Introducing parallel programming to traditional undergraduate courses

Abstract

Parallel programming is an important issue for current multi-core processors and necessary for new generations of many-core architectures. This includes processors, computers, and clusters. However, the introduction of parallel programming in undergraduate courses demands new efforts to prepare students for this new reality. This paper describes an experiment on a traditional Computer Science course during a two-year period. The main focus is the question of when to introduce parallel programming models in order to improve the quality of learning. The goal is to propose a method of introducing parallel programming based on OpenMP (a shared-variable model) and MPI (a message-passing model). Results show that when the OpenMP model is introduced before the MPI model the best results are achieved. The main contribution of this paper is the proposed method that correlates several concepts such as concurrency, parallelism, speedup, and scalability to improve student motivation and learning.