Improve 'VS C++ redistributable' error message

[anandijain]

pkg> add CUDA

julia> versioninfo()
Julia Version 1.6.0-rc1
Commit a58bdd9010 (2021-02-06 15:49 UTC)
Platform Info:
  OS: Windows (x86_64-w64-mingw32)
  CPU: Intel(R) Core(TM) i7-7700HQ CPU @ 2.80GHz
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-11.0.1 (ORCJIT, skylake)

julia> CUDA.versioninfo()
CUDA toolkit 11.1.1, artifact installation
CUDA driver 11.2.0

Libraries:
- CUBLAS: 11.3.0
- CURAND: 10.2.2
- CUFFT: 10.3.0
- CUSOLVER: 11.0.1
- CUSPARSE: 11.3.0
- CUPTI: 14.0.0
- NVML: missing
- CUDNN: 8.0.4 (for CUDA 11.1.0)
- CUTENSOR: missing

Toolchain:
- Julia: 1.6.0-rc1
- LLVM: 11.0.1
- 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 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: GeForce GTX 1050 (sm_61, 3.226 GiB / 4.000 GiB available)

julia> using CUDA

julia> cu(rand(10))
  Downloaded artifact: CUTENSOR_CUDA111
┌ Error: Could not load CUTENSOR; please file an issue (if on Windows, be sure to install the VS C++ redistributable first)
│   exception =
│    could not load library "C:\Users\Anand\.julia\artifacts\1af4317261411b403eee62561b401a92b6b49b3b\bin\cutensor.dll"
│    Access is denied.
│    Stacktrace:
│      [1] dlopen(s::String, flags::UInt32; throw_error::Bool)
│        @ Base.Libc.Libdl .\libdl.jl:114
│      [2] dlopen
│        @ .\libdl.jl:114 [inlined]
│      [3] use_artifact_cutensor(release::VersionNumber)
│        @ CUDA ~\.julia\packages\CUDA\Zmd60\deps\bindeps.jl:340
│      [4] use_artifact_cuda()
│        @ CUDA ~\.julia\packages\CUDA\Zmd60\deps\bindeps.jl:199
│      [5] __init_dependencies__()
│        @ CUDA ~\.julia\packages\CUDA\Zmd60\deps\bindeps.jl:379
│      [6] __runtime_init__()
│        @ CUDA ~\.julia\packages\CUDA\Zmd60\src\initialization.jl:103
│      [7] macro expansion
│        @ ~\.julia\packages\CUDA\Zmd60\src\initialization.jl:32 [inlined]
│      [8] macro expansion
│        @ .\lock.jl:209 [inlined]
│      [9] _functional(show_reason::Bool)
│        @ CUDA ~\.julia\packages\CUDA\Zmd60\src\initialization.jl:26
│     [10] functional(show_reason::Bool)
│        @ CUDA ~\.julia\packages\CUDA\Zmd60\src\initialization.jl:19
│     [11] libcuda()
│        @ CUDA ~\.julia\packages\CUDA\Zmd60\src\initialization.jl:47
│     [12] macro expansion
│        @ ~\.julia\packages\CUDA\Zmd60\lib\cudadrv\libcuda.jl:29 [inlined]
│     [13] macro expansion
│        @ ~\.julia\packages\CUDA\Zmd60\lib\cudadrv\error.jl:102 [inlined]
│     [14] cuDeviceGet
│        @ ~\.julia\packages\CUDA\Zmd60\lib\utils\call.jl:26 [inlined]
│     [15] CuDevice
│        @ ~\.julia\packages\CUDA\Zmd60\lib\cudadrv\devices.jl:25 [inlined]
│     [16] initialize_thread(tid::Int64)
│        @ CUDA ~\.julia\packages\CUDA\Zmd60\src\state.jl:121
│     [17] prepare_cuda_call()
│        @ CUDA ~\.julia\packages\CUDA\Zmd60\src\state.jl:80
│     [18] device
│        @ ~\.julia\packages\CUDA\Zmd60\src\state.jl:227 [inlined]
│     [19] alloc
│        @ ~\.julia\packages\CUDA\Zmd60\src\pool.jl:271 [inlined]
│     [20] CuArray{Float32, 1}(#unused#::UndefInitializer, dims::Tuple{Int64})
│        @ CUDA ~\.julia\packages\CUDA\Zmd60\src\array.jl:20
│     [21] CuArray
│        @ ~\.julia\packages\CUDA\Zmd60\src\array.jl:76 [inlined]
│     [22] similar
│        @ .\abstractarray.jl:779 [inlined]
│     [23] convert
│        @ ~\.julia\packages\GPUArrays\WV76E\src\host\construction.jl:82 [inlined]
│     [24] adapt_storage
│        @ ~\.julia\packages\CUDA\Zmd60\src\array.jl:330 [inlined]
│     [25] adapt_structure
│        @ ~\.julia\packages\Adapt\orWD2\src\Adapt.jl:42 [inlined]
│     [26] adapt
│        @ ~\.julia\packages\Adapt\orWD2\src\Adapt.jl:40 [inlined]
│     [27] cu(xs::Vector{Float64})
│        @ CUDA ~\.julia\packages\CUDA\Zmd60\src\array.jl:342
│     [28] top-level scope
│        @ REPL[2]:1
│     [29] eval(m::Module, e::Any)
│        @ Core .\boot.jl:360
│     [30] eval_user_input(ast::Any, backend::REPL.REPLBackend)
│        @ REPL C:\buildbot\worker\package_win64\build\usr\share\julia\stdlib\v1.6\REPL\src\REPL.jl:139
│     [31] repl_backend_loop(backend::REPL.REPLBackend)
│        @ REPL C:\buildbot\worker\package_win64\build\usr\share\julia\stdlib\v1.6\REPL\src\REPL.jl:200
│     [32] start_repl_backend(backend::REPL.REPLBackend, consumer::Any)
│        @ REPL C:\buildbot\worker\package_win64\build\usr\share\julia\stdlib\v1.6\REPL\src\REPL.jl:185
│     [33] run_repl(repl::REPL.AbstractREPL, consumer::Any; backend_on_current_task::Bool)
│        @ REPL C:\buildbot\worker\package_win64\build\usr\share\julia\stdlib\v1.6\REPL\src\REPL.jl:317
│     [34] run_repl(repl::REPL.AbstractREPL, consumer::Any)
│        @ REPL C:\buildbot\worker\package_win64\build\usr\share\julia\stdlib\v1.6\REPL\src\REPL.jl:305
│     [35] (::Base.var"#878#880"{Bool, Bool, Bool})(REPL::Module)
│        @ Base .\client.jl:387
│     [36] #invokelatest#2
│        @ .\essentials.jl:707 [inlined]
│     [37] invokelatest
│        @ .\essentials.jl:706 [inlined]
│     [38] run_main_repl(interactive::Bool, quiet::Bool, banner::Bool, history_file::Bool, color_set::Bool)
│        @ Base .\client.jl:372
│     [39] exec_options(opts::Base.JLOptions)
│        @ Base .\client.jl:302
│     [40] _start()
│        @ Base .\client.jl:485
└ @ CUDA C:\Users\Anand\.julia\packages\CUDA\Zmd60\deps\bindeps.jl:342

So I see (if on Windows, be sure to install the VS C++ redistributable first) but have no idea what this means. So minumum would be nice to include a link or more detailed instruction.

While I got this error, it seems cu still works and arr = cu(rand(10)) gives back a CuArray, so my wonder is if it's specific to the tensor library.

Thanks!

[maleadt]

Dup of #757. Please try latest master.

So I see (if on Windows, be sure to install the VS C++ redistributable first) but have no idea what this means. So minumum would be nice to include a link or more detailed instruction.

If you google VS C++ redistributable the top results are all relevant.

[maleadt]

This has been added to the documentation, which AFAICT is the only thing we can do here.