MRI: Acquisition of a Shared Scalable Research Storage System

MRI：获取共享的可扩展研究存储系统

• 批准号: 1625039
• 负责人: Kenneth De Jong
• 金额: $ 45万
• 依托单位: George Mason 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: 2016-09-15 至 2019-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1625039&HistoricalAwards=false
• 关键词: MRI; Acquisition; Shared; Scalable; Research

This project, acquiring a high-end scalable network storage system, aims to integrate an innovative storage architecture (MEMORI) into the existing research computing infrastructure at the institution to address the needs of both traditional and non-traditional HPC researchers. The proponents will then instantiate that architecture with the acquisition of the high-end scalable network storage system. The instrumentation will be managed centrally, but shared with the entire research community. The instrumentation enables a variety of projects in cyber-security, mental health, climate dynamics and social systems, all of which positively benefit the health and economic well-being of the country. In particular, the storage system is designed to support shared access by sister institutions, since GMU is a member of the 4-VA university consortium that provides state-level infrastructure promoting resource sharing. Data access by potential outside stakeholders will also be enhanced. The current research computing infrastructure is unable to support the growing storage needs for the wide variety of current research projects involving elements of "big data." As a result, individual projects are limited in their ability to store, mine, visualize and share large data sets. Rather than forcing research projects to deal with these limitations on an individual and ad hoc basis, the researchers will take advantage of recent developments in storage technologies to provide a shared storage server capable of supporting current storage needs and scalable in a cost-effective manner for future needs. The proposed architecture is specifically designed to support research projects in the humanities and social sciences, as well as the more traditional science and engineering disciplines. Furthermore, centrally managing the instrumentation creates a secure environment for multi-university shared access, appropriate control of sensitive data, and a reliable framework for data management plans, backups, and archiving. In addition, a variety of departments offer courses in data mining, data analytics, and data visualization. These courses are currently limited in their ability to support datasets of significant size, and will greatly benefit from the proposed system. The library services will be significantly enhanced by the instrumentation. Fast network access to the system provides the ability to store local copies of large databases for text mining research by faculty and students, as well as visualization capabilities.

该项目收购了一个高端可扩展的网络存储系统，旨在将创新的存储架构（MEMORI）集成到该机构现有的研究计算基础设施中，以满足传统和非传统HPC研究人员的需求。然后，支持者将通过收购高端可扩展网络存储系统来实例化该架构。仪器将集中管理，但与整个研究界共享。该仪器使网络安全，心理健康，气候动态和社会系统的各种项目成为可能，所有这些都对该国的健康和经济福祉产生了积极影响。特别是，存储系统旨在支持姐妹机构的共享访问，因为GMU是4-VA大学联盟的成员，该联盟提供促进资源共享的州级基础设施。潜在的外部利益攸关方获取数据的机会也将得到加强。当前的研究计算基础架构无法支持当前涉及“大数据”元素的各种研究项目不断增长的存储需求。“因此，单个项目在存储、挖掘、可视化和共享大型数据集的能力方面受到限制。研究人员将利用存储技术的最新发展，提供一个能够支持当前存储需求的共享存储服务器，并以经济高效的方式为未来的需求进行扩展，而不是迫使研究项目在个人和临时的基础上处理这些限制。拟议的架构是专门为支持人文和社会科学以及更传统的科学和工程学科的研究项目而设计的。此外，集中管理仪器为多所大学共享访问、敏感数据的适当控制以及数据管理计划、备份和归档的可靠框架创造了安全的环境。 此外，各种部门提供数据挖掘，数据分析和数据可视化课程。这些课程目前在支持大规模数据集方面能力有限，将从拟议的系统中受益匪浅。图书馆服务将因仪器仪表而大大加强。快速网络访问系统提供了存储大型数据库的本地副本的能力，供教师和学生进行文本挖掘研究，以及可视化功能。