Coarse Approximator Compilation

粗略近似器编译

• 批准号: EP/P010946/1
• 负责人: Christian Fensch
• 金额: $ 12.72万
• 依托单位: Heriot-Watt University
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2017
• 资助国家: 英国
• 起止时间: 2017 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FP010946%2F1
• 关键词: Coarse; Approximator; Compilation

Computers have revolutionised our lives, from mobile phones that exceed the computational power of early supercomputers by orders of magnitudes, to today's supercomputers that help discovery of new drugs to cure serious diseases and to design more energy efficient vehicles and buildings. All this progress has been made possible by continuously increasing computational power. However, there are two threats to this trend. First, harnessing this resource has become increasingly difficult. Imagine a car that provides direct control of fuel mix, 20 gears and adjustable valve timing. This car will provide excellent performance, but requires a driver with an engineering degree to make the optimal adjustments. Second, similar to improved car fuel efficiency, there is increasing demand for improved computational energy efficiency. We cannot attach larger batteries to a mobile phone, or build a nuclear power station next to each data centre. While there are ongoing discoveries that improve efficiency, these solutions intensify the first problem: they increase the difficulty. For a solution to be truly practical it needs to be usable by non-experts! This project aims to address this in case of Approximate Computing -- a recently proposed technology aiming to increase energy efficiency by orders of magnitude.The basic insight of approximate computing is that, traditionally, computers always provide a precise and exact solution instead of a good enough solution. This obsession with precision is very energy wasteful. Imagine that you quickly look into your wallet to check how much cash you carry, you wonder if it is a 1-2 GBP, about 20 GBP or more than 50 GBP. One usually does not really care if it is 17.42 GBP or 17.43 GBP. In such a situation, it would be a waste of time to count the cash precisely. Research has shown that a vast body of problems can take advantage of this kind of imprecision.This research project aims to make approximate computing technology available to non-expert programmers. In particular, the main obstacle for widespread adaptation is that current state of the art in approximate computing burdens the application programmer with providing a suitable approximate alternative. This is comparable to burdening the driver of a car with sophisticated mechanical tasks such as changing a timing belt. The premise of this project is that it is possible to derive an approximation automatically and that this process should be integrated with the tool that every programmer already uses -- the compiler.

计算机已经彻底改变了我们的生活，从移动电话的计算能力超过早期超级计算机的数量级，到今天的超级计算机帮助发现治疗严重疾病的新药，以及设计更节能的车辆和建筑。所有这些进步都是通过不断提高计算能力而实现的。然而，这一趋势面临两个威胁。首先，利用这一资源变得越来越困难。想象一下，一辆汽车可以直接控制燃料混合，有20个档位和可调节的气门正时。这款车将提供出色的性能，但需要具有工程学位的驾驶员进行最佳调整。第二，与提高汽车燃油效率类似，对提高计算能源效率的需求也在不断增加。我们无法在移动电话上安装更大的电池，也无法在每个数据中心旁边建造核电站。虽然不断有新发现提高了效率，但这些解决方案加剧了第一个问题：它们增加了难度。对于一个真正实用的解决方案，它需要被非专业人士使用！该项目旨在解决近似计算的问题，近似计算是一种最近提出的技术，旨在提高能源效率的数量级。近似计算的基本观点是，传统上，计算机总是提供一个精确和精确的解决方案，而不是一个足够好的解决方案。这种对精确度的痴迷是非常浪费能源的。想象一下，你快速地查看你的钱包，看看你带了多少现金，你想知道它是1-2英镑，大约20英镑或超过50英镑。人们通常不在乎是17.42英镑还是17.43英镑。在这种情况下，精确地数钱是浪费时间。研究表明，大量的问题可以利用这种不精确。这个研究项目旨在使非专业程序员也能使用近似计算技术。特别是，广泛适应的主要障碍是近似计算技术的当前状态给应用程序程序员提供合适的近似替代方案带来了负担。这相当于给汽车司机增加了更换正时皮带等复杂机械任务的负担。这个项目的前提是有可能自动推导出一个近似，并且这个过程应该与每个程序员已经使用的工具——编译器集成在一起。