Database Paper Browser

Back to papers

Accelerating Dynamic Graph Analytics on GPUs

Summary: Proposes an update-efficient GPU storage scheme for dynamic graphs to support high-velocity stream updates and immediate analytics. Introduces parallel GPU update algorithms and demonstrates superior performance on three streaming applications with real and synthetic data. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
11601
Venue
VLDB
Year
2018
Pagerank
6.0709631e-05
Overall Rank
4,577 | 68.16%
DOI
10.14778/3136610.3136619

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 14 of 14 citing papers.

Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 9 of 9 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