Could not load CUTENSOR artifact dll on Windows 10 #355

stillyslalom · 2020-08-06T17:45:09Z

Describe the bug

When installing CUDA#master in Julia 1.5 on Windows 10 (after nuking .julia/ to start fresh), a (504) Gateway Timeout exception is thrown while downloading artifacts, followed by an error resulting from failure to load cutensor.dll, despite the existence of the library at the specified path.

To reproduce

The Minimal Working Example (MWE) for this bug:

PS C:\Users\alexa\AppData\Local\Programs\Julia 1.5.0\bin> Set-Variable -Name "JULIA_DEBUG" -Value "CUDA"

julia> using CUDA
[ Info: Precompiling CUDA [052768ef-5323-5732-b1bb-66c8b64840ba]

julia> CUDA.version()
Downloading artifact: CUDA110
Exception calling "DownloadFile" with "2" argument(s): "The remote server returned an error: (504) Gateway Timeout."
At line:12 char:1
+ $webclient.DownloadFile("https://pkg.julialang.org/artifact/4747fe73a ...
+ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
    + CategoryInfo          : NotSpecified: (:) [], MethodInvocationException
    + FullyQualifiedErrorId : WebException
ERROR: could not load library "C:\Users\alexa\.julia\artifacts\804435c7dbe9d002d6caa0a8b3596d11a6faa778\bin\cutensor.dll"
The specified module could not be found.
Stacktrace:
 [1] dlopen(::String, ::UInt32; throw_error::Bool) at D:\buildbot\worker\package_win64\build\usr\share\julia\stdlib\v1.5\Libdl\src\Libdl.jl:109
 [2] dlopen at D:\buildbot\worker\package_win64\build\usr\share\julia\stdlib\v1.5\Libdl\src\Libdl.jl:109 [inlined] (repeats 2 times)
 [3] use_artifact_cutensor(::VersionNumber) at C:\Users\alexa\.julia\packages\CUDA\YU1DS\deps\bindeps.jl:315
 [4] use_artifact_cuda() at C:\Users\alexa\.julia\packages\CUDA\YU1DS\deps\bindeps.jl:177
 [5] __init_dependencies__() at C:\Users\alexa\.julia\packages\CUDA\YU1DS\deps\bindeps.jl:342
 [6] __runtime_init__() at C:\Users\alexa\.julia\packages\CUDA\YU1DS\src\initialization.jl:112
 [7] (::CUDA.var"#609#610"{Bool})() at C:\Users\alexa\.julia\packages\CUDA\YU1DS\src\initialization.jl:32
 [8] lock(::CUDA.var"#609#610"{Bool}, ::ReentrantLock) at .\lock.jl:161
 [9] _functional(::Bool) at C:\Users\alexa\.julia\packages\CUDA\YU1DS\src\initialization.jl:26
 [10] functional(::Bool) at C:\Users\alexa\.julia\packages\CUDA\YU1DS\src\initialization.jl:19
 [11] libcuda() at C:\Users\alexa\.julia\packages\CUDA\YU1DS\src\initialization.jl:50
 [12] (::CUDA.var"#676#cache_fptr!#7")() at C:\Users\alexa\.julia\packages\CUDA\YU1DS\lib\utils\call.jl:31
 [13] macro expansion at C:\Users\alexa\.julia\packages\CUDA\YU1DS\lib\utils\call.jl:39 [inlined]
 [14] macro expansion at C:\Users\alexa\.julia\packages\CUDA\YU1DS\lib\cudadrv\libcuda.jl:28 [inlined]
 [15] macro expansion at C:\Users\alexa\.julia\packages\CUDA\YU1DS\lib\cudadrv\error.jl:108 [inlined]
 [16] cuDriverGetVersion(::Base.RefValue{Int32}) at C:\Users\alexa\.julia\packages\CUDA\YU1DS\lib\utils\call.jl:93
 [17] version() at C:\Users\alexa\.julia\packages\CUDA\YU1DS\lib\cudadrv\version.jl:10
 [18] top-level scope at REPL[3]:1

julia> ispath(raw"C:\Users\alexa\.julia\artifacts\804435c7dbe9d002d6caa0a8b3596d11a6faa778\bin\cutensor.dll")
true

Manifest.toml

# This file is machine-generated - editing it directly is not advised

[[AbstractFFTs]]
deps = ["LinearAlgebra"]
git-tree-sha1 = "051c95d6836228d120f5f4b984dd5aba1624f716"
uuid = "621f4979-c628-5d54-868e-fcf4e3e8185c"
version = "0.5.0"

[[Adapt]]
deps = ["LinearAlgebra"]
git-tree-sha1 = "0fac443759fa829ed8066db6cf1077d888bb6573"
uuid = "79e6a3ab-5dfb-504d-930d-738a2a938a0e"
version = "2.0.2"

[[Base64]]
uuid = "2a0f44e3-6c83-55bd-87e4-b1978d98bd5f"

[[BinaryProvider]]
deps = ["Libdl", "Logging", "SHA"]
git-tree-sha1 = "ecdec412a9abc8db54c0efc5548c64dfce072058"
uuid = "b99e7846-7c00-51b0-8f62-c81ae34c0232"
version = "0.5.10"

[[CEnum]]
git-tree-sha1 = "215a9aa4a1f23fbd05b92769fdd62559488d70e9"
uuid = "fa961155-64e5-5f13-b03f-caf6b980ea82"
version = "0.4.1"

[[CUDA]]
deps = ["AbstractFFTs", "Adapt", "BinaryProvider", "CEnum", "DataStructures", "ExprTools", "GPUArrays", "GPUCompiler", "LLVM", "Libdl", "LinearAlgebra", "Logging", "MacroTools", "NNlib", "Pkg", "Printf", "Random", "Reexport", "Requires", "SparseArrays", "Statistics", "TimerOutputs"]
git-tree-sha1 = "33975e799350f944295c6ccfb481cd902a54aa20"
repo-rev = "master"
repo-url = "https://github.com/JuliaGPU/CUDA.jl.git"
uuid = "052768ef-5323-5732-b1bb-66c8b64840ba"
version = "1.2.1"

[[DataStructures]]
deps = ["InteractiveUtils", "OrderedCollections"]
git-tree-sha1 = "88d48e133e6d3dd68183309877eac74393daa7eb"
uuid = "864edb3b-99cc-5e75-8d2d-829cb0a9cfe8"
version = "0.17.20"

[[Dates]]
deps = ["Printf"]
uuid = "ade2ca70-3891-5945-98fb-dc099432e06a"

[[ExprTools]]
git-tree-sha1 = "6f0517056812fd6aa3af23d4b70d5325a2ae4e95"
uuid = "e2ba6199-217a-4e67-a87a-7c52f15ade04"
version = "0.1.1"

[[GPUArrays]]
deps = ["AbstractFFTs", "Adapt", "LinearAlgebra", "Printf", "Random", "Serialization"]
git-tree-sha1 = "9027d6128645d227fa9ba7d5b3aa00af696b9aaf"
uuid = "0c68f7d7-f131-5f86-a1c3-88cf8149b2d7"
version = "5.0.0"

[[GPUCompiler]]
deps = ["DataStructures", "InteractiveUtils", "LLVM", "Libdl", "TimerOutputs", "UUIDs"]
git-tree-sha1 = "d6db068d8373bb45ac17e14744cc1d3681d0dbc7"
uuid = "61eb1bfa-7361-4325-ad38-22787b887f55"
version = "0.5.5"

[[InteractiveUtils]]
deps = ["Markdown"]
uuid = "b77e0a4c-d291-57a0-90e8-8db25a27a240"

[[LLVM]]
deps = ["CEnum", "Libdl", "Printf", "Unicode"]
git-tree-sha1 = "a662366a5d485dee882077e8da3e1a95a86d097f"
uuid = "929cbde3-209d-540e-8aea-75f648917ca0"
version = "2.0.0"

[[LibGit2]]
deps = ["Printf"]
uuid = "76f85450-5226-5b5a-8eaa-529ad045b433"

[[Libdl]]
uuid = "8f399da3-3557-5675-b5ff-fb832c97cbdb"

[[LinearAlgebra]]
deps = ["Libdl"]
uuid = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"

[[Logging]]
uuid = "56ddb016-857b-54e1-b83d-db4d58db5568"

[[MacroTools]]
deps = ["Markdown", "Random"]
git-tree-sha1 = "f7d2e3f654af75f01ec49be82c231c382214223a"
uuid = "1914dd2f-81c6-5fcd-8719-6d5c9610ff09"
version = "0.5.5"

[[Markdown]]
deps = ["Base64"]
uuid = "d6f4376e-aef5-505a-96c1-9c027394607a"

[[NNlib]]
deps = ["Libdl", "LinearAlgebra", "Pkg", "Requires", "Statistics"]
git-tree-sha1 = "8ec4693a5422f0b064ce324f59351f24aa474893"
uuid = "872c559c-99b0-510c-b3b7-b6c96a88d5cd"
version = "0.7.4"

[[OrderedCollections]]
git-tree-sha1 = "293b70ac1780f9584c89268a6e2a560d938a7065"
uuid = "bac558e1-5e72-5ebc-8fee-abe8a469f55d"
version = "1.3.0"

[[Pkg]]
deps = ["Dates", "LibGit2", "Libdl", "Logging", "Markdown", "Printf", "REPL", "Random", "SHA", "UUIDs"]
uuid = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f"

[[Printf]]
deps = ["Unicode"]
uuid = "de0858da-6303-5e67-8744-51eddeeeb8d7"

[[REPL]]
deps = ["InteractiveUtils", "Markdown", "Sockets"]
uuid = "3fa0cd96-eef1-5676-8a61-b3b8758bbffb"

[[Random]]
deps = ["Serialization"]
uuid = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"

[[Reexport]]
deps = ["Pkg"]
git-tree-sha1 = "7b1d07f411bc8ddb7977ec7f377b97b158514fe0"
uuid = "189a3867-3050-52da-a836-e630ba90ab69"
version = "0.2.0"

[[Requires]]
deps = ["UUIDs"]
git-tree-sha1 = "d37400976e98018ee840e0ca4f9d20baa231dc6b"
uuid = "ae029012-a4dd-5104-9daa-d747884805df"
version = "1.0.1"

[[SHA]]
uuid = "ea8e919c-243c-51af-8825-aaa63cd721ce"

[[Serialization]]
uuid = "9e88b42a-f829-5b0c-bbe9-9e923198166b"

[[Sockets]]
uuid = "6462fe0b-24de-5631-8697-dd941f90decc"

[[SparseArrays]]
deps = ["LinearAlgebra", "Random"]
uuid = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"

[[Statistics]]
deps = ["LinearAlgebra", "SparseArrays"]
uuid = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"

[[TimerOutputs]]
deps = ["Printf"]
git-tree-sha1 = "f458ca23ff80e46a630922c555d838303e4b9603"
uuid = "a759f4b9-e2f1-59dc-863e-4aeb61b1ea8f"
version = "0.5.6"

[[UUIDs]]
deps = ["Random", "SHA"]
uuid = "cf7118a7-6976-5b1a-9a39-7adc72f591a4"

[[Unicode]]
uuid = "4ec0a83e-493e-50e2-b9ac-8f72acf5a8f5"

Expected behavior

Automatic download/installation of binary artifacts

Version info

Details on Julia:

julia> versioninfo()
Julia Version 1.5.0
Commit 96786e22cc (2020-08-01 23:44 UTC)
Platform Info:
  OS: Windows (x86_64-w64-mingw32)
  CPU: AMD Ryzen 9 4900HS with Radeon Graphics
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-9.0.1 (ORCJIT, znver1)
Environment:
  JULIA_NUM_THREADS = 8

Details on CUDA:

julia> CUDA.versioninfo()
ERROR: AssertionError: CUDA.jl did not successfully initialize, and is not usable.
Stacktrace:
 [1] macro expansion at C:\Users\alexa\.julia\packages\CUDA\YU1DS\src\initialization.jl:50 [inlined]
 [2] toolkit_version at C:\Users\alexa\.julia\packages\CUDA\YU1DS\deps\bindeps.jl:25 [inlined]
 [3] versioninfo(::Base.TTY) at C:\Users\alexa\.julia\packages\CUDA\YU1DS\src\utilities.jl:43 (repeats 2 times)
 [4] top-level scope at REPL[5]:1

Additional context

PS C:\Users\alexa> nvidia-smi
Thu Aug 06 12:06:19 2020
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 451.67       Driver Version: 451.67       CUDA Version: 11.0     |
|-------------------------------+----------------------+----------------------+
| GPU  Name            TCC/WDDM | Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|===============================+======================+======================|
|   0  GeForce RTX 206... WDDM  | 00000000:01:00.0 Off |                  N/A |
| N/A   27C    P8    12W /  N/A |    164MiB /  6144MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
|  No running processes found                                                 |
+-----------------------------------------------------------------------------+

The text was updated successfully, but these errors were encountered:

maleadt · 2020-08-06T17:51:26Z

Can you list the files in C:\Users\alexa\.julia\artifacts\804435c7dbe9d002d6caa0a8b3596d11a6faa778\bin\?

stillyslalom · 2020-08-06T18:00:05Z

cutensor.dll is the only file in that folder. There are two other artifact folders containing various other CUDA dlls:

maleadt · 2020-08-06T20:36:07Z

I'm not sure why the DLL wouldn't load then (The specified module could not be found.), and I don't have much Windows experience to debug that. I'll see if I can reproduce.

stillyslalom · 2020-08-06T21:34:05Z

The cutensor artifact is intact, which rules out download corruption. CUDA 11 support is a pretty recent development, right? Any chance the artifact itself is broken?

julia> artifact_toml = joinpath(pkgdir(CUDA), "Artifacts.toml")
"C:\\Users\\alexa\\.julia\\packages\\CUDA\\YU1DS\\Artifacts.toml"

julia> artifact_hash("CUTENSOR_CUDA110", artifact_toml) |> verify_artifact
true

This is the subset of dlls that's loaded during CUDA.jl initialization before the error:

julia> setdiff(finaldlls, initdlls)
23-element Array{String,1}:
 "C:\\Users\\alexa\\AppData\\Local\\Programs\\Julia 1.5.0\\bin\\libdSFMT.DLL"
 "C:\\WINDOWS\\SYSTEM32\\nvcuda.DLL"
 "C:\\WINDOWS\\SYSTEM32\\VERSION.DLL"
 "C:\\WINDOWS\\system32\\DriverStore\\FileRepository\\nvami.inf_amd64_aceb5b140d1d131e\\nvcuda64.dll"
 "C:\\WINDOWS\\SYSTEM32\\nvapi64.dll"
 "C:\\WINDOWS\\System32\\SETUPAPI.DLL"
 "C:\\WINDOWS\\System32\\cfgmgr32.dll"
 "C:\\WINDOWS\\System32\\SHLWAPI.DLL"
 "C:\\WINDOWS\\SYSTEM32\\dxgi.dll"
 "C:\\Users\\alexa\\AppData\\Local\\Programs\\Julia 1.5.0\\bin\\libopenlibm.DLL"
 "C:\\Users\\alexa\\.julia\\artifacts\\4747fe73a29e16337cb33702edae26b4e681ae52\\bin\\cublas64_11.dll"
 "C:\\Users\\alexa\\.julia\\artifacts\\4747fe73a29e16337cb33702edae26b4e681ae52\\bin\\cublasLt64_11.dll"
 "C:\\Users\\alexa\\.julia\\artifacts\\4747fe73a29e16337cb33702edae26b4e681ae52\\bin\\cusparse64_11.dll"
 "C:\\Users\\alexa\\.julia\\artifacts\\4747fe73a29e16337cb33702edae26b4e681ae52\\bin\\cusolver64_10.dll"
 "C:\\Users\\alexa\\.julia\\artifacts\\4747fe73a29e16337cb33702edae26b4e681ae52\\bin\\cufft64_10.dll"
 "C:\\Users\\alexa\\.julia\\artifacts\\4747fe73a29e16337cb33702edae26b4e681ae52\\bin\\curand64_10.dll"
 "C:\\Users\\alexa\\.julia\\artifacts\\430f2638c1882d64e7673183c57b1564edaba69f\\bin\\cudnn_ops_infer64_8.dll"
 "C:\\Users\\alexa\\.julia\\artifacts\\430f2638c1882d64e7673183c57b1564edaba69f\\bin\\cudnn_ops_train64_8.dll"
 "C:\\Users\\alexa\\.julia\\artifacts\\430f2638c1882d64e7673183c57b1564edaba69f\\bin\\cudnn_cnn_infer64_8.dll"
 "C:\\Users\\alexa\\.julia\\artifacts\\430f2638c1882d64e7673183c57b1564edaba69f\\bin\\cudnn_cnn_train64_8.dll"
 "C:\\Users\\alexa\\.julia\\artifacts\\430f2638c1882d64e7673183c57b1564edaba69f\\bin\\cudnn_adv_infer64_8.dll"
 "C:\\Users\\alexa\\.julia\\artifacts\\430f2638c1882d64e7673183c57b1564edaba69f\\bin\\cudnn_adv_train64_8.dll"
 "C:\\Users\\alexa\\.julia\\artifacts\\430f2638c1882d64e7673183c57b1564edaba69f\\bin\\cudnn64_8.dll"

stillyslalom · 2020-08-06T21:46:16Z

I downloaded cutensor.dll v11 from Nvidia, and the artifact is identical, so that's not the issue

julia> ct1 = read(raw"C:\Users\alexa\.julia\artifacts\804435c7dbe9d002d6caa0a8b3596d11a6faa778\bin\cutensor.dll");

julia> ct2 = read(raw"C:\Program Files\NVIDIA cuTENSOR\v1.2\lib\11.0\cutensor.dll");

julia> ct1 == ct2
true

stillyslalom · 2020-08-06T22:06:32Z

The issue's coming from CUDA110, which must be improperly linking to cutensor:

julia> artifact_hash("CUDA110", artifact_toml) |> verify_artifact
false

I think it may be related to JuliaLang/Pkg.jl#1892.

timkimd · 2020-08-13T11:48:28Z

I think I'm having similar issue. (I'm using Windows, and I can't load Flux or DiffEqFlux with Julia 1.4.2 or 1.5.0, but the error doesn't occur when using Julia 1.3.1.)

FluxML/Flux.jl#1313

charleskawczynski · 2020-08-13T14:39:51Z

I'm also using Windows, and I can't load CUDA with Julia 1.4.2 or 1.5.0, but I can with Julia 1.3.1.

stillyslalom · 2020-08-13T14:54:34Z

Which version of CUDA are you running? (check with nvidia-smi in the console). I'm on 11.0. It's unclear whether it's just a problem with the 11.0 DLLs, or if it's more general than that.

charleskawczynski · 2020-08-13T16:19:06Z

Hm, not sure how to use the nvidia-smi command:

bash: nvidia-smi: command not found

But,

julia> CUDA.version()
┌ Warning: `haskey(::TargetIterator, name::String)` is deprecated, use `Target(; name=name) !== nothing` instead.
│   caller = llvm_compat(::VersionNumber) at compatibility.jl:181
└ @ CUDA C:\Users\kawcz\.julia\packages\CUDA\42B9G\deps\compatibility.jl:181
v"10.2.0"
julia> versioninfo()
Julia Version 1.3.1
Commit 2d5741174c (2019-12-30 21:36 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-6.0.1 (ORCJIT, skylake)

stillyslalom · 2020-08-13T20:18:01Z

You should be able to run nvidia-smi from one of the built-in Windows terminals (cmd or Powershell), but yeah, you're on CUDA v10.2. What's the error message you see on Julia 1.5?

charleskawczynski · 2020-08-13T23:01:32Z

I believe it was the same, or very similar to the issue post.

stillyslalom · 2020-08-14T00:27:17Z

The download issue should be fixed now, which leaves us with a secondary issue involving improperly-linked DLLs. Can you confirm that you're able to download those artifacts without a 502/504 error?

HenriDeh · 2020-08-14T15:31:29Z

I get 504 error when downloading CUDNN_CUDA102 on CUDA#master. Not fixed evidently.

maleadt · 2020-08-16T12:20:51Z

I get 504 error when downloading CUDNN_CUDA102 on CUDA#master. Not fixed evidently.

Please refer to JuliaLang/Pkg.jl#1892; this is not an issue on the CUDA.jl side.

maleadt · 2020-08-16T12:25:51Z

For the people where the CUTENSOR dll fails to load, which version of Windows are you using exactly? Could you open the CUTENSOR dll in Dependencies and report what you see:

HenriDeh · 2020-08-17T09:01:42Z

@maleadt I also have the cutensor load issue. I am on windows 10 family version 1903. Here is what Dependencies shows :

Hoovering over the ? entry displays "VCRUNTIME140_1.dll module could not be found on disk"
Tell me if you need more details.

stillyslalom · 2020-08-17T13:27:37Z

Try installing Visual Studio C++ - that provides VCRUNTIME. After installing, I'm able to initialize CUDA.jl:

julia> CUDA.versioninfo()
CUDA toolkit 11.0.194, artifact installation
CUDA driver 11.0.0
NVIDIA driver 451.67.0

Libraries:
- CUBLAS: 11.1.0
- CURAND: 10.2.1
- CUFFT: 10.2.0
- CUSOLVER: 10.5.0
- CUSPARSE: 11.1.0
- CUPTI: 13.0.0
- NVML: 11.0.0+451.67
- CUDNN: 8.0.1 (for CUDA 11.0.0)
- CUTENSOR: 1.2.0 (for CUDA 11.0.0)

Toolchain:
- Julia: 1.5.0
- LLVM: 9.0.1
- PTX ISA support: 3.2, 4.0, 4.1, 4.2, 4.3, 5.0, 6.0, 6.1, 6.3, 6.4
- Device support: sm_35, sm_37, sm_50, sm_52, sm_53, sm_60, sm_61, sm_62, sm_70, sm_72, sm_75

1 device(s):
- GeForce RTX 2060 with Max-Q Design (sm_75, 5.840 GiB / 6.000 GiB available)

HenriDeh · 2020-08-17T13:33:39Z

I directly downloaded the dll from here and now CUDA works. (save it in C:\Windows\sytem32)

stillyslalom · 2020-08-17T14:04:17Z

It may suffice to install the 2015-2019 VS C++ redistributable. @charleskawczynski can you give that a shot? If so, we can just add a note to the installation instructions.

'Fixes' #355

charleskawczynski · 2020-09-02T14:19:28Z

It may suffice to install the 2015-2019 VS C++ redistributable. @charleskawczynski can you give that a shot? If so, we can just add a note to the installation instructions.

This doesn't seem like the right way of fixing this problem.

I'm running into this again after updating CUDA.

[ Info: Precompiling ClimateMachine [777c4786-024f-11e9-21a3-85d5d4106250]
┌ 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\kawcz\.julia\artifacts\d6605f4aac98265f0bc1e17d7b6442ffbdee6e9a\bin\cutensor.dll"
│    The specified module could not be found.
│
│    Stacktrace:
│     [1] #dlopen#3(::Bool, ::typeof(Libdl.dlopen), ::String, ::UInt32) at D:\buildbot\worker\package_win64\build\usr\share\julia\stdlib\v1.3\Libdl\src\Libdl.jl:109
│     [2] dlopen at D:\buildbot\worker\package_win64\build\usr\share\julia\stdlib\v1.3\Libdl\src\Libdl.jl:109 [inlined] (repeats 2 times)
│     [3] use_artifact_cutensor(::VersionNumber) at C:\Users\kawcz\.julia\packages\CUDA\dZvbp\deps\bindeps.jl:318
│     [4] use_artifact_cuda() at C:\Users\kawcz\.julia\packages\CUDA\dZvbp\deps\bindeps.jl:179
│     [5] __init_dependencies__() at C:\Users\kawcz\.julia\packages\CUDA\dZvbp\deps\bindeps.jl:355
│     [6] __runtime_init__() at C:\Users\kawcz\.julia\packages\CUDA\dZvbp\src\initialization.jl:110
│     [7] (::CUDA.var"#609#610"{Bool})() at C:\Users\kawcz\.julia\packages\CUDA\dZvbp\src\initialization.jl:32
│     [8] lock(::CUDA.var"#609#610"{Bool}, ::ReentrantLock) at .\lock.jl:151
│     [9] _functional(::Bool) at C:\Users\kawcz\.julia\packages\CUDA\dZvbp\src\initialization.jl:26
│     [10] functional(::Bool) at C:\Users\kawcz\.julia\packages\CUDA\dZvbp\src\initialization.jl:19
│     [11] has_cuda at C:\Users\kawcz\.julia\packages\CUDA\dZvbp\src\initialization.jl:173 [inlined]
│     [12] has_cuda_gpu at C:\Users\kawcz\.julia\packages\CUDA\dZvbp\src\initialization.jl:183 [inlined] (repeats 2 times)
│     [13] #init#6(::Bool, ::Nothing, ::Bool, ::Base.Iterators.Pairs{Symbol,String,Tuple{Symbol},NamedTuple{(:output_dir,),Tuple{String}}}, ::typeof(ClimateMachine.init)) at C:\Users\kawcz\Dropbox\Caltech\work\dev\CliMA\ClimateMachine.jl\src\Driver\Driver.jl:430
│     [14] (::ClimateMachine.var"#kw##init")(::NamedTuple{(:parse_clargs, :output_dir),Tuple{Bool,String}}, ::typeof(ClimateMachine.init)) at .\none:0
│     [15] top-level scope at C:\Users\kawcz\Dropbox\Caltech\work\dev\CliMA\ClimateMachine.jl\test\Atmos\EDMF\bomex_edmf.jl:2
│     [16] include at .\boot.jl:328 [inlined]
│     [17] include_relative(::Module, ::String) at .\loading.jl:1105
│     [18] include(::Module, ::String) at .\Base.jl:31
│     [19] include(::String) at .\client.jl:424
│     [20] top-level scope at REPL[6]:1
│     [21] eval(::Module, ::Any) at .\boot.jl:330
│     [22] eval_user_input(::Any, ::REPL.REPLBackend) at D:\buildbot\worker\package_win64\build\usr\share\julia\stdlib\v1.3\REPL\src\REPL.jl:86
│     [23] macro expansion at D:\buildbot\worker\package_win64\build\usr\share\julia\stdlib\v1.3\REPL\src\REPL.jl:118 [inlined]
│     [24] (::REPL.var"#26#27"{REPL.REPLBackend})() at .\task.jl:333
└ @ CUDA C:\Users\kawcz\.julia\packages\CUDA\dZvbp\deps\bindeps.jl:320

julia> versioninfo()
Julia Version 1.3.1
Commit 2d5741174c (2019-12-30 21:36 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-6.0.1 (ORCJIT, skylake)
Environment:
  JULIA_PKG_DEVDIR = C:/Users/kawcz/Dropbox/Caltech/work/dev/julia

@maleadt I'm on Windows 10 Home.

maleadt · 2020-09-02T14:45:05Z

Please inspect the dependencies then, as listed higher up.

charleskawczynski · 2020-09-02T15:17:22Z

Please inspect the dependencies then, as listed higher up.

Per Dependencies documentation:

Dependencies needs Visual C++ Redistributable installed to run properly.

Once installing Visual C++ Redistributable, I'm able to using CUDA. Will installing Visual C++ Redistributable affect what Dependencies reports?

charleskawczynski · 2020-09-02T15:19:39Z

I am seeing some ? display entries:

but the top window looks clear of issues AFAICT

maleadt · 2020-09-02T15:42:08Z

So installing the Visual C++ Redistributable fixed it? Isn't that exactly what the CUDA.jl error suggested? Or what did you mean with 'This doesn't seem like the right way of fixing this problem.'?

charleskawczynski · 2020-09-02T16:05:05Z

So installing the Visual C++ Redistributable fixed it? Isn't that exactly what the CUDA.jl error suggested?

Yes, and yes.

Or what did you mean with 'This doesn't seem like the right way of fixing this problem.'?

I was thinking that everything should be shipped with ] add CUDA. Sorry for the noise, I'm not very familiar with how the installation/deps work.

maleadt · 2020-09-02T16:07:03Z

I was thinking that everything should be shipped with ] add CUDA. Sorry for the noise, I'm not very familiar with how the installation/deps work.

Ah, ok, no that makes sense but I don't think we have that readily available yet (and I thought that the VC C++ redistributable is a common thing to request users to install).

@giordano @staticfloat Do we have the VC C++ redistributable packaged up somehow?

staticfloat · 2020-09-02T16:37:36Z

No, we don't. I think the best solution here would be to auto-determine that it doesn't exist, and if that is the case, download and run this executable: https://aka.ms/vs/16/release/vc_redist.x64.exe

I think using the actual executable to install the libraries is better than us trying to do it with a JLL, since these are pretty common libraries and it's better for the user to get them in the way that MS intended.

giordano · 2020-09-02T16:40:20Z

Shameless self-plug: https://github.com/giordano/DependencyWalker.jl can be useful to debug why a library can't be loaded

jonniedie · 2020-10-09T19:11:56Z

It would be nice if there was a way to do this without the MS executable, as that requires admin privileges.

SeniorCtrlPlayer · 2021-01-27T19:19:03Z

I directly downloaded the dll from here and now CUDA works. (save it in C:\Windows\sytem32)

Work for me

stillyslalom added the bug Something isn't working label Aug 6, 2020

stillyslalom mentioned this issue Aug 6, 2020

CUTENSOR for windows #301

Closed

maleadt added the installation CUDA is easy to install, right? label Aug 6, 2020

maleadt changed the title ~~Artifact download fails on Windows 10~~ Could not load CUTENSOR artifact dll on Windows 10 Aug 16, 2020

HenriDeh mentioned this issue Aug 18, 2020

getting WebExceptions on 1.5 rc1 JuliaLang/Pkg.jl#1892

Closed

maleadt added a commit that referenced this issue Aug 18, 2020

Catch and warn about CUTENSOR load failures.

d2d790a

'Fixes' #355

maleadt closed this as completed in 2cf8ae3 Aug 19, 2020

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Could not load CUTENSOR artifact dll on Windows 10 #355

Could not load CUTENSOR artifact dll on Windows 10 #355

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Could not load CUTENSOR artifact dll on Windows 10 #355

Could not load CUTENSOR artifact dll on Windows 10 #355

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