TNL::Matrices Namespace Reference

Namespace for different matrix types. More...

Namespaces
namespace	Sandbox
	Namespace for sandbox matrices.

Classes
class	DenseMatrix
	Implementation of dense matrix, i.e. matrix storing explicitly all of its elements including zeros. More...
class	DenseMatrixElement
	Accessor for dense matrix elements. More...
class	DenseMatrixRowView
	RowView is a simple structure for accessing rows of dense matrix. More...
class	DenseMatrixView
	Implementation of dense matrix view. More...
class	DistributedMatrix
struct	GeneralMatrix
	General non-symmetric matrix type. More...
class	GinkgoOperator
	Wraps a general TNL matrix as a Ginkgo LinOp. More...
class	HypreCSRMatrix
	Wrapper for Hypre's sequential CSR matrix. More...
class	HypreParCSRMatrix
	Wrapper for Hypre's sequential CSR matrix. More...
class	LambdaMatrix
	"Matrix-free matrix" based on lambda functions. More...
class	LambdaMatrixElement
	Accessor for elements of lambda matrix. More...
struct	LambdaMatrixFactory
	Helper class for creating instances of LambdaMatrix. More...
class	LambdaMatrixRowView
	RowView is a simple structure for accessing rows of Lambda matrix. More...
class	LambdaMatrixRowViewIterator
class	Matrix
	Base class for other matrix types. More...
struct	MatrixInfo
class	MatrixOperations
class	MatrixOperations< Devices::Cuda >
class	MatrixReader
	Helper class for importing of matrices from different input formats. More...
class	MatrixRowViewIterator
class	MatrixSetter
class	MatrixSetterTraverserUserData
struct	MatrixType
	Structure for specifying type of sparse matrix. More...
class	MatrixView
	Base class for other matrix types views. More...
class	MatrixWriter
	Helper class for exporting of matrices to different output formats. More...
class	MultidiagonalMatrix
	Implementation of sparse multidiagonal matrix. More...
class	MultidiagonalMatrixElement
	Accessor for multidiagonal matrix elements. More...
class	MultidiagonalMatrixRowView
	RowView is a simple structure for accessing rows of multidiagonal matrix. More...
class	MultidiagonalMatrixView
	Implementation of sparse multidiagonal matrix. More...
class	SparseMatrix
	Implementation of sparse matrix, i.e. matrix storing only non-zero elements. More...
class	SparseMatrixElement
	Accessor for sparse matrix elements. More...
class	SparseMatrixRowView
	RowView is a simple structure for accessing rows of sparse matrix. More...
class	SparseMatrixView
	Implementation of sparse matrix view. More...
class	StaticMatrix
struct	SymmetricMatrix
	Symmetric matrix type. More...
class	TridiagonalMatrix
	Implementation of sparse tridiagonal matrix. More...
class	TridiagonalMatrixRowView
	RowView is a simple structure for accessing rows of tridiagonal matrix. More...
class	TridiagonalMatrixView
	Implementation of sparse tridiagonal matrix. More...

Functions
template<typename Matrix , typename InVector , typename OutVector >
__global__ void	ColumnMajorDenseMatrixViewVectorMultiplicationKernel (const Matrix matrix, const InVector inVector, OutVector outVector, const int begin, const int end, int gridIdx)
template<typename Matrix , typename AdjacencyMatrix >
void	copyAdjacencyStructure (const Matrix &A, AdjacencyMatrix &B, bool has_symmetric_pattern=false, bool ignore_diagonal=true)
template<typename Matrix1 , typename Matrix2 >
void	copySparseMatrix (Matrix1 &A, const Matrix2 &B)
template<typename Matrix1 , typename Matrix2 >
std::enable_if< std::is_same< typenameMatrix1::DeviceType, typenameMatrix2::DeviceType >::value >::type	copySparseMatrix_impl (Matrix1 &A, const Matrix2 &B)
template<typename Matrix1 , typename Matrix2 >
std::enable_if<!std::is_same< typenameMatrix1::DeviceType, typenameMatrix2::DeviceType >::value &&std::is_same< typenameMatrix2::DeviceType, Devices::Host >::value >::type	copySparseMatrix_impl (Matrix1 &A, const Matrix2 &B)
template<typename Matrix1 , typename Matrix2 >
std::enable_if<!std::is_same< typenameMatrix1::DeviceType, typenameMatrix2::DeviceType >::value &&std::is_same< typenameMatrix2::DeviceType, Devices::Cuda >::value >::type	copySparseMatrix_impl (Matrix1 &A, const Matrix2 &B)
template<int tileDim, int tileRowBlockSize, typename ResultMatrix , typename Matrix1 , typename Matrix2 >
__global__ void	DenseMatrixProductKernel (ResultMatrix resultMatrix, const Matrix1 matrixA, const Matrix2 matrixB, const typename ResultMatrix::RealType matrixMultiplicator, const typename ResultMatrix::IndexType gridIdx_x, const typename ResultMatrix::IndexType gridIdx_y)
template<int tileDim, int tileRowBlockSize, typename OutputMatrix , typename InputMatrix , typename Real , typename Index >
__global__ void	DenseTranspositionAlignedKernel (OutputMatrix resultMatrix, const InputMatrix inputMatrix, const Real matrixMultiplicator, const Index gridIdx_x, const Index gridIdx_y)
template<int tileDim, int tileRowBlockSize, typename OutputMatrix , typename InputMatrix , typename Real , typename Index >
__global__ void	DenseTranspositionNonAlignedKernel (OutputMatrix resultMatrix, const InputMatrix inputMatrix, const Real matrixMultiplicator, const Index gridIdx_x, const Index gridIdx_y)
template<typename RealType , typename IndexType >
__global__ void	GeamCudaKernel (const IndexType m, const IndexType n, const RealType alpha, const RealType *A, const IndexType lda, const RealType beta, const RealType *B, const IndexType ldb, RealType *C, const IndexType ldc)
template<typename RealType , typename IndexType >
__global__ void	GemvCudaKernel (const IndexType m, const IndexType n, const RealType alpha, const RealType *A, const IndexType lda, const RealType *x, const RealType beta, RealType *y)
template<typename Matrix >
auto	getGinkgoMatrixCsr (std::shared_ptr< const gko::Executor > exec, Matrix &matrix) -> std::unique_ptr< gko::matrix::Csr< typename Matrix::RealType, typename Matrix::IndexType > >
	Converts any TNL sparse matrix to a Ginkgo Csr matrix. More...
template<typename Matrix >
auto	getGinkgoMatrixCsrView (std::shared_ptr< const gko::Executor > exec, Matrix &matrix) -> std::unique_ptr< gko::matrix::Csr< typename Matrix::RealType, typename Matrix::IndexType > >
	Creates a Ginkgo Csr matrix view from a TNL CSR matrix. More...
template<typename InMatrixView , typename OutMatrixView , typename Real , typename Index >
__global__ void	MultidiagonalMatrixTranspositionCudaKernel (const InMatrixView inMatrix, OutMatrixView outMatrix, const Real matrixMultiplicator, const Index gridIdx)
template<typename Real , typename Device , typename Index , typename Real_ , typename Device_ , typename Index_ , ElementsOrganization Organization, typename RealAllocator >
bool	operator!= (const DenseMatrixView< Real, Device, Index, Organization > &leftMatrix, const DenseMatrix< Real_, Device_, Index_, Organization, RealAllocator > &rightMatrix)
	Comparison operator with another dense matrix view. More...
template<typename Real , typename Device , typename Index , ElementsOrganization Organization, typename RealAllocator >
std::ostream &	operator<< (std::ostream &str, const DenseMatrix< Real, Device, Index, Organization, RealAllocator > &matrix)
	Insertion operator for dense matrix and output stream. More...
template<typename MatrixElementsLambda , typename CompressedRowLengthsLambda , typename Real , typename Device , typename Index >
std::ostream &	operator<< (std::ostream &str, const LambdaMatrix< MatrixElementsLambda, CompressedRowLengthsLambda, Real, Device, Index > &matrix)
	Insertion operator for lambda matrix and output stream. More...
template<typename MatrixElementsLambda , typename CompressedRowLengthsLambda , typename Real , typename Index >
std::ostream &	operator<< (std::ostream &str, const LambdaMatrixRowView< MatrixElementsLambda, CompressedRowLengthsLambda, Real, Index > &row)
	Insertion operator for a Lambda matrix row. More...
template<typename Real , typename Device , typename Index >
std::ostream &	operator<< (std::ostream &str, const Matrix< Real, Device, Index > &matrix)
	Overloaded insertion operator for printing a matrix to output stream. More...
template<typename Real , typename Device , typename Index >
std::ostream &	operator<< (std::ostream &str, const MatrixView< Real, Device, Index > &matrix)
	Overloaded insertion operator for printing a matrix to output stream. More...
template<typename SegmentView , typename ValuesView , typename ColumnsIndexesView >
std::ostream &	operator<< (std::ostream &str, const SparseMatrixRowView< SegmentView, ValuesView, ColumnsIndexesView > &row)
	Insertion operator for a sparse matrix row. More...
template<typename Real , typename Device , typename Index , typename Real_ , typename Device_ , typename Index_ , ElementsOrganization Organization, typename RealAllocator >
bool	operator== (const DenseMatrixView< Real, Device, Index, Organization > &leftMatrix, const DenseMatrix< Real_, Device_, Index_, Organization, RealAllocator > &rightMatrix)
	Comparison operator with another dense matrix view. More...
template<typename Matrix , typename PermutationArray >
void	permuteMatrixColumns (Matrix &matrix, const PermutationArray &iperm)
template<typename Matrix , typename PermutationArray >
void	permuteMatrixRows (Matrix &matrix, const PermutationArray &perm)
template<typename Array1 , typename Array2 , typename PermutationArray >
void	reorderArray (const Array1 &src, Array2 &dest, const PermutationArray &perm)
template<typename Matrix1 , typename Matrix2 , typename PermutationArray >
void	reorderSparseMatrix (const Matrix1 &matrix1, Matrix2 &matrix2, const PermutationArray &perm, const PermutationArray &iperm)
template<typename Matrix , typename InVector , typename OutVector >
__global__ void	RowMajorDenseMatrixViewVectorMultiplicationKernel (const Matrix matrix, const InVector inVector, OutVector outVector, const int first, const int last, int gridIdx)
template<typename Matrix1 , typename Matrix2 >
__global__ void	SparseMatrixCopyKernel (Matrix1 *A, const Matrix2 *B, const typename Matrix2::IndexType *rowLengths, typename Matrix2::IndexType rows)
template<typename Vector , typename Matrix >
__global__ void	SparseMatrixSetRowLengthsVectorKernel (Vector *rowLengths, const Matrix *matrix, typename Matrix::IndexType rows, typename Matrix::IndexType cols)
template<typename InMatrixView , typename OutMatrixView , typename Real , typename Index >
__global__ void	TridiagonalMatrixTranspositionCudaKernel (const InMatrixView inMatrix, OutMatrixView outMatrix, Real matrixMultiplicator, Index gridIdx)
template<int BlockSize, int ThreadsPerRow, typename Matrix , typename InVector , typename OutVector >
__global__ void	VectorColumnMajorDenseMatrixViewVectorMultiplicationKernel (const Matrix matrix, const InVector inVector, OutVector outVector, const int begin, const int end, int gridIdx)
template<typename Device , typename Real , typename Index >
SparseMatrixView< Real, Device, Index, GeneralMatrix, Algorithms::Segments::CSRViewDefault >	wrapCSRMatrix (const Index &rows, const Index &columns, Index *rowPointers, Real *values, Index *columnIndexes)
	Function for wrapping of arrays defining CSR format into a sparse matrix view. More...
template<typename Device , typename Real , typename Index , ElementsOrganization Organization = Algorithms::Segments::DefaultElementsOrganization< Device >::getOrganization()>
DenseMatrixView< Real, Device, Index, Organization >	wrapDenseMatrix (const Index &rows, const Index &columns, Real *values)
	Function for wrapping an array of values into a dense matrix view. More...
template<typename Device , ElementsOrganization Organization, typename Real , typename Index , int Alignment = 1>
auto	wrapEllpackMatrix (const Index rows, const Index columns, const Index nonzerosPerRow, Real *values, Index *columnIndexes) -> decltype(EllpackMatrixWrapper< Device, Organization, Real, Index, Alignment >::wrap(rows, columns, nonzerosPerRow, values, columnIndexes))
	Function for wrapping of arrays defining Ellpack format into a sparse matrix view. More...

Detailed Description

Namespace for different matrix types.

Namespace for different matrix formats.

Namespace for matrix formats.

Function Documentation

operator!=()

template<typename Real , typename Device , typename Index , typename Real_ , typename Device_ , typename Index_ , ElementsOrganization Organization, typename RealAllocator >

bool TNL::Matrices::operator!=	(	const DenseMatrixView< Real, Device, Index, Organization > &	leftMatrix,
		const DenseMatrix< Real_, Device_, Index_, Organization, RealAllocator > &	rightMatrix
	)

Comparison operator with another dense matrix view.

Parameters

leftMatrix	is the left-hand side matrix view.
rightMatrix	is the right-hand side matrix.

Returns

false if the both matrices are is equal, true otherwise.

operator<<() [1/6]

template<typename Real , typename Device , typename Index , ElementsOrganization Organization, typename RealAllocator >

std::ostream & TNL::Matrices::operator<<	(	std::ostream &	str,
		const DenseMatrix< Real, Device, Index, Organization, RealAllocator > &	matrix
	)

Insertion operator for dense matrix and output stream.

Parameters

str	is the output stream.
matrix	is the dense matrix.

Returns

reference to the stream.

operator<<() [2/6]

template<typename MatrixElementsLambda , typename CompressedRowLengthsLambda , typename Real , typename Device , typename Index >

std::ostream & TNL::Matrices::operator<<	(	std::ostream &	str,
		const LambdaMatrix< MatrixElementsLambda, CompressedRowLengthsLambda, Real, Device, Index > &	matrix
	)

Insertion operator for lambda matrix and output stream.

Parameters

str	is the output stream.
matrix	is the lambda matrix.

Returns

reference to the stream.

operator<<() [3/6]

template<typename MatrixElementsLambda , typename CompressedRowLengthsLambda , typename Real , typename Index >

std::ostream & TNL::Matrices::operator<<	(	std::ostream &	str,
		const LambdaMatrixRowView< MatrixElementsLambda, CompressedRowLengthsLambda, Real, Index > &	row
	)

Insertion operator for a Lambda matrix row.

Parameters

str	is an output stream.
row	is an input Lambda matrix row.

Returns

reference to the output stream.

operator<<() [4/6]

template<typename Real , typename Device , typename Index >

std::ostream & TNL::Matrices::operator<<	(	std::ostream &	str,
		const Matrix< Real, Device, Index > &	matrix
	)

Overloaded insertion operator for printing a matrix to output stream.

Template Parameters

Real	is a type of the matrix elements.
Device	is a device where the matrix is allocated.
Index	is a type used for the indexing of the matrix elements.

Parameters

str	is a output stream.
matrix	is the matrix to be printed.

Returns

a reference to the output stream std::ostream.

operator<<() [5/6]

template<typename Real , typename Device , typename Index >

std::ostream & TNL::Matrices::operator<<	(	std::ostream &	str,
		const MatrixView< Real, Device, Index > &	matrix
	)

Overloaded insertion operator for printing a matrix to output stream.

Template Parameters

Real	is a type of the matrix elements.
Device	is a device where the matrix is allocated.
Index	is a type used for the indexing of the matrix elements.

Parameters

str	is a output stream.
matrix	is the matrix to be printed.

Returns

a reference to the output stream std::ostream.

operator<<() [6/6]

template<typename SegmentView , typename ValuesView , typename ColumnsIndexesView >

std::ostream & TNL::Matrices::operator<<	(	std::ostream &	str,
		const SparseMatrixRowView< SegmentView, ValuesView, ColumnsIndexesView > &	row
	)

Insertion operator for a sparse matrix row.

Parameters

str	is an output stream.
row	is an input sparse matrix row.

Returns

reference to the output stream.

operator==()

template<typename Real , typename Device , typename Index , typename Real_ , typename Device_ , typename Index_ , ElementsOrganization Organization, typename RealAllocator >

bool TNL::Matrices::operator==	(	const DenseMatrixView< Real, Device, Index, Organization > &	leftMatrix,
		const DenseMatrix< Real_, Device_, Index_, Organization, RealAllocator > &	rightMatrix
	)

Comparison operator with another dense matrix view.

Parameters

leftMatrix	is the left-hand side matrix view.
rightMatrix	is the right-hand side matrix.

Returns

true if the both matrices are is equal, false otherwise.

VectorColumnMajorDenseMatrixViewVectorMultiplicationKernel()

template<int BlockSize, int ThreadsPerRow, typename Matrix , typename InVector , typename OutVector >

__global__ void TNL::Matrices::VectorColumnMajorDenseMatrixViewVectorMultiplicationKernel	(	const Matrix	matrix,
		const InVector	inVector,
		OutVector	outVector,
		const int	begin,
		const int	end,
		int	gridIdx
	)

The following kernel is an attempt to map more CUDA threads to one matrix row.

wrapCSRMatrix()

template<typename Device , typename Real , typename Index >

SparseMatrixView< Real, Device, Index, GeneralMatrix, Algorithms::Segments::CSRViewDefault > TNL::Matrices::wrapCSRMatrix	(	const Index &	rows,
		const Index &	columns,
		Index *	rowPointers,
		Real *	values,
		Index *	columnIndexes
	)

Function for wrapping of arrays defining CSR format into a sparse matrix view.

Template Parameters

Device	is a device on which the arrays are allocated.
Real	is a type of matrix elements values.
Index	is a type for matrix elements indexing.

Parameters

rows	is a number of matrix rows.
columns	is a number of matrix columns.
rowPointers	is an array holding row pointers of the CSR format ( ROW_INDEX here)
values	is an array with values of matrix elements ( V here)
columnIndexes	is an array with column indexes of matrix elements ( COL_INDEX here)

Returns

instance of SparseMatrixView with CSR format.

The size of array rowPointers must be equal to number of rows + 1. The last element of the array equals to the number of all nonzero matrix elements. The sizes of arrays values and columnIndexes must be equal to this number.

Example

#include <iostream>
#include <TNL/Matrices/DenseMatrix.h>
#include <TNL/Matrices/MatrixWrapping.h>
#include <TNL/Devices/Host.h>
#include <TNL/Devices/Cuda.h>
 
template< typename Device >
void wrapMatrixView()
{
   /***
    * Encode the following matrix to CSR format...
    *
    * /  1  2  0  0 \.
    * |  0  6  0  0 |
    * |  9  0  0  0 |
    * \  0  0 15 16 /
    */
   const int rows( 4 ), columns( 4 );
   TNL::Containers::Vector< double, Device > valuesVector     { 1, 2, 6, 9, 15, 16 };
   TNL::Containers::Vector< int, Device > columnIndexesVector { 0, 1, 1, 0,  2,  3 };
   TNL::Containers::Vector< int, Device > rowPointersVector   { 0, 2, 3, 4, 6 };
 
   double* values = valuesVector.getData();
   int* columnIndexes = columnIndexesVector.getData();
   int* rowPointers = rowPointersVector.getData();
 
   /***
    * Wrap the arrays `rowPointers, `values` and `columnIndexes` to sparse matrix view
    */
   auto matrix = TNL::Matrices::wrapCSRMatrix< Device >( rows, columns, rowPointers, values, columnIndexes );
 
   std::cout << "Matrix reads as: " << std::endl << matrix << std::endl;
}
 
int main( int argc, char* argv[] )
{
   std::cout << "Wraping matrix view on host: " << std::endl;
   wrapMatrixView< TNL::Devices::Host >();
 
#ifdef __CUDACC__
   std::cout << "Wraping matrix view on CUDA device: " << std::endl;
   wrapMatrixView< TNL::Devices::Cuda >();
#endif
}

Output

Wraping matrix view on host: 
Matrix reads as: 
Row: 0 ->     0:1       1:2   
Row: 1 ->     1:6   
Row: 2 ->     0:9   
Row: 3 ->     2:15      3:16  
 
Wraping matrix view on CUDA device: 
Matrix reads as: 
Row: 0 ->     0:1       1:2   
Row: 1 ->     1:6   
Row: 2 ->     0:9   
Row: 3 ->     2:15      3:16  
 

wrapDenseMatrix()

template<typename Device , typename Real , typename Index , ElementsOrganization Organization = Algorithms::Segments::DefaultElementsOrganization< Device >::getOrganization()>

DenseMatrixView< Real, Device, Index, Organization > TNL::Matrices::wrapDenseMatrix	(	const Index &	rows,
		const Index &	columns,
		Real *	values
	)

Function for wrapping an array of values into a dense matrix view.

Template Parameters

Device	is a device on which the array is allocated.
Real	is a type of array elements.
Index	is a type for indexing of matrix elements.
Organization	is matrix elements organization - see TNL::Algorithms::Segments::ElementsOrganization.

Parameters

rows	is a number of matrix rows.
columns	is a number of matrix columns.
values	is the array with matrix elements values.

Returns

instance of DenseMatrixView wrapping the array.

The array size must be equal to product of rows and columns. The dense matrix view does not deallocate the input array at the end of its lifespan.

Example

#include <iostream>
#include <TNL/Matrices/DenseMatrix.h>
#include <TNL/Matrices/MatrixWrapping.h>
#include <TNL/Devices/Host.h>
#include <TNL/Devices/Cuda.h>
 
template< typename Device >
void wrapMatrixView()
{
   const int rows( 3 ), columns( 4 );
   TNL::Containers::Vector< double, Device > valuesVector {
      1,  2,  3,  4,
      5,  6,  7,  8,
      9, 10, 11, 12 };
   double* values = valuesVector.getData();
 
   /***
    * Wrap the array `values` to dense matrix view
    */
   auto matrix = TNL::Matrices::wrapDenseMatrix< Device >( rows, columns, values );
   std::cout << "Matrix reads as: " << std::endl << matrix << std::endl;
}
 
int main( int argc, char* argv[] )
{
   std::cout << "Wraping matrix view on host: " << std::endl;
   wrapMatrixView< TNL::Devices::Host >();
 
#ifdef __CUDACC__
   std::cout << "Wraping matrix view on CUDA device: " << std::endl;
   wrapMatrixView< TNL::Devices::Cuda >();
#endif
}

Output

Wraping matrix view on host: 
Matrix reads as: 
Row: 0 ->     0:1       1:2       2:3       3:4   
Row: 1 ->     0:5       1:6       2:7       3:8   
Row: 2 ->     0:9       1:10      2:11      3:12  
Wraping matrix view on CUDA device: 
Matrix reads as: 
Row: 0 ->     0:1       1:4       2:7       3:10  
Row: 1 ->     0:2       1:5       2:8       3:11  
Row: 2 ->     0:3       1:6       2:9       3:12  

wrapEllpackMatrix()

template<typename Device , ElementsOrganization Organization, typename Real , typename Index , int Alignment = 1>

auto TNL::Matrices::wrapEllpackMatrix	(	const Index	rows,
		const Index	columns,
		const Index	nonzerosPerRow,
		Real *	values,
		Index *	columnIndexes
	)		-> decltype( EllpackMatrixWrapper< Device, Organization, Real, Index, Alignment >::wrap( rows, columns, nonzerosPerRow, values, columnIndexes ) )

Function for wrapping of arrays defining Ellpack format into a sparse matrix view.

This is to prevent from appearing in Doxygen documentation.

Template Parameters

Device	is a device on which the arrays are allocated.
Real	is a type of matrix elements values.
Index	is a type for matrix elements indexing.
Alignment	defines alignment of data. The number of matrix rows is rounded to a multiple of this number. It it usefull mainly for GPUs.

Parameters

rows	is a number of matrix rows.
columns	is a number of matrix columns.
nonzerosPerRow	is number of nonzero matrix elements in each row.
values	is an array with values of matrix elements.
columnIndexes	is an array with column indexes of matrix elements.

Returns

instance of SparseMatrixView with CSR format.

The sizes of arrays values and columnIndexes must be equal to rows * nonzerosPerRow. Use -1 as a column index for padding zeros.

Example

#include <iostream>
#include <TNL/Matrices/DenseMatrix.h>
#include <TNL/Matrices/MatrixWrapping.h>
#include <TNL/Devices/Host.h>
#include <TNL/Devices/Cuda.h>
 
template< typename Device >
void wrapMatrixView()
{
   /***
    * Encode the following matrix to Ellpack format...
    *
    * /  1  2  0  0 \.
    * |  0  6  0  0 |
    * |  9  0  0  0 |
    * \  0  0 15 16 /
    */
   const int rows( 4 ), columns( 4 );
   TNL::Containers::Vector< double, Device > valuesVector     { 1,  2,  6,  0,  9,  0, 15, 16 };
   TNL::Containers::Vector< int, Device > columnIndexesVector { 0,  1,  1, -1,  0, -1,  2,  3 };
 
   double* values = valuesVector.getData();
   int* columnIndexes = columnIndexesVector.getData();
 
   /***
    * Wrap the arrays `values` and `columnIndexes` to sparse matrix view
    */
   auto matrix = TNL::Matrices::wrapEllpackMatrix< Device, TNL::Algorithms::Segments::RowMajorOrder >( rows, columns, 2, values, columnIndexes );
 
   std::cout << "Matrix reads as: " << std::endl << matrix << std::endl;
}
 
int main( int argc, char* argv[] )
{
   std::cout << "Wraping matrix view on host: " << std::endl;
   wrapMatrixView< TNL::Devices::Host >();
 
#ifdef __CUDACC__
   std::cout << "Wraping matrix view on CUDA device: " << std::endl;
   wrapMatrixView< TNL::Devices::Cuda >();
#endif
}

Output

Wraping matrix view on host: 
Matrix reads as: 
Row: 0 ->     0:1       1:2   
Row: 1 ->     1:6   
Row: 2 ->     0:9   
Row: 3 ->     2:15      3:16  
 
Wraping matrix view on CUDA device: 
Matrix reads as: 
Row: 0 ->     0:1       1:2   
Row: 1 ->     1:6   
Row: 2 ->     0:9   
Row: 3 ->     2:15      3:16