High Performance Computing (HPC) and, in general, Parallel and Distributed Computing (PDC) has become pervasive, from supercomputers and server farms containing multicore CPUs and GPUs, to individual PCs, laptops, and mobile devices. Even casual users of computers now depend on parallel processing. Therefore, it is important for every computer user (and especially every programmer) to understand how parallelism and distributed computing affect problem solving. It is essential for educators to impart a range of PDC and HPC knowledge and skills at multiple levels within the educational fabric woven by Computer Science (CS), Computer Engineering (CE), and related computational curricula including data science. Companies and laboratories need people with these skills, and, as a result, they are finding that they must now engage in extensive on-the-job training. Nevertheless, rapid changes in hardware platforms, languages, and programming environments increasingly challenge educators to decide what to teach and how to teach it, in order to prepare students for careers that are increasingly likely to involve PDC and HPC.
EduHiPC aims to provide a forum that brings together academia, industry, government, and non-profit organizations - especially from Indian subcontinent, its vicinity, and Asia - for exploring and exchanging experiences and ideas about the inclusion of high-performance, parallel, and distributed computing into undergraduate and graduate curriculum of Computer Science and Engineering, Computational Science, Computational Engineering, and computational courses for STEM and business and other non-STEM disciplines. The workshop will invite unpublished manuscripts from academia, industry, and government laboratories on topics pertaining to approaches for augmenting undergraduate and graduate education in these disciplines with PDC and HPC concepts. Authors are also encouraged to submit work demonstrating use of generative AI and large language models (LLMs) to enhance instruction, foster deeper understanding, and prepare students for the evolving landscape of parallel and distributed computing. Researchers, scholars, and practitioners are invited to submit their work for consideration in one of two paper tracks, or for poster or Peachy assignments sessions.
Topics of interest include, but are not limited to:
EduHiPC is a sister workshop of the Edu* series of workshops EduPar and EduHPC that are being held in conjunction, respectively, with IPDPS and Supercomputing conferences. HiPC is a premium conference on High Performance computing sponsored by IEEE. HiPC encompasses all aspects of HPC such as algorithms, application, architecture etc. except for educational aspects of HPC. EduHiPC workshop will complement and enhance current efforts of HiPC. The workshop is particularly dedicated to bringing together stakeholders from industry (both hardware vendors and employers), government labs, and academia in the context of HiPC-25. The goal is for each to hear the challenges faced by others, to learn about various approaches to addressing these challenges, and to have opportunities to exchange ideas and solutions.
Submission Open: August 15, 2025
Submission Deadline: October 6, 2025
Author Notification: October 30, 2025
Camera Ready Paper: November 14, 2025
Workshop Date: December 17, 2025
Authors should submit papers in PDF format through the submission site (https://easychair.org/conferences?conf=eduhipc2025)
We are accepting submissions for Track 1 Full Papers (6-8 pages), Track 2 Short Papers (3-4 pages), Posters (2-page abstracts), and Peachy Parallel Assignments (2-page abstracts). Please see the details below for each category of submission. Submissions should be formatted as single-spaced, double-column pages ( IEEE format). Authors must try to revise their papers to incorporate feedback from the reviewers. All accepted full and short papers will be published in the HiPC Workshop Proceedings and will be included in the IEEE Xplore digital library — every accepted paper will have at least one author who will register at the notified registration fee and also present the paper at the conference. For extraneous circumstances authors may be allowed to present virtually. Accepted papers will be available from the CDER website approximately 2 weeks before the workshop so that attendees can read papers before attending the talks. Papers that are not accepted as full papers may be optionally accepted as short poster papers ( 2 pages). Authors of papers accepted as poster papers will be invited to revise their papers in a 2-page format. Authors of all accepted full and short papers must be present at the workshop. Authors of accepted Posters and Peachy Assignments will present their work during the workshop poster sessions. Summary papers of all accepted posters and all accepted Peachy Assignments will also be published in the workshop proceedings. Summary papers will be written by the Poster and Peachy Assignment chairs and will include, as co-authors, all Poster and Peachy Assignment authors. Authors will be further invited to publish their work in a Journal of Parallel and Distributed Computing (JPDC) special issue, as in the past workshops.Please make sure to include “Track#:” before the title for papers submitted to each track.
For this track, we welcome researchers unpublished 6-8 page manuscripts from individuals or teams from academia, industry, and other educational and research institutes from all over the world on topics about the teaching of PDC topics in the Computer Science and Computer Engineering curriculum as well as in domain-specific computational and data science and engineering curricula. This track emphasizes conducting pedagogical research related to PDC education and evaluating it within classroom or other settings.
For this particular track, we welcome researchers to submit 3-4 page manuscripts discussing their innovative experiences in integrating their research, as well as associated methods, tools, models, simulations, or datasets, into educational settings, with a focus on undergraduate levels, or fostering broader community engagement. Submissions do not need to include an assessment of teaching techniques or in-class evaluations. Following is a list of sample PDC research topics but not limited to: parallel algorithm visualization and interactive learning tools, resource allocation simulations, fault tolerance demonstrations, multi-core programming exercises, gpu computing introductions, programming models and frameworks, software performance engineering, emerging technologies integration, such as, quantum computing basics, edge computing scenarios, machine learning parallelization. Early career faculty, are especially encouraged to submit.
High-quality poster presentations are an integral part of EduHiPC 2025. We seek posters (2-page abstracts) describing recent or ongoing research.
Course assignments are integral to student learning and also play an important role in student perceptions of the field. EduHiPC 2025 will include a session showcasing "Peachy Parallel Assignments" - high-quality assignments, previously tested in class, that are readily adoptable by other educators teaching topics in parallel and distributed computing. Assignments may be previously published, but the author must have the right to publish a description of it and share all supporting materials. We are seeking assignments that are:
Sushil K. Prasad, University of Texas San Antonio, USA,
sushil.prasad@utsa.edu
Ashish Kuvelkar, C-DAC, India,
ashishk@cdac.in
Sharad Sinha, IIT Goa, India, sharad@iitgoa.ac.in
Purushotham Bangalore, University of Alabama, USA
pvbangalore@ua.edu
David P. Bunde, Knox College, USA
Buddhi Ashan Mallika Kankanamalage, University of Texas San Antonio, USA
Sudhakar Yogaraj, IIT Goa, India
Ramachandran Vaidyanathan, Louisiana State University, USA
Martina Barnas, Indiana University Bloomington, USA
Nasser Giacaman, The University of Auckland, NZ
Mike Rogers, Tennessee Tech University, USA
Anshul Gupta, IBM Research, USA
Kishore Kothapalli, International Institute of Information Technology, Hyderabad, India
Krishna Kant, Temple University, USA
Seetha Rama Krishna Nookala, Intel, India
Ritu Arora, University of Texas San Antonio, USA
Sukhamay Kundu, Louisiana State University, USA
R. K. Shyamasundar, IIT Bombay Mumbai, India
R. Govindarajan, Indian Institute of Science, India
Andrew Lumsdaine, University of Washington, USA
Manish Parashar, NSF & Rutgers University, USA
Cynthia Phillips, Sandia National Laboratories, USA
Noemi Rodriguez, PUC-Rio, Brazil
David Brown, Elmhurst College, USA
Chitra P. Thiagarajan College of Engineering, India
Somnath Roy, IIT Kharagpur, India
Sudhakar Yogaraj, IIT Goa, India