size - 1 ) );

      else

         EXPECT_EQ( this->result[ i ], - 0.5 * this->size * ( this->size - 1 ) );

   }

}



#endif // HAVE_GTEST





#include "../GtestMissingError.h"

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

{

#ifdef HAVE_GTEST

   ::testing::InitGoogleTest( &argc, argv );

   return RUN_ALL_TESTS();

#else

   throw GtestMissingError();

#endif

}

src/UnitTests/Containers/VectorTest.h

+1 −1
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@@ -23,8 +23,8 @@ 


using namespace TNL;

using namespace TNL::Containers;

using namespace TNL::Arithmetics; 

using namespace TNL::Containers::Algorithms;

using namespace TNL::Arithmetics;



// should be small enough to have fast tests, but larger than minGPUReductionDataSize

// and large enough to require multiple CUDA blocks for reduction