Commit a556f79e authored by Jakub Klinkovský's avatar Jakub Klinkovský
Browse files

Removed HostType and CudaType aliases in containers, matrices and grids 

They are not suitable for more than 2 devices/execution types; their design
breaks the Open-Closed Principle. Instead, a type template "Self" was
created, which allows to change any template parameter.
parent d81d168e

src/Benchmarks/DistSpMV/tnl-benchmark-distributed-spmv.h

+4 −4
Original line number Diff line number Diff line
@@ -73,8 +73,8 @@ benchmarkSpmvCuda( Benchmark& benchmark, 
{

   using RealType = typename Matrix::RealType;

   using IndexType = typename Matrix::IndexType;

   using CudaMatrix = typename Matrix::CudaType;

   using CudaVector = typename Vector::CudaType;

   using CudaMatrix = typename Matrix::template Self< RealType, Devices::Cuda >;

   using CudaVector = typename Vector::template Self< typename Vector::RealType, Devices::Cuda >;



   CudaVector cuda_x;

   cuda_x = x;
@@ -125,8 +125,8 @@ benchmarkDistributedSpmvCuda( Benchmark& benchmark, 
{

   using RealType = typename Matrix::RealType;

   using IndexType = typename Matrix::IndexType;

   using CudaMatrix = typename Matrix::CudaType;

   using CudaVector = typename Vector::CudaType;

   using CudaMatrix = typename Matrix::template Self< RealType, Devices::Cuda >;

   using CudaVector = typename Vector::template Self< typename Vector::RealType, Devices::Cuda >;



   CudaVector cuda_x;

   cuda_x = x;

src/Benchmarks/LinearSolvers/tnl-benchmark-linear-solvers.h

+6 −4
Original line number Diff line number Diff line
@@ -119,8 +119,8 @@ benchmarkIterativeSolvers( Benchmark& benchmark, 
                           const Vector& b )

{

#ifdef HAVE_CUDA

   using CudaMatrix = typename Matrix::CudaType;

   using CudaVector = typename Vector::CudaType;

   using CudaMatrix = typename Matrix::template Self< typename Matrix::RealType, Devices::Cuda >;

   using CudaVector = typename Vector::template Self< typename Vector::RealType, Devices::Cuda >;



   CudaVector cuda_x0, cuda_b;

   cuda_x0 = x0;
@@ -461,9 +461,11 @@ struct LinearSolversBenchmark 
         SharedPointer< CSR > matrixCopy;

         Matrices::copySparseMatrix( *matrixCopy, *matrixPointer );



         SharedPointer< typename CSR::CudaType > cuda_matrixCopy;

         using CudaCSR = Matrices::CSR< RealType, Devices::Cuda, IndexType >;

         using CudaVector = typename VectorType::template Self< RealType, Devices::Cuda >;

         SharedPointer< CudaCSR > cuda_matrixCopy;

         *cuda_matrixCopy = *matrixCopy;

         typename VectorType::CudaType cuda_x0, cuda_b;

         CudaVector cuda_x0, cuda_b;

         cuda_x0.setLike( x0 );

         cuda_b.setLike( b );

         cuda_x0 = x0;

src/Benchmarks/NDArray/tnl-benchmark-ndarray-boundary.h

+2 −1
Original line number Diff line number Diff line
@@ -52,7 +52,8 @@ template< typename Array > 
void expect_eq( Array& a, Array& b )

{

   if( std::is_same< typename Array::DeviceType, TNL::Devices::Cuda >::value ) {

      typename Array::HostType a_host, b_host;

      using HostArray = typename Array::template Self< typename Array::ValueType, TNL::Devices::Host >;

      HostArray a_host, b_host;

      a_host = a;

      b_host = b;

      expect_eq_chunked( a_host, b_host );

src/Benchmarks/NDArray/tnl-benchmark-ndarray.h

+2 −1
Original line number Diff line number Diff line
@@ -54,7 +54,8 @@ template< typename Array > 
void expect_eq( Array& a, Array& b )

{

   if( std::is_same< typename Array::DeviceType, TNL::Devices::Cuda >::value ) {

      typename Array::HostType a_host, b_host;

      using HostArray = typename Array::template Self< typename Array::ValueType, TNL::Devices::Host >;

      HostArray a_host, b_host;

      a_host = a;

      b_host = b;

      expect_eq_chunked( a_host, b_host );

src/TNL/Containers/Array.h

+9 −11
Original line number Diff line number Diff line
@@ -73,7 +73,6 @@ template< typename Value, 
class Array

{

   public:



      /**

       * \brief Type of elements stored in this array.

       */
@@ -98,16 +97,6 @@ class Array 
       */

      using AllocatorType = Allocator;



      /**

       * \brief Defines the same array type but allocated on host (CPU).

       */

      using HostType = Array< Value, TNL::Devices::Host, Index >;



      /**

       * \brief Defines the same array type but allocated on CUDA device (GPU).

       */

      using CudaType = Array< Value, TNL::Devices::Cuda, Index >;



      /**

       * \brief Compatible ArrayView type.

       */
@@ -118,6 +107,15 @@ class Array 
       */

      using ConstViewType = ArrayView< std::add_const_t< Value >, Device, Index >;



      /**

       * \brief A template which allows to quickly obtain an \ref Array type with changed template parameters.

       */

      template< typename _Value,

                typename _Device = Device,

                typename _Index = Index,

                typename _Allocator = typename Allocators::Default< _Device >::template Allocator< _Value > >

      using Self = Array< _Value, _Device, _Index, _Allocator >;





      /**

       * \brief Constructs an empty array with zero size.