NeTS: CSR: Large: Collaborative Research: Co-Design of Network, Storage and Computation Fabrics for Disaggregated Datacenters

NeTS：CSR：大型：协作研究：分解数据中心的网络、存储和计算结构的协同设计

基本信息

批准号：
1704941
负责人：
Sylvia Ratnasamy
金额：
$ 90万
依托单位：
International Computer Science Institute
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2017
资助国家：
美国
起止时间：
2017-09-15 至 2023-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1704941&HistoricalAwards=false
关键词：
NeTS CSR Large Collaborative Research

项目摘要

Traditional datacenters are built using servers, each of which tightly integrates a small amount of CPU (central processing unit), memory and storage onto a single motherboard. However, the end of Dennard's scaling and the slowdown of Moore's Law has led to surfacing of several fundamental limitations of such server-centric architectures (e.g., the memory-capacity wall making CPU-memory co-location unsustainable). Consequently, a new computing paradigm is emerging -- a disaggregated architecture, where each resource type is built as a standalone 'blade' and a network fabric interconnects the resource blades within and across racks. The computer architecture community has established a number of benefits of such disaggregated architectures, including the potential to have 10-100x larger resource capacity. While beneficial from the computer architecture perspective, disaggregated architectures alter several assumptions that once guided the design and optimization of existing networks, systems and applications (e.g., CPU-storage colocation, high CPU-memory bandwidth, storage hierarchy, data locality, failure models, etc.). Capitalizing on the benefits of disaggregated architectures will thus require re-architecting legacy systems and networks. This project aims to co-design the network, storage and compute fabrics for disaggregated datacenters.On the network front, the project will design ultra-low latency intra-rack and inter-rack fabrics including a new network software stack that incorporates efficient congestion control, failure tolerance and scheduling mechanisms. The co-design of network and storage fabrics will lead to new (distributed) memory and storage management stacks for disaggregated storage, and a resource manager that provides essential isolation, sharing and elasticity guarantees across multiple applications sharing disaggregated storage and network fabrics. Finally, the project will build new distributed programming frameworks and re-architect existing applications to efficiently and correctly operate on disaggregated architectures. This project will provide solutions to some of the most difficult and important technical questions surrounding this emerging computing paradigm and will have broad community impact primarily through educational and outreach activities, and technology transfer. Software artifacts resulting from this project will be publicly released to ensure repeatability and to foster follow up research. The project also has a substantial educational component including new courses and public release of teaching materials. Finally, the project will provide the necessary thrust to build an inter-disciplinary research community via mentoring of graduate students and postdoctoral scholars, yearly workshops and industry retreats to bridge the gap between industrial development and academic research.

传统的数据中心是使用服务器构建的，每个服务器都会紧密整合了少量的CPU（中央处理单元），内存和存储在单个主板上。但是，丹纳德（Dennard）的扩展和摩尔定律的放缓的终结导致了这种以服务器为中心的架构的几个基本限制（例如，内存容量墙，使CPU - 内存共同位置不可持续）。因此，新的计算范式正在出现 - 一种分类的体系结构，每种资源类型都是作为独立的“刀片”构建的，而网络面料将资源叶片互连在机架内和跨机架内。计算机架构社区已经建立了这种分类体系结构的许多好处，包括具有更大资源能力的潜力。虽然从计算机体系结构的角度有益，但分解体系结构改变了几个假设，这些假设曾经指导现有网络，系统和应用程序的设计和优化（例如CPU存储托管验证，高CPU - 内存带宽，存储层次结构，数据局部性，数据局部性，失败模型等）。因此，利用分解架构的好处将需要重新构造的旧系统和网络。该项目旨在共同设计分解数据中心的网络，存储和计算织物。在网络前沿，该项目将设计超低潜伏期内置内置内置和式机构面料，包括新的网络软件堆栈，其中包括有效的充电控制，失败的容忍度，容忍度和调度机制。网络和存储面料的共同设计将导致用于分类存储的新（分布式）内存和存储管理堆栈，以及提供基本隔离，共享和弹性保证的资源管理器，共享分享分类的存储和网络面料的多个应用程序。最后，该项目将构建新的分布式编程框架并重新构造现有应用程序，以有效，正确地在分类的体系结构上操作。该项目将为围绕这种新兴计算范式的一些最困难，最重要的技术问题提供解决方案，并主要通过教育和外展活动以及技术转移产生广泛的社区影响。该项目产生的软件工件将公开发布，以确保重复性并促进后续研究。该项目还拥有大量的教育组成部分，包括新课程和公开发布教材。最后，该项目将通过指导研究生和博士后学者，年度研讨会和行业务虚会，以弥合工业发展与学术研究之间的差距，从而提供必要的力量来建立跨学科研究社区。

项目成果

期刊论文数量（10）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Monotasks: Architecting for Performance Clarity in Data Analytics Frameworks

单任务：数据分析框架中性能清晰度的架构

DOI：
10.1145/3132747.3132766
发表时间：
2017
期刊：
SOSP 2017
影响因子：
0
作者：
Ousterhout, Kay;Canel, Christopher;Ratnasamy, Sylvia;Shenker, Scott
通讯作者：
Shenker, Scott

Efficient Scheduling Policies for Microsecond-Scale Tasks

微秒级任务的高效调度策略

DOI：
发表时间：
2022
期刊：
USENIX Symposium on Networked Systems Design and Implementation
影响因子：
0
作者：
Sarah McClure, Amy Ousterhout
通讯作者：
Sarah McClure, Amy Ousterhout

Datacenter congestion control: identifying what is essential and making it practical

DOI：
10.1145/3371927.3371932
发表时间：
2019-11
期刊：
Comput. Commun. Rev.
影响因子：
0
作者：
Aisha Mushtaq;R. Mittal;J. McCauley;Mohammad Alizadeh;Sylvia Ratnasamy;S. Shenker
通讯作者：
Aisha Mushtaq;R. Mittal;J. McCauley;Mohammad Alizadeh;Sylvia Ratnasamy;S. Shenker

Remote Memory Calls

DOI：
10.1145/3422604.3425923
发表时间：
2020-11
期刊：
Proceedings of the 19th ACM Workshop on Hot Topics in Networks
影响因子：
0
作者：
Emmanuel Amaro;Zhihong Luo;Amy Ousterhout;A. Krishnamurthy;Aurojit Panda;Sylvia Ratnasamy;S. Shenker
通讯作者：
Emmanuel Amaro;Zhihong Luo;Amy Ousterhout;A. Krishnamurthy;Aurojit Panda;Sylvia Ratnasamy;S. Shenker

Revisiting network support for RDMA

DOI：
10.1145/3230543.3230557
发表时间：
2018-06
期刊：
Proceedings of the 2018 Conference of the ACM Special Interest Group on Data Communication
影响因子：
0
作者：
R. Mittal;Alexander Shpiner;Aurojit Panda;E. Zahavi;A. Krishnamurthy;Sylvia Ratnasamy;S. Shenker
通讯作者：
R. Mittal;Alexander Shpiner;Aurojit Panda;E. Zahavi;A. Krishnamurthy;Sylvia Ratnasamy;S. Shenker