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Awesome GitHub RepositoriesBatch Vector Queries
Techniques for processing multiple vector search queries simultaneously to maximize throughput.
Distinct from Vector Search: Distinct from Vector Search: focuses on the bulk processing of multiple queries as tensors rather than single-query retrieval.
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Awesome Batch Vector Queries GitHub Repositories
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- unum-cloud/usearch
unum-cloud/USearch
3,888Auf GitHub ansehenUSearch is a high-performance vector similarity search engine and approximate nearest neighbor index designed for dense embeddings. It functions as a low-level vector database core and high-dimensional vector indexer, providing the primitives necessary to store and retrieve vectors across massive datasets. The engine distinguishes itself through hardware-level SIMD acceleration for distance kernels and a proximity-graph indexing system that enables fast retrieval across billions of vectors. It supports multi-precision vector quantization to balance memory usage and accuracy, and utilizes memo
Enables simultaneous querying of multiple vectors using tensors to increase throughput for bulk workloads.
C++approximate-nearest-neighbor-searchclusteringdatabase
