# Failed to load \`CUDAdrv\`
**URL:** https://discourse.julialang.org/t/failed-to-load-cudadrv/32524
**Category:** GPU
**Created:** [December 20, 2019, 6:51pm UTC](https://discourse.julialang.org/t/failed-to-load-cudadrv/32524 "2019-12-20T18:51:46Z")
**Posts on this page:** 4
**Page:** 1
### Author:  [@affans](https://discourse.julialang.org/u/affans)
#### Post date: [December 20, 2019, 6:51pm UTC](https://discourse.julialang.org/t/failed-to-load-cudadrv/32524/1 "2019-12-20T18:51:46Z")
I am, for the first time, trying to learn how GPU programming works. I have two Tesla K80s on a HPC. To begin I request the proper node through slurm, and launch an interactive job.
```julia
[affans@hpc ~]$ srun -p gpuq --gres=gpu:2 --pty bash
[affans@node018 ~]$ nvidia-smi
Fri Dec 20 13:46:43 2019
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 384.111 Driver Version: 384.111 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
|===============================+======================+======================|
| 0 Tesla K80 On | 00000000:06:00.0 Off | 0 |
| N/A 30C P8 27W / 149W | 0MiB / 11439MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
| 1 Tesla K80 On | 00000000:07:00.0 Off | 0 |
| N/A 24C P8 27W / 149W | 0MiB / 11439MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: GPU Memory |
| GPU PID Type Process name Usage |
|=============================================================================|
| No running processes found |
+-----------------------------------------------------------------------------+
```
Then I launch Julia in this bash and try to compile `CUDAdrv`. (I have two installations… one local to my home directory v1.2 and one installed at the system level 1.0.3 that no one uses).
```julia
[affans@node018 ~]$ export JULIA_CUDA_VERBOSE=true
[affans@node018 ~]$ ./bin/julia
_
_ _ _(_)_ | Documentation: https://docs.julialang.org
(_) | (_) (_) |
_ _ _| |_ __ _ | Type "?" for help, "]?" for Pkg help.
| | | | | | |/ _` | |
| | |_| | | | (_| | | Version 1.2.0 (2019-08-20)
_/ |\ __'_|_|_|\__'_| | Official https://julialang.org/ release
|__/ |
julia> using CUDAdrv
┌ Error: CUDAdrv.jl failed to initialize
│ exception =
│ CUDA error: unknown error (code 999, ERROR_UNKNOWN)
│ Stacktrace:
│ [1] throw_api_error(::CUDAdrv.cudaError_enum) at /home/affans/.julia/packages/CUDAdrv/i465Q/src/error.jl:131 │ [2] macro expansion at /home/affans/.julia/packages/CUDAdrv/i465Q/src/error.jl:144 [inlined]
│ [3] cuInit at /home/affans/.julia/packages/CUDAdrv/i465Q/src/libcuda.jl:18 [inlined]
│ [4] __init__ () at /home/affans/.julia/packages/CUDAdrv/i465Q/src/CUDAdrv.jl:56
│ [5] _include_from_serialized(::String, ::Array{Any,1}) at ./loading.jl:685
│ [6] _require_search_from_serialized(::Base.PkgId, ::String) at ./loading.jl:765
│ [7] _require(::Base.PkgId) at ./loading.jl:990
│ [8] require(::Base.PkgId) at ./loading.jl:911
│ [9] require(::Module, ::Symbol) at ./loading.jl:906
│ [10] eval(::Module, ::Any) at ./boot.jl:330
│ [11] eval_user_input(::Any, ::REPL.REPLBackend) at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.2/REPL/src/REPL.jl:86
│ [12] macro expansion at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.2/REPL/src/REPL.jl:118 [inlined]
│ [13] (::getfield(REPL, Symbol("##26#27")){REPL.REPLBackend})() at ./task.jl:268
└ @ CUDAdrv ~/.julia/packages/CUDAdrv/i465Q/src/CUDAdrv.jl:67
```
The error message is very cryptic. No idea how to even debug this.
I think I should use a basic C script first to test out the GPUs and making sure the libraries work before using Julia. Is there a basic C script that simply prints out the name of the devices?
---
### Author:  [@maleadt](https://discourse.julialang.org/u/maleadt)
#### Post date: [December 20, 2019, 10:12pm UTC](https://discourse.julialang.org/t/failed-to-load-cudadrv/32524/2 "2019-12-20T22:12:39Z")
> [@affans](#):
>
> The error message is very cryptic. No idea how to even debug this.
We can’t provide you with much more information though, that’s just what the NVIDIA driver reports. Please make sure CUDA C-compiled binaries work (the CUDA toolkit comes with samples). This error happens when initializing CUDA, and is one of the first things CUDAdrv does. Typically it is not Julia/CUDAdrv related.
---
### Author:  [@affans](https://discourse.julialang.org/u/affans)
#### Post date: [December 25, 2019, 9:33pm UTC](https://discourse.julialang.org/t/failed-to-load-cudadrv/32524/3 "2019-12-25T21:33:34Z")
That’s what I figured. What would be the simplest C script to run to see if everything is working as intended? “simple C GPU script” dosn’t really help on Google.
---
### Author:  [@KajWiik](https://discourse.julialang.org/u/KajWiik)
#### Post date: [December 26, 2019, 1:02am UTC](https://discourse.julialang.org/t/failed-to-load-cudadrv/32524/4 "2019-12-26T01:02:22Z")
See e.g.
> **[CUDA Samples :: CUDA Toolkit Documentation](https://docs.nvidia.com/cuda/cuda-samples/index.html#simple)**
>
> CUDA Samples.
Here’s how I compiled and tested Julia CUDA libraries in our cluster:
```julia
mkdir bin; cd bin
curl -o julia-1.3.0-linux-x86_64.tar.gz https://julialang-s3.julialang.org/bin/linux/x64/1.3/julia-1.3.0-linux-x86_64.tar.gz
tar xzvf julia-1.3.0-linux-x86_64.tar.gz
module add CUDA
ln -s julia-1.3.0 julia
julia/bin/julia
]
pkg> add CUDAapi CUDAdrv CUDAnative CuArrays BenchmarkTools DiffResults ForwardDiff Compat
```
```julia
cat > buildcuarrays.jl
using Pkg
Pkg.test("CuArrays")
```
```julia
srun -p gpu --mem=50G --time=5:00:00 bash -c 'pwd;echo $SLURMD_NODENAME;~/bin/julia-1.3.0/bin/julia ~/bin/testcuarrays.jl'
```