How does NumPy handle alignment and memory padding?

NumPy aligns data in memory for optimal CPU access and cache efficiency.

Aligned memory ensures faster SIMD and vectorized instructions. Padding may be introduced between elements in structured arrays to satisfy hardware alignment constraints, improving performance in low-level operations.