Collaborative Research: CNS Core: Medium: Programmable Disaggregated Storage

合作研究：CNS 核心：媒介：可编程分类存储

• 批准号: 2212193
• 负责人: Arvind Krishnamurthy
• 金额: $ 80万
• 依托单位: University of Washington
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-10-01 至 2026-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2212193&HistoricalAwards=false
• 关键词: Collaborative; Research; CNS; Core; Medium

Disaggregated storage has become an increasingly popular storage infrastructure, gaining significant attention in public clouds and in the enterprise. Today’s storage disaggregation lacks multi-tenancy support and dynamic adaptation to consolidated workloads. Further, it requires costly coordination and provides no application-specific control. This leads to severe interference, suboptimal performance, and cost inefficiencies. This project’s goal is to make disaggregated storage programmable. Programmable disaggregated storage (PDS) can provide end-to-end control over disaggregated storage access. It leverages recent storage and network innovations to make the entire disaggregated storage data path programmable. This allows PDS to adapt to the workload requirements and backend infrastructure conditions. PDS aims to provide predictably high performance, enable flexible storage access, and offer efficient isolation and fairness guarantees. Several research questions are addressed to make PDS practical, such as how to build an elastic and backward compatible client-side virtual disk; how to design control-plane and data-plane programming frameworks to express application intents and define flexible computations; how to enforce control-plane policies and perform fair resource allocations across heterogeneous I/O substrates; how to schedule data-plane operators across different devices; and how to achieve predictable storage access latencies. Storage infrastructure is used by billions of people around the globe on a daily basis. By tightly integrating disaggregated storage with emerging programmable entities, this project has the potential to substantially improve the performance, cost efficiency, scalability, and multi-tenancy of storage applications. There are ample opportunities for involving undergraduate students and bringing research into the classroom. For the broader community of users and the society at large, this project endeavors to publicly release hardware and software prototypes, enabling a rich set of storage applications.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.

分散存储已成为越来越受欢迎的存储基础设施，在公共云和企业中获得了极大的关注。当今的存储分解缺乏多租户支持和对整合工作负载的动态适应。此外，它需要昂贵的协调，并且不提供特定于应用的控制。这导致严重的干扰、次优性能和成本效率低下。该项目的目标是使分散存储可编程。可编程分散存储（PDS）可以提供对分散存储访问的端到端控制。它利用最新的存储和网络创新，使整个分散存储数据路径可编程。这允许PDS适应工作负载要求和后端基础设施条件。PDS旨在提供可预测的高性能，实现灵活的存储访问，并提供有效的隔离和公平性保证。为使PDS实用化，提出了几个研究问题，如如何构建一个弹性和向后兼容的客户端虚拟磁盘，如何设计控制平面和数据平面编程框架来表达应用意图和定义灵活的计算，如何在异构I/O底层上执行控制平面策略和执行公平的资源分配，如何在不同设备上调度数据平面操作，如何在不同的设备上实现数据平面操作，如何在异构I/O底层上实现数据平面操作。以及如何实现可预测的存储访问延迟。地球仪上的数十亿人每天都在使用存储基础架构。通过将分散存储与新兴的可编程实体紧密集成，该项目有可能大幅提高存储应用程序的性能、成本效益、可扩展性和多租户。有足够的机会让本科生参与并将研究带入课堂。该项目致力于向广大用户和社会公开发布硬件和软件原型，从而实现丰富的存储应用程序。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评审标准进行评估，被认为值得支持。