SHF: Small: ASF: An Adaptive Scaling Framework for High Scalability of XOR-Based RAID Systems

SHF：小型：ASF：基于 XOR 的 RAID 系统的高可扩展性的自适应扩展框架

• 批准号: 1702474
• 负责人: Xubin He
• 金额: $ 16.24万
• 依托单位: Temple University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-08-15 至 2019-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1702474&HistoricalAwards=false
• 关键词: SHF; Small; ASF; Adaptive; Scaling

Explosive growth in data volume, heterogeneity, and complexity imposes unprecedented challenges in data analysis and organization in data centers. RAID particularly XOR-based RAID plays an important role to provide both reliability and high performance storage services for these data centers. However, they suffer from problems on the scalability issue due to multi-folded factors, including: heterogeneous RAID layouts and various erasure codes, high overhead of existing scaling process to significantly downgrade the storage performance, and lack of bidirectional scaling support. The objective of this project is to address the scalability challenge for storage systems in large data centers. This project designs novel techniques to exploit XOR-based parity codes to achieve efficient scaling, develops a series of scalable XOR-based erasure codes to bridge the relations among heterogeneous RAID forms for interoperability, and integrates various erasure codes in a framework to provide a unified user interface for RAID scaling. The research will facilitate the storage systems to effectively tackle the scalability challenge in large data centers. It cohesively investigates how to utilize and integrate proper RAID scaling technologies to improve the scalability of storage systems. This project will yield fundamental contributions to research on efficient big data management in high-performance data centers, and greatly contribute to enabling high-performance computing systems to stay on track of their historic scaling, and hence benefit numerous real-life data-intensive applications such as biology, chemistry, earth science, health care, and so on.

数据量，异质性和复杂性的爆炸性增长在数据中心的数据分析和组织中构成了前所未有的挑战。 突袭特别基于XOR的RAID在为这些数据中心提供可靠性和高性能存储服务起着重要作用。但是，由于多折叠因素，它们在可伸缩性问题上遇到了问题，包括：异构突袭布局和各种擦除代码，现有缩放过程的高间接开销，以显着降低存储性能以及缺乏双向扩展支持。该项目的目的是应对大数据中心存储系统的可伸缩性挑战。该项目设计了新技术来利用基于XOR的奇偶校验代码来实现有效的缩放，开发了一系列可扩展的基于XOR的擦除代码，以弥合异质的突袭形式之间的关系以互操作性，并将各种擦除代码集成到一个框架中，以提供统一的攻击用户界面。该研究将促进存储系统有效地应对大型数据中心的可伸缩性挑战。它凝聚力研究了如何利用和整合适当的RARED缩放技术以提高存储系统的可扩展性。该项目将对高性能数据中心的有效大数据管理的研究产生基本贡献，并极大地有助于使高性能计算系统能够保持其历史性扩展，从而使许多现实的数据密集型应用，例如生物学，化学，地球科学，医疗保健等。

项目成果

A Set-Aware Key-Value Store on Shingled Magnetic Recording Drives with Dynamic Band

• DOI: 10.1109/ipdps.2018.00040
• 发表时间: 2018-05
• 期刊: 2018 IEEE International Parallel and Distributed Processing Symposium (IPDPS)
• 作者: Ting Yao;Zhi-hu Tan;Ji-guang Wan;Ping Huang;Yiwen Zhang;C. Xie;Xubin He

Chameleon: An Adaptive Wear Balancer for Flash Clusters

• DOI: 10.1109/ipdps.2018.00125
• 发表时间: 2018-05
• 期刊: 2018 IEEE International Parallel and Distributed Processing Symposium (IPDPS)
• 作者: Nannan Zhao;Ali Anwar;Yue Cheng;Mohammed Salman;Daping Li;Ji-guang Wan;C. Xie;Xubin He;Feiyi Wang;A. Butt

RAFI: Risk-Aware Failure Identification to Improve the RAS in Erasure-coded Data Centers

• 发表时间: 2018
• 作者: Juntao Fang;Shenggang Wan;Xubin He

DREAM: Data Representation Aware of Damage to Extend the Lifetime of MLC NAND Flash Memory

• 发表时间: 2018
• 作者: T. Ye;Shenggang Wan;Xubin He;Weijun Xiao;C. Xie

SELF: A High Performance and Bandwidth Efficient Approach to Exploiting Die-Stacked DRAM as Part of Memory

SELF：一种利用裸片堆叠 DRAM 作为内存一部分的高性能和带宽高效方法

• DOI: 10.1109/mascots.2017.23
• 发表时间: 2017
• 期刊: and Simulation of Computer and Telecommunication Systems (MASCOTS
• 作者: Guo, Yuhua;Liu, Qing;Xiao, Weijun;Huang, Ping;Podhorszki, Norbert;Klasky, Scott;He, Xubin
• 通讯作者: He, Xubin