Float16 vs bfloat16: bfloat16 has same exponent range as float32, less precision but more stable

What LSM trees optimize: write-heavy workloads by buffering writes in memory

LSM trees optimize write-heavy workloads through in-memory buffering

Why memory coalescing matters — adjacent threads reading adjacent memory addresses

Memory coalescing reduces cache misses, improving multithreaded application performance

Why second-order methods (Newton's) converge faster but are expensive: O(n³) per step

Newton's method has quadratic convergence but requires cubic computational cost per iteration

Time complexity of binary search: O(log n) — halves search space each step

Binary search reduces search space by half with each iteration, achieving O(log n) complexity

What BPE tokenization does: iteratively merges the most frequent byte pairs

BPE tokenization merges the most frequent byte pairs iteratively to create subword units

How tiling works in matrix multiplication — loading blocks into shared memory

Tiling in matrix multiplication optimizes cache usage by partitioning matrices into submatrices