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: 2321726
• 负责人: Vincent Liu
• 金额: $ 166.67万
• 依托单位: University of Pennsylvania
• 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=2321726&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更加分散。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、边缘计算位置和多个云）启用并优化应用程序逻辑的正确和安全执行，实现对计算资源整个空间的访问。为了实现该项目的随处执行愿景，有必要为四个系统支持层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）可以在任何地方无缝访问数据的大量缓存; 3）与缓存协作以确保应用程序一致性和数据持久性的数据存储;以及4）调度器，其集成来自其他层的信息以决定在何处运行计算和移动数据，从而优化性能、可用性、成本和能量。这些共同设计的层的开发将利用六个研究者的密切协作的不同专业知识。它的发展有可能改善作为人们生活组成部分的在线应用程序。该项目应该使应用程序的延迟，成本，带宽使用和能源效率的自动优化可用于许多应用程序，即使是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，对农村社区和互联网连接较差的其他地区的用户影响特别大。此外，它有可能充分利用和优化无处不在的计算和数据资源，并提供给所有人。此外，它还将通过让调查者所在大学的本科生，特别是为代表性不足的群体提供研究经验的机构的本科生参与，培训研究生，该奖项反映了NSF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进行评估，被认为值得支持的搜索.