The university education in parallel and high-performance computing often suffers from a significant gap between the effects and potential performance taught in the lectures on the one hand and those practically experienced in exercises or lab courses on the other hand. With a small number of processors, the results obtained are often hardly convincing; however, supercomputers are rarely accessible to students doing their first steps in parallel programming. In this contribution, we present our experiences of how a state-of-the-art mid-size Linux cluster, bought and operated on a department level primarily for education and algorithm development purposes, can be used for teaching a large variety of HPC aspects. Special focus is put on the effects of such an approach on the intensity and sustainability of learning.
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The university education in parallel and high-performance computing often suffers from a significant gap between the effects and potential performance taught in the lectures on the one hand and those practically experienced in exercises or lab courses on the other hand. With a small number of processors, the results obtained are often hardly convincing; however, supercomputers are rarely accessible to students doing their first steps in parallel programming. In this contribution, we present our...
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