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- Type of Document: M.Sc. Thesis
- Language: Farsi
- Document No: 43449 (19)
- University: Sharif University of Technology
- Department: Computer Engineering
- Advisor(s): Goudarzi, Maziar
- Abstract:
- Size and number of high-performance data centers are fast growing all over the world in recent years. The growth in the leakage power consumption of servers along with its exponential dependency on the ever increasing process variation in nanometer technologies have made it inevitable to move toward variation-aware power reduction strategies. In this thesis, we simultaneously apply thermal- and variation-aware server placement and chassis consolidation methods to reduce total power consumption of data centers. We introduce two server placement heuristics as well as an Integer Linear Programming (ILP)-based server placement method based on power consumption of each server and the data center heat recirculation model which are used in conjunction with a thermal- and variation-aware ILP-based chassis consolidation method to find the optimum server placement and task assignment solution. Results from small-scale data center simulations show that simultaneously applying thermal- and variation-aware server placement and chassis consolidation techniques leads to up to 14.6% improvement at common data center utilization rates compared to state-of-the-art variation-unaware approaches and, this improvement can be increased up to 22% where variation effects are increased with further technology scaling
- Keywords:
- Data Center ; Process Variation ; Task Assignment ; Power Reduction ; Thermal Variation ; Server Placement
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