MRI: Acquisition of High-Performance Distributed Computing and Storage Infrastructure at UTA

EIA-0216500Sharma ChakravartyYuksel A.作者声明：J. Das; Lawrence B.保持器; Jakhoon YuTexas ArlingtonMRI：收购高性能分布式计算和存储基础设施的建议，获得高性能计算和存储基础设施，旨在满足需要分布式和并行计算资源的几个团体的研究需求。 涉及UTA的计算机科学与工程（CSE）和物理学系以及UT西南医学院的皮肤科的合作，研究工作包括：a.数据库和数据挖掘（例如，搜索的可视化），B.软件工程（例如，形式方法），c.物理学（例如，高能物理学-HEP-实验），d.皮肤病学（例如，图像数据库/皮肤损伤分析），e.分布式计算（例如，调度，信息电网上的负载平衡），和f.联网（例如，无线、光学;模拟）。关键特征包括：a.通用设备和基础设施的多学科使用，B.多机构共享设备，C。加强当前的研究工作，创造新的协同效应，从而产生新的研究思路。将Internet 2的高带宽与高性能计算和存储基础设施相结合，以促进大型图像数据库和视频流研究，并从校园外访问大量实验数据。预计将通过增强至少40名CS和10名物理学生以及15名教师以跨学科模式使用资源的经验来产生教育影响。 联合活动应促成高质量的跨学科研究，并通过合作加以促进。

EIA-0216500Sharma ChakravarthyYuksel A. Aslandogan; Sajal K. Das; Lawrence B. Holder; Jachoon YuUniversity of Texas ArlingtonMRI: Acquisition of High Performance Distributed Computing and Storage Infrastructure at UTAThis proposal, acquiring high-performance computing and storage infrastructure, aims to satisfy the research needs of several groups that require distributed and parallel computing resources. Involving collaboration from the departments of Computer Science and Engineering (CSE) and Physics at UTA, and Dermatology at UT Southwestern Medical School, the research efforts include:a. Database and Data Mining (e.g., visualization of search),b. Software Engineering (e.g., formal methods),c. Physics (e.g., high energy physics -HEP- experiments),d. Dermatology (e.g., image database/analysis of skin lesion), e. Distributed Computing (e.g., scheduling, load balancing on Information Power Grid), andf. Networking (e.g., wireless, optical; simulations).The key characteristics involve:a. Multi-disciplinary use of common equipment and infrastructure,b. Multi-institutional sharing of equipment,c. Enhancing current-research efforts and creating new synergy leading to new research ideas,d. Combining the high-bandwith of Internet 2 with high-performance computing and storage infrastructure to facilitate large image databases and video streaming research, and access to vast amounts of experimental data from outside the campus.Educational impact is expected by enhancing the experiences of at least 40 CS and 10 physics students and 15 faculty using the resource in an interdisciplinary mode. Joint activities should lead to high quality of inter-disciplinary research fostered by the collaboration.