update to CUDA.jl

SciML · Jul 7, 2020 · 9787de4 · 9787de4
1 parent ff0c555
commit 9787de4
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Showing 6 changed files with 17 additions and 21 deletions.
diff --git a/Project.toml b/Project.toml
@@ -4,18 +4,14 @@ authors = ["Chris Rackauckas", "JuliaDiffEq"]
 version = "1.3.0"
 
 [deps]
-CUDAdrv = "c5f51814-7f29-56b8-a69c-e4d8f6be1fde"
-CUDAnative = "be33ccc6-a3ff-5ff2-a52e-74243cff1e17"
-CuArrays = "3a865a2d-5b23-5a0f-bc46-62713ec82fae"
+CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba"
 DiffEqBase = "2b5f629d-d688-5b77-993f-72d75c75574e"
 Distributed = "8ba89e20-285c-5b6f-9357-94700520ee1b"
 KernelAbstractions = "63c18a36-062a-441e-b654-da1e3ab1ce7c"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 
 [compat]
-CUDAdrv = "4.0, 5.0, 6.0"
-CUDAnative = "2.5, 3.0"
-CuArrays = "1.4, 2.0"
+CUDA = "1"
 DiffEqBase = "6.5"
 KernelAbstractions = "0.2, 0.3"
 julia = "1"

diff --git a/src/DiffEqGPU.jl b/src/DiffEqGPU.jl
@@ -1,8 +1,8 @@
 module DiffEqGPU
 
-using KernelAbstractions, CuArrays, CUDAnative, DiffEqBase, LinearAlgebra, Distributed
-using CUDAdrv: CuPtr, CU_NULL, Mem, CuDefaultStream
-using CuArrays: CUBLAS
+using KernelAbstractions, CUDA, DiffEqBase, LinearAlgebra, Distributed
+using CUDA: CuPtr, CU_NULL, Mem, CuDefaultStream
+using CUDA: CUBLAS
 
 @kernel function gpu_kernel(f,du,u,p,t)
     i = @index(Global, Linear)

diff --git a/test/distributed_multi_gpu.jl b/test/distributed_multi_gpu.jl
@@ -1,6 +1,6 @@
 using Distributed
 addprocs(2)
-@everywhere using DiffEqGPU, CuArrays, OrdinaryDiffEq, Test, Random
+@everywhere using DiffEqGPU, CUDA, OrdinaryDiffEq, Test, Random
 
 @everywhere begin
     function lorenz_distributed(du,u,p,t)
@@ -11,7 +11,7 @@ addprocs(2)
      end
      nothing
     end
-    CuArrays.allowscalar(false)
+    CUDA.allowscalar(false)
     u0 = Float32[1.0;0.0;0.0]
     tspan = (0.0f0,100.0f0)
     p = (10.0f0,28.0f0,8/3f0)

diff --git a/test/ensemblegpuarray.jl b/test/ensemblegpuarray.jl
@@ -1,4 +1,4 @@
-using DiffEqGPU, CuArrays, OrdinaryDiffEq, Test
+using DiffEqGPU, CUDA, OrdinaryDiffEq, Test
 
 function lorenz(du,u,p,t)
  @inbounds begin
@@ -9,7 +9,7 @@ function lorenz(du,u,p,t)
  nothing
 end
 
-CuArrays.allowscalar(false)
+CUDA.allowscalar(false)
 u0 = Float32[1.0;0.0;0.0]
 tspan = (0.0f0,100.0f0)
 p = (10.0f0,28.0f0,8/3f0)

diff --git a/test/ensemblegpuarray_sde.jl b/test/ensemblegpuarray_sde.jl
@@ -1,4 +1,4 @@
-using DiffEqGPU, CuArrays, StochasticDiffEq, Test
+using DiffEqGPU, CUDA, StochasticDiffEq, Test
 
 function lorenz(du,u,p,t)
  @inbounds begin
@@ -18,7 +18,7 @@ function multiplicative_noise(du,u,p,t)
  nothing
 end
 
-CuArrays.allowscalar(false)
+CUDA.allowscalar(false)
 u0 = Float32[1.0;0.0;0.0]
 tspan = (0.0f0,10.0f0)
 p = (10.0f0,28.0f0,8/3f0)

diff --git a/test/gpu_ode.jl b/test/gpu_ode.jl
@@ -1,4 +1,4 @@
-using GPUifyLoops, CuArrays, SimpleDiffEq
+using GPUifyLoops, CUDA, SimpleDiffEq
 using StaticArrays
 
 function loop(u, p, t)
@@ -20,7 +20,7 @@ const odeoop = ODEProblem{false}(loop, SVector{3}(u0), (0.0f0, 10.0f0),  Float32
 sol2 = solve(odeoop,GPUSimpleTsit5(),dt=dt)
 cps = Array([@SVector [10f0,28f0,8/3f0] for i in 1:32])
 ps = CuArray([@SVector [10f0,28f0,8/3f0] for i in 1:32])
-CuArrays.allowscalar(false)
+CUDA.allowscalar(false)
 
 function f(p)
     solve(odeoop,GPUSimpleTsit5(),dt=dt)
@@ -42,7 +42,7 @@ map(_f2,ps)
 
 
 using GPUifyLoops, SimpleDiffEq, StaticArrays
-using CuArrays, Cthulhu
+using CUDA, Cthulhu
 
 function loop(u, p, t)
     @inbounds begin
@@ -61,7 +61,7 @@ dt = 1f-1
 odeoop = ODEProblem{false}(loop, SVector{3}(u0), (0.0f0, 10.0f0),  Float32[10, 28, 8/3])
 sol2 = solve(odeoop,GPUSimpleATsit5(),save_everystep=false).u[end]
 ps = CuArray([@SVector [10f0,28f0,8/3f0] for i in 1:10])
-CuArrays.allowscalar(false)
+CUDA.allowscalar(false)
 
 function f(p)
     prob = ODEProblem{false}(loop, su0, (0.0f0, 10.0f0),  p)
@@ -87,7 +87,7 @@ end
 _f2 = GPUifyLoops.contextualize(f2)
 map(_f2,ps)
 
-using GPUifyLoops, CuArrays, SimpleDiffEq
+using GPUifyLoops, CUDA, SimpleDiffEq
 using StaticArrays, Cthulhu
 
 function loop(u, p, t)
@@ -115,7 +115,7 @@ odeoop = ODEProblem{false}(loop, SVector{3}(u0), (0.0f0, 10.0f0),  Float32[10, 2
 sol2 = solve(odeoop,GPUSimpleTsit5(),dt=dt)
 ps = CuArray([@SVector [10f0,28f0,8/3f0] for i in 1:600])
 _ps = [@SVector [10f0,28f0,8/3f0] for i in 1:600]
-CuArrays.allowscalar(false)
+CUDA.allowscalar(false)
 
 function f(p)
     prob = ODEProblem{false}(loop, su0, (0.0f0, 10.0f0),  p)