How does NumPy optimize reductions like sum along axes?

NumPy performs axis reductions using optimized C loops with memory-aware traversal.

Reduction operations like sum, mean, and max are optimized by traversing memory in the most contiguous order possible. NumPy selects loop order based on strides to maximize cache locality. In some builds, parallel execution is used for large arrays.