CPUs don't have vector search instructions. You borrow from neural nets and video codecs instead.
Elasticsearch's simdvec engine reformulates vector math to fit whatever the CPU already runs fast. Four recent examples:
- int7 quantization: fit unsigned-only multiply-accumulate by trading 1 bit of precision. ~6x faster.
- int8 bias rewrite: algebraic shift + precomputed correction. ~20% bulk gain.
- bf16 Euclidean distance as 3 dot products instead of a float32 conversion. Up to 2.4x.
- Binary dot product via popcount: AND the bits, count the 1s. ~4x over scalar.
A compiler can't make these calls. Each one requires reformulating the problem to fit an instruction the hardware was never designed to use this way.