Visualization in the Design and Operation of Efficient Data Centers

VISIT 2010 – Fujitsu Forum Europe 1

Innovation Forum – Room 12

Shapingtomorrowwith you.

Visualization in the Design and Operation of Efficient Data Centerswith you.

Dr. David SnellingResearch Project Manager Computer Architectures, Fujitsu Laboratories

17:15 h17:15 h

VISIT 2010 – Fujitsu Forum Europe

3

Visualization in the Design andVisualization in the Design and Operation of Efficient Data Centers

Dr. David SnellingF jit L b t i f EFujitsu Laboratories of Europe

Copyright 2010 Fujitsu Laboratories

BackgroundgThe reduction of energy consumption and CO2 emissions are serious environmental issuesare serious environmental issues.Energy spent on non-IT functions, e.g. air conditioning and power management, need to be reduced.and power management, need to be reduced.IT equipment efficiency needs improving.

140250

消費電力量（億kWh）h)

IT equipment Air conditioner0

100

120

140

150

200

消費電力量（億kWh）

総床面積(万m2)

on (x1

08kW

h

e（x1

04㎡

）

sum

ptio

n

or S

pace

IT facilitiesIT resources

IT equipment

Power unit40

60

80

50

100

consu

mptio

Flo

or

spac

e

rgy

Con

s

Floo

Ratio of energy consumption in IDC

Lighting

0

20

2007 2008 2009 2010 2011 2012

0

50

Energ

y F

(FY)2007 2008 2009 2010 2011 2012

Ene

VISIT 2010 Fujitsu European Forum Copyright 2010 Fujitsu Laboratories

Ratio of energy consumption in IDC(Fujitsu, FY2006)Energy consumption of IDC in Japan

（MIC Research Institute 2008)5

Holistic Approachpp

100%Data Centre input


Data Centre100%

CERES

40%IT input

40%IT input

Equipment40%

25%Power

35%Cooling

65%Servers65%

ServersServers26%

15% 20%Network

Storage

30%CPU30%CPU

CPU7.8%

25%Power

45%Others

20%Work20%Work

Utilisation1 6%

80%Idle

VISIT 2010 Fujitsu European Forum

1.6%

Copyright 2010 Fujitsu Laboratories6

CERES MotivationCost and EnergygyReduction EvaluationService

9%

29%

3%Power

Cooling

IT

Aims:Reduce energy use in

59%Other

Reduce energy use in data centersQuantify savings in advance 9%3%Quantify savings in advanceof decision makingPredict effects of operational

29%

59%

Power

Cooling

IT

OtherPredict effects of operationalchanges to facilitate risk analysisIdentify precisely where energy losses exist


Identify precisely where energy losses exist


Holistic SimulationRESULTS

Visible ¥ and CO

RESULTS

Visible ¥ and CO

WHY

Soaring energ

WHY

Soaring energ

Data center energy and heat schematicVisible ¥ and CO2impact promotes

best practice

DC lifetime cost &

Visible ¥ and CO2impact promotes

best practice

DC lifetime cost &

Soaring energy costs

CO2 is a regulatory

Soaring energy costs

CO2 is a regulatory

environmental impact known for

all services

New green

environmental impact known for

all services

New green

issue

CSR

Energy

issue

CSR

Energy New green services

New green services

Energy constraints

Energy constraints

Final results of this example show reduction incost and CO2 by using more efficient chillers

HOWMathematically link IT use to direct & indirect energy use

HOWMathematically link IT use to direct & indirect energy use

HOWBuild on existing technologies to

predict actual costs

HOWBuild on existing technologies to

predict actual costs

HOWDerive immediate customer

value from reduced energy use

HOWDerive immediate customer

value from reduced energy use

cost and CO2 by using more efficient chillers


direct & indirect energy usedirect & indirect energy use predict actual costspredict actual costs value from reduced energy usevalue from reduced energy use


Example OutcomesCompleted a CO2 Value Analysis for a UK DC

Simulator validated: 95% to 98% accurate

Action Recommended for UK DC by CO2 Value Analysis

% CO2 Reduction

Annual Cost Savings

Shutdown air conditioning and UPS 1 4% £8K / Ygwhen disaster recovery hall not in use 1.4% £8K / Year

Use exactly the right air conditioning in main computer halls 9% £52K / Yearmain computer hallsAdd free cooling to data center 17% £98K / Year

Use variable speed fans in computer room air conditioners 14% £81K / Year

All the above 29% £167K / Y


29% £167K / Year


Server Level



Data Centre100%

40%IT input

40%IT input

Equipment40%

25%Power

35%Cooling Fiber Optic

65%Servers65%

ServersServers26%

15% 20%Network

Storage

30%CPU30%CPU

CPU7.8%

25%Power

45%Others

20%Work20%Work

Utilisation1 6%

80%Idle


1.6%


Real-Time Multiple-Point Measurement

Temperature distribution is easily and precisely p y p ymeasured by observing Raman scattering light10 000 data points along 10 000m single10,000 data points along 10,000m single optical fiber

Data CentreData Centre Temp Principle of measurement Principle of measurement Data Centre Data Centre Temp.

Laser Laser pulse Optical Fiber

Optical fibre Intensity of Raman scattering light Detector

Raman Scattering Light

Servers

Temp. of points in optical fiber

Propagationtime

Floor


Distance 11

Temperature Distributionp

24 Hot spot

2D temperature distribution of server rack surfaces24

21

Temperature distribution along an optical fibre

erat

ure

Location

Tem

pe

Knowing the precise temperature distribution across racks every 20 seconds facilitates emergency responseAn energ sa ing of 10% to 30% b optimi ing air conditioning

Location


An energy saving of 10% to 30% by optimizing air-conditioning

12

Device Level



Data Centre100%

40%IT input

40%IT input

Equipment40%

25%Power

35%Cooling

65%Servers65%

ServersServers26%

15% 20%Network

Storage

30%CPU30%CPU

CPU7.8%

25%Power

45%Others

20%Work20%Work

Utilisation1 6%

80%Idle

GaN HEMT


1.6%


GaN HEMT TechnologygyNew transistor in Fujitsu Labs. Ｔhe world's highest on-state current density while achieving a turn-on voltage of +3 V, making it the first GaN-HEMT in the world that has the characteristics required for power supply.

Target area for power supply

ty

1200

Why GaN for power supply applications ?

urre

nt d

ensi

tA

/mm

)

800

1200Electrode Electrode

Si

other reports

0O

n-st

ate

cu (mA

400GaN Smaller transistor sizes became possible.

・Breakdown voltage：10 times higher・Electron velocity：2 times higher

Small size


Turn-on voltage （V)

2 40 60Electron velocity：2 times higher

・Electron density：10 times higherLow loss

14

Effect of GaN HEMT

Power loss can be reduced by one-thirdPower loss can be reduced by one third compared to power supplies based on conventional silicon transistorsconventional silicon transistors.

Silicon Transistor GaN TransistorSwitching

Other lossesOnl

-lossPower -saving

Other losses

(i.e., Transformer)-loss saving

VISIT 2010 Fujitsu European Forum Copyright 2010 Fujitsu Laboratories15

Gallium Nitride (GaN) HEMT( )Power-saving data center

Data-center power consumption in Japan could be reduced by 12% (330,000 tons CO2)

Small-size power supplySmaller power supplies would contribute to reducing space requirements in serversThe size of AC adapters for notebook PCs could be reduced to one tenth current sizes “Brickless” laptopsreduced to one-tenth current sizes – Brickless laptops

Power Supply ApplicationsGaN Transistor Power Supply ApplicationsGaN Transistor


Server Data Centre Laptop

16

Where to Next?

Power-saving server

Power plants

Power-saving laptop PC with small AC adaptor

Power savingIndustrial machines

Power-savinghome electronics

Lifestyle innovation

Motors

bil h


Electric vehiclemobile phone

17

Service Level



Data Centre100%

40%IT input

40%IT input

Equipment40%

25%Power

35%Cooling

65%Servers65%

ServersServers26%

15% 20%Network

Storage

30%CPU30%CPU

CPU7.8%

25%Power

45%Others

20%Work20%Work

Utilisation1 6%

80%Idle


1.6%SysViz


SysViz: MotivationSystem performance has

suddenly degraded, but how to locate the cause?

y

It will take hours to cross-check the logs of

components (network, database, middleware)!

Open, multi-vendor, huge

We have to solve it quickly in order to meet SLA!

and complex systems

Challenge: View and understand the interactive behavior of large numbers of heterogeneous components in real-time

• See where current and future problems/opportunities exist• Manage them appropriately


Manage them appropriately• Retain agility to meet customer demands at the service level


SysViz: Deploymenty p y

Non-intrusive, agent-less monitoring, g gNetwork traffic directly captured from the IP network by port-mirroring network devicesy p g

• no need of agents on servers nor software modification• no risk of system performance/reliability degradation

Just plug SysViz engine to the network device

It can be applied to operational systems without affecting its operation

VISIT 2010 Fujitsu European Forum Copyright 2010 Fujitsu Laboratories20

SysViz: Configurationy gAutomatic system behavior modeling

System behavior model gives the sequence of messages that compose each business transaction• generated by our event mining technology that identifies• generated by our event mining technology that identifies • correlations and causalities between network messages

Target S stem B h i M d lCrude

Target System

350

400

450

[ms]

Response breakdown

[ms]

Behavior Model

100

150

200

250

300

350

均サ

ーバ

処理

時間

　es

pons

e Ti

me

Auto Generate Report

0

50

9:30

9:31

9:32

9:33

9:34

9:35

9:36

9:37

9:38

9:39

9:40

9:41

9:42

9:43

9:44

9:45

9:46

9:47

9:48

9:49

9:50

9:51

9:52

9:53

9:54

9:55

9:56

9:57

9:58

9:59

時刻

平均

Web/AP DB BTOnline(HTTP) BTOnline(DB)

Re

Frequency


erroneous causalities

21

SysViz: Operationy pReal-time model based monitoring

Refine a crude model manually during operations to represent y g p pnormal behavior of business transactions.Network traffic is filtered by using this behavioral model • Unusual behavior that deviates from the model U usua be a o a de a es o e ode• raises alerts in the monitoring dashboard

B h i M d lTarget System OperationCrudeRefined

Behavior ModelTarget System

This component

Operation Manager

This component is slower than

usualVisualizeAuto Generate

These components show unusual operation flow


erroneous causalities

22

Holistic Summaryy



Data Centre100%

CERES

40%IT input

40%IT input

Equipment40%

25%Power

35%Cooling Fiber Optic

65%Servers65%

ServersServers26%

15% 20%Network

Storage

30%CPU30%CPU

CPU7.8%

25%Power

45%Others

20%Work20%Work

Utilisation1 6%

80%Idle

GaN HEMT


1.6%SysViz


VISIT 2010 Fujitsu European Forum 24


Date post:	14-Dec-2014
Category:	Technology
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