SING is an in-memory index that uses the GPU's parallelization opportunities (as well as SIMD, multi-core and multi-socket), in order to accelerate similarity search.
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Updated
Sep 25, 2022 - C
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similarity-search
Here are 7 public repositories matching this topic...
Repository for the paper "Odyssey: A Journey in the Land of Distributed Data Series Similarity Search", Manos Chatzakis, Panagiota Fatourou, Eleftherios Kosmas, Themis Palpanas and Botao Peng, PVLDB 2023
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Feb 5, 2023 - C
The Similarity Search Tree is an efficient method for indexing high dimensional feature vectors. The main objective of this data structure is to obtain the nearest neighbors given a certain query vector in a reasonable amount of time. In this project, the k-NN algorithm was adapted for supporting image retrieval.
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Nov 13, 2023 - C
utils to use word embedding models like word2vec vectors in a PostgreSQL database
word2vec
postgresql
word-embeddings
knn-search
inverted-index
product-quantization
similarity-search
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Oct 6, 2021 - C
Similar images search for PostgreSQL
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Feb 22, 2024 - C
Up to 200x Faster Dot Products & Similarity Metrics — for Python, Rust, C, JS, and Swift, supporting f64, f32, f16 real & complex, i8, and bit vectors using SIMD for both AVX2, AVX-512, NEON, SVE, & SVE2 📐
information-retrieval
metrics
neon
numpy
assembly
simd
scipy
blas
avx2
similarity-measures
avx512
simd-instructions
distance-calculation
blas-libraries
arm-neon
similarity-search
float16
vector-search
bfloat16
arm-sve
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Nov 18, 2024 - C
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