Hands-On Research and Training in High Performance Data Sciences, Data Analytics, and Machine Learning for Emerging Environments

Kwai Wong; Stanimire Tomov; Jack Dongarra

doi:10.1007/978-3-030-34356-9_49

Hands-On Research and Training in High Performance Data Sciences, Data Analytics, and Machine Learning for Emerging Environments

Kwai Wong, Stanimire Tomov, Jack Dongarra

Computer Science and Mathematics Div

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

This paper describes a hands-on Research Experiences for Computational Science, Engineering, and Mathematics (RECSEM) program in high-performance data sciences, data analytics, and machine learning on emerging computer architectures. RECSEM is a Research Experiences for Undergraduates (REU) site program supported by the USA National Science Foundation. This site program at the University of Tennessee (UTK) directs a group of ten undergraduate students to explore, as well as contribute to the emergent interdisciplinary computational science models and state-of-the-art HPC techniques via a number of cohesive compute and data intensive applications in which numerical linear algebra is the fundamental building block.

Original language	English
Title of host publication	High Performance Computing - ISC High Performance 2019 International Workshops, Revised Selected Papers
Editors	Michèle Weiland, Guido Juckeland, Sadaf Alam, Heike Jagode
Publisher	Springer
Pages	643-655
Number of pages	13
ISBN (Print)	9783030343552
DOIs	https://doi.org/10.1007/978-3-030-34356-9_49
State	Published - 2019
Event	34th International Conference on High Performance Computing, ISC High Performance 2019 - Frankfurt, Germany Duration: Jun 16 2019 → Jun 20 2019

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11887 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	34th International Conference on High Performance Computing, ISC High Performance 2019
Country/Territory	Germany
City	Frankfurt
Period	06/16/19 → 06/20/19

Funding

This work was conducted at the Joint Institute for Computational Sciences (JICS), sponsored by the National Science Foundation (NSF), through NSF REU Award #1262937 and #1659502, with additional Support from the University of Tennessee, Knoxville (UTK), and the National Institute for Computational Sciences (NICS). This work used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation grant number ACI-1548562. Computational Resources are available through a XSEDE education allocation award TG-ASC170031.

Keywords

Computational science
Data analytics
Educational outreach
HPC
Hands-on experiences and education
Machine learning (ML)
Research Experiences for Undergraduates

Access to Document

10.1007/978-3-030-34356-9_49

Cite this

Wong, K., Tomov, S., & Dongarra, J. (2019). Hands-On Research and Training in High Performance Data Sciences, Data Analytics, and Machine Learning for Emerging Environments. In M. Weiland, G. Juckeland, S. Alam, & H. Jagode (Eds.), High Performance Computing - ISC High Performance 2019 International Workshops, Revised Selected Papers (pp. 643-655). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11887 LNCS). Springer. https://doi.org/10.1007/978-3-030-34356-9_49

Wong, Kwai ; Tomov, Stanimire ; Dongarra, Jack. / Hands-On Research and Training in High Performance Data Sciences, Data Analytics, and Machine Learning for Emerging Environments. High Performance Computing - ISC High Performance 2019 International Workshops, Revised Selected Papers. editor / Michèle Weiland ; Guido Juckeland ; Sadaf Alam ; Heike Jagode. Springer, 2019. pp. 643-655 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "This paper describes a hands-on Research Experiences for Computational Science, Engineering, and Mathematics (RECSEM) program in high-performance data sciences, data analytics, and machine learning on emerging computer architectures. RECSEM is a Research Experiences for Undergraduates (REU) site program supported by the USA National Science Foundation. This site program at the University of Tennessee (UTK) directs a group of ten undergraduate students to explore, as well as contribute to the emergent interdisciplinary computational science models and state-of-the-art HPC techniques via a number of cohesive compute and data intensive applications in which numerical linear algebra is the fundamental building block.",

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Wong, K, Tomov, S & Dongarra, J 2019, Hands-On Research and Training in High Performance Data Sciences, Data Analytics, and Machine Learning for Emerging Environments. in M Weiland, G Juckeland, S Alam & H Jagode (eds), High Performance Computing - ISC High Performance 2019 International Workshops, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11887 LNCS, Springer, pp. 643-655, 34th International Conference on High Performance Computing, ISC High Performance 2019, Frankfurt, Germany, 06/16/19. https://doi.org/10.1007/978-3-030-34356-9_49

Hands-On Research and Training in High Performance Data Sciences, Data Analytics, and Machine Learning for Emerging Environments. / Wong, Kwai; Tomov, Stanimire; Dongarra, Jack.
High Performance Computing - ISC High Performance 2019 International Workshops, Revised Selected Papers. ed. / Michèle Weiland; Guido Juckeland; Sadaf Alam; Heike Jagode. Springer, 2019. p. 643-655 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11887 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Wong K, Tomov S, Dongarra J. Hands-On Research and Training in High Performance Data Sciences, Data Analytics, and Machine Learning for Emerging Environments. In Weiland M, Juckeland G, Alam S, Jagode H, editors, High Performance Computing - ISC High Performance 2019 International Workshops, Revised Selected Papers. Springer. 2019. p. 643-655. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-34356-9_49

Hands-On Research and Training in High Performance Data Sciences, Data Analytics, and Machine Learning for Emerging Environments

Abstract

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Keywords

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