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CC* Data Storage: Flexible Affordable Scalable Technology for Research Storage (FAST-Research Storage)

CC* Data Storage: Flexible Affordable Scalable Technology for Research Storage (FAST-Research Storage)
CC* 数据存储:用于研究存储的灵活且经济实惠的可扩展技术(FAST-Research Storage)
批准号:
2232810
负责人:
Charles Kneifel
金额:
$50.0万
依托单位:
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
项目状态:
已结题
起止时间:
2022-09-01 至 2024-08-31

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中文摘要
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英文摘要
The Flexible Affordable Scalable Technology for Research Storage (FAST) is a shared research storage system based on commodity data center hardware and open source CEPH software that provides a flexible, high-performance, cost-effective, tiered data storage system in support of research data storage requirements. The FAST system provides both Network Attached Storage (NAS) and Object Store storage models, along with guidance for choosing wisely between them. Object storage services support efficient packaging of data sets, including the complete set of metadata, for both operational use and long-term data storage. FAST also includes scripts to package, migrate data between storage tiers, and facilitate the use of appropriate storage to meet researcher’s requirements. Cloud-based long-term cold storage environments are part of the data lifecycle to support data retention requirements cost-effectively. By using commodity hardware FAST is easily expanded and capable of incorporating researcher purchased hardware into the environment. The system (20%) will be shared with the community via the Open Science Data Federation (OSDF) as well as with minority service institutions in North Carolina through a community storage grant program. Both sharing models allow researchers to publish data for public consumption, stage data to facilitate local analysis and provide robust storage service to schools which may not otherwise have access to these services. The expected impact of FAST is to reduce the amount of time, effort, and money that researchers spend managing their data, ensuring long-term access to data, with the data stored in the right place at the right time and cost.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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CC* Compute: NCShare Compute as a Service
  • 批准号:
    2201105
  • 项目类别:
    Standard Grant
  • 资助金额:
    $39.76万
  • 财政年份:
    2022
  • 负责人:
    Charles Kneifel
  • 依托单位:
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
Data-driven Recommendation System Construction of an Online Medical Platform Based on the Fusion of Information
Development of a Linear Stochastic Model for Wind Field Reconstruction from Limited Measurement Data
  • 批准号:
    --
  • 项目类别:
    --
  • 资助金额:
    40万元
  • 批准年份:
    2020
  • 负责人:
    Vikrant Gupta
  • 依托单位:
基于Linked Open Data的Web服务语义互操作关键技术
  • 批准号:
    61373035
  • 项目类别:
    面上项目
  • 资助金额:
    77.0万元
  • 批准年份:
    2013
  • 负责人:
    冯志勇
  • 依托单位: