Teaching High–performance Computing Systems – A Case Study with Parallel Programming APIs: MPI, OpenMP and CUDA
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-63783-4_29
Reference34 articles.
1. Adams, J., Brown, R., Shoop, E.: Patterns and exemplars: compelling strategies for teaching parallel and distributed computing to CS undergraduates. In: 2013 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Ph.d. Forum, pp. 1244–1251 (2013). https://doi.org/10.1109/IPDPSW.2013.275
2. Al-Jody, T., Aagela, H., Holmes, V.: Inspiring the next generation of HPC engineers with reconfigurable, multi-tenant resources for teaching and research. Sustainability 13(21), 11782 (2021). https://doi.org/10.3390/su132111782
3. Alvarez, L., Ayguade, E., Mantovani, F.: Teaching HPC systems and parallel programming with small-scale clusters. In: 2018 IEEE/ACM Workshop on Education for High-Performance Computing (EduHPC), pp. 1–10 (2018).https://doi.org/10.1109/EduHPC.2018.00004
4. Ben-Nun, T., Hoefler, T.: Demystifying parallel and distributed deep learning: an in-depth concurrency analysis. ACM Comput. Surv. 52(4), 3320060 (2019). https://doi.org/10.1145/3320060
5. Bernreuther, M., Brenk, M., Bungartz, H.J., Mundani, R.P., Muntean, I.L.: Teaching high-performance computing on a high-performance cluster. In: Sunderam, V.S., van Albada, G.D., Sloot, P.M.A., Dongarra, J.J. (eds.) Computational Science - ICCS 2005, pp. 1–9. Springer, Heidelberg (2005). https://doi.org/10.1007/11428848_1
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