Abstract
High-performance computing (HPC) has become a strategic resource that drives innovation and economic growth. In addition, it is important to educate a workforce with advanced computational skills to maintain economic competitiveness. In this project, we studied 133 domestic and international university HPC centers to understand the status of HPC. Diverse operating models have been identified and analyzed. To explore the need for and challenges associated with HPC within Wisconsin, faculty and students within the University of Wisconsin System and personnel in local industries were surveyed; in addition, we engaged in conversations with university leaders and officials from government agencies. A strong need for HPC resources has been identified, as well as several serious challenges. A state-wide initiative, the Wisconsin Big Data Alliance, which requires legislative support, is recommended as the platform to foster public–private partnerships, drive scientific and technological innovations, and promote workforce development, leading to an efficient usage of computing resources.
Similar content being viewed by others
Data availability
The authors declare that the data supporting the findings of this study are available within the paper and its Supplementary Information files.
References
Adenaike, O., Olabanjo, O. E., & Adedeji, A. A. (2023) Integrating computational skills in undergraduate microbiology curricula in developing countries. Biology Methods and Protocols, 8. https://doi.org/10.1093/biomethods/bpad008
Al-Jody, T., Aagela, H., & Holmes, V. (2021). Inspiring the next generation of hpc engineers with reconfigurable, multi-tenant resources for teaching and research. Sustainability (switzerland),13, 11782. https://doi.org/10.3390/su132111782
Bethune, I., Carter, A., Guo, X., & Korosoglou, P. (2012). Million atom KS-DFT with CP2K partnership for advanced computing in Europe. https://era.ed.ac.uk/handle/1842/6543
Chaudhury, B., Varma, A., Keswani, Y., Bhatnagar, Y., & Parikh, S. (2018). Let’s HPC: A web-based platform to aid parallel, distributed and high performance computing education. Journal of Parallel Distributed Computing,118, 213–232. https://doi.org/10.1016/j.jpdc.2018.03.001
Chen, S., He, Z., Han, X., He, X., Li, R., Zhu, H., Zhao, D., Dai, C., Zhang, Y., Lu, Z., Chi, X., & Niu, B. (2019). How big data and high-performance computing drive brain science. Genomics, Proteomics & Bioinformatics,17, 381–392. https://doi.org/10.1016/j.gpb.2019.09.003
Cui, S., Wang, Y., Li, L., Peng, X., & Yalvac, B. (2016). Introducing high performance computing to undergraduate students. Computers in Education Journal, 16. https://doi.org/10.18260/p.25453.
Ezell, S. J., & Atkinson, R. D. (2016). The vital importance of high- performance computing to US competitiveness (pp. 1–58). ITIF. https://itif.org/publications/2016/04/28/vital-importance-high-performance-computing-us-competitiveness/
Fernández, Á., Fernández, C., Miguel-Dávila, J. Á., & Conde, M. (2021). Integrating supercomputing clusters into education: A case study in biotechnology. J. Supercomp.,77, 240–253. https://doi.org/10.1007/s11227-020-03360-5
Fossum, C., Laatsch, B., Lowater, H., Narkiewicz-Jodko, A., Lonzarich, L., Hati, S., & Bhattacharyya, S. (2022). Pre-Existing oxidative stress creates a docking-ready conformation of the SARS-CoV-2 receptor-binding domain. ACS Bio & Med Chem Au,2, 84–93. https://doi.org/10.1021/acsbiomedchemau.1c00040
Ghosh, A., Kunkel, W., Varghese, A., Ma, Y., Gomes, R., Bhattacharyya, S., Mohr, M., Doss, I., Hebert, J. (2023). Inter-institutional Resource Sharing in Undergraduate HPC Education: Interviews with University Administrators. In SIGCSE 2023 - Proceedings of the 54th ACM Technical Symposium on Computer Science Education. https://doi.org/10.1145/3545945.3569784
Gomes, R., Kamrowski, C., Langlois, J., Rozario, P., Dircks, I., Grottodden, K., Martinez, M., Tee, W. Z., Sargeant, K., LaFleur, C., & Haley, M. (2022a). A comprehensive review of machine learning used to combat COVID-19. Diagnostics,12, 1853. https://doi.org/10.3390/diagnostics12081853
Gomes, R., Kamrowski, C., Mohan, P. D., Senor, C., Langlois, J., & Wildenberg, J. (2022b). Application of deep learning to IVC filter detection from CT Scans. Diagnostics.,12, 2475. https://doi.org/10.3390/diagnostics12102475
Hati, S., & Bhattacharyya, S. (2016). Incorporating modeling and simulations in undergraduate biophysical chemistry course to promote understanding of structure-dynamics-function relationships in proteins. Biochemistry and Molecular Biology Education,44, 140–159. https://doi.org/10.1002/bmb.20942
Heifetz, A. (2024). Accelerating COVID-19 drug discovery with high-performance computing. Methods in Molecular Biology, 2716. https://doi.org/10.1007/978-1-0716-3449-3_19
Hunter, J. (2019). Pedagogy, leading from the middle and digital technologies: Potent forces for STEM education in Australian primary schools. Australian Educational Leader, 41, 6–28.
Karsakov, A., Bilyatdinova, A., & Bezgodov, A. (2015). Improving visualization courses in russian higher education in computational science and high performance computing. Procedia Computer Science. https://doi.org/10.1016/j.procs.2015.11.083
Kruchten, A. E. (2020). A curricular bioinformatics approach to teaching undergraduates to analyze metagenomic datasets using R. Frontiers in Microbiology,11, 578600. https://doi.org/10.3389/fmicb.2020.578600
Lynn, T., Fox, G., Gourinovitch, A., & Rosati, P. (2020). Understanding the determinants and future challenges of cloud computing adoption for high performance computing. Future Internet.,12, 135. https://doi.org/10.3390/FI12080135
Mullen, J., Byun, C., Gadepally, V., Samsi, S., Reuther, A., & Kepner, J. (2017). Learning by doing, high performance computing education in the MOOC era. Journal of Parallel and Distributed Computing,105, 105–117. https://doi.org/10.1016/j.jpdc.2017.01.015
Neelima, B. (2017). High performance computing education in an Indian Engineering Institute. J. Parallel Distrib Comput.,105, 73–82. https://doi.org/10.1016/j.jpdc.2017.01.019
No Author. (2021). Fighting COVID-19 with HPC. Nature Computational Science, 1, 769–770. https://doi.org/10.1038/s43588-021-00180-2
Ponce, M., Spence, E., van Zon, R., & Gruner, D. (2019). Scientific computing, high-performance computing and data science in higher education. Journal of Educational Computing Research,10, 24–31. https://doi.org/10.22369/issn.2153-4136/10/1/5
Pyzer-Knapp, E. O., Pitera, J. W., Staar, P. W. J., Takeda, S., Laino, T., Sanders, D. P., Sexton, J., Smith, J. R., & Curioni, A. (2022). Accelerating materials discovery using artificial intelligence, high performance computing and robotics. NPJ Computational Materials,8, 84. https://doi.org/10.1038/s41524-022-00765-z
Raj, R. K., Romanowski, C. J., Impagliazzo, J., Aly, S. G., Becker, B. A., Chen, J., Ghafoor, S., Giacaman, N., Gordon, S. I., Izu, C., Rahimi, S., Robson, M. P., Thota, N. (2020). High performance computing education: Current challenges and future directions. In ITiCSE-WGR’20, pp. 51–74. https://doi.org/10.1145/3437800.3439203
Samuel, J., Brennan-Tonetta, M., Samuel, Y., Subedi, P., & Smith, J. (2022). Strategies for democratization of supercomputing: Availability, accessibility and usability of high performance computing for education and practice of big data analytics. Journal of Big Data Theoretical Practice,1, 51–65. https://doi.org/10.54116/jbdtp.v1i1.16
Shields, G. C. (2020). Twenty years of exceptional success: The molecular education and research consortium in undergraduate computational chemistry (MERCURY). International Journal of Quantum Chemistry,120, e26274. https://doi.org/10.1002/qua.26274
Shuja, J., Ahmad, R. W., Gani, A., Abdalla Ahmed, A. I., Siddiqa, A., Nisar, K., Khan, S. U., & Zomaya, A. Y. (2017). Greening emerging IT technologies: Techniques and practices. Journal of Internet Services and Applications,8, 9. https://doi.org/10.1186/s13174-017-0060-5
Suhail, S., Zajac, J., Fossum, C., Lowater, H., McCracken, C., Severson, N., Laatsch, B., Narkiewicz-Jodko, A., Johnson, B., Liebau, J., Bhattacharyya, S., & Hati, S. (2020). Role of Oxidative Stress on SARS-CoV (SARS) and SARS-CoV-2 (COVID-19) Infection: A review. Protein Journal.,39, 644–656. https://doi.org/10.1007/s10930-020-09935-8
Townsend-Nicholson, A. (2020). Educating and engaging new communities of practice with high performance computing through the integration of teaching and research: Using technology to transform learning. Interface Focus,10, 20200003. https://doi.org/10.1098/rsfs.2020.0003
Vavilala, V. S. (2020). Combining high-performance hardware, cloud computing, and deep learning frameworks to accelerate physical simulations: Probing the Hopfield network. European Journal of Physics,41, 035802. https://doi.org/10.1088/1361-6404/ab7027
Wozney, A. J., Smith, M. A., Abdrabbo, M., Birch, C. M., Cicigoi, K. A., Dolan, C. C., Gerzema, A. E. L., Hansen, A., Henseler, E. J., LaBerge, B., Leavens, C. M., Le, C. N., Lindquist, A. C., Ludwig, R. K., O’Reilly, M. G., Reynolds, J. H., Sherman, B. A., Sillman, H. W., Smith, M. A., … Bhattacharyya, S. (2022). Evolution of stronger SARS-CoV-2 variants as revealed through the lens of molecular dynamics simulations. Protein Journal.https://doi.org/10.1007/s10930-022-10065-6
Zajac, J., Anderson, H., Adams, L., Wangmo, D., Suhail, S., Almen, A., Berns, L., Coerber, B., Dawson, L., Hunger, A., Jehn, J., Johnson, J., Plack, N., Strasser, S., Williams, M., Bhattacharyya, S., & Hati, S. (2020). Effects of Distal Mutations on Prolyl-Adenylate Formation of Escherichia coli Prolyl-tRNA Synthetase. Protein Journal.,39, 542. https://doi.org/10.1007/s10930-020-09910-3
Acknowledgements
This work was supported in part by in part by Tommy G. Thompson Center on Public Leadership Grant, Madison, WI (project entitled “Exploring Policies to Promote High-Performance Computing in Post-Pandemic Undergraduate Education in Wisconsin”) and by the National Institutes of Health (Grant Number 2R15GM117510-02 to SB).
Date:12/20/2023
Author information
Authors and Affiliations
Corresponding authors
Ethics declarations
Conflict of interest
None.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Below is the link to the electronic supplementary material.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Hebert, J., Hratisch, R., Gomes, R. et al. High-performance computing in undergraduate education at primarily undergraduate institutions in Wisconsin: Progress, challenges, and opportunities. Educ Inf Technol (2024). https://doi.org/10.1007/s10639-024-12582-6
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s10639-024-12582-6