| Issue |
E3S Web of Conf.
Volume 508, 2024
International Conference on Green Energy: Intelligent Transport Systems - Clean Energy Transitions (GreenEnergy 2023)
|
|
|---|---|---|
| Article Number | 03002 | |
| Number of page(s) | 10 | |
| Section | IoT, AI and Data Analytics | |
| DOI | https://doi.org/10.1051/e3sconf/202450803002 | |
| Published online | 05 April 2024 | |
Choosing a library for the Python programming language for visualizing the operation of parallel algorithms
1 Dmytro Motornyi Tavria State Agrotechnological University, 66 Zhukovsky Str., Zaporizhzhia, 69600, Ukraine
2 Bogdan Khmelnitsky Melitopol State Pedagogical University, 59 Naukovoho mistechka Str., Zaporizhzhia, 69000, Ukraine
3 Pavlo Tychyna Uman State Pedagogical University, 2 Sadova Str., Uman, 20300, Ukraine
* Corresponding author: segsharov@gmail.com
The research compares the capabilities of several libraries for the Python language, which allow creating a test application and visually demonstrate the operation of a parallel program in real time. It was found that the Python language is often used to develop parallel programs with internal and external libraries. To provide multithreading and parallelism, applications created in Python use external libraries, including mpi4py.futures, PETSc for Python, MPI for Python, d2o, Playdoh, PyOMP, and others. Visualization and animation of the operation of parallel programs will help to understand the principles of parallel computing. We compared test applications created with the use of Matplotlib, Seaborn, Plotly, Bokeh, Pygame, PyOpenGL libraries. According to the results of the observation, it was found that the Seaborn library is the best choice for developing a test application for animating the operation of a parallel program.
Key words: Python / parallel computing / programming / libraries
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.