A Case Study: Incorporating Parallel and Distributed Computing into Computer Science Curriculum

Ali Abu-El Humos, Sungbum Hong, Tzusheng Pei, Omar Aljawfi

Recent technology advances in parallel computing such as multicore CPUs, GPUs, and their driving software require a well-prepared workforce to support this demanding and fast changing industry. Parallel and Distributed Computing (PDC) education for computer science and computer engineering majors will play a major role in preparing well trained graduates to join this workforce. In this work, we share past and future plans to update the computer science curriculum at Jackson State University (JSU) with PDC modules. As part of this effort, some of the NSF/IEEE-TCPP curriculum initiative on PDC modules were integrated into department-wide core and elective courses offered in both fall and spring semesters. These courses were: CSC 119 Object Oriented Programming (core) [2, 4, 6, 9], CSC 216 Computer Architecture and Organization (core) [3, 5, 9], CSC 312 Advanced Computer Architecture (core) [3,5], CSC 325 Operating Systems (core) [6, 9], CSC 350 Organization of Programming Languages (core) [9], CSC 425 Parallel Computing (elective) [1, 2, 6] , CSC 499 Special Topics: Data Mining (elective) and UNIV 100 University Success course, which is a university-wide class offered for all JSU majors. In an effort to update the contents of the UNIV 100 course, some contemporary PDC topics and their essence in higher education were incorporated into this course. The inclusion of the PDC modules was gradual and light weighted in the lower level courses and more aggressive in the higher-level courses to let the students easily grasp PDC concepts. Specific test questions, homework assignments and projects were developed to assess students’ performance.

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