Workload-Aware CPU Performance Scaling for Transactional Database Systems
Summary: POLARIS directly controls processor DVFS and DB transaction scheduling to minimize power while meeting latency. By exploiting workload knowledge, it outperforms OS DVFS governors in power and latency for mixed, fluctuating transactional workloads. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Mustafa Korkmaz
- 2. Martin Karsten
- 3. Kenneth Salem
- 4. Semih Salihoglu
Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 8,760 | DimmStore: Memory Power Optimization for Database Systems | 2019 | VLDB | 4.456315e-05 |
| 10,564 | PlanRGCN: Predicting SPARQL Query Performance | 2025 | VLDB | 4.1945683e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 4 of 4 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 694 | Analyzing the Energy Efficiency of a Database Server | 2010 | SIGMOD | 0.00018061803 |
| 718 | Performance Prediction for Concurrent Database Workloads | 2011 | SIGMOD | 0.0001763106 |
| 979 | Interactive Analytical Processing in Big Data Systems: A Cross-Industry Study of MapReduce Workloads | 2012 | VLDB | 0.0001488055 |
| 3,180 | Energy Management for MapReduce Clusters | 2010 | VLDB | 7.4302009e-05 |
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