SHF:Small:Collabroative Research: Elastic Fidelity: Trading off Computational Accuracy for Energy Efficiency

SHF:Small：协作研究：弹性保真度：以计算精度换取能源效率

• 批准号: 1217353
• 负责人: Srinivasan Parthasarathy
• 金额: $ 18.2万
• 依托单位: Ohio State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-08-01 至 2016-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1217353&HistoricalAwards=false
• 关键词: SHF; Small; Collabroative; Research; Elastic

Energy and power consumption have become a critical issue ranging from microarchitectures to large-scale data centers and supercomputers. Conservative estimates suggest that the information technology industry world-wide energy consumption is in excess of 400 TWh and growing, generating roughly the same carbon footprint as the airline industry, accounting for 2% of global emissions. At the same time, the power constraints of chips hamper their performance, and the shrinking transistor geometries and low supply voltages increase the severity of processor variations resulting in higher timing error rates. High error rates lead to a significant drop in yield and increased manufacturing costs, calling for designs that are able to withstand them. This project seeks to understand and explore the novel paradigm of elastic fidelity computing. Elastic fidelity computing capitalizes on the observation that many applications can naturally tolerate errors, and that not all of them need to run at 100% fidelity all the time. Specifically, the goal of this work is to understand the error models of various hardware components as they relate to data movement, storage, and computation, and simultaneously to understand the error resiliency of applications and re-architect them to leverage elastic fidelity. Elastic fidelity offers potentially transformative effects for science and society, by challenging conventional wisdom and taking a fresh look at the interplay of errors, output quality and energy efficiency for an important class of pervasive streaming and data-intensive applications. More specifically, elastic fidelity promises significant energy savings that can put computing on an environmentally sustainable path, by lowering the operational costs in major economic sectors, and making the manufacturing of future chips cheaper by relaxing the accuracy requirements of hardware components. The results of this research will be disseminated through publications, workshops, advanced curriculum, and releases of the developed infrastructure in the public domain. To accelerate broad societal effects, the project participants will seek to foster technology transfer by promoting collaboration and industry involvement through presentations and site visit

从微架构到大规模数据中心和超级计算机，能源和功耗已成为一个关键问题。据保守估计，信息技术行业的全球能源消耗超过400太瓦时，并在不断增长，产生的碳足迹与航空业大致相同，占全球排放量的2%。与此同时，芯片的功率限制阻碍了它们的性能，并且缩小的晶体管几何形状和低电源电压增加了处理器变化的严重性，从而导致更高的定时错误率。高错误率会导致产量显著下降并增加制造成本，因此需要能够承受这些错误的设计。 这个项目旨在理解和探索弹性保真度计算的新范式。弹性保真度计算利用了许多应用程序可以自然地容忍错误的观察结果，并且不是所有应用程序都需要始终以100%的保真度运行。具体来说，这项工作的目标是了解各种硬件组件的错误模型，因为它们与数据移动，存储和计算有关，同时了解应用程序的错误弹性并重新构建它们以利用弹性保真度。弹性保真度为科学和社会提供了潜在的变革性影响，挑战传统智慧，并重新审视一类重要的普遍流媒体和数据密集型应用程序的错误，输出质量和能源效率的相互作用。更具体地说，弹性保真度承诺显著的节能，可以通过降低主要经济部门的运营成本，使计算走上环境可持续的道路，并通过放宽硬件组件的精度要求，使未来芯片的制造成本更低。这项研究的结果将通过出版物、讲习班、高级课程和在公共领域发布已开发的基础设施来传播。为了加速产生广泛的社会影响，项目参与者将通过演示和实地考察促进合作和行业参与，