SHF: Small: Exploring and Enhancing Capabilities of Emerging Hybrid/Convertible Solid-State Drives

SHF：小型：探索和增强新兴混合/可转换固态硬盘的功能

• 批准号: 2208317
• 负责人: Bingzhe Li
• 金额: $ 58.39万
• 依托单位: Oklahoma State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-01 至 2024-02-29
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2208317&HistoricalAwards=false
• 关键词: SHF; Small; Exploring; Enhancing; Capabilities

The world’s digital data has increased immensely with the tremendous development of technology. By 2025, the total amount of digital data will reach 175 Zettabytes. It becomes a critical and increasing challenge to manage this huge amount of data. The demand for high-performance and large-capacity storage systems is rapidly increased to cover this big data environment; still, it is a critical challenge to satisfy both high performance and large capacity in a single storage device with a low cost. To achieve this goal, an emerging storage device named hybrid/convertible Solid-State Drive (SSD) provides unique properties compared to traditional storage devices and can satisfy the requirement in such an environment. However, the emerging device has not been fully investigated and cannot reach its full potential. This project aims to fully explore the abilities of hybrid/convertible SSDs. The completion of this project will initialize a paradigm shift in today’s storage systems to handle massive amounts of data more efficiently with high capacity and high-speed access. The research will also impact the burgeoning storage market, implement outreach to K-12, undergraduate, and minority students, and incorporate research results into courses, thus enhancing the student experience.This project intends to develop and enhance the capabilities of the emerging hybrid/convertible SSD through the following three thrusts: 1) A novel management scheme for hybrid/convertible SSDs is developed to balance the performance and capacity of the storage system. In particular, this thrust focuses on device management and advanced the zone named space technique. 2) A high-performance Redundant Array of Inexpensive Disks system is built inside hybrid/convertible SSDs to efficiently protect data stored in these drives while retaining the same reliability. 3) An efficient key-value store system in the emerging storage devices is investigated to solve big data issues. In particular, this thrust develops a high-performance log-structured merge tree-based key-value system based on the unique properties of the emerging storage device.This project is jointly funded by the SHF program cluster of the CISE/CCF directorate and the Established Program to Stimulate Competitive Research (EPSCoR).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.

随着技术的飞速发展，世界上的数字数据量也在急剧增加。到2025年，数字数据总量将达到175泽字节。管理如此庞大的数据量成为一项日益严峻的挑战。为适应大数据环境，对高性能、大容量存储系统的需求迅速增加，但如何在单个存储设备中以低成本同时满足高性能和大容量的要求，仍然是一个严峻的挑战。为了实现这一目标，一种名为混合/可转换固态驱动器（SSD）的新兴存储设备提供了与传统存储设备相比独特的属性，并且可以满足这样的环境中的需求。然而，这一新兴设备尚未得到充分研究，无法充分发挥其潜力。该项目旨在充分探索混合/可转换SSD的能力。该项目的完成将启动当今存储系统的范式转变，以更有效地处理大量数据，并提供高容量和高速访问。该研究还将影响蓬勃发展的存储市场，对K-12，本科生和少数民族学生进行宣传，并将研究成果纳入课程，从而增强学生体验。该项目旨在通过以下三个方面开发和增强新兴混合/可转换SSD的功能：1）提出了一种新的混合/可转换固态硬盘管理方案，以平衡存储系统的性能和容量。特别是，这个推力集中在设备管理和先进的区域命名空间技术。2)混合/可转换固态硬盘内置了高性能的廉价冗余阵列系统，可有效保护存储在这些驱动器中的数据，同时保持相同的可靠性。3)为了解决大数据问题，研究了新兴存储设备中高效的键值存储系统。特别是，该项目是由CISE/CCF理事会的SHF项目群和刺激竞争研究的既定计划（EPSCoR）共同资助的该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查进行评估，被认为值得支持的搜索.

项目成果

Work-in-Progress: ExpCache: Online-Learning based Cache Replacement Policy for Non-Volatile Memory

正在进行中的工作：ExpCache：基于在线学习的非易失性内存缓存替换策略

• DOI: 10.1109/cases55004.2022.00010
• 发表时间: 2022
• 期刊: and Synthesis for Embedded Systems
• 作者: Yang, Jinfeng;Li, Bingzhe;Yuan, Jianjun;Shen, Zhaoyan;Du, David;Lilja, David
• 通讯作者: Lilja, David

Machine Learning-based Adaptive Migration Algorithm for Hybrid Storage Systems

• DOI: 10.1109/nas55553.2022.9925545
• 发表时间: 2022-10
• 期刊: 2022 IEEE International Conference on Networking, Architecture and Storage (NAS)
• 作者: Milan M. Shetti;Bingzhe Li;D. Du

HL-DNA: A Hybrid Lossy/Lossless Encoding Scheme to Enhance DNA Storage Density and Robustness for Images

HL-DNA：一种增强图像 DNA 存储密度和鲁棒性的有损/无损混合编码方案

• DOI: 10.1109/iccd56317.2022.00071
• 发表时间: 2022
• 期刊: IEEE International Conference on Computer Design
• 作者: Li, Yi;Du, David H.C.;Ou, Li;Li, Bingzhe
• 通讯作者: Li, Bingzhe