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EduHPC-17: Workshop on Education for High-Performance Computing

              EduHPC-17: Workshop on Education for High-Performance Computing                                        

                                                                   Mon, Nov 13, 2017 

Time: 9:00 AM - 5:30 PM

Held in conjunction with SC-17: The International Conference on High Performance Computing, Networking, Storage, and Analysis


Technical Program


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.

This workshop invites unpublished manuscripts from academia, industry, and government laboratories on topics pertaining to the needs and approaches for augmenting undergraduate and graduate education in Computer Science and Engineering, Computational Science, and computational courses for both STEM and business disciplines with PDC and HPC concepts.  We also encourage papers on large-scale data science.

The workshop is particularly dedicated to bringing together stakeholders from industry (both hardware vendors and employers), government labs, and academia in the context of SC-17.  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. In addition to contributed talks, this workshop may feature invited talks on opportunities for collaboration, resource sharing, educator training, internships, and other means of increasing cross-fertilization between industry, government, and academia.

This effort is in coordination with the NSF/TCPP curriculum initiative on Parallel and Distributed Computing and the Center for Parallel and Distributed Computing Curriculum Development and Educational Resources (CDER).

Topics of interest include, but are not limited to:

1. Pedagogical issues in incorporating PDC and HPC in undergraduate and graduate education, especially in core courses
2. Novel ways of teaching PDC and HPC topics
3. Data Science and Big Data aspects of teaching HPC/PDC including early experience with data science degree programs.
4. Experience with incorporating PDC and HPC topics into core CS/CE courses and in domain Computational Science and Engineering courses
5. Pedagogical tools, programming environments, infrastructures, languages, and projects for PDC and HPC
6. Employers' experiences with and expectation of the level of PDC and HPC proficiency among new graduates
7. Education resources based on higher-level programming languages, models, and environments such as PGAS, X10, Chapel, Haskell, Python, Cilk, CUDA, OpenCL, OpenACC, and Hadoop  
8. Parallel and distributed models of programming and computation suitable for teaching, learning, and workforce development.
9. Projects or units that introduce students to concepts relevant to Internet of Things, networking, or other topics in mobile devices or sensor networks.
10. Issues and experiences addressing the gender gap in computing and broadening participation of underrepresented groups.


Papers: Authors should submit 6-8 page papers in pdf format through the EasyChair submission site at Submissions should be formatted as single-spaced, double-column pages (IEEE format), including figures, tables, and references. See style templates for details. Accepted papers will be published in the IEEE digital library.  Accepted papers will be available from the CDER website approximately 2 weeks before the workshop so attendees can read papers before attending the talks. Authors may optionally (modestly) revise their papers to incorporate feedback from the workshop.

IEEE Template

KEYNOTE: There will be one keynote address.

Because EduHPC will be a full-day workshop, there will be some special sessions.  Please check back to the EduHPC 2017 website in the near future for details on how to participate in a special session. Proposals for panels and special sessions are also welcome.  If you have an idea for a panel or a special session, please contact the program committee chair, Cynthia Phillips (

Submission deadline: Friday, September 8, Monday, September 11, 2017 (11:59 pm Anywhere On Earth)
Author notification: Monday, October 9, 2017
Camera-ready paper deadline: Monday, October 30, 2017
Workshop: Monday, November 13, 2017
Optional revised camera-ready paper deadline: Friday, December 1, 2017


Organizing Committee:
Sushil Prasad, Georgia State University
Martina Barnas, Indiana University, Bloomington
Sheikh Ghafoor, Tennessee Technological University
Anshul Gupta, IBM Research
Cynthia Phillips, Sandia National Laboratories
Arnold Rosenberg, Northeastern University
Alan Sussman, University of Maryland
Charles Weems, University of Massachusetts
Ramachandran Vaidyanathan, Louisiana State University

Workshop Chair: Sushil K. Prasad, Georgia State University

Program Chair: Cynthia Phillips, Sandia National Laboratories

Proceedings Chair: Satish Puri, Marquette University

Program Committee

Martina Barnas, Indiana University Bloomington
Jonathan Berry, Sandia National Laboratories
Virendra Bhavsar, University of New Brunswick
David Bunde, Knox College
Randy Bryant, CMU
Rezaul Chowdhury, Stony Brook University,
Debzani Deb, Winston-Salem State University
Joshua Eckroth, Stetson University
Victor Gergel,  Nizhni Novgorod State University
Sheikh K. Ghafoor,  Tennessee Technological University
Nasser  Giacaman, University of Auckland
Domingo Gimenez , University of Murcia
Ganesh Gopalakrishnan, University of Utah
Ajay Gupta, University of Western Michigan
Anshul Gupta,  IBM Thomas J. Watson Research Center
David Juedes, Ohio University
Karen Karavanic, Portland State University
Peter Pacheco, University of San Francisco
Manish Parashar, Rutgers University
Thomas  Rauber, University Bayreuth
Robert (Bob) Robey, Los Alamos National Laboratories
Arnold Rosenberg, Northeastern University
Gudula Ruenger, Chemnitz University of Technology
Erik Saule, University of North Carolina at Charlotte
Jawwad  Shamsi, FAST National University of Computer and Emerging Sciences
Chi Shen, Kentucky State University
Suzanne Shontz, University of Kansas
Rudrapatna Shyamasundar, Tata Institute of Fundamental Research
Leonel Sousa, Universidade de Lisboa
Alan Sussman, University of Maryland
Michela Taufer, University of Delaware
Dominique Thiebaut, Smith College
Ramachandran Vaidyanathan,  Louisiana State University
Susan Wang, Mills College
Charles Weems, University of Massachusetts, Amherst
Maxwell Young, Mississippi State