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: 10778
Venue: VLDB
Year: 2013
Pagerank: 5.594227e-05
Overall Rank: 7,571 | 48.06%
DOI: 10.14778/2536274.2536293

Incoming Non-self Citations Over Time

Authors

1. Jianlong Zhong (Nanyang Technological University)
2. Bingsheng He (Nanyang Technological University)

BibTeX Citation

@article{zhong_vldb13,
        title = {{Parallel Graph Processing on Graphics Processors Made Easy}},
        author = {Zhong, Jianlong and He, Bingsheng},
        journal = {PVLDB},
        series = {{VLDB} '13},
        volume = {6},
        number = {12},
        pages = {1270--1273},
        doi = {10.14778/2536274.2536293},
        url = {https://doi.org/10.14778/2536274.2536293},
        year = {2013}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
2,874	iBFS: Concurrent Breadth-First Search on GPUs	2016	SIGMOD	8.0094569e-05

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
3	Pregel: A System for Large-Scale Graph Processing	2010	SIGMOD	0.0012250108

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