TLDR Tech / DevOps
How we built Elasticsearch simdvec to make vector search one of the fastest in the world
Elasticsearch's simdvec is a hand-tuned SIMD kernel library that accelerates vector distance computations across all query types, using techniques like bulk scoring, prefetching, and architecture-specific optimizations to significantly outperform alternatives—especially at large scale when data exceeds CPU cache. Its biggest advantage comes not from raw compute speed but from efficiently hiding memory latency, enabling faster, more scalable vector search across diverse data types and hardware.
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