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Efficient Parallel Lists Intersection and Index Compression Algorithms using Graphics Processing Units

Summary: GPU-accelerated parallel list intersection using parallel binary search; long inverted lists grow roughly linearly, enabling Linear Regression and Hash Segmentation to contract search ranges. Introduces a Linear Regression compression schema and GPU-friendly intersection of compressed lists; demonstrates large throughput gains across datasets. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
10276
Venue
VLDB
Year
2011
Pagerank
9.686731e-05
Overall Rank
2,051 | 85.74%
DOI
-

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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
1,124 Improving the Performance of List Intersection 2009 VLDB 0.00013847565
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