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CNS Core: Small: Optimizing Distributed Transactions on Emerging Hardware

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:
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
项目状态:
已结题
起止时间:
2020-10-01 至 2024-09-30

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中文摘要
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英文摘要
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.
期刊论文(2)
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会议论文
DOI: 10.1145/3477132.3483555
发表时间: 2021-10
期刊: Proceedings of the ACM SIGOPS 28th Symposium on Operating Systems Principles
影响因子: --
作者: [Henry N. Schuh;Weihao Liang;Ming G. Liu;J. Nelson;A. Krishnamurthy]
通讯作者: Henry N. Schuh;Weihao Liang;Ming G. Liu;J. Nelson;A. Krishnamurthy
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
影响因子: --
作者: [Min, Jaehong, Liu, Ming, Chugh, Tapan, Zhao, Chenxingyu, Wei, Andrew, Doh, In Hwan, Krishnamurthy, Arvind]
通讯作者: Krishnamurthy, Arvind
Collaborative Research: CNS Core: Large: Runtime Programmable Networks
  • 批准号:
    2213387
  • 项目类别:
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  • 资助金额:
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  • 财政年份:
    2022
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  • 依托单位:
Collaborative Research: CNS Core: Medium: Programmable Disaggregated Storage
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  • 批准号:
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  • 负责人:
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