Hello, I would like to ask if the following error regarding CuArray is Julia version specific. I was able to run the following basic CuArray test with Julia 1.8.0-Dev.1370, but when I tried with the latest release of Julia 1.9.0-DEV.239, it gave the following error. Can anyone help look into the problem and provide a solution to get it around? Thanks!
[jin6@node0026 Julia-03232022]$ ./julia
_
_ _ _ (_) _ | Documentation: https://docs.julialang.org
(_) | (_) (_) |
_ _ | | __ _ | Type “?” for help, “]?” for Pkg help.
| | | | | | |/ _` | |
| | || | | | (| | | Version 1.9.0-DEV.239 (2022-03-23)
/ |_‘|||_’_| | Commit a5fe945b4f (0 days old master)
|__/ |
julia> VERSION
v"1.9.0-DEV.239"
julia> import Pkg; Pkg.add(“CUDA”)
Updating registry at ~/.julia/registries/General
Updating git-repo https://github.com/JuliaRegistries/General.git
Resolving package versions…
No Changes to ~/.julia/environments/v1.9/Project.toml
No Changes to ~/.julia/environments/v1.9/Manifest.toml
Precompiling project…
46 dependencies successfully precompiled in 44 seconds
julia> using CUDA
julia> CUDA.versioninfo()
CUDA toolkit 11.6, artifact installation
NVIDIA driver 470.42.1, for CUDA 11.4
CUDA driver 11.4
Libraries:
-
CUBLAS: 11.8.1
-
CURAND: 10.2.9
-
CUFFT: 10.7.0
-
CUSOLVER: 11.3.2
-
CUSPARSE: 11.7.1
-
CUPTI: 16.0.0
-
NVML: 11.0.0+470.42.1
-
CUDNN: 8.30.2 (for CUDA 11.5.0)
-
CUTENSOR: 1.4.0 (for CUDA 11.5.0)
Toolchain:
-
Julia: 1.9.0-DEV.239
-
LLVM: 13.0.1
-
PTX ISA support: 3.2, 4.0, 4.1, 4.2, 4.3, 5.0, 6.0, 6.1, 6.3, 6.4, 6.5, 7.0
-
Device capability support: sm_35, sm_37, sm_50, sm_52, sm_53, sm_60, sm_61, sm_62, sm_70, sm_72, sm_75, sm_80
1 device:
0: Tesla V100-PCIE-16GB (sm_70, 15.756 GiB / 15.782 GiB available)
julia> [CUDA.capability(dev) for dev in CUDA.devices()]
1-element Vector{VersionNumber}:
v"7.0.0"
julia> a = CuArray([1,2,3,4])
4-element CuArray{Int64, 1, CUDA.Mem.DeviceBuffer}:
1
2
3
4
julia> a .+= 1
ERROR: MethodError: no method matching return_types(::GPUArrays.var"#broadcast_kernel#17", ::Type{Tuple{CUDA.CuKernelContext, CuDeviceVector{Int64, 1}, Base.Broadcast.Broadcasted{CUDA.CuArrayStyle{1}, Tuple{Base.OneTo{Int64}}, typeof(+), Tuple{Base.Broadcast.Extruded{CuDeviceVector{Int64, 1}, Tuple{Bool}, Tuple{Int64}}, Int64}}, Int64}}, ::GPUCompiler.GPUInterpreter)
Closest candidates are:
return_types(::Any, ::Any; world, interp) at reflection.jl:1294
return_types(::Any) at reflection.jl:1294
Stacktrace:
[1] check_method( job::GPUCompiler.CompilerJob )
@ GPUCompiler ~/.julia/packages/GPUCompiler/I9fZc/src/validation.jl:19
[2] macro expansion
@ ~/.julia/packages/TimerOutputs/nDhDw/src/TimerOutput.jl:252 [inlined]
[3] macro expansion
@ ~/.julia/packages/GPUCompiler/I9fZc/src/driver.jl:89 [inlined]
[4] emit_julia( job::GPUCompiler.CompilerJob )
@ GPUCompiler ~/.julia/packages/GPUCompiler/I9fZc/src/utils.jl:64
[5] cufunction_compile( job::GPUCompiler.CompilerJob )
@ CUDA ~/.julia/packages/CUDA/5jdFl/src/compiler/execution.jl:324
[6] cached_compilation( cache::Dict{UInt64, Any}, job::GPUCompiler.CompilerJob, compiler::typeof(CUDA.cufunction_compile), linker::typeof(CUDA.cufunction_link) )
@ GPUCompiler ~/.julia/packages/GPUCompiler/I9fZc/src/cache.jl:90
[7] cufunction( f::GPUArrays.var"#broadcast_kernel#17", tt::Type{Tuple{CUDA.CuKernelContext, CuDeviceVector{Int64, 1}, Base.Broadcast.Broadcasted{CUDA.CuArrayStyle{1}, Tuple{Base.OneTo{Int64}}, typeof(+), Tuple{Base.Broadcast.Extruded{CuDeviceVector{Int64, 1}, Tuple{Bool}, Tuple{Int64}}, Int64}}, Int64}}; name::Nothing, kwargs::Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}} )
@ CUDA ~/.julia/packages/CUDA/5jdFl/src/compiler/execution.jl:297
[8] cufunction
@ ~/.julia/packages/CUDA/5jdFl/src/compiler/execution.jl:291 [inlined]
[9] macro expansion
@ ~/.julia/packages/CUDA/5jdFl/src/compiler/execution.jl:102 [inlined]
[10] #launch_heuristic#282
@ ~/.julia/packages/CUDA/5jdFl/src/gpuarrays.jl:17 [inlined]
[11] _copyto!
@ ~/.julia/packages/GPUArrays/VNhDf/src/host/broadcast.jl:73 [inlined]
[12] materialize!
@ ~/.julia/packages/GPUArrays/VNhDf/src/host/broadcast.jl:51 [inlined]
[13] materialize!( dest::CuArray{Int64, 1, CUDA.Mem.DeviceBuffer}, bc::Base.Broadcast.Broadcasted{CUDA.CuArrayStyle{1}, Nothing, typeof(+), Tuple{CuArray{Int64, 1, CUDA.Mem.DeviceBuffer}, Int64}} )
@ Base.Broadcast ./broadcast.jl:868
[14] top-level scope
@ REPL[7]:1
[15] top-level scope
@ ~/.julia/packages/CUDA/5jdFl/src/initialization.jl:52
