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The case for energy proportional computing

The case for energy proportional computing. Discussion topics. State up-to three reasons of why energy efficient computing is important . What does energy proportional computing mean (compare it with human body )? Why energy proportionality is important for computing servers ?

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The case for energy proportional computing

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  1. The case for energy proportional computing

  2. Discussion topics • State up-to three reasons of why energy efficient computing is important. • What does energy proportional computing mean (compare it with human body)? • Why energy proportionality is important for computing servers? • How does the paper define the energy efficiency of computing? • One solution to achieve energy proportional computing in server farms (data centers) is active server set resizing which means adjusting the number of active servers to the offered workload and suspend the rest. What are the problems for this solution in practice? • Mobile devices take advantage of inactive power mode for the sake of energy efficiency. Can this solution be applied for computing servers? Why? • What solutions does paper suggest to achieve energy proportionality for computing servers?

  3. Energy efficiency is an Issue! • Energy consumptions for computing keeps growing • Long-term technology trends indicate that higher performance means increased energy usage • Dollar and CO2 • Electricity cost is a problem • Energy cost tends to be a dominant factor in the total cost of ownership • Climate affect

  4. Full Energy Proportional Systems • Energy consumption should be proportional to the system workload. • At 0% utilization level system should consume no power and power consumption should linearly increase with increasing utilization PPeak Power Consumption (Watts) PIdle 0 100 % utilization

  5. Current systems are non energy proportional • How does energy proportionality make difference on energy efficiency of computing systems? • Computing power efficiency of different systems • Utilization/watt • Utilization: Percentage of time that system is busy (doing work) • Computing power efficiency for energy proportional and non-energy proportional systems

  6. Why energy proportionality is important Average CPU utilization of more than 5,000 servers during a six-month period. Servers are rarely completely idle and seldom operate near their maximum utilization, instead operating most of the time at between 10 and 50 percent of their maximum utilization levels. Can provider provision servers according to average demand? -QoS violation -Need for reasonable amount of slack

  7. Toward energy proportional Machines

  8. Possible ways to make systems energy proportional 1- Dynamic server provisioning • Adjusting number of active servers to the offered workload and suspend the rest • Challenges • Data availability, eliminating bottlenecks : spreading data over machines to increase data availability • Networked servers frequently perform many small background tasks

  9. Possible ways to make systems energy proportional 2- Power state transition for the servers • Restructuring applications to create useful idle intervals periods of reduced load • Challenges • Hard to maintain • Wake up penalties 3- Dynamic power range for different components

  10. Understanding where does power go? • Is the CPU the most contributor in the power consumption? • The need for more dynamic power range for other components

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