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EduPar-26 Technical Program Schedule

EduPar-26 Technical Program

Tuesday , May 26, 2026

Location: Salon D

Link back to CFP

New Orleans, USA

EduPar is being held in conjunction with IPDPS. We encourage EduPar participants to register for IPDPS (IPDPS registration includes access to conference and workshop proceedings as well as email updates about the conference and its associated workshops: http://www.ipdps.org/)

*note: times are listed in the Eastern Time Zone

 

Time*
Event
Presenters
9:00-9:10

Welcome and Logistics

Sushil Prasad, Workshop Chair

Satish Puri, Program Chair

9:10-10:00

Keynote

Session Chair:
Sushil Prasad

Title: Preparing for the Quantum Era: Systems, Software, and Education

Dilma Da Silva

NSF/Texas A&M University

(ppt)

Abstract: This talk discusses the emerging role of the parallel and distributed computing community in advancing quantum information science. Rapid progress over the past decade suggests that quantum technologies may reach transformative capabilities within the next decade, but realizing this potential will depend critically on advances in quantum systems software. The computing research community has a central role to play in this effort, particularly in enabling the effective integration of classical and quantum systems.

The quantum software layers (from compilers upward) and hybrid quantum–classical workflows raise fundamental challenges in resource management, orchestration, and performance optimization; these are domains where expertise from parallel and distributed computing is directly relevant. The parallel and distributed computing community is well-positioned not only to support the quantum ecosystem but also to shape novel approaches for quantum algorithms and workflows.

The talk will also highlight the need for education initiatives that prepare the next generation of researchers and practitioners to work across classical and quantum paradigms. Finally, it will provide an overview of current NSF investments in Quantum Information Science.

Speaker Bio: Dilma Da Silva is a Regents Professor and holder of the Ford Design Professorship II in the Department of Computer Science and Engineering at Texas A&M University. Since July 2022, she has served at the U.S. National Science Foundation in several leadership roles: as Senior Science and Engineering Advisor at the Office of the Director, as Division Director for Computing and Communication Foundations, and as Assistant Director in the Directorate of Computer and Information Science and Engineering (CISE). Her previous roles at Texas A&M include Department Head (2014-2019), Associate Dean (2019-2020), interim Director of the Texas A&M Institute of Data Science, and interim Director of the Texas A&M Cybersecurity Center. Her primary research interests are distributed systems, operating systems, and computer science education. Before joining Texas A&M, she worked at Qualcomm Research (2012-2014), IBM Research (2000-2012), and the University of São Paulo (1996-2000).

10:00-10:30
Coffee Break
 
10:30-11:45

Paper Session I:

Session Chair:
Vaidy Ramachandran

Leveraging Graph-Based Retrieval-Augmented Generation for Parallel and Distributed Computing Education,

Rithvik Dhanpal, Vinay Regu, Ramaprasanna Devarapally, Jiayin Wang, Sushil Prasad, Srishti Srivastava, Liudong Zuo, Michelle Zhu

Evaluating LLM-Generated Instructional Content for Parallel Computing Education,

Xinyao Yi, Yonghong Yan

Online Self-Service Learning Modules for Running AI-Driven Scientific Workflows,

Pari Hirenkumar Patel, Vani Seth, Bishwas Wagle, Roshan Lal Neupane, Ashish Pandey, Sanjit Subhash, Sharan Srinivas, Prasad Calyam

11:45-12:00

CDER Session

CDER center activities, Sushil Prasad (ppt)

12:00-1:30
Lunch
 
1:30-2:30

Panel

Moderator: Sushil Prasad

Title: Impact of AI on PDC Education

Questions to discuss

  • Early courses: TCPP Curriculum Initiative has led the movement that PDC should be infused throughout Computer Science (CS) and Computer Engineering (CE) curriculum, starting with the early CS core courses. Same is being asked of instructors about AI infusion. How AI and PDC be infused more effectively into the introductory courses - CS1/CS2 programming oriented courses and Computer Systems course? What/how can instructors teach and how should students learn to be well prepared for advanced courses?
  • Students: How are (will be) students studying for better effectiveness and competencies in PDC (and in AI skills)? AI help for chapter and paper summaries, notes making, understanding of concepts, solving problems and programming assignments, preparing for tests, presentations, writing term papers…
  • Job preparation: How do students prepare their PDC/software artifacts portfolio to showcase their PDC and AI competencies to potential employers? How can they prove themselves during online job interviews?
  • AI degrees: What should be taught related to PDC/HPC in the budding AI degrees - BS, MS? Why should students pursue traditional Computer Science or Computer Engineering, why not a BS or MS in AI? Are AI degrees primarily renaming exercises?
  • PDC Elective courses: For teaching parallel and distributed computing (PDC) elective classes, how is the pedagogy and curriculum changing, in terms of teaching strategy and tools, programming assignments and their rigor - should they use LLM or not, new AI related content, dropped old content, and testing of the students?

Panelists: Abhinav Bhatele (University of Maryland), Umit Catalyurek (Amazon/GaTech), Dilma Da Silva (NSF/TAMU), Dhabaleswar K Panda (Ohio State University), Chip Weems (UMass)

2:30-3:00

Paper Session II:

Session Chair:
David Bunde

3:00-3:30
Coffee Break
 
4:45-5:00

TCPP Curriculum

Workshop Wrap-up

Computer Engg. Curriculum update, R. Vaidyanathan (ppt)

Final thoughts - Sushil Prasad and Dennis Brylow