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  2. How to do I update CUDA driver nvidia on Windows 10?

    stackoverflow.com/questions/60979854

    9. Uninstall your current installation of CUDA. Note that the installation guide for CUDA is here. Read the description in the installation guide, go to this page, choose your OS, architecture, CUDA version ("11" will give you the latest version), and installer type (choose 'local' and then download a 2 to 3 GB installer file).

  3. nvidia-smi --query-gpu=driver_version --format=csv,noheader --id=0 returns result as a string that doesn't require further parsing like: 470.82.00. In case nvidia-smi is not available for some reason, information can be obtained by calling into driver APIs. Driver libraries can be loaded using Python ctypes library.

  4. How to install NVIDIA graphics driver on Azure VM

    stackoverflow.com/questions/66288275

    1. Under advanced settings during the setup of a VM, you can click on 'select an extension to install' which will give the option to install an NVIDIA driver (among others). This is to add an extension via UI and my reply is to add the extension with the PowerShell command. It works the same.

  5. Make sure an nvidia driver is installed on the host system. Follow the steps here to setup the nvidia container toolkit. Make sure cuda, cudnn is installed in the image. Run a container with the --gpus flag (as explained in the link above) I guess you have done the first 3 points because nvidia-docker2 is working.

  6. It looks like my docker image needs an nvidia driver. I've modified the Dockerfile like this: FROM ubuntu:18.04. RUN apt install software-properties-common. RUN add-apt-repository ppa:graphics-drivers. RUN apt update. RUN apt install nvidia-driver-440. COPY addarrays /addarrays. ENTRYPOINT [ "/addarrays" ]

  7. Following the above link, you might have to purge your current cuda installation for a while, but it can be easily installed once you have upgraded your NVIDIA drivers. I highly recommend that you purge your current installation of CUDA before going ahead, as a lot of links are formed during the installation, which might be the cause of the ...

  8. In the test above I was using nvidia-driver-525 I've tried using different versions of the driver with the same results. At this point I'm not sure if I'm doing something wrong or if Vulkan is not supported in the Nvidia Container Toolkit for Ubuntu 22.04 even though it claims to be.

  9. Solution 3: hold specific packages. Use this guide on how to hold certain packages. Read the apt history as mentioned above to determine which packages you have to put on hold. Probably CUDA related packages such as nvidia-cuda-toolkit. Hard to say since some information is missing from your post.

  10. Different CUDA versions shown by nvcc and NVIDIA-smi

    stackoverflow.com/questions/53422407

    The discrepancy between the CUDA versions reported by nvcc --version and nvidia-smi is due to the fact that they report different aspects of your system's CUDA setup. nvcc --version reports the version of the CUDA toolkit you have installed. This is the version that is used to compile CUDA code. nvidia-smi, on the other hand, reports the ...

  11. I installed WSL2, and installed NVIDIA driver for Cuda on WSL from GeForce Driver: https: ...