A Planning Workshop on Curriculum Standards for Parallel and Distributed Computing Feb 5-6, Washington DC, Hilton Arlington Sushil K. Prasad Georgia State.

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Presentation transcript:

A Planning Workshop on Curriculum Standards for Parallel and Distributed Computing Feb 5-6, Washington DC, Hilton Arlington Sushil K. Prasad Georgia State University Session 1:

Who are we? Agarwal, Dinesh, Georgia State University Chtchelkanova, Almadena - NSF Dehne, Frank - University of Carleton, Canada Gouda, Mohamed - University of Texas, Austin, NSF Gupta, Anshu - lIBM T.J. Watson Research Center JaJa, Joseph - University of Maryland Kant, Krishna - NSF, Intel Lumsdaine, Andrew - Indiana University Padua, David- University of Illinois at Urbana-Champaign Parashar, Manish- Rutgers, NSF Prasad, Sushil- Georgia State University Prasanna, Viktor- University of Southern California Robert, Yves- INRIA, France Rosenberg, Arnold- Colorado State University Sahni, Sartaj- University of Florida Shirazi, Behrooz- Washington State University Sussman, Alan - University of Maryland Wu, Jie - Temple University

Why this initiative? Why now? Stakeholders Current State of Practice Curriculum Data Sampled

Why now? Computing Landscape has changed – Mass marketing of multi-cores – General purpose GPUs even in laptops (and handhelds) A computer scientist with even a Bachelors must acquire skill sets to develop parallel software – No longer instruction in parallel and distributed computing primarily for research or high-end specialized computing – Industry is filling the curriculum gap with their preferred hardware/software platforms and “training” curriculums as alternatives with an eye toward mass market.

Stakeholders Students Educators Universities and Colleges Employers Developers Vendors Authors Researchers NSF and other funding agencies IEEE Technical Committees/Societies, ACM SIGs,

Current State of Practice Students and Educators – Educators struggle to choose topics, language, software/hardware platform, and balance of theory, algorithm, architecture, programming techniques… – Textbooks selection has increasingly become problematic each year, as authors cannot keep up; no single book seems sufficient – Industry promotes whatever best suits their latest hardware/software platforms. – The big picture is getting extremely difficult to capture. – Students have no well-defined expectation for a course in parallel/distributed computing and do not know what skill set they must graduate with.

Current State of Practice University and Colleges New programs at colleges (nationally and internationally) Existing programs/courses need some periodic guidance and ACM curriculum cannot keep pace Employers – Need to know the basic skill sets of graduates – No well-defined expectations from students, but will increasingly require them – Retraining and certifications of existing professionals

Current State of Practice Vendors – May employ the curriculum standards to steer products, especially their programming IDEs, tools, debuggers, etc. Currently these promotes whatever best suits their latest hardware/software platforms. – Hardware/software vendors can participate in this curriculum development process – May collaborate with other stakeholders to offer shared educational infrastructures

Current State of Practice Authors – Will directly benefit when revising textbooks – Expected to participate in the curriculum process NSF and Funding Agencies – Educational Agenda setting – Help fund shared resources Sisters Organizations (IEEE TCs: TCPP, TCDP, TCSC, ACMSIGs, etc.) – Need help in setting their Educational Agenda – Employ this template elsewhere

Curriculum Data Sampled 73 universities 91 courses – 18 courses through website upload, others manually scouted Separately categorized as – Parallel and Distributed Computing (PDC) – Parallel Algorithms (PA) – Computational Sciences/Applications – Also has distributed systems courses, etc.

Curriculum Data Sampled Statistics: – Topic-wise distribution for 51 PDC and Parallel Algorithms (PA) Courses Topic-wise distribution for 40 PDC Courses Topic-wise distribution for 11 Parallel Algorithms (PA) Courses – Courses uploaded through website has weekly distribution

Sample Statistics PDC Topic Distribution Week-wise Av. Distribution of Uploaded Courses

Goals The primary goal of this planning workshop – setup mechanism and processes which would provide periodic curricular guidelines Secondary goal – employ the mechanism to develop sample curriculums (My role: facilitator for the workshop; Coordinator for follow-up actitivities)