Energise: Refactorings and Skeletons for Energy-Aware Applications on High-Performance Embedded Systems

非功能属性，包括例如能量，对于编程嵌入式设备变得越来越重要。这些设备通常严重依赖于电池功率，并且具有在其内操作的限制性约束（或能量预算）。平板电脑、手机、无人机、医疗设备和物联网等设备在社会中变得越来越普遍，这推动了对在其上执行的应用程序中优化能源使用的迫切需求。此外，随着全球气候变化危机变得至关重要，我们的碳足迹正在以惊人的速度加速，部分原因是现代世界中计算设备的能耗增加。需要新的绿色计算技术，以便在不降低计算设备的整体性能的情况下降低计算设备的整体能耗。尽管如此，处理能源消耗通常被视为次要问题，当解决时，对于普通开发人员来说就像是一种黑艺术，开发人员通常通过随机更改源代码或应用优化来满足能源预算，希望能源消耗间接实现预算。此外，这些嵌入式设备正变得越来越并行，多核硬件现在在例如智能手机和平板电脑中很常见。然而，在语言层面处理能量属性通常需要开发人员具有高度专业化的技能，并使用低级工具和技术。即使是小型设备，如Raspberry Pi和Jetson Nano，也可以提供高性能低能耗的硬件模型，价格非常实惠。并行硬件可以为硬件制造商提供低能耗的途径，因为多核通常提高软件的性能，同时也降低其能量使用。因此，非常明确和及时地需要为典型的非专业程序员提供必要的软件开发工具和编程抽象，所述软件开发工具和编程抽象需要开发能够符合指定能量要求的应用，从而使软件开发人员更加精简、敏捷和高效;软件和运行它们的设备更加环保。迄今为止，在以下基本和本质问题上的努力很少：-为程序员提供合适的抽象，允许他们以能量为目标进行编程;以及-确定如何正确地变换码结构以使其产生最佳能量结果，或将软件定位在预-Energise项目将通过建立和补充目前对这两个领域的研究来直接解决这些基本问题。程序转换和算法框架。不寻常的是，非常重要的是，\TheProject{}从软件工程的角度解决了能源危机，采用了软件开发技术，如重构，以及使用新的能源优化框架的高级编程抽象。这是解决能源危机的关键和基本目标--因此，绿色计算--一般危机。

Non-functional properties, including, for example, energy, are becoming increasingly and critically important for programming embedded devices. These devices, typically rely heavily on battery power, and have restrictive constraints (or energy budgets) within which to operate. Devices such as tablets, phones, drones, medical devices and the Internet of Things, all of which are becoming ever more commonplace in society, are driving the pressing demand for optimisation of energy usage in applications that execute on them.Furthermore, as the global climate change crisis becomes critical, our carbon footprints are accelerating at an alarming rate, partly due to increased energy consumption from computing devices in the modern world. New green-computing techniques are needed in order to reduce the overall energy consumption of computing devices, without decreasing their overall performance. Despite this, dealing with energy consumption is often treated as a secondary concern, and when addressed, something of a black-art to the average developer, where energy budgets are often met by developers randomly changing source code or applying optimisations in the hope that energy budgets will be achieved indirectly. Furthermore, these embedded devices are becoming increasingly parallel, with multi-core hardware now commonplace in e.g. smart phones and tablets. However, dealing with energy properties at the language level usually requires developers to have highly specialised skills, and use low-level tools and techniques.Even small devices, such as the Raspberry Pi and the Jetson Nano, offer high-performance low-energy models of hardware, at very affordable prices. Parallel hardware can offer hardware manufacturers a route to low-energy consumption, as multi-core typically increases the performance of the software, while also decreasing its energy usage.Consequently, there is a very clear and timely need to provide the typical non-specialist programmer with the necessary software development tools and programming abstractions required to develop applications that are able to conform to specified energy requirements, thereby making software developers more lean, agile and productive; and software, and the devices they run on, more greener. To date, there has been very little effort on the fundamental and essential problems of:- providing suitable abstractions to the programmer, allowing them to program with energy as a target goal; and,- determining how to correctly transform code structure so that it yields optimal energy results, or targets the software to stay within a pre-defined energy budget.The Energise project will directly tackle these fundamental problems by building on and complementing current research into both program transformation and algorithmic skeletons. Unusually, and very importantly, \TheProject{} \emph{tackles the energy crisis from a software-engineering perspective}, employing software-development techniques such as refactoring, and high-level programming abstractions using novel energy-optimised skeletons.This is a critical and fundamental goal to solving the energy ---and, therefore, the green-computing--- crisis in general.