CIEG: Cyberinfrastructure Experience for Graduate Students in Manufacturing Design and Innovation (NSF Engineering)

这项资助为加州大学圣地亚哥分校（UCSD）圣地亚哥超级计算机中心（SDSC）的工程研究生提供实习和指导计划的资金。该项目旨在鼓励博士生将CI工具纳入他们的研究，并建立同行社区，以进一步扩大CI工具在其领域的使用。在介绍CI工具在研究中的广泛应用和使用之后，工程研究生将与具有工程和并行编程专业知识的SDSC科学家配对。他们的暑期实习将专注于为学生的论文研究探索和调整CI和高性能计算（HPC）工具。电子指导将持续整个学年，并在2008年春季学生向教师、导师、学生同伴和NSF项目官员展示实习成果时达到高潮。再加上通过生物学获得的平行奖项，该项目允许评估两种模式，以向研究生介绍适用于其研究的CI和HPC资源。这两种模式将在可扩展性、培养研究生CI技能的成功程度以及创建持续的同伴社区的能力方面进行比较。如果该项目成功，研究生将申请国家科学高性能计算资源的分配，将高性能计算纳入他们的论文研究，并在他们回到家乡的机构时与他们的教授和同学分享他们新的CI知识。此外，实习生团队将形成基于领域的实践社区，这将鼓励其他人探索CI工具在该领域的价值。比较两种实习模式的结果将有助于美国国家科学基金会确定培养科学和工程领域精通ci的研究人员的最具成本效益的方法。进一步实习项目的结果和建议将在全国TeraGrid合作组织中分享。

This grant provides funding for an internship and mentoring program for graduate students in engineering at the San Diego Supercomputer Center (SDSC) at the University of California, San Diego (UCSD). The project is designed to encourage doctoral students to incorporate CI tools in their research and to build peer communities to further expand the use of CI tools in their field. Following an introductory workshop covering the wide applications and uses of CI tools in research, engineering graduate students will be paired with scientists at SDSC with expertise in engineering and parallel programming. Their summer internships will focus on exploring and adapting CI and high performance computing (HPC) tools for the student's thesis research. E-mentoring will continue through the academic year, culminating with student presentations in spring 2008 for faculty, mentors, student peers, and NSF program officers highlighting internship results. Coupled with a parallel award through Biology, this project allows evaluation of two models for introducing graduate students to CI and HPC resources applicable to their research. The two models will be compared for scalability, success in building graduate students' CI skills, and ability to create a sustained community of peers. If the program is successful, graduate students will request allocations on the nation's scientific HPC resources, incorporate high performance computing into their thesis research, and share their new CI knowledge with their professors and fellow students when they return to their home institutions. Additionally, the teams of interns will form domain-based communities of practice that will encourage others to explore the value of CI tools for the field. Comparison of the two internship models' results will help NSF determine the most cost effective approach to building CI-savvy researchers in science and engineering. Results and recommendations for further internship programs will be shared throughout the national TeraGrid partner organizations.