Abstract: The paper describes an ontology-based methods and framework for design of learning courses covering the HPC and Big Data areas and how to include these into Computational Science training within the remit of existing courses of Master Programme entitled “Applied Mathematics and Computer Science” (Faculty of Mechanics and Mathematics, Perm State University, Russia). It helped bringing together the university and IT-companies around a real industry projects in the field of Big Data with active participation of master’s students. In this paper, the visual tools and ontology-based methods for computer-supported collaborative learning environment will be also presented.

Abstract: High-Performance Computing (HPC) and the ability to process large amounts of data are of paramount importance for UK business and economy as outlined by Rt Hon David Willetts MP at the HPC and Big Data conference in February 2014. However there is a shortage of skills and available training in HPC to prepare and expand the workforce for the HPC and Big Data research and development. Currently, HPC skills are acquired mainly by students and staff taking part in HPC-related research projects, MSc courses, and at the dedicated training centres such as Edinburgh University’s EPCC. There are few UK universities teaching the HPC, Clusters and Grid Computing courses at the undergraduate level. To address the issue of skills shortages in the HPC it is essential to provide teaching and training as part of both postgraduate and undergraduate courses. The design and development of such courses is challenging since the technologies and software in the fields of large scale distributed systems such as Cluster, Cloud and Grid computing are undergoing continuous change. The students completing the HPC courses should be proficient in these evolving technologies and equipped with practical and theoretical skills for future jobs in this fast developing area. In this paper we present our experience in developing the HPC, Cluster and Grid modules including a review of existing HPC courses offered at the UK universities. The topics covered in the modules are described, as well as the coursework project based on practical laboratory work. We conclude with an evaluation based on our experience over the last ten years in developing and delivering the HPC modules on the undergraduate courses, with suggestions for future work.

Abstract: Recently, the idea of quantum computation is becoming more and more popular and there are many attempts to build quantum computers. Therefore, there is a need to introduce this topic to regular students of computer science and engineering. In this paper we present a concept of a course powered by the Quantum Integrated Development Environment (QuIDE), the new quantum computer simulator that joins features of GUI based simulators with interpreters and simulation library approach. The idea of the course is to put together theoretical aspects with practical assignments realized on the QuIDE simulator. Such an approach enables studying a variety of topics in a way understandable for this category of students. The topics of the course included understanding the concept of quantum gates, registers and a series of algorithms: Deutsch and Bernstein-Vazirani Problems, Grover's Fast Database Search, Shor's Prime Factorization, Quantum Teleportation and Quantum Dense Coding. We describe results of QuIDE assessment during the course; our solution scored more points in System Usability Scale survey then the other tool previously used for that purpose. We also show that the most useful features of such a tool indicated by students are similar to the assumptions made on the simulator functionality.

Abstract: In this paper the use of adaptive scientific visualization tools in education, including in the area of high performance computing education is proposed in order to help students understand in depth the nature of particular scientific problems and to help them to learn parallel computing approaches to solving these problems. The proposed approach may help to bridge the talent gap in natural and computational sciences, since high quality visualization can help to uncover hidden regularities in the data with which the researchers and students work and can lead to new level of understanding how the data can be partitioned and processed in parallel. A multiplatform client-server scientific visualization system is presented that can be easily integrated with third-party solvers from any field of science. This system can be used as a visual aid and a collaboration tool in high performance computing education.