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)
Incoming Non-self Citations Over Time
Authors
- 1. Yiqiu Wang
- 2. Anshumali Shrivastava
- 3. Jonathan Wang
- 4. Junghee Ryu
Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 4,230 | Locality-Sensitive Hashing Scheme based on Longest Circular Co-Substring | 2020 | SIGMOD | 6.3337893e-05 |
| 10,103 | Query-Aware Path Inference from Spatial Videos | 2026 | SIGMOD | 4.1905499e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 5 of 5 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 78 | A Quantitative Analysis and Performance Study for Similarity-Search Methods in High-Dimensional Spaces | 1998 | VLDB | 0.00056385781 |
| 399 | Multi-Probe LSH: Efficient Indexing for High-Dimensional Similarity Search | 2007 | VLDB | 0.00024359304 |
| 579 | Locality-Sensitive Hashing Scheme Based on Dynamic Collision Counting | 2012 | SIGMOD | 0.0001982328 |
| 2,872 | Streaming Similarity Search over one Billion Tweets using Parallel Locality-Sensitive Hashing | 2013 | VLDB | 7.9797548e-05 |
| 3,689 | Database-friendly Random Projections | 2001 | PODS | 6.8363304e-05 |
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