Hi @MarkusHoHo,
Thank you for the warm welcome to the NVIDIA developer forums. I’m excited to be a part of the wider CUDA development community!
Regarding the installation of CUDA, I’ve tried two methods. First, I followed the instructions on the NVIDIA website to install CUDA. Additionally, I also used the command “pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu117” to install PyTorch with CUDA support. I want to mention that I’m using Windows and not Linux.
I have taken the necessary steps to ensure that all the required paths are correctly set up. I understand the importance of a proper setup, especially when it comes to using CUDA with PyTorch.
It’s good to know that the A1000 GPU is compatible with the latest CUDA versions.
However, I am still encountering the same issue where CUDA is not available.
I would also like to mention that I am using a virtual machine, specifically an ncv3 instance. I have installed the appropriate driver from the Azure website, which indicates that CUDA 11 is the suitable version for it. I created a new environment and installed all the necessary dependencies, including CUDA 11. I have verified the paths, and when I run “!nvidia-smi,” I get the following output:
+---------------------------------------------------------------------------------------+
| NVIDIA-SMI 531.14 Driver Version: 451.82 CUDA Version: 11.0 |
|-----------------------------------------+----------------------+----------------------+
| GPU Name TCC/WDDM | Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|=========================================+======================+======================|
| 0 Tesla V100-PCIE-16GB TCC | 00000001:00:00.0 Off | 0 |
| N/A 29C P0 25W / 250W| Not Supported | 0% Default |
| | | N/A |
+-----------------------------------------+----------------------+----------------------+
+---------------------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=======================================================================================|
| No running processes found |
+---------------------------------------------------------------------------------------+
Additionally, when I run “!nvcc --version,” I get the following output:
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2020 NVIDIA Corporation
Built on Thu_Jun_11_22:26:48_Pacific_Daylight_Time_2020
Cuda compilation tools, release 11.0, V11.0.194
Build cuda_11.0_bu.relgpu_drvr445TC445_37.28540450_0
However, when I run the following Python code:
print(torch.__version__)
print(torch.cuda.is_available())
print(torchvision.__version__)
I get the output:
2.0.1
False
0.15.2
I dant know what is the problem
If you have any further recommendations or details on CUDA setup, installation, or usage, I would greatly appreciate your guidance. Thank you once again for the warm welcome!