1. Download and install CUDA v9.2+ from the NVIDIA developer website URL: https://developer.nvidia.com/cuda-downloads.
2. Configure the CUDA dependencies. For Linux, go to a Terminal and edit the .bashrc file. Run the following commands and make sure you replace username and the CUDA version number as per your downloaded version:

nano /home/username/.bashrc
 export PATH=/usr/local/cuda-9.2/bin${PATH:+:${PATH}}$
 
 export LD_LIBRARY_PATH=/usr/local/cuda-9.2/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
 
 source .bashrc
 

3. Add the lib64 directory to PATH for older DL4J versions.
4. Run the nvcc --version command to verify the CUDA installation.
5. Add Maven dependencies for the ND4J CUDA backend:

<dependency>
 <groupId>org.nd4j</groupId>
 <artifactId>nd4j-cuda-9.2</artifactId>
 <version>1.0.0-beta3</version>
 </dependency> 

6. Add the DL4J CUDA Maven dependency:

<dependency>
 <groupId>org.deeplearning4j</groupId>
 <artifactId>deeplearning4j-cuda-9.2</artifactId>
 <version>1.0.0-beta3</version>
 </dependency> 

7. Add cuDNN dependencies to use bundled CUDA and cuDNN:

<dependency>
 <groupId>org.bytedeco.javacpp-presets</groupId>
 <artifactId>cuda</artifactId>
 <version>9.2-7.1-1.4.2</version>
 <classifier>linux-x86_64-redist</classifier> //system specific
 </dependency>