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Introduction to Volume 16 Issue 1
David Joinerpp. 1–1
A brief introduction to this issue of the Journal of Computational Science Education from the editor.
Volume 16 Issue 1 — March 2025
Contents
Integration of Actors in HPC Ecosystems: Transdisciplinarity, Interdisciplinarity and Interactions
Carlos J. Barrios H., Sergio A. Gelvez C., and Luis A. Torres N.pp. 2–6
https://doi.org/10.22369/issn.2153-4136/16/1/1BibTeX
@article{jocse-16-1-1,
author={Carlos J. Barrios H. and Sergio A. Gelvez C. and Luis A. Torres N.},
title={Integration of Actors in HPC Ecosystems: Transdisciplinarity, Interdisciplinarity and Interactions},
journal={The Journal of Computational Science Education},
year=2025,
month=mar,
volume=16,
issue=1,
pages={2--6},
doi={https://doi.org/10.22369/issn.2153-4136/16/1/1}
}
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Interest in High-Performance Computing (HPC) has surged, driven by the demand for skills to utilize advanced computing methods. These methods include managing vast amounts of data, implementing complex algorithms, and developing Artificial Intelligence (AI) applications. HPC ecosystems play a crucial role in tackling intricate scientific and engineering problems. However, integrating various stakeholders demands a deep understanding of collaboration and innovation within HPC settings. This proposal explores how different stakeholders—from students across diverse fields to scientists and policymakers—have been integrated at various levels. This integration is facilitated by introducing new formal courses, incorporating relevant topics into existing curricula, and other related activities.
HPC-ED: Building a Sustainable Community Driven CyberTraining Catalog
Susan Mehringer, Katharine Cahill, Charlie Dey, Brian Guilfoos, David Joiner, Richard Knepper, John-Paul Navarro, Jeaime H. Powell, Mary P. Thomas, Zilu Wang, and Jiesen Zhangpp. 7–13
https://doi.org/10.22369/issn.2153-4136/16/1/2BibTeX
@article{jocse-16-1-2,
author={Susan Mehringer and Katharine Cahill and Charlie Dey and Brian Guilfoos and David Joiner and Richard Knepper and John-Paul Navarro and Jeaime H. Powell and Mary P. Thomas and Zilu Wang and Jiesen Zhang},
title={HPC-ED: Building a Sustainable Community Driven CyberTraining Catalog},
journal={The Journal of Computational Science Education},
year=2025,
month=mar,
volume=16,
issue=1,
pages={7--13},
doi={https://doi.org/10.22369/issn.2153-4136/16/1/2}
}
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HPC-ED is working to improve discovery and sharing of Cyber- Training resources through the combination of the HPC-ED CyberTraining Catalog, an effective and flexible interface, thoughtful metadata design, and active community participation. HPC-ED encourages authors to share training resource information while retaining ownership and allows organizations to enrich their local portals with shared materials. By basing the architecture on an established, flexible framework, HPC-ED can provide a range of solutions people and organizations can employ for sharing and discovering materials. In this paper we describe the initial pilot phase of the project, where we prototyped the HPC-ED catalog, established an initial metadata set, provided documentation, and began using the system to share and discover materials. We gathered community feedback through a variety of means, and are now planning an implementation phase based on evolving our architecture and tools to meet community needs and feedback through improved interfaces and tools designed to address a range of preferences.
Exercise: Design a Learning Pathway
Weronika Filinger, Jeremy Cohen, and Samantha Wittkepp. 14–15
https://doi.org/10.22369/issn.2153-4136/16/1/3BibTeX
@article{jocse-16-1-3,
author={Weronika Filinger and Jeremy Cohen and Samantha Wittke},
title={Exercise: Design a Learning Pathway},
journal={The Journal of Computational Science Education},
year=2025,
month=mar,
volume=16,
issue=1,
pages={14--15},
doi={https://doi.org/10.22369/issn.2153-4136/16/1/3}
}
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Despite the quantity of existing training materials, acquisition and development of the specialist skills required for High Performance Computing (HPC) is not straightforward enough to address the needs of the growing, diversifying and constantly evolving HPC community. The HPC education and training community is exploring different approaches that could facilitate the uptake and progression of technical skills - one of those new approaches is focused on defining and formalising learning pathways. In this lightning talk we will briefly present an exercise designed as a starting point for capturing and outlining learning pathways for the HPC community. This exercise was run for the first time during the ISC'24 BoF on Developing a Sustainable Future for HPC and RSE Skills: Training Pathways and Structures, and was accompanied by a Mentimeter survey to evaluate its effectiveness. The summary of the survey results is also included.
T3-CIDERS: Fostering a Community of Practice in CI- and Data-Enabled Cybersecurity Research Through a Train-the-Trainer Program
Wirawan Purwanto, Mohan Yang, Peng Jiang, Masha Sosonkina, and Hongyi Wupp. 16–19
https://doi.org/10.22369/issn.2153-4136/16/1/4BibTeX
@article{jocse-16-1-4,
author={Wirawan Purwanto and Mohan Yang and Peng Jiang and Masha Sosonkina and Hongyi Wu},
title={T3-CIDERS: Fostering a Community of Practice in CI- and Data-Enabled Cybersecurity Research Through a Train-the-Trainer Program},
journal={The Journal of Computational Science Education},
year=2025,
month=mar,
volume=16,
issue=1,
pages={16--19},
doi={https://doi.org/10.22369/issn.2153-4136/16/1/4}
}
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We present a training program named T3-CIDERS, the Train- The-Trainer approach to fostering cyberinfrastructure (CI)- and Data-Enabled Research in CyberSecurity. T3-CIDERS is a train-the-trainer program for advanced cyberinfrastructure (CI) skills that is designed to be synergistic with research, teaching, and learning activities in cybersecurity and cyber-related disciplines. The participants, termed 'future trainers' (FTs), are trained in effective instructional design and CI hands-on materials from DeapSECURE, developed in a previous CyberTraining program. T3-CIDERS aims to enhance cybersecurity research and education through broader adoption of advanced CI techniques such as artificial intelligence, big data, parallel programming, and platforms like high-performance computing (HPC) systems. T3-CIDERS includes pre-training, a weeklong summer institute, ongoing learning engagements, and local training activities. The FTs conduct local training tailored to the needs at their respective home institutions. They will also develop a new CI training module (called 'Module X') based on the observed common needs in the cybersecurity research community. Community building is integral to T3-CIDERS as its overarching goal. The first cohort of FTs who took the 2024 summer institute comprises faculty members, researchers, and students representing multiple states.
The Use of High-Performance Computing Services in University Settings: A Usability Case Study of the University of Cincinnati's High-Performance Computing Clusters
Mahmoud Junior Suleman, Amy Latessa, Shane Halse, and Jess Kropczynskipp. 20–27
https://doi.org/10.22369/issn.2153-4136/16/1/5BibTeX
@article{jocse-16-1-5,
author={Mahmoud Junior Suleman and Amy Latessa and Shane Halse and Jess Kropczynski},
title={The Use of High-Performance Computing Services in University Settings: A Usability Case Study of the University of Cincinnati's High-Performance Computing Clusters},
journal={The Journal of Computational Science Education},
year=2025,
month=mar,
volume=16,
issue=1,
pages={20--27},
doi={https://doi.org/10.22369/issn.2153-4136/16/1/5}
}
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High-performance computing (HPC) clusters are powerful tools that can be used to support a wide range of research projects across all disciplines. However, HPC clusters can be complex and difficult to use, limiting their accessibility to researchers without a strong technical background. This study used a mixed method to investigate ways to make HPC clusters more accessible to researchers from all disciplines on a university campus. A usability study of 19 university researchers was conducted to understand the needs of HPC users and identify areas where user experience could be improved. Our findings reveal the need to build a customized graphical user interface HPC management portal to serve users' needs and invest in workforce development by introducing an academic credit-based High-Performance Computing Course for students and partnering with other faculties to introduce special programs, e.g., Student Cluster Competitions which would draw more student interest.
Education and Support of Large Language Models in a Research Institution
Juan José García Mesa and Gil Speyerpp. 28–30
https://doi.org/10.22369/issn.2153-4136/16/1/6BibTeX
@article{jocse-16-1-6,
author={Juan Jos\'{e} García Mesa and Gil Speyer},
title={Education and Support of Large Language Models in a Research Institution},
journal={The Journal of Computational Science Education},
year=2025,
month=mar,
volume=16,
issue=1,
pages={28--30},
doi={https://doi.org/10.22369/issn.2153-4136/16/1/6}
}
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As the capabilities of large language models (LLMs) continue to expand, with more accurate and powerful models being released monthly, researchers and educators are increasingly eager to incorporate these tools into their work. The growing demand for this technology reflects its transformative potential in natural language and its impact on scientific research. However, as more users seek to harness the power of LLMs, the need to provide comprehensive education and scalable support becomes ever more critical. Our institution has recognized this challenge and developed a support framework to educate users through regular educational events, consultations, and project support. To address the growing need for LLM support, we have implemented several key strategies, including deploying Jupyter Lab sessions using Open OnDemand for seamless HPC access and integrating cloud-based solutions via Jetstream2. We provide insights into our approach, detailing how we empower researchers and educators to leverage the capabilities of LLMs in their diverse applications.
HPC Carpentry: Recent Progress and Incubation Toward an Official Carpentries Lesson Program
Andrew Reid, Trevor Keller, Alan O'Cais, Annajiat Alim Rasel, Wirawan Purwanto, Jane Herriman, Benson Muite, and Marc-André Hermannspp. 31–34
https://doi.org/10.22369/issn.2153-4136/16/1/7BibTeX
@article{jocse-16-1-7,
author={Andrew Reid and Trevor Keller and Alan O'Cais and Annajiat Alim Rasel and Wirawan Purwanto and Jane Herriman and Benson Muite and Marc-Andr\'{e} Hermanns},
title={HPC Carpentry: Recent Progress and Incubation Toward an Official Carpentries Lesson Program},
journal={The Journal of Computational Science Education},
year=2025,
month=mar,
volume=16,
issue=1,
pages={31--34},
doi={https://doi.org/10.22369/issn.2153-4136/16/1/7}
}
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The HPC Carpentry project aims to develop highly interactiveworkshop training materials to empower novices to effectively leverage HPC to solve scientific and technical problems in their domains. Modeled after The Carpentries training programs, the project's goal is to develop foundational HPC skills and a sense of empowerment, rather than expertise. The workshop setting provides learners with hands-on experience that elicits confidence working with HPC systems and provides sufficient vocabulary to make subsequent self-study more effective. In a major milestone, the steering committee is leading HPC Carpentry through the formal incubation process to become an official Carpentries lesson program alongside the existing Software, Data, and Library Carpentry programs. This achievement is the product of significant work over the past several years, incorporating valuable materials from many contributors. Our most recent focus has been developing materials for a user workshop.We begin with an introduction to the command-line shell (using Software Carpentry's Unix Shell lesson), followed by our Introduction to HPC lesson, covering remote access and resource management. We end with a newly developed lesson on HPC workflow management, which walks learners through the execution of a scaling study on an HPC system, emphasizing both the benefits and limitations of the system for domain applications. This workshop program was recently run in full at the Lawrence Livermore National Laboratory. Future plans include building a developer workshop, reconnecting with disparate contributors, and engaging with the broader community through regular open conference calls and outreach.
Integrating Captive Portal Technology into Computer Science Education: A Modular, Hands-On Approach to Infrastructure
Lianting Wang and Marcelo Poncepp. 35–42
https://doi.org/10.22369/issn.2153-4136/16/1/8BibTeX
@article{jocse-16-1-8,
author={Lianting Wang and Marcelo Ponce},
title={Integrating Captive Portal Technology into Computer Science Education: A Modular, Hands-On Approach to Infrastructure},
journal={The Journal of Computational Science Education},
year=2025,
month=mar,
volume=16,
issue=1,
pages={35--42},
doi={https://doi.org/10.22369/issn.2153-4136/16/1/8}
}
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In this paper, we present an educational project aimed to introduce students to the technology behind Captive Portals infrastructures. For doing this, we developed a series of modules to emphasize each of the different aspects and features of this technology. The project is based on an open source implementation which is widely used in many computer network courses, making it well-suited and very appealing for instructors and practitioners in this field.
From Student SIG to Success: The journey of a student HPC Special Interest Group towards sustainable training and success in Student Cluster Competitions
Bryan Johnston, Lara Timm, David Macleod, John Poole, Lily de Melo, Sayfullah Jumoorty, Jonathan Faller, Reinhard Jansen van Vuuren, and Michael Beukmanpp. 43–49
https://doi.org/10.22369/issn.2153-4136/16/1/9BibTeX
@article{jocse-16-1-9,
author={Bryan Johnston and Lara Timm and David Macleod and John Poole and Lily de Melo and Sayfullah Jumoorty and Jonathan Faller and Reinhard Jansen van Vuuren and Michael Beukman},
title={From Student SIG to Success: The journey of a student HPC Special Interest Group towards sustainable training and success in Student Cluster Competitions},
journal={The Journal of Computational Science Education},
year=2025,
month=mar,
volume=16,
issue=1,
pages={43--49},
doi={https://doi.org/10.22369/issn.2153-4136/16/1/9}
}
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This paper provides an overview of the student HPC Special Interest Group (SIG) formed at the University of the Witwatersrand that focuses on delivering HPC training to the undergraduate student community. The paper outlines the approach towards growing and maintaining the interest group, including teaching and learning strategies to prepare Wits students for Student Cluster Competitions. Insights into the challenges experienced and lessons learned are discussed, particularly with respect to sustainable workforce development. These insights could help develop a structured framework for creating effective and sustainable HPC special interest groups, centred around student involvement.
Computational Skills Training for Undergraduate Researchers in Molecular Engineering
Kristen Finch, Ryan Beck, Xiaosong Li, Nam Pho, and Xiao Zhupp. 50–56
https://doi.org/10.22369/issn.2153-4136/16/1/10BibTeX
@article{jocse-16-1-10,
author={Kristen Finch and Ryan Beck and Xiaosong Li and Nam Pho and Xiao Zhu},
title={Computational Skills Training for Undergraduate Researchers in Molecular Engineering},
journal={The Journal of Computational Science Education},
year=2025,
month=mar,
volume=16,
issue=1,
pages={50--56},
doi={https://doi.org/10.22369/issn.2153-4136/16/1/10}
}
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In June 2024, the University of Washington's (UW) Clean Energy Institute (CEI) and Molecular Engineering and Materials Center (MEMC) in partnership with UW Research Computing (RC) prepared complimentary training for a group of 25 Research Experience for Undergraduates (REU) participants.Workshop participants had completed zero to four years of post-secondary education and came from 17 colleges and universities across eight states with 29% currently attending 2-year programs. On average, 14 students attended a given workshop. The program included four targeted workshop offerings, spanning essential skills in computational science and advanced topics: (1) Python via Jupyter, (2) Command Line Interface (CLI) and high performance computing (HPC), (3) Gaussian and Quantum Espresso, and (4) data analysis using linear and logistic regression as well as neural networks. The program's effectiveness was evaluated with a post-workshop survey. Survey results indicated most participants had little prior experience in these topics but indicated the content was relevant for their current and future aspirations. The survey showed some students agreed with statements indicating that learning objectives were met, but overall scores and open responses indicated areas for improvement. In the future, the CLI and HPC session will be converted from one to two sessions and the material in the applied Gaussian and Quantum Espresso demonstrations reduced. The program's materials are reproducible and publicly accessible, compatible with most academic HPC clusters. Our program addressed a wide range of training and education needs within computational science, emphasizing practical skills and interdisciplinary applicability.
HPC Andragogy: Automating Batch Scheduler Feedback
Kyriakos Tsoukalaspp. 57–61
https://doi.org/10.22369/issn.2153-4136/16/1/11BibTeX
@article{jocse-16-1-11,
author={Kyriakos Tsoukalas},
title={HPC Andragogy: Automating Batch Scheduler Feedback},
journal={The Journal of Computational Science Education},
year=2025,
month=mar,
volume=16,
issue=1,
pages={57--61},
doi={https://doi.org/10.22369/issn.2153-4136/16/1/11}
}
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This paper proposes a monitoring system that emails feedback to users about submitted jobs and has the capability to stop and resubmit jobs to a batch scheduler. The proposed system has been implemented for a small supercomputing environment with a mix of high-performance and high-throughput computing jobs. User feedback includes alerts for over- and under-utilization of CPU and physical memory. This paper also discusses how predefined system thresholds were chosen and proposes three algorithms. An algorithm for the proposed monitoring system and two algorithms for the prediction of CPU and physical memory utilization. The latter algorithms are based on users' input of the identification string (job ID) of a similar job that should have finished execution without errors. Lastly, a git repository is shared to make the code accessible for review.