CNS Core: Small: Optimizing Distributed Transactions on Emerging Hardware

CNS 核心：小型：优化新兴硬件上的分布式事务

• 批准号: 2006349
• 负责人: Arvind Krishnamurthy
• 金额: $ 49.99万
• 依托单位: University of Washington
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-10-01 至 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2006349&HistoricalAwards=false
• 关键词: CNS; Core; Small; Optimizing; Distributed

Replicated transactional storage simplifies the programming and reasoning about distributed systems by providing a simple and powerful abstraction: atomic and durable execution of transactions that can survive node failures. As a consequence, many datacenter systems using transactional storage as a critical building block. This project revisits this research topic to address the opportunities and challenges posed by multiple hardware trends, e.g., large core counts on processors, programmable network interfaces, and low-latency storage. The project seeks to build distributed transactional storage systems using principles that reduce coordination and maximize network and storage performance.In particular, the project seeks to optimize distributed transactional storage by taking advantage of modern hardware features ranging from core-heavy servers to programmable network devices and tiered and highly-parallel durable storage. A key goal is to design distributed protocols that minimize cross-core coordination traffic to provide multi-core scalable solutions. Further, the project will distill remote access communication primitives, enabled by a programmable network interface, in order to optimize transaction processing. The project will also examine how to support durable data structures on heterogeneous storage that includes low-latency non-volatile memory.Datacenter applications that require support for transactional storage are used by literally billions of people around the globe daily. By improving the efficiency of distributed transactions and reducing latency/overheads, the project seeks to dramatically reduce the cost of existing datacenter-based services as well as make it much cheaper for new public services to be developed. Collaborators at hardware vendors are equal partners in this effort, providing access to new hardware technologies and assisting in project execution and technology transfer to the industry. The developed software will also enrich the distributed systems curriculum at all levels.For the broader community of users and the society at large, the project will periodically release the developed software to enable a rich set of distributed systems and high-performance datacenter applications. A public repository will be maintained until at least December 2025 at https://github.com/arvindkrish/dist-transactions/tree/master.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.

复制的交易存储通过提供简单而强大的抽象来简化有关分布式系统的编程和推理：可以在节点失败中生存的交易的原子和持久执行。结果，许多使用交易存储作为关键构建块的数据中心系统。该项目重新讨论了该研究主题，以解决多种硬件趋势所带来的机遇和挑战，例如，对处理器，可编程网络接口和低延迟存储的核心核心计数。该项目旨在使用降低协调并最大化网络和存储性能的原理来构建分布式的交易存储系统。尤其是，该项目试图通过利用现代硬件功能，从而优化分布式的交易存储，从而从可编程的网络设备到可编程网络设备以及层次以及层次以及高度合理的耐用耐用存储。一个关键目标是设计分布式协议，以最大程度地减少跨核协调流量，以提供多核可扩展的解决方案。此外，该项目将蒸馏出可编程网络接口启用的远程访问通信原始图，以优化事务处理。该项目还将研究如何支持包括低延迟性非挥发性内存的异质存储的耐用数据结构。每天数十亿人使用需要支持交易存储的DateCenter应用程序。通过提高分布式交易的效率并降低延迟/间接费用，该项目旨在大大降低现有基于数据中心服务的成本，并使得开发新的公共服务更便宜。硬件供应商的合作者在这项工作中是平等的合作伙伴，提供了对新硬件技术的访问，并协助项目执行和技术转移到该行业。开发的软件还将在各个级别上丰富分布式系统课程。对于更广泛的用户和整个社会社区，该项目将定期发布开发的软件，以启用丰富的分布式系统和高性能数据中心应用程序。至少在2025年12月在https://github.com/arvindkrish/dist-transactions/tree/master.this奖中，将维持一个公共存储库，以反映NSF的法定任务，并被认为是值得通过基金会的智力和更广泛影响的评估来通过评估来支持的。

项目成果

Gimbal: enabling multi-tenant storage disaggregation on SmartNIC JBOFs

Gimbal：在 SmartNIC JBOF 上启用多租户存储分解

• DOI: 10.1145/3452296.3472940
• 发表时间: 2021
• 期刊: SIGCOMM
• 作者: Min, Jaehong;Liu, Ming;Chugh, Tapan;Zhao, Chenxingyu;Wei, Andrew;Doh, In Hwan;Krishnamurthy, Arvind
• 通讯作者: Krishnamurthy, Arvind

Xenic: SmartNIC-Accelerated Distributed Transactions

• DOI: 10.1145/3477132.3483555
• 发表时间: 2021-10
• 期刊: Proceedings of the ACM SIGOPS 28th Symposium on Operating Systems Principles
• 作者: Henry N. Schuh;Weihao Liang;Ming G. Liu;J. Nelson;A. Krishnamurthy