Phase-II IUCRC Texas Tech University: Center for Cloud and Autonomic Computing

第二阶段 IUCRC 德克萨斯理工大学：云和自主计算中心

• 批准号: 1939140
• 负责人: Yong Chen
• 金额: $ 50万
• 依托单位: Texas Tech University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-03-15 至 2025-02-28
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1939140&HistoricalAwards=false
• 关键词: Phase; II; IUCRC; Texas; Tech

In this project, Texas Tech University will extend the previously successful industry-driven research program of the Cloud and Autonomic Computing (CAC) Industry-University Cooperative Research Center (IUCRC) as part of the NSF IUCRC program. The CAC Center currently comprises participants from two principal academic institutions, Texas Tech University (TTU) and the University of Arizona (UA), as well as two affiliate sites associated with TTU: the University of North Texas and Texas State University, and two international sites associated with UA: Universidad de Sonora, Mexico and American University of Malta. The mission of the NSF CAC Center across all participating sites is to conduct research and development activities that advance the knowledge of how to design and engineer highly distributed (cloud) and highly automated (autonomic) computing systems for practical applications with stakeholders including industry, federal agencies, and academia together. This grant will extend the IUCRC research of the CAC at TTU from Phase I to Phase II.The TTU site of the NSF CAC focuses on advances in algorithms, methods, standards, and tools for cloud and highly automated computing systems. The Phase-II program of CAC@TTU site will continue research and development in areas including: 1) code development and Application Programming Interface (API) design for data acquisition, procedural, and workflow control; 2) high-performance data analytics and visualization in the cloud and autonomic computing settings; 3) improvements to practical applications of methods that use these and other cloud and autonomic computing techniques and methods; 4) standards implementations and design for cloud software and underlying infrastructure; and 5) applications of the above to data center control based in both industry and academic arenas. The CAC@TTU site will pursue these overall themes while remaining open to new and emerging opportunities that relate to the needs of current and future industry members or that come up through pursuit of the program of research.NSF funding for this project plays a key role in facilitating and promoting research collaboration among stakeholders including industry, federal agencies, and academia. This project will also train a broadly inclusive and globally competitive science workforce for the nation by integrating the latest development and advanced knowledge into mentoring and educational activities. Texas Tech University is a Hispanic-Serving Institution, and the Phase-II CAC@TTU effort will leverage its experience in Phase I to carry out research and development activities to have broader impacts, including targeted efforts to integrate hands-on learning experiences for historically under-represented population groups, actively engaging undergraduate students in research programs, and organizing community activities such as workshops and conferences. These activities will also be coordinated with the overall CAC center program of broader engagement.The Phase-II CAC@TTU site will distribute portions of its output through GitHub repositories (https://github.com/nsfcac) and websites including https://nsfcac.org/, http://cac.ttu.edu/, and https://discl.cs.ttu.edu/ for public releases of software, data, and results. The project members will provide industry motivation, expertise, and materials to facilitate research and development progress. The websites and repositories will be maintained for three years past the project completion date, and principal investigators will strive to maintain the associated output software products that remain in use as long as possible.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.

在这个项目中，德克萨斯理工大学将扩展之前成功的云与自主计算(CAC)产学合作研究中心(IUCRC)的行业驱动研究计划，作为NSF IUCRC计划的一部分。CAC中心目前的参与者来自两个主要学术机构--德克萨斯理工大学(TTU)和亚利桑那大学(UA)，以及与TTU相关的两个附属网站：北得克萨斯大学和德克萨斯州立大学，以及与UA相关的两个国际网站：墨西哥索诺拉大学和马耳他美国大学。NSF CAC中心在所有参与站点的使命是开展研究和开发活动，与包括行业、联邦机构和学术界在内的利益相关者一起，促进关于如何设计和设计用于实际应用的高度分布式(云)和高度自动化(自主)计算系统的知识。这笔赠款将把TTU CAC的IUCRC研究从第一阶段扩展到第二阶段。NSF CAC的TTU站点专注于云和高度自动化计算系统的算法、方法、标准和工具方面的进展。CAC@TTU网站的第二阶段计划将继续在以下领域进行研究和开发：1)数据采集、程序和工作流控制的代码开发和应用编程接口(API)设计；2)云和自主计算环境中的高性能数据分析和可视化；3)改进使用这些和其他云和自主计算技术和方法的方法的实际应用；4)云软件和底层基础设施的标准实施和设计；以及5)上述在行业和学术领域的数据中心控制应用。CAC@TTU网站将追求这些总体主题，同时保持对与当前和未来行业成员的需求有关的新出现的机会或通过追求研究计划而出现的机会的开放。NSF为该项目提供的资金在促进和促进包括行业、联邦机构和学术界在内的利益相关者之间的研究合作方面发挥着关键作用。该项目还将通过将最新发展和先进知识融入指导和教育活动，为国家培养一支具有广泛包容性和全球竞争力的科学劳动力队伍。德克萨斯理工大学是一所为拉美裔美国人服务的机构，第二阶段CAC@TTU的努力将利用其在第一阶段的经验开展研究和开发活动，以产生更广泛的影响，包括有针对性地努力为历史上代表性不足的人口群体整合实践学习经验，积极让本科生参与研究项目，以及组织社区活动，如研讨会和会议。这些活动还将与更广泛的整体CAC中心计划进行协调。第二阶段CAC@TTU站点将通过GitHub存储库(https://github.com/nsfcac)和包括https://nsfcac.org/，http://cac.ttu.edu/，和https://discl.cs.ttu.edu/在内的网站)分发部分成果，以公开发布软件、数据和结果。项目成员将提供行业动力、专业知识和材料，以促进研发进展。网站和存储库将在项目完成日期后的三年内进行维护，主要调查人员将努力保持相关的输出软件产品尽可能长时间地保持在使用中。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

MonSTer: An Out-of-the-Box Monitoring Tool for High Performance Computing Systems

MonSTer：用于高性能计算系统的开箱即用的监控工具

• DOI: 10.1109/cluster49012.2020.00022
• 发表时间: 2020
• 期刊: IEEE International Conference on Cluster Computing (CLUSTER'20
• 作者: Li, Jie;Ali, Ghazanfar;Nguyen, Ngan;Hass, Jon;Sill, Alan;Dang, Tommy;Chen, Yang
• 通讯作者: Chen, Yang

Towards xBGAS on CHERI: Supporting a Secure Global Memory

在 CHERI 上迈向 xBGAS：支持安全的全局内存

• DOI: 10.1109/ipdpsw59300.2023.00100
• 发表时间: 2023
• 期刊: IEEE
• 作者: Side, Mert;Williams, Brody;Leidel, John;Woodruff, Jonathan;Moore, Simon W.;Chen, Yong
• 通讯作者: Chen, Yong

PRS: A Pattern-Directed Replication Scheme for Heterogeneous Object-Based Storage

• DOI: 10.1109/tc.2019.2954089
• 发表时间: 2020-04
• 期刊: IEEE Transactions on Computers
• 影响因子: 3.7
• 作者: Jiang Zhou;Yong Chen;Wei Xie;Dong Dai;Shuibing He;Weiping Wang

Data Distribution for Heterogeneous Storage Systems

• DOI: 10.1109/tc.2022.3223302
• 发表时间: 2023-06
• 期刊: IEEE Transactions on Computers
• 影响因子: 3.7
• 作者: Jiang Zhou;Yong Chen;Mai Zheng;Weiping Wang

RaiderSTREAM: Adapting the STREAM Benchmark to Modern HPC Systems

RaiderSTREAM：使 STREAM 基准适应现代 HPC 系统

• DOI: 10.1109/hpec55821.2022.9926292
• 发表时间: 2022
• 期刊: Proccedings of the 27th IEEE High Performance Extreme Computing Conference (HPEC'22
• 作者: Beebe, Michael;Williams, Brody;Devaney, Stephen;Leidel, John;Chen, Yong;Poole, Steve
• 通讯作者: Poole, Steve