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

该补助金为加州大学圣地亚哥分校（UCSD）圣地亚哥超级计算机中心（SDSC）工程专业研究生的实习和指导计划提供资金。该项目旨在鼓励博士生将竞争情报工具纳入他们的研究，并建立同行社区，以进一步扩大竞争情报工具在其领域的使用。在介绍性研讨会之后，涵盖了CI工具在研究中的广泛应用和使用，工程研究生将与SDSC的科学家在工程和并行编程方面的专业知识配对。 他们的暑期实习将专注于探索和适应CI和高性能计算（HPC）工具，以用于学生的论文研究。 电子辅导将持续整个学年，最终在2008年春季为教师，导师，学生同行和NSF项目官员强调实习结果的学生演讲。 再加上通过生物学的平行奖，该项目允许两个模型的评估，介绍研究生CI和HPC资源适用于他们的研究。这两种模式将比较的可扩展性，成功地建立研究生的CI技能，并能够创建一个持续的社区的同行。如果该计划成功，研究生将要求分配国家的科学HPC资源，将高性能计算纳入他们的论文研究，并在返回家乡机构时与教授和同学分享他们的新CI知识。此外，实习生团队将形成基于领域的实践社区，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NSF确定最具成本效益的方法来培养科学和工程领域的精通CI的研究人员。进一步实习计划的结果和建议将在全国TeraGrid合作伙伴组织中分享。

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.