Commit 1ec0be26 authored by Jakub Klinkovský's avatar Jakub Klinkovský
Browse files

Merge branch 'cineca/solvers' into 'develop' 

Decoupling linear solvers from PDE solvers

See merge request mmg/tnl-dev!5
parents 5764cc28 9207dcb1

src/Python/pytnl/tnl/SparseMatrix.h

+1 −1
Original line number Diff line number Diff line
@@ -99,7 +99,7 @@ void export_Matrix( py::module & m, const char* name ) 
        // TODO: these two don't work

        //.def("addMatrix",           &Matrix::addMatrix)

        //.def("getTransposition",    &Matrix::getTransposition)

        .def("performSORIteration", &Matrix::template performSORIteration< VectorType >)

        .def("performSORIteration", &Matrix::template performSORIteration< VectorType, VectorType >)

//        .def("assign",              &Matrix::operator=)

        .def("assign", []( Matrix& matrix, const Matrix& other ) -> Matrix& {

                return matrix = other;

src/TNL/Containers/Algorithms/ArrayOperations.h

+2 −4
Original line number Diff line number Diff line
@@ -39,7 +39,7 @@ class ArrayOperations< Devices::Host > 
                                    const Element& value );



      template< typename Element >

      static Element getMemoryElement( Element* data );

      static Element getMemoryElement( const Element* data );



      template< typename Element, typename Index >

      static bool setMemory( Element* data,
@@ -86,12 +86,10 @@ class ArrayOperations< Devices::Cuda > 
      static void freeMemory( Element* data );



      template< typename Element >

      __cuda_callable__

      static void setMemoryElement( Element* data,

                                    const Element& value );



      template< typename Element >

      __cuda_callable__

      static Element getMemoryElement( const Element* data );



      template< typename Element, typename Index >

src/TNL/Containers/Algorithms/ArrayOperationsCuda_impl.h

+2 −10
Original line number Diff line number Diff line
@@ -60,32 +60,24 @@ freeMemory( Element* data ) 
}



template< typename Element >

__cuda_callable__ void

void

ArrayOperations< Devices::Cuda >::

setMemoryElement( Element* data,

                  const Element& value )

{

   TNL_ASSERT_TRUE( data, "Attempted to set data through a nullptr." );

#ifdef __CUDAARCH__

   *data = value;

#else   

   ArrayOperations< Devices::Cuda >::setMemory( data, value, 1 );

#endif   

}



template< typename Element >

__cuda_callable__ Element

Element

ArrayOperations< Devices::Cuda >::

getMemoryElement( const Element* data )

{

   TNL_ASSERT_TRUE( data, "Attempted to get data through a nullptr." );

#ifdef __CUDAARCH__

   return *data;

#else   

   Element result;

   ArrayOperations< Devices::Host, Devices::Cuda >::copyMemory< Element, Element, int >( &result, data, 1 );

   return result;

#endif   

}

src/TNL/Containers/Algorithms/ArrayOperationsHost_impl.h

+3 −3
Original line number Diff line number Diff line
@@ -51,15 +51,15 @@ setMemoryElement( Element* data, 
                  const Element& value )

{

   *data = value;

};

}



template< typename Element >

Element

ArrayOperations< Devices::Host >::

getMemoryElement( Element* data )

getMemoryElement( const Element* data )

{

   return *data;

};

}



template< typename Element, typename Index >

bool

src/TNL/Containers/Algorithms/Reduction_impl.h

+2 −2
Original line number Diff line number Diff line
@@ -69,12 +69,12 @@ reduce( Operation& operation, 
    */

   if( can_reduce_all_on_host && size <= Reduction_minGpuDataSize )

   {

      DataType1 hostArray1[ Reduction_minGpuDataSize ];

      typename std::remove_const< DataType1 >::type hostArray1[ Reduction_minGpuDataSize ];

      if( ! ArrayOperations< Devices::Host, Devices::Cuda >::copyMemory( hostArray1, deviceInput1, size ) )

         return false;

      if( deviceInput2 ) {

         using _DT2 = typename std::conditional< std::is_same< DataType2, void >::value, DataType1, DataType2 >::type;

         _DT2 hostArray2[ Reduction_minGpuDataSize ];

         typename std::remove_const< _DT2 >::type hostArray2[ Reduction_minGpuDataSize ];

         if( ! ArrayOperations< Devices::Host, Devices::Cuda >::copyMemory( hostArray2, (_DT2*) deviceInput2, size ) )

            return false;

         return Reduction< Devices::Host >::reduce( operation, size, hostArray1, hostArray2, result );