Analysis and optimization of energy consumption of IT infrastructure

November, 2014

Norwegian Ministry of Foreign Affairs HERD/Energy The Programme in Higher Education, Research and Development in the Western Balkans 2010-2016

Analysis and optimization of energy consumption of IT infrastructure*

Description: This is an accordance with Macedonian and regional energy research priorities basis of the countrys readiness and future potential, too. This project can help in development of policies , methods and knowledge needed for energy security, optimization and conservation in IT infrastructures. Proposed small R&D projects, will provide links between academia and industry. Small research project will contribute beside teaching and research activities the collaboration with industry sector. *This proposal was prepared in cooperation with Asseco SEE company (http://asseco.com/see/).

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From industry sector

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beginning Over the last 40 years, the data center has gone through a

tremendous evolution. ENIAC could be seen as the grandfather of the data centers we know today:

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Prior to 1945-1955, the U.S. Army developed a machine called Eniac (Electronic Numerator, Integrator, Analyzer and Computer): weight 27mt, 160m2 of floor space, 150kW of power to deliver a compute performance of 0.05 MIPS and 6 full-time technicians to keep running.

past

During the 1960s, computers were large mainframes stored in rooms what we call a data center today. They were costly and businesses could rent out space on the mainframe to fulfill specific functions.

During the 1980s, the computer industry experienced the boom of the microcomputer era and computers were being widely used in the office.

When the dot-com bubble occurred in the 1990s, so did the boom of data centers. Businesses needed a quick way to establish presence on the Internet.

In 2006 a U.S. government study put total power usage of all servers in the U.S. at about 24 million MWh.

As of 2007, the average datacenter consumes as much energy as 25,000 homes.

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present situation

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Average of annual energy usage, a 400W server may use approximately 1,314 kWh a year (which is simply just powering it on) to about 2,600 kWh per year, energy costs are 800Euro to more about 1600Euro.

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Typical data center

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Analysis of a typical 460m2 data center shows that demand-side computing equipment accounts for 52 percent of energy usage and supply-side systems account for 48 percent. Source: Emerson Network Power

Cascade Effect of power savings

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1-Watt savings at the server-component level creates a reduction in facility energy consumption of approximately 2.84 Watts.

Source: Emerson Network Power

Effective approaches for optimization

The most effective approaches to infrastructure optimization include: Power management Monitoring and optimization DCIM - Data center infrastructure management High efficiency power supplies Low power processors Server virtualizations Cooling best practices Supplemental cooling

Virtualization has had the largest impact on the Data Centers physical infrastructure since the end of the Mainframe - Gartner 2013 Environmental Protection Agency concluded that best practices can reduce data center energy consumption by 50 percent by 2011.

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Worldwide IT use electricity consumption

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Worldwide use electricity consumption of communication networks, personal computers and data centers. ICT products and services in the total worldwide electricity consumption has increased from about 4% in 2007 to 4.7% in 2012.

Source: ICT - Information and Communication Technologies

What On-site technologies can we use

Current Power Technologies powering Data Centers:

Fuel cells eBay

Natural gas turbines Global Bank

Natural gas engines Technology Company

Micro-turbines Datagryd

Renewables for cells or turbines Microsoft

Other promising Applications:

- Biogas turbines more than 2500 installations

- Dual fuel generators Diesel and Natural gas

Source: The Data Centers, LLC (TDC)

http://www.thedatacenters.com/

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Onsite Clean Energy at Google Headquarters An array of Bloom Energy Server fuel cells

running on natural gas are providing the primary power for the new eBay data center in Utah

Top Data Centers stories

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A blimp sponsored by Greenpeace flies over the Facebook headquarters campus in Palo Alto, California. Congratulating Apple, Facebook and Google for their progress using renewable energy in their data centers. (Greenpeace)

Apple, Facebook and Google are leading the shift to a greener Internet, according to a new report from Greenpeace.

Reliability average-downtime/year

While no down-time is ideal, the tier system allows for unavailability of services as listed below over a period of one year (525,600 minutes):

Tier 1 (99.671%) status would allow 1729.224 minutes or 28.8h Tier 2 (99.741%) status would allow 1361.304 minutes or 22h Tier 3 (99.982%) status would allow 94.608 minutes or 1.6h Tier 4 (99.995%) status would allow 26.28 minutes or 0.44h

99.999% Reliability average, 5.3 minutes Non-availability per year 99.9999%, 32 seconds 99.99999%+, 3.2 seconds

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Power usage effectiveness (PUE)

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The initial goal of PUE was to focus on reducing loss and increasing efficiency in the facility.

PUE= Total Facility Energy

IT Equipment Energy

PUE was developed by a consortium called The Green Grid.

Useful Computing

UPS - Uninterruptible power supply PDU - Power Distribution Systems

What is PUE

PUE (power usage effectiveness) is a metric used to determine the energy efficiency of a data center.

This is determined how much energy is used by the computing equipment in contrast to cooling and other facility overhead.

An ideal PUE is 1.0.

Anything that isnt considered a computing device in data center (cooling, lighting, ) falls into the category of facility energy consumption.

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Real-world data center PUE

The average data center in the US has a PUE of 2.0 ("Report to Congress on Server and Data Center Energy Efficiency". U.S. Environmental Protection Agency ENERGY STAR Program)

State-of-the-art data center energy efficiency is estimated to be roughly 1.2.("Data Center Energy Forecast". Silicon Valley Leadership Group)

Google reported that the companys average PUE for 2011 was 1.14.

Microsoft PUE for newest data centers range from 1.13 to 1.2

eBay announced a new data center that has a PUE of 1.35

Yahoo has designs that can deliver a PUE of 1.08

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?

FLOPS/Watt Focus for speed paying attention to other criteria, consumed energy

Green500 list ranks according to FLOPS/Watt current Ranking (November 2013): Measure how efficient a computer solves a dense system of linear equations

with floating point operations. 1. - TSUBAME-KFC, Tokyo Institute of Technology, 4.503,17MFLOPS/Watt, TOP500 rank: 311, Japan 2. - WILKES, Cambridge University 3.631,86 MFLOPS/Watt, TOP500 rank: 166, UK 3. - HA-PACS TCA, University of Tsukuba, 3.517,84 MFLOPS/Watt TOP500 rank: 73, Japan In fact only one supercomputer in both top tens 4. - Piz Daint, Swiss National Supercomputing Centre, 3.185,91 MFLOPS/Watt TOP500 rank: 6, Switzerland. Green500 position of fastest supercomputer 41. - Tianhe-2, Nat. Supercomputer center Guangzhou, 1.901,54 MFLOPS/Watt TOP500 rank: 1, China

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Smart metering

Measurement of Electrical and non-electrical quantities

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Infrared thermography (IRT), thermal imaging, of data center room space can be very useful for correction of air flow and increase efficiency of cooling systems.

Lord Kelvin: If you dont measure you cant improve.

Data Center Measurement System as a part of Energy Monitoring and Demand Side Response of SEEU Campus

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TR_04 TR_01 TR_02 TR_03

PV100 304

Communication net layer as infrastructure is above existing SEEU IT network.

With the installation of smart meters at the SEEU data center entry points , it is possible:

Monitoring of the consumption electricity power

- Identification of peak loads (amount and time of submission), distortions, .

Power Quality delivery from operators

The real time data and historical trends, processing and analysis.

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Power Disturbances

Storm activity Lightning, wind, ice Accidents, object coming in contact with power line Utility fault clearing Construction activity Equipment failure Overloading Load switching Non-Linear loads Poor grounding ESD - Electrostatic discharge EMI - Electromagnetic interference

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Monitoring Power Quality (PQ) Common Power Problems:

Power Failure a total loss of utility power Power Sag short term low voltage Power Surge short term high voltage above 110% Under Voltage reduce line voltage for extended period of time Over Voltage increased line voltage for extended period of time Line Noise high frequency waveforms caused by RFI or EMI Frequency variations change in frequency stability Switching Transients in range of nanoseconds Harmonic Distortion distortion of the normal voltage sinusoidal

waveform

Monitoring different Power Quality phenomena according to standards such are:

- EN 50160 - IEEE 519-1992 - EN 61000-4-15 - flicker measurement

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Monitoring non-electrical but very important quantities for data center

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Running Hot! - 27oC is an appropriate temp to run a data center per ASHRAE Standards - Use of Air Economization / Free Cooling

Typical Rack Enclosure Mounted Server

Expectation of project Reduction of Energy Consumption

Getting beyond PUE

Power management, Power Quality monitoring and tracking

More efficient IT and the Power chain

Looking ahead at new possibilities and technologies

Create a comprehensive Energy Management Plan

Strategize on upgrades/changes to reach the goal

Integration of smart metering, information and communications technology, Data centers becomes one step closer to smart grid solution.

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Thank you for your attention!

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