pratik chube - energy logic: calculating data center efficiency - interop mumbai 2009
DESCRIPTION
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.TRANSCRIPT
Pratik Chube
General Manager – Product & Marketing
Emerson Network Power
Energy LogicCalculating Data Center Efficiency –True Story of IT Energy Efficiency
Energy LogicEnergy LogicCalculating Data Center Efficiency Calculating Data Center Efficiency ––True Story of IT Energy EfficiencyTrue Story of IT Energy Efficiency
2
AgendaAgendaAgenda
� 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.
3
Data Center Efficiency RevisitedData Center Efficiency RevisitedData Center Efficiency Revisited
Data CenterEfficiency =
Data Center Output
Energy Consumed
Two Ways to Improve Efficiency:1. Increase Data Center Output2. Decrease Amount of Energy Consumed
4
Data Center Output: No Universal Measure Exists Data Center Output: Data Center Output: No Universal Measure Exists 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.
Simple Data Center Layout(Energy Demand, Distribution and Supply)Simple Data Center LayoutSimple Data Center Layout(Energy Demand, Distribution and Supply)(Energy Demand, Distribution and Supply)
Energy Logic Model5,000 square foot Data CenterEnergy Logic ModelEnergy Logic Model5,000 square foot Data Center5,000 square foot Data Center
6
Energy Logic: The ‘Cascade’ EffectEnergy Logic: The Energy Logic: The ‘‘CascadeCascade’’ EffectEffect
1 Watt saved at the server component levelresults in cumulative savings of about
2.84 Watts in total consumption
7
Energy Logic:Prioritized Energy Saving StrategiesEnergy Logic:Energy Logic:Prioritized Energy Saving StrategiesPrioritized Energy Saving Strategies
© 2007 Emerson Network Power
Higher AC voltage improves efficiency
8
Energy Logic Addresses Space, Power & Cooling ConstraintsEnergy Logic Addresses Space, Power Energy Logic Addresses Space, Power & Cooling Constraints& Cooling Constraints
© 2007 Emerson Network Power
65% Space Freed Up43% Cooling Capacity and33% Power Capacity Saved
BEFORE
9
5,000 sq. ft. / 465 sq. m.
1,768 sq. ft. / 164 sq. m
AFTER
10
Energy Logic:Payback PeriodEnergy Logic:Energy Logic:Payback PeriodPayback Period
© 2007 Emerson Network Power
11
Energy Logic: 4 Key TakeawaysEnergy Logic: 4 Key TakeawaysEnergy 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
- Efficiency Without CompromiseTM
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 Availablehttp://www.liebert.com/common/ViewDocument.aspx?id=880
© 2007 Emerson Network Power
12
Data Center Efficiency:Importance of Measuring Data Center OutputData Center Efficiency:Data Center Efficiency:Importance of Measuring Data Center OutputImportance 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 CenterEfficiency
=
Data Center Output
Energy Consumed
13
Measuring Data Center Output:ChallengesMeasuring Data Center Output:Measuring Data Center Output:ChallengesChallenges
� 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
14
0%
1000%
2000%
3000%
4000%
5000%
6000%
7000%
8000%
1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
IT Performance Improvement: 2002 – 2007IT Performance Improvement: 2002 IT Performance Improvement: 2002 –– 20072007
Source: Electronics Cooling magazine (Feb 2007)Belady, C., P.E., Hewlett-Packard, ‘In the Datacenter, Power & Cooling Costs More than IT Equipment it supports”
75X
10X
1998 – 2007 : 7400% Improvement (75x)
2002 – 2007 : 650% Improvement (7.5x)
Ra
w P
erf
orm
an
ce
Ga
in
1X
15
IT Performance Improvement: 2002 – 2007IT Performance Improvement: 2002 IT Performance Improvement: 2002 –– 20072007
Source: Intel
Intel x86 2002 2007
TFLOPS 3.7 3.7
Servers 512 53 blades
GFLOPS/server 7.2 69.8
7.2 GFlops/Server
69.8 GFlops/Server 2002 – 2007
870% Improvement
(9.7x)
2002
2007
16
Introducing “CUPS”Introducing Introducing ““CUPSCUPS””� 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
© 2007 Emerson Network Power
Data Center
Efficiency = =
CUPS
WattsConsumed
Data Center Output
Energy 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)
17
How Does CUPS fit with Moore’s Law?How Does CUPS fit with MooreHow Does CUPS fit with Moore’’s Law?s Law?
CUPS
5899
9351
0
2000
4000
6000
8000
10000
2002 2007
Total Data Center Power Draw (MW)
Server and Data Center Output andEfficiency Improvement 2002 - 2007Server and Data Center Output andServer and Data Center Output andEfficiency Improvement 2002 Efficiency Improvement 2002 -- 20072007
2293
4027
0
1000
2000
3000
4000
5000
2002 2007
Total Server Power Draw (MW)
1.8X
1
7
0.0
2.0
4.0
6.0
8.0
2002 2007
Server Performance (MCUPS / Server)
7.0X 14.0X
321
2432
0
500
1000
1500
2000
2500
3000
2002 2007
Server Efficiency (CUPS / Server Watt)
1048
125
0
200
400
600
800
1000
1200
2002 2007
Data Center Efficiency (CUPS / Datacenter Watt)
8.4X7.6X
0.7
9.8
0.0
2.0
4.0
6.0
8.0
10.0
12.0
2002 2007
Total Compute Output (TCUPS)
18
1.6X
19
Data Center EfficiencyImproved Dramatically from 2002 to 2007Data Center EfficiencyData Center EfficiencyImproved Dramatically from 2002 to 2007Improved 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.
59%
1300%
738%
0%
200%
400%
600%
800%
1000%
1200%
1400%
% I
ncre
ase
2002 - 2007
Consumption
Output
Efficiency
Gets the Most Attention
20
Efficiency Improvement: Cars vs. ComputersEfficiency Improvement: Efficiency Improvement: Cars vs. ComputersCars vs. Computers
If fuel efficiency had kept pace with data center efficiency improvement, cars would get
163 miles to the gallon!
CAGR53.0%
CAGR0.8%
21
IT Efficiency in PerspectiveDramatic Impact on Business, Economy, SocietyIT Efficiency in PerspectiveIT Efficiency in PerspectiveDramatic Impact on Business, Economy, SocietyDramatic 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
Applying Energy Logic:Improvements in Compute EfficiencyApplying Energy Logic:Applying Energy Logic:Improvements in Compute EfficiencyImprovements in Compute Efficiency
0 500 1000 1500 2000
Base
High Efficiency Power Supply
Power Management Features
Blade Servers
Virtualization
Power Distribution Architecture
Cooling Best Practices
Variable Capacity Cooling
High Density Cooling
Monitoring & Optimization
604 1,335
5 IT Actions
2,198
CUPS / Datacenter Watt ����
Server Replacement
2.2x Efficiency Improvement!
All Ten Energy Logic Steps
3.6x Efficiency Improvement!!
5 InfrastructureActions
22
Low Power Processor
1,673
23
Energy Logic: Measuring Data Center Efficiency - 4 Key StepsEnergy Logic: Measuring Data Center Energy Logic: Measuring Data Center Efficiency Efficiency -- 4 Key Steps4 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
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Defining Criteria for aData Center Efficiency MetricDefining Criteria for aDefining Criteria for aData Center Efficiency MetricData 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
Data Center
Efficiency=
Data Center Output
Energy Consumed
� 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
25
Energy Logic ShowsUsing PUE Does Not Drive Right BehaviorEnergy Logic ShowsEnergy Logic ShowsUsing PUE Does Not Drive Right BehaviorUsing PUE Does Not Drive Right Behavior
1
2
3
Total Facility
Power
(Mega Watts)
IT Equipment
Power
(Mega Watts)
PUE
Un-optimized Data Center
1.127 0.588 1.9
Five IT Actions Only
0.713 (-37%)
0.370(-37%)
1.9
Five Infrastructure Actions Only
0.858 MW(-24%)
0.582(-1%)
1.5
*PUE: Power Usage Effectiveness
PUE =Total Facility Power
IT Equipment Power
Using PUE does not drive the right behavior.
PUE does not change even though energy consumption reduces by 37%!!
26
Computing Output
(Mega CUPS)
Total Facility Power
(Mega Watts)
Data Center Efficiency
(CUPS / Watt)
Un-optimized Data Center
680.96 1.127 604
Five IT Actions Only1,192.31
(75%)0.713(-37%)
1,673(+177%)
Five Infrastructure Actions Only
680.96(0%)
0.858(-24%)
794(+31%)
Fully Optimized Data Center
1,192.31(75%)
0.5425(-52%)
2,198(+264%)
Energy Logic ShowsCUPS / Watt Drives Right BehaviorEnergy Logic ShowsEnergy Logic ShowsCUPS / Watt Drives Right BehaviorCUPS / Watt Drives Right Behavior
1
2
3
4
Data Center
Efficiency=
Data Center Output
Energy Consumed
CUPS / Watt drives the right behavior.
27
Simple Tool for Assessing Data Center EfficiencySimple Tool for Assessing Data Center EfficiencySimple 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
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Data Center Efficiency – Sample TemplateData Center Efficiency Data Center Efficiency –– Sample TemplateSample Template
Complete this Sample Template for each Data Center Location
Columbus Data Center Jan 1, 2009
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
29
Data Center Efficiency – Sample TemplateData Center Efficiency Data Center Efficiency –– Sample TemplateSample Template
In the absence of an industry standard for computing output, Energy Logic II provides MCUPS estimates to use as a starting point.
Columbus Data Center Jan 1, 2009
Estimated Output per Server can be
modified based on your specific situation.
30
Data Center Efficiency – Sample TemplateData Center Efficiency Data Center Efficiency –– Sample TemplateSample Template
Step 1For a given location, fill in the number of servers / blade servers purchased each year.
50
25
25
Columbus Data Center Jan 1, 2009
31
Data Center Efficiency – Sample TemplateData Center Efficiency Data Center Efficiency –– Sample TemplateSample Template
Step 2Enter the average server utilization rate for each ‘year’ of servers.
16%
65%
20%
Columbus Data Center Jan 1, 2009
Note: Higher Utilization due to virtualization.
32
Data Center Efficiency – Sample TemplateData Center Efficiency Data Center Efficiency –– Sample TemplateSample Template
Step 3For each row, multiply Columns A, B, and C to calculate total computing output of servers from each year of purchase.
= 8 MCUPS50 16%X X
Columbus Data Center Jan 1, 2009
33
Data Center Efficiency – Sample TemplateData Center Efficiency Data Center Efficiency –– Sample TemplateSample Template
Step 4Add up the Total Output of each row and enter the total into the Total Data Center Output field.
+
50
25
25
16%
65%
20%
8
52.8
35
95.8
Columbus Data Center Jan 1, 2009
34
Data Center Efficiency – Sample TemplateData Center Efficiency Data Center Efficiency –– Sample TemplateSample Template
Step 5Enter the Total Energy Consumption (Mega Watts) for the data center into Field E.
0.25
35
Data Center Efficiency – Sample TemplateData Center Efficiency Data Center Efficiency –– Sample TemplateSample Template
Step 6Calculate Data Center Efficiency by dividing Total Data Center Output by Total Energy Consumption.
383.2
0.25
95.8
For the first time, we have an understanding of the true data center efficiency.
36
Data Center EfficiencyUsing Sample Template to Compare LocationsData Center EfficiencyData Center EfficiencyUsing Sample Template to Compare LocationsUsing Sample Template to Compare Locations
Select data center locations on which to focus efforts using Data Center Efficiency and Total Energy Consumption measures.
383.2
0.25
95.8
Now that we know the efficiency of each of our data centers, we can compare each of our locations.
537.5
0.2
107.5
A
B
37
Data Center EfficiencyUsing Sample Template to Justify InvestmentData Center EfficiencyData Center EfficiencyUsing Sample Template to Justify InvestmentUsing Sample Template to Justify Investment
Columbus Data Center Jan 1, 2009
50
25
25
16%
65%
20%
8
52.8
35
X 25
25 35%
4
90
X
Once specific actions to take have been identified, ‘before’ and ‘after’ templates can be used to justify the investment.
After
38
Data Center EfficiencyUsing Sample Template to Justify Investment
Data Center EfficiencyData Center EfficiencyUsing Sample Template to Justify InvestmentUsing Sample Template to Justify Investment
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.
383.2
0.25
95.8
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
909.0
0.2
181.8
Be
fore
Aft
er
39
Data Center EfficiencyTrack Each Location Over TimeData Center EfficiencyData Center EfficiencyTrack Each Location Over TimeTrack Each Location Over Time
Track performance over time to identify trends, bring attention to efficiency
improvement efforts, and to establish a process of continuous improvement.
383.2
0.25
95.8
909.0
0.2
181.8
2008
2009
1145.0
0.3
343.5
2010
40
IT & Data Center Managers Are AskingIT & Data Center Managers Are AskingIT & 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
Data Center – Web ConfiguratorData Center Data Center –– Web ConfiguratorWeb Configurator
Design-IT-Your Self Data Center Configuration Tools
www.EmersonNetworkPower.co.in/tools
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Thank You !Thank You !Thank You !Pratik Chube