Part 5/12:
JAX's jit decorator compiles functions into highly optimized machine code at runtime, resulting in significant performance boosts. For example, in one test, applying JIT for a softmax function reduced execution time from ~14 milliseconds to under 8 milliseconds, a 50% speedup—a critical enhancement in real-world scenarios.
Vectorization and Parallelism
JAX promotes automatic vectorization through transformations like vmap, which allow efficient batch processing without explicit loops. It replaces nested or heavy for-loops with vectorized operations, greatly improving efficiency and reducing code complexity.