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

由于云和边缘服务器的广泛普及，边缘和云计算以及人工智能（AI）加速的可持续加速方法的开发对社会广泛有益，特别是计算机科学界。减少碳和甲烷排放对于实现减少变暖的环境目标至关重要，这些目标已设定为2030年和2050年。该项目解决了边缘和云计算日益普及的广泛影响，以执行AI，建立超越纯粹能源效率的可持续计算系统设计方法。与专注于降低功耗和碳排放的节能设计不同，该项目将构建硬件/软件协同设计框架，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。该框架将指导未来的可持续硬件设计。为了实现这一目标，该框架在建模、算法、调度和硬件四个层面上进行了全面的协同设计，通过引入计算范式和新兴人工智能应用之间的新协同效应，这项研究的成果将有利于整个人工智能行业，从硬件开发到算法设计和最终用户的应用。拟议的共同设计框架将是社区中第一个建立整体可持续人工智能系统的研究，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，当代计算机体系结构和人工智能的研究兴趣。计算机组织，算法和计算系统的现有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构建模拟原型的实践经验来增强。该项目由可持续计算设计（NSF 22-060）基金资助。该奖项反映了NSF的法定使命，通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.