# CUDA.jl tests on windows

**URL:** <https://discourse.julialang.org/t/cuda-jl-tests-on-windows/43378>\
**Category:** GPU\
**Created:** [July 20, 2020, 2:27pm UTC](https://discourse.julialang.org/t/cuda-jl-tests-on-windows/43378 "2020-07-20T14:27:10Z")\
**Posts on this page:** 20\
**Page:** 1

<div class="post-metadata">

**Author:** ![anj](https://avatars.discourse-cdn.com/v4/letter/a/779978/32.png) [@anj](https://discourse.julialang.org/u/anj)\
**Post date:** [July 20, 2020, 2:27pm UTC](https://discourse.julialang.org/t/cuda-jl-tests-on-windows/43378/1 "2020-07-20T14:27:10Z")

</div>

Trying to migrate to CUDA.jl. However can’t make tests passing (both with artifact download and local). Not 100% sure if this is a bug in CUDA.jl or I missed something. Any idea if tests meant to pass on Windows (I understand the main dev env is linux for this lib)?

I created just an empty environment with only CUDA and Distributed packages

test with artifacts

```julia
julia> Pkg.test("CUDA")
    Testing CUDA
Status `C:\Users\andre\AppData\Local\Temp\jl_OtYeSM\Manifest.toml`
  [621f4979] AbstractFFTs v0.5.0
  [79e6a3ab] Adapt v2.0.2
  [b99e7846] BinaryProvider v0.5.10
  [fa961155] CEnum v0.4.1
  [052768ef] CUDA v1.2.0
  [bbf7d656] CommonSubexpressions v0.3.0
  [e66e0078] CompilerSupportLibraries_jll v0.3.3+0
  [adafc99b] CpuId v0.2.2
  [864edb3b] DataStructures v0.17.19
  [163ba53b] DiffResults v1.0.2
  [b552c78f] DiffRules v1.0.1
  [ffbed154] DocStringExtensions v0.8.2
  [e2ba6199] ExprTools v0.1.1
  [7a1cc6ca] FFTW v1.2.2
  [f5851436] FFTW_jll v3.3.9+5
  [1a297f60] FillArrays v0.8.13
  [f6369f11] ForwardDiff v0.10.12
  [0c68f7d7] GPUArrays v4.0.1
  [61eb1bfa] GPUCompiler v0.5.3
  [1d5cc7b8] IntelOpenMP_jll v2018.0.3+0
  [929cbde3] LLVM v2.0.0
  [bdcacae8] LoopVectorization v0.8.18
  [856f044c] MKL_jll v2020.1.216+0
  [1914dd2f] MacroTools v0.5.5
  [a6bfbf70] NNPACK_jll v2018.6.22+0
  [872c559c] NNlib v0.7.3
  [77ba4419] NaNMath v0.3.4
  [6fe1bfb0] OffsetArrays v1.1.1
  [efe28fd5] OpenSpecFun_jll v0.5.3+3
  [bac558e1] OrderedCollections v1.3.0
  [189a3867] Reexport v0.2.0
  [ae029012] Requires v1.0.1
  [21efa798] SIMDPirates v0.8.16
  [476501e8] SLEEFPirates v0.5.4
  [276daf66] SpecialFunctions v0.10.3
  [90137ffa] StaticArrays v0.12.4
  [a759f4b9] TimerOutputs v0.5.6
  [3a884ed6] UnPack v1.0.1
  [3d5dd08c] VectorizationBase v0.12.24
  [2a0f44e3] Base64
  [ade2ca70] Dates
  [8ba89e20] Distributed
  [b77e0a4c] InteractiveUtils
  [76f85450] LibGit2
  [8f399da3] Libdl
  [37e2e46d] LinearAlgebra
  [56ddb016] Logging
  [d6f4376e] Markdown
  [44cfe95a] Pkg
  [de0858da] Printf
  [3fa0cd96] REPL
  [9a3f8284] Random
  [ea8e919c] SHA
  [9e88b42a] Serialization
  [6462fe0b] Sockets 
  [2f01184e] SparseArrays
  [10745b16] Statistics
  [8dfed614] Test
  [cf7118a7] UUIDs
  [4ec0a83e] Unicode
┌ Warning: NNPACK not available for your platform: Windows(x86_64-w64-mingw32-libgfortran5-cxx11)
│ You will be able to use only the default Julia NNlib backend
└ @ NNlib C:\Users\andre\.julia\packages\NNlib\sSn9M\src\NNlib.jl:14
┌ Debug: Initializing CUDA driver
└ @ CUDA C:\Users\andre\.julia\packages\CUDA\h38pe\src\initialization.jl:91
┌ Debug: Trying to use artifacts...
└ @ CUDA C:\Users\andre\.julia\packages\CUDA\h38pe\deps\bindeps.jl:121
┌ Debug: Selecting artifacts based on driver version 11.0.0
└ @ CUDA C:\Users\andre\.julia\packages\CUDA\h38pe\deps\bindeps.jl:130
ERROR: LoadError: AssertionError: isfile(__libcupti[])
Stacktrace:
 [1] use_artifact_cuda() at C:\Users\andre\.julia\packages\CUDA\h38pe\deps\bindeps.jl:157
 [2] __init_dependencies__ () at C:\Users\andre\.julia\packages\CUDA\h38pe\deps\bindeps.jl:314
 [3] __runtime_init__ () at C:\Users\andre\.julia\packages\CUDA\h38pe\src\initialization.jl:112
 [4] (::CUDA.var"#609#610"{Bool})() at C:\Users\andre\.julia\packages\CUDA\h38pe\src\initialization.jl:32
 [5] lock(::CUDA.var"#609#610"{Bool}, ::ReentrantLock) at .\lock.jl:161
 [6] _functional(::Bool) at C:\Users\andre\.julia\packages\CUDA\h38pe\src\initialization.jl:26
 [7] functional(::Bool) at C:\Users\andre\.julia\packages\CUDA\h38pe\src\initialization.jl:19
 [8] macro expansion at C:\Users\andre\.julia\packages\CUDA\h38pe\src\initialization.jl:50 [inlined]
 [9] toolkit_release() at C:\Users\andre\.julia\packages\CUDA\h38pe\deps\bindeps.jl:32
 [10] top-level scope at C:\Users\andre\.julia\packages\CUDA\h38pe\test\runtests.jl:112
 [11] include(::String) at .\client.jl:439
 [12] top-level scope at none:6
in expression starting at C:\Users\andre\.julia\packages\CUDA\h38pe\test\runtests.jl:112
ERROR: Package CUDA errored during testing
Stacktrace:
 [1] pkgerror(::String, ::Vararg{String,N} where N) at D:\buildbot\worker\package_win64\build\usr\share\julia\stdlib\v1.4\Pkg\src\Types.jl:53   
 [2] test(::Pkg.Types.Context, ::Array{Pkg.Types.PackageSpec,1}; coverage::Bool, julia_args::Cmd, test_args::Cmd, test_fn::Nothing) at D:\buildbot\worker\package_win64\build\usr\share\julia\stdlib\v1.4\Pkg\src\Operations.jl:1510
 [3] test(::Pkg.Types.Context, ::Array{Pkg.Types.PackageSpec,1}; coverage::Bool, test_fn::Nothing, julia_args::Cmd, test_args::Cmd, kwargs::Base.Iterators.Pairs{Union{},Union{},Tuple{},NamedTuple{(),Tuple{}}}) at D:\buildbot\worker\package_win64\build\usr\share\julia\stdlib\v1.4\Pkg\src\API.jl:316
 [4] test(::Pkg.Types.Context, ::Array{Pkg.Types.PackageSpec,1}) at D:\buildbot\worker\package_win64\build\usr\share\julia\stdlib\v1.4\Pkg\src\API.jl:303
 [5] #test#68 at D:\buildbot\worker\package_win64\build\usr\share\julia\stdlib\v1.4\Pkg\src\API.jl:297 [inlined]
 [6] test at D:\buildbot\worker\package_win64\build\usr\share\julia\stdlib\v1.4\Pkg\src\API.jl:297 [inlined]
 [7] #test#67 at D:\buildbot\worker\package_win64\build\usr\share\julia\stdlib\v1.4\Pkg\src\API.jl:296 [inlined]
 [8] test at D:\buildbot\worker\package_win64\build\usr\share\julia\stdlib\v1.4\Pkg\src\API.jl:296 [inlined]
 [9] test(::String; kwargs::Base.Iterators.Pairs{Union{},Union{},Tuple{},NamedTuple{(),Tuple{}}}) at D:\buildbot\worker\package_win64\build\usr\share\julia\stdlib\v1.4\Pkg\src\API.jl:295
 [10] test(::String) at D:\buildbot\worker\package_win64\build\usr\share\julia\stdlib\v1.4\Pkg\src\API.jl:295
 [11] top-level scope at none:0

```

aj

---

<div class="post-metadata">

**Author:** ![anj](https://avatars.discourse-cdn.com/v4/letter/a/779978/32.png) [@anj](https://discourse.julialang.org/u/anj)\
**Post date:** [July 20, 2020, 2:27pm UTC](https://discourse.julialang.org/t/cuda-jl-tests-on-windows/43378/2 "2020-07-20T14:27:56Z")

</div>

ok. Maybe there is something going on with artifact download. So I try using the ones coming with local CUDA installation from Nvidia. here is that I am getting

```julia
Status `C:\Users\andre\AppData\Local\Temp\jl_zbZb7L\Manifest.toml`
  [621f4979] AbstractFFTs v0.5.0
  [79e6a3ab] Adapt v2.0.2
  [b99e7846] BinaryProvider v0.5.10
  [fa961155] CEnum v0.4.1
  [052768ef] CUDA v1.2.0
  [bbf7d656] CommonSubexpressions v0.3.0
  [e66e0078] CompilerSupportLibraries_jll v0.3.3+0
  [adafc99b] CpuId v0.2.2
  [864edb3b] DataStructures v0.17.19
  [163ba53b] DiffResults v1.0.2     
  [b552c78f] DiffRules v1.0.1       
  [ffbed154] DocStringExtensions v0.8.2
  [e2ba6199] ExprTools v0.1.1
  [7a1cc6ca] FFTW v1.2.2
  [f5851436] FFTW_jll v3.3.9+5
  [1a297f60] FillArrays v0.8.13
  [f6369f11] ForwardDiff v0.10.12
  [0c68f7d7] GPUArrays v4.0.1
  [61eb1bfa] GPUCompiler v0.5.3
  [1d5cc7b8] IntelOpenMP_jll v2018.0.3+0
  [929cbde3] LLVM v2.0.0
  [bdcacae8] LoopVectorization v0.8.18
  [856f044c] MKL_jll v2020.1.216+0
  [1914dd2f] MacroTools v0.5.5
  [a6bfbf70] NNPACK_jll v2018.6.22+0
  [872c559c] NNlib v0.7.3
  [77ba4419] NaNMath v0.3.4
  [6fe1bfb0] OffsetArrays v1.1.1
  [efe28fd5] OpenSpecFun_jll v0.5.3+3
  [bac558e1] OrderedCollections v1.3.0
  [189a3867] Reexport v0.2.0
  [ae029012] Requires v1.0.1
  [21efa798] SIMDPirates v0.8.16
  [476501e8] SLEEFPirates v0.5.4
  [276daf66] SpecialFunctions v0.10.3
  [90137ffa] StaticArrays v0.12.4
  [a759f4b9] TimerOutputs v0.5.6
  [3a884ed6] UnPack v1.0.1
  [3d5dd08c] VectorizationBase v0.12.24
  [2a0f44e3] Base64
  [ade2ca70] Dates
  [8ba89e20] Distributed
  [b77e0a4c] InteractiveUtils
  [76f85450] LibGit2
  [8f399da3] Libdl
  [37e2e46d] LinearAlgebra
  [56ddb016] Logging
  [d6f4376e] Markdown 
  [44cfe95a] Pkg
  [de0858da] Printf
  [3fa0cd96] REPL
  [9a3f8284] Random
  [ea8e919c] SHA
  [9e88b42a] Serialization
  [6462fe0b] Sockets
  [2f01184e] SparseArrays
  [10745b16] Statistics
  [8dfed614] Test
  [cf7118a7] UUIDs
  [4ec0a83e] Unicode
┌ Info: System information:
│ CUDA toolkit 11.0.194, local 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: missing
│ - NVML: 11.0.0+451.67
│ - CUDNN: missing
│ - CUTENSOR: missing
│ 
│ Toolchain:
│ - Julia: 1.4.2
│ - LLVM: 8.0.1
│ - PTX ISA support: 3.2, 4.0, 4.1, 4.2, 4.3, 5.0, 6.0, 6.1, 6.3
│ - Device support: sm_35, sm_37, sm_50, sm_52, sm_53, sm_60, sm_61, sm_62, sm_70, sm_72, sm_75
│ 
│ Environment:
│ - JULIA_CUDA_VERBOSE: true
│ - JULIA_CUDA_USE_BINARYBUILDER: false
│ 
│ 2 device(s):
│ - GeForce RTX 2070 (sm_75, 7.843 GiB / 8.000 GiB available)
└ - GeForce RTX 2080 Ti (sm_75, 10.790 GiB / 11.000 GiB available)
[ Info: Testing using device 2 (GeForce RTX 2080 Ti, UUID 4d228dab-1287-5f37-f4db-e53f82e2bc60)
[ Info: Skipping the following tests: cudnn, cutensor, device\wmma
                                      | | ---------------- GPU ---------------- | ---------------- CPU ---------------- |
Test (Worker) | Time (s) | GC (s) | GC % | Alloc (MB) | RSS (MB) | GC (s) | GC % | Alloc (MB) | RSS (MB) |
initialization (2) | failed at 2020-07-20T15:51:54.047
apiutils (3) | failed at 2020-07-20T15:51:54.253
codegen (6) | failed at 2020-07-20T15:52:10.367
curand (9) | failed at 2020-07-20T15:52:14.689
iterator (15) | failed at 2020-07-20T15:52:22.522
broadcast (5) | failed at 2020-07-20T15:52:30.061

```

---

<div class="post-metadata">

**Author:** ![anj](https://avatars.discourse-cdn.com/v4/letter/a/779978/32.png) [@anj](https://discourse.julialang.org/u/anj)\
**Post date:** [July 20, 2020, 2:38pm UTC](https://discourse.julialang.org/t/cuda-jl-tests-on-windows/43378/3 "2020-07-20T14:38:05Z")

</div>

and enabling debug lines I get much larger printout than discource allows. so here: [https://pastebin.com/embed\_js/gdFEmLXZ](https://pastebin.com/embed_js/gdFEmLXZ)

---

<div class="post-metadata">

**Author:** ![maleadt](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/maleadt/32/10097_2.png) [@maleadt](https://discourse.julialang.org/u/maleadt)\
**Post date:** [July 23, 2020, 6:35am UTC](https://discourse.julialang.org/t/cuda-jl-tests-on-windows/43378/4 "2020-07-23T06:35:46Z")

</div>

[https://github.com/JuliaGPU/CUDA.jl/issues/300](https://github.com/JuliaGPU/CUDA.jl/issues/300)

---

<div class="post-metadata">

**Author:** ![maleadt](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/maleadt/32/10097_2.png) [@maleadt](https://discourse.julialang.org/u/maleadt)\
**Post date:** [July 23, 2020, 1:20pm UTC](https://discourse.julialang.org/t/cuda-jl-tests-on-windows/43378/5 "2020-07-23T13:20:08Z")

</div>

Should be fixed on CUDA master, would be useful if you could verify that (also requires GPUArrays#master).

---

<div class="post-metadata">

**Author:** ![anj](https://avatars.discourse-cdn.com/v4/letter/a/779978/32.png) [@anj](https://discourse.julialang.org/u/anj)\
**Post date:** [July 23, 2020, 3:58pm UTC](https://discourse.julialang.org/t/cuda-jl-tests-on-windows/43378/6 "2020-07-23T15:58:50Z")

</div>

with local installation I now get

```julia
┌ Error: Exception while generating log record in module CUDA at C:\Users\andre\.julia\packages\CUDA\B3eVM\deps\discovery.jl:96
│ exception =
│ MethodError: no method matching iterate(::typeof(names))
│ Closest candidates are:
│ iterate(::Core.SimpleVector) at essentials.jl:603
│ iterate(::Core.SimpleVector, ::Any) at essentials.jl:603
│ iterate(::ExponentialBackOff) at error.jl:253
│ ...
│ Stacktrace:
│ [1] join(::Base.GenericIOBuffer{Array{UInt8,1}}, ::Function, ::String) at .\strings\io.jl:294
│ [2] sprint(::Function, ::Function, ::Vararg{Any,N} where N; context::Nothing, sizehint::Int64) at .\strings\io.jl:105
│ [3] sprint(::Function, ::Function, ::Vararg{Any,N} where N) at .\strings\io.jl:101
│ [4] join(::Function, ::String) at .\strings\io.jl:301
│ [5] macro expansion at .\logging.jl:322 [inlined]
│ [6] find_binary(::String; locations::Array{String,1}) at C:\Users\andre\.julia\packages\CUDA\B3eVM\deps\discovery.jl:96
│ [7] find_cuda_binary at C:\Users\andre\.julia\packages\CUDA\B3eVM\deps\discovery.jl:224 [inlined]
│ [8] use_local_cuda() at C:\Users\andre\.julia\packages\CUDA\B3eVM\deps\bindeps.jl:189
│ [9] __init_dependencies__ () at C:\Users\andre\.julia\packages\CUDA\B3eVM\deps\bindeps.jl:313
│ [10] __runtime_init__ () at C:\Users\andre\.julia\packages\CUDA\B3eVM\src\initialization.jl:112
│ [11] (::CUDA.var"#609#610"{Bool})() at C:\Users\andre\.julia\packages\CUDA\B3eVM\src\initialization.jl:32
│ [12] lock(::CUDA.var"#609#610"{Bool}, ::ReentrantLock) at .\lock.jl:161
│ [13] _functional(::Bool) at C:\Users\andre\.julia\packages\CUDA\B3eVM\src\initialization.jl:26
│ [14] functional(::Bool) at C:\Users\andre\.julia\packages\CUDA\B3eVM\src\initialization.jl:19
│ [15] macro expansion at C:\Users\andre\.julia\packages\CUDA\B3eVM\src\initialization.jl:50 [inlined]
│ [16] toolkit_release() at C:\Users\andre\.julia\packages\CUDA\B3eVM\deps\bindeps.jl:32
│ [17] top-level scope at C:\Users\andre\.julia\packages\CUDA\B3eVM\test\runtests.jl:112
│ [18] include(::String) at .\client.jl:439
│ [19] top-level scope at none:6
│ [20] eval(::Module, ::Any) at .\boot.jl:331
│ [21] exec_options(::Base.JLOptions) at .\client.jl:264
│ [22] _start() at .\client.jl:484
└ @ CUDA C:\Users\andre\.julia\packages\CUDA\B3eVM\deps\discovery.jl:96

```

Double checking that CUDA and GPUArrays are #master

```julia
  [621f4979] AbstractFFTs v0.5.0   
  [79e6a3ab] Adapt v2.0.2
  [b99e7846] BinaryProvider v0.5.10
  [fa961155] CEnum v0.4.1
  [052768ef] CUDA v1.2.0 #master (https://github.com/JuliaGPU/CUDA.jl)
  [bbf7d656] CommonSubexpressions v0.3.0
  [e66e0078] CompilerSupportLibraries_jll v0.3.3+0
  [adafc99b] CpuId v0.2.2
  [864edb3b] DataStructures v0.17.19
  [163ba53b] DiffResults v1.0.2
  [b552c78f] DiffRules v1.0.1
  [ffbed154] DocStringExtensions v0.8.2
  [e2ba6199] ExprTools v0.1.1
  [7a1cc6ca] FFTW v1.2.2
  [f5851436] FFTW_jll v3.3.9+5
  [1a297f60] FillArrays v0.8.13
  [f6369f11] ForwardDiff v0.10.12
  [0c68f7d7] GPUArrays v4.0.1 #master (https://github.com/JuliaGPU/GPUArrays.jl)
  [61eb1bfa] GPUCompiler v0.5.3
  [1d5cc7b8] IntelOpenMP_jll v2018.0.3+0
  [929cbde3] LLVM v2.0.0
  [bdcacae8] LoopVectorization v0.8.19
  [856f044c] MKL_jll v2020.1.216+0
  [1914dd2f] MacroTools v0.5.5
  [a6bfbf70] NNPACK_jll v2018.6.22+0
  [872c559c] NNlib v0.7.3
  [77ba4419] NaNMath v0.3.4
  [6fe1bfb0] OffsetArrays v1.1.1
  [efe28fd5] OpenSpecFun_jll v0.5.3+3
  [bac558e1] OrderedCollections v1.3.0
  [189a3867] Reexport v0.2.0
  [ae029012] Requires v1.0.1
  [21efa798] SIMDPirates v0.8.17
  [476501e8] SLEEFPirates v0.5.5
  [276daf66] SpecialFunctions v0.10.3
  [90137ffa] StaticArrays v0.12.4
  [a759f4b9] TimerOutputs v0.5.6
  [3a884ed6] UnPack v1.0.1
  [3d5dd08c] VectorizationBase v0.12.25

```

---

<div class="post-metadata">

**Author:** ![anj](https://avatars.discourse-cdn.com/v4/letter/a/779978/32.png) [@anj](https://discourse.julialang.org/u/anj)\
**Post date:** [July 23, 2020, 4:09pm UTC](https://discourse.julialang.org/t/cuda-jl-tests-on-windows/43378/7 "2020-07-23T16:09:46Z")

</div>

with artifacts I get first this

```julia
┌ Debug: Selecting artifacts based on driver version 11.0.0
└ @ CUDA C:\Users\andre\.julia\packages\CUDA\B3eVM\deps\bindeps.jl:138
┌ Debug: CUDA toolkit identified as 11.0.194
└ @ CUDA C:\Users\andre\.julia\packages\CUDA\B3eVM\deps\discovery.jl:322
┌ Debug: Using CUDA 11.0.194 from an artifact at C:\Users\andre\.julia\artifacts\bbabcb11fa2760ee54b821c074b8b77699c260b3
└ @ CUDA C:\Users\andre\.julia\packages\CUDA\B3eVM\deps\bindeps.jl:177
┌ Debug: Could not use CUDNN from artifacts
│ exception =
│ KeyError: key v"11.0.0" not found
│ Stacktrace:
│ [1] getindex at .\dict.jl:477 [inlined]
│ [2] use_artifact_cudnn(::VersionNumber) at C:\Users\andre\.julia\packages\CUDA\B3eVM\deps\bindeps.jl:248
│ [3] use_artifact_cuda() at C:\Users\andre\.julia\packages\CUDA\B3eVM\deps\bindeps.jl:179
│ [4] __init_dependencies__ () at C:\Users\andre\.julia\packages\CUDA\B3eVM\deps\bindeps.jl:309
│ [5] __runtime_init__ () at C:\Users\andre\.julia\packages\CUDA\B3eVM\src\initialization.jl:112
│ [6] (::CUDA.var"#609#610"{Bool})() at C:\Users\andre\.julia\packages\CUDA\B3eVM\src\initialization.jl:32
│ [7] lock(::CUDA.var"#609#610"{Bool}, ::ReentrantLock) at .\lock.jl:161
│ [8] _functional(::Bool) at C:\Users\andre\.julia\packages\CUDA\B3eVM\src\initialization.jl:26
│ [9] functional(::Bool) at C:\Users\andre\.julia\packages\CUDA\B3eVM\src\initialization.jl:19
│ [10] macro expansion at C:\Users\andre\.julia\packages\CUDA\B3eVM\src\initialization.jl:50 [inlined]
│ [11] toolkit_release() at C:\Users\andre\.julia\packages\CUDA\B3eVM\deps\bindeps.jl:32
│ [12] top-level scope at C:\Users\andre\.julia\packages\CUDA\B3eVM\test\runtests.jl:112
│ [13] include(::String) at .\client.jl:439
│ [14] top-level scope at none:6
│ [15] eval(::Module, ::Any) at .\boot.jl:331
│ [16] exec_options(::Base.JLOptions) at .\client.jl:264
│ [17] _start() at .\client.jl:484
└ @ CUDA C:\Users\andre\.julia\packages\CUDA\B3eVM\deps\bindeps.jl:250
┌ Debug: Could not use CUTENSOR from artifacts
│ exception =
│ Cannot locate artifact 'CUTENSOR_CUDA110' in 'C:\Users\andre\.julia\packages\CUDA\B3eVM\Artifacts.toml'
│ Stacktrace:
│ [1] error(::String) at .\error.jl:33
│ [2] do_artifact_str(::String, ::Dict{String,Any}, ::String, ::Module) at D:\buildbot\worker\package_win64\build\usr\share\julia\stdlib\v1.4\Pkg\src\Artifacts.jl:1019
│ [3] #invokelatest#1 at .\essentials.jl:712 [inlined]
│ [4] invokelatest at .\essentials.jl:711 [inlined]
│ [5] macro expansion at D:\buildbot\worker\package_win64\build\usr\share\julia\stdlib\v1.4\Pkg\src\Artifacts.jl:1058 [inlined]
│ [6] (::CUDA.var"#672#675")() at C:\Users\andre\.julia\packages\CUDA\B3eVM\deps\bindeps.jl:272
│ [7] use_artifact_cutensor(::VersionNumber) at C:\Users\andre\.julia\packages\CUDA\B3eVM\deps\bindeps.jl:279
│ [8] use_artifact_cuda() at C:\Users\andre\.julia\packages\CUDA\B3eVM\deps\bindeps.jl:180
│ [9] __init_dependencies__ () at C:\Users\andre\.julia\packages\CUDA\B3eVM\deps\bindeps.jl:309
│ [10] __runtime_init__ () at C:\Users\andre\.julia\packages\CUDA\B3eVM\src\initialization.jl:112
│ [11] (::CUDA.var"#609#610"{Bool})() at C:\Users\andre\.julia\packages\CUDA\B3eVM\src\initialization.jl:32
│ [12] lock(::CUDA.var"#609#610"{Bool}, ::ReentrantLock) at .\lock.jl:161
│ [13] _functional(::Bool) at C:\Users\andre\.julia\packages\CUDA\B3eVM\src\initialization.jl:26
│ [14] functional(::Bool) at C:\Users\andre\.julia\packages\CUDA\B3eVM\src\initialization.jl:19
│ [15] macro expansion at C:\Users\andre\.julia\packages\CUDA\B3eVM\src\initialization.jl:50 [inlined]
│ [16] toolkit_release() at C:\Users\andre\.julia\packages\CUDA\B3eVM\deps\bindeps.jl:32
│ [17] top-level scope at C:\Users\andre\.julia\packages\CUDA\B3eVM\test\runtests.jl:112
│ [18] include(::String) at .\client.jl:439
│ [19] top-level scope at none:6
│ [20] eval(::Module, ::Any) at .\boot.jl:331
│ [21] exec_options(::Base.JLOptions) at .\client.jl:264
│ [22] _start() at .\client.jl:484
└ @ CUDA C:\Users\andre\.julia\packages\CUDA\B3eVM\deps\bindeps.jl:281
┌ Debug: Toolchain with LLVM 8.0.1, CUDA driver 11.0.0 and toolkit 11.0.194 supports devices 3.5, 3.7, 5.0, 5.2, 5.3, 6.0, 6.1, 6.2, 7.0, 7.2 and 7.5; PTX 3.2, 4.0, 4.1, 4.2, 4.3, 5.0, 6.0, 6.1 and 6.3
└ @ CUDA C:\Users\andre\.julia\packages\CUDA\B3eVM\deps\compatibility.jl:239
┌ Info: System information:
│ 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: missing
│ - CUTENSOR: missing
│ 
│ Toolchain:
│ - Julia: 1.4.2
│ - LLVM: 8.0.1
│ - PTX ISA support: 3.2, 4.0, 4.1, 4.2, 4.3, 5.0, 6.0, 6.1, 6.3
│ - Device support: sm_35, sm_37, sm_50, sm_52, sm_53, sm_60, sm_61, sm_62, sm_70, sm_72, sm_75
│ 
│ Environment:
│ - JULIA_CUDA_VERBOSE: true
│ 
│ 2 device(s):
│ - GeForce RTX 2070 (sm_75, 7.843 GiB / 8.000 GiB available)
└ - GeForce RTX 2080 Ti (sm_75, 10.790 GiB / 11.000 GiB available)
[ Info: Testing using device 2 (GeForce RTX 2080 Ti, UUID 4d228dab-1287-5f37-f4db-e53f82e2bc60)
[ Info: Skipping the following tests: cudnn, cutensor, device\wmma

```

and then more

```julia
┌ Debug: Could not use CUDNN from artifacts
│ exception =
│ KeyError: key v"11.0.0" not found
│ Stacktrace:
│ [1] getindex at .\dict.jl:477 [inlined]
│ [2] use_artifact_cudnn(::VersionNumber) at C:\Users\andre\.julia\packages\CUDA\B3eVM\deps\bindeps.jl:248
│ [3] use_artifact_cuda() at C:\Users\andre\.julia\packages\CUDA\B3eVM\deps\bindeps.jl:179
│ [4] __init_dependencies__ () at C:\Users\andre\.julia\packages\CUDA\B3eVM\deps\bindeps.jl:309
│ [5] __runtime_init__ () at C:\Users\andre\.julia\packages\CUDA\B3eVM\src\initialization.jl:112
│ [6] (::CUDA.var"#609#610"{Bool})() at C:\Users\andre\.julia\packages\CUDA\B3eVM\src\initialization.jl:32
│ [7] lock(::CUDA.var"#609#610"{Bool}, ::ReentrantLock) at .\lock.jl:161
│ [8] _functional(::Bool) at C:\Users\andre\.julia\packages\CUDA\B3eVM\src\initialization.jl:26
│ [9] functional(::Bool) at C:\Users\andre\.julia\packages\CUDA\B3eVM\src\initialization.jl:19
│ [10] libcuda at C:\Users\andre\.julia\packages\CUDA\B3eVM\src\initialization.jl:50 [inlined]
│ [11] (::CUDA.var"#714#cache_fptr!#47")() at C:\Users\andre\.julia\packages\CUDA\B3eVM\lib\utils\call.jl:31
│ [12] macro expansion at C:\Users\andre\.julia\packages\CUDA\B3eVM\lib\utils\call.jl:39 [inlined]
│ [13] macro expansion at C:\Users\andre\.julia\packages\CUDA\B3eVM\lib\cudadrv\libcuda.jl:149 [inlined]
│ [14] macro expansion at C:\Users\andre\.julia\packages\CUDA\B3eVM\lib\cudadrv\error.jl:108 [inlined]
│ [15] cuCtxGetCurrent(::Base.RefValue{Ptr{Nothing}}) at C:\Users\andre\.julia\packages\CUDA\B3eVM\lib\utils\call.jl:93
│ [16] CuCurrentContext at C:\Users\andre\.julia\packages\CUDA\B3eVM\lib\cudadrv\context.jl:81 [inlined]
│ [17] initialize_thread(::Int64) at C:\Users\andre\.julia\packages\CUDA\B3eVM\src\state.jl:51
│ [18] prepare_cuda_call at C:\Users\andre\.julia\packages\CUDA\B3eVM\src\state.jl:34 [inlined]
│ [19] macro expansion at C:\Users\andre\.julia\packages\CUDA\B3eVM\src\pool.jl:432 [inlined]
│ [20] top-level scope at C:\Users\andre\.julia\packages\CUDA\B3eVM\test\setup.jl:46
│ [21] eval at .\boot.jl:331 [inlined]
│ [22] runtests(::Function, ::String, ::Bool, ::Nothing) at C:\Users\andre\.julia\packages\CUDA\B3eVM\test\setup.jl:56
│ [23] (::Distributed.var"#104#106"{Distributed.CallMsg{:call_fetch}})() at D:\buildbot\worker\package_win64\build\usr\share\julia\stdlib\v1.4\Distributed\src\process_messages.jl:294
│ [24] run_work_thunk(::Distributed.var"#104#106"{Distributed.CallMsg{:call_fetch}}, ::Bool) at D:\buildbot\worker\package_win64\build\usr\share\julia\stdlib\v1.4\Distributed\src\process_messages.jl:79
│ [25] macro expansion at D:\buildbot\worker\package_win64\build\usr\share\julia\stdlib\v1.4\Distributed\src\process_messages.jl:294 [inlined]
│ [26] (::Distributed.var"#103#105"{Distributed.CallMsg{:call_fetch},Distributed.MsgHeader,Sockets.TCPSocket})() at .\task.jl:358
└ @ CUDA C:\Users\andre\.julia\packages\CUDA\B3eVM\deps\bindeps.jl:250

```

---

<div class="post-metadata">

**Author:** ![maleadt](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/maleadt/32/10097_2.png) [@maleadt](https://discourse.julialang.org/u/maleadt)\
**Post date:** [July 24, 2020, 6:20am UTC](https://discourse.julialang.org/t/cuda-jl-tests-on-windows/43378/8 "2020-07-24T06:20:43Z")

</div>

> [@anj](#):
>
> ```julia
> ┌ Error: Exception while generating log record in module CUDA at C:\Users\andre\.julia\packages\CUDA\B3eVM\deps\discovery.jl:96
> │ exception =
> │ MethodError: no method matching iterate(::typeof(names))
> │ Closest candidates are:
> │ iterate(::Core.SimpleVector) at essentials.jl:603
> │ iterate(::Core.SimpleVector, ::Any) at essentials.jl:603
> │ iterate(::ExponentialBackOff) at error.jl:253
> 
> ```

Ah yes, a typo in the debug printing. Fixed!

> [@anj](#):
>
> ```julia
> ┌ Debug: Could not use CUDNN from artifacts
> │ exception =
> │ KeyError: key v"11.0.0" not found
> 
> ```

This is expected, and only a debug message. There wasn’t a CUDNN for CUDA 11 last I checked (only a release candidate).

---

<div class="post-metadata">

**Author:** ![anj](https://avatars.discourse-cdn.com/v4/letter/a/779978/32.png) [@anj](https://discourse.julialang.org/u/anj)\
**Post date:** [July 24, 2020, 8:24am UTC](https://discourse.julialang.org/t/cuda-jl-tests-on-windows/43378/9 "2020-07-24T08:24:41Z")

</div>

now local installation fails with no obvious (to me) reason  
[https://pastebin.com/dn5QRyqr](https://pastebin.com/dn5QRyqr)

downloaded artifacts  
[https://pastebin.com/fHf7eQuw](https://pastebin.com/fHf7eQuw)

---

<div class="post-metadata">

**Author:** ![maleadt](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/maleadt/32/10097_2.png) [@maleadt](https://discourse.julialang.org/u/maleadt)\
**Post date:** [July 24, 2020, 9:00am UTC](https://discourse.julialang.org/t/cuda-jl-tests-on-windows/43378/10 "2020-07-24T09:00:35Z")

</div>

There are no errors in those logs, and your toolchain is correctly discovered. Try calling `CUDA.versioninfo()`. At the end of the logs, there’s test failures, but without a stack trace so its unclear what the cause is (did you press CTRL-C?)

---

<div class="post-metadata">

**Author:** ![anj](https://avatars.discourse-cdn.com/v4/letter/a/779978/32.png) [@anj](https://discourse.julialang.org/u/anj)\
**Post date:** [July 24, 2020, 11:46am UTC](https://discourse.julialang.org/t/cuda-jl-tests-on-windows/43378/11 "2020-07-24T11:46:12Z")

</div>

Sorry about that. Yes, I pressed Ctrl+C after first test fail messages. so now I run it fully.

I get a lot of those

```julia
Status `C:\Users\andre\AppData\Local\Temp\jl_7lNIMd\Manifest.toml`
  [621f4979] AbstractFFTs v0.5.0
  [79e6a3ab] Adapt v2.0.2
  [b99e7846] BinaryProvider v0.5.10
  [fa961155] CEnum v0.4.1
  [052768ef] CUDA v1.2.0 #master (https://github.com/JuliaGPU/CUDA.jl)
  [bbf7d656] CommonSubexpressions v0.3.0
  [e66e0078] CompilerSupportLibraries_jll v0.3.3+0
  [adafc99b] CpuId v0.2.2
  [864edb3b] DataStructures v0.17.19
  [163ba53b] DiffResults v1.0.2
  [b552c78f] DiffRules v1.0.1
  [ffbed154] DocStringExtensions v0.8.2
  [e2ba6199] ExprTools v0.1.1
  [7a1cc6ca] FFTW v1.2.2
  [f5851436] FFTW_jll v3.3.9+5
  [1a297f60] FillArrays v0.8.13
  [f6369f11] ForwardDiff v0.10.12
  [0c68f7d7] GPUArrays v4.0.1 #master (https://github.com/JuliaGPU/GPUArrays.jl)
  [61eb1bfa] GPUCompiler v0.5.3
  [1d5cc7b8] IntelOpenMP_jll v2018.0.3+0
  [929cbde3] LLVM v2.0.0
  [bdcacae8] LoopVectorization v0.8.19
  [856f044c] MKL_jll v2020.1.216+0
  [1914dd2f] MacroTools v0.5.5
  [a6bfbf70] NNPACK_jll v2018.6.22+0
  [872c559c] NNlib v0.7.3
  [77ba4419] NaNMath v0.3.4
  [6fe1bfb0] OffsetArrays v1.1.1
  [efe28fd5] OpenSpecFun_jll v0.5.3+3
  [bac558e1] OrderedCollections v1.3.0
  [189a3867] Reexport v0.2.0
  [ae029012] Requires v1.0.1
  [21efa798] SIMDPirates v0.8.17
  [476501e8] SLEEFPirates v0.5.5
  [276daf66] SpecialFunctions v0.10.3
  [90137ffa] StaticArrays v0.12.4
  [a759f4b9] TimerOutputs v0.5.6
  [3a884ed6] UnPack v1.0.1
  [3d5dd08c] VectorizationBase v0.12.25
  [2a0f44e3] Base64
  [ade2ca70] Dates
  [8ba89e20] Distributed
  [b77e0a4c] InteractiveUtils
  [76f85450] LibGit2
  [8f399da3] Libdl
  [37e2e46d] LinearAlgebra
  [56ddb016] Logging
  [d6f4376e] Markdown
  [44cfe95a] Pkg
  [de0858da] Printf
  [3fa0cd96] REPL
  [9a3f8284] Random
  [ea8e919c] SHA
  [9e88b42a] Serialization
  [6462fe0b] Sockets
  [2f01184e] SparseArrays
  [10745b16] Statistics
  [8dfed614] Test 
  [cf7118a7] UUIDs
  [4ec0a83e] Unicode
┌ Info: System information:
│ 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: missing
│ - CUTENSOR: missing
│ 
│ Toolchain:
│ - Julia: 1.4.2
│ - LLVM: 8.0.1
│ - PTX ISA support: 3.2, 4.0, 4.1, 4.2, 4.3, 5.0, 6.0, 6.1, 6.3
│ - Device support: sm_35, sm_37, sm_50, sm_52, sm_53, sm_60, sm_61, sm_62, sm_70, sm_72, sm_75
│ 
│ Environment:
│ - JULIA_CUDA_VERBOSE: true
│ 
│ 2 device(s):
│ - GeForce RTX 2070 (sm_75, 7.843 GiB / 8.000 GiB available)
└ - GeForce RTX 2080 Ti (sm_75, 10.790 GiB / 11.000 GiB available)
[ Info: Testing using device 2 (GeForce RTX 2080 Ti, UUID 4d228dab-1287-5f37-f4db-e53f82e2bc60)
[ Info: Skipping the following tests: cudnn, cutensor, device\wmma
                                      | | ---------------- GPU ---------------- | ---------------- CPU ---------------- |
Test (Worker) | Time (s) | GC (s) | GC % | Alloc (MB) | RSS (MB) | GC (s) | GC % | Alloc (MB) | RSS (MB) |  
initialization (2) | failed at 2020-07-24T13:27:34.893
apiutils (3) | failed at 2020-07-24T13:27:35.226
codegen (6) | failed at 2020-07-24T13:27:53.291
curand (9) | failed at 2020-07-24T13:27:57.349
iterator (15) | failed at 2020-07-24T13:28:04.485
cufft (8) | failed at 2020-07-24T13:28:13.621
broadcast (5) | failed at 2020-07-24T13:28:14.394
memory (16) | failed at 2020-07-24T13:28:20.196
nvml (18) | failed at 2020-07-24T13:28:30.279
cusparse (11) | failed at 2020-07-24T13:28:31.791
nnlib (17) | failed at 2020-07-24T13:28:37.649
nvtx (19) | failed at 2020-07-24T13:28:39.256
pointer (20) | failed at 2020-07-24T13:28:40.567
array (4) | failed at 2020-07-24T13:28:47.409
cublas (7) | failed at 2020-07-24T13:28:50.406
forwarddiff (14) | failed at 2020-07-24T13:28:57.716
cusolver (10) | failed at 2020-07-24T13:28:59.912
utils (24) | failed at 2020-07-24T13:29:05.855
cudadrv\context (25) | failed at 2020-07-24T13:29:06.031
cudadrv\devices (26) | failed at 2020-07-24T13:29:06.953
threading (23) | failed at 2020-07-24T13:29:14.078
cudadrv\errors (27) | failed at 2020-07-24T13:29:14.339
statistics (21) | failed at 2020-07-24T13:29:15.874
cudadrv\events (28) | failed at 2020-07-24T13:29:16.084
cudadrv\execution (29) | failed at 2020-07-24T13:29:26.568
cudadrv\memory (30) | failed at 2020-07-24T13:29:27.926
cudadrv\occupancy (32) | failed at 2020-07-24T13:29:32.272
cudadrv\module (31) | failed at 2020-07-24T13:29:32.563
cudadrv\profile (33) | failed at 2020-07-24T13:29:33.742
texture (22) | failed at 2020-07-24T13:29:35.591
cudadrv\stream (34) | failed at 2020-07-24T13:29:39.586
cudadrv\version (35) | failed at 2020-07-24T13:29:40.345
device\array (37) | failed at 2020-07-24T13:29:58.933
examples (12) | failed at 2020-07-24T13:29:59.271
gpuarrays/input output (42) | failed at 2020-07-24T13:30:01.632
device\pointer (39) | failed at 2020-07-24T13:30:11.444
cusolver\cusparse (36) | failed at 2020-07-24T13:30:13.575
gpuarrays/math (41) | failed at 2020-07-24T13:30:14.664
execution (13) | failed at 2020-07-24T13:30:17.007
gpuarrays/interface (44) | failed at 2020-07-24T13:30:19.197
gpuarrays/value constructors (43) | failed at 2020-07-24T13:30:23.082
gpuarrays/indexing (40) | failed at 2020-07-24T13:30:30.843
gpuarrays/conversions (48) | failed at 2020-07-24T13:30:33.976
gpuarrays/iterator constructors (45) | failed at 2020-07-24T13:30:38.571
gpuarrays/constructors (50) | failed at 2020-07-24T13:30:41.724
gpuarrays/uniformscaling (46) | failed at 2020-07-24T13:30:45.063
gpuarrays/fft (49) | failed at 2020-07-24T13:30:45.665
gpuarrays/base (52) | failed at 2020-07-24T13:31:12.59
gpuarrays/random (51) | failed at 2020-07-24T13:31:14.822
device\intrinsics (38) | failed at 2020-07-24T13:31:16.072
gpuarrays/linear algebra (47) | failed at 2020-07-24T13:31:33.447
gpuarrays/broadcasting (54) | failed at 2020-07-24T13:31:57.442
gpuarrays/mapreduce essentials (53) | failed at 2020-07-24T13:32:22.903
gpuarrays/mapreduce (old tests) (56) | failed at 2020-07-24T13:32:40.311
gpuarrays/mapreduce derivatives (55) | failed at 2020-07-24T13:33:17.178
initialization: Error During Test at none:1
  Test threw exception
  Expression: initialization
  On worker 2:
  InexactError: check_top_bit(Int64, 18446744073709551615)
  throw_inexacterror at .\boot.jl:557
  check_top_bit at .\boot.jl:571 [inlined]
  toInt64 at .\boot.jl:632 [inlined]
  Int64 at .\boot.jl:707 [inlined]
  #448 at .\none:0 [inlined]
  iterate at .\generator.jl:47 [inlined]
  _all at .\reduce.jl:819 [inlined]
  all at .\reduce.jl:815 [inlined]
  Dict at .\dict.jl:130
  compute_processes at C:\Users\andre\.julia\packages\CUDA\Wfh4d\lib\nvml\device.jl:123 [inlined]
  runtests at C:\Users\andre\.julia\packages\CUDA\Wfh4d\test\setup.jl:64
  #104 at D:\buildbot\worker\package_win64\build\usr\share\julia\stdlib\v1.4\Distributed\src\process_messages.jl:294
  run_work_thunk at D:\buildbot\worker\package_win64\build\usr\share\julia\stdlib\v1.4\Distributed\src\process_messages.jl:79       
  macro expansion at D:\buildbot\worker\package_win64\build\usr\share\julia\stdlib\v1.4\Distributed\src\process_messages.jl:294 [inlined]
  #103 at .\task.jl:358

```

also this type

```julia
Worker 6 failed running test codegen:
Some tests did not pass: 17 passed, 1 failed, 0 errored, 0 broken.
codegen: Test Failed at C:\Users\andre\.julia\packages\CUDA\Wfh4d\test\codegen.jl:78
  Expression: !(occursin("gpu_report_exception", ir))
   Evaluated: !(occursin("gpu_report_exception", "\n; @ C:\\Users\\andre\\.julia\\packages\\CUDA\\Wfh4d\\test\\codegen.jl:76 within `bar'\n; Function Attrs: uwtable\ndefine i64 @julia_bar_19729(i64) local_unnamed_addr #0 {\ntop:\n; ┌ @ operators.jl:294 within `>'\n; │┌ @ int.jl:49 within `<'\n %1 = icmp sgt i64 %0, 0\n; └└\n; ┌ @ C:\\Users\\andre\\.julia\\packages\\CUDA\\Wfh4d\\src\\device\\llvm.jl:5 within `assume'\n %2 = call fastcc %jl_value_t addrspace(10)* @gpu_gc_pool_alloc(i64 16)\n %3 = addrspacecast %jl_value_t addrspace(10)* %2 to %jl_value_t addrspace(11)*\n %4 = bitcast %jl_value_t addrspace(10)* %2 to %jl_value_t addrspace(10)* addrspace(10)*\n store %jl_value_t addrspace(10)* addrspacecast (%jl_value_t* inttoptr (i64 381362496 to %jl_value_t*) to %jl_value_t addrspace(10)*), %jl_value_t addrspace(10)* addrspace(10)* %4, align 8\n %5 = bitcast %jl_value_t addrspace(11)* %3 to i8 addrspace(11)*\n %6 = getelementptr inbounds i8, i8 addrspace(11)* %5, i64 8\n %7 = bitcast i8 addrspace(11)* %6 to %jl_value_t addrspace(10)* addrspace(11)*\n store %jl_value_t addrspace(10)* addrspacecast (%jl_value_t* inttoptr (i64 1031050640 to %jl_value_t*) 
to %jl_value_t addrspace(10)*), %jl_value_t addrspace(10)* addrspace(11)* %7, align 8\n call void @llvm.assume(i1 %1)\n; └\n; ┌ @ 
div.jl:227 within `cld'\n; │┌ @ div.jl:270 within `div' @ div.jl:215 @ int.jl:230\n %8 = icmp eq i64 %0, 0\n br i1 %8, label %fail, label %pass\n\nfail: ; preds = %top\n call fastcc void @gpu_report_exception(i64 ptrtoint ([10 x i8]* @exception to i64))\n call fastcc void @gpu_signal_exception()\n call void asm sideeffect \"exit;\", \"\"() #1\n br label %pass\n\npass: ; preds = %top, %fail\n %9 = udiv i64 42, %0\n; 
││ @ div.jl:271 within `div'\n; ││┌ @ int.jl:54 within `*'\n %10 = mul i64 %9, %0\n; ││└\n; ││┌ @ operators.jl:193 within `!='\n; │││┌ @ promotion.jl:398 within `=='\n %11 = icmp ne i64 %10, 42\n; ││└└\n; ││┌ @ int.jl:858 within `+'\n; │││┌ @ int.jl:442 within `rem'\n; ││││┌ @ number.jl:7 within `convert'\n; │││││┌ @ boot.jl:707 within `Int64'\n; ││││││┌ @ boot.jl:634 within `toInt64'\n %12 = zext i1 %11 to i64\n; │││└└└└\n; │││ @ int.jl:860 within `+' @ int.jl:53\n %13 = add nuw nsw i64 %9, %12\n; └└└\n ret i64 %13\n}\n"))
Stacktrace:
 [1] record(::Test.DefaultTestSet, ::Union{Test.Error, Test.Fail}) at D:\buildbot\worker\package_win64\build\usr\share\julia\stdlib\v1.4\Test\src\Test.jl:775
 [2] top-level scope at C:\Users\andre\.julia\packages\CUDA\Wfh4d\test\runtests.jl:442
 [3] include(::String) at .\client.jl:439
 [4] top-level scope at none:6
 [5] eval(::Module, ::Any) at .\boot.jl:331
 [6] exec_options(::Base.JLOptions) at .\client.jl:264
 [7] _start() at .\client.jl:484

```

then a lot of those

```julia
Worker 13 failed running test execution:
Some tests did not pass: 72 passed, 8 failed, 0 errored, 0 broken.
execution: Test Failed at C:\Users\andre\.julia\packages\CUDA\Wfh4d\test\execution.jl:568
  Expression: code == 1
   Evaluated: 0 == 1
Stacktrace:
 [1] record(::Test.DefaultTestSet, ::Union{Test.Error, Test.Fail}) at D:\buildbot\worker\package_win64\build\usr\share\julia\stdlib\v1.4\Test\src\Test.jl:775
 [2] top-level scope at C:\Users\andre\.julia\packages\CUDA\Wfh4d\test\runtests.jl:442
 [3] include(::String) at .\client.jl:439
 [4] top-level scope at none:6
 [5] eval(::Module, ::Any) at .\boot.jl:331
 [6] exec_options(::Base.JLOptions) at .\client.jl:264
 [7] _start() at .\client.jl:484

```

The actual result

```julia
Test Summary: | Pass Fail Error Total
  Overall | 89 9 53 151
    initialization | 1 1
    apiutils | 1 1
    codegen | 17 1 18
    curand | 1 1
    iterator | 1 1
    cufft | 1 1
    broadcast | 1 1
    memory | 1 1
    nvml | 1 1
    cusparse | 1 1
    nnlib | 1 1
    nvtx | 1 1
    pointer | 1 1
    array | 1 1
    cublas | 1 1
    forwarddiff | 1 1
    cusolver | 1 1
    utils | 1 1
    cudadrv\context | 1 1
    cudadrv\devices | 1 1
    threading | 1 1
    cudadrv\errors | 1 1
    statistics | 1 1
    cudadrv\events | 1 1
    cudadrv\execution | 1 1
    cudadrv\memory | 1 1
    cudadrv\occupancy | 1 1
    cudadrv\module | 1 1
    cudadrv\profile | 1 1
    texture | 1 1
    cudadrv\stream | 1 1
    cudadrv\version | 1 1
    device\array | 1 1
    examples | 1 1
    gpuarrays/input output | 1 1
    device\pointer | 1 1
    cusolver\cusparse | 1 1
    gpuarrays/math | 1 1
    execution | 72 8 80
    gpuarrays/interface | 1 1
    gpuarrays/value constructors | 1 1
    gpuarrays/indexing | 1 1
    gpuarrays/conversions | 1 1
    gpuarrays/iterator constructors | 1 1
    gpuarrays/constructors | 1 1
    gpuarrays/uniformscaling | 1 1
    gpuarrays/fft | 1 1
    gpuarrays/base | 1 1
    gpuarrays/random | 1 1
    device\intrinsics | 1 1
    gpuarrays/linear algebra | 1 1
    gpuarrays/broadcasting | 1 1
    gpuarrays/mapreduce essentials | 1 1
    gpuarrays/mapreduce (old tests) | 1 1
    gpuarrays/mapreduce derivatives | 1 1

```

I case I missed something important. here whole thing

[https://pastebin.com/hvszZz9i](https://pastebin.com/hvszZz9i)

---

<div class="post-metadata">

**Author:** ![maleadt](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/maleadt/32/10097_2.png) [@maleadt](https://discourse.julialang.org/u/maleadt)\
**Post date:** [July 24, 2020, 11:55am UTC](https://discourse.julialang.org/t/cuda-jl-tests-on-windows/43378/12 "2020-07-24T11:55:41Z")

</div>

Weirdly, the process IDs returned there aren’t valid. Could you try the following code:

```julia
julia> using CUDA

julia> CuArray([1]); # to initialize CUDA

julia> using .NVML

julia> count_ref = Ref{Cuint}(0);

julia> dev = first(NVML.devices())
CUDA.NVML.Device(Ptr{Nothing} @0x00007fde5d7aae38)

julia> NVML.nvmlDeviceGetComputeRunningProcesses(dev, count_ref, C_NULL)
ERROR: NVMLError: Insufficient Size (code 7)

julia> # NVML_ERROR_INSUFFICIENT_SIZE is expected here

julia> count_ref[]
0x00000003

julia> infos = Vector{NVML.nvmlProcessInfo_t}(undef, count_ref[]);

julia> NVML.nvmlDeviceGetComputeRunningProcesses(dev, count_ref, infos)

julia> infos
3-element Array{CUDA.NVML.nvmlProcessInfo_st,1}:
 CUDA.NVML.nvmlProcessInfo_st(0x0000cb97, 0x000000000cd00000)
 CUDA.NVML.nvmlProcessInfo_st(0x0000fe64, 0x0000000008f00000)
 CUDA.NVML.nvmlProcessInfo_st(0x00010c92, 0x0000000007500000)

```

Note that the failures are in the code that reports test output, actual functionality is likely working perfectly.

---

<div class="post-metadata">

**Author:** ![anj](https://avatars.discourse-cdn.com/v4/letter/a/779978/32.png) [@anj](https://discourse.julialang.org/u/anj)\
**Post date:** [July 24, 2020, 12:09pm UTC](https://discourse.julialang.org/t/cuda-jl-tests-on-windows/43378/13 "2020-07-24T12:09:14Z")

</div>

```julia
julia> using CUDA

julia> 

julia> CuArray([1]); # to initialize CUDA

julia> 

julia> using .NVML

julia> 

julia> count_ref = Ref{Cuint}(0);

julia> 

julia> dev = first(NVML.devices())
CUDA.NVML.Device(Ptr{Nothing} @0x00007ffd42659c20)

julia> 

julia> NVML.nvmlDeviceGetComputeRunningProcesses(dev, count_ref, C_NULL)

julia> 

julia> count_ref[]
0x00000000

julia>

julia> infos = Vector{NVML.nvmlProcessInfo_t}(undef, count_ref[]);

julia>

julia> NVML.nvmlDeviceGetComputeRunningProcesses(dev, count_ref, infos)

julia>

julia> infos
0-element Array{CUDA.NVML.nvmlProcessInfo_st,1}

```

---

<div class="post-metadata">

**Author:** ![maleadt](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/maleadt/32/10097_2.png) [@maleadt](https://discourse.julialang.org/u/maleadt)\
**Post date:** [July 24, 2020, 3:11pm UTC](https://discourse.julialang.org/t/cuda-jl-tests-on-windows/43378/14 "2020-07-24T15:11:01Z")

</div>

Looks like CUDA didn’t initialize. Can you add a `@show infos` in `compute_processes` before it errors on line 123 (and then run the tests)?

---

<div class="post-metadata">

**Author:** ![anj](https://avatars.discourse-cdn.com/v4/letter/a/779978/32.png) [@anj](https://discourse.julialang.org/u/anj)\
**Post date:** [July 24, 2020, 3:35pm UTC](https://discourse.julialang.org/t/cuda-jl-tests-on-windows/43378/15 "2020-07-24T15:35:38Z")

</div>

all workers seem to report this

```julia
From worker 2: infos = CUDA.NVML.nvmlProcessInfo_st[CUDA.NVML.nvmlProcessInfo_st(0x00002fb0, 0xffffffffffffffff), 
CUDA.NVML.nvmlProcessInfo_st(0x00004e94, 0xffffffffffffffff), CUDA.NVML.nvmlProcessInfo_st(0x000084ec, 0xffffffffffffffff), CUDA.NVML.nvmlProcessInfo_st(0x00002d28, 0xffffffffffffffff), CUDA.NVML.nvmlProcessInfo_st(0x0000808c, 0xffffffffffffffff), CUDA.NVML.nvmlProcessInfo_st(0x00009114, 0xffffffffffffffff), CUDA.NVML.nvmlProcessInfo_st(0x0000971c, 0xffffffffffffffff), CUDA.NVML.nvmlProcessInfo_st(0x00000fe8, 0xffffffffffffffff), CUDA.NVML.nvmlProcessInfo_st(0x00003b30, 0xffffffffffffffff), CUDA.NVML.nvmlProcessInfo_st(0x00004e98, 0xffffffffffffffff), CUDA.NVML.nvmlProcessInfo_st(0x00007a1c, 0xffffffffffffffff), CUDA.NVML.nvmlProcessInfo_st(0x00002084, 0xffffffffffffffff)]

```

---

<div class="post-metadata">

**Author:** ![maleadt](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/maleadt/32/10097_2.png) [@maleadt](https://discourse.julialang.org/u/maleadt)\
**Post date:** [July 24, 2020, 3:37pm UTC](https://discourse.julialang.org/t/cuda-jl-tests-on-windows/43378/16 "2020-07-24T15:37:54Z")

</div>

Aha, it’s not the PID but the usedGpuMemory that’s unavailable here. I’ll push a fix.  
[https://github.com/JuliaGPU/CUDA.jl/pull/314](https://github.com/JuliaGPU/CUDA.jl/pull/314)

```julia
       unsigned long long usedGpuMemory
           Amount of used GPU memory in bytes. Under WDDM, NVML_VALUE_NOT_AVAILABLE is always
           reported because Windows KMD manages all the memory and not the NVIDIA driver.

```

---

<div class="post-metadata">

**Author:** ![anj](https://avatars.discourse-cdn.com/v4/letter/a/779978/32.png) [@anj](https://discourse.julialang.org/u/anj)\
**Post date:** [July 24, 2020, 6:18pm UTC](https://discourse.julialang.org/t/cuda-jl-tests-on-windows/43378/17 "2020-07-24T18:18:57Z")

</div>

Yes, above is helping. only some tests are failing now

```julia
Status `C:\Users\andre\AppData\Local\Temp\jl_zJKTY5\Manifest.toml`
  [621f4979] AbstractFFTs v0.5.0
  [79e6a3ab] Adapt v2.0.2
  [b99e7846] BinaryProvider v0.5.10
  [fa961155] CEnum v0.4.1
  [052768ef] CUDA v1.2.0 [`C:\Src\cuda\cuda\dev\CUDA`]
  [bbf7d656] CommonSubexpressions v0.3.0
  [e66e0078] CompilerSupportLibraries_jll v0.3.3+0
  [adafc99b] CpuId v0.2.2
  [864edb3b] DataStructures v0.17.19
  [163ba53b] DiffResults v1.0.2
  [b552c78f] DiffRules v1.0.1
  [ffbed154] DocStringExtensions v0.8.2
  [e2ba6199] ExprTools v0.1.1
  [7a1cc6ca] FFTW v1.2.2
  [f5851436] FFTW_jll v3.3.9+5
  [1a297f60] FillArrays v0.8.13
  [f6369f11] ForwardDiff v0.10.12
  [0c68f7d7] GPUArrays v4.0.1 #master (https://github.com/JuliaGPU/GPUArrays.jl)
  [61eb1bfa] GPUCompiler v0.5.3
  [1d5cc7b8] IntelOpenMP_jll v2018.0.3+0
  [929cbde3] LLVM v2.0.0
  [bdcacae8] LoopVectorization v0.8.19
  [856f044c] MKL_jll v2020.1.216+0
  [1914dd2f] MacroTools v0.5.5
  [a6bfbf70] NNPACK_jll v2018.6.22+0
  [872c559c] NNlib v0.7.3
  [77ba4419] NaNMath v0.3.4
  [6fe1bfb0] OffsetArrays v1.1.1
  [efe28fd5] OpenSpecFun_jll v0.5.3+3
  [bac558e1] OrderedCollections v1.3.0
  [189a3867] Reexport v0.2.0
  [ae029012] Requires v1.0.1
  [21efa798] SIMDPirates v0.8.17
  [476501e8] SLEEFPirates v0.5.5
  [276daf66] SpecialFunctions v0.10.3
  [90137ffa] StaticArrays v0.12.4
  [a759f4b9] TimerOutputs v0.5.6
  [3a884ed6] UnPack v1.0.1
  [3d5dd08c] VectorizationBase v0.12.25
  [2a0f44e3] Base64
  [ade2ca70] Dates
  [8ba89e20] Distributed
  [b77e0a4c] InteractiveUtils
  [76f85450] LibGit2
  [8f399da3] Libdl
  [37e2e46d] LinearAlgebra
  [56ddb016] Logging
  [d6f4376e] Markdown
  [44cfe95a] Pkg
  [de0858da] Printf
  [3fa0cd96] REPL
  [9a3f8284] Random
  [ea8e919c] SHA
  [9e88b42a] Serialization
  [6462fe0b] Sockets
  [2f01184e] SparseArrays
  [10745b16] Statistics
  [8dfed614] Test 
  [cf7118a7] UUIDs
  [4ec0a83e] Unicode
┌ Info: System information:
│ 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: missing
│ - CUTENSOR: missing
│ 
│ Toolchain:
│ - Julia: 1.4.2
│ - LLVM: 8.0.1
│ - PTX ISA support: 3.2, 4.0, 4.1, 4.2, 4.3, 5.0, 6.0, 6.1, 6.3
│ - Device support: sm_35, sm_37, sm_50, sm_52, sm_53, sm_60, sm_61, sm_62, sm_70, sm_72, sm_75
│ 
│ Environment:
│ - JULIA_CUDA_VERBOSE: true
│ 
│ 2 device(s):
│ - GeForce RTX 2070 (sm_75, 7.843 GiB / 8.000 GiB available)
└ - GeForce RTX 2080 Ti (sm_75, 10.790 GiB / 11.000 GiB available)
[ Info: Testing using 1 device(s): 2. GeForce RTX 2080 Ti (UUID 4d228dab-1287-5f37-f4db-e53f82e2bc60)
[ Info: Skipping the following tests: cudnn, cutensor, device\wmma
                                      | | ---------------- GPU ---------------- | ---------------- CPU ---------------- |
Test (Worker) | Time (s) | GC (s) | GC % | Alloc (MB) | RSS (MB) | GC (s) | GC % | Alloc (MB) | RSS (MB) |
initialization (2) | 3.65 | 0.00 | 0.0 | 0.00 | N/A | 0.05 | 1.4 | 199.20 | 562.26 |
apiutils (3) | 0.81 | 0.00 | 0.0 | 0.00 | N/A | 0.03 | 3.5 | 85.70 | 552.87 |
iterator (3) | 2.71 | 0.27 | 10.0 | 1.25 | N/A | 0.09 | 3.4 | 281.28 | 552.87 |
memory (3) | 1.53 | 0.00 | 0.0 | 0.00 | N/A | 0.33 | 21.2 | 142.82 | 552.87 |
codegen (6) | failed at 2020-07-24T20:12:39.053
nnlib (3) | 13.92 | 0.15 | 1.1 | 0.00 | N/A | 0.59 | 4.2 | 1550.51 | 980.92 |
nvml (3) | 0.51 | 0.00 | 0.0 | 0.00 | N/A | 0.02 | 3.4 | 58.52 | 986.84 |
nvtx (3) | 0.49 | 0.00 | 0.0 | 0.00 | N/A | 0.03 | 6.8 | 63.11 | 990.04 |
pointer (3) | 0.11 | 0.00 | 0.0 | 0.00 | N/A | 0.00 | 0.0 | 7.06 | 990.66 |
curand (9) | 23.48 | 0.26 | 1.1 | 0.02 | N/A | 1.18 | 5.0 | 2416.18 | 634.97 |
statistics (3) | 16.18 | 0.00 | 0.0 | 0.00 | N/A | 0.81 | 5.0 | 1582.73 | 1046.86 |
utils (3) | 0.85 | 0.00 | 0.0 | 0.00 | N/A | 0.02 | 2.7 | 118.93 | 1046.86 |
cufft (8) | 38.56 | 0.27 | 0.7 | 133.23 | N/A | 1.97 | 5.1 | 4257.42 | 1189.55 |
cudadrv\context (3) | 0.58 | 0.00 | 0.0 | 0.00 | N/A | 0.02 | 2.8 | 32.43 | 1099.50 |
cudadrv\devices (8) | 0.34 | 0.00 | 0.0 | 0.00 | N/A | 0.00 | 0.0 | 40.12 | 1189.55 |
broadcast (5) | 39.32 | 0.27 | 0.7 | 0.00 | N/A | 1.56 | 4.0 | 3605.98 | 677.96 |
cudadrv\errors (3) | 0.15 | 0.00 | 0.0 | 0.00 | N/A | 0.00 | 0.0 | 21.96 | 1099.50 |
cudadrv\events (8) | 0.15 | 0.00 | 0.0 | 0.00 | N/A | 0.00 | 0.0 | 14.93 | 1189.55 |
cudadrv\module (8) | 0.37 | 0.00 | 0.0 | 0.00 | N/A | 0.01 | 3.2 | 46.07 | 1189.55 |
cudadrv\occupancy (8) | 0.11 | 0.00 | 0.0 | 0.00 | N/A | 0.00 | 0.0 | 8.55 | 1189.55 |
cudadrv\profile (8) | 0.30 | 0.00 | 0.0 | 0.00 | N/A | 0.01 | 4.8 | 49.13 | 1189.55 |
cudadrv\execution (5) | 1.01 | 0.00 | 0.0 | 0.00 | N/A | 0.05 | 5.4 | 108.96 | 677.96 |
cudadrv\version (5) | 0.01 | 0.00 | 0.0 | 0.00 | N/A | 0.00 | 0.0 | 0.08 | 677.96 |
cudadrv\stream (8) | 0.21 | 0.00 | 0.0 | 0.00 | N/A | 0.02 | 9.0 | 20.06 | 1189.55 |
cudadrv\memory (3) | 2.10 | 0.00 | 0.0 | 0.00 | N/A | 0.07 | 3.5 | 206.39 | 1099.50 |
device\array (8) | 3.58 | 0.00 | 0.0 | 0.00 | N/A | 0.10 | 2.8 | 339.27 | 1194.57 |
texture (9) | 26.26 | 0.00 | 0.0 | 0.08 | N/A | 0.92 | 3.5 | 2530.68 | 720.41 |
device\pointer (8) | 7.09 | 0.00 | 0.0 | 0.00 | N/A | 0.20 | 2.9 | 568.32 | 1208.79 |
gpuarrays/math (8) | 2.93 | 0.00 | 0.0 | 0.00 | N/A | 0.09 | 3.2 | 306.95 | 1217.26 |
gpuarrays/input output (8) | 1.19 | 0.00 | 0.0 | 0.00 | N/A | 0.04 | 3.7 | 126.49 | 1217.26 |
cusparse (11) | 56.99 | 0.32 | 0.6 | 4.46 | N/A | 2.41 | 4.2 | 6253.25 | 967.00 |
threading (14) | 16.95 | 4.44 | 26.2 | 56.25 | N/A | 0.83 | 4.9 | 1801.75 | 1274.68 |
forwarddiff (2) | 58.55 | 0.30 | 0.5 | 0.00 | N/A | 1.32 | 2.3 | 3334.10 | 737.97 |
gpuarrays/interface (11) | 3.34 | 0.00 | 0.0 | 0.00 | N/A | 0.11 | 3.4 | 253.39 | 975.28 |
cusolver\cusparse (5) | 19.97 | 0.00 | 0.0 | 0.19 | N/A | 0.84 | 4.2 | 2063.14 | 1441.06 |
gpuarrays/value constructors (8) | 7.89 | 0.00 | 0.0 | 0.00 | N/A | 0.17 | 2.2 | 573.97 | 1238.47 |
gpuarrays/fft (8) | 1.24 | 0.00 | 0.1 | 6.01 | N/A | 0.04 | 3.3 | 133.59 | 1247.52 |
gpuarrays/conversions (5) | 4.46 | 0.00 | 0.0 | 0.01 | N/A | 0.19 | 4.3 | 626.51 | 1448.38 |
gpuarrays/constructors (8) | 1.42 | 0.00 | 0.2 | 0.04 | N/A | 0.01 | 0.9 | 76.52 | 1249.82 |
gpuarrays/indexing (9) | 17.71 | 0.00 | 0.0 | 0.12 | N/A | 0.57 | 3.2 | 1458.04 | 750.68 |
gpuarrays/uniformscaling (2) | 8.12 | 0.00 | 0.0 | 0.01 | N/A | 0.26 | 3.2 | 762.20 | 737.97 |
array (4) | 73.13 | 0.20 | 0.3 | 5.20 | N/A | 2.67 | 3.7 | 6785.38 | 784.63 |
cublas (7) | 75.23 | 0.35 | 0.5 | 11.12 | N/A | 3.19 | 4.2 | 8831.23 | 1199.72 |
gpuarrays/iterator constructors (14) | 19.32 | 0.00 | 0.0 | 0.02 | N/A | 0.62 | 3.2 | 1829.22 | 1278.43 |
gpuarrays/base (8) | 15.86 | 0.00 | 0.0 | 17.61 | N/A | 0.60 | 3.8 | 1872.71 | 1348.77 |
cusolver (10) | 83.64 | 0.42 | 0.5 | 1229.85 | N/A | 3.46 | 4.1 | 8887.82 | 1574.50 |
gpuarrays/random (5) | 19.85 | 0.00 | 0.0 | 0.00 | N/A | 0.53 | 2.7 | 1656.92 | 1505.24 |
device\intrinsics (3) | 67.58 | 0.00 | 0.0 | 0.01 | N/A | 1.30 | 1.9 | 5025.86 | 1201.33 |
gpuarrays/linear algebra (11) | 48.93 | 0.01 | 0.0 | 1.42 | N/A | 1.53 | 3.1 | 5037.09 | 1463.40 |
examples (12) | 124.64 | 0.00 | 0.0 | 0.00 | N/A | 0.08 | 0.1 | 132.75 | 562.43 |
gpuarrays/broadcasting (2) | 60.48 | 0.00 | 0.0 | 1.19 | N/A | 2.02 | 3.3 | 7448.78 | 853.78 |
execution (13) | failed at 2020-07-24T20:14:35.877
gpuarrays/mapreduce essentials (9) | 89.02 | 0.01 | 0.0 | 3.19 | N/A | 2.43 | 2.7 | 10171.24 | 980.95 |
gpuarrays/mapreduce (old tests) (7) | 92.07 | 0.01 | 0.0 | 130.20 | N/A | 2.21 | 2.4 | 10276.32 | 1506.56 |
gpuarrays/mapreduce derivatives (4) | 126.02 | 0.01 | 0.0 | 3.06 | N/A | 3.02 | 2.4 | 13688.27 | 1117.89 |
Worker 6 failed running test codegen:
Some tests did not pass: 17 passed, 1 failed, 0 errored, 0 broken.
codegen: Test Failed at C:\Src\cuda\cuda\dev\CUDA\test\codegen.jl:78
  Expression: !(occursin("gpu_report_exception", ir))
   Evaluated: !(occursin("gpu_report_exception", "\n; @ C:\\Src\\\cuda\\cuda\\dev\\CUDA\\test\\codegen.jl:76 within `bar'\n; Function Attrs: uwtable\ndefine i64 @julia_bar_19727(i64) local_unnamed_addr #0 {\ntop:\n; ┌ @ operators.jl:294 within `>'\n; │┌ @ int.jl:49 within `<'\n %1 = icmp sgt i64 %0, 0\n; └└\n; ┌ @ C:\\Src\\\cuda\\cuda\\dev\\CUDA\\src\\device\\llvm.jl:5 within `assume'\n %2 = call fastcc %jl_value_t addrspace(10)* @gpu_gc_pool_alloc(i64 16)\n %3 = addrspacecast %jl_value_t addrspace(10)* %2 to %jl_value_t addrspace(11)*\n %4 = bitcast %jl_value_t addrspace(10)* %2 to %jl_value_t addrspace(10)* addrspace(10)*\n store %jl_value_t addrspace(10)* addrspacecast (%jl_value_t* inttoptr (i64 1023020288 to %jl_value_t*) to %jl_value_t addrspace(10)*), %jl_value_t addrspace(10)* addrspace(10)* %4, align 8\n %5 = bitcast %jl_value_t addrspace(11)* %3 to i8 addrspace(11)*\n %6 = getelementptr inbounds i8, i8 addrspace(11)* %5, i64 8\n %7 
= bitcast i8 addrspace(11)* %6 to %jl_value_t addrspace(10)* addrspace(11)*\n store %jl_value_t addrspace(10)* addrspacecast (%jl_value_t* inttoptr (i64 370085648 to %jl_value_t*) to %jl_value_t addrspace(10)*), %jl_value_t addrspace(10)* addrspace(11)* %7, align 8\n call void @llvm.assume(i1 %1)\n; └\n; ┌ @ div.jl:227 within `cld'\n; │┌ @ div.jl:270 within `div' @ div.jl:215 @ int.jl:230\n %8 = icmp eq i64 %0, 0\n br i1 %8, label %fail, label %pass\n\nfail:
                         ; preds = %top\n call fastcc void @gpu_report_exception(i64 ptrtoint ([10 x i8]* @exception to 
i64))\n call fastcc void @gpu_signal_exception()\n call void asm sideeffect \"exit;\", \"\"() #1\n br label %pass\n\npass: ; preds = %top, %fail\n %9 = udiv i64 42, %0\n; ││ @ div.jl:271 within `div'\n; ││┌ @ int.jl:54 within `*'\n %10 = mul i64 %9, %0\n; ││└\n; ││┌ @ operators.jl:193 within `!='\n; │││┌ @ promotion.jl:398 within `=='\n %11 = icmp ne i64 %10, 42\n; ││└└\n; ││┌ @ int.jl:858 within `+'\n; │││┌ @ int.jl:442 within `rem'\n; ││││┌ @ number.jl:7 within `convert'\n; │││││┌ @ boot.jl:707 within `Int64'\n; ││││││┌ @ boot.jl:634 within `toInt64'\n %12 = zext i1 %11 to i64\n; │││└└└└\n; │││ @ int.jl:860 within `+' @ int.jl:53\n %13 = add nuw nsw i64 %9, %12\n; └└└\n ret i64 %13\n}\n"))
Stacktrace:
 [1] record(::Test.DefaultTestSet, ::Union{Test.Error, Test.Fail}) at D:\buildbot\worker\package_win64\build\usr\share\julia\stdlib\v1.4\Test\src\Test.jl:775
 [2] top-level scope at C:\Src\cuda\cuda\dev\CUDA\test\runtests.jl:444
 [3] include(::String) at .\client.jl:439
 [4] top-level scope at none:6
 [5] eval(::Module, ::Any) at .\boot.jl:331
 [6] exec_options(::Base.JLOptions) at .\client.jl:264
 [7] _start() at .\client.jl:484
Worker 13 failed running test execution:
Some tests did not pass: 72 passed, 8 failed, 0 errored, 0 broken.
execution: Test Failed at C:\Src\cuda\cuda\dev\CUDA\test\execution.jl:568
  Expression: code == 1
   Evaluated: 0 == 1
Stacktrace:
 [1] record(::Test.DefaultTestSet, ::Union{Test.Error, Test.Fail}) at D:\buildbot\worker\package_win64\build\usr\share\julia\stdlib\v1.4\Test\src\Test.jl:775
 [2] top-level scope at C:\Src\cuda\cuda\dev\CUDA\test\runtests.jl:444
 [3] include(::String) at .\client.jl:439
 [4] top-level scope at none:6
 [5] eval(::Module, ::Any) at .\boot.jl:331
 [6] exec_options(::Base.JLOptions) at .\client.jl:264
 [7] _start() at .\client.jl:484
execution: Test Failed at C:\Src\cuda\cuda\dev\CUDA\test\execution.jl:569
  Expression: occursin("ERROR: KernelException: exception thrown during kernel execution on device", err)
   Evaluated: occursin("ERROR: KernelException: exception thrown during kernel execution on device", "error in running finalizer: CUDA.KernelException(dev=CUDA.CuDevice(handle=0))\n")
Stacktrace:
 [1] record(::Test.DefaultTestSet, ::Union{Test.Error, Test.Fail}) at D:\buildbot\worker\package_win64\build\usr\share\julia\stdlib\v1.4\Test\src\Test.jl:775
 [2] top-level scope at C:\Src\cuda\cuda\dev\CUDA\test\runtests.jl:444
 [3] include(::String) at .\client.jl:439
 [4] top-level scope at none:6
 [5] eval(::Module, ::Any) at .\boot.jl:331
 [6] exec_options(::Base.JLOptions) at .\client.jl:264
 [7] _start() at .\client.jl:484
execution: Test Failed at C:\Src\cuda\cuda\dev\CUDA\test\execution.jl:575
  Expression: code == 1
   Evaluated: 0 == 1
Stacktrace:
 [1] record(::Test.DefaultTestSet, ::Union{Test.Error, Test.Fail}) at D:\buildbot\worker\package_win64\build\usr\share\julia\stdlib\v1.4\Test\src\Test.jl:775
 [2] top-level scope at C:\Src\cuda\cuda\dev\CUDA\test\runtests.jl:444
 [3] include(::String) at .\client.jl:439
 [4] top-level scope at none:6
 [5] eval(::Module, ::Any) at .\boot.jl:331
 [6] exec_options(::Base.JLOptions) at .\client.jl:264
 [7] _start() at .\client.jl:484
execution: Test Failed at C:\Src\cuda\cuda\dev\CUDA\test\execution.jl:576
  Expression: occursin("ERROR: KernelException: exception thrown during kernel execution on device", err)
   Evaluated: occursin("ERROR: KernelException: exception thrown during kernel execution on device", "error in running finalizer: CUDA.KernelException(dev=CUDA.CuDevice(handle=0))\n")
Stacktrace:
 [1] record(::Test.DefaultTestSet, ::Union{Test.Error, Test.Fail}) at D:\buildbot\worker\package_win64\build\usr\share\julia\stdlib\v1.4\Test\src\Test.jl:775
 [2] top-level scope at C:\Src\cuda\cuda\dev\CUDA\test\runtests.jl:444
 [3] include(::String) at .\client.jl:439
 [4] top-level scope at none:6
 [5] eval(::Module, ::Any) at .\boot.jl:331
 [6] exec_options(::Base.JLOptions) at .\client.jl:264
 [7] _start() at .\client.jl:484
execution: Test Failed at C:\Src\cuda\cuda\dev\CUDA\test\execution.jl:582
  Expression: code == 1
   Evaluated: 0 == 1
Stacktrace:
 [1] record(::Test.DefaultTestSet, ::Union{Test.Error, Test.Fail}) at D:\buildbot\worker\package_win64\build\usr\share\julia\stdlib\v1.4\Test\src\Test.jl:775
 [2] top-level scope at C:\Src\cuda\cuda\dev\CUDA\test\runtests.jl:444
 [3] include(::String) at .\client.jl:439
 [4] top-level scope at none:6
 [5] eval(::Module, ::Any) at .\boot.jl:331
 [6] exec_options(::Base.JLOptions) at .\client.jl:264
 [7] _start() at .\client.jl:484
execution: Test Failed at C:\Src\cuda\cuda\dev\CUDA\test\execution.jl:583
  Expression: occursin("ERROR: KernelException: exception thrown during kernel execution on device", err)
   Evaluated: occursin("ERROR: KernelException: exception thrown during kernel execution on device", "error in running finalizer: CUDA.KernelException(dev=CUDA.CuDevice(handle=0))\n")
Stacktrace:
 [1] record(::Test.DefaultTestSet, ::Union{Test.Error, Test.Fail}) at D:\buildbot\worker\package_win64\build\usr\share\julia\stdlib\v1.4\Test\src\Test.jl:775
 [2] top-level scope at C:\Src\cuda\cuda\dev\CUDA\test\runtests.jl:444
 [3] include(::String) at .\client.jl:439
 [4] top-level scope at none:6
 [5] eval(::Module, ::Any) at .\boot.jl:331
 [6] exec_options(::Base.JLOptions) at .\client.jl:264
 [7] _start() at .\client.jl:484
execution: Test Failed at C:\Src\cuda\cuda\dev\CUDA\test\execution.jl:609
  Expression: code == 1
   Evaluated: 0 == 1
Stacktrace:
 [1] record(::Test.DefaultTestSet, ::Union{Test.Error, Test.Fail}) at D:\buildbot\worker\package_win64\build\usr\share\julia\stdlib\v1.4\Test\src\Test.jl:775
 [2] top-level scope at C:\Src\cuda\cuda\dev\CUDA\test\runtests.jl:444
 [3] include(::String) at .\client.jl:439
 [4] top-level scope at none:6
 [5] eval(::Module, ::Any) at .\boot.jl:331
 [6] exec_options(::Base.JLOptions) at .\client.jl:264
 [7] _start() at .\client.jl:484
execution: Test Failed at C:\Src\cuda\cuda\dev\CUDA\test\execution.jl:610
  Expression: occursin("ERROR: KernelException: exception thrown during kernel execution on device", err)
   Evaluated: occursin("ERROR: KernelException: exception thrown during kernel execution on device", "error in running finalizer: CUDA.KernelException(dev=CUDA.CuDevice(handle=0))\n")
Stacktrace:
 [1] record(::Test.DefaultTestSet, ::Union{Test.Error, Test.Fail}) at D:\buildbot\worker\package_win64\build\usr\share\julia\stdlib\v1.4\Test\src\Test.jl:775
 [2] top-level scope at C:\Src\cuda\cuda\dev\CUDA\test\runtests.jl:444
 [3] include(::String) at .\client.jl:439
 [4] top-level scope at none:6
 [5] eval(::Module, ::Any) at .\boot.jl:331
 [6] exec_options(::Base.JLOptions) at .\client.jl:264
 [7] _start() at .\client.jl:484

Test Summary: | Pass Fail Broken Total
  Overall | 8167 9 2 8178
    initialization | 11 11
    apiutils | 15 15
    iterator | 30 30
    memory | 10 10
    codegen | 17 1 18
    nnlib | 3 3
    nvml | 7 7
    nvtx | No tests
    pointer | 13 13
    curand | 102 102
    statistics | 12 12
    utils | 5 5
    cufft | 151 151
    cudadrv\context | 12 12
    cudadrv\devices | 5 5
    broadcast | 29 29
    cudadrv\errors | 6 6
    cudadrv\events | 6 6
    cudadrv\module | 11 11
    cudadrv\occupancy | 1 1
    cudadrv\profile | 2 2
    cudadrv\execution | 15 15
    cudadrv\version | 3 3
    cudadrv\stream | 7 7
    cudadrv\memory | 50 1 51
    device\array | 20 20
    texture | 26 1 27
    device\pointer | 57 57
    gpuarrays/math | 8 8
    gpuarrays/input output | 5 5
    cusparse | 468 468
    threading | No tests
    forwarddiff | 106 106
    gpuarrays/interface | 7 7
    cusolver\cusparse | 84 84
    gpuarrays/value constructors | 120 120
    gpuarrays/fft | 12 12
    gpuarrays/conversions | 72 72
    gpuarrays/constructors | 335 335
    gpuarrays/indexing | 113 113
    gpuarrays/uniformscaling | 56 56
    array | 154 154
    cublas | 1885 1885
    gpuarrays/iterator constructors | 24 24
    gpuarrays/base | 38 38
    cusolver | 1493 1493
    gpuarrays/random | 40 40
    device\intrinsics | 265 265
    gpuarrays/linear algebra | 393 393
    examples | 7 7
    gpuarrays/broadcasting | 155 155
    execution | 72 8 80
    gpuarrays/mapreduce essentials | 522 522
    gpuarrays/mapreduce (old tests) | 297 297
    gpuarrays/mapreduce derivatives | 810 810
    FAILURE

Error in testset codegen:
Test Failed at C:\Src\cuda\cuda\dev\CUDA\test\codegen.jl:78
  Expression: !(occursin("gpu_report_exception", ir))
   Evaluated: !(occursin("gpu_report_exception", "\n; @ C:\\Src\\\cuda\\cuda\\dev\\CUDA\\test\\codegen.jl:76 within `bar'\n; Function Attrs: uwtable\ndefine i64 @julia_bar_19727(i64) local_unnamed_addr #0 {\ntop:\n; ┌ @ operators.jl:294 within `>'\n; │┌ @ int.jl:49 within `<'\n %1 = icmp sgt i64 %0, 0\n; └└\n; ┌ @ C:\\Src\\\cuda\\cuda\\dev\\CUDA\\src\\device\\llvm.jl:5 within `assume'\n %2 = call fastcc %jl_value_t addrspace(10)* @gpu_gc_pool_alloc(i64 16)\n %3 = addrspacecast %jl_value_t addrspace(10)* %2 to %jl_value_t addrspace(11)*\n %4 = bitcast %jl_value_t addrspace(10)* %2 to %jl_value_t addrspace(10)* addrspace(10)*\n store %jl_value_t addrspace(10)* addrspacecast (%jl_value_t* inttoptr (i64 1023020288 to %jl_value_t*) to %jl_value_t addrspace(10)*), %jl_value_t addrspace(10)* addrspace(10)* %4, align 8\n %5 = bitcast %jl_value_t addrspace(11)* %3 to i8 addrspace(11)*\n %6 = getelementptr inbounds i8, i8 addrspace(11)* %5, i64 8\n %7 
= bitcast i8 addrspace(11)* %6 to %jl_value_t addrspace(10)* addrspace(11)*\n store %jl_value_t addrspace(10)* addrspacecast (%jl_value_t* inttoptr (i64 370085648 to %jl_value_t*) to %jl_value_t addrspace(10)*), %jl_value_t addrspace(10)* addrspace(11)* %7, align 8\n call void @llvm.assume(i1 %1)\n; └\n; ┌ @ div.jl:227 within `cld'\n; │┌ @ div.jl:270 within `div' @ div.jl:215 @ int.jl:230\n %8 = icmp eq i64 %0, 0\n br i1 %8, label %fail, label %pass\n\nfail:
                         ; preds = %top\n call fastcc void @gpu_report_exception(i64 ptrtoint ([10 x i8]* @exception to 
i64))\n call fastcc void @gpu_signal_exception()\n call void asm sideeffect \"exit;\", \"\"() #1\n br label %pass\n\npass: ; preds = %top, %fail\n %9 = udiv i64 42, %0\n; ││ @ div.jl:271 within `div'\n; ││┌ @ int.jl:54 within `*'\n %10 = mul i64 %9, %0\n; ││└\n; ││┌ @ operators.jl:193 within `!='\n; │││┌ @ promotion.jl:398 within `=='\n %11 = icmp ne i64 %10, 42\n; ││└└\n; ││┌ @ int.jl:858 within `+'\n; │││┌ @ int.jl:442 within `rem'\n; ││││┌ @ number.jl:7 within `convert'\n; │││││┌ @ boot.jl:707 within `Int64'\n; ││││││┌ @ boot.jl:634 within `toInt64'\n %12 = zext i1 %11 to i64\n; │││└└└└\n; │││ @ int.jl:860 within `+' @ int.jl:53\n %13 = add nuw nsw i64 %9, %12\n; └└└\n ret i64 %13\n}\n"))
Error in testset execution:
Test Failed at C:\Src\cuda\cuda\dev\CUDA\test\execution.jl:568
  Expression: code == 1
   Evaluated: 0 == 1
Error in testset execution:
Test Failed at C:\Src\cuda\cuda\dev\CUDA\test\execution.jl:569
  Expression: occursin("ERROR: KernelException: exception thrown during kernel execution on device", err)
   Evaluated: occursin("ERROR: KernelException: exception thrown during kernel execution on device", "error in running finalizer: CUDA.KernelException(dev=CUDA.CuDevice(handle=0))\n")
Error in testset execution:
Test Failed at C:\Src\cuda\cuda\dev\CUDA\test\execution.jl:575
  Expression: code == 1
   Evaluated: 0 == 1
Error in testset execution:
Test Failed at C:\Src\cuda\cuda\dev\CUDA\test\execution.jl:576
  Expression: occursin("ERROR: KernelException: exception thrown during kernel execution on device", err)
   Evaluated: occursin("ERROR: KernelException: exception thrown during kernel execution on device", "error in running finalizer: CUDA.KernelException(dev=CUDA.CuDevice(handle=0))\n")
Error in testset execution:
Test Failed at C:\Src\cuda\cuda\dev\CUDA\test\execution.jl:582
  Expression: code == 1
   Evaluated: 0 == 1
Error in testset execution:
Test Failed at C:\Src\cuda\cuda\dev\CUDA\test\execution.jl:583
  Expression: occursin("ERROR: KernelException: exception thrown during kernel execution on device", err)
   Evaluated: occursin("ERROR: KernelException: exception thrown during kernel execution on device", "error in running finalizer: CUDA.KernelException(dev=CUDA.CuDevice(handle=0))\n")
Error in testset execution:
Test Failed at C:\Src\cuda\cuda\dev\CUDA\test\execution.jl:609
  Expression: code == 1
   Evaluated: 0 == 1
Error in testset execution:
Test Failed at C:\Src\cuda\cuda\dev\CUDA\test\execution.jl:610
  Expression: occursin("ERROR: KernelException: exception thrown during kernel execution on device", err)
   Evaluated: occursin("ERROR: KernelException: exception thrown during kernel execution on device", "error in running finalizer: CUDA.KernelException(dev=CUDA.CuDevice(handle=0))\n")
ERROR: LoadError: Test run finished with errors
in expression starting at C:\Src\cuda\cuda\dev\CUDA\test\runtests.jl:475

```

---

<div class="post-metadata">

**Author:** ![maleadt](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/maleadt/32/10097_2.png) [@maleadt](https://discourse.julialang.org/u/maleadt)\
**Post date:** [July 25, 2020, 8:07am UTC](https://discourse.julialang.org/t/cuda-jl-tests-on-windows/43378/18 "2020-07-25T08:07:46Z")

</div>

Interesting failures. The `assume` I haven’t seen before, it’s weird how your LLVM optimizes differently, but the functionality isn’t used so the failure is harmless. The other failures are harmless too, although they might indicate a CUDA driver bug. I’ve created [https://github.com/JuliaGPU/CUDA.jl/pull/319](https://github.com/JuliaGPU/CUDA.jl/pull/319) to make the test more robust and hopefully pass that test on your system.

---

<div class="post-metadata">

**Author:** ![anj](https://avatars.discourse-cdn.com/v4/letter/a/779978/32.png) [@anj](https://discourse.julialang.org/u/anj)\
**Post date:** [July 27, 2020, 12:16pm UTC](https://discourse.julialang.org/t/cuda-jl-tests-on-windows/43378/20 "2020-07-27T12:16:38Z")

</div>

I still see errors in test

```julia
Status `C:\Users\andre\AppData\Local\Temp\jl_hFTchO\Manifest.toml`
  [621f4979] AbstractFFTs v0.5.0
  [79e6a3ab] Adapt v2.0.2
  [b99e7846] BinaryProvider v0.5.10
  [fa961155] CEnum v0.4.1
  [052768ef] CUDA v1.2.0 [`C:\Users\andre\.julia\dev\CUDA`]
  [bbf7d656] CommonSubexpressions v0.3.0
  [e66e0078] CompilerSupportLibraries_jll v0.3.3+0
  [adafc99b] CpuId v0.2.2
  [864edb3b] DataStructures v0.17.19
  [163ba53b] DiffResults v1.0.2
  [b552c78f] DiffRules v1.0.1
  [ffbed154] DocStringExtensions v0.8.2
  [e2ba6199] ExprTools v0.1.1
  [7a1cc6ca] FFTW v1.2.2
  [f5851436] FFTW_jll v3.3.9+5
  [1a297f60] FillArrays v0.8.13
  [f6369f11] ForwardDiff v0.10.12
  [0c68f7d7] GPUArrays v4.0.1 #master (https://github.com/JuliaGPU/GPUArrays.jl)
  [61eb1bfa] GPUCompiler v0.5.3
  [1d5cc7b8] IntelOpenMP_jll v2018.0.3+0
  [929cbde3] LLVM v2.0.0
  [bdcacae8] LoopVectorization v0.8.20
  [856f044c] MKL_jll v2020.1.216+0
  [1914dd2f] MacroTools v0.5.5
  [a6bfbf70] NNPACK_jll v2018.6.22+0
  [872c559c] NNlib v0.7.3
  [77ba4419] NaNMath v0.3.4
  [6fe1bfb0] OffsetArrays v1.1.2
  [efe28fd5] OpenSpecFun_jll v0.5.3+3
  [bac558e1] OrderedCollections v1.3.0
  [189a3867] Reexport v0.2.0
  [ae029012] Requires v1.0.1
  [21efa798] SIMDPirates v0.8.21
  [476501e8] SLEEFPirates v0.5.5
  [276daf66] SpecialFunctions v0.10.3
  [90137ffa] StaticArrays v0.12.4
  [a759f4b9] TimerOutputs v0.5.6
  [3a884ed6] UnPack v1.0.1
  [3d5dd08c] VectorizationBase v0.12.29
  [2a0f44e3] Base64
  [ade2ca70] Dates
  [8ba89e20] Distributed
  [b77e0a4c] InteractiveUtils
  [76f85450] LibGit2
  [8f399da3] Libdl
  [37e2e46d] LinearAlgebra
  [56ddb016] Logging
  [d6f4376e] Markdown
  [44cfe95a] Pkg
  [de0858da] Printf
  [3fa0cd96] REPL
  [9a3f8284] Random
  [ea8e919c] SHA 
  [9e88b42a] Serialization
  [6462fe0b] Sockets
  [2f01184e] SparseArrays
  [10745b16] Statistics
  [8dfed614] Test
  [cf7118a7] UUIDs
  [4ec0a83e] Unicode
┌ Info: System information:
│ 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: missing
│ - CUTENSOR: missing
│ 
│ Toolchain:
│ - Julia: 1.4.2
│ - LLVM: 8.0.1
│ - PTX ISA support: 3.2, 4.0, 4.1, 4.2, 4.3, 5.0, 6.0, 6.1, 6.3
│ - Device support: sm_35, sm_37, sm_50, sm_52, sm_53, sm_60, sm_61, sm_62, sm_70, sm_72, sm_75
│ 
│ Environment:
│ - JULIA_CUDA_VERBOSE: true
│ 
│ 2 device(s):
│ - GeForce RTX 2070 (sm_75, 7.843 GiB / 8.000 GiB available)
└ - GeForce RTX 2080 Ti (sm_75, 10.790 GiB / 11.000 GiB available)
[ Info: Testing using 1 device(s): 2. GeForce RTX 2080 Ti (UUID 4d228dab-1287-5f37-f4db-e53f82e2bc60)
[ Info: Skipping the following tests: cudnn, cutensor, device\wmma
                                      | | ---------------- GPU ---------------- | ---------------- CPU ---------------- |
Test (Worker) | Time (s) | GC (s) | GC % | Alloc (MB) | RSS (MB) | GC (s) | GC % | Alloc (MB) | RSS (MB) |
apiutils (3) | 0.56 | 0.00 | 0.0 | 0.00 | N/A | 0.02 | 3.6 | 85.74 | 541.16 |
initialization (2) | 3.57 | 0.00 | 0.0 | 0.00 | N/A | 0.07 | 1.8 | 199.58 | 566.14 |
iterator (2) | 2.69 | 0.29 | 10.7 | 1.25 | N/A | 0.11 | 4.2 | 283.23 | 566.14 |
memory (2) | 1.67 | 0.00 | 0.0 | 0.00 | N/A | 0.36 | 21.8 | 146.26 | 566.14 |
codegen (6) | failed at 2020-07-27T14:09:49.998
nnlib (2) | 14.42 | 0.15 | 1.0 | 0.00 | N/A | 0.56 | 3.9 | 1549.00 | 1073.51 |
nvml (2) | 0.51 | 0.00 | 0.0 | 0.00 | N/A | 0.03 | 5.6 | 58.10 | 1073.51 |
nvtx (2) | 0.48 | 0.00 | 0.0 | 0.00 | N/A | 0.02 | 3.3 | 74.69 | 1073.51 |
pointer (2) | 0.12 | 0.00 | 0.0 | 0.00 | N/A | 0.00 | 0.0 | 7.09 | 1073.51 |
curand (9) | 23.46 | 0.29 | 1.2 | 0.02 | N/A | 1.25 | 5.3 | 2369.98 | 604.86 |
statistics (2) | 16.12 | 0.00 | 0.0 | 0.00 | N/A | 0.84 | 5.2 | 1625.56 | 1090.46 |
broadcast (5) | 38.18 | 0.30 | 0.8 | 0.00 | N/A | 1.58 | 4.1 | 3502.24 | 675.89 |
cufft (8) | 39.44 | 0.30 | 0.8 | 133.23 | N/A | 1.98 | 5.0 | 4259.85 | 1181.87 |
utils (5) | 1.21 | 0.00 | 0.0 | 0.00 | N/A | 0.07 | 5.9 | 151.43 | 675.89 |
cudadrv\errors (5) | 0.16 | 0.00 | 0.0 | 0.00 | N/A | 0.00 | 0.0 | 22.49 | 675.89 |
cudadrv\devices (8) | 0.37 | 0.00 | 0.0 | 0.00 | N/A | 0.00 | 0.0 | 39.87 | 1181.87 |
cudadrv\events (5) | 0.15 | 0.00 | 0.0 | 0.00 | N/A | 0.00 | 0.0 | 14.25 | 675.89 |
cudadrv\execution (8) | 1.47 | 0.00 | 0.0 | 0.00 | N/A | 0.02 | 1.1 | 74.55 | 1183.48 |
threading (2) | 4.16 | 0.92 | 22.0 | 56.25 | N/A | 0.11 | 2.6 | 469.27 | 1218.40 |
cudadrv\module (8) | 0.59 | 0.00 | 0.0 | 0.00 | N/A | 0.01 | 2.1 | 42.89 | 1185.80 |
cudadrv\occupancy (2) | 0.10 | 0.00 | 0.0 | 0.00 | N/A | 0.00 | 0.0 | 8.42 | 1218.86 |
cudadrv\profile (8) | 0.31 | 0.00 | 0.0 | 0.00 | N/A | 0.01 | 4.7 | 49.02 | 1185.80 |
cudadrv\stream (2) | 0.30 | 0.00 | 0.2 | 0.00 | N/A | 0.05 | 17.8 | 29.84 | 1218.96 |
cudadrv\version (8) | 0.01 | 0.00 | 0.0 | 0.00 | N/A | 0.00 | 0.0 | 0.08 | 1185.80 |
cudadrv\memory (5) | 2.89 | 0.00 | 0.0 | 0.00 | N/A | 0.09 | 3.0 | 211.58 | 678.09 |
cudadrv\context (14) | 1.18 | 0.00 | 0.0 | 0.00 | N/A | 0.04 | 3.3 | 121.68 | 616.20 |
device\array (8) | 3.60 | 0.00 | 0.0 | 0.00 | N/A | 0.09 | 2.4 | 336.02 | 1196.71 |
texture (9) | 25.67 | 0.00 | 0.0 | 0.08 | N/A | 1.07 | 4.2 | 2776.62 | 734.56 |
gpuarrays/math (9) | 2.83 | 0.00 | 0.0 | 0.00 | N/A | 0.09 | 3.3 | 314.90 | 734.91 |
gpuarrays/input output (9) | 1.29 | 0.00 | 0.0 | 0.00 | N/A | 0.02 | 1.7 | 127.70 | 734.91 |
cusparse (11) | 57.69 | 0.31 | 0.5 | 4.46 | N/A | 2.54 | 4.4 | 6234.63 | 967.88 |
forwarddiff (3) | 59.99 | 0.38 | 0.6 | 0.00 | N/A | 1.47 | 2.5 | 3475.23 | 719.55 |
cusolver\cusparse (2) | 17.83 | 0.01 | 0.0 | 0.19 | N/A | 0.77 | 4.3 | 1926.42 | 1684.84 |
gpuarrays/interface (11) | 2.81 | 0.00 | 0.0 | 0.00 | N/A | 0.10 | 3.5 | 263.06 | 975.27 |
gpuarrays/value constructors (9) | 7.52 | 0.00 | 0.0 | 0.00 | N/A | 0.20 | 2.7 | 650.63 | 753.97 |
device\pointer (14) | 17.74 | 0.29 | 1.6 | 0.00 | N/A | 0.82 | 4.6 | 1818.78 | 616.20 |
gpuarrays/conversions (9) | 4.16 | 0.00 | 0.0 | 0.01 | N/A | 0.21 | 5.0 | 581.19 | 767.15 |
gpuarrays/indexing (8) | 19.63 | 0.00 | 0.0 | 0.13 | N/A | 0.71 | 3.6 | 1936.64 | 1286.61 |
gpuarrays/constructors (9) | 1.53 | 0.00 | 0.2 | 0.04 | N/A | 0.03 | 1.7 | 86.16 | 777.34 |
gpuarrays/uniformscaling (2) | 7.45 | 0.00 | 0.0 | 0.01 | N/A | 0.20 | 2.7 | 630.02 | 1684.84 |
array (4) | 71.59 | 0.30 | 0.4 | 5.20 | N/A | 2.88 | 4.0 | 6732.22 | 774.98 |
gpuarrays/fft (14) | 7.95 | 0.00 | 0.0 | 6.01 | N/A | 0.33 | 4.2 | 872.91 | 1176.69 |
cublas (7) | 76.81 | 0.36 | 0.5 | 11.12 | N/A | 3.34 | 4.3 | 8808.45 | 1240.90 |
gpuarrays/iterator constructors (3) | 19.00 | 0.00 | 0.0 | 0.02 | N/A | 0.73 | 3.8 | 2004.91 | 758.60 |
cusolver (10) | 82.26 | 0.40 | 0.5 | 1229.85 | N/A | 3.64 | 4.4 | 8737.55 | 1571.16 |
gpuarrays/base (9) | 16.35 | 0.00 | 0.0 | 17.61 | N/A | 0.75 | 4.6 | 1867.16 | 856.94 |
gpuarrays/random (8) | 20.07 | 0.00 | 0.0 | 0.00 | N/A | 0.51 | 2.6 | 1659.26 | 1369.74 |
device\intrinsics (5) | 67.23 | 0.00 | 0.0 | 0.01 | N/A | 1.40 | 2.1 | 4967.24 | 859.46 |
gpuarrays/linear algebra (11) | 57.55 | 0.01 | 0.0 | 1.42 | N/A | 1.49 | 2.6 | 5148.27 | 1519.13 |
examples (12) | 127.03 | 0.00 | 0.0 | 0.00 | N/A | 0.09 | 0.1 | 132.75 | 555.79 |
gpuarrays/broadcasting (4) | 57.83 | 0.00 | 0.0 | 1.19 | N/A | 1.97 | 3.4 | 7069.32 | 933.43 |
execution (13) | failed at 2020-07-27T14:11:53.175
gpuarrays/mapreduce (old tests) (7) | 84.84 | 0.01 | 0.0 | 130.20 | N/A | 2.53 | 3.0 | 10279.09 | 1458.08 |
gpuarrays/mapreduce essentials (2) | 93.39 | 0.01 | 0.0 | 3.19 | N/A | 3.03 | 3.2 | 12281.01 | 1899.16 |
gpuarrays/mapreduce derivatives (14) | 127.34 | 0.01 | 0.0 | 3.06 | N/A | 3.44 | 2.7 | 15804.64 | 1610.81 |
Worker 6 failed running test codegen:
Some tests did not pass: 17 passed, 1 failed, 0 errored, 0 broken.
codegen: Test Failed at C:\Users\andre\.julia\dev\CUDA\test\codegen.jl:78
  Expression: !(occursin("gpu_report_exception", ir))
   Evaluated: !(occursin("gpu_report_exception", "\n; @ C:\\Users\\andre\\.julia\\dev\\CUDA\\test\\codegen.jl:76 within `bar'\n; Function Attrs: uwtable\ndefine i64 @julia_bar_19729(i64) local_unnamed_addr #0 {\ntop:\n; ┌ @ operators.jl:294 within `>'\n; │┌ @ int.jl:49 within `<'\n %1 = icmp sgt i64 %0, 0\n; └└\n; ┌ @ C:\\Users\\andre\\.julia\\dev\\CUDA\\src\\device\\llvm.jl:5 within `assume'\n %2 = call fastcc %jl_value_t addrspace(10)* @gpu_gc_pool_alloc(i64 16)\n %3 = addrspacecast %jl_value_t addrspace(10)* %2 to %jl_value_t addrspace(11)*\n %4 = bitcast %jl_value_t addrspace(10)* %2 to %jl_value_t addrspace(10)* addrspace(10)*\n store %jl_value_t addrspace(10)* addrspacecast (%jl_value_t* inttoptr (i64 1035379872 to %jl_value_t*) to %jl_value_t addrspace(10)*), %jl_value_t addrspace(10)* addrspace(10)* %4, align 8\n %5 = bitcast %jl_value_t addrspace(11)* %3 to i8 addrspace(11)*\n %6 = getelementptr inbounds i8, i8 addrspace(11)* %5, i64 8\n %7 = 
bitcast i8 addrspace(11)* %6 to %jl_value_t addrspace(10)* addrspace(11)*\n store %jl_value_t addrspace(10)* addrspacecast (%jl_value_t* inttoptr (i64 1033654928 to %jl_value_t*) to %jl_value_t addrspace(10)*), %jl_value_t addrspace(10)* addrspace(11)* %7, align 8\n call void @llvm.assume(i1 %1)\n; └\n; ┌ @ div.jl:227 within `cld'\n; │┌ @ div.jl:270 within `div' 
@ div.jl:215 @ int.jl:230\n %8 = icmp eq i64 %0, 0\n br i1 %8, label %fail, label %pass\n\nfail:
                        ; preds = %top\n call fastcc void @gpu_report_exception(i64 ptrtoint ([10 x i8]* @exception to i64))\n call fastcc void @gpu_signal_exception()\n call void asm sideeffect \"exit;\", \"\"() #1\n br label %pass\n\npass: ; preds = %top, %fail\n %9 = udiv i64 42, %0\n; ││ @ div.jl:271 within `div'\n; ││┌ @ int.jl:54 within `*'\n %10 = mul i64 %9, %0\n; ││└\n; ││┌ @ operators.jl:193 within `!='\n; │││┌ @ promotion.jl:398 within `=='\n %11 = icmp ne i64 %10, 42\n; ││└└\n; ││┌ @ int.jl:858 within `+'\n; │││┌ @ int.jl:442 within `rem'\n; ││││┌ @ number.jl:7 within `convert'\n; │││││┌ @ boot.jl:707 within `Int64'\n; ││││││┌ @ boot.jl:634 within `toInt64'\n %12 = zext i1 %11 to i64\n; │││└└└└\n; │││ @ int.jl:860 within `+' @ int.jl:53\n %13 = add nuw nsw i64 %9, %12\n; └└└\n ret i64 %13\n}\n"))
Stacktrace:
 [1] record(::Test.DefaultTestSet, ::Union{Test.Error, Test.Fail}) at D:\buildbot\worker\package_win64\build\usr\share\julia\stdlib\v1.4\Test\src\Test.jl:775
 [2] top-level scope at C:\Users\andre\.julia\dev\CUDA\test\runtests.jl:444
 [3] include(::String) at .\client.jl:439
 [4] top-level scope at none:6
 [5] eval(::Module, ::Any) at .\boot.jl:331
 [6] exec_options(::Base.JLOptions) at .\client.jl:264
 [7] _start() at .\client.jl:484
Worker 13 failed running test execution:
Some tests did not pass: 78 passed, 2 failed, 0 errored, 0 broken.
execution: Test Failed at C:\Users\andre\.julia\dev\CUDA\test\execution.jl:617
  Expression: code == 1
   Evaluated: 0 == 1
Stacktrace:
 [1] record(::Test.DefaultTestSet, ::Union{Test.Error, Test.Fail}) at D:\buildbot\worker\package_win64\build\usr\share\julia\stdlib\v1.4\Test\src\Test.jl:775
 [2] top-level scope at C:\Users\andre\.julia\dev\CUDA\test\runtests.jl:444
 [3] include(::String) at .\client.jl:439
 [4] top-level scope at none:6
 [5] eval(::Module, ::Any) at .\boot.jl:331
 [6] exec_options(::Base.JLOptions) at .\client.jl:264
 [7] _start() at .\client.jl:484
execution: Test Failed at C:\Users\andre\.julia\dev\CUDA\test\execution.jl:618
  Expression: occursin("ERROR: KernelException: exception thrown during kernel execution on device", err)
   Evaluated: occursin("ERROR: KernelException: exception thrown during kernel execution on device", "error in running finalizer: CUDA.KernelException(dev=CUDA.CuDevice(handle=0))\n")
Stacktrace:
 [1] record(::Test.DefaultTestSet, ::Union{Test.Error, Test.Fail}) at D:\buildbot\worker\package_win64\build\usr\share\julia\stdlib\v1.4\Test\src\Test.jl:775
 [2] top-level scope at C:\Users\andre\.julia\dev\CUDA\test\runtests.jl:444
 [3] include(::String) at .\client.jl:439
 [4] top-level scope at none:6
 [5] eval(::Module, ::Any) at .\boot.jl:331
 [6] exec_options(::Base.JLOptions) at .\client.jl:264
 [7] _start() at .\client.jl:484

Test Summary: | Pass Fail Broken Total
  Overall | 8173 3 2 8178
    apiutils | 15 15
    initialization | 11 11
    iterator | 30 30
    memory | 10 10
    codegen | 17 1 18
    nnlib | 3 3
    nvml | 7 7
    nvtx | No tests
    pointer | 13 13
    curand | 102 102
    statistics | 12 12
    broadcast | 29 29
    cufft | 151 151
    utils | 5 5
    cudadrv\errors | 6 6
    cudadrv\devices | 5 5
    cudadrv\events | 6 6
    cudadrv\execution | 15 15
    threading | No tests
    cudadrv\module | 11 11
    cudadrv\occupancy | 1 1
    cudadrv\profile | 2 2
    cudadrv\stream | 7 7
    cudadrv\version | 3 3
    cudadrv\memory | 50 1 51
    cudadrv\context | 12 12
    device\array | 20 20
    texture | 26 1 27
    gpuarrays/math | 8 8
    gpuarrays/input output | 5 5
    cusparse | 468 468
    forwarddiff | 106 106
    cusolver\cusparse | 84 84
    gpuarrays/interface | 7 7
    gpuarrays/value constructors | 120 120
    device\pointer | 57 57
    gpuarrays/conversions | 72 72
    gpuarrays/indexing | 113 113
    gpuarrays/constructors | 335 335
    gpuarrays/uniformscaling | 56 56
    array | 154 154
    gpuarrays/fft | 12 12
    cublas | 1885 1885
    gpuarrays/iterator constructors | 24 24
    cusolver | 1493 1493
    gpuarrays/base | 38 38
    gpuarrays/random | 40 40
    device\intrinsics | 265 265
    gpuarrays/linear algebra | 393 393
    examples | 7 7
    gpuarrays/broadcasting | 155 155
    execution | 78 2 80
    gpuarrays/mapreduce (old tests) | 297 297
    gpuarrays/mapreduce essentials | 522 522
    gpuarrays/mapreduce derivatives | 810 810
    FAILURE

Error in testset codegen:
Test Failed at C:\Users\andre\.julia\dev\CUDA\test\codegen.jl:78
  Expression: !(occursin("gpu_report_exception", ir))
   Evaluated: !(occursin("gpu_report_exception", "\n; @ C:\\Users\\andre\\.julia\\dev\\CUDA\\test\\codegen.jl:76 within `bar'\n; Function Attrs: uwtable\ndefine i64 @julia_bar_19729(i64) local_unnamed_addr #0 {\ntop:\n; ┌ @ operators.jl:294 within `>'\n; │┌ @ int.jl:49 within `<'\n %1 = icmp sgt i64 %0, 0\n; └└\n; ┌ @ C:\\Users\\andre\\.julia\\dev\\CUDA\\src\\device\\llvm.jl:5 within `assume'\n %2 = call fastcc %jl_value_t addrspace(10)* @gpu_gc_pool_alloc(i64 16)\n %3 = addrspacecast %jl_value_t addrspace(10)* %2 to %jl_value_t addrspace(11)*\n %4 = bitcast %jl_value_t addrspace(10)* %2 to %jl_value_t addrspace(10)* addrspace(10)*\n store %jl_value_t addrspace(10)* addrspacecast (%jl_value_t* inttoptr (i64 1035379872 to %jl_value_t*) to %jl_value_t addrspace(10)*), %jl_value_t addrspace(10)* addrspace(10)* %4, align 8\n %5 = bitcast %jl_value_t addrspace(11)* %3 to i8 addrspace(11)*\n %6 = getelementptr inbounds i8, i8 addrspace(11)* %5, i64 8\n %7 = 
bitcast i8 addrspace(11)* %6 to %jl_value_t addrspace(10)* addrspace(11)*\n store %jl_value_t addrspace(10)* addrspacecast (%jl_value_t* inttoptr (i64 1033654928 to %jl_value_t*) to %jl_value_t addrspace(10)*), %jl_value_t addrspace(10)* addrspace(11)* %7, align 8\n call void @llvm.assume(i1 %1)\n; └\n; ┌ @ div.jl:227 within `cld'\n; │┌ @ div.jl:270 within `div' 
@ div.jl:215 @ int.jl:230\n %8 = icmp eq i64 %0, 0\n br i1 %8, label %fail, label %pass\n\nfail:
                        ; preds = %top\n call fastcc void @gpu_report_exception(i64 ptrtoint ([10 x i8]* @exception to i64))\n call fastcc void @gpu_signal_exception()\n call void asm sideeffect \"exit;\", \"\"() #1\n br label %pass\n\npass: ; preds = %top, %fail\n %9 = udiv i64 42, %0\n; ││ @ div.jl:271 within `div'\n; ││┌ @ int.jl:54 within `*'\n %10 = mul i64 %9, %0\n; ││└\n; ││┌ @ operators.jl:193 within `!='\n; │││┌ @ promotion.jl:398 within `=='\n %11 = icmp ne i64 %10, 42\n; ││└└\n; ││┌ @ int.jl:858 within `+'\n; │││┌ @ int.jl:442 within `rem'\n; ││││┌ @ number.jl:7 within `convert'\n; │││││┌ @ boot.jl:707 within `Int64'\n; ││││││┌ @ boot.jl:634 within `toInt64'\n %12 = zext i1 %11 to i64\n; │││└└└└\n; │││ @ int.jl:860 within `+' @ int.jl:53\n %13 = add nuw nsw i64 %9, %12\n; └└└\n ret i64 %13\n}\n"))
Error in testset execution:
Test Failed at C:\Users\andre\.julia\dev\CUDA\test\execution.jl:617
  Expression: code == 1
   Evaluated: 0 == 1
Error in testset execution:
Test Failed at C:\Users\andre\.julia\dev\CUDA\test\execution.jl:618
  Expression: occursin("ERROR: KernelException: exception thrown during kernel execution on device", err)
   Evaluated: occursin("ERROR: KernelException: exception thrown during kernel execution on device", "error in running finalizer: CUDA.KernelException(dev=CUDA.CuDevice(handle=0))\n")
ERROR: LoadError: Test run finished with errors
in expression starting at C:\Users\andre\.julia\dev\CUDA\test\runtests.jl:475

```

And I double checked. I did get the code needed

 ![Screenshot_1](https://global.discourse-cdn.com/julialang/original/3X/e/6/e6e76d8d92803a75036f1d63e96921a591ab4166.png)

---

<div class="post-metadata">

**Author:** ![maleadt](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/maleadt/32/10097_2.png) [@maleadt](https://discourse.julialang.org/u/maleadt)\
**Post date:** [July 27, 2020, 2:07pm UTC](https://discourse.julialang.org/t/cuda-jl-tests-on-windows/43378/21 "2020-07-27T14:07:09Z")

</div>

Yes, those are the `llvm.assume` differences I mentioned.

> [@maleadt](#):
>
> The `assume` I haven’t seen before, it’s weird how your LLVM optimizes differently, but the functionality isn’t used so the failure is harmless.

[Next page](https://discourse.julialang.org/t/cuda-jl-tests-on-windows/43378.md?page=2)