1. Downloading cuDNN
In order to download cuDNN, ensure you are registered for the NVIDIA Developer Program.
- Go to: NVIDIA cuDNN home page. (https://developer.nvidia.com/rdp/cudnn-download)
- Join/Signup and complete the short survey and click Submit.
- Accept the Terms and Conditions. A list of available download versions of cuDNN displays.
- Select the cuDNN version you want to install. A list of available resources displays. (I prefer
cuDNN v7.0 Library for Linux)
2. Before we begin, let's assume that -
- your CUDA directory path is referred to as /usr/local/cuda/
- your cuDNN download path is referred to as
3. Installing from a Tar File (In may case: cudnn-9.0-linux-x64-v7.tgz)
- Navigate to your
directory containing the cuDNN Tar file.
- Unzip the cuDNN package.
$ tar -xzvf cudnn-9.0-linux-x64-v7.tgz
- Copy the following files into the CUDA Toolkit directory.
$ sudo cp cuda/include/cudnn.h /usr/local/cuda/include $ sudo cp cuda/lib64/libcudnn* /usr/local/cuda/lib64 $ sudo chmod a+r /usr/local/cuda/include/cudnn.h /usr/local/cuda/lib64/libcudnn*
To verify that cuDNN is installed and is running properly, compile the mnistCUDNN sample located in the /usr/src/cudnn_samples_v7 directory in the debian file. If there is no such samples, download
cuDNN v7.0 Code Samples and User Guide for Ubuntu16.04 (Deb) from the same list mentioned above.
- Go to the writable path.
$ cd $HOME/cudnn_samples_v7/mnistCUDNN
- Compile the mnistCUDNN sample.
$ make clean && make
- Run the mnistCUDNN sample.
If cuDNN is properly installed and running on your Linux system, you will see a message similar to the following: Test passed!
Read more at: http://docs.nvidia.com/deeplearning/sdk/cudnn-install/index.html#ixzz4vJYBjUpe