NeMeSys - A Showcase of Data Oriented Near Memory Graph Processing
Summary: NUMA-aware, near-memory graph pattern processing engine enabling scalable in-memory graph analytics. It blends transactional DB techniques with graph processing, employing partitioning strategies and Bloom-filter messaging, and demonstrates energy-aware CPU frequency scaling. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Alexander Krause
- 2. Thomas Kissinger
- 3. Dirk Habich
- 4. Wolfgang Lehner
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| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9,721 | Adaptive Energy-Control for In-Memory Database Systems | 2018 | SIGMOD | 4.2965439e-05 |
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