CUDA_ERROR_NO_DEVICE "no CUDA-capable device is detected"

[EricLBuehler]

Hello all,

Thanks for your great work here! When I run using cudarc, I get the error:

called `Result::unwrap()` on an `Err` value: Cuda(Cuda(DriverError(CUDA_ERROR_NO_DEVICE, "no CUDA-capable device is detected")))

Here is my system information:

$ nvidia-smi
Tue Jun 11 23:53:28 2024       
+---------------------------------------------------------------------------------------+
| NVIDIA-SMI 535.72                 Driver Version: 536.45       CUDA Version: 12.2     |
|-----------------------------------------+----------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |         Memory-Usage | GPU-Util  Compute M. |
|                                         |                      |               MIG M. |
|=========================================+======================+======================|
|   0  Quadro M2000M                  On  | 00000000:01:00.0 Off |                  N/A |
| N/A    0C    P8              N/A / 200W |      0MiB /  4096MiB |      1%      Default |
|                                         |                      |                  N/A |
+-----------------------------------------+----------------------+----------------------+

+---------------------------------------------------------------------------------------+
| Processes:                                                                            |
|  GPU   GI   CI        PID   Type   Process name                            GPU Memory |
|        ID   ID                                                             Usage      |
|=======================================================================================|
|    0   N/A  N/A        33      G   /Xwayland                                 N/A      |
+---------------------------------------------------------------------------------------+

$ nvcc -V
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2024 NVIDIA Corporation
Built on Wed_Apr_17_19:19:55_PDT_2024
Cuda compilation tools, release 12.5, V12.5.40
Build cuda_12.5.r12.5/compiler.34177558_0

$ nvidia-smi --query-gpu=compute_cap --format=csv
compute_cap
5.0

$ echo $CUDA_VISIBLE_DEVICES
0

I would appreciate any help!

[coreylowman]

Is pytorch able to see the GPU? Also what cuda toolkit version is being targeted by cudarc (if using cuda-version-from-build-system, is it being compiled on this machine?)

[coreylowman]

@EricLBuehler any more information on this issue? Will close in a week if not

[EricLBuehler]

@coreylowman sorry for not getting back! I am running this on my GPU and Pytorch can see it (torch.cuda.is_available() == True).

[coreylowman]

@EricLBuehler are there any differences with dynamic loading vs dynamic linking features for cudarc? Also curious about what toolkit version you are targeting in cudarc features

[EricLBuehler]

I am using cuda-version-from-build-system and dynamic-linking. How should I try dynamic loading?

[coreylowman]

If you don't enable the dynamic-linking feature it will use dynamic loading.

🤔 Could you try targeting 12.2 (cuda-12020) instead of version from build system? Just curious if that would change anything.

[EricLBuehler]

Hmm yeah, same error. Current:

cudarc = { version = "0.11.5", features = ["std", "cublas", "cublaslt", "curand", "driver", "nvrtc", "f16", "cuda-12020"], default-features=false }

[coreylowman]

I got nothing off the top of my head. Do you get this error if you git clone cudarc and try to run the unit tests?

cargo test --tests --no-default-features -F std,cuda-12050,driver

Is this running inside a docker container?

If that doesn't work I'd probably try to go to c++ level and verify a simple example there that links to cuda finds gpu. If that doesn't work then that at least tells us that pytorch is doing something special that we need to copy.

[jianshu93]

Hi both, I also have as similar error:

DriverError(CUDA_ERROR_INVALID_PTX, "a PTX JIT compilation failed") note: run with RUST_BACKTRACE=1 environment variable to display a backtrace Aborted [jzhao399@atl1-1-02-018-25-0 release]$ which nvidia-smi /usr/bin/nvidia-smi [jzhao399@atl1-1-02-018-25-0 release]$ nvidia-smi Wed Jul 17 11:25:54 2024
+-----------------------------------------------------------------------------------------+ | NVIDIA-SMI 550.54.15 Driver Version: 550.54.15 CUDA Version: 12.4 | |-----------------------------------------+------------------------+----------------------+ | GPU Name Persistence-M | Bus-Id Disp.A | Volatile Uncorr. ECC | | Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. | | | | MIG M. | |=========================================+========================+======================| | 0 NVIDIA A100-PCIE-40GB On | 00000000:C1:00.0 Off | 0 | | N/A 34C P0 43W / 250W | 0MiB / 40960MiB | 0% Default | | | | Disabled | +-----------------------------------------+------------------------+----------------------+

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

via PyTorch, this can be solved but not sure how to solve here.

Thanks,

Jianshu