1. Optimizing Power and Energy Lei Fan, Martyn Romanko

2. Motivation  31% of TCO attributed to power and cooling  Intermittent power constraints  Renewable energy  Grid balancing  20% - 30% utilization on average  Green: good for the environment  Green: saves money

3. Themes  Hybrid (hardware/software) optimizations  Dynamic DRAM refresh rates (Flikker)  Dynamic voltage/frequency scaling (MemScale)  Distributed UPS management  Power cycling (Blink)  Software optimizations  Dynamic adaptation (PowerDial)

4. Flikker: Saving DRAM Refresh-power through Critical Data Partitioning  Partitioning of data into critical vs. non-critical  Partitioning of DRAM into normal vs. low refresh rates  Programming language construct  Allows marking of critical/non-critical sections  Primarily software with suggested hardware optimizations  OS and run-time support  Refresh rate optimizations

5. Flikker

6. MemScale: Active Low-Power Modes for Main Memory  Modern DRAM devices allow for static scaling  MemScale adds:  DVFS for MC; DFS for memory channels and DRAM devices  Policy based on power consumption and performance slack

7. MemScale

8. Managing Distributed UPS Energy for Effective Power Capping in Data Centers  Use of distributed UPSs to sustain peak power loads  Based on existing distributed UPS models  Larger batteries needed for longer peak spikes  Allows for more servers to be provisioned  Analysis of effect on battery lifetime  Argued benefit outweighed cost of extra batteries  Lacked detailed analysis on cooling costs

9. Blink: Managing Server Clusters on Intermittent Power  Reducing energy footprint of data centers  Power-driven vs. workload driven  Blink: power-driven technique  Metered transitions between  High power active states  Low power inactive states

10. Blink  Three policies  Synchronous: optimizes for fairness  Activation: optimizes for hit rate  Load-proportional: both  Unknown effects of power cycling on component lifetime

11. PowerDial: Dynamic Knobs for Power- Aware Computing  When is this applicable for a program?  QoS (accuracy) vs. power/performance tradeoff  Subject to system fluctuations  Dynamic tuning of program parameters  Adaptable to fluctuations in power/load  Determines control variables  Application Heartbeats framework provides feedback  Automatic insertion of API calls

12. PowerDial

13. Discussion, Questions?