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: 2212192
• 负责人: Ming Liu
• 金额: $ 40万
• 依托单位: University of Wisconsin-Madison
• 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=2212192&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.

分解存储已经成为一种日益流行的存储基础设施，在公共云和企业中获得了极大的关注。目前的存储分解缺乏多租户支持和对合并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程序的控制。这将导致严重的干扰、次优性能和低成本效率。这个项目的目标是使分解存储可编程。可编程分解存储（PDS）可以提供对分解存储访问的端到端控制。它利用最新的存储和网络创新，使整个分解存储数据路径可编程。这允许PDS适应工作负载需求和后端基础设施条件。PDS旨在提供可预测的高性能，支持灵活的存储访问，并提供有效的隔离和公平性保证。为了使PDS切实可行，本文提出了几个研究问题，例如如何构建弹性且向后兼容的客户端虚拟磁盘；如何设计控制面和数据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基板上执行控制平面策略和公平的资源分配；如何跨不同设备调度数据平面操作符；以及如何实现可预测的存储访问延迟。全球数十亿人每天都在使用存储基础设施。通过将分解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、成本效率、可伸缩性和多租户。有足够的机会让本科生参与进来，并将研究带入课堂。对于更广泛的用户社区和整个社会，该项目努力公开发布硬件和软件原型，从而实现丰富的存储应用程序集。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。

项目成果

LEED: A Low-Power, Fast Persistent Key-Value Store on SmartNIC JBOFs

• DOI: 10.1145/3603269.3604880
• 发表时间: 2023-09
• 期刊: Proceedings of the ACM SIGCOMM 2023 Conference
• 作者: Zerui Guo;Chenxingyu Zhao;Yunru Bai

eZNS: An Elastic Zoned Namespace for Commodity ZNS SSDs

• 发表时间: 2023
• 作者: Jaehong Min;Chenxingyu Zhao;Ming Liu;Arvind Krishnamurthy