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Randomized Algorithms Accelerated over CPU-GPU for Ultra-High Dimensional Similarity Search

Summary: FLASH: CPU-GPU accelerated LSH-style similarity search for ultra-high dimensional data on a single node. Fuses reservoir sampling, minwise hashing, and count-based estimations with HPC optimizations to cut compute, delivering sub-10s full k-NN on webspam. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5571
Venue
SIGMOD
Year
2018
Pagerank
4.768971e-05
Overall Rank
7,301 | 49.21%
DOI
10.1145/3183713.3196925

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Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
4,243 Locality-Sensitive Hashing Scheme based on Longest Circular Co-Substring 2020 SIGMOD 6.32976e-05
10,103 Query-Aware Path Inference from Spatial Videos 2026 SIGMOD 4.1945683e-05
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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