1. Power Provisioning for a
Warehouse-Sized Computer
Christin Panjaitan
M10202815

2. 1. Data Center Power Provisioning
Fig 1. Simplified datacenter power distribution hierarchy
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3. Inefficient use of the power budget
Staged Deployment
Fragmentation
Conservative Equipment Ratings
Variable Load
Statistical Effects
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4. 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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5. 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 Total
213 W
Power Supply
Efficient 85 %
Nameplate :
251 W
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6. 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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7. Fig 2. Websearch-CDF of power usage normalized to actual peak
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8. Fig 3. Webmail -CDF of power usage normalized to actual peak
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9. Fig 4. Mapreduce -CDF of power usage normalized to actual peak
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10. Fig 5. CDF of a Real Datacenter
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11. 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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12. 2. Improving Non-Peak Power Efficiency
Fig 7. Idle power as fraction of peak power in 5 server configurations
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13. Fig 8. Power and Energy Savings Achievable by reducing
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