| Issue |
E3S Web of Conf.
Volume 390, 2023
VIII International Conference on Advanced Agritechnologies, Environmental Engineering and Sustainable Development (AGRITECH-VIII 2023)
|
|
|---|---|---|
| Article Number | 03017 | |
| Number of page(s) | 6 | |
| Section | Information Technologies, Automation Engineering and Digitization of Agriculture | |
| DOI | https://doi.org/10.1051/e3sconf/202339003017 | |
| Published online | 01 June 2023 | |
Comparative analysis of the implementation of parallel algorithms on the central processors of automation systems in agriculture
1 Department of Biophysics and information technologies of Urgench branch of Tashkent Medical Academy, Uzbekistan
2 Urgench branch of Tashkent University of Information Technologies named after Muhammad al Khwarizmi, Uzbekistan
* Corresponding author: bahtiyar1975@mail.ru
The article presents a comparative analysis of the implementation of parallel algorithms on the central processors of automation systems in agriculture. Modern automation systems impose increased requirements on the reliability of the implementation of parallel algorithms in real time. It is proposed to use models for the development, analysis and comparison of parallel algorithms on GPUs. The proposed model of parallel computing on GPUs is designed to simplify the development of parallel algorithms for a heterogeneous CPU-GPU environment. Those, with this model, you can: develop parallel algorithms that use data parallelism, while applying the existing experience in creating parallel algorithms for the PRAM machine; evaluate the running time of the parallel algorithm and analyze which part of it is the most resource-intensive and requires optimization; compare parallel algorithms according to some parameters of the model, and, if required, select the best one according to these parameters in real time for automation in agriculture.
© The Authors, published by EDP Sciences, 2023
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.
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