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KatoANN: Enabling Near-Exact Vector Search at the Speed of Lossy Scans with CPU Matrix Engines
Distance scans in partition-family approximate nearest-neighbor (ANN) search are typically limited by memory bandwidth. Existing systems therefore improve throughput by reading fewer bytes per candidate, often at the cost of recall. We present KatoANN, a CPU ANN search system that removes this trade
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