Merge pull request #209 from SciML/arraypartition_cuarray

Fix ArrayPartition CuArray transformation

Author: ChrisRackauckas

Project.toml

@@ -1,7 +1,7 @@
 name = "RecursiveArrayTools"
 uuid = "731186ca-8d62-57ce-b412-fbd966d074cd"
 authors = ["Chris Rackauckas <[email protected]>"]
-version = "2.29.0"
+version = "2.29.1"
 
 [deps]
 Adapt = "79e6a3ab-5dfb-504d-930d-738a2a938a0e"

src/array_partition.jl

@@ -65,6 +65,7 @@ Base.zero(A::ArrayPartition, dims::NTuple{N,Int}) where {N} = zero(A)
 
 ## Array
 
+Base.Array(A::ArrayPartition) = ArrayPartition(Array.(A.x))
 Base.Array(VA::AbstractVectorOfArray{T,N,A}) where {T,N,A <: AbstractVector{<:ArrayPartition}} = reduce(hcat,Array.(VA.u))
 
 ## ones

test/gpu/ode_gpu.jl

@@ -0,0 +1,29 @@
+using CUDA, LinearAlgebra, OrdinaryDiffEq
+
+u0 = cu(rand(100))
+
+A = cu(randn(100,100))
+
+f(du,u,p,t) = mul!(du,A,u)
+
+prob = ODEProblem(f,u0,(0.0f0,1.0f0))
+
+sol = solve(prob,Tsit5())
+
+Array(sol)
+
+# https://discourse.julialang.org/t/results-of-secondorderodeproblem-give-error-this-object-is-not-a-gpu-array/82100
+
+u0 = cu(rand(100))
+
+du0 = cu(rand(100))
+
+A = cu(randn(100,100))
+
+f(ddu,du,u,p,t) = mul!(ddu,A,u)
+
+prob = SecondOrderODEProblem(f,du0,u0,(0.0f0,1.0f0))
+
+sol = solve(prob,Tsit5())
+
+CuArray(sol)