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REU Site : Research Experiences in Computational Science, Engineering, and Mathematics (RECSEM)

REU 网站：计算科学、工程和数学的研究经验 (RECSEM)

基本信息

批准号：
1659502
负责人：
Kwai Wong
金额：
$ 35.94万
依托单位：
University of Tennessee Knoxville
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2017
资助国家：
美国
起止时间：
2017-05-15 至 2020-12-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1659502&HistoricalAwards=false
关键词：
REU Site Research Experiences Computational

项目摘要

The Research Experiences in Computational Science, Engineering, and Mathematics (RECSEM) REU site program at the University of Tennessee (UTK) directs a group of ten undergraduate students to explore the emergent interdisciplinary computational science models and techniques via a number of cohesive compute and data intensive applications. The RECSEM program complements the growing importance of computational sciences in many advanced degree programs and provides scientific understanding and discovery to undergraduates with an intellectual focus on research projects using high performance computing (HPC). This program aims to deliver a real-world research experience to the students by partnering with teams of scientists engaged in scientific computing research at the National Institutes of Computational Sciences (NICS), the Innovative Computing Laboratory (ICL), and the Joint Institute for Computational Sciences (JICS) at UTK and Oak Ridge National Laboratory. Additional international students supported by PI's partner universities in Hong Kong also participate in this program. Together the students of RECSEM work collaboratively to achieve their research tasks, and at the same time share a unique opportunity for trading academic experiences, scientific ideas, and cultural social activities in this ten week long program. Thus, this REU site program supports the NSF's mission to promote the progress of science and to advance the national prosperity.This program is organized around a synergetic theme of ideas and practices those are common to many scientific applications. The research projects are categorized in three interrelated areas of research interests: engineering applications, numerical mathematics, and linear algebraic software and tools. The scope of work for these projects put emphasis on conducting software development, model implementation, and design and evaluation of numerical experiments under the guidance of a team of experts in each scientific domain. Projects include computation in multi-scale materials science and biomechanics applications, simulation of traffic flow phenomena, implementation of high order parallel numerical schemes, and processing of images with different techniques and algorithms of machine learning and data analytics. The students would have opportunities to perform large-scale scientific simulations on HPC clusters as well as world-class state-of-the-art supercomputers equipped with the latest hardware technologies provided by the Extreme Science and Engineering Discovery Environment (XSEDE) organization. These latest computing units include graphical processing units (GPUs), multicore processors and the Intel Xeon Phi processors (MIC). This program is organized in four major stages: HPC training, research formulation, project action, and scientific reporting. These stages aim to gradually assist the students towards finishing their research projects in time with appropriate level of motivation and guidance.

田纳西大学（UTK）的计算科学，工程和数学（RECSEM）REU站点计划的研究经验指导一组十名本科生通过一些有凝聚力的计算和数据密集型应用程序探索新兴的跨学科计算科学模型和技术。RECSEM计划补充了计算科学在许多高级学位课程中日益增长的重要性，并为本科生提供了科学的理解和发现，重点是使用高性能计算（HPC）的研究项目。该计划旨在通过与美国国立计算科学研究院（NICS），创新计算实验室（ICL）以及UTK和橡树岭国家实验室的计算科学联合研究所（JICS）的科学家团队合作，为学生提供真实的研究体验。由PI在香港的合作大学支持的其他国际学生也参加了这个计划。RECSEM的学生一起合作，以实现他们的研究任务，并在同一时间分享一个独特的机会，在这个为期十周的计划交易学术经验，科学思想和文化社会活动。因此，该REU站点计划支持NSF的使命，以促进科学的进步和促进国家的繁荣。该计划是围绕协同主题的思想和实践，这些是共同的许多科学应用。研究项目分为三个相互关联的研究领域：工程应用，数值数学和线性代数软件和工具。这些项目的工作范围侧重于在每个科学领域的专家小组的指导下进行软件开发、模型实施以及数值实验的设计和评价。项目包括多尺度材料科学和生物力学应用中的计算，交通流现象的模拟，高阶并行数值方案的实现，以及使用机器学习和数据分析的不同技术和算法处理图像。学生将有机会在HPC集群以及配备了极限科学与工程发现环境（XSEDE）组织提供的最新硬件技术的世界一流的最先进的超级计算机上进行大规模科学模拟。这些最新的计算单元包括图形处理单元（GPU）、多核处理器和英特尔至强融核处理器（MIC）。该计划分为四个主要阶段：HPC培训，研究制定，项目行动和科学报告。这些阶段旨在通过适当的动机和指导，逐步帮助学生及时完成研究项目。

项目成果

期刊论文数量（8）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Project-Based Research and Training in High Performance Data Sciences, Data Analytics, and Machine Learning

高性能数据科学、数据分析和机器学习领域基于项目的研究和培训

DOI：
10.22369/issn.2153-4136/11/1/7
发表时间：
2020
期刊：
The Journal of Computational Science Education
影响因子：
0
作者：
Wong, Kwai;Tomov, Stanimire;Dongarra, Jack
通讯作者：
Dongarra, Jack

MagmaDNN: Accelerated Deep Learning Using MAGMA

DOI：
10.1145/3332186.3333047
发表时间：
2019-07
期刊：
Proceedings of the Practice and Experience in Advanced Research Computing on Rise of the Machines (learning)
影响因子：
0
作者：
Daniel Nichols;Kwai Wong;S. Tomov;Lucien Ng;Sihan Chen;Alexander Gessinger
通讯作者：
Daniel Nichols;Kwai Wong;S. Tomov;Lucien Ng;Sihan Chen;Alexander Gessinger

Brain connectivity evaluation during selective attention using EEG-based brain-computer interface