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)
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Authors
- 1. Alexander Krause (Technical University of Dresden)
- 2. Thomas Kissinger (Technical University of Dresden)
- 3. Dirk Habich (Technical University of Dresden)
- 4. Wolfgang Lehner (Technical University of Dresden)
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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| 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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