Extending access to HPC skills through a blended online course

Steven I. Gordon, James Demmel, Lizanne Destefano, Lorna Rivera

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Extending expertise in parallel computing is critical to all those using high performance computing to gain insights into science and engineering problems. Many campuses do not offer such a course because of course load limits, a lack of faculty expertise, and/or lack of access to appropriate computing resources. MOOCs for this type of course are difficult to scale both because of constraints on computing resources as well as the need for individual attention with programming problems. Using a blended online course with collaborating faculty that offer academic credit for their students, we have been able to facilitate course participation at many institutions that might not otherwise have covered the topic. This has had a significant benefit for both the faculty and students. Our paper summarizes the nature of these impacts and offers some insights on best practices for extending technical courses to multiple institutions.

Original languageEnglish (US)
Title of host publicationProceedings of the XSEDE 2015 Conference
Subtitle of host publicationScientific Advancements Enabled by Enhanced Cyberinfrastructure
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450337205
DOIs
StatePublished - Jul 26 2015
Event4th Annual Conference on Extreme Science and Engineering Discovery Environment, XSEDE 2015 - St. Louis, United States
Duration: Jul 26 2015Jul 30 2015

Publication series

NameACM International Conference Proceeding Series
Volume2015-July

Other

Other4th Annual Conference on Extreme Science and Engineering Discovery Environment, XSEDE 2015
Country/TerritoryUnited States
CitySt. Louis
Period7/26/157/30/15

Keywords

  • High performance computing
  • Online learning
  • Parallel programming

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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