NSF/IEEE-TCPP Curriculum on Parallel and Distributed Computing for Undergraduates - Version II – Big Data, Energy, and Distributed Computing
This special session will report on the updated NSF/IEEE-TCPP Curriculum on Parallel and Distributed Computing released in Nov 2020 by the Center for Parallel and Distributed Computing Curriculum Development and Educational Resources (CDER). The purpose of the special session is to obtain SIGCSE community feedback on this curriculum in a highly interactive manner employing the hybrid modality and supported by a full-time CDER booth for the duration of SIGCSE. In this era of big data, cloud, and multi- and many-core systems, it is essential that the computer science (CS) and computer engineering (CE) graduates have basic skills in parallel and distributed computing (PDC). The topics are primarily organized into the areas of architecture, programming, and algorithms topics. A set of pervasive concepts that percolate across area boundaries are also identified. Version 1 of this curriculum was released in December 2012. That curriculum guideline has over 100 early adopter institutions worldwide and has been incorporated into the 2013 ACM/IEEE Computer Science curricula. This Version-II represents a major revision. The updates have focused on enhancing coverage related to the topical aspects of Big Data, Energy, and Distributed Computing.
The session will also report on related CDER activities including a workshop series on a PDC institute conceptualization, developing a CE-oriented version of the curriculum, and identifying a minimal set of PDC topics aligned with ABET’s exposure-level PDC requirements.
The interested SIGCSE audience includes educators, authors, publishers, curriculum committee members, department chairs and other administrators, professional societies, and the computing industry.
Thu 16 MarDisplayed time zone: Eastern Time (US & Canada) change
13:45 - 15:00
|NSF/IEEE-TCPP Curriculum on Parallel and Distributed Computing for Undergraduates - Version II – Big Data, Energy, and Distributed ComputingHybrid|
Sushil Prasad Georgia State University, Charles Weems University of Massachusetts, Alan Sussman University of Maryland, Anshul Gupta IBM, Trilce Estrada University of New Mexico, Ramachandran Vaidyanathan Louisiana State University, Sheikh Ghafoor Tennessee Tech University, Krishna Kant Temple University, Craig Stunkel IBM ResearchDOI