Code | DMI741 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Name | Introduction to High Performance Computing Technology CUDA | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Status | Compulsory/Courses of Limited Choice | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Level and type | Undergraduate Studies, Academic | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Field of study | Computer Science | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Faculty | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Academic staff | Arnis Lektauers | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Credit points | 3.0 (4.5 ECTS) | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Parts | 1 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Annotation |
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. In addition to the theoretical lectures, in the laboratory classes there are provided the opportunities to gain practical skills in the development of information technology solutions using the CUDA technology. . |
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Contents |
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Goals and objectives of the course in terms of competences and skills |
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Learning outcomes and assessment |
Able to define, interpret and use professional terminology in the field of graphics processor-based high-performance computing. - Test successfully passed. Able to develop a software solution based on CUDA technology. - Is able to explain the nature, possibilities, limitations and importance of the use of high-performance computing technologies in certain fields of science and practice. Able to evaluate the basic ways of developing the proposed high-performance software solution, as well as the limitations of use and optimization options. - During the laboratory work and individual research, the student is able to identify possible solutions and limitations of the given task and offer alternative solutions. Able to explain the nature, possibilities, limitations and importance of the use of high-performance computing technologies in certain fields of science and practice. - During the exam, the ability to recognize the essence of the formulated thematic questions, as well as to give a concise and correct explanation of the given topics is demonstrated. |
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Evaluation criteria of study results |
Laboratory tasks - 25%
Research task - 25% Test - 20% Exam - 30% |
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Course prerequisites | Basic knowledge of C / C ++ programming language | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Course planning |
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