CyberTraining: CIC: CyberTraining for Students and Technologies from Generation Z

网络培训：CIC：针对 Z 世代学生和技术的网络培训

• 批准号: 2200409
• 负责人: Geoffrey Fox
• 金额: $ 49.23万
• 依托单位: University of Virginia Main Campus
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-12-01 至 2023-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2200409&HistoricalAwards=false
• 关键词: CyberTraining; CIC; Students; Technologies; Generation

Information technology is playing a dramatically increasing role in society, industry, and research. This includes design and use of large databases, simulations and artificial intelligence applications hosted on clouds and supercomputers with convergent technologies. Correspondingly, there is an increasing need for research workforce job skills in these and related areas. This project takes freshly created Indiana University Engineering course material on this cyberinfrastructure and adapts it for training with an emphasis on the needs of under-represented communities. The techniques of the successful open source software movement are used to create sustainable communities around the course curriculum and software. The project is creating new technologies to enable this for today's generation of students. Skills in core cloud computing, big data, supercomputing and artificial intelligence are exemplified by applications in the life science and nanotechnology areas. This project enables the future research workforce to contribute effectively using advanced cyberinfrastructure, promoting the progress of science and advancing the national health, prosperity, and welfare, which serves the national interest, as stated by NSF's mission. The future economic progress and research leadership of the U.S. is dependent on having a research workforce that is capable of making use of advanced cyberinfrastructure (CI) resources as articulated by the National Strategic Computing Initiative (NSCI). This requires a curriculum that changes and integrates modern concepts and practices for the new generation of students aiming at a "data-enabled computational science and engineering" expertise. This project takes what Indiana University has learned from a brand new four-year undergraduate engineering curriculum designed ab initio and taught so far to its first two undergraduate classes, and invests it into developing active training modules. The innovative curriculum integrates big data, simulations, clouds and high performance computing systems presented in a uniform framework. The course material is customized for communities of cyberinfrastructure researchers nucleated, built, and sustained via the dynamic use of GitHub and enhanced by innovative tools to build a novel learning management system optimized for cyberinfrastructure-intensive classes. The project modules include Cloud Computing, Big Data Applications and Analytics, Networking, High-Performance Computing, Artificial Intelligence/Machine Learning, and Information Visualization. There are residential sessions, with a call for participants, and purely online courses and these have both "teach the student" and "teach the teacher" modes; the latter enables easy spread of the classes. Hands-on learning with research projects built around the class material is fully supported. The project offers CyberTraining with all of the popular approaches used by the Apache Software Foundation, including Meetups and Hackathons. Modules for domain scientists and engineers, e.g., the cyberinfrastructure users that exploit advanced CI methods for research in nanoengineering and bioengineering are included. Both students and teachers contribute to the course improving the text, the software, including a unique set of examples and the project aims to show that one can build both learning and sustainability communities by using the proven techniques of the open source software community. The project uses proactive measures to enhance the involvement of under-represented communities in its activities.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.

信息技术在社会、工业和研究中发挥着越来越重要的作用。这包括设计和使用大型数据库，模拟和人工智能应用程序托管在云和具有融合技术的超级计算机上。相应地，在这些领域和相关领域，对劳动力工作技能的研究需求越来越大。该项目采用新创建的印第安纳州大学工程课程材料，并将其用于培训，重点是代表性不足的社区的需求。成功的开源软件运动的技术被用来围绕课程和软件创建可持续的社区。该项目正在创造新的技术，使这对今天的一代学生。生命科学和纳米技术领域的应用体现了核心云计算、大数据、超级计算和人工智能方面的技能。该项目使未来的研究人员能够有效地利用先进的网络基础设施，促进科学进步，促进国家健康，繁荣和福利，这符合国家利益，正如NSF的使命所述。美国未来的经济进步和研究领导地位取决于拥有一支能够利用国家战略计算计划（NSCI）所阐述的先进网络基础设施（CI）资源的研究队伍。这需要一个课程，改变和整合现代概念和实践，为新一代的学生，旨在“数据支持的计算科学和工程”的专业知识。该项目采用了印第安纳州大学从一个全新的四年制本科工程课程中学到的东西，该课程从一开始就设计，到目前为止已经教授给了前两个本科班，并将其投入到开发积极的培训模块中。创新的课程整合了大数据，模拟，云和高性能计算系统在一个统一的框架。该课程材料是为网络基础设施研究人员社区定制的，这些研究人员通过动态使用GitHub进行培养、构建和维持，并通过创新工具进行增强，以构建一个针对网络基础设施密集型课程进行优化的新型学习管理系统。项目模块包括云计算，大数据应用和分析，网络，高性能计算，人工智能/机器学习和信息可视化。有住宅会议，呼吁参与者，和纯粹的在线课程，这些都有“教学生”和“教老师”模式;后者使课程的传播变得容易。实践学习与研究项目建立在类材料是完全支持的。该项目为CyberTraining提供了Apache软件基金会使用的所有流行方法，包括Meetups和Hackathons。面向领域科学家和工程师的模块，例如，网络基础设施的用户，利用先进的CI方法在纳米工程和生物工程的研究也包括在内。学生和教师都为课程做出了贡献，改进了文本，软件，包括一套独特的例子，该项目旨在表明，人们可以通过使用开源软件社区的成熟技术来建立学习和可持续发展社区。这个奖项反映了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

Opportunities for enhancing MLCommons efforts while leveraging insights from educational MLCommons earthquake benchmarks efforts

加强 MLCommons 工作的机会，同时利用教育 MLCommons 地震基准工作的见解

• DOI: 10.3389/fhpcp.2023.1233877
• 发表时间: 2023
• 期刊: Frontiers in High Performance Computing
• 作者: von Laszewski, Gregor;Fleischer, J. P.;Knuuti, Robert;Fox, Geoffrey C.;Kolessar, Jake;Butler, Thomas S.;Fox, Judy
• 通讯作者: Fox, Judy

Time Series Analysis of Cryptocurrency Prices Using Long Short-Term Memory

• DOI: 10.3390/a15070230
• 发表时间: 2022-07-01
• 期刊: ALGORITHMS
• 影响因子: 2.3
• 作者: Fleischer, Jacques Phillipe;von Laszewski, Gregor;Bautista, Yohn Jairo Parra
• 通讯作者: Bautista, Yohn Jairo Parra

Templated Hybrid Reusable Computational Analytics Workflow Management with Cloudmesh, Applied to the Deep Learning MLCommons Cloudmask Application

使用 Cloudmesh 进行模板化混合可重用计算分析工作流程管理，应用于深度学习 MLCommons Cloudmask 应用程序

• DOI: 10.1109/e-science58273.2023.10254942
• 发表时间: 2023
• 期刊: IEEE
• 作者: von Laszewski, Gregor;Fleischer, J.P.;Fox, Geoffrey C.;Papay, Juri;Jackson, Sam;Thiyagalingam, Jeyan
• 通讯作者: Thiyagalingam, Jeyan

Using Cloudmesh GAS for Speedy Generation of Hybrid Multi-Cloud Auto Generated AI Services

使用 Cloudmesh GAS 快速生成混合多云自动生成的 AI 服务

• DOI: 10.1109/compsac51774.2021.00032
• 发表时间: 2021
• 期刊: and Applications Conference (COMPSAC
• 作者: Laszewski, Gregor von;Orlowski, Anthony;Otten, Richard H.;Markowitz, Reilly;Gandhi, Sunny;Chai, Adam;Fox, Geoffrey C.;Chang, Wo L.
• 通讯作者: Chang, Wo L.