Gen AI in Business - Global Trends Report 2024.pdf
SURA Meeting Washington
1. Climate Change: Challenges and Opportunities for R&E networks Bill St. Arnaud CANARIE Inc – www.canarie.ca [email_address] Unless otherwise noted all material in this slide deck may be reproduced, modified or distributed without prior permission of the author
5. The Planet is Already Committed to a Dangerous Level of Warming V. Ramanathan and Y. Feng, Scripps Institution of Oceanography, UCSD September 23, 2008 www.pnas.orgcgidoi10.1073pnas.0803838105 Source: Larry Smarr CAL-It2 Temperature Threshold Range that Initiates the Climate-Tipping Additional Warming over 1750 Level 90% of the Additional 1.6 Degree Warming Will Occur in the 21 st Century
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9. IT biggest power draw Heating, Cooling and Ventilation 40-50% Lighting 11% IT Equipment 30-40% Other 6% Sources: BOMA 2006, EIA 2006, AIA 2006 Energy Consumption Typical Building Energy Consumption World Wide Transportation 25% Manufacturing 25% Buildings 50%
13. State GHG Targets 2009 SOURCE: Pew Center on Global Climate Change, Climate101-State Actions, January 2009 42% of States Have Existing GHG Reduction Targets
18. The Cost of Regulation: The University of British Columbia SOURCE: UBC Sustainability Office, August 2009 SOURCE: http://climateaction.ubc.ca/category/emission-sources SOURCE : UBC Climate Action Plan, GHG 2006 Inventory Source: Jerry Sheehan UCSD UBC Greenhouse Gas Liability 2010-2012 2010 2011 2012 Carbon Offset $1,602,750 $1,602,750 $1,602,750 Carbon Tax $1,179,940 $1,474,925 $1,769,910 Total $2,782,690 $3,077,675 $3,372,660
24. Many examples already Hydro-electric powered data centers Data Islandia Digital Data Archive ASIO solar powered data centers Wind powered data centers Ecotricity in UK builds windmills at data center locations with no capital cost to user
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26. Optical Network as Enabler SOURCE: Eric Bernier, CTO CANARIE Bandwidth when required … where required 100GBPS Ready
27. Zero Carbon Data Center source: Dan Gillard BCnet 04/09 BC’s Green Data Centre MUST be in Proximity to a Clean Source of Power
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32. GENI Topology optimized by source destination Source: Peter Freeman NSF Wind Power Substrate Router Solar Power Wireless Base Station Sensor Network Thin Client Edge Site Mobile Wireless Network
33. GENI with router nodes at renewable energy sites Sensor Network Thin Client Edge Site Source: Peter Freeman NSF Wind Power Substrate Router Solar Power Wireless Base Station Topology optimized by availability of energy Mobile Wireless Network
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35. The SC06 VMT Demonstrator Computation at the Right Place & Time! We migrate live Virtual Machines, unbeknownst to applications and clients, for data affinity, business continuity / disaster recovery, load balancing, or power management DataCenter @Tampa SC|2006 Nortel’s Sensor Services Platform Korea KREOnet Netherlight DRAC Controlled Lightpaths Internal/External Sensor Webs Amsterdam
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47. Virtualization and De-materialization Source: European Commission Joint Research Centre, “The Future Impact of ICTs on Environmental Sustainability”, August 2004 Direct replacement of physical goods – 10% - 20% impact
51. Other sectors (40%) (e.g. manufacturing, coal mining, export transport) Emissions under direct consumer control (35%) Consumer influenced sectors (25%) (e.g. retail, food and drink, wholesale, agriculture, public sector) Heating Private cars Electricity Other transport Consumers control or influence 60 per cent of emissions http://www.cbi.org.uk/pdf/climatereport2007full.pdf 30
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Notas del editor
ERM has a strong pro-active dimension. As much about proactively managing as measuring It is a key part of our mission to Enable you to make decisions that are based on risk across the enterprise, levels of users,
Assume each higher-ed produces 1-2 x 10e5 metric tons COe2 There are 3 x 10e3 higher ed institutions Therefore total higher ed CO2 emissions = 3-6 x 10e8 tons US total emissions 7 x 10e9 COe2 Therefore high ed percentage 3-6 x 10e8/7 x 10e9= 4.5 – 8.5%
Future projections from Gartner
Each element (component) shown is a sophisticated network router or computer system. A given experiment will be allocated a portion of each of a subset of these elements and of the links connecting these elements. This partition of physical resources is called a slice. Software to be developed will allow a large number of experiments to simultaneously run, each in its own slice, without interfering with other experiments. Virtualization refers to the ability of experiments to behave as if they are not sharing the same physical elements or links. The facility is programmable in the sense that software for a slice can be downloaded from a researcher workstation to elements on which the slice resides using tools provided by GENI. In addition, a researcher can define a slice and request its allocation for an experiment from a local workstation. In effect, experimenters will operate as if they are using a new internet based on their own innovations.
Each element (component) shown is a sophisticated network router or computer system. A given experiment will be allocated a portion of each of a subset of these elements and of the links connecting these elements. This partition of physical resources is called a slice. Software to be developed will allow a large number of experiments to simultaneously run, each in its own slice, without interfering with other experiments. Virtualization refers to the ability of experiments to behave as if they are not sharing the same physical elements or links. The facility is programmable in the sense that software for a slice can be downloaded from a researcher workstation to elements on which the slice resides using tools provided by GENI. In addition, a researcher can define a slice and request its allocation for an experiment from a local workstation. In effect, experimenters will operate as if they are using a new internet based on their own innovations.