Carbon Intelligent Computing for Hyper-scale Data-centres: Matching Computing and Networking with Global Economy Needs

超大规模数据中心的碳智能计算：将计算和网络与全球经济需求相匹配

• 批准号: RGPIN-2021-04013
• 负责人: Kaur, Kuljeet
• 金额: $ 1.98万
• 依托单位: École de technologie supérieure
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=754010
• 关键词: Carbon; Intelligent; Computing; Hyper; scale

Information and Communication Technology (ICT) has significantly changed the global business landscape in the last couple of years and has made it virtually accessible anywhere and anytime. Much of this credit can be attributed to the inception of the Cloud Computing platform that provides virtualised, distributed, and powerful computing infrastructure to cater to the ever-growing economy's needs. The pillars of this powerful platform rest on gigantic industrial facilities called HyperScale Data-centres (DCs), which are characteristic of their colossal setup space, seamless computing, and more than 100 MWs of electricity requirements. However, these DCs consume almost 200 TWh of energy every year to support different business needs, which leads to 0.3% carbon emissions worldwide. Various reports indicate that this trend will sharply rise soon. For instance, by the time a child born today reaches her teens, the energy consumption of these cloud DCs will escalate to almost 20% globally. Furthermore, the growing dependence of the ICT industry on electricity has also changed the way the energy is being produced and used worldwide. During the last two decades, many tech giants have made serious efforts for reduced energy consumption and have adopted clean energy initiatives. Google, one of the biggest Internet and Cloud giants that is carbon neutral since 2007, has introduced one of the latest trends in this direction called "carbon intelligent computing". It supports the notion to shift the computational and network-intensive tasks of the cloud DCs to the periods of high green energy availability in contrast to storing the off-peak power and using it during the peak hours. However, this iconic shift towards 24/7 utilisation of carbon-free energy raises an important research question, i.e., how to match the variable renewable energy availability with the variable digital needs for data processing, storage, and transmission? Another important research challenge is how to shift the DC load in both time and space to meet higher sustainability goals without jeopardising DC's performance. Therefore, in my discovery research program, I will attempt to analyse, elaborate, and address the critical challenges related to the adoption of carbon intelligent computing across the globally distributed HyperScale DCs, and designing optimal scheduling and distribution algorithms for the incoming workloads and traffic across these HyperScale DCs. Thus, the overall idea is to match the computing and networking needs within the HyperScale DCs to the global market in a sustainable and energy-efficient manner. The research program's overall benefits are to further the academic knowledge and industrial advances for efficient Carbon Intelligent Computing since it involves the training of many graduate students. Moreover, the research results will be disseminated using open access preprints and the transfer of intellectual property to Canadian Industries.

在过去的几年里，信息和通信技术（ICT）显著改变了全球商业格局，并使其几乎可以随时随地访问。这在很大程度上归功于云计算平台的诞生，该平台提供虚拟化、分布式和强大的计算基础设施，以满足不断增长的经济需求。这个强大的平台的支柱依赖于称为超大规模数据中心（DC）的巨大工业设施，其特点是巨大的设置空间，无缝计算和超过100兆瓦的电力需求。然而，这些DC每年消耗近200 TWh的能源来支持不同的业务需求，这导致全球碳排放量增加0.3%。各种报告表明，这一趋势很快将急剧上升。例如，当今天出生的孩子长到十几岁时，这些云DC的能源消耗将在全球范围内增加近20%。此外，信通技术行业对电力的日益依赖也改变了全世界生产和使用能源的方式。在过去的二十年里，许多科技巨头都在努力减少能源消耗，并采取了清洁能源计划。谷歌是自2007年以来碳中和的最大互联网和云计算巨头之一，它已经引入了这个方向的最新趋势之一，称为“碳智能计算”。它支持将云DC的计算和网络密集型任务转移到高绿色能源可用性时期的概念，而不是存储非高峰电力并在高峰时段使用它。然而，这种向全天候利用无碳能源的标志性转变提出了一个重要的研究问题，即，如何将可变的可再生能源供应与数据处理、存储和传输的可变数字需求相匹配？另一个重要的研究挑战是如何在时间和空间上转移DC负载，以满足更高的可持续性目标，而不会危及DC的性能。因此，在我的发现研究计划中，我将尝试分析，阐述和解决与在全球分布式HyperScale DC中采用碳智能计算相关的关键挑战，并为这些HyperScale DC中的传入工作负载和流量设计最佳调度和分发算法。因此，总体思路是以可持续和节能的方式将超大规模数据中心内的计算和网络需求与全球市场相匹配。 该研究计划的总体好处是进一步提高学术知识和工业进步，以实现高效的碳智能计算，因为它涉及到许多研究生的培训。此外，研究成果将通过开放获取预印本和向加拿大工业转让知识产权来传播。