Adding some prelimiar Adapt statements

src/adapt.jl

@@ -50,3 +50,43 @@ function Adapt.adapt_structure(to,v::PSparseMatrix)
     row_par = v.row_partition
     PSparseMatrix(matrix_partition,row_par,col_par,v.assembled)
 end
+
+function Adapt.adapt_structure(to,v::PVector)
+    new_local_values = map(local_values(v)) do myvals
+         Adapt.adapt_structure(to,myvals)
+    end
+    new_cache = Adapt.adapt_structure(to,v.cache)
+    new_v = PVector(new_local_values,v.index_partition, new_cache)
+    new_v
+end
+
+function Adapt.adapt_structure(to, cache::SplitVectorAssemblyCache)
+    # Adapt all the components
+    neighbors_snd =  cache.neighbors_snd
+    neighbors_rcv =  cache.neighbors_rcv
+    buffer_snd = map(cache.buffer_snd) do ja
+        Adapt.adapt_structure(to, ja)
+    end
+    buffer_rcv = map(cache.buffer_rcv) do ja
+        Adapt.adapt_structure(to, ja)
+    end
+    exchange_setup =  cache.exchange_setup
+    ghost_indices_snd = map(cache.ghost_indices_snd) do ja
+        Adapt.adapt_structure(to, ja)
+    end
+    own_indices_rcv = map(cache.own_indices_rcv) do ja
+        Adapt.adapt_structure(to, ja)
+    end
+
+    # Create new cache with adapted components
+    SplitVectorAssemblyCache(
+        neighbors_snd,
+        neighbors_rcv,
+        ghost_indices_snd,
+        own_indices_rcv,
+        buffer_snd,
+        buffer_rcv,
+        exchange_setup,
+        false
+    )
+end

test/adapt_tests.jl

@@ -14,8 +14,8 @@ function Adapt.adapt_storage(::Type{<:FakeCuVector},x::AbstractArray)
 end
 
 function adapt_tests(distribute)
-
-    rank = distribute(LinearIndices((2,2)))
+    parts_per_dir = (2,2)
+    rank = distribute(LinearIndices(parts_per_dir))
 
     a = [[1,2],[3,4,5],Int[],[3,4]]
     b = JaggedArray(a)
@@ -61,4 +61,14 @@ function adapt_tests(distribute)
         @test typeof(val_b) == FakeCuVector{typeof(val_a)}
         @test val_b.vector == val_a
     end
-end
+
+    p = prod(parts_per_dir)
+    ranks = distribute(LinearIndices((p,)))
+    nodes_per_dir = map(i->2*i,parts_per_dir)
+    args = laplacian_fdm(nodes_per_dir,parts_per_dir,ranks)
+    A = psparse(args...) |> fetch
+    Adapt.adapt(FakeCuVector, A)
+    b = pzeros(axes(A, 2), split_format=true)
+    Adapt.adapt(FakeCuVector, b)
+
+end