DBScholar

Back to papers

Realtime Top-k Personalized PageRank over Large Graphs on GPUs

Summary: Realtime top-k Personalized PageRank on Internet-scale graphs with GPUs. kPAR combines adaptive forward push and inverted random walks with GPU-aware load balancing, delivering quality guarantees and ~10x CPU speedups. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
12247
Venue
VLDB
Year
2020
Pagerank
6.821373e-05
Overall Rank
4,225 | 71.02%
DOI
10.14778/3357377.3357379

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{shi_vldb20,
        title = {{Realtime Top-k Personalized PageRank over Large Graphs on GPUs}},
        author = {Shi, Jieming and Yang, Renchi and Jin, Tianyuan and Xiao, Xiaokui and Yang, Yin},
        journal = {PVLDB},
        series = {{VLDB} '20},
        volume = {13},
        number = {1},
        pages = {15--28},
        doi = {10.14778/3357377.3357379},
        url = {https://doi.org/10.14778/3357377.3357379},
        year = {2020}
}

Incoming Citations (Sorted by Pagerank)

Showing 11 of 11 citing papers.

Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 13 of 13 cited papers.

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

Previous Page 1 / 1 Next

Semantically Similar Papers