Collaborative Research: CNS Core: Medium: Movement of Computation and Data in Splitkernel-disaggregated, Data-intensive Systems

合作研究：CNS 核心：媒介：Splitkernel 分解的数据密集型系统中的计算和数据移动

• 批准号: 2406598
• 负责人: Ang Chen
• 金额: $ 30万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 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 2024-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2406598&HistoricalAwards=false
• 关键词: Collaborative; Research; CNS; Core; Medium

Resource disaggregation promises to change the way in which we design and operate cloud infrastructure. But despite its positive impact on the operation and cost-efficiency of data centers, disaggregation comes with overheads that arise from introducing a PCIe and network round trip for each access to remote memory, storage, or accelerators -- overheads that are particularly pronounced for data-intensive applications. The core research question that this proposal will answer is what the advent of disaggregation implies for the decades of architectural decisions made by the designers of data-intensive systems, and likewise, what OS-level primitives are required to adapt these systems to a disaggregated setting. To that end, this work proposes a co-design of disaggregated operating systems and middleware for data-intensive systems that achieves both high performance and ease of use, Data-intensive systems like the ones targeted by this work power much of today’s world, providing analytics for everything from business informatics to Internet search and healthcare. The proposed work will assist data center operators in transitioning their infrastructure to support resource disaggregation while minimizing performance overheads to applications written in common frameworks.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.

资源分解有望改变我们设计和操作云基础架构的方式。但是，尽管它对数据中心的运行和成本效率的积极影响，但分解伴随着由远程内存，存储或加速器引入PCIE和网络往返引起的间接费用 - 对于数据密集型应用程序特别明显。该提案将回答的核心研究问题是，分类的出现意味着在数十年的建筑决策中，由数据密集型系统的设计师做出的几十年，并且同样，OS级别的原始词需要哪些OS级别的原始系统来使这些系统适应分离的设置。为此，这项工作提出了一个分开的操作系统和中间件共同设计的数据密集型系统，这些系统既可以实现高性能和易用性，诸如当今世界上大部分工作能力的数据密集型系统，从而为从业务信息到互联网搜索和互联网搜索和医疗保健提供了分析。拟议的工作将协助数据中心运营商过渡其基础架构以支持资源分解，同时最大程度地限制对公共框架中编写的应用程序的绩效间接费用。该奖项反映了NSF的法定任务，并被认为是通过基金会的知识分子优点和更广泛的审查标准通过评估来通过评估来支持的。