Using XLA to enhance computational performance

Accelerated linear algebra (XLA) is a domain-specific compiler for linear algebra. According to https://www.tensorflow.org/performance/xla/, it is still in the experimental stage and is used to optimize TensorFlow computations. It can provide improvements in execution speed, memory usage, and portability on the server and mobile platforms. It provides two-way JIT (Just In Time) compilation or AoT (Ahead of Time) compilation. Using XLA, you can produce platform-dependent binary files (for a large number of platforms like x64, ARM, and so on), which can be optimized for both memory and speed.