CCF Core: Small: Hardware/Software Co-Design for Sustainability at the Edge

CCF 核心：小型：硬件/软件协同设计，实现边缘的可持续性

• 批准号: 2233808
• 负责人: Hai Li
• 金额: $ 60万
• 依托单位: Duke University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-11-01 至 2025-10-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2233808&HistoricalAwards=false
• 关键词: CCF; Core; Small; Hardware; Software

Due to the wide proliferation of cloud and now edge servers, the development of sustainable acceleration methods for edge and cloud computing and artificial intelligence (AI) acceleration is beneficial to society broadly and the computer science community, in particular. Reducing carbon and methane emissions is important to reaching environmental goals for reducing warming for which targets of 2030 and 2050 have been set. This project tackles the broader implications of the growing popularity of edge and cloud computing for executing AI to establish a sustainable computing system design methodology beyond pure energy efficiency. Unlike solely energy-efficient designs that focus on reducing power consumption and carbon emissions as a by-product, this project will build a hardware/software co-design framework to generate the optimal hardware and algorithm designs that meet specific constraints of functionality, performance, sustainability, and other system requirements. The framework will guide future sustainable hardware design. Towards this goal, the proposed framework engages holistic co-design efforts across four levels - modeling, algorithm, scheduling, and hardware.By introducing new synergies between computing paradigms and emerging AI applications, the outcomes of this research will benefit the entire AI industry, from hardware development to algorithm design and the applications for the end-users. The proposed co-design framework will be the first research in the community to build holistically sustainable AI systems which are recently recognized as emerging in importance. The success of this project will pave the road for future sustainable computing system design. The educational efforts aim at cultivating students' interests in the study of sustainable computing, contemporary computer architecture, and artificial intelligence. The existing curricula of computer organization, algorithms, and computing systems will be enhanced by the interdisciplinary research topics on sustainable computing, edge computing, and machine learning, as well as the hands-on experiences in building the simulation prototypes. Special attention will be given to recruiting underrepresented groups and enriching studentsí study experiences through new education forums.This project is funded by funds allocated to Design for Sustainable Computing (NSF 22-060)This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

由于云和现在的边缘服务器的广泛扩散，用于边缘和云计算和人工智能（AI）加速的可持续加速方法的开发对社会尤其是计算机科学界有益。减少碳和甲烷排放对于达到减少2030年和2050年目标的变暖的环境目标很重要。该项目解决了边缘和云计算日益普及的更广泛的含义，以执行AI，以建立超出纯能效率的可持续计算系统设计方法。与仅仅用于减少功耗和碳排放作为副产品的唯一节能设计不同，该项目将建立硬件/软件共同设计框架，以生成最佳的硬件和算法设计，以符合特定的功能，性能，可持续性和其他系统要求。该框架将指导未来的可持续硬件设计。 Towards this goal, the proposed framework engages holistic co-design efforts across four levels - modeling, algorithm, scheduling, and hardware.By introducing new synergies between computing paradigms and emerging AI applications, the outcomes of this research will benefit the entire AI industry, from hardware development to algorithm design and the applications for the end-users.拟议的共同设计框架将是社区中首次建立整体可持续的AI系统的研究，这些系统最近被认为是重要的。该项目的成功将为未来的可持续计算系统设计铺平道路。教育工作旨在培养学生对可持续计算，当代计算机架构和人工智能的研究的兴趣。有关可持续计算，边缘计算和机器学习的跨学科研究主题以及构建模拟原型的动手经验，将增强计算机组织，算法和计算系统的现有课程。将特别关注招募人数不足的小组并通过新的教育论坛丰富学生的学习经验。该项目由分配给可持续计算设计设计的资金（NSF 22-060）资助，该奖项反映了NSF的法定任务，并通过该基金会的知识优点和广泛的影响来评估NSF的法定任务。