Impact of Blue Waters Education and Training

William Kramer, Scott Lathrop, Steven I. Gordon, Robert M. Panoff, Aaron Weeden, and Lizanne DeStefano

Volume 13, Issue 2 (December 2022), pp. 21–30

https://doi.org/10.22369/issn.2153-4136/13/2/5

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BibTeX
@article{jocse-13-2-5,
  author={William Kramer and Scott Lathrop and Steven I. Gordon and Robert M. Panoff and Aaron Weeden and Lizanne DeStefano},
  title={Impact of Blue Waters Education and Training},
  journal={The Journal of Computational Science Education},
  year=2022,
  month=dec,
  volume=13,
  issue=2,
  pages={21--30},
  doi={https://doi.org/10.22369/issn.2153-4136/13/2/5}
}
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The Blue Waters proposal to NSF, entitled "Leadership-Class Scientific and Engineering Computing: Breaking Through the Limits," identified education and training as essential components for the computational and data analysis research and education communities. The Blue Waters project began in 2007, the petascale computing system began operations on March 28, 2013, and the system served the community longer than originally planned as it was decommissioned in January 2022. This paper contributes to the Blue Waters project's commitment to document the lessons learned and longitudinal impact of its activities. The Blue Waters project pursued a broad range of workforce development activities to recruit, engage, and support a diverse mix of students, educators, researchers, and developers across the U.S. The focus was on preparing the current and future workforce to contribute to advancing scholarship and discovery using computational and data analytics resources and services. Formative and summative evaluations were conducted to improve the activities and track the impact. Many of the lessons learned have been implemented by the National Center for Supercomputing Applications (NCSA) and the New Frontiers Initiative (NFI) at the University of Illinois, and by other organizations. We are committed to sharing our experiences with other organizations that are working to reproduce, scale up, and/or sustain activities to prepare the computational and data analysis workforce.