E Effi i Energy Efficiency in ICT - OECD

E Effi i Energy Efficiency in ICT

Prof. Dr.-Ing. Wolfgang Nebel

22nd of May 2008 OFFIS – Institute for Information Technology

Energy Consumption, Climate Protection, Costs

Power Consumption of ICT (End Devices and Infrastructure) in Germany (Source: Cremer et al. 2003)

2001 38 TWh (8% f ti )2001: 38 TWh (8% of power consumption)Compared to 10.7 TWh generated from wind energy(Source: Bundesverband Windenergie)

2010: 55 TWh (11% of power consumption)

CO2-Emissions 2004 in GermanyICT: 28 Mio. t CO2 (due to power consumption)Compared to complete aircraft traffic of 22 Mio. t CO2p p 2

Increase especially in ICT-Infrastructure(UMTS-Network, Servers, Routers etc.)

The highest electricity consumers are data centersServers: 180 TWh in 2005 relate to 18 nuclear powerplants worldwide80% of all servers are located in data centers

Increase of Operating Expenses due to Energy CostsEnergy costs worldwide for servers in 2008: approx. 40 billion US$Soon 50% of operating expenses will be caused by power supply and cooling

22nd of May 2008OFFIS – Institute for Information Technology


Energy Consumption of ICT in Germany

ICT-infrastructure in private homes

Infrastructure mobile communication

Server, office

Audio stationary

Source: Borderstep 2007/Cremer et. al. 2003

TV



Worldwide Energy Consumption of Servers 2005 vs. 2000

3

2

2,5

1

1,5

Reference 2000:

0,5

1Reference 2000:

0

Volume

Rang

e

gh-E

ndTo

tal

AnzahlNumber

Source: Koomey, 2007

Vo

Mid-R

High T

Energie/ServerGesamtenergie

Energy/Server

Total Energy



The Economic Consequences

Source: IDC 2006



Problem Awareness of Data Center Operators

Power supply and cooling together: 74%



Energy Consumption in Enterprises (2,500 PCs)

1000000kWh

600000

800000

400000

600000

0

200000

0

ntro

lled

lized

PM

ched

off

Closing time

unco

n

cent

raliz

switc

h Closing timeWorking hours

Source: Gartner 2007



Core of the Problem: The Required Computing Performance

Source: tom‘s hardware guide



Cause: The Performance Barrier

Source: tom‘s hardware guide



Technical and Economic Challenges

Limited Run-TimeEnergy demand raises faster than battery capacityProblematic for mobile devices: E

nerg

y

Required by MobileDevices

Problematic for mobile devices:notebooks, mobile phones, PDAs, …

Added Costs

BatteryCapacity

Added CostsTypically relevant for devices for private use:desktop PCs, TVs, DVD players, …Of increasing importance in the commercial domain:

Generation

Of increasing importance in the commercial domain:e.g. work station PCs

Energy Supply and Disposal Problemgy pp y pIncreasingly problematicin data centersComplex air conditioning for 1:1p genergy disposal requiredSometimes, even the supplyof energy is a problem

Supply(electrical)

Disposal(thermal)



Abstract Examination – Energy Efficiency

What is Energy Efficiency?ss efficient

notefficient

op

tim

ize

ffect

iven

e

C l i E ffi ie

Light BulbConclusion: Energy efficiency

can be achieved by:

• Optimized effectivenessEne g cons mption

EnergySaving Bulb

LEDIlluminant

um

pti

on

to u

sag

e

1Energy

always on

1 Energy

light dimmed, ifroom not used

1Energy Efficiency

light off, ifroom not used

• Energy consumptionproportional to usage

• High utilization

erg

y c

on

sup

ort

ion

al

t 1

EnergyEfficiency

Energy

EnergyEfficiency

Energy

en

ep

ro

efficient onlyat high utilization

alwaysefficient

Utilizationof the Room

1 Utilizationof the Room

1 Utilizationof the Room

1



at high utilization efficient

Practical Implementation – Energy Efficiency in Mobile Phones

Optimize EffectivenessAdoption of low-power technologiesand design solutions in chip development

low VT Dual VT

Objective: minimizing steady-statepower dissipation

Raising Utilization Sleep States

high VT

Raising UtilizationBy means of load alignment

Energy Consumption Proportional to Usage DISPLAY

standby

Sleep States

Sophisticated power managementDisabling unused circuitsReducing performance during phases

ll d bg p g p

of lower utilizationObjective: Customizing the energy consumptionaccording to the respective usage scenario

VDD

Circuit

controlled byutilization

DVFS

Conclusion: Due to technical problems, vigoroususage of techniques to raise energy efficiency

Clk



Practical Implementation – Energy Efficiency in PCs 1/3

Optimize EffectivenessOptimize EffectivenessTechnically feasible: low power CPU, low powergraphics card, 80% mains supply, thus no need for a fanToday instead of energy consumption rather performanceToday, instead of energy consumption rather performanceand pricing are important purchase criteriaOnly secondary effects (fan noise, high temperatures and short battery life time in notebooks) are reasons to purchase energy efficient systems) p gy y

Raising UtilizationMatching of the resources

„sending emails“ and „surfing“ needs no high-end PCMatching of the load

temporally - spatially

Energy Consumption Proportional to UsageTechnically feasible:

Shut down of individual components (hard disc display ) possibleShut down of individual components (hard disc, display, …) possibleLow power consumption during standby state

Controlled by software with a timeout-based power management




Problems of the Present Timeout Based Power Managements

Idea: After some idle-time, the useris considered to be absent-> turn off device (e.g. display)Error-prone (e.g. while user reads)Th h b l b t i The chosen balance between saving energyand annoyance often is to the disadvantageof energy saving

Solution: Intelligent Power Management

Intel06

Solution: Intelligent Power ManagementIdea: Adapt the power management to the pattern of useFor the first time, basic research was included in a product




Comparing Results of Adaptive vs. Timeout Based Power ManagementUse case: “Work of a traveling salesman”

Maximum at optimal power management83 i

Runtime of the notebookwithout PM: 5h

Maximum at optimal power management83min

54min62min adaptivetimeout

based

ng

er

nti

me

Due to breaks (phone call,reading of papers, …)max. extra time: 83min

21min

0min

lon

run

“adaptive” more energy efficient,with less false shut downs

mu

m u

sag

e

ap

top

nst

op

on

scalablean

no

yan

ceConclusion:

Energy efficiency is often a question of “financial sweeteners”

min

imb

att

ery

L

No

gy y qTechnical possibilities are available; but until now not sufficiently used



Practical Implementation–Energy Efficiency in Data Centers 1/3

EffectivenessEnergy efficiency only if neutral to performance

Mains supply with high effectiveness (e.g. in Blade servers)

Smaller improvements arepossible, but one cannot

t j d t expect major advancements in the near future

Optimize UtilizationOptimize UtilizationAverage utilization oftoday’s servers (measuredapprox. 5,000 servers overapprox. 5,000 servers overa 6 month period)

Source: Google 2007




Optimize UtilizationAdditional strong dependencyon time and type of server

Optimization by consolidationImplementation of several servers

h d on one hardware resource

Realization by virtualizationl i t l tiseveral virtual operating

systems are independentlyexecuted on one singlehost systemhost system

Source: Vossel Solutions




Energy Consumption Proportional to Usage typical load

FrüherPast State-of-the-art Vision

1

Energy

Energy Efficiency1

Energy

EnergyEfficiency

1Energy

EnergyEfficiency

1

Energy

1

y

1

• Server without power management

• Power management inmodern CPUs result in

• Complete usage dependantenergy consumption

• Constant consumption• Energy efficiency only

depending onutilization

a minor utilizationdependant consumption

• in Blade servers loaddependant control ofmains supply

• Realizable by globalpower management inthe entire data center

mains supply

ConclusionRaising the load by consolidationNearly complete usage-proportional energy consumption is reachable with system wide

Research Projectat OFFIS

y p g p p gy p ypower management

Without penalty on performance With higher availability



Practical Implementation – Possibilities by System Management

Hardware Resources virtualized serversVirtualized Data Center

R1…G1

kn

ow

n

G3

G2

ors

/o

ls

Rn R2R3Regarding their behavior, known and unknown virtualized servers

G5

un

kn

ow

nG6

G4

binding

monitors

mo

nit

oco

ntr

pla

ns

System Management

System Managementmonitors virtualized serversmonitors and controls the hardware resourcesplans binding

Optimi ation C ite ia

optimization criteria

1

energy

energy efficiency

Optimization CriteriaEnergy/Performancethermal behaviorh i

reduction ofinhomogeneous

aging

performance/energy

optimization

1

energyhomogeneous aging

prevention ofthermal

hot-spots



g gp p

Power Consumption of German Data Centers

Source: Borderstep 2007

Scenario “state-of-the art”

Scenario “present efficiency trends”

Scenario “best-practice”

present development



CO2 Emissions of German Data Centers



Scenario “state-of-the-art”


present development



Energy Costs of German Data Centers



Scenario “state-of-the-art”


present development



Practical Implementation – Example Projects

Strato’s CO2-free Data CenterffIncreased energy efficiency

Low power CPUs, optimized software (Sun Solaris 10)optimized building services and air conditioning

Energy supply by water powerEnergy supply by water power

The “green” Data Center of Host EuropeHighly available and energy efficient,Raised effectiveness of the supply components,cooling with outside air, …,30% lesser energy consumption

Bio-Gas Fuel Cell in T-Systems RZ-Munich“Our servers devour green stuff”250 kW of altogether 10 MW



Finally …

Google 2005 1 cluster = 31,654 serversserved 40 Mio. requests/daycosts about 300 MWh/dayone request costs about 8 Wh

Second Life 2007approx. 2000 servers36,000 players simultaneously36,000 players simultaneouslyone avatar costs about 195 kWh/year or 129 kg CO2

Compare: a human exhales about 250 – 400 kg CO2

Thanks to Rolf Kersten: http://blogs.sun.com/rolfk/



Conclusion

Technical problems already force manufacturers of mobile devices to implement radical new concepts. Increasing technical, economic and environmental interest in energy g , gyefficiency in data centers and ICT-infrastructures:

Potential and first technical alternatives are already available.Further innovative ideas have to be developed and evaluated.Holistic concepts have to be developed.Savings potential in 2010 more than 8 TWh / 5,4 Mio t CO2 / 1,1 Mrd. €

Very good prerequisites for applying new technologies, since y g p q pp y g g ,environmentally and economically reasonable,technically required and feasible.

ActionsRaise cost awareness in decision makers“Best practice” informationRoadmap to coordinate suppliers towards market launch Roadmap to coordinate suppliers towards market launch Flagship initiatives (improving the state-of-the-art)Energy-labels for the consumers market



E Effi i Energy Efficiency in ICT - OECD

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