Collaborative Research:CyberTraining:Implementation:Medium: Broadening Adoption of Parallel and Distributed Computing in Undergraduate Computer Science and Engineering Curricula

合作研究：网络培训：实施：中：在本科计算机科学与工程课程中扩大并行和分布式计算的采用

• 批准号: 2017590
• 负责人: Sushil Prasad
• 金额: $ 70.18万
• 依托单位: University of Texas at San Antonio
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-10-15 至 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2017590&HistoricalAwards=false
• 关键词: Collaborative; Research; CyberTraining; Implementation; Medium

This collaborative project represents a multi-faceted effort to shift computer science and engineering education toward ensuring that students can use 21st century platforms that pervasively incorporate parallel and distributed computing (PDC). Twentieth century computers were mostly designed around a single processor, executing a sequence of operations. But this century is characterized by widespread deployment of multi-core, graphics, and AI tensor processors, as well as a shift to cloud servers, and the internet of things, all of which depend on the much different PDC approach to problem solving and programming. Financial, technical, scientific, engineering and medical companies, government labs, the department of defense, the intelligence community, and many other sectors are desperately seeking employees who can exploit PDC systems, because the existing workforce was heavily steeped in the old model. Yet most students continue to learn the old approach due to significant inertia in academia. To turn the tide toward infusing PDC into the early stages of computer science and engineering education, this project will guide curricula and accreditation standards, prepare teachers, and foster a strong PDC education community. It will thus strategically serve the national interest, as stated by NSF's mission: to promote the progress of science; to advance the national health, prosperity and welfare; and to secure the national defense. It will be a significant step toward modernizing the emerging workforce to have the computing skills needed for the United States to maintain leadership in all of these areas.The Center for Parallel and Distributed Computing Curriculum Development and Educational Resources (CDER) is preparing the 2020 update of their 2013 curriculum guidelines for introducing parallel and distributed computing (PDC) into early undergraduate courses. This project will engage in four areas of activity to foster adoption of the curriculum, and extend it, with the goal of modernizing computer science and engineering workforce development.One major thrust is running summer training workshops for teachers, to learn both PDC concepts and experimental course evaluation methodology. The discipline is still in a phase of discovery with respect to PDC education approaches, and must encourage a diverse set of well-designed experiments to test and evaluate a broad range of pedagogical hypotheses. The workshop participants will be drawn from a diverse pool of educators, and given curriculum development grants in support of experimental course offerings and evaluation, leading to conference or journal publications, as well as contributions of exemplars to the CDER online course materials repository. A second effort is to help ABET/CSAB to formulate core PDC requirements and to inform/train ABET/CSAB evaluators (CSAB is the lead society within ABET for accreditation of degree programs in computer science). A third effort is expanding the curriculum guidelines to explicitly address adding PDC to computer engineering programs, which present novel curricular opportunities. Lastly, it will continue CDER's successes in organizing PDC education workshops in conjunction with major conferences, publishing PDC education books and journal special issues, maintaining and curating an online repository of PDC education resources, and providing free access to a publicly available PDC education cluster system.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.

该合作项目代表了一项多方面的努力，旨在将计算机科学和工程教育转变为确保学生能够使用普遍采用并行和分布式计算 (PDC) 的 21 世纪平台。二十世纪的计算机主要是围绕单个处理器设计的，执行一系列操作。但本世纪的特点是多核、图形和 AI 张量处理器的广泛部署，以及向云服务器和物联网的转变，所有这些都依赖于截然不同的 PDC 解决问题和编程的方法。金融、技术、科学、工程和医疗公司、政府实验室、国防部、情报界和许多其他部门都在拼命寻找能够利用 PDC 系统的员工，因为现有的劳动力严重依赖于旧模式。然而，由于学术界的巨大惯性，大多数学生继续学习旧的方法。为了扭转将 PDC 融入计算机科学和工程教育早期阶段的趋势，该项目将指导课程和认证标准、培养教师并培育强大的 PDC 教育社区。因此，它将在战略上服务于国家利益，正如 NSF 的使命所述：促进科学进步；促进国民健康、繁荣和福利；并确保国防。拥有美国在所有这些领域保持领先地位所需的计算技能，这将是实现新兴劳动力现代化的重要一步。并行和分布式计算课程开发和教育资源中心 (CDER) 正在准备 2020 年更新他们的 2013 年课程指南将并行和分布式计算 (PDC) 引入早期本科课程。该项目将开展四个领域的活动，以促进课程的采用和扩展，以实现计算机科学和工程劳动力发展现代化的目标。其中一个主要推动力是为教师举办夏季培训研讨会，以学习 PDC 概念和实验课程评估方法。该学科仍处于 PDC 教育方法的发现阶段，必须鼓励一系列精心设计的实验来测试和评估广泛的教学假设。研讨会参与者将来自不同的教育工作者群体，并获得课程开发资助，以支持实验课程的提供和评估，从而发表会议或期刊出版物，以及向 CDER 在线课程材料存储库贡献范例。第二项工作是帮助 ABET/CSAB 制定核心 PDC 要求，并通知/培训 ABET/CSAB 评估人员（CSAB 是 ABET 内计算机科学学位课程认证的主导协会）。第三项努力是扩展课程指南，明确将 PDC 添加到计算机工程课程中，这提供了新的课程机会。最后，它将延续 CDER 的成功经验，结合主要会议组织 PDC 教育研讨会、出版 PDC 教育书籍和期刊特刊、维护和管理 PDC 教育资源的在线存储库，以及免费提供对公共可用的 PDC 教育集群系统的访问该奖项反映了 NSF 的法定使命，并通过使用基金会的智力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

Integrating Parallel and Distributed Computing in Early Computing Classes

在早期计算课程中集成并行和分布式计算

• DOI: 10.1145/3545947.3569623
• 发表时间: 2022-03
• 期刊: ACM
• 作者: Ghafoor, Sheikh;Weems, Charles;Sussman, Alan;Vaidyanathan, Ramachandran;Prasad, Sushil
• 通讯作者: Prasad, Sushil

Message from the EduPar-23 Workshop Chairs and Workshop Organization

EduPar-23 研讨会主席和研讨会组织致辞

• DOI: 10.1109/ipdpsw59300.2023.00048
• 发表时间: 2023-05
• 期刊: 2023 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW
• 作者: Bogaerts, Steven;Prasad, Sushil K
• 通讯作者: Prasad, Sushil K

4 th Workshop on Education for High Performance Computing

第四届高性能计算教育研讨会

• DOI: 10.1109/hipcw57629.2022.00016
• 发表时间: 2022-12
• 期刊: IEEE
• 作者: Prasad, Sushil K.;Ghafoor, Sheikh;Kuvelkar, Ashish;Malakar, Preeti
• 通讯作者: Malakar, Preeti

NSF/IEEE-TCPP Curriculum on Parallel and Distributed Computing for Undergraduates - Version II - Big Data, Energy, and Distributed Computing

NSF/IEEE-TCPP 本科生并行和分布式计算课程 - 第二版 - 大数据、能源和分布式计算

• DOI: 10.1145/3545947.3569594
• 发表时间: 2022-03
• 期刊: ACM
• 作者: Prasad, Sushil;Weems, Charles;Sussman, Alan;Gupta, Anshul;Estrada, Trilce;Vaidyanathan, Ramachandran;Ghafoor, Sheikh;Kant, Krishna;Stunkel, Craig
• 通讯作者: Stunkel, Craig