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Asked: 2024-09-26T14:02:36+05:30 In:

What are the steps to install the NVIDIA CUDA toolkit on Ubuntu 18.04 for a Coffee Lake processor, and is it compatible?

I’ve been diving into some deep learning stuff lately and I’ve heard a lot about how awesome NVIDIA’s CUDA toolkit is for accelerating computations. I’m running Ubuntu 18.04 on my machine, which is powered by a Coffee Lake processor. However, I’ve done a bit of digging and I’m a bit confused about the compatibility and the whole installation process.

First off, I’ve read conflicting opinions on whether CUDA actually supports Coffee Lake processors since it’s more focused on the NVIDIA GPU side. Do I need to worry about my CPU type when it comes to CUDA installation or is it all about the GPU? I’ve got an NVIDIA GTX 1050, so I think my GPU should definitely support CUDA. But then again, I want to make sure everything is in sync before I jump into the installation.

Now, speaking of installation, I’ve seen some guides online that provide steps to install CUDA, but they all seem to have slight variations. So if anyone could break it down for me, that would be super helpful. Like, what are the specific commands I need to run in the terminal? Do I need to add any external repositories or dependencies first? Also, I’ve come across a few issues with the NVIDIA drivers that some people mention—like needing to blacklist Nouveau. Is that the case, and if so, how do I go about doing that without messing everything up?

Another thing I’m wondering about is whether I should install the latest version of the CUDA toolkit or is it better to stick with an older version that might be more stable with the software I’m planning to use?

It would be amazing if you legends could share your tips or even recount your own experiences with the process. It’d be great to compile all your insights into a step-by-step guide that can help not just me, but probably many others in the same boat. Thanks in advance for any help!

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    2 Answers



    1. CUDA Installation Guide for Ubuntu 18.04

      NVIDIA CUDA Toolkit Installation on Ubuntu 18.04

      CPU Compatibility

      Don’t stress too much about your Coffee Lake processor! CUDA is primarily concerned with your NVIDIA GPU (in your case, the GTX 1050),
      so as long as the GPU supports CUDA, you’re good to go. Your CPU type won’t affect the installation or functionality. Just make sure
      you have the latest drivers for your GPU!

      Installation Steps

      1. Update your package lists:

        sudo apt update
      2. Install required dependencies:

        sudo apt install build-essential dkms
      3. Add the NVIDIA package repository:

        sudo add-apt-repository ppa:graphics-drivers/ppa
      4. Install the NVIDIA drivers:

        sudo apt install nvidia-driver-470

        Replace ‘470’ with the latest driver version if necessary. Check the NVIDIA drivers page.

      5. Blacklist Nouveau drivers:

        To prevent conflicts with the NVIDIA drivers, you’ll need to blacklist Nouveau:

        
echo "blacklist nouveau" | sudo tee /etc/modprobe.d/blacklist-nouveau.conf
echo "options nouveau modeset=0" | sudo tee -a /etc/modprobe.d/blacklist-nouveau.conf
sudo update-initramfs -u
      6. Reboot your system:

        sudo reboot
      7. Install CUDA toolkit:

        Go to the CUDA downloads page and select the appropriate version for Ubuntu 18.04.

        You can choose to install via deb or runfile, but deb is usually easier:

        sudo apt install cuda

      Version Considerations

      It’s usually a good idea to install the latest stable version of CUDA unless you have specific software requirements that
      necessitate an older version. Check the documentation of the deep learning frameworks (like TensorFlow or PyTorch) you’re planning to use
      to see which version they recommend.

      Final Thoughts

      After everything, you can verify the installation by running:

      nvcc --version

      If it shows the version of CUDA, then you’re all set! Good luck with your deep learning journey!



    2. When it comes to CUDA installation, the good news is that the compatibility primarily revolves around your NVIDIA GPU rather than your CPU. Since you have an NVIDIA GTX 1050, you are indeed in the clear, as this GPU supports CUDA. Coffee Lake processors, or any CPU for that matter, do not present a barrier for CUDA installation. However, it is essential to ensure that your system meets the other requirements, such as having the appropriate NVIDIA driver installed to support your GPU and CUDA version. The installation process is mainly about ensuring your GPU drivers are up to date, so don’t stress too much about your Coffee Lake CPU; it won’t interfere with CUDA usage.

      For installing CUDA on Ubuntu 18.04, a straightforward method is to use the official NVIDIA repository. First, you’ll want to add the repository and update the package lists using the following commands in your terminal: sudo apt-key adv --fetch-keys http://developer.download.nvidia.com/compute/cuda/7fa2af80.pub followed by sudo add-apt-repository "deb http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/ " and sudo apt update. Once that’s set, you can install CUDA with sudo apt install cuda. Prior to installation, you may need to blacklist Nouveau by creating a file at /etc/modprobe.d/blacklist-nouveau.conf and adding the lines blacklist nouveau and options nouveau modeset=0 to it. Afterward, run sudo update-initramfs -u and reboot. As for choosing the version, if you are using newer deep learning frameworks, it’s usually recommended to go for the latest stable version of CUDA for compatibility, but ensure it supports your specific software stack. Overall, documenting each step and troubleshooting issues as they arise will streamline your experience—and don’t hesitate to refer to the official NVIDIA documentation for further guidance.


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