Transcript 04-740_power.pptx

Optimizing Power and
Energy
Lei Fan, Martyn Romanko
Motivation
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31% of TCO attributed to power and cooling
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Intermittent power constraints
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Renewable energy
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Grid balancing
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20% - 30% utilization on average
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Green: good for the environment
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Green: saves money
Themes
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Hybrid (hardware/software) optimizations
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Dynamic DRAM refresh rates (Flikker)
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Dynamic voltage/frequency scaling (MemScale)
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Distributed UPS management
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Power cycling (Blink)
Software optimizations
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Dynamic adaptation (PowerDial)
Flikker: Saving DRAM Refresh-power
through Critical Data Partitioning
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Partitioning of data into critical vs. non-critical
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Partitioning of DRAM into normal vs. low refresh rates
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Programming language construct
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Allows marking of critical/non-critical sections
Primarily software with suggested hardware optimizations
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OS and run-time support
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Refresh rate optimizations
Flikker
MemScale: Active Low-Power Modes for
Main Memory
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Modern DRAM devices allow for static scaling
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MemScale adds:
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DVFS for MC; DFS for memory channels and DRAM devices
Policy based on power consumption and performance slack
MemScale
Managing Distributed UPS Energy for
Effective Power Capping in Data Centers
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Use of distributed UPSs to sustain peak power loads
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Based on existing distributed UPS models
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Larger batteries needed for longer peak spikes
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Allows for more servers to be provisioned
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Analysis of effect on battery lifetime
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Argued benefit outweighed cost of extra batteries
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Lacked detailed analysis on cooling costs
Blink: Managing Server Clusters on
Intermittent Power
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Reducing energy footprint of data centers
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Power-driven vs. workload driven
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Blink: power-driven technique
Metered transitions between
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High power active states
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Low power inactive states
Blink
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Three policies
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Synchronous: optimizes for fairness
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Activation: optimizes for hit rate
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Load-proportional: both
Unknown effects of power cycling on component lifetime
PowerDial: Dynamic Knobs for PowerAware Computing
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When is this applicable for a program?
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QoS (accuracy) vs. power/performance tradeoff
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Subject to system fluctuations
Dynamic tuning of program parameters
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Adaptable to fluctuations in power/load
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Determines control variables
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Application Heartbeats framework provides feedback
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Automatic insertion of API calls
PowerDial
Discussion, Questions?