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: 2107147
• 负责人: Vincent Liu
• 金额: $ 89.81万
• 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: 2021
• 资助国家: 美国
• 起止时间: 2021-06-15 至 2025-05-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2107147&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运营云基础设施的方式。但是，尽管分解对数据中心的运营和成本效益产生了积极影响，但它也带来了开销，因为每次访问远程内存、存储或加速器时都要引入PCIe和网络往返，这对于数据密集型应用来说尤其明显。 这个建议将回答的核心研究问题是，数据密集型系统的设计者所做的几十年的架构决策意味着什么，同样，需要什么样的操作系统级原语来适应这些系统的分散设置。 为此，这项工作提出了一个数据密集型系统的分散操作系统和中间件的协同设计，实现了高性能和易用性，数据密集型系统，如这项工作的目标是当今世界的大部分，提供从商业信息到互联网搜索和医疗保健的分析。 这项提议的工作将帮助数据中心运营商将其基础设施过渡到支持资源分解，同时最大限度地减少在通用框架中编写的应用程序的性能开销。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标准进行评估，被认为值得支持。

项目成果

Rolis: a software approach to efficiently replicating multi-core transactions

• DOI: 10.1145/3492321.3519561
• 发表时间: 2022-03
• 期刊: Proceedings of the Seventeenth European Conference on Computer Systems
• 作者: Weihai Shen;Ansh Khanna;Sebastian Angel;S. Sen;Shuai Mu

CompuCache: Remote Computable Caching using Spot VMs

• 发表时间: 2022
• 作者: Qizhen Zhang;P. Bernstein;Daniel S. Berger;Badrish Chandramouli;Vincent Liu;B. T. Loo

Templating Shuffles

模板随机播放

• 发表时间: 2023
• 期刊: CIDR
• 作者: Zhang, Qizhen;Wu, Jiacheng;Chen, Ang;Liu, Vincent;Loo, Boon Thau
• 通讯作者: Loo, Boon Thau

Efficient Representation of Numerical Optimization Problems for SNARKs

• 发表时间: 2021
• 期刊: IACR Cryptol. ePrint Arch.
• 作者: Sebastian Angel;A. Blumberg;Eleftherios Ioannidis;Jess Woods

Mycelium: Large-Scale Distributed Graph Queries with Differential Privacy

• DOI: 10.1145/3477132.3483585
• 发表时间: 2021-10
• 期刊: Proceedings of the ACM SIGOPS 28th Symposium on Operating Systems Principles
• 作者: Edo Roth;Karan Newatia;Ke Zhong;Sebastian Angel;Andreas Haeberlen