Education and training for exascale

This editorial focuses on education and training approaches on the route to exascale. In a wider context the editorial outlines how the Computational Science research methods can be used in university studies and professional training in HPC in order to narrow the HPC and Computational Science skills gap. It provides short analysis of the HPC and Computational Science research context and analyses the current state. It also describes and proposes the relevant curricula structure covering not only mathematics, computer science and supercomputing areas but also natural and life sciences domains. It is aimed at enhancing student's and professional's research profiles developing their abilities to investigate complex problems, build and apply advanced mathematical models, analyze the resulting data and use adequately HPC environments and tools for computation and visualization all so needed on the route to exascale. It also gives examples how this approach can be applied in Higher Education setting in case of specific scientific domains with explicitly taught and embedded Computational Science subjects and in case of professional training and outlines the differences and similarities in both cases as well as links the proposed approach with the papers in the special section.