Added example on getLinearSolver and getPreconditioner.

   IterativeLinearSolverWithMonitorExample

   IterativeLinearSolverWithTimerExample

   IterativeLinearSolverWithPreconditionerExample

   IterativeLinearSolverWithRuntimeTypesExample

)

if( BUILD_CUDA )

#include <iostream>

#include <memory>

#include <TNL/Algorithms/ParallelFor.h>

#include <TNL/Matrices/SparseMatrix.h>

#include <TNL/Devices/Host.h>

#include <TNL/Devices/Cuda.h>

#include <TNL/Solvers/LinearSolverTypeResolver.h>

template< typename Device >

void iterativeLinearSolverExample()

{

   /***

    * Set the following matrix (dots represent zero matrix elements):

    *

    *   /  2.5 -1    .    .    .   \

    *   | -1    2.5 -1    .    .   |

    *   |  .   -1    2.5 -1.   .   |

    *   |  .    .   -1    2.5 -1   |

    *   \  .    .    .   -1    2.5 /

    */

   using MatrixType = TNL::Matrices::SparseMatrix< double, Device >;

   using Vector = TNL::Containers::Vector< double, Device >;

   const int size( 5 );

   auto matrix_ptr = std::make_shared< MatrixType >();

   matrix_ptr->setDimensions( size, size );

   matrix_ptr->setRowCapacities( Vector( { 2, 3, 3, 3, 2 } ) );

   auto f = [=] __cuda_callable__ ( typename MatrixType::RowView& row ) mutable {

      const int rowIdx = row.getRowIndex();

      if( rowIdx == 0 )

      {

         row.setElement( 0, rowIdx,    2.5 );    // diagonal element

         row.setElement( 1, rowIdx+1, -1 );      // element above the diagonal

      }

      else if( rowIdx == size - 1 )

      {

         row.setElement( 0, rowIdx-1, -1.0 );    // element below the diagonal

         row.setElement( 1, rowIdx,    2.5 );    // diagonal element

      }

      else

      {

         row.setElement( 0, rowIdx-1, -1.0 );    // element below the diagonal

         row.setElement( 1, rowIdx,    2.5 );    // diagonal element

         row.setElement( 2, rowIdx+1, -1.0 );    // element above the diagonal

      }

   };

   /***

    * Set the matrix elements.

    */

   matrix_ptr->forAllRows( f );

   std::cout << *matrix_ptr << std::endl;

   /***

    * Set the right-hand side vector.

    */

   Vector x( size, 1.0 );

   Vector b( size );

   matrix_ptr->vectorProduct( x, b );

   x = 0.0;

   std::cout << "Vector b = " << b << std::endl;

   /***

    * Solve the linear system using diagonal (Jacobi) preconditioner.

    */

   auto solver_ptr = TNL::Solvers::getLinearSolver< MatrixType >( "tfqmr" );

   auto preconditioner_ptr = TNL::Solvers::getPreconditioner< MatrixType >( "diagonal");

   preconditioner_ptr->update( matrix_ptr );

   solver_ptr->setMatrix( matrix_ptr );

   solver_ptr->setPreconditioner( preconditioner_ptr );

   solver_ptr->solve( b, x );

   std::cout << "Vector x = " << x << std::endl;

}

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

{

   std::cout << "Solving linear system on host: " << std::endl;

   iterativeLinearSolverExample< TNL::Devices::Sequential >();

#ifdef HAVE_CUDA

   std::cout << "Solving linear system on CUDA device: " << std::endl;

   iterativeLinearSolverExample< TNL::Devices::Cuda >();

#endif

}

IterativeLinearSolverWithRuntimeTypesExample.cpp

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