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Pratik Chube - Energy Logic: Calculating Data Center Efficiency - Interop Mumbai 2009
 

Pratik Chube - Energy Logic: Calculating Data Center Efficiency - Interop Mumbai 2009

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The lack of a true data center efficiency metric is challenging IT and data center managers as they try to justify much needed IT investments to management. It also adds to the difficulty that data ...

The lack of a true data center efficiency metric is challenging IT and data center managers as they try to justify much needed IT investments to management. It also adds to the difficulty that data center managers have in comparing efficiencies across their data centers to prioritize where efficiency-improving actions will have the greatest impact. In addition, they need to be able to track data center efficiencies over time. Attend this session to find out how IT and data center managers can use an efficiency metric to address these challenges, by following a prioritized set of actions to gain the greatest improvement in efficiency.

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    Pratik Chube - Energy Logic: Calculating Data Center Efficiency - Interop Mumbai 2009 Pratik Chube - Energy Logic: Calculating Data Center Efficiency - Interop Mumbai 2009 Presentation Transcript

    • Energy Logic Calculating Data Center Efficiency – Calculating Data Center Efficiency – True Story of IT Energy Efficiency True Story of IT Energy Efficiency Pratik Chube General Manager – Product & Marketing Emerson Network Power Pratik.Chube@Emerson.com
    • Agenda Data Center Efficiency Revisited Initial Steps: Reducing Data Center Energy Consumption A Measure for Data Center Compute Output Next Phase: The Four Prioritized Efficiency-Improving Actions Simple Tool to Measure, Prioritize and Justify Investments to Improve Data Center Efficiency . Click 2 Brick Virtual Data Center Build Tool. About Emerson. 2
    • Data Center Efficiency Revisited Data Center Output Data Center Efficiency = Energy Consumed Two Ways to Improve Efficiency: 1. Increase Data Center Output 2. Decrease Amount of Energy Consumed 3
    • Data Center Output: No Universal Measure Exists First we will address the issue of reducing energy consumption using Energy Logic, then we will turn our attention to addressing data center output. 4
    • Simple Data Center Layout (Energy Demand, Distribution and Supply) (Energy Demand, Distribution and Supply)
    • Energy Logic Model 5,000 square foot Data Center 5,000 square foot Data Center 6
    • Energy Logic: The ‘Cascade’ Effect ‘Cascade’ 1 Watt saved at the server component level results in cumulative savings of about 2.84 Watts in total consumption 7
    • Energy Logic: Prioritized Energy Saving Strategies Higher AC voltage improves efficiency © 2007 Emerson Network Power 8
    • Energy Logic Addresses Space, Power & Cooling Constraints 5,000 sq. ft. / 465 sq. m. B E F O R E A 65% Space Freed Up F 43% Cooling Capacity and T 33% Power Capacity Saved E R 1,768 sq. ft. / 164 sq. m © 2007 Emerson Network Power 9
    • Energy Logic: Payback Period © 2007 Emerson Network Power 10
    • Energy Logic: 4 Key Takeaways 1. Start by reducing consumption at the IT equipment level and then work your way back through the supporting equipment Every Watt saved at the equipment level has a cascading effect upstream. 2. Availability & Flexibility do not have to be compromised in order to increase data center efficiency TM - Efficiency Without Compromise 3. High Density Architecture contributes toward increased efficiency - IT Consolidation, Cooling Efficiencies 4. In addition to improving energy efficiency by reducing consumption, implementing these strategies frees up capacity of key constraints: Power, Cooling & Space Energy Logic White Paper Available http://www.liebert.com/common/ViewDocument.aspx?id=880 11 © 2007 Emerson Network Power
    • Data Center Efficiency: Importance of Measuring Data Center Output A Measure of Data Center Output is needed to help drive the right behavior for improving efficiency Lack of output metric limits focus and attention – to the infrastructure (supply) side rather than on both the IT (demand) and infrastructure sides – to consumption rather than on both output and consumption Data Center Output Data Center = Efficiency Energy Consumed 12
    • Measuring Data Center Output: Challenges Data centers perform different types of work – Processing-intensive for scientific and financial applications – Data transfer-intensive for Web-based applications Data center requirements change as mix of workload shifts However, industry experts can agree that performance has improved dramatically over the last 5 to 10 years 13
    • IT Performance Improvement: 2002 – 2007 1998 – 2007 : 7400% Improvement (75x) 2002 – 2007 : 650% Improvement (7.5x) 8000% 75X 7000% Raw Performance Gain 6000% 5000% 4000% 3000% 2000% 1000% 10X 1X 0% 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 Source: Electronics Cooling magazine (Feb 2007) Belady, C., P.E., Hewlett-Packard, ‘In the Datacenter, Power & Cooling Costs More than IT Equipment it supports” 14
    • IT Performance Improvement: 2002 – 2007 2007 69.8 GFlops/ 2002 Server 2002 – 2007 7.2 870% Improvement GFlops/ (9.7x) Server Intel x86 2002 2007 TFLOPS 3.7 3.7 Servers 512 53 blades GFLOPS/server 7.2 69.8 Source: Intel 15
    • Introducing “CUPS” “CUPS” We introduce CUPS, or Compute Units per Second, as a temporary or placeholder measure for what will be the eventual universal metric for data center output Data Center Output CUPS Data Center Efficiency = = Watts Energy Consumed Consumed Based on information on performance gains, we assume CUPS has improved by 7x between 2002 and 2007 (compared to 7.5x Belady; 9.7x Intel) 16 © 2007 Emerson Network Power
    • How Does CUPS fit with Moore’s Law? Moore’s CUPS 17
    • Server and Data Center Output and Efficiency Improvement 2002 - 2007 Total Server Power Draw (MW) Total Data Center Power Draw (MW) 10000 9351 5000 4027 1.6X 4000 8000 2293 1.8X 5899 3000 6000 2000 4000 1000 2000 0 0 2002 2007 2002 2007 Server Performance (MCUPS / Server) Total Compute Output (TCUPS) 8.0 7 12.0 9.8 6.0 10.0 7.0X 8.0 14.0X 4.0 6.0 2.0 4.0 1 2.0 0.7 0.0 0.0 2002 2007 2002 2007 Server Efficiency (CUPS / Server Watt) Data Center Efficiency (CUPS / Datacenter Watt) 3000 1200 2500 1000 2000 2432 800 1048 1500 7.6X 8.4X 600 1000 321 400 125 500 200 0 0 2002 2007 2002 2007 18
    • Data Center Efficiency Improved Dramatically from 2002 to 2007 Server efficiency improved over 650% (7.6x) Data Center efficiency improved over 735% (8.4x) If computing demand in 2007 was the same as in 2002, 2007 power consumption would have been <1/8th of 2002 consumption. Gets the Most 1400% 1300% Attention 1200% % Increase 1000% 738% 800% Consumption 600% Output 400% Efficiency 200% 59% 0% 2002 - 2007 19
    • Efficiency Improvement: Cars vs. Computers CAGR CAGR 0.8% 53.0% If fuel efficiency had kept pace with data center efficiency improvement, cars would get 163 miles to the gallon! 20
    • IT Efficiency in Perspective Dramatic Impact on Business, Economy, Society Significant improvement in productivity through automation of tasks and processes Better and faster decision making driven by availability of richer real-time information and communication Wider utilization of best cost resources around the world, driving global economic development Increased level of conveniences and benefits at the individual and societal level 10X productivity gain across all industries per KW ICT* Increase in energy consumption has been small relative to increase in output -- and benefits to economy and society. * ACEEE: Information and Communication Technologies: The Power of Productivity, Report # E081 21
    • Applying Energy Logic: Improvements in Compute Efficiency CUPS / Datacenter Watt 5 Infrastructure 5 IT Actions Actions 1,673 Base 604 1,335 2,198 0 500 1000 1500 2000 Low Power Processor High Efficiency Power Supply Power Management Features Blade Servers Server Replacement Virtualization 2.2x Efficiency Improvement! Power Distribution Architecture Cooling Best Practices All Ten Energy Logic Steps Variable Capacity Cooling High Density Cooling 3.6x Efficiency Improvement!! Monitoring & Optimization 22
    • Energy Logic: Measuring Data Center Efficiency - 4 Key Steps Most impactful ways to improve data center efficiency: 1. Speed up refresh cycle for IT technology • Blades provide a modular platform for continued improvement 2. Implement server power management policies 3. Virtualize 4. Adopt a high-density architecture Energy Logic: Measuring Data Center Efficiency http://www.emerson.com/edc/docs/EnergyLogicMetricPaper.pdf 23
    • Defining Criteria for a Data Center Efficiency Metric A Measure of Data Center Output, even if less-than-ideal, can help drive the right energy-saving behaviors – Effective measure vs. Ideal or Fair Measure Three criteria an effective measure must fulfill: 1. Most importantly, does it drive the right behavior? 2. Must be published at device level so that users can evaluate competing technologies 3. Must be scalable to the data center, allowing the output of the devices to be added together to produce an overall measure of data center efficiency Data Center Output Data Center Efficiency = Energy Consumed 24
    • Energy Logic Shows Using PUE Does Not Drive Right Behavior Total Facility IT Equipment Power Power PUE PUE does not (Mega Watts) (Mega Watts) change even 1 Un-optimized 1.127 0.588 1.9 though energy Data Center consumption reduces by 37%!! Five IT 0.713 0.370 2 Actions Only (-37%) (-37%) 1.9 Five 0.858 MW 0.582 3 Infrastructure (-24%) (-1%) 1.5 Actions Only Total Facility Power Using PUE does not PUE = drive the right behavior. IT Equipment Power *PUE: Power Usage Effectiveness 25
    • Energy Logic Shows CUPS / Watt Drives Right Behavior Computing Output Total Facility Power Data Center Efficiency (Mega CUPS) (Mega Watts) (CUPS / Watt) Un-optimized Data 1 Center 680.96 1.127 604 1,192.31 0.713 1,673 2 Five IT Actions Only (75%) (-37%) (+177%) Five Infrastructure 680.96 0.858 794 3 Actions Only (0%) (-24%) (+31%) 4 Fully Optimized 1,192.31 0.5425 2,198 Data Center (75%) (-52%) (+264%) Data Center Output CUPS / Watt drives the Data Center right behavior. Efficiency = Energy Consumed 26
    • Simple Tool for Assessing Data Center Efficiency IT and Data Center Managers need a way to: – Compare and prioritize data centers for: • Efficiency improvement actions • Space / Power / Cooling constraint relieving opportunities – Justify IT investments in new technologies to management – Track data center efficiencies over time Energy Logic provides a Sample Template that can be used to accomplish these tasks 27
    • Data Center Efficiency – Sample Template Columbus Data Center Jan 1, 2009 Complete this Sample Template for each Data Center Location This sample template is a Simple Tool that only accounts for servers. It can easily be modified to account for other IT equipment as data becomes available. Data Center Efficiency Tool available on-line at: http://www.emerson.com/edc/Calculator/default.aspx 28
    • Data Center Efficiency – Sample Template Columbus Data Center Jan 1, 2009 In the absence of an industry standard for computing output, Energy Logic II provides MCUPS estimates to use as a starting point. Estimated Output per Server can be modified based on your specific situation. 29
    • Data Center Efficiency – Sample Template Columbus Data Center Jan 1, 2009 50 Step 1 For a given location, fill in the number of 25 servers / blade servers purchased each year. 25 30
    • Data Center Efficiency – Sample Template Columbus Data Center Jan 1, 2009 16% Step 2 Enter the average server utilization rate for 65% each ‘year’ of servers. 20% Note: Higher Utilization due to virtualization. 31
    • Data Center Efficiency – Sample Template Columbus Data Center Jan 1, 2009 X 50 X 16% = 8 MCUPS Step 3 For each row, multiply Columns A, B, and C to calculate total computing output of servers from each year of purchase. 32
    • Data Center Efficiency – Sample Template Columbus Data Center Jan 1, 2009 Step 4 Add up the Total Output 50 16% 8 of each row and enter 25 65% 52.8 the total into the Total 25 20% 35 Data Center Output field. + 95.8 33
    • Data Center Efficiency – Sample Template Step 5 Enter the Total Energy Consumption (Mega Watts) for the data center into Field E. 0.25 34
    • Data Center Efficiency – Sample Template Step 6 Calculate Data Center Efficiency by dividing Total Data Center Output by Total Energy Consumption. 95.8 0.25 383.2 For the first time, we have an understanding of the true data center efficiency. 35
    • Data Center Efficiency Using Sample Template to Compare Locations Now that we know the efficiency of each of our data centers, we can compare each of our locations. 95.8 A 0.25 383.2 107.5 B 0.2 537.5 Select data center locations on which to focus efforts using Data Center Efficiency and Total Energy Consumption measures. 36
    • Data Center Efficiency Using Sample Template to Justify Investment Columbus Data Center Jan 1, 2009 After X50 25 16% X 8 4 25 65% 52.8 25 20% 35 25 35% 90 Once specific actions to take have been identified, ‘before’ and ‘after’ templates can be used to justify the investment. 37
    • Data Center Efficiency Using Sample Template to Justify Investment To estimate energy consumption in the ‘after’ scenario, calculate energy savings of new servers and apply estimated cascade effect multiplier. 1 (conservative) to 1.8 is recommended After Before 95.8 0.25 383.2 181.8 0.2 909.0 The quantified improvement in Data Center Efficiency as well as the lower energy costs from the reduction in Total Energy Consumption provide meaningful data to management to justify project investment. 38
    • Data Center Efficiency Track Each Location Over Time 95.8 2008 0.25 383.2 181.8 2009 0.2 909.0 343.5 2010 0.3 1145.0 Track performance over time to identify trends, bring attention to efficiency improvement efforts, and to establish a process of continuous improvement. 39
    • IT & Data Center Managers Are Asking How to compare efficiencies across data centers, to prioritize for action What specific actions to take to improve efficiency How to justify IT investments to management How to track efficiencies over time Data Center Efficiency Tool available on-line at: http://www.emerson.com/edc/Calculator/default.aspx White Paper available at: http://www.emerson.com/edc/docs/EnergyLogicMetricPaper.pdf 40
    • Data Center – Web Configurator www.EmersonNetworkPower.co.in/tools Design-IT-Your Self Data Center Configuration Tools
    • About Emerson Rank Corporations 09 Score 1 General Electric 7.44 2 Emerson 7.12 3 Panasonic 6.78 4 Siemens 6.40 5 Sony 6.30 6 Whirlpool 6.01 7 Royal Philips Elect. 5.98 8 Toshiba 5.94 9 Samsung Elect. 5.88 10 Hitachi 5.86 • Founded in 1890 in St. Louis, MO • 136,000 Employees worldwide, 245 Mfg Locations, 150 Country Operations • Outstanding Management Practices & Solid Financial Position • FY 07 Sales Revenue - $24.8 billion, EPS – 3.11 $, Market Cap – $ 50 billion • Top 100 companies for IT Excellence – CIO Magazine • 100% of Fortune 500 company rely on Emerson to protect their critical IT infra.
    • Thank You ! Pratik Chube pratik.chube@emerson.com