Cudnn-11.2-linux-x64-v8.1.1.33.tgz

: Ensure /usr/local/cuda/lib64 is in your LD_LIBRARY_PATH environment variable so your software can find the libraries.

: Ensure you have the matching CUDA version installed. You can verify this by running nvcc --version in your terminal.

sudo chmod a+r /usr/local/cuda/include/cudnn*.h /usr/local/cuda/lib64/libcudnn* Use code with caution. Copied to clipboard Verification cudnn-11.2-linux-x64-v8.1.1.33.tgz

To install the cudnn-11.2-linux-x64-v8.1.1.33.tgz library on Linux, you need to extract the archive and copy its contents into your existing CUDA Toolkit directory. This specific version is designed for on 64-bit Linux systems. Prerequisites

This will create a directory named cuda containing include and lib64 subdirectories. sudo chmod a+r /usr/local/cuda/include/cudnn*

You should see values representing , Minor 1 , and Patch 1 . Troubleshooting

sudo cp cuda/include/cudnn*.h /usr/local/cuda/include sudo cp -P cuda/lib64/libcudnn* /usr/local/cuda/lib64 Use code with caution. Copied to clipboard Prerequisites This will create a directory named cuda

Do you need help to a specific framework like TensorFlow or PyTorch? Installing cuDNN Backend on Windows