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Toward High Performance Computing Education

Published: 15 June 2020 Publication History

Abstract

High Performance Computing (HPC) is the ability to process data and perform complex calculations at extremely high speeds. Current HPC platforms can achieve calculations on the order of quadrillions of calculations per second with quintillions on the horizon. The past three decades witnessed a vast increase in the use of HPC across different scientific, engineering and business communities, for example, sequencing the genome, predicting climate changes, designing modern aerodynamics, or establishing customer preferences. Although HPC has been well incorporated into science curricula such as bioinformatics, the same cannot be said for most computing programs. This working group will explore how HPC can make inroads into computer science education, from the undergraduate to postgraduate levels. The group will address research questions designed to investigate topics such as identifying and handling barriers that inhibit the adoption of HPC in educational environments, how to incorporate HPC into various curricula, and how HPC can be leveraged to enhance applied critical thinking and problem solving skills. Four deliverables include: (1) a catalog of core HPC educational concepts, (2) HPC curricula for contemporary computing needs, such as in artificial intelligence, cyberanalytics, data science and engineering, or internet of things, (3) possible infrastructures for implementing HPC coursework, and (4) HPC-related feedback to the CC2020 project.

References

[1]
Apache Software Foundation. 2019. Apache Hadoop. https://hadoop.apache.org.
[2]
Didier El Baz. 2014. IoT and the Need for High Performance Computing. In 2014 International Conference on Identification, Information and Knowledge in the Internet of Things. IEEE, Beijing, China, 6. https://doi.org/10.1109/IIKI.2014.8
[3]
Richard Brown, Elizabeth Shoop, Joel Adams, Curtis Clifton, Mark Gardner, Michael Haupt, and Peter Hinsbeeck. 2010. Strategies for Preparing Computer Science Students for the Multicore World. In Proceedings of the 2010 ITiCSE Working Group Reports (ITiCSE-WGR '10). Association for Computing Machinery, New York, NY, USA, 97--115. https://doi.org/10.1145/1971681.1971689
[4]
Rob Farber. 2017. AI-HPC is Happening Now. Technical Report. insideHPC, USA. https://www.intel.com/content/dam/www/public/us/en/documents/white-papers/the-convergence-of-ai-and-hpc.pdf.
[5]
Tony Hey, Stewart Tansley, and Kristin M. Tolle (Eds.). 2009. The Fourth Paradigm: Data-Intensive Scientific Discovery .Microsoft Research, Redmond, Washington. http://research.microsoft.com/en-us/collaboration/fourthparadigm/
[6]
Scott Lathrop. 2016. A Call to Action to Prepare the High-Performance Computing Workforce. Computing in Science Engineering, Vol. 18, 6 (Nov 2016), 80--83. https://doi.org/10.1109/MCSE.2016.101
[7]
Scott Lathrop and Thomas Murphy. 2008. High-Performance Computing Education. Computing in Science Engineering, Vol. 10, 5 (Sep. 2008), 9--11. https://doi.org/10.1109/MCSE.2008.132
[8]
Raffael Marty. 2013. Cyber Security: How Visual Analytics Unlock Insight. In Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD '13). Association for Computing Machinery, New York, NY, USA, 1139. https://doi.org/10.1145/2487575.2491132
[9]
NetApp, Inc. 2019. What Is High-Performance Computing? https://www.netapp.com/us/info/what-is-high-performance-computing.aspx.
[10]
Esteban Perez-Wohlfeil, Oscar Torreno, Louisa J. Bellis, Pedro L. Fernandes, Brane Leskosek, and Oswaldo Trelles. 2018. Training Bioinformaticians in High Performance Computing. Heliyon, Vol. 4, 12 (2018), 18. https://doi.org/10.1016/j.heliyon.2018.e01057
[11]
Dimitri Perrin, Marija Bezbradica, Martin Crane, Heather J. Ruskin, and Christophe Duhamel. 2012. High-Performance Computing for Data Analytics. In 2012 IEEE/ACM 16th International Symposium on Distributed Simulation and Real Time Applications. IEEE, New York, 234--242. https://doi.org/10.1109/DS-RT.2012.41
[12]
Rajendra K. Raj, Allen Parrish, John Impagliazzo, Carol J. Romanowski, Sherif G. Aly, Casey C. Bennett, Karen C. Davis, Andrew McGettrick, Teresa Susana Mendes Pereira, and Lovisa Sundin. 2019. An Empirical Approach to Understanding Data Science and Engineering Education. In Proceedings of the Working Group Reports on Innovation and Technology in Computer Science Education (ITiCSE-WGR '19). Association for Computing Machinery, New York, NY, USA, 73--87. https://doi.org/10.1145/3344429.3372503
[13]
Daniel A. Reed and Jack Dongarra. 2015. Exascale Computing and Big Data. Commun. ACM, Vol. 58, 7 (June 2015), 56--68. https://doi.org/10.1145/2699414
[14]
Shayan Shams, Richard Platania, Kisung Lee, and Seung-Jong Park. 2017. Evaluation of Deep Learning Frameworks Over Different HPC Architectures. In 2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS). IEEE, New York, 1389--1396. https://doi.org/10.1109/ICDCS.2017.259

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cover image ACM Conferences
ITiCSE '20: Proceedings of the 2020 ACM Conference on Innovation and Technology in Computer Science Education
June 2020
615 pages
ISBN:9781450368742
DOI:10.1145/3341525
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Published: 15 June 2020

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Author Tags

  1. HPC
  2. computer science education
  3. contemporary computing education
  4. high performance computing
  5. high-performance computing curricula
  6. iticse working group

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