CAREER: Flashing Up Data Centers: An Orchestrated Design for Flash-based Distributed Storage Systems
职业:闪存数据中心:基于闪存的分布式存储系统的精心设计
基本信息
- 批准号:1453705
- 负责人:
- 金额:$ 54万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Continuing Grant
- 财政年份:2015
- 资助国家:美国
- 起止时间:2015-02-01 至 2021-06-30
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
A large-scale deployment of flash devices into data centers can greatly improve the overall system performance and reduce the rapidly growing management cost (e.g., power, cooling, staffing, floor space). Despite the technical merits promised, such a grand technical transition fundamentally changes the long-held system design assumption for a disk-based storage and will inevitably bring major critical challenges in a real-world practice. For example, underutilization of flash space would cause huge economic loss; premature device wear-out may result in catastrophic data corruption; unbalanced system could bring severe resource contention; unoptimized applications may not receive anticipated benefits; and many others. This project aims to address these challenges. Research will be conducted to develop a cohesive design approach to providing an orchestrated whole-system optimization. By revisiting the entire storage hierarchy, from hardware, operating system, cluster middleware, to applications, the team will redesign the device architecture to enable an organic integration of flash devices as integral elements in a huge flash storage system, create a flash-based distributed storage service with optimized resource utilization and guaranteed data reliability. Furthermore, a set of key data center applications will be enhanced to fully exploit the great potential of the flash technology. As part of this CAREER project, the team will also seek influence to the industry, contribution to curriculum, and outreach to local area under represented students.
将闪存设备大规模部署到数据中心可以极大地提高整体系统性能,并降低快速增长的管理成本(例如电力、冷却、人员配备、占地面积)。尽管具有技术优势,但如此重大的技术过渡从根本上改变了长期以来对基于磁盘的存储的系统设计假设,并将不可避免地在实际实践中带来重大的关键挑战。例如,闪存空间利用不足会造成巨大的经济损失;设备过早损坏可能会导致灾难性的数据损坏;系统不平衡可能会带来严重的资源争用;未优化的应用程序可能得不到预期的好处等等。该项目旨在应对这些挑战。将进行研究,以开发一种协调一致的设计方法,以提供协调一致的全系统优化。通过重新考察从硬件、操作系统、集群中间件到应用程序的整个存储层次结构,该团队将重新设计设备体系结构,以实现闪存设备作为庞大闪存存储系统中不可或缺的元素的有机集成,创建基于闪存的分布式存储服务,并优化资源利用率和保证数据可靠性。此外,还将增强一系列关键数据中心应用,以充分挖掘闪存技术的巨大潜力。作为这一职业项目的一部分,该团队还将寻求对行业的影响力,对课程的贡献,以及对有代表性的学生所在地区的外联。
项目成果
期刊论文数量(4)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
SlimCache: An Efficient Data Compression Scheme for Flash-based Key-value Caching
SlimCache:一种基于闪存的键值缓存的高效数据压缩方案
- DOI:10.1145/3383124
- 发表时间:2020
- 期刊:
- 影响因子:1.7
- 作者:Jia, Yichen;Shao, Zili;Chen, Feng
- 通讯作者:Chen, Feng
Kill Two Birds with One Stone: Auto-tuning RocksDB for High Bandwidth and Low Latency
- DOI:10.1109/icdcs47774.2020.00113
- 发表时间:2020-11
- 期刊:
- 影响因子:0
- 作者:Yichen Jia;Feng Chen
- 通讯作者:Yichen Jia;Feng Chen
From Flash to 3D XPoint: Performance Bottlenecks and Potentials in RocksDB with Storage Evolution
从闪存到 3D XPoint:RocksDB 存储演进的性能瓶颈和潜力
- DOI:10.1109/ispass48437.2020.00034
- 发表时间:2020
- 期刊:
- 影响因子:0
- 作者:Jia, Yichen;Chen, Feng
- 通讯作者:Chen, Feng
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Feng Chen其他文献
In situ self-transformation synthesis of g-C3N4-modified CdS heterostructure with enhanced photocatalytic activity
原位自转化合成具有增强光催化活性的g-C3N4修饰的CdS异质结构
- DOI:
10.1016/j.apsusc.2015.06.074 - 发表时间:
2015-12 - 期刊:
- 影响因子:6.7
- 作者:
Huogen Yu;Fengyun Chen;Feng Chen;Xuefei Wang - 通讯作者:
Xuefei Wang
Determination of iodine in seawater: methods and applications
海水中碘的测定:方法和应用
- DOI:
10.1016/b978-0-12-374135-6.00001-7 - 发表时间:
2009 - 期刊:
- 影响因子:0
- 作者:
Huabin Li;Xiangrong Xu;Feng Chen - 通讯作者:
Feng Chen
A preliminary investigation of metal element profiles in the serum of patients with bloodstream infections using inductively-coupled plasma mass spectrometry (ICP-MS)
使用电感耦合等离子体质谱 (ICP-MS) 对血流感染患者血清中金属元素谱进行初步研究
- DOI:
10.1016/j.cca.2018.07.013 - 发表时间:
2018 - 期刊:
- 影响因子:5
- 作者:
Suying Zhao;Shuyuan Cao;Lan Luo;Zhan Zhang;Gehui Yuan;Yanan Zhang;Yanting Yang;Weihui Guo;Li Wang;Feng Chen;Qian Wu;Lei Li - 通讯作者:
Lei Li
Development and Validation of a Novel Predictive Model for the Early Differentiation of Cardiac and Non-Cardiac Syncope
心源性晕厥和非心源性晕厥早期区分的新型预测模型的开发和验证
- DOI:
10.2147/ijgm.s454521 - 发表时间:
2024 - 期刊:
- 影响因子:2.3
- 作者:
Sijin Wu;Zhongli Chen;Yuan Gao;S. Shu;Feng Chen;Ying Wu;Yan Dai;Shu Zhang;Keping Chen - 通讯作者:
Keping Chen
Training of Multi-class Linear Classifier with BFGS Method
用BFGS方法训练多类线性分类器
- DOI:
- 发表时间:
2014 - 期刊:
- 影响因子:0
- 作者:
Xiaobo Jin;Junwei Yu;Feng Chen;Pengfei Zhu - 通讯作者:
Pengfei Zhu
Feng Chen的其他文献
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{{ truncateString('Feng Chen', 18)}}的其他基金
ATD: Sparse and Localized Graph Convolutional Networks for Anomaly Detection and Active Learning
ATD:用于异常检测和主动学习的稀疏和局部图卷积网络
- 批准号:
2220574 - 财政年份:2023
- 资助金额:
$ 54万 - 项目类别:
Standard Grant
Collaborative Research: SHF: Medium: Hardware and Software Support for Memory-Centric Computing Systems
协作研究:SHF:中:以内存为中心的计算系统的硬件和软件支持
- 批准号:
2312509 - 财政年份:2023
- 资助金额:
$ 54万 - 项目类别:
Continuing Grant
FAI: A novel paradigm for fairness-aware deep learning models on data streams
FAI:数据流上具有公平意识的深度学习模型的新颖范式
- 批准号:
2147375 - 财政年份:2022
- 资助金额:
$ 54万 - 项目类别:
Standard Grant
Collaborative Research: SHF: Medium: A New Direction of Research and Development to Fulfill the Promise of Computational Storage
合作研究:SHF:Medium:实现计算存储承诺的研发新方向
- 批准号:
2210755 - 财政年份:2022
- 资助金额:
$ 54万 - 项目类别:
Continuing Grant
III: Medium: Collaborative Research: MUDL: Multidimensional Uncertainty-Aware Deep Learning Framework
III:媒介:协作研究:MUDL:多维不确定性感知深度学习框架
- 批准号:
2107449 - 财政年份:2021
- 资助金额:
$ 54万 - 项目类别:
Continuing Grant
III: Small: Collaborative Research: A novel paradigm for detecting complex anomalous patterns in multi-modal, heterogeneous, and high-dimensional multi-source data sets
III:小型:协作研究:一种检测多模态、异构和高维多源数据集中复杂异常模式的新范式
- 批准号:
1954409 - 财政年份:2019
- 资助金额:
$ 54万 - 项目类别:
Standard Grant
CAREER: SPARK: A Theoretical Framework for Discovering Complex Patterns in Big Attributed Networks
职业:SPARK:发现大属性网络中复杂模式的理论框架
- 批准号:
1954376 - 财政年份:2019
- 资助金额:
$ 54万 - 项目类别:
Continuing Grant
SHF: Small: Redesigning the System Architecture for Ultra-High Density Data Storage
SHF:小型:重新设计超高密度数据存储的系统架构
- 批准号:
1910958 - 财政年份:2019
- 资助金额:
$ 54万 - 项目类别:
Standard Grant
CAREER: SPARK: A Theoretical Framework for Discovering Complex Patterns in Big Attributed Networks
职业:SPARK:发现大属性网络中复杂模式的理论框架
- 批准号:
1750911 - 财政年份:2018
- 资助金额:
$ 54万 - 项目类别:
Continuing Grant
III: Small: Collaborative Research: A novel paradigm for detecting complex anomalous patterns in multi-modal, heterogeneous, and high-dimensional multi-source data sets
III:小型:协作研究:一种检测多模态、异构和高维多源数据集中复杂异常模式的新范式
- 批准号:
1815696 - 财政年份:2018
- 资助金额:
$ 54万 - 项目类别:
Standard Grant
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