PQ FastScan

pqfs is a SIMD-accelerated variant of Product Quantization that fixes pq_bits = 4 and uses a memory layout designed for the AVX-2 / AVX-512 “FastScan” lookup-table kernel. At the cost of being 4-bit only, it delivers significantly higher distance-computation throughput.

Implementation: src/quantization/product_quantization/pq_fastscan_quantizer.cpp, parameter file pq_fastscan_quantizer_parameter.cpp.

When to use it

• The platform has AVX-2 (and ideally AVX-512); the FastScan kernel is the main reason to choose pqfs over pq.
• Search throughput, not just memory, matters.
• 4-bit subspace codebooks (16 centroids per subvector) are sufficient for your recall target — typically yes when combined with reorder.

If your platform does not advertise the required SIMD width, fall back to plain pq.

Memory cost (codes only)

ceil(pq_dim / 2) = (pq_dim + 1) / 2 bytes per vector — both even and odd pq_dim are supported (src/quantization/product_quantization/pq_fastscan_quantizer.cpp:41). Codebooks: pq_dim × 16 × subspace_dim × 4 bytes — significantly smaller than 8-bit pq because the codebook has only 16 centroids per subspace.

Parameters

Exposed on HGraph as base_pq_dim (src/algorithm/hgraph.cpp:465-472).

{
    "dtype": "float32",
    "metric_type": "l2",
    "dim": 128,
    "index_param": {
        "base_quantization_type": "pqfs",
        "base_pq_dim": 32,
        "max_degree": 32,
        "ef_construction": 300,
        "use_reorder": true,
        "precise_quantization_type": "fp16"
    }
}

Training

NEED_TRAIN is set. Trains 16-centroid codebooks per subspace; cheaper than the 256-centroid training in pq.

Metric compatibility

l2, ip, cosine — same coverage as pq. The LUT layout is metric- specific but transparently handled by the quantizer.

Tips

• pq_dim should be a multiple of the SIMD-batch width the kernel expects (the implementation uses 32 internally on AVX-512). When in doubt, choose pq_dim ∈ {32, 64, 96, 128}.
• The benefit over pq is throughput at the same recall, not memory (4-bit codes are inherently smaller, but pq with pq_bits = 4 would match).
• For maximum recall recovery, pair with use_reorder: true and an fp16 or fp32 precise store.

Related pages

• Product Quantization (PQ)
• HGraph index
• Transform Quantizer
• Quantization overview