Automated holistic efficiency for next generation data centres

数据中心(DC)提供支撑现代经济的关键基础设施；它们拥有现代生活所依赖的软件和数据。这些设施使用大量电力；从几千瓦到数百兆瓦，其中大部分是由传统的碳生产发电站产生的。尽管绿色能源供应的趋势越来越大，但从整体上讲，提高直流效率的需要对英国工业至关重要。到目前为止，大部分工作都集中在物理系统上。这个项目将从根本上改进当前的方法，通过极大地扩展所使用的建模和模拟服务器的方法。我们将通过创建一个考虑软件、硬件、设施和人类行为的整体框架来引入DC效率的阶梯变化，并将其用于培训高级智能代理，以在不影响性能的情况下实现大幅节能。DC的数量和规模正在快速增长，因为它们是物联网、5G、人工智能等新兴技术的骨干。目前DC的能源使用量约占全球消耗的3%；但到2030年可能高达10%。为了在这个不断增长的领域保持竞争力，至关重要的是，英国DC必须控制能源使用，以便与绿色电力廉价的地区竞争。DC效率由多个因素驱动：减少碳排放、降低成本，以及在电力受限的情况下提高能力。Edgetic是一家初创阶段的科技公司，旨在通过软件服务提高DC效率。DC效率的标准衡量标准是PUE(电源利用效率)：整个设施消耗的电力与IT设备消耗的电力的比率。PUE为1是理论上的最小值，意味着能量仅由IT硬件使用；效率随着PUE的增加而恶化。关注PUE，该行业一直将改善孤立的外围系统放在首位，而不是降低整体能耗。随着外围、相互依赖的系统达到个人优化的极限，PUE的改善正在放缓；提高IT效率是下一个研究前沿。Edgetic使用IT行为的预测数学模型为DC做出优化决策。但是，我们当前的方法需要对DC中的每种工作负载和服务器类型进行单独建模。目前，这是可以接受的，但为了大幅增长业务，提高建模过程的可伸缩性至关重要，因为每个DC都是唯一的。硬件和工作负载的每一次额外变化都会大大增加所需的评估。这个项目的目的是开发新的方法来加快服务器评估，估计新硬件组合的行为，并预测不同工作负载的性能。独一无二的是，这些方法将被用于现有的优化技术，并为新的人工智能工具提供基础，以使用整体行为模拟来优化DC操作。这种全面的方法将允许根据所需的特点，使用针对个别DC量身定做的新运营战略，实现DC的自动优化。这样做的好处是从根本上提高了数据中心的效率，进而减少了DC对气候的影响，并保持了英国在数据中心行业的领先地位。

Data centres (DCs) provide critical infrastructure underpinning modern economies; they hold the software and data that modern life depends on. These facilities use massive amounts of power; from a few kilowatts up to hundreds of megawatts, much of it being generated in traditional carbon producing power stations. Although there is an increasing trend towards green energy supply, the need to improve DC efficiency as a whole is critical to UK industry. To date, most of the effort has focussed on physical systems. This project will radically improve current approaches by greatly expanding on the methodologies used model and simulate servers. We will introduce a step-change to DC efficiency by creating a holistic framework that accounts for software, hardware, facility, and human behaviours and use it in training advanced intelligent agents to achieve substantial energy reductions without affecting performance.The number and size of DCs is growing rapidly as they are the backbone of emerging technologies like IoT, 5G, AI, etc. Current DC energy usage is approximately 3% of global consumption; but could reach as high as 10% by 2030. To remain competitive in this growing sector it is vital that UK DCs keep their energy usage in check to compete with regions where green power is cheap. DC efficiency is driven by a number of factors: reducing carbon emissions, reducing costs and increasing capability where power is restricted. Edgetic is an early stage technology company aiming to improve DC efficiency via software services.The standard measure of DC efficiency is PUE (Power Utilisation Effectiveness): a ratio of the power consumed by the whole facility to that consumed by the IT equipment. A PUE of 1 is a theoretical minimum implying energy is only used by the IT hardware; efficiency worsens as PUE increases. Focusing on PUE, the industry has prioritised improving isolated peripheral systems rather than reducing overall energy consumption. PUE improvements are slowing as peripheral, co-dependant systems reach the limits of individual optimisation; improving IT efficiency is the next research frontier. Edgetic uses predictive mathematical modes of IT behaviour to make optimising decisions for the DC. However, our current approach requires individually modelling each workload and type of server in a DC. At present this is acceptable, but in order to substantially grow the business it is vital to improve the scalability of the modelling process since every DC is unique. Every additional variation in hardware and workload substantially increases the required evaluation. The aim of this project is to develop novel methods to speed up server evaluation, estimate behaviours of new hardware combinations and predict performance for different workloads. Uniquely, these methods will be employed in both the existing optimisation technology and provide the foundation for new artificial intelligence tools to optimise DC operation using holistic behaviour simulations. The holistic approach will allow automatic DC optimisation using new operating strategies tailored to individual DCs based on their required characteristics. This has the benefit of radically improving data centre efficiency which in turn reduces the climate impact of DCs and maintains the UK's leading position in the data centre industry.