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CyberTraining: Pilot: Fostering Computational Excellence (FOCEX): Addressing the Disconnect between Advanced CyberInfrastructure and Educational Preparedness

CyberTraining: Pilot: Fostering Computational Excellence (FOCEX): Addressing the Disconnect between Advanced CyberInfrastructure and Educational Preparedness
网络培训:试点:促进卓越计算 (FOCEX):解决先进网络基础设施与教育准备之间的脱节
批准号:
2320943
负责人:
Carlos Pantano-Rubino
金额:
$30.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-09-01 至 2025-08-31

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中文摘要
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英文摘要
This project will develop training materials in the form of workshops and teaching kits for students and researchers in science, technology, mathematics, and engineering (STEM) to aid in translating computational research into modern high-end computing platforms. This project addresses the longstanding challenges researchers encounter when working with computing and data-intensive applications that rely on new computing accelerator hardware deployed in modern high-performance computing clusters. The training will focus on computational fluid dynamics (CFD) applications, i.e., predicting the flow around objects like an aircraft. Additionally, the training material will share many common elements with other disciplines and will be easily applicable to other fields besides CFD. The workshop will present general concepts and exemplary code and demonstrate its functionality in a real-world application. An archival and dissemination plan is included in the project, and advertising to a broad audience will be pursued.This project will train a cohort of researchers and students to tackle challenging problems in fluid mechanics by employing state-of-the-art numerical techniques and efficiently utilizing modern heterogeneous computing architectures in advanced cyberinfrastructure (CI). This project has two major components; direct training and teaching facilitation. Direct training will be piloted as a 4-week-long summer school designed program for graduate and undergraduate students with a foundational understanding of CFD and programming. During this program, the participants will gain hands-on intensive training in research CFD pipelines, which include understanding numerical techniques, knowledge of the heterogeneous computing architectures available in advanced CI, and the programming skills needed to effectively utilize them, as well as machine learning and optimization. The training modules will be developed to prepare teaching kits to be distributed to instructors throughout the NSF ACCESS program. The aim is to facilitate the integration of these subjects in different coursework across the nation. The direct training pilot is expected to host students directly while teaching facilitation has the potential to scale up and benefit many more students.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.
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