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In recent years, GPUs have gained attention as a powerful tool for accelerating scientific computing tasks. In this seminar, we will discuss the advantages of GPU computing over traditional CPU computing, including the ability to handle large amounts of data in parallel and significantly reduce processing time. In order to get a better overview of GPU computing practices, practical examples will be provided using CuPy, a powerful open-source library that simplifies GPU programming and makes it accessible to a wider range of users. With CuPy at our disposal, we will explore the benefits of using GPUs for data analysis, focusing on a case study using Gaia DR3 data.