Add SparseHalo creation function, match Halo constructor

cajita/src/Cajita_Halo.hpp

@@ -943,7 +943,7 @@ struct ArrayPackMemorySpace
 
 //---------------------------------------------------------------------------//
 /*!
-  \brief Array creation function.
+  \brief Halo creation function.
   \param pattern The pattern to build the halo from.
   \param width Must be less than or equal to the width of the array halo.
   \param arrays The arrays over which to build the halo.

cajita/src/Cajita_SparseHalo.hpp

@@ -43,7 +43,7 @@ namespace Experimental
   communicator and halo size. The arrays must also reside in the same memory
   space. These requirements are checked at construction.
 */
-template <class MemorySpace, class DataMembers, class EntityType,
+template <class MemorySpace, class DataTypes, class EntityType,
           std::size_t NumSpaceDim, unsigned long long cellBitsPerTileDim,
           typename Value = int, typename Key = uint64_t>
 class SparseHalo
@@ -71,7 +71,7 @@ class SparseHalo
     };
 
     //! data members in AoSoA structure
-    using aosoa_member_types = DataMembers;
+    using aosoa_member_types = DataTypes;
     //! AoSoA tuple type
     using tuple_type = Cabana::Tuple<aosoa_member_types>;
 
@@ -114,13 +114,11 @@ class SparseHalo
         \brief constructor
         \tparam LocalGridType local grid type
         \param pattern The halo pattern to use for halo communication
-        \param local_grid_ptr pointer to sparse local grid
-        \param comm MPI communicator
+        \param sparse_array Sparse array to communicate
     */
-    template <class LocalGridType>
+    template <class SparseArrayType>
     SparseHalo( halo_pattern_type pattern,
-                const std::shared_ptr<LocalGridType>& local_grid_ptr,
-                MPI_Comm comm )
+                const std::shared_ptr<SparseArrayType>& sparse_array )
         : _pattern( pattern )
     {
         // Function to get the local id of the neighbor.
@@ -151,17 +149,20 @@ class SparseHalo
             std::accumulate( soa_byte_array.begin(), soa_byte_array.end(), 0 ),
             static_cast<int>( sizeof( tuple_type ) ) );
 
+        // Get the local grid the array uses.
+        auto local_grid = sparse_array->layout().localGrid();
+
         // linear MPI rank ID of the current working rank
         _self_rank =
-            local_grid_ptr->neighborRank( std::array<int, 3>( { 0, 0, 0 } ) );
+            local_grid->neighborRank( std::array<int, 3>( { 0, 0, 0 } ) );
 
         // set the linear neighbor rank ID
         // set up correspondence between sending and receiving buffers
         auto neighbors = _pattern.getNeighbors();
         for ( const auto& n : neighbors )
         {
             // neighbor rank linear ID
-            int rank = local_grid_ptr->neighborRank( n );
+            int rank = local_grid->neighborRank( n );
 
             // if neighbor is valid
             if ( rank >= 0 )
@@ -176,10 +177,10 @@ class SparseHalo
                 _receive_tags.push_back( neighbor_id( flip_id( n ) ) );
 
                 // build communication data for owned entries
-                buildCommData( Own(), local_grid_ptr, n, _owned_buffers,
+                buildCommData( Own(), local_grid, n, _owned_buffers,
                                _owned_tile_steering, _owned_tile_spaces );
                 // build communication data for ghosted entries
-                buildCommData( Ghost(), local_grid_ptr, n, _ghosted_buffers,
+                buildCommData( Ghost(), local_grid, n, _ghosted_buffers,
                                _ghosted_tile_steering, _ghosted_tile_spaces );
 
                 auto& own_index_space = _owned_tile_spaces.back();
@@ -215,25 +216,24 @@ class SparseHalo
         \tparam DecompositionTag  decomposition tag type
         \tparam LocalGridType  sparse local grid type
         \param decomposition_tag tag to indicate if it's owned or ghosted halo
-        \param local_grid_ptr sparse local grid shared pointer
+        \param local_grid sparse local grid shared pointer
         \param nid neighbor local id (ijk in pattern)
         \param buffers buffer to be used to store communicated data
         \param steering steering to be used to guide communications
         \param spaces sparse tile index spaces
     */
     template <class DecompositionTag, class LocalGridType>
     void buildCommData( DecompositionTag decomposition_tag,
-                        const std::shared_ptr<LocalGridType>& local_grid_ptr,
+                        const std::shared_ptr<LocalGridType>& local_grid,
                         const std::array<int, num_space_dim>& nid,
                         std::vector<buffer_view>& buffers,
                         std::vector<steering_view>& steering,
                         std::vector<tile_index_space>& spaces )
     {
         // get the halo sparse tile index space sharsed with the neighbor
         spaces.push_back(
-            local_grid_ptr
-                ->template sharedTileIndexSpace<cell_bits_per_tile_dim>(
-                    decomposition_tag, entity_type(), nid ) );
+            local_grid->template sharedTileIndexSpace<cell_bits_per_tile_dim>(
+                decomposition_tag, entity_type(), nid ) );
         auto& index_space = spaces.back();
 
         // allocate the buffer to store shared data with given neighbor
@@ -251,10 +251,10 @@ class SparseHalo
     /*!
         \brief update tile index space according to current partition
         \tparam LocalGridType sparse local grid type
-        \param local_grid_ptr sparse local grid pointer
+        \param local_grid sparse local grid pointer
     */
     template <class LocalGridType>
-    void updateTileSpace( const std::shared_ptr<LocalGridType>& local_grid_ptr )
+    void updateTileSpace( const std::shared_ptr<LocalGridType>& local_grid )
     {
         // clear index space array first
         _owned_tile_spaces.clear();
@@ -267,19 +267,19 @@ class SparseHalo
             // get neighbor relative id
             auto& n = _valid_neighbor_ids[i];
             // get neighbor linear MPI rank ID
-            int rank = local_grid_ptr->neighborRank( n );
+            int rank = local_grid->neighborRank( n );
             // check if neighbor rank is valid
             // the neighbor id should always be valid (as all should be
             // well-prepared during construction/initialization)
             if ( rank == _neighbor_ranks[i] )
             {
                 // get shared tile index spcae from local grid
                 _owned_tile_spaces.push_back(
-                    local_grid_ptr
+                    local_grid
                         ->template sharedTileIndexSpace<cell_bits_per_tile_dim>(
                             Own(), entity_type(), n ) );
                 _ghosted_tile_spaces.push_back(
-                    local_grid_ptr
+                    local_grid
                         ->template sharedTileIndexSpace<cell_bits_per_tile_dim>(
                             Ghost(), entity_type(), n ) );
 
@@ -1283,6 +1283,34 @@ class SparseHalo
     // SoA total bytes count
     std::size_t _soa_total_bytes;
 };
+
+//---------------------------------------------------------------------------//
+// Sparse halo creation.
+//---------------------------------------------------------------------------//
+/*!
+  \brief SparseHalo creation function.
+  \param pattern The pattern to build the sparse halo from.
+  \param array The sparse array over which to build the halo.
+*/
+template <class DeviceType, unsigned long long cellBitsPerTileDim,
+          class DataTypes, class EntityType, class MeshType,
+          class SparseMapType, class Pattern, typename Value = int,
+          typename Key = uint64_t>
+auto createSparseHalo(
+    const Pattern& pattern,
+    const std::shared_ptr<
+        SparseArray<DataTypes, DeviceType, EntityType, MeshType, SparseMapType>>
+        array )
+{
+    using array_type =
+        SparseArray<DataTypes, DeviceType, EntityType, MeshType, SparseMapType>;
+    using memory_space = typename array_type::memory_space;
+    static constexpr std::size_t num_space_dim = array_type::num_space_dim;
+    return std::make_shared<
+        SparseHalo<memory_space, DataTypes, EntityType, num_space_dim,
+                   cellBitsPerTileDim, Value, Key>>( pattern, array );
+}
+
 }; // namespace Experimental
 }; // end namespace Cajita
 

cajita/unit_test/tstSparseHalo.hpp

@@ -465,8 +465,8 @@ void haloScatterAndGatherTest( ReduceOp reduce_op, EntityType entity )
     auto sparse_array = createSparseArray<TEST_DEVICE>(
         std::string( "test_sparse_grid" ), *sparse_layout );
 
-    SparseHalo<TEST_MEMSPACE, DataTypes, EntityType, 3, cell_bits_per_tile_dim>
-        halo( NodeHaloPattern<3>(), local_grid, MPI_COMM_WORLD );
+    auto halo = createSparseHalo<TEST_DEVICE, cell_bits_per_tile_dim>(
+        NodeHaloPattern<3>(), sparse_array );
 
     // sample valid halos on rank 0 and broadcast to other ranks
     // Kokkos::View<T* [3], TEST_MEMSPACE> tile_view;
@@ -517,7 +517,7 @@ void haloScatterAndGatherTest( ReduceOp reduce_op, EntityType entity )
             } );
 
         sparse_array->resize( sparse_map.sizeCell() );
-        halo.template register_halo<TEST_EXECSPACE>( sparse_map );
+        halo->template register_halo<TEST_EXECSPACE>( sparse_map );
         MPI_Barrier( MPI_COMM_WORLD );
     }
 
@@ -605,10 +605,10 @@ void haloScatterAndGatherTest( ReduceOp reduce_op, EntityType entity )
     // halo scatter and gather
     /// false means the heighbors' halo counting information is not
     /// collected
-    halo.scatter( TEST_EXECSPACE(), reduce_op, *sparse_array, false );
+    halo->scatter( TEST_EXECSPACE(), reduce_op, *sparse_array, false );
     /// halo counting info already collected in the previous scatter, thus true
     /// and no need to recount again
-    halo.gather( TEST_EXECSPACE(), *sparse_array, true );
+    halo->gather( TEST_EXECSPACE(), *sparse_array, true );
     MPI_Barrier( MPI_COMM_WORLD );
 
     // check results