Call for Papers Workshop on HPC Education and Training for Emerging Technologies (HETET23)

ISC23 Conference

High performance computing has become central for empowering progress in diverse scientific and non-scientific domains. With the advent of myriad different technologies in the post peta-scale computing era, the future of HPC involves a significantly greater degree of parallelism than we are observing currently. The rapid advancement and introduction of new processing technologies for HPC has facilitated the convergence of Artificial Intelligence (AI) and Machine Learning (ML), Data Analytics and Big Data and the High Performance Computing (HPC) domains platforms to solve complex large-scale real-time analytics and scientific applications pertaining to diverse scientific and non-scientific fields. As we move towards exascale future and beyond, the new convergent computing platforms along with a paradigm shift in programming applications leveraging these platforms provide both challenges and opportunities for cyberinfrastructure facilitators, trainers and educators to develop, deliver, support, and prepare a diverse community of students and professionals for careers that utilize high performance computing along with emerging technologies to execute increasingly hard jobs and predict evolving trends, equipping them to solve real-world complex scientific, engineering, and technological problems.

The HETET23 workshop is an ACM SIGHPC Education Chapter coordinated effort aimed at fostering collaborations among the practitioners from traditional and emerging fields to explore strategies to enhance computational, data-enabled, AI and HPC educational needs. Attendees will discuss approaches for developing and deploying HPC education and training, as well as identifying new challenges and opportunities for keeping pace with the rapid pace of technological advances - from collaborative and online learning tools to new HPC platforms; advanced technology solutions supporting HPC, Accelerated Analytics, and AI applications. The workshop will provide opportunities for: learning about methods for conducting effective HPC education and training for emerging technologies; promoting collaborations among HPC educators, trainers and users; and for disseminating resources, materials, lessons learned and good/best practices.

This half-day workshop is aimed at users, professionals, researchers, scholars, educators, and other interested community members with an active interest in training, educating, using and supporting the HPC community of developers, researchers, educators, and practitioners.

The workshop will include a panel, presentations and lightning talks.  Topics of interest include but are not limited to:

  • Pedagogical methods/tools from TinyML through to Exascale (and everything in between)
  • Pedagogical methods/tools enabling Cybersecurity, Accelerated Analytics, AI, Quantum, Cloud applications and other emerging technologies.
  • Pedagogical methods/tools for High performance data analytics and cognitive computing
  • Best practices and models for teaching and learning HPC topics and course materials
  • Sustainable educational strategies for HPC education and training
  • Emerging and scalable online environments and tools for HPC education and training
  • Evaluation and assessment of training and instructional materials
  • Legal issues involved in training (e.g. ADA compliance, software licenses, intellectual property rights, etc.)
  • Novel andragogical approaches for training and education
  • Development of Research Software Engineering Skills in the HPC context
  • Pedagogical methods/tools for non-traditional HPC disciplines
  • Approaches to broadening the participation and improving the accessibility of teaching and training opportunities

We invite submissions for full papers and extended abstract lightning talks.  All accepted papers and extended abstracts will be considered for publication in a special issue of Journal of Computational Science Education.

Important Dates:

Submission Deadline:  March 30, 2023

Notification of acceptance: April 7, 2023

Final camera ready submissions: April 14, 2023

Paper Submission

To be accepted for publication, each paper should describe:

  • the nature of the training or education program
  • Strategy
  • assessment or evaluation technique
  • situations for which it is relevant or in which it was applied
  • an evaluation of its success
  • lessons learned
  • reproducibility of the processes and resources
  • relevance to the broad range of training or education topics associated with the workshop

Paper Format

The submitted paper must follow the Journal of Computational Science Education templates to generate your PDF: MS Word and Latex.  Papers that do not comply with ACM format and maximum 8 page length limit will be returned.

Selection Criteria

The submitted papers will be assessed based on their novelty, technical quality, potential impact, insightfulness, depth, clarity, and reproducibility. The authors must describe the algorithms and resources and processes used in the paper as completely as possible to allow reproducibility. This includes experimental methodology, empirical evaluations, and results.

The reproducibility factor will play an important role in the assessment of each submission. Authors are strongly encouraged to make their code and data publicly available whenever possible.

Review Process

Submissions will be peer-reviewed by at least 3 individuals. After the preliminary notification date, authors may rebut reviewer inquiries and their comments. Based on the rebuttal feedback, the Program Committee will notify authors of the final decision.

Organizing Committee:

  • Nitin Sukhija, Slippery Rock University of Pennsylvania
  • Scott Lathrop, NCSA, University of Illinois at Urbana-Champaign
  • Nia Alexandrov, Daresbury Laboratory, Sci-Tech Daresbury
  • Mozhgan Chimeh, Nvidia
  • Weronika Filinger, The University of Edinburgh

Workshop Chairs:

  • Nitin Sukhija, Slippery Rock University of Pennsylvania
  • Scott Lathrop, NCSA, University of Illinois at Urbana-Champaign
  • Mozhgan Chimeh, Nvidia

Proceedings Chair:

  • David Joiner, Editor, Journal of Computational Science Education

Program Committee (Tentative):

  • Susan H. Mehringer, Cornell University
  • Scott Lathrop, NCSA, University of Illinois at Urbana-Champaign
  • Maxim Belkin, NCSA, University of Illinois at Urbana-Champaign
  • Henry Neeman, University of Oklahoma
  • Gowtham Shankara, Michigan Technological University
  • John Coulter, Georgia Institute of Technology
  • Julia Mullen, MIT Lincoln Laboratory
  • Fernanda Foertter, BioTeam Inc.
  • Mozhgan Kabiri Chimeh, NVIDIA
  • Fouzhan Hossein, NAG
  • Martin Callaghan, University of Leeds, UK
  • Bryan Johnston, CHPC- South Africa
  • Geert Jan Bex, Universiteit Hasselt - Campus Diepenbeek
  • Juan Chen, National University of Defense Technology, China
  • Ann Backhaus, Pawsey Supercomputing Centre, Australia
  • Marion Weinzier, Durham University, UK
  • Ilya Zhukov, Juelich Supercomputing Centre , Germany
  • Samantha Wittke, CSC - IT Centre for Science, Finland
  • Karina Pesatova, IT4Innovation, Czech Republic
  • TBD

About SIGHPC Education

The SIGHPC Education chapter has as its purpose the promotion of interest in and knowledge of applications of High Performance Computing (HPC).