"RuntimeError: Found no NVIDIA driver on your system" despite meeting driver requirements for CUDA 11.8

3outeille: <p>Hi,</p>
<p>I am trying to run the following snippet of code in torch 2 with the following command <code>LD_LIBRARY_PATH=/usr/local/cuda-11.8/targets/x86_64-linux/lib/stubs/libcuda.so python draft.py</code></p>
<pre><code class="lang-auto">import torch
print(torch.cuda.get_device_name(0))
</code></pre>
<p>but got the following error</p>
<pre><code class="lang-auto">torch._C._cuda_init()
RuntimeError: Found no NVIDIA driver on your system. Please check that you have an NVIDIA GPU and installed a driver from http://www.nvidia.com/Download/index.aspx
</code></pre>
<ul>
<li>I checked the minimum driver version for CUDA 11.8 and I meet the minimum requirements:</li>
</ul>
<p><img src="https://i.imgur.com/SAOI3sD.png" alt="" role="presentation" width="690" height="148"></p>
<p><img src="https://i.imgur.com/0KZzLtD.png" alt="" role="presentation" width="490" height="304"></p>
<ul>
<li>Here is my env information:</li>
</ul>
<pre><code class="lang-auto">Collecting environment information...
PyTorch version: 2.0.0.dev20230209+cu118
Is debug build: False
CUDA used to build PyTorch: 11.8
ROCM used to build PyTorch: N/A
OS: CentOS Linux 7 (Core) (x86_64)
GCC version: (GCC) 4.8.5 20150623 (Red Hat 4.8.5-44)
Clang version: Could not collect
CMake version: version 3.25.0
Libc version: glibc-2.17
Python version: 3.9.12 (main, Feb  9 2023, 16:08:09)  [GCC 4.8.5 20150623 (Red Hat 4.8.5-44)] (64-bit runtime)
Python platform: Linux-5.4.188-1.el7.x86_64-x86_64-with-glibc2.17
Is CUDA available: True
CUDA runtime version: 11.8.89
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: GPU 0: Tesla V100-PCIE-16GB
Nvidia driver version: 520.61.05
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True
CPU:
Architecture:          x86_64
CPU op-mode(s):        32-bit, 64-bit
Byte Order:            Little Endian
CPU(s):                32
On-line CPU(s) list:   0-31
Thread(s) per core:    2
Core(s) per socket:    8
Socket(s):             2
NUMA node(s):          2
Vendor ID:             GenuineIntel
CPU family:            6
Model:                 85
Model name:            Intel(R) Xeon(R) Gold 6134 CPU @ 3.20GHz
Stepping:              4
CPU MHz:               3326.804
CPU max MHz:           3700.0000
CPU min MHz:           1200.0000
BogoMIPS:              6400.00
Virtualization:        VT-x
L1d cache:             32K
L1i cache:             32K
L2 cache:              1024K
L3 cache:              25344K
NUMA node0 CPU(s):     0-7,16-23
NUMA node1 CPU(s):     8-15,24-31
Flags:                 fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf pni pclmulqdq dtes64 monitor ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l3 cdp_l3 invpcid_single pti intel_ppin ssbd mba ibrs ibpb stibp tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 erms invpcid rtm cqm mpx rdt_a avx512f avx512dq rdseed adx smap clflushopt clwb intel_pt avx512cd avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local dtherm ida arat pln pts hwp hwp_act_window hwp_pkg_req pku ospke md_clear flush_l1d arch_capabilities
Versions of relevant libraries:
[pip3] numpy==1.24.1
[pip3] pytorch-triton==2.0.0+0d7e753227
[pip3] torch==2.0.0.dev20230209+cu118
[pip3] torchaudio==2.0.0.dev20230208+cu118
[pip3] torchvision==0.15.0.dev20230209+cu118
[conda] Could not collect
</code></pre>

ptrblck: <p>You are trying to add the stub <code>libcuda.so</code> to your dynamic linker, which won’t work. Use the real <code>libcuda.so</code> instead. I also don’t know why you would try to add files manually to <code>LD_LIBRARY_PATH</code> in the first place as the driver installation should have added the right paths (not files) to this env variable.</p>

3outeille: <p>I did a cleanup and installed cudnn 8.5 and cuda 11.7 without manually setting any env variables. Now I found myself with a <code>/usr/bin/ld: cannot find -lcuda</code></p>
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