Improving Student Skills on Parallel Programming via Code Evaluation and Feedback Debugging

Yuxiao Zhang, Jiang Li, Di Wu, Yunfei Du

Abstract: The importance of high-performance computing (HPC) motivates an increasing number of students to study parallel programming. However, a major obstacle for students to learn parallel programming is the lack of large-scale computing resources and feedback for their programs. In this paper, we design and implement an online HPC educational programming system, which provides free computing resources for students and the support of multiple HPC programming languages. The students can easily write HPC programs on our platform and submit to the Tianhe-2 supercomputer for execution. The execution results will be returned and displayed on the front-end web browser of users. In addition, our system also supports code evaluation and feedback debugging via integrating mpiP and TAU into our system kernel. The evaluation results and feedback allow students to look into the execution details of their programs and further optimize their submitted programs.