Reducing the Global ICT Footprint via Self-adaptive Large-scale ICT Systems
Reducing the Global ICT Footprint via Self-adaptive Large-scale ICT Systems
批准号:
EP/V007092/1
负责人:
Peter Garraghan
金额:
$148.7万
依托单位:
依托单位国家:
英国
项目类别:
Fellowship
财政年份:
2021
资助国家:
英国
项目状态:
未结题
起止时间:
2021 至 --
中文摘要
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英文摘要
ICT now consumes approximately 10% of global electricity, with large-scale ICT systems such as Cloud datacentres, IoT, and HPC systems generating a substantial ICT footprint in terms of energy consumption and GHG emissions, and are growing contributors to climate change. Researchers across Computer Science and various engineering disciplines have predominantly tackled this problem via enhancing the energy-efficiency of individual components (software, servers, networking, cooling) via improvements to scheduling, software optimisation, hardware, and cooling.However, enhancing system component efficiency has still resulted in a growing global ICT footprint - more data, greater compute ability, and more devices. This is due to the rebound effect, whereby technological progress enhances system efficiency, however increases the rate of consumption and end-use demand. This is of increasing concern given the end of Moore's law, growing global digital service consumption, and the rise of Big Data and AI services in society - all when combined result in a rapidly increasing ICT footprint. It is no longer possible to rely on the conventional perception that 'green' large-scale ICT systems can be achieved just by solely improving component energy-efficiency. There needs to focused effort to actually reverse the global ICT footprint.We believe that this problem is not insurmountable however, yet requires a radical rethink how large-scale ICT systems are designed and operate. A system's ICT footprint is a by-product of its operation; we propose to inverse this dynamic - whereby system operation is instead a by-product of, and directly dictated by, its ICT footprint. What is required isn't greater efficiency, but instead precise control over how ICT systems operate and respond to energy levels and footprint targets; a significant research challenge given the sheer scale and complexity in understanding the relationship between ICT footprint manifestation, component interactions, and the impact of organisational sustainability practises. This challenge is further compounded by potential organisational resistance who may champion commercial profits over environment concerns. However, overcoming this challenge would allow ICT systems operation to be directly matched to energy generated from renewable sources, adhere to a specified GHG emission targets defined at organisational or national level, or dynamically align with an organisation's commercial targets or OpEx restrictions. This fellowship will design a large-scale ICT system capable of self-adapting its operation in response to energy availability and ICT footprint targets. This specifically entails:(1) Studying of causes of ICT footprint manifestation within technology organisations, and understand the rationale and impact of enacting sustainability practises.(2) Determine and model the precise relationship between complex ICT component interactions and resultant ICT footprint. (3) Design a self-adaptive framework that coordinates ICT energy-efficient decision making holistically.(4) Create a holistic resource manager underpinned by energy availability and ICT footprint targets.This fellowship is backed by a consortium of industrial and academic Computer Science and sustainability collaborators in the UK and beyond, and will be underpinned by considerable empirical analysis and experimentation in both production and laboratory CPU/GPU-based datacentre and HPC systems. Findings from this fellowship are potentially ground breaking towards designing future digital infrastructure in the face of environmental change. Our key outcomes include: - Reducing ICT system energy use between 25-50% with no software performance penalty. - Demonstrating the feasibility to reverse global ICT footprint growth via unshackling system operation from the rebound effect. - Releasing the largest in-depth operational and energy data from real-world ICT systems.
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DOI:
10.1109/tpds.2021.3079202
发表时间:
2022-01
期刊:
IEEE Transactions on Parallel and Distributed Systems
影响因子:
5.3
作者:
[Gingfung Yeung;Damian Borowiec;Renyu Yang;A. Friday;R. Harper;Peter Garraghan]
通讯作者:
Gingfung Yeung;Damian Borowiec;Renyu Yang;A. Friday;R. Harper;Peter Garraghan
DOI:
10.1109/tpds.2023.3279233
发表时间:
2023-07
期刊:
IEEE Transactions on Parallel and Distributed Systems
影响因子:
5.3
作者:
[Damian Borowiec;Gingfung Yeung;A. Friday;Richard Harper;Peter Garraghan]
通讯作者:
Damian Borowiec;Gingfung Yeung;A. Friday;Richard Harper;Peter Garraghan
A material social view on data center waste heat: Novel uses and metrics
关于数据中心废热的重要社会观点:新颖的用途和指标
DOI:
10.3389/frsus.2022.1008583
发表时间:
2023
期刊:
Frontiers in Sustainability
影响因子:
--
作者:
[Terenius P]
通讯作者:
Terenius P
HUNTER: AI based Holistic Resource Management for Sustainable Cloud Computing
HUNTER:基于人工智能的可持续云计算整体资源管理
DOI:
10.48550/arxiv.2110.05529
发表时间:
2021
期刊:
影响因子:
--
作者:
[Tuli S]
通讯作者:
Tuli S
DOI:
10.1109/cloud55607.2022.00061
发表时间:
2022-07
期刊:
2022 IEEE 15th International Conference on Cloud Computing (CLOUD)
影响因子:
--
作者:
[Damian Borowiec;Gingfung Yeung;A. Friday;Richard Harper;Peter Garraghan]
通讯作者:
Damian Borowiec;Gingfung Yeung;A. Friday;Richard Harper;Peter Garraghan
共 7 条
Pin the Tail: Understanding Straggler Manifestation in Internet-based Distributed Systems
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批准号:EP/P031617/1
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项目类别:Research Grant
-
资助金额:$12.31万
-
财政年份:2017
-
负责人:Peter Garraghan
-
依托单位:
国内基金
海外基金
Identification and quantification of primary phytoplankton functional types in the global oceans from hyperspectral ocean color remote sensing
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批准号:--
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项目类别:--
-
资助金额:160万元
-
批准年份:2022
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负责人:李忠平
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依托单位:
磁层亚暴触发过程的全球(global)MHD-Hall数值模拟
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批准号:40536030
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项目类别:重点项目
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资助金额:120.0万元
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批准年份:2005
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负责人:马志为
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依托单位: