Track 4: Advanced CI Coordination Ecosystem: Monitoring and Measurement Services

轨道 4：高级 CI 协调生态系统：监控和测量服务

• 批准号: 2137603
• 负责人: Thomas Furlani
• 金额: $ 999.56万
• 依托单位: SUNY at Buffalo
• 依托单位国家: 美国
• 项目类别: Cooperative Agreement
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-05-01 至 2027-10-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2137603&HistoricalAwards=false
• 关键词: Track; Advanced; CI; Coordination; Ecosystem

The SUNY at Buffalo team provides monitoring and measurement services as part of the Advanced Cyberinfrastructure Coordination Ecosystem: Services & Support (ACCESS) program. Advanced cyberinfrastructure (CI), which includes high performance computing (HPC), cloud computing and advanced networks, plays a pivotal role in ensuring U.S. leadership in science and engineering and serves as a powerful tool to help drive the U.S. economy. Indeed, CI performance is essential in all technology fields from research and design to manufacturing. Given the importance of CI, as well as its substantial cost, it is important that all stakeholders, i.e., the public, end-users, system support personnel, application developers and decision makers, have at their disposal tools to help optimize and measure CI performance, as well as the applications that use it.The University at Buffalo is developing CI measurement and optimization tools, namely XDMoD (XD Metrics on Demand) and its open-source counterpart, Open XDMoD, which are in use worldwide for advanced CI monitoring and reporting in academia and industry. This project builds upon and expands this foundation for measuring and monitoring services for the large NSF investment in the Advanced Cyberinfrastructure Coordination Ecosystem: Services & Support program. Highlights of this project include: (1) development of a flexible framework that allows stakeholders to use analytical tools they desire on performance data from national and local CI resources; (2) development of a comprehensive view of the CI ecosystem, including network, data, and public clouds, to facilitate CI planning from the local to the national level; (3) development of a CI simulator to predict the response of the CI ecosystem to proposed new systems or changes in existing systems enabling efficient deployment and use; and (4) development of automated tools to monitor application performance metrics (including energy) on established and novel CI architectures. The relationship between time-to-solution versus energy consumed is important to determine the feasibility of adopting novel CI architectures which promise lower energy consumption.Open XDMoD has a broad impact through its use by institutions worldwide to better manage their CI assets, including academic, industrial, and governmental research centers. Development and deployment of the tools include a range of activities to train the future CI workforce in an inclusive manner promoting diversity and equity.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.

纽约州立大学布法罗分校的团队提供监测和测量服务，作为高级网络基础设施协调生态系统：服务支持（ACCESS）计划的一部分。先进的网络基础设施（CI），包括高性能计算（HPC），云计算和先进的网络，在确保美国在科学和工程领域的领导地位方面发挥着关键作用，并成为帮助推动美国经济的强大工具。事实上，CI性能在从研究和设计到制造的所有技术领域都至关重要。 鉴于传播和信息的重要性及其巨大的成本，所有利益攸关方，即：公众、最终用户、系统支持人员、应用程序开发人员和决策者都可以使用工具来帮助优化和测量CI性能，以及使用它的应用程序。布法罗大学正在开发CI测量和优化工具，即XDMOD（XD随需应变）及其开源对应物Open XDMoD，它们在全球范围内用于学术界和工业界的高级CI监控和报告。 该项目建立在并扩展了NSF在高级网络基础设施协调生态系统：服务支持计划中的大型投资的测量和监测服务的基础上。该项目的重点包括：（1）开发一个灵活的框架，使利益相关者能够使用他们希望从国家和地方传播与信息资源中获得的绩效数据分析工具;（2）开发传播与信息生态系统的综合视图，包括网络，数据和公共云，以促进从地方到国家的传播与信息规划;（3）开发CI模拟器，以预测CI生态系统对提议的新系统或现有系统中的更改的响应，从而实现有效的部署和使用;以及（4）开发自动化工具，以监控已建立的和新的CI架构上的应用程序性能指标（包括能量）。解决方案时间与能耗之间的关系对于确定采用新型CI架构的可行性非常重要，这些架构承诺降低能耗。Open XDMoD通过全球机构的使用产生了广泛的影响，以更好地管理其CI资产，包括学术，工业和政府研究中心。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值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

First Impressions of the NVIDIA Grace CPU Superchip and NVIDIA Grace Hopper Superchip for Scientific Workloads

针对科学工作负载的 NVIDIA Grace CPU 超级芯片和 NVIDIA Grace Hopper 超级芯片的第一印象

• DOI: 10.1145/3636480.3637097
• 发表时间: 2024
• 期刊: ACM
• 作者: Simakov, Nikolay A.;Jones, Matthew D.;Furlani, Thomas R.;Siegmann, Eva;Harrison, Robert J.
• 通讯作者: Harrison, Robert J.

Are we ready for broader adoption of ARM in the HPC community: Performance and Energy Efficiency Analysis of Benchmarks and Applications Executed on High-End ARM Systems

• DOI: 10.1145/3581576.3581618
• 发表时间: 2023-02
• 期刊: Proceedings of the HPC Asia 2023 Workshops
• 作者: N. Simakov;R. L. Deleon;Joseph P. White;Matthew D. Jones;T. Furlani;E. Siegmann;R. J. Harrison

System-Auditing, Data Analysis and Characteristics of Cyber Attacks for Big Data Systems

大数据系统的系统审计、数据分析和网络攻击特征

• DOI: 10.1145/3511808.3557185
• 发表时间: 2022
• 期刊: CIKM '22: Proceedings of the 31st ACM International Conference on Information & Knowledge Management
• 作者: Huang, Liangyi;Hall, Sophia;Shao, Fei;Nihar, Arafath;Chaudhary, Vipin;Wu, Yinghui;French, Roger;Xiao, Xusheng
• 通讯作者: Xiao, Xusheng