CAREER: Towards Learning-Based Storage Systems with Hardware-Software Co-Design

职业:通过软硬件协同设计实现基于学习的存储系统

基本信息

  • 批准号:
    2144796
  • 负责人:
  • 金额:
    $ 59.34万
  • 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
  • 起止时间:
    2022-03-01 至 2027-02-28
  • 项目状态:
    未结题

项目摘要

Storage systems today have been built into a complicated ecosystem, which involves the development and deployment of storage devices, storage software, and application-level data stores. To rapidly meet the ever-increasing storage performance and efficiency requirements, the entire storage hardware and software stack need to adapt instantly in a coordinated fashion. However, it is challenging to achieve this with current human-driven systems-building approaches. Recent advancements in machine learning techniques show that the learning-based approach is a promising method to solve system optimization problems. However, it remains unclear how the storage ecosystem should be advanced to embrace the learning techniques to facilitate its development, deployment, and optimizations across the full stack. This project proposes to develop systems and architecture techniques to build a learning-based storage ecosystem. It has four major thrusts. First, the project proposes to enable the development of customized storage devices for specific application types with automated tuning of hardware specifications, therefore, we can enable developers to identify optimal device specifications with much less time and effort. Second, the project plans to develop elastic storage management for multi-tenant applications using reinforcement learning, thus, we can achieve both improved resource utilization and performance isolation. Third, the project proposes to integrate the storage hardware knowledge into the learning procedure to facilitate the development of learning-based storage software. Finally, the project will revisit the storage hardware architecture for building learning-based storage drives to further enhance the learning-based storage ecosystem. The project will facilitate the development of a new course that centers around memory and storage technologies. The project will also promote computer systems and architecture education to underrepresented and high school students through various research workshops and summer camps.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.
如今的存储系统已经构建成一个复杂的生态系统,其中涉及到存储设备、存储软件和应用程序级数据存储的开发和部署。为了快速满足不断增长的存储性能和效率要求,整个存储硬件和软件堆栈需要以协调的方式即时适应。然而,用目前的人为驱动的系统建设方法来实现这一点是具有挑战性的。机器学习技术的最新进展表明,基于学习的方法是解决系统优化问题的一种很有前途的方法。但是,目前尚不清楚应如何推进存储生态系统以采用学习技术来促进其在整个堆栈中的开发、部署和优化。该项目建议开发系统和体系结构技术,以构建基于学习的存储生态系统。它有四个主要推力。首先,该项目建议通过自动调整硬件规格来支持针对特定应用类型的定制存储设备的开发,因此,我们可以让开发人员以更少的时间和精力确定最佳设备规格。其次,该项目计划使用强化学习为多租户应用开发弹性存储管理,从而实现提高资源利用率和性能隔离。第三,项目提出将存储硬件知识融入到学习过程中,促进基于学习的存储软件的开发。最后,该项目将重新审视用于构建基于学习的存储驱动器的存储硬件体系结构,以进一步增强基于学习的存储生态系统。该项目将促进以内存和存储技术为中心的新课程的开发。该项目还将通过各种研究研讨会和夏令营向代表不足的高中生推广计算机系统和体系结构教育。该奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。

项目成果

期刊论文数量(6)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
G10: Enabling An Efficient Unified GPU Memory and Storage Architecture with Smart Tensor Migrations
Learning to Drive Software-Defined Solid-State Drives
学习驱动软件定义的固态硬盘
LeaFTL: A Learning-Based Flash Translation Layer for Solid-State Drives
BlockFlex: Enabling Storage Harvesting with Software-Defined Flash in Modern Cloud Platforms
  • DOI:
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Benjamin Reidys;Jinghan Sun;Anirudh Badam;S. Noghabi;Jian Huang
  • 通讯作者:
    Benjamin Reidys;Jinghan Sun;Anirudh Badam;S. Noghabi;Jian Huang
Learning to Drive Software-Defined Storage
  • DOI:
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Jian Huang;Daixuan Li;Jinghan Sun
  • 通讯作者:
    Jian Huang;Daixuan Li;Jinghan Sun
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Jian Huang其他文献

Regularized biomarker selection in microarray meta-analysis
微阵列荟萃分析中的常规生物标志物选择
  • DOI:
  • 发表时间:
    2007
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Shuangge Ma;Jian Huang
  • 通讯作者:
    Jian Huang
Study on isolating Matsutake mycorrhizas-associated actinobacteria and evaluating their impacts on fungal growth
松茸菌根相关放线菌的分离及其对真菌生长影响的研究
  • DOI:
    10.11519/jfsc.128.0_505
  • 发表时间:
    2017
  • 期刊:
  • 影响因子:
    0
  • 作者:
    C. Lian;Yan Xia;Jian Huang;Hiroyuki Kurokuchi;N. Matsushita;Y. Ota;P. Pawara;Shijie Zhang;Lu
  • 通讯作者:
    Lu
Design of multichannel QMF banks via frequency-domain optimizations
通过频域优化设计多通道 QMF 组
A Case Probe into Emotional Experiences of Chinese English Majors in L2 Listening Learning Process: A Positive Psychology Perspective
中国英语专业学生二语听力学习过程中情绪体验的个案探讨:积极心理学视角
  • DOI:
    10.1177/21582440221079815
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    2
  • 作者:
    Jian Huang
  • 通讯作者:
    Jian Huang
The Fate of Ultrafine Particle Matters in Air and Their Detection Techniques
空气中超细颗粒物质的归宿及其检测技术

Jian Huang的其他文献

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{{ truncateString('Jian Huang', 18)}}的其他基金

Collaborative Research: Elements: Towards A Scalable Infrastructure for Archival and Reproducible Scientific Visualizations
协作研究:要素:建立用于存档和可重复科学可视化的可扩展基础设施
  • 批准号:
    2209767
  • 财政年份:
    2022
  • 资助金额:
    $ 59.34万
  • 项目类别:
    Standard Grant
EAGER: CRYO: Continuous Adiabatic Demagnetization Refrigeration Below 1K without Helium-3
EAGER:CRYO:连续绝热退磁制冷低于 1K,无需 Helium-3
  • 批准号:
    2232489
  • 财政年份:
    2022
  • 资助金额:
    $ 59.34万
  • 项目类别:
    Standard Grant
Collaborative Research: Integrating multi-dimensional omics data for quantifying disease heterogeneity
协作研究:整合多维组学数据以量化疾病异质性
  • 批准号:
    1916199
  • 财政年份:
    2019
  • 资助金额:
    $ 59.34万
  • 项目类别:
    Standard Grant
SPX: Collaborative Research: Scaling the Software-Defined Data Center with Network-Storage Stack Co-Design
SPX:协作研究:通过网络存储堆栈协同设计扩展软件定义的数据中心
  • 批准号:
    1919044
  • 财政年份:
    2019
  • 资助金额:
    $ 59.34万
  • 项目类别:
    Standard Grant
CRII: CSR: System Techniques to Exploit the Byte-Accessibility of Solid-State Drives
CRII:CSR:利用固态硬盘字节可访问性的系统技术
  • 批准号:
    1850317
  • 财政年份:
    2019
  • 资助金额:
    $ 59.34万
  • 项目类别:
    Standard Grant
II-New: Collaborative: A Mixed Reality Environment for Enabling Everywhere Data-Centric Work
II-新:协作:支持无处不在的以数据为中心的工作的混合现实环境
  • 批准号:
    1629890
  • 财政年份:
    2016
  • 资助金额:
    $ 59.34万
  • 项目类别:
    Standard Grant
Quantum electron solids and interaction-driven phenomena in two- and one-dimensional systems
二维和一维系统中的量子电子固体和相互作用驱动的现象
  • 批准号:
    1410302
  • 财政年份:
    2014
  • 资助金额:
    $ 59.34万
  • 项目类别:
    Standard Grant
Constrained Group Selection and Structure Estimation in Semiparametric Models
半参数模型中的约束组选择和结构估计
  • 批准号:
    1208225
  • 财政年份:
    2012
  • 资助金额:
    $ 59.34万
  • 项目类别:
    Standard Grant
Undergraduate Training at NSF Teragrid XD RDAV Center
NSF Teragrid XD RDAV 中心的本科生培训
  • 批准号:
    1136246
  • 财政年份:
    2011
  • 资助金额:
    $ 59.34万
  • 项目类别:
    Standard Grant
Electron-Electron Interaction Driven Phase Transition in Low Dimensional Systems
低维系统中电子-电子相互作用驱动的相变
  • 批准号:
    1105183
  • 财政年份:
    2011
  • 资助金额:
    $ 59.34万
  • 项目类别:
    Continuing Grant

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