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.

由于云服务器和现在的边缘服务器的广泛扩散，开发用于边缘和云计算以及人工智能(AI)加速的可持续加速方法对整个社会都是有益的，尤其是对计算机科学界。减少碳和甲烷排放对于实现减少变暖的环境目标非常重要，目前已经设定了2030年和2050年的目标。该项目解决了边缘和云计算日益流行的更广泛的影响，以执行人工智能，以建立一个可持续的计算系统设计方法，而不仅仅是纯粹的能源效率。与单纯注重降低能耗和碳排放作为副产品的节能设计不同，该项目将构建一个硬件/软件联合设计框架，以生成满足功能、性能、可持续性和其他系统要求的特定约束的最佳硬件和算法设计。该框架将指导未来可持续的硬件设计。为了实现这一目标，建议的框架在建模、算法、调度和硬件四个层面进行整体合作设计。通过引入计算范例和新兴人工智能应用之间的新协同效应，这项研究的结果将使整个人工智能行业受益，从硬件开发到算法设计和最终用户的应用。拟议的联合设计框架将是社区中建立全面可持续人工智能系统的第一项研究，该系统最近被认为是正在出现的重要性。该项目的成功将为未来可持续计算系统的设计铺平道路。这些教育努力旨在培养学生对可持续计算、当代计算机体系结构和人工智能的学习兴趣。现有的计算机组织、算法和计算系统课程将通过可持续计算、边缘计算和机器学习的跨学科研究主题以及在构建模拟原型方面的实践经验来加强。该项目由分配给可持续计算设计(NSF 22-060)的资金资助。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。