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Published byLucas Miles Modified over 9 years ago
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Optimizing Power and Energy Lei Fan, Martyn Romanko
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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
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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)
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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
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Flikker
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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
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MemScale
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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
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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
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Blink Three policies Synchronous: optimizes for fairness Activation: optimizes for hit rate Load-proportional: both Unknown effects of power cycling on component lifetime
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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
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PowerDial
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Discussion, Questions?
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