DL4J/ND4J-specific configuration

Apart from general benchmarking guidelines, we need to follow additional benchmarking configurations that are DL4J/ND4J-specific. These are important benchmarking configurations that target the hardware and mathematical computations.

Because ND4J is the JVM computation library for DL4J, benchmarks mostly target mathematical computations. Any benchmarks discussed with regard to ND4J can then also be applied to DL4J. Let's discuss DL4J/ND4J-specific benchmarks.

Getting ready

Make sure you have downloaded cudNN from the following link: https://developer.nvidia.com/cudnn. Install it before attempting to configure it with DL4J. Note that cuDNN doesn't come as a bundle with CUDA. So...