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II-NEW: Shared High Performance Data Center

II-NEW: Shared High Performance Data Center
II-新:共享高性能数据中心
批准号:
1305302
负责人:
Yijuan Lu
金额:
$37.58万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2013
资助国家:
美国
项目状态:
已结题
起止时间:
2013-10-01 至 2018-09-30

项目摘要

项目成果

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中文摘要
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英文摘要
The creation, management, and access of data is key to the advancement of the state-of-the-art in computer science. Currently many research and educational activities in social network, web mining, multimedia retrieval, and high performance computing, just to name a few, need to involve big data. However, existing infrastructure of the Computer Science Department at Texas State University falls far behind its increasing research and educational needs.This project builds a shared high-performance data center, providing the fundamental facilities to collect, process, and manage large volumes of data. The new data center supplies the necessary computational power and storage to support the exploration and development of new research and technologies within and beyond the department in the fields of computer vision, wireless network, information retrieval, data mining, human computer interaction, software engineering, high performance computing, and security. The data center also supports quality undergraduate and graduate student research experience, enables the integration of research and education, encourages inter-departmental and cross-university collaborations, and promotes the Ph.D. program development in the Computer Science Department. The developed infrastructure will significantly enhance the current research and educational capabilities of the department, university, and community.
期刊论文(3)
专著(0)
科研奖励(0)
会议论文
DOI: 10.1109/igcc.2017.8323574
发表时间: 2017
期刊: 2017 Eighth International Green and Sustainable Computing Conference (IGSC
影响因子: --
作者: [Qasem, Apan, Teich, Samuel]
通讯作者: Teich, Samuel
Automatically Selecting Profitable Thread Block Sizes for Accelerated Kernels
自动为加速内核选择有利可图的线程块大小
DOI: 10.1109/hpcc-smartcity-dss.2017.58
发表时间: 2017
期刊: IEEE 19th International Conference on High Performance Computing and Communications;
影响因子: --
作者: [Connors, Tiffany A., Qasem, Apan]
通讯作者: Qasem, Apan
A Machine Learning Approach to Automatic Creation of Architecture-Sensitive Performance Heuristics
自动创建架构敏感的性能启发式的机器学习方法
DOI: 10.1109/hpcc-smartcity-dss.2017.3
发表时间: 2017
期刊: IEEE 19th International Conference on High Performance Computing and Communications;
影响因子: --
作者: [Saha, Biplab Kumar, Connors, Tiffany A., Rahman, Saami, Qasem, Apan]
通讯作者: Qasem, Apan
II-NEW: Shared High Performance Data Center
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