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Collaborative Research: CNS Core: Medium: Programmable Disaggregated Storage

Collaborative Research: CNS Core: Medium: Programmable Disaggregated Storage
合作研究:CNS 核心:媒介:可编程分类存储
批准号:
2212193
负责人:
Arvind Krishnamurthy
金额:
$80.0万
依托单位:
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2022
资助国家:
美国
项目状态:
未结题
起止时间:
2022-10-01 至 2026-09-30

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中文摘要
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英文摘要
Disaggregated storage has become an increasingly popular storage infrastructure, gaining significant attention in public clouds and in the enterprise. Today’s storage disaggregation lacks multi-tenancy support and dynamic adaptation to consolidated workloads. Further, it requires costly coordination and provides no application-specific control. This leads to severe interference, suboptimal performance, and cost inefficiencies. This project’s goal is to make disaggregated storage programmable. Programmable disaggregated storage (PDS) can provide end-to-end control over disaggregated storage access. It leverages recent storage and network innovations to make the entire disaggregated storage data path programmable. This allows PDS to adapt to the workload requirements and backend infrastructure conditions. PDS aims to provide predictably high performance, enable flexible storage access, and offer efficient isolation and fairness guarantees. Several research questions are addressed to make PDS practical, such as how to build an elastic and backward compatible client-side virtual disk; how to design control-plane and data-plane programming frameworks to express application intents and define flexible computations; how to enforce control-plane policies and perform fair resource allocations across heterogeneous I/O substrates; how to schedule data-plane operators across different devices; and how to achieve predictable storage access latencies. Storage infrastructure is used by billions of people around the globe on a daily basis. By tightly integrating disaggregated storage with emerging programmable entities, this project has the potential to substantially improve the performance, cost efficiency, scalability, and multi-tenancy of storage applications. There are ample opportunities for involving undergraduate students and bringing research into the classroom. For the broader community of users and the society at large, this project endeavors to publicly release hardware and software prototypes, enabling a rich set of storage applications.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.
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