CRI: IAD Acquisition of a Cluster and High Performance Storage for data-intensive applications in Materials Science, Power Systems and Systems Biology

CRI：IAD 收购集群和高性能存储，用于材料科学、电力系统和系统生物学中的数据密集型应用

基本信息

批准号：
0751157
负责人：
Srinivas Aluru
金额：
$ 71.9万
依托单位：
Iowa State University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2008
资助国家：
美国
起止时间：
2008-03-15 至 2011-02-28
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=0751157&HistoricalAwards=false
关键词：
CRI IAD Acquisition Cluster Performance

项目摘要

This project supports the acquisition of a high performance cluster and storage system for data-intensive applications in materials science, electrical power systems and systems biology. In materials science, the investigators will develop methods to analyze data from the LEAP atom probe tomography, and find ways to understand material properties from the arrangement of its constitute atoms. This new instrumentation is increasingly being adopted by materials scientists, and the project will provide an archive for such data and develop analysis tools. In power systems, the researchers will investigate improving the security, reliability and efficiency of national energy infrastructure by utilizing high-performance computing for complex system analysis in energy control centers. In systems biology, the investigators will collectively analyze large-scale gene expression data from experiments conducted worldwide to build robust gene networks. These research efforts will lead to significant advances in the penetration of high performance computing technology in materials science, power systems research, and molecular biology. The project will bring together multiple departments and research centers at Iowa State University and further enrich interdisciplinary culture and training opportunities.A number of students will be trained in computation-centric interdisciplinary research.

该项目支持采购高性能集群和存储系统，用于材料科学、电力系统和系统生物学中的数据密集型应用。在材料科学领域，研究人员将开发分析 LEAP 原子探针断层扫描数据的方法，并找到从其构成原子的排列来了解材料特性的方法。这种新仪器越来越多地被材料科学家采用，该项目将为此类数据提供档案并开发分析工具。在电力系统中，研究人员将研究通过利用高性能计算在能源控制中心进行复杂系统分析来提高国家能源基础设施的安全性、可靠性和效率。在系统生物学中，研究人员将集体分析来自世界各地进行的实验的大规模基因表达数据，以建立强大的基因网络。这些研究工作将导致高性能计算技术在材料科学、电力系统研究和分子生物学领域的渗透取得重大进展。该项目将汇集爱荷华州立大学多个院系和研究中心，进一步丰富跨学科文化和培训机会。一批学生将接受以计算为中心的跨学科研究培训。