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REU SITE: Computer Systems Research in High Performance Cloud Computing Environments

REU SITE: Computer Systems Research in High Performance Cloud Computing Environments
REU 站点:高性能云计算环境中的计算机系统研究
批准号:
1005153
负责人:
Michael Lewis
金额:
$33.19万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2010
资助国家:
美国
项目状态:
已结题
起止时间:
2010-04-01 至 2014-03-31

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中文摘要
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英文摘要
Binghamton University in general, and its Computer Science (CS) Department in particular, are successfully complementing an outstanding reputation for undergraduate education with vibrant and growing graduate-level research programs. This combination provides fertile ground for an outstanding NSF REU Site in experimental computer systems research. Each summer, the Binghamton CISE REU Site attracts ten top undergraduate students from a wide variety of CS and Computer Engineering departments across the country. Participants include (i) students from under-represented groups, (ii) women, and (iii) students with limited local access to graduate-level research programs in their home institutions. Students immerse themselves in intensive high-quality research projects directed by one or more CS Faculty Research Mentors at Binghamton, for a ten week period in the summer.Binghamton's CISE REU Site exposes students to high-quality computer systems research, trains them to be effective researchers, and influences them through exciting and positive experiences to continue to pursue a research-oriented career path, including graduate study both at Binghamton and at other universities. As part of the REU experience, students write research-style papers and make public conference-style presentations in Binghamton's CS Department. In preparing to do so, the students make significant contributions to the department's research programs.Departmental research areas of expertise (and therefore potential areas for REU student projects) include computer architecture, energy-aware computing, graphics and image computing, virtualization, Internet search and information retrieval, security, cloud and grid computing, circuit design, algorithmic optimization, data mining, mobile and sensor networks, and more. The program includes an effective evaluation strategy carried out by a local educational evaluation expert. The combination of a high quality research environment, dedicated and talented Faculty Research Mentors, and a feedback loop driven by this evaluation professional, ensure the strong intellectual merit of the proposed activity.
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