Collaborative Research: CISE: Large: Systems Support for Run-Anywhere Serverless

协作研究：CISE：大型：对 Run-Anywhere Serverless 的系统支持

• 批准号: 2321725
• 负责人: Shuai Mu
• 金额: $ 83.32万
• 依托单位: SUNY at Stony Brook
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-10-01 至 2028-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2321725&HistoricalAwards=false
• 关键词: Collaborative; Research; CISE; Large; Systems

Computing resources are more abundant and more distributed than ever before. In principle, this abundance of compute and storage should allow applications to run faster, cheaper, and more energy efficiently. Yet applications that do so are few and far between, and usually belong to one of the very few large tech organizations. This project aims to democratize access to the full space of computing resources by enabling, and then optimizing, correct and safe execution of application logic anywhere: across client devices, edge computing locations, and multiple clouds. To realize the project’s execute-anywhere vision it will be necessary to develop a new co-design for four layers of system support: 1) a runtime that can execute applications anywhere; 2) an abundance of caches that enable seamless access to data anywhere; 3) a data store that collaborates with caches to ensure application consistency and data durability; and 4) a scheduler that integrates information from the other layers to decide where to run computations and move data in order optimize performance, availability, cost, and energy.The development of these co-designed layers will leverage the diverse expertise of the six investigators in close collaboration. Its development has the potential to improve the online applications that are an integral part of people’s lives. The project should make automatic optimization of an application’s latency, cost, bandwidth usage, and energy efficiency accessible to many applications, even those developed by a single person. The optimization of an application’s latency will improve the experience of all users with an especially large effect on users in rural communities and other locations with poor Internet connectivity. Further, it has the potential to make the full use and optimization of compute and data resources ubiquitous and available to all. In addition, it will advance discovery and broaden participation by involving undergraduates from the investigators’ universities and especially institutions that serve under-represented groups in research experiences, training graduate students, and broadening undergraduate participation in Computer Science.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.

计算资源比以往任何时候都更加丰富和分散。原则上，这种丰富的计算和存储应该允许应用程序运行得更快、更便宜、更节能。然而，这样做的应用程序很少，而且通常属于极少数的大型技术组织之一。该项目旨在通过在任何地方（跨客户端设备、边缘计算位置和多云）启用和优化应用程序逻辑的正确和安全执行，实现对计算资源全部空间的民主化访问。为了实现项目的随处执行愿景，有必要为四层系统支持开发一个新的协同设计：1)可以在任何地方执行应用程序的运行时；2)丰富的缓存，可以在任何地方无缝访问数据；3)与缓存协作的数据存储，以确保应用程序的一致性和数据的持久性；4)一个调度程序，它集成了来自其他层的信息，以决定在哪里运行计算和移动数据，从而优化性能、可用性、成本和能源。这些共同设计的层的发展将利用六名调查员在密切合作的不同专业知识。它的发展有可能改善人们生活中不可或缺的在线应用程序。项目应该自动优化应用程序的延迟、成本、带宽使用和能源效率，这些都可以被许多应用程序访问，即使是那些由一个人开发的应用程序。应用程序延迟的优化将改善所有用户的体验，对农村社区和其他互联网连接差的地区的用户产生特别大的影响。此外，它有潜力充分利用和优化无处不在的计算和数据资源，并为所有人提供。此外，它将促进发现和扩大参与，包括来自研究人员所在大学的本科生，特别是那些在研究经验中服务于代表性不足群体的机构，培训研究生，扩大计算机科学的本科生参与。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。