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Parallel Graph Processing on Graphics Processors Made Easy

Summary: Medusa offers a GPU graph framework enabling sequential C/C++ via a tiny API, with a runtime that automatically parallelizes work on the GPU. Key novelty: graph-centric optimizations that exploit GPU architecture to accelerate real-world and synthetic graph workloads. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
10590
Venue
VLDB
Year
2013
Pagerank
4.804655e-05
Overall Rank
7,192 | 49.97%
DOI
-

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
3,233 iBFS: Concurrent Breadth-First Search on GPUs 2016 SIGMOD 7.3361904e-05
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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
4 Pregel: A System for Large-Scale Graph Processing 2010 SIGMOD 0.0019005923
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