Design of Practical Experiences to Improve Student Understanding of Efficiency and Scalability Issues in High Performance Computing: (Abstract Only).

With the increasing demand of big data technology, there has been a growing interest of introducing high performance computing in computer science curriculum. One challenge in helping students understand the nature of efficiency and scalability issues in high performance computing is the lack of opportunities for them to be engaged in large-scale applications that run on supercomputer system architecture. This poster presents a collection of example projects that have been used in a parallel computing course in multiple universities in China, including National University of Defense Technology, Sun Yat-sen University and Hunan University. These projects were adopted from a wide range of scientific computing applications such as CFD, text mining of biomedical literature and so on. The large-scale computing resource for courses is supported by two National Supercomputing Centers, one in Guangzhou and the other in Changsha. The poster describes the background, objective, structure, task, practice process and outcome for each project. It also discusses the impact on student understanding all kinds of key topics and major challenges related to computational efficiency and scalability. Such projects build a positive practical environment to make students indulge in doing all kinds of interesting and helpful trials to validate their assumptions, especially when they have different perspectives or results for one problem. The poster presents our design evaluation rubric to reflect the effectiveness of our practice, as well as the statistics about the students" achievements for the last three semesters.