Splitting sparse-matrix vector product unit test into separate functions. (364fb421) · Commits · TNL / tnl-dev

src/UnitTests/Matrices/SparseMatrixVectorProductTest.h

+44 −2

Original line number	Diff line number	Diff line
		@@ -32,11 +32,53 @@ protected:

		TYPED_TEST_SUITE( MatrixTest, MatrixTypes);

		TYPED_TEST( MatrixTest, vectorProductTest )
		TYPED_TEST( MatrixTest, vectorProductTest_smallMatrix1 )
		{
		using MatrixType = typename TestFixture::MatrixType;

		test_VectorProduct< MatrixType >();
		test_VectorProduct_smallMatrix1< MatrixType >();
		}

		TYPED_TEST( MatrixTest, vectorProductTest_smallMatrix2 )
		{
		using MatrixType = typename TestFixture::MatrixType;

		test_VectorProduct_smallMatrix2< MatrixType >();
		}

		TYPED_TEST( MatrixTest, vectorProductTest_smallMatrix3 )
		{
		using MatrixType = typename TestFixture::MatrixType;

		test_VectorProduct_smallMatrix3< MatrixType >();
		}

		TYPED_TEST( MatrixTest, vectorProductTest_mediumSizeMatrix1 )
		{
		using MatrixType = typename TestFixture::MatrixType;

		test_VectorProduct_mediumSizeMatrix1< MatrixType >();
		}

		TYPED_TEST( MatrixTest, vectorProductTest_mediumSizeMatrix2 )
		{
		using MatrixType = typename TestFixture::MatrixType;

		test_VectorProduct_mediumSizeMatrix2< MatrixType >();
		}

		TYPED_TEST( MatrixTest, vectorProductTest_largeMatrix )
		{
		using MatrixType = typename TestFixture::MatrixType;

		test_VectorProduct_largeMatrix< MatrixType >();
		}

		TYPED_TEST( MatrixTest, vectorProductTest_longRowsMatrix )
		{
		using MatrixType = typename TestFixture::MatrixType;

		test_VectorProduct_longRowsMatrix< MatrixType >();
		}

		#endif

src/UnitTests/Matrices/SparseMatrixVectorProductTest.hpp

+78 −16

Original line number	Diff line number	Diff line
		@@ -25,7 +25,7 @@
		#include <gtest/gtest.h>

		template< typename Matrix >
		void test_VectorProduct()
		void test_VectorProduct_smallMatrix1()
		{
		using RealType = typename Matrix::RealType;
		using DeviceType = typename Matrix::DeviceType;
		@@ -75,6 +75,15 @@ void test_VectorProduct()
		EXPECT_EQ( outVector_1.getElement( 1 ), 10 );
		EXPECT_EQ( outVector_1.getElement( 2 ), 8 );
		EXPECT_EQ( outVector_1.getElement( 3 ), 10 );
		}

		template< typename Matrix >
		void test_VectorProduct_smallMatrix2()
		{
		using RealType = typename Matrix::RealType;
		using DeviceType = typename Matrix::DeviceType;
		using IndexType = typename Matrix::IndexType;
		using VectorType = TNL::Containers::Vector< RealType, DeviceType, IndexType >;

		/*
		* Sets up the following 4x4 sparse matrix:
		@@ -120,6 +129,15 @@ void test_VectorProduct()
		EXPECT_EQ( outVector_2.getElement( 1 ), 8 );
		EXPECT_EQ( outVector_2.getElement( 2 ), 36 );
		EXPECT_EQ( outVector_2.getElement( 3 ), 16 );
		}

		template< typename Matrix >
		void test_VectorProduct_smallMatrix3()
		{
		using RealType = typename Matrix::RealType;
		using DeviceType = typename Matrix::DeviceType;
		using IndexType = typename Matrix::IndexType;
		using VectorType = TNL::Containers::Vector< RealType, DeviceType, IndexType >;

		/*
		* Sets up the following 4x4 sparse matrix:
		@@ -166,6 +184,15 @@ void test_VectorProduct()
		EXPECT_EQ( outVector_3.getElement( 1 ), 30 );
		EXPECT_EQ( outVector_3.getElement( 2 ), 48 );
		EXPECT_EQ( outVector_3.getElement( 3 ), 66 );
		}

		template< typename Matrix >
		void test_VectorProduct_mediumSizeMatrix1()
		{
		using RealType = typename Matrix::RealType;
		using DeviceType = typename Matrix::DeviceType;
		using IndexType = typename Matrix::IndexType;
		using VectorType = TNL::Containers::Vector< RealType, DeviceType, IndexType >;

		/*
		* Sets up the following 8x8 sparse matrix:
		@@ -234,6 +261,15 @@ void test_VectorProduct()
		EXPECT_EQ( outVector_4.getElement( 5 ), 188 );
		EXPECT_EQ( outVector_4.getElement( 6 ), 280 );
		EXPECT_EQ( outVector_4.getElement( 7 ), 330 );
		}

		template< typename Matrix >
		void test_VectorProduct_mediumSizeMatrix2()
		{
		using RealType = typename Matrix::RealType;
		using DeviceType = typename Matrix::DeviceType;
		using IndexType = typename Matrix::IndexType;
		using VectorType = TNL::Containers::Vector< RealType, DeviceType, IndexType >;

		/*
		* Sets up the following 8x8 sparse matrix:
		@@ -307,6 +343,16 @@ void test_VectorProduct()
		EXPECT_EQ( outVector_5.getElement( 5 ), 224 );
		EXPECT_EQ( outVector_5.getElement( 6 ), 352 );
		EXPECT_EQ( outVector_5.getElement( 7 ), 520 );
		}


		template< typename Matrix >
		void test_VectorProduct_largeMatrix()
		{
		using RealType = typename Matrix::RealType;
		using DeviceType = typename Matrix::DeviceType;
		using IndexType = typename Matrix::IndexType;
		using VectorType = TNL::Containers::Vector< RealType, DeviceType, IndexType >;

		/////
		// Large test
		@@ -362,6 +408,15 @@ void test_VectorProduct()
		for( IndexType i = 0; i < rows; i++ )
		EXPECT_EQ( out.getElement( i ), ( i + 1 ) * ( i + 2 ) / 2 );
		}
		}

		template< typename Matrix >
		void test_VectorProduct_longRowsMatrix()
		{
		using RealType = typename Matrix::RealType;
		using DeviceType = typename Matrix::DeviceType;
		using IndexType = typename Matrix::IndexType;
		using VectorType = TNL::Containers::Vector< RealType, DeviceType, IndexType >;

		/**
		* Long row test
		@@ -372,22 +427,29 @@ void test_VectorProduct()
		if( ! std::is_same< typename Matrix::SegmentsViewType, ChunkedEllpackView_ >::value )
		{
		// TODO: Fix ChunkedEllpack for this test - seems that it allocates too much memory
		const int columns = 3000;
		const int rows = 1;
		for( auto columns : { 64, 65, 128, 129, 256, 257, 512, 513, 1024, 1025, 2048, 2049, 3000 } )
		{
		//std::cerr << "Long-rows-matrix-test: columns = " << columns << std::endl;
		//const int columns = 3000;
		const int rows = 33;
		Matrix m3( rows, columns );
		TNL::Containers::Vector< IndexType, DeviceType, IndexType > rowsCapacities( rows );
		rowsCapacities = columns;
		m3.setRowCapacities( rowsCapacities );
		auto f = [] __cuda_callable__ ( IndexType row, IndexType localIdx, IndexType& column, RealType& value, bool& compute ) {
		column = localIdx;
		value = localIdx + 1;
		value = localIdx + row;
		};
		m3.forAllElements( f );
		TNL::Containers::Vector< double, DeviceType, IndexType > in( columns, 1.0 ), out( rows, 0.0 );
		m3.vectorProduct( in, out );
		EXPECT_EQ( out.getElement( 0 ), ( double ) columns * ( double ) (columns + 1 ) / 2.0 );
		for( IndexType rowIdx = 0; rowIdx < rows; rowIdx++ )
		{
		//std::cerr << "Long-rows-matrix-test: rowIndex = " << rowIdx << std::endl;
		EXPECT_EQ( out.getElement( rowIdx ), ( double ) columns * ( double ) (columns - 1 ) / 2.0 + columns * rowIdx );
		}
		}
		}
		}


		#endif