Download and install CUDA v9.2+ from the NVIDIA developer website URL: https://developer.nvidia.com/cuda-downloads .
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 y our 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
Add the lib64 directory to PATH for older DL4J versions.
Run the nvcc --version command to verify the CUDA installation.
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>
Add the DL4J CUDA Maven dependency:
<dependency> <groupId>org.deeplearning4j</groupId> <artifactId>deeplearning4j-cuda-9.2</artifactId> <version>1.0.0-beta3</version> </dependency>
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>
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