As a consequence of the COVID-19 pandemic and measures to secure public health, many processes have moved to the online space. The educational process is not an exception. Our main goal, which is presented in this article, was to re-design the educational process from face-to-face to distance learning in the Mathematics 1 course at the Technical University of Košice. This article describes our approach to teaching, observations, and experience. This case study examines three factors: Firstly, the impact of distance education on overall assessments of students. Using descriptive statistics, the results of student evaluations were compared from the overall assessments for the last six academic years. It was found that distance learning does not affect excellent students and eliminates the number of students who do not pass. Secondly, the participation of students during online lessons, and thirdly, the use of electronic materials. The questionnaire survey and the data from the learning management system Moodle were used to examine the second and third factors. Descriptive statistics were used to describe the questionnaire survey data (frequencies, percentages and averages). An exploratory factor analysis was performed in order to assess the underlying key concepts regarding student evaluation of the teaching process. The exploratory factor analysis confirmed that this questionnaire followed the four key concepts.

This paper deals with the design and implementation of cross-platform, D2Q9-BGK and D3Q27-MRT, lattice Boltzmann method solver for 2D and 3D flows developed with ArrayFire library for high-performance computing. The solver leverages ArrayFire’s just-in-time compilation engine for compiling high-level code into optimized kernels for both CUDA and OpenCL GPU backends. We also provide C++ and Rust implementations and show that it is possible to produce fast cross-platform lattice Boltzmann method simulations with minimal code, effectively less than 90 lines of code. An illustrative benchmarks (lid-driven cavity and Kármán vortex street) for single and double precision floating-point simulations on 4 different GPUs are provided.

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