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Module 3Building a Green ICT community
Diarmuid Ó Briain
27 March 2017
Green ICT Workshop
EACO Working Group 1027 – 29 March 2017
netLabs! Uganda
Learning Objectives
● By the end of this module you should be able to:– Describe the ecological footprint.
– Describe climate change and the impact that ICT can have.
– Classify ICT as an enabler to Smart technologies as a key element of the fight back.
– Recognise Green ICT as an important approach to reducing the effect of ICT on the ecological footprint both in reducing its own impact as well as an enabler within other fields.
– Differentiate the different elements within the Green ICT approach.
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Earth Overshoot day
1960 1970 1980 1990 2000 2010 2020 2030
28/6/2030
30%
Humanities choice
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Green ICT
● Environmental sustainable technology and processes
● Designing, manufacturing, using and disposing ● Minimal or no impact to environment: 3P’s
(People, Planet, Profit).
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Factors driving Green ICT implementation
12
3
● Decreased consumables use
● Decreased electricity use
● Increased features and functionality for the business
● Decreased expenses or investments
● Meeting demands from customers
● Realise credits or rebates government and/or local utilities.
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The greening of ICT
Product longevity
Data centre design
Software
Power Management
Materials recycling
Cloud computingTelecommuting
Telecommunications & network devices
Supercomputers
VirtualisationResource allocation
Terminal servers
Algorithmic efficiency
Software & deployment optimisation
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Product longevity
● Computer manufacturing process accounts for 70% of the natural resources used in the life cycle of it.
● The biggest contribution to green ICT is extending the life of the computers used – Random Access Memory (RAM)
– Solid State Drive (SSD).
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Data Centre design
● 2015 Data Centres electricity use:– 416.2 Terawwatt (TW) hours
– 3% of the world’s total energy use that year
– Treble the amount of electricity in the next decade.● Energy efficient data centre design means addressing:
– ICT systems
– Environmental conditions
– Air management
– Cooling systems
– Electrical systems.● better utilisation of the space.● Increased performance.● Increased efficiency.
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Software and deployment optimisation
VirtualisationResource allocation
Terminal servers
Algorithmic efficiency
Software & deployment optimisation
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Software - Algorithmic efficiency
● Algorithmic efficiency affects the computer resources required for any given computing task.
● Algorithm changes, such as switching from a slow linear search algorithm to a fast hashed or indexed search algorithm can reduce resource usage for a given task from substantial to close to zero.
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Software - Resource allocation
● Routing Algorithms can route data to data centres with: – the cheapest energy costs
● Does not actually reduce the energy costs.
– that are powered by green energy. ● Data centres in temperate climates● Hemispheres.
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Software - Virtualisation
● Abstraction of computer process of running two or more logical computer systems on one set of physical hardware.
– Hypervisor
– Virtual Machines (VM).
Hypervisor - Virtualisation Layer
Host Operating System
x86 Architecture
Guest Operating System #1
Application1
Application2
Application3
Application4
Virtual machine #1
Guest Operating System #2
Application1
Application2
Application3
Application4
Virtual machine #2 VM #x
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Software - Terminal Servers / Thin clients
● Low power terminals connect to a central terminal server where the actual computing is carried out
● 1/8 fraction of the energy of a workstation● Terminal server can be located in a data centre with efficient
energy consumption.
Network
Internet
Virtualisation
Thin clients
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Power Management
● Computer manufacturing process accounts for 70% of the natural resources used in the life cycle of it.
● The biggest contribution to green ICT is extending the life of the computers used
– Random Access Memory (RAM)
– Solid State Drive (SSD).
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Power – Data Centre
● Extraordinarily high energy demand.● Can improve energy and space efficiency:
– Storage consolidation
– Virtualisation. ● Siting of data centres
– Temperate climates.● Data Centre infrastructure Efficiency (DCiE):
– DCiE of 1 – 100% powering the IT equipment
– DCiE 0.75 – 75% of the powers the IT equipment.
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Data Centre power consumption
Statistics Uganda Ireland
Population (2017) 36 million 4.5 million
Total power consumption 489 MW 24 TW
Wind (Tororo Wind Power Station) 20 MW 3 TW
Solar 10 MW 1 MW
Hydro 800 MW 500 MW
National Data Centre consumption (2017) 0 MW 550 MW
National Data Centre consumption (2019) 0 MW 1000 MW
1 TW = 1,000,000 MW = 1,000,000,000,000 W
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Power – Operating Systems
● Operating Systems have included power management features for some time.
– Stand-by (suspend to RAM)
– Monitor low power state
– Hibernate (suspend to disk)
– Advanced Configuration & Power Interface (ACPI).
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Power – Power supplies
● 70–80% efficient with the remaining energy dissipated as heat.
● EnergyStar vertified PSU as 80%+ efficient.– Programme was suspended.
● 2014 Level VI standards to PSUs from 5 W to 150 W: – Requirement in USA from February 10, 2016
– Addresses active mode with efficiency is increased by roughly 5%
– No load.● Code of Conduct (CoC) Tier 1 and Tier 2:
– 2017 Tier 1 Level VI
– 2018 Tier 2.
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Power – Display
● Cathode Ray Tube (CRT)● Lower power Liquid Crystal Display (LCD)
– Cold-cathode fluorescent bulb
– Array of Light-Emitting Diodes (LED).
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Materials recycling
● Recycling computing equipment harmful materials:– Lead, mercury, and hexavalent chromium
– Replace equipment that would need to be manufactured
● Saving further energy and emissions.
– Re-purposed. ● Printer cartridges, paper, and batteries may also be
recycled.● Computer dumping.● Privacy concerns.
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Cloud computing
● The practice of using a network of remote servers hosted on the Internet to store, manage, and process data, rather than a local server:
– Elastic compute
– Elastic storage.● Hardware in Data Centres specialising in mass computing. ● Addresses Green ICT challenges:
– Energy usage
– Resource consumption
– LE - energy consumption & carbon emissions by 30%
– SME - energy consumption & carbon emissions by 90%.
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Telecommuting
● Teleconferencing and telepresence technologies:
– Increased worker satisfaction
– Reduction of greenhouse gas emissions (travel)
– Increased profit margins (less office costs, heating, light and space).
● Heat, air conditioning and lighting accounting for 70% of all energy consumed in offices. Many types of jobs, such as sales, consulting, and field service are
– Hot-desking.● Voice over the Internet Protocol (VoIP)● phone extension mobility.
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Telecom and network device virtualisation
● Energy consumption of:
– Compute 9.4%
– Network 5.3%.● Modern networks:
– Software Defined Networking (SDN)
– Network Functions Virtualisation (NFV).
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Supercomputers
● Large power requirements.
– TOP500
– Green500● LINPACK Benchmarks
– Floating Point Operations Per Second (FLOPS) per watt.● DGX SATURNV and Piz Daint:
– NVIDIA’s P100 Tesla GPU
– 9.46 gigaflops per watt ● 40% on previous● NVIDIA Pascal architecture:
– 16 nanometre FinFET for unprecedented energy efficiency– An exponential leap in performance per watt– Scale applications across multiple GPUs– Chip on Wafer on Substrate (CoWoS)
● boosts memory bandwidth performance for big data workloads.● New Artificial Intelligence (AI) Algorithms.
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Class Assignment
● As a civil servant in the Ugandan Ministry for Agriculture you have been assigned to a group which must develop a paper to explain the concept for the building of a green ICT community between:– the ministry
– the agri-industry
– the farming community.
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Class Assignment
● Your initial tasks are:– Consider the make-up of the group. Who should
be in it?, who should chair it?
– What are the 3 key current contextual issues which the group will need to consider when developing the paper
– SWOT which the group will need to consider when drafting the paper
– Prepare a SWOT analysis chart for discussion with the group.