Power Provisioning for a Warehouse-Sized ComputerChristin Panjaitan

M10202815

1. Data Center Power Provisioning

Fig 1. Simplified datacenter power distribution hierarchy

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Inefficient use of the power budget

Staged Deployment

Fragmentation

Conservative Equipment Ratings

Variable Load

Statistical Effects

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2. Power Estimation

• Observe power usage profile of a typical server

Table 1. Component peak power breakdown for a typical server

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Nameplate vs Actual Peak Power

Nameplate indicates maximum power draw of that machine.

Nameplate is important to supply power to the machine.

According to their benchmark, the maximum is 145 W

System Total213 W

Power SupplyEfficient 85 %

Nameplate :251 W

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3. Power Usage Characterization

Baseline characterization of the power usage of three scale workloads :

• Websearch

• Webmail

• Mapreduce

Evaluation :

Set of servers selected are running well-tuned workloads above and typically at high activity levels.

Rack = 40 machines

PDU = 20 racks (20 x 40 = 800 machines)

Cluster = 5000 machines

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Fig 2. Websearch-CDF of power usage normalized to actual peak

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Fig 3. Webmail -CDF of power usage normalized to actual peak

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Fig 4. Mapreduce -CDF of power usage normalized to actual peak

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Fig 5. CDF of a Real Datacenter

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Power Savings Approaches

1. CPU Voltage / Frequency Scalling

CPU Voltage and frequency scaling (DVS) is a technique to manage energy consumption.

Fig 6. Impact of CPU DVS at Datacenter Level

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2. Improving Non-Peak Power Efficiency

Fig 7. Idle power as fraction of peak power in 5 server configurations

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Fig 8. Power and Energy Savings Achievable by reducing

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