The Kelvin Living Lab: Towards Net Zero High-Performance Computing

开尔文生活实验室:迈向净零高性能计算

基本信息

  • 批准号:
    EP/Z531054/1
  • 负责人:
  • 金额:
    $ 69.03万
  • 依托单位:
  • 依托单位国家:
    英国
  • 项目类别:
    Research Grant
  • 财政年份:
    2024
  • 资助国家:
    英国
  • 起止时间:
    2024 至 无数据
  • 项目状态:
    未结题

项目摘要

The purpose of this project is to evaluate options which reduce the carbon emissions of the Kelvin-2 high-performance computing (HPC) to zero or negative. This will be achieved by improving efficiency, and implementing scheduling and complementary technologies. HPC is a large electricity consumer and has a commensurate cooling requirement which can significantly increase power consumption. Therefore, targeting the processing efficiency and waste heat offers the greatest opportunity to decarbonise. The proposed outputs focus on these options and seek to demonstrate an effective 40% improvement in energy-efficiency with the resulting guidelines made available to other Tier-2 centres. We aim to improve the sustainability of HPC through a multi-pronged approach:1. Analysing and deploying software and hardware to improve utilisation and energy-efficiency of the infrastructureIn the last two decades, various research has proposed ways to improve energy-efficiency of HPC systems, such as efficient scheduling of parallel applications, dynamic parallelism control and dynamic voltage and frequency scaling, including research by the PI and de Supinski, e.g., EP/M01147X/1, EP/L000555/1 and EP/M015742/1. However, these techniques have not transitioned from research to practise due to unknown risks on the service. Our goal is to re-evaluate and adjust such techniques on an isolated slice of the Kelvin-2 system. Additionally, we will explore alternative node architectures as different node architectures may present better energy-efficiency for specific applications. We will moreover investigate if we can leverage dynamic voltage and frequency scaling to help maintain the electrical utility grid's stability, as renewable energy sources reduce the grid's ability to counter dynamic stability problems, which limits their adoption. Based on expertise in time-synchronised instrumentation (OpenPMU), we will explore adaptation of power consumption of HPC infrastructures in real time to counter electrical grid frequency fluctuations.2. User engagement with sustainabilityIt is an open question for HPC centres how to incentivise users to execute jobs sustainably. We can however inform users on the environmental impact of their jobs, e.g., through reporting energy and carbon usage. The missing links are operational policies and scheduling algorithms that prioritise jobs with environmental impact in mind. This requires a fair charging scheme that reflects on the optimality of the time-vs-energy trade-off of executing jobs (avoiding penalising large energy-efficient jobs because of their size).3. Operations for Net zero HPCUtilising renewable sources can reduce the emissions associated with data processing significantly. By integrating HPC with other technologies which utilise the waste heat to capture or reduce the emissions of other processes they can be truly net zero. Using temperature data we will investigate various options for thermal enabled decarbonisation such as evaluation of novel direct air carbon capture (DAC) and co-location with heat consumers.We will maximise the impact of this project through knowledge sharing with other HPC facilities and stakeholders, which will be supported through collaborations with Northern Ireland HPC (https://ni-hpc.ac.uk/), the eFutures 3.0 network on electronics, and industry partners Dell Technologies, AlcesFlight and Northern Ireland Electricity Networks.
该项目的目的是评估将开尔文-2高性能计算(HPC)的碳排放减少到零或负的方案。这将通过提高效率、实施调度和互补技术来实现。高性能计算是一个大的电力消费者,并有相应的冷却要求,这可以显著增加电力消耗。因此,以加工效率和废热为目标提供了脱碳的最大机会。拟议的产出侧重于这些选择,并力求证明能源效率有效提高40%,并将由此产生的指导方针提供给其他二级中心。我们的目标是通过多管齐下的方法来提高高性能计算的可持续性:在过去的二十年中,各种研究提出了提高高性能计算系统能效的方法,例如并行应用的高效调度,动态并行控制和动态电压和频率缩放,包括PI和de Supinski的研究,例如EP/M01147X/1, EP/L000555/1和EP/M015742/1。然而,由于未知的服务风险,这些技术尚未从研究过渡到实践。我们的目标是在一个孤立的开尔文-2系统上重新评估和调整这些技术。此外,我们将探索可替代的节点架构,因为不同的节点架构可能为特定的应用程序提供更好的能源效率。此外,我们还将研究是否可以利用动态电压和频率缩放来帮助维持电网的稳定性,因为可再生能源降低了电网应对动态稳定性问题的能力,这限制了它们的采用。基于时间同步仪器(OpenPMU)的专业知识,我们将探索实时适应HPC基础设施的功耗,以对抗电网频率波动。用户对可持续性的参与对于高性能计算中心来说,如何激励用户可持续地执行工作是一个悬而未决的问题。然而,我们可以告知用户他们的工作对环境的影响,例如,通过报告能源和碳的使用情况。缺少的环节是操作策略和调度算法,这些算法优先考虑对环境的影响。这需要一个公平的收费方案,反映执行作业的时间与能量权衡的最优性(避免因其规模而惩罚大型节能作业)。利用可再生能源实现净零排放的操作可以显著减少与数据处理相关的排放。通过将HPC与其他利用废热捕获或减少其他过程排放的技术相结合,它们可以真正实现净零排放。利用温度数据,我们将研究热使能脱碳的各种选择,如评估新型直接空气碳捕获(DAC)和与热消费者共同定位。我们将通过与其他HPC设施和利益相关者的知识共享来最大化该项目的影响,这将通过与北爱尔兰HPC (https://ni-hpc.ac)的合作得到支持。uk/),电子产品eFutures 3.0网络,以及行业合作伙伴戴尔科技,AlcesFlight和北爱尔兰电力网络。

项目成果

期刊论文数量(0)
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专利数量(0)

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Hans Vandierendonck其他文献

Parallel Programming of General-Purpose Programs Using Task-Based Programming Models
使用基于任务的编程模型对通用程序进行并行编程
Towards automatic program partitioning
走向自动程序分区
  • DOI:
    10.1145/1531743.1531759
  • 发表时间:
    2009
  • 期刊:
  • 影响因子:
    0
  • 作者:
    S. Rul;Hans Vandierendonck;K. D. Bosschere
  • 通讯作者:
    K. D. Bosschere
A significance-driven programming framework for energy-constrained approximate computing
用于能量约束近似计算的显着性驱动编程框架
PGT: a prompt based generative transformer for the patent domain
PGT:专利领域基于提示的生成变压器
  • DOI:
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Dimitrios Christofidellis;Antonio Berrios Torres;A. Dave;M. Roveri;Kristin Schmidt;Sarath Swaminathan;Hans Vandierendonck;D. Zubarev;Matteo Manica
  • 通讯作者:
    Matteo Manica
Language and Runtime System: Requirements
语言和运行时系统:要求
  • DOI:
  • 发表时间:
    2016
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Hans Vandierendonck
  • 通讯作者:
    Hans Vandierendonck

Hans Vandierendonck的其他文献

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{{ truncateString('Hans Vandierendonck', 18)}}的其他基金

Relaxed Semantics Across the Data Analytics Stack
整个数据分析堆栈的宽松语义
  • 批准号:
    EP/X029174/1
  • 财政年份:
    2023
  • 资助金额:
    $ 69.03万
  • 项目类别:
    Research Grant
Asynchronous Scientific Continuous Computations Exploiting Disaggregation (ASCCED)
利用分解的异步科学连续计算 (ASCCED)
  • 批准号:
    EP/X01794X/1
  • 财政年份:
    2023
  • 资助金额:
    $ 69.03万
  • 项目类别:
    Research Grant
DiPET: Distributed Stream Processing on Fog and Edge Systems via Transprecise Computing
DiPET:通过 Transprecise 计算在雾和边缘系统上进行分布式流处理
  • 批准号:
    EP/T022345/1
  • 财政年份:
    2020
  • 资助金额:
    $ 69.03万
  • 项目类别:
    Research Grant
Hybrid Static/Dynamic Scheduling for Task Dataflow Parallel Programs
任务数据流并行程序的混合静态/动态调度
  • 批准号:
    EP/L027402/1
  • 财政年份:
    2014
  • 资助金额:
    $ 69.03万
  • 项目类别:
    Research Grant

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ELABORATOR: THE EUROPEAN LIVING LAB ON DESIGNING SUSTAINABLE URBAN MOBILITY TOWARDS CLIMATE NEUTRAL CITIES
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