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

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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 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11887 LNCS, pp. 643–655). Springer. https://doi.org/10.1007/978-3-030-34356-9_49

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