DBScholar

Back to papers

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

Summary: GPU-oriented inverted-list processing exploits empirically linear docID distributions: Linear Regression and Hash Segmentation tighten parallel intersection searches, while Linear Regression Compression enables parallel decompression. Experiments show higher query throughput than CPU-centric approaches. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
10467
Venue
VLDB
Year
2011
Pagerank
0.00010103504
Overall Rank
1,655 | 88.65%
DOI
10.14778/2002974.2002975

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{ao_vldb11,
        title = {{Efficient Parallel Lists Intersection and Index Compression Algorithms using Graphics Processing Units}},
        author = {Ao, Naiyong and Zhang, Fan and Wu, Di and Stones, Douglas S. and Wang, Gang and Liu, Xiaoguang and Liu, Jing and Lin, Sheng},
        journal = {PVLDB},
        series = {{VLDB} '11},
        volume = {4},
        number = {8},
        pages = {470--481},
        doi = {10.14778/2002974.2002975},
        url = {https://doi.org/10.14778/2002974.2002975},
        year = {2011}
}

Incoming Citations (Sorted by Pagerank)

Showing 12 of 12 citing papers.

Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 1 of 1 cited papers.

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

Rank Cited Paper Year Venue Pagerank
1,717 Improving the Performance of List Intersection 2009 VLDB 9.9327227e-05
Previous Page 1 / 1 Next

Semantically Similar Papers