10.04.30 Distinguished Lecture Scientific Computing and Imaging (SCI) Institute University of Utah Title: The Growing Interdependence of the Internet and Climate Change Salt Lake City, UT

1. ―The Growing Interdependence of the Internet
and Climate Change‖
Scientific Computing and Imaging (SCI) Institute
Distinguished Lecture
University of Utah
April 30, 2010
Dr. Larry Smarr
Director, California Institute for Telecommunications and
Information Technology
Harry E. Gruber Professor,
Dept. of Computer Science and Engineering
Jacobs School of Engineering, UCSD
Twitter: lsmarr

2. Abstract
Greenhouse gas (GHG) emissions continue their relentless rise, even though the global
CO2 level is already considerably higher than it has been on earth for over two million
years. The Information and Communication Technology (ICT) industry currently
produces ~2-3 % of global GHG emissions and will nearly triple, in a business as usual
scenario, from 2002 to 2020. On the other hand, the Climate Group estimates that
transformative application of ICT to electricity grids, logistic chains, intelligent
transportation and building infrastructure, and other social systems can reduce global
GHG emissions by ~15%, five times ICT's own footprint! I will discuss three campus
testbeds for exploring these complex tradeoffs. The first testbed is the NSF-funded
GreenLight Project deployed at UCSD, which creates an instrumented data center that
can guide users who wish to lower the energy cost of computation and storage. The
second testbed is the campus itself, in which the move to centralized computing and
storage can greatly reduce the GHG emissions of the current distributed set of clusters
and storage. The third testbed is the global set of dedicated optical networks (operating
at 10,000 Mbps), coupled to large tiled wall OptIPortals (with fractions of a billion pixels)
and high definition (2 Mpixel/frame) or digital cinema (8Mpixel/frame), to create next
generation "telepresence" systems for "sewing remote rooms together" as a way to
reduce the need for transportation for national or global collaboration.

3. ICT Could be a Key Factor
in Reducing the Rate of Climate Change
Applications of ICT
could enable emissions reductions
of 15% of business-as-usual emissions.
But it must keep its own growing footprint in check
and overcome a number of hurdles
if it expects to deliver on this potential.
www.smart2020.org

4. Rapid Increase in the Greenhouse Gas CO2
Since Industrial Era Began
Source: David JC MacKay,
Sustainable Energy Without the Hot Air (2009)
388 ppm in 2010
Medieval
Little
Warm
Ice Age 290 ppm in 1900
Period

5. Global Average Temperature Per Decade
Over the Last 160 Years

6. Atmospheric CO2 Levels for 800,000 Years
and Projections for the 21st Century
Source: U.S.
Global Change (MIT Study)
Research
Program Report
(2009)
(Shell Study)
www.globalchange.gov/publications/reports/scientific-assessments
/us-impacts/download-the-report

7. Global Climatic Disruption Example:
The Arctic Sea Ice
―A pervasive cooling of the Arctic in progress 2000 years ago continued
through the Middle Ages and into the Little Ice Age. It was reversed during
the 20th century, with four of the five warmest decades of
our 2000-year-long reconstruction occurring between 1950 and 2000. The most
recent 10-year interval (1999–2008) was the warmest of the past 200 decades.‖
Mean of all records transformed to summer temperature anomaly
relative to the 1961–1990 reference period, with first-order linear trend
for all records through 1900 with 2 standard deviations
Science v. 325 pp 1236 (September 4, 2009)

8. Arctic Summer Ice Melting
Accelerating Relative to IPCC 2007 Predictions
Source: www.copenhagendiagnosis.org

9. Global Climatic Disruption Early Signs:
Area of Arctic Summer Ice is Rapidly Decreasing
"We are almost out of
multiyear sea ice in the
northern hemisphere--
I've never seen anything
like this in my 30 years
of working in the high
Arctic.‖
--David Barber, Canada's
Research Chair in Arctic
System Science at the
University of Manitoba
October 29, 2009
http://news.yahoo.com/s/nm/20091029/
sc_nm/us_climate_canada_arctic_1
http://news.cnet.com/8301-11128_3-10213891-54.html

10. Summer Arctic Sea Ice Volume
Shows Even More Extreme Melting—Ice Free by 2015?
Source: Wieslaw Maslowski
Naval Postgraduate School,
AAAS Talk 2010

11. The Latest Science on Global Climatic Disruption
An Update to the 2007 IPCC Report
www.copenhagendiagnosis.org

12. The Global ICT Carbon Footprint is Significant
and Growing at 6% Annually!
the assumptions behind the growth in emissions expected in 2020:
• takes into account likely efficient technology developments
that affect the power consumption of products and services
• and their expected penetration in the market in 2020
www.smart2020.org

13. Reduction of ICT Emissions is a Global Challenge –
U.S. and Canada are Small Sources
U.S. plus Canada Percentage Falls From
25% to 14% of Global ICT Emissions by 2020
www.smart2020.org

14. The Global ICT Carbon Footprint
by Subsector
The Number of PCs (Desktops and Laptops)
Globally is Expected to Increase
from 592 Million in 2002
to More Than Four Billion in 2020
PCs Are Biggest
Data Centers Are
Problem
Rapidly Improving
www.smart2020.org

15. Making University Campuses
Living Laboratories for the Greener Future
www.educause.edu/EDUCAUSE+Review/EDUCAUSEReviewMagazineVolume44/CampusesasLivingLaboratoriesfo/185217

16. Increasing Laptop Energy Efficiency:
Putting Machines To Sleep Transparently
Rajesh Gupta, UCSD CSE; Calit2
Network
interface
Secondary Network
processor interface
Management
software Low power domain
Main processor, Peripheral
RAM, etc
IBM X60 Power Consumption
Laptop
Power Consumption (Watts)
20
16W
18
(4.1 Hrs)
Somniloquy 16
11.05W
Enables Servers 14
(5.9 Hrs)
to Enter and Exit Sleep 12
10
While Maintaining 8
Their Network and 6
Application Level 0.74W 1.04W
4
(88 Hrs) (63 Hrs)
Presence 2
0
Sleep (S3) Somniloquy Baseline (Low
16 Normal
Power)

17. Desktops: Power Savings with SleepServer:
A Networked Server-Based Energy Saving System
State Power
Normal Idle State 102.1W
Lowest CPU Frequency 97.4W
Disable Multiple Cores 93.1W Dell OptiPlex 745
“Base Power” 93.1W Desktop PC
Sleep state (ACPI State S3) 2.3W
Using SleepServers
– Power Drops from 102W to < 2.5W
– Assuming a 45 Hour Work Week
– 620kWh Saved per Year, for Each PC
– Additional Application Latency: 3s - 10s Across Applications
– Not Significant as a Percentage of Resulting Session
17
Source: Rajesh Gupta, UCSD CSE, Calit2

18. PC: 68% Energy Saving Since SSR Deployment
kW-Hours:488.77 kW-H Averge Watts:55.80 W
energy.ucsd.edu Energy costs:$63.54
Estimated Energy Savings with Sleep Server: 32.62%
Estimated Cost Savings with Sleep Server: $28.4

19. ―Blueprint for the Digital University‖--Report of the
UCSD Research Cyberinfrastructure Design Team
• Focus on Greener Data Storage and Data Curation
– These Become the Centralized Components
– Other Common Elements ―Plug In‖
April 24, 2009
research.ucsd.edu/documents/rcidt/RCIDTReportFinal2009.pdf

20. Campus Preparations Needed
to Accept CENIC CalREN Handoff to Campus
Source: Jim Dolgonas, CENIC

21. Current UCSD Prototype Optical Core:
Bridging End-Users to CENIC L1, L2, L3 Services
Quartzite Communications
To 10GigE cluster
node interfaces
Core Year 3
Enpoints:
Quartzite Wavelength
>= 60 endpoints at 10 GigE
Core
Selective
.....
Switch
>= 32 Packet switched Lucent To 10GigE cluster
node interfaces and
>= 32 Switched wavelengths other switches
To cluster nodes
.....
>= 300 Connected endpoints
Glimmerglass
To cluster nodes
.....
Production
GigE Switch with
OOO
Dual 10GigE Upliks
Switch
To cluster nodes
Approximately 0.5 TBit/s
32 10GigE
.....
Arrive at the ―Optical‖ GigE Switch with
Force10 Dual 10GigE Upliks
Center of Campus.
...
GigE Switch with
Switching is a Hybrid of:
To Packet Switch CalREN-HPR
Research
Dual 10GigE Upliks
Packet, Lambda, Circuit --
other
nodes
Cloud
GigE
OOO and Packet Switches
10GigE
Campus Research
4 GigE
4 pair fiber
Cloud
Juniper T320
Source: Phil Papadopoulos, SDSC/Calit2
(Quartzite PI, OptIPuter co-PI)
Quartzite Network MRI #CNS-0421555;
OptIPuter #ANI-0225642

22. UCSD Campus Investment in Fiber Enables
Consolidation of Energy Efficient Computing & Storage
CENIC, NLR, I2DCN
Nx
10Gbe
Gordon –
HPC System
Cluster
Condo
DataOasis
(Central) Storage
Triton – Petadata
Analysis
Scientific
Instruments
Digital Data Campus Lab OptIPortal
Collections Cluster Tile Display Wall
Source: Philip Papadopoulos, SDSC, UCSD

23. The GreenLight Project:
Instrumenting the Energy Cost of Computational Science
• Focus on 5 Communities with At-Scale Computing Needs:
– Metagenomics
– Ocean Observing
– Microscopy
– Bioinformatics
– Digital Media
• Measure, Monitor, & Web Publish
Real-Time Sensor Outputs
– Via Service-oriented Architectures
– Allow Researchers Anywhere To Study Computing Energy Cost
– Enable Scientists To Explore Tactics For Maximizing Work/Watt
• Develop Middleware that Automates Optimal Choice
of Compute/RAM Power Strategies for Desired Greenness
• Partnering With Minority-Serving Institutions
Cyberinfrastructure Empowerment Coalition
Source: Tom DeFanti, Calit2; GreenLight PI

24. GreenLight’s Data is Available Remotely:
Virtual Version in Calit2 StarCAVE
30 HD Connected at
Projectors! 50 Gb/s to Quartzite
Source: Tom DeFanti, Greg Dawe, Jurgen Schulze, Calit2

25. Research Needed
on How to Deploy a Green CI
MRI • Computer Architecture
– Rajesh Gupta/CSE
• Software Architecture, Clouds
– Amin Vahdat, Ingolf Kruger/CSE
• CineGrid Exchange
– Tom DeFanti/Calit2
• Visualization
– Falko Kuster/Structural Engineering
• Power and Thermal
Management
– Tajana Rosing/CSE
• Analyzing Power
Consumption Data
– Jim Hollan/Cog Sci
• Direct DC Datacenters
– Tom Defanti, Greg Hidley
http://greenlight.calit2.net

26. New Techniques for Dynamic Power and Thermal
Management to Reduce Energy Requirements
NSF Project Greenlight
• Green Cyberinfrastructure in
Energy-Efficient Modular Facilities
• Closed-Loop Power &Thermal
Management
Dynamic Power Management (DPM) Dynamic Thermal Management (DTM)
• Optimal DPM for a Class of Workloads • Workload Scheduling:
• Machine Learning to Adapt • Machine learning for Dynamic
• Select Among Specialized Policies Adaptation to get Best Temporal and
• Use Sensors and Spatial Profiles with Closed-Loop
Performance Counters to Monitor Sensing
• Multitasking/Within Task Adaptation • Proactive Thermal Management
of Voltage and Frequency • Reduces Thermal Hot Spots by Average
• Measured Energy Savings of 60% with No Performance Overhead
Up to 70% per Device
CNS System Energy Efficiency Lab (seelab.ucsd.edu)
Prof. Tajana Šimunić Rosing, CSE, UCSD

27. Application of ICT Can Lead to a 5-Fold Greater
Decrease in GHGs Than its Own Carbon Footprint
While the sector plans to significantly step up
the energy efficiency of its products and services,
ICT’s largest influence will be by enabling
energy efficiencies in other sectors, an opportunity
that could deliver carbon savings five times larger than
the total emissions from the entire ICT sector in 2020.
--Smart 2020 Report
Major Opportunities for the United States*
– Smart Electrical Grids
– Smart Transportation Systems
– Smart Buildings
– Virtual Meetings
* Smart 2020 United States Report Addendum
www.smart2020.org

28. Real-Time Monitoring of Building Energy Usage:
UCSD Has 34 Buildings On-Line
http://mscada01.ucsd.edu/ion/

29. Comparision Between UCSD Buildings:
kW/sqFt Year Since 1/1/09
Calit2 and
CSE are
Very Energy
Intensive
Buildings

30. Power Management in Mixed Use Buildings:
The UCSD CSE Building is Energy Instrumented
• 500 Occupants, 750 Computers
• Detailed Instrumentation to Measure
Macro and Micro-Scale Power Use
– 39 Sensor Pods, 156 Radios, 70 Circuits
– Subsystems: Air Conditioning & Lighting
• Conclusions:
– Peak Load is Twice Base Load
– 70% of Base Load is PCs
and Servers
– 90% of That Could Be Avoided!
Source: Rajesh Gupta,
CSE, Calit2

31. Contributors to the CSE Base Load
• IT loads account for 50% (peak) to 80% (off-peak)!
– Includes machine room + plug loads
• IT equipment, even when idle, not put to sleep
• Duty-Cycling IT loads essential to reduce baseline
31
Source: Rajesh Gupta, UCSD CSE, Calit2

32. HD Talk to Australia’s Monash University from Calit2:
Reducing International Travel
July 31, 2008
Qvidium Compressed HD ~140 mbps
Source: David Abramson, Monash Univ

33. Linking the Calit2 Auditoriums at UCSD and UCI
with LifeSize HD for Shared Seminars
Sept. 8, 2009 2009
September 8,
Photo by Erik Jepsen, UC San Diego

34. First Tri-Continental Premier of
a Streamed 4K Feature Film With Global HD Discussion
4K Film Director,
Beto Souza
Keio Univ., Japan Calit2@UCSD
Source:
Sheldon Brown, San Paulo, Brazil Auditorium
CRCA, Calit2
4K Transmission Over 10Gbps--
4 HD Projections from One 4K Projector

35. The OptIPuter Project: Creating High Resolution Portals
Over Dedicated Optical Channels to Global Science Data
Scalable
Adaptive
Graphics
Environment
(SAGE)
Picture
Source:
Mark
Ellisman,
David Lee,
Jason Leigh
Calit2 (UCSD, UCI), SDSC, and UIC Leads—Larry Smarr PI
Univ. Partners: NCSA, USC, SDSU, NW, TA&M, UvA, SARA, KISTI, AIST
Industry: IBM, Sun, Telcordia, Chiaro, Calient, Glimmerglass, Lucent

36. On-Line Resources
Help You Build Your Own OptIPortal
www.optiputer.net
http://wiki.optiputer.net/optiportal
www.evl.uic.edu/cavern/sage/
http://vis.ucsd.edu/~cglx/
OptIPortals Are Built
From Commodity PC Clusters and LCDs
To Create a 10Gbps Scalable Termination Device

37. the AESOP Nearly Seamless OptIPortal
46‖ NEC Ultra-Narrow Bezel 720p LCD Monitors
Source: Tom DeFanti, Calit2@UCSD;

38. High Definition Video Connected OptIPortals:
Virtual Working Spaces for Data Intensive Research
NASA Ames
Mountain View, CA
NASA Interest
in Supporting
Virtual
Institutes
LifeSize HD
Calit2@UC San Diego
Enables Collaboration
Without Travel
Source: Falko Kuester, Kai Doerr Calit2; Michael Sims, NASA

39. Providing End-to-End CI
for Petascale End Users
Two 64K Mike Norman, SDSC
Images October 10, 2008
From a
Cosmological
Simulation log of gas temperature log of gas density
of Galaxy
Cluster
Formation

40. 3D Stereo Head Tracked OptIPortal:
NexCAVE
Array of JVC HDTV 3D LCD Screens
KAUST NexCAVE = 22.5MPixels
www.calit2.net/newsroom/article.php?id=1584
Source: Tom DeFanti, Calit2@UCSD

41. 3D CAVE to CAVE Collaboration
with HD Video
Photo: Tom DeFanti
Calit2’s Jurgen Schulze in San Diego in StarCAVE and
Kara Gribskov at SC’09 in Portland, OR with NextCAVE

42. For Technical Details
On OptIPuter Project and OptIPortals
“OptIPlanet: The OptIPuter
Global Collaboratory” –
Special Section of
Future Generations
Computer Systems,
Volume 25, Issue 2,
February 2009

43. Follow My Talks and Tweets at lsmarr.calit2.net