The study course covers the theoretical and practical principles of massively parallel high-performance computing that are implemented in a unified framework of multiprocessor systems and specialized software environment. The study course includes an overview of types of high-performance computing hardware and software architecture, computing algorithms, application libraries and tools.

This study course covers the theoretical and practical principles of high performance computing that are implemented using graphics processing hardware and specialized software. The study course includes an overview of CUDA parallel computing platform architecture based on graphics processors, parallel computing algorithms, application libraries and tools. An in-depth focus is put on the interdisciplinary application of CUDA, for example, in the areas of big data analysis, interoperability with computer graphics, image processing, computational modelling and machine learning.