This course is intended for master and PhD students, postdocs and scientists who want to enhance the performance of their scripts and algorithms currently running on Matlab. No prior knowledge of MPI or supercomputer usage is required. Basic knowledge of Python is recommended. Attendants are highly encouraged to bring their own Matlab scripts. This course involves theoretical and hands on sessions which will be guided by experts in Python, Matlab and High Performance Computing. The course will focus on numerical and statistical analysis as well as on image processing applications. Finally, code will be taken to the supercomputers where basic parallel programming (MPI) will be used to exploit parallelism in the computation. Then, optimization of scripts using more Pythonic data structures and functions will be shown. The training course will be divided into three stages: First, attendants will learn how to do a direct translation of language concepts from Matlab to Python. Python also provides high portability and flexibility (interaction with other open source and proprietary software packages) without any licensing costs. Matlab and Python have a comparable language philosophy and Python offers complementary alternatives for optimizations and parallelization. In this course we want to introduce Matlab programmers to the usage of Python. Python is becoming a popular language for scientific applications and is increasingly used for high performance computing. Python gives you lots of control but can take longer to do the same. Seems like matlab is better for quickly banging out an image/result but doesnt give you much control. Python took longer, was more fun and interesting to learn and has more use in home projects. The link to the online platform will be provided to the registrants only. Matlab didnt take me very long to get familiar with. This course will take place as an online event. 1712022 in the training programme 2022 of Forschungszentrum Jülich)
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