Whether you're a beginner in machine learning or an experienced AI developer, setting up the right environment is crucial for efficient model training and inference. One key component of GPU-accelerated deep learning is NVIDIA's CUDA Deep Neural Network library (cuDNN). In this forum post, we’ll provide a detailed and beginner-friendly guide on how to install cuDNN on Ubuntu 22.04, using instructions adapted from the official Vultr tutorial.



Why cuDNN Is Important

cuDNN is a GPU-accelerated library that provides highly optimized implementations for deep learning operations such as forward and backward convolution, normalization, and activation layers. It is widely used by machine learning frameworks like TensorFlow, PyTorch, and Keras to leverage NVIDIA GPUs for faster computations.

Installing cuDNN correctly can significantly reduce training time and improve the efficiency of your AI workflows. If you're working with Ubuntu 22.04 and an NVIDIA GPU, following this guide ensures you’ll get the best performance out of your setup.



Prerequisites

Before installing cuDNN, ensure you have:

A system running Ubuntu 22.04





A compatible NVIDIA GPU





Installed NVIDIA drivers





The CUDA Toolkit installed and configured





If you haven’t installed the NVIDIA driver or CUDA Toolkit yet, make sure to follow the appropriate installation guides before proceeding with cuDNN.



Step-by-Step: Install cuDNN on Ubuntu 22.04

Step 1: Download cuDNN

Visit the NVIDIA cuDNN download page and sign in with your NVIDIA Developer account. Select the version of cuDNN that matches your installed CUDA version. For Ubuntu 22.04, download the following .deb files:

libcudnn8_*.deb





libcudnn8-dev_*.deb





libcudnn8-samples_*.deb





Save all three files in a local directory.



Step 2: Install cuDNN Packages

Open a terminal, navigate to the folder where the .deb packages were downloaded, and run the following commands:

sudo dpkg -i libcudnn8_*.deb

sudo dpkg -i libcudnn8-dev_*.deb

sudo dpkg -i libcudnn8-samples_*.deb



These commands will install the runtime libraries, development headers, and sample applications required for testing the installation.



Step 3: Verify cuDNN Installation

To test whether cuDNN is properly installed, compile and run the sample code provided with the installation:

cp -r /usr/src/cudnn_samples_v8/ ~/

cd ~/cudnn_samples_v8/mnistCUDNN

make

./mnistCUDNN



If the output displays inference results without any errors, your cuDNN installation is complete and functioning correctly.

Conclusion

Knowing how to install cuDNN on Ubuntu 22.04 is essential for any developer working in the AI or deep learning space. With cuDNN correctly installed, your system is now capable of running GPU-accelerated workloads that can handle complex neural network models more efficiently.

The Vultr guide offers a reliable and easy-to-follow approach that simplifies the entire process. Bookmark it as a reference for future setups or troubleshooting. With cuDNN on board, you're ready to take your AI projects to the next level.