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NeMeSys - A Showcase of Data Oriented Near Memory Graph Processing

Summary: NeMeSys is a NUMA-aware near-memory graph pattern engine combining transactional-database and graph-processing techniques for scalable in-memory execution. Its showcase explores partitioning, Bloom-filter messaging, workload control, and DVFS-based energy savings. (summarized by gpt-5.6-luna on Jul 21 2026)

Paper ID
5796
Venue
SIGMOD
Year
2019
Pagerank
-
Overall Rank
13,497 | 7.40%
DOI
10.1145/3299869.3320226

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Authors

BibTeX Citation

@inproceedings{krause_sigmod19,
        title = {{NeMeSys - A Showcase of Data Oriented Near Memory Graph Processing}},
        author = {Krause, Alexander and Kissinger, Thomas and Habich, Dirk and Lehner, Wolfgang},
        series = {{SIGMOD} '19},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3299869.3320226},
        url = {https://dl.acm.org/doi/10.1145/3299869.3320226},
        year = {2019}
}

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

Rank Cited Paper Year Venue Pagerank
9,858 Adaptive Energy-Control for In-Memory Database Systems 2018 SIGMOD 5.2061847e-05
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