Computational science and HPC education for graduate students: Paving the way to exascale

The article discusses the experience of teaching supercomputer disciplines to students specializing in Computational Mathematics. Graduates specializing in this field become future developers and users of complex supercomputing applications and systems. The article presents the structure of a training program that has been implemented at the Faculty of Computational Mathematics and Cybernetics of Lomonosov Moscow State University. It focuses on the content of disciplines related to parallel computing with a detailed description of the structure and content of the course “Supercomputing Simulation and Technologies”, which is offered as part of the Master's degree training program at the Faculty. The content of practical assignments supporting this discipline is discussed in detail, along with the results produced by the students who performed these practical assignments on Lomonosov and IBM Blue Gene/P supercomputers. The main contribution of the paper is twofold: we draw attention to the importance of study of a wide set of parallel algorithms properties and provide a practical methodology to reach this goal.