REU Site : Research Experiences in Computational Science, Engineering, and Mathematics (RECSEM)
REU Site : Research Experiences in Computational Science, Engineering, and Mathematics (RECSEM)
批准号:
1659502
负责人:
Kwai Wong
金额:
$35.94万
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
项目状态:
已结题
起止时间:
2017-05-15 至 2020-12-31
中文摘要
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.
英文摘要
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.
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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:
--
作者:
[Wong, Kwai, Tomov, Stanimire, Dongarra, Jack]
通讯作者:
Dongarra, Jack
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:
--
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
DOI:
10.1080/2326263x.2019.1651186
发表时间:
2019-01-01
期刊:
BRAIN-COMPUTER INTERFACES
影响因子:
2.1
作者:
[Borhani, Soheil, Abiri, Reza, Zhao, Xiaopeng]
通讯作者:
Zhao, Xiaopeng
DOI:
10.1177/0361198119838261
发表时间:
2019-05
期刊:
Transportation Research Record
影响因子:
1.7
作者:
[Siyue Yang;C. Brakewood;Virgile Nicolas;Jake Sion]
通讯作者:
Siyue Yang;C. Brakewood;Virgile Nicolas;Jake Sion
DOI:
10.1007/978-3-030-34356-9_37
发表时间:
2019-06
期刊:
影响因子:
--
作者:
[Daniel Nichols;N. Tomov;Frank Betancourt;S. Tomov;Kwai Wong;J. Dongarra]
通讯作者:
Daniel Nichols;N. Tomov;Frank Betancourt;S. Tomov;Kwai Wong;J. Dongarra
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