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，每个服务器都将少量的CPU（中央处理单元）、内存和存储紧密集成到单个主板上。然而，登纳德扩展的结束和摩尔定律的放缓导致这种以服务器为中心的架构出现了一些基本限制（例如，内存容量墙使得 CPU-内存共置变得不可持续）。因此，一种新的计算范式正在出现——一种分解架构，其中每种资源类型都构建为独立的“刀片”，并且网络结构将机架内和机架之间的资源刀片互连。计算机体系结构社区已经确定了这种分解体系结构的许多好处，包括拥有 10-100 倍更大资源容量的潜力。虽然从计算机架构的角度来看是有益的，但分解架构改变了一些曾经指导现有网络、系统和应用程序的设计和优化的假设（例如，CPU 存储托管、高 CPU 内存带宽、存储层次结构、数据局部性、故障模型、 ETC。）。因此，要充分利用分解架构的优势，就需要重新架构遗留系统和网络。该项目旨在为分散的数据中心共同设计网络、存储和计算结构。在网络方面，该项目将设计超低延迟的机架内和机架间结构，包括包含高效拥塞控制的新网络软件堆栈、容错和调度机制。网络和存储结构的协同设计将带来用于分解存储的新的（分布式）内存和存储管理堆栈，以及一个资源管理器，该资源管理器可以跨共享分解存储和网络结构的多个应用程序提供基本的隔离、共享和弹性保证。最后，该项目将构建新的分布式编程框架并重新架构现有应用程序，以便在分解架构上高效、正确地运行。该项目将为围绕这一新兴计算范式的一些最困难和最重要的技术问题提供解决方案，并将主要通过教育和外展活动以及技术转让产生广泛的社区影响。该项目产生的软件工件将公开发布，以确保可重复性并促进后续研究。该项目还包含大量教育内容，包括新课程和公开发布教材。最后，该项目将通过研究生和博士后学者的指导、年度研讨会和行业务虚会，为建立跨学科研究社区提供必要的推动力，以弥合行业发展和学术研究之间的差距。

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