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: Texas State University - San Marcos
• 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
• 起止时间: 2013-10-01 至 2018-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1305302&HistoricalAwards=false
• 关键词: II; NEW; Shared; Performance; Data

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.

数据的创建、管理和访问是计算机科学发展的关键。目前，社交网络、Web挖掘、多媒体检索和高性能计算等领域的许多研究和教育活动都需要涉及大数据。德州州立大学福尔斯计算机科学系现有的基础设施远远不能满足其日益增长的科研和教学需求，本项目构建了一个共享的高性能数据中心，为收集、处理和管理大量数据提供基础设施。新的数据中心提供必要的计算能力和存储，以支持在计算机视觉，无线网络，信息检索，数据挖掘，人机交互，软件工程，高性能计算和安全等领域的部门内外的新研究和技术的探索和开发。该数据中心还支持高质量的本科生和研究生研究体验，实现研究与教育的整合，鼓励跨部门和跨大学的合作，并促进博士学位。计算机科学系的程序开发。发达的基础设施将显着提高部门，大学和社区目前的研究和教育能力。

项目成果

Evaluating the impact of data layout and placement on the energy efficiency of heterogeneous applications

评估数据布局和放置对异构应用程序能效的影响

• DOI: 10.1109/igcc.2017.8323574
• 发表时间: 2017
• 期刊: 2017 Eighth International Green and Sustainable Computing Conference (IGSC
• 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;
• 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;
• 作者: Saha, Biplab Kumar;Connors, Tiffany A.;Rahman, Saami;Qasem, Apan
• 通讯作者: Qasem, Apan