Expand description
Binary Quantization (BBQ) for OmenDB
1-bit quantization with SIMD-optimized Hamming distance.
§Algorithm
- Quantize: bit[d] = 1 if f32[d] > threshold[d] else 0
- Distance: Hamming distance via XOR + popcnt
- Correction: Apply norm-based correction for accurate ranking
§Performance
- 32x compression (f32 → 1 bit)
- 2-4x faster search than SQ8 (SIMD Hamming is extremely fast)
- ~85% raw recall, ~95-98% with rescore
§When to Use
- Dimensions >= 384 (below this, SQ8 has better recall)
- Large datasets (>100K vectors) where memory matters
- Cost-sensitive deployments
Structs§
- Binary
Params - Binary quantization parameters
Functions§
- corrected_
distance - Compute corrected distance for binary quantization
- hamming_
distance - Compute Hamming distance between two binary vectors