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18 November 2024 Research on parallel optimization and acceleration technology for new energy power generation large model computing based on localized supercomputing platforms
Rundong Gan, Bin Wang, Chen Luo, Xuepeng Mu, Che Wang, Haibin Su, Bin Liu
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Proceedings Volume 13403, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2024) ; 1340321 (2024) https://doi.org/10.1117/12.3051633
Event: International Conference on Algorithms, High Performance Computing, and Artificial Intelligence, 2024, Zhengzhou, China
Abstract
Due to the disconnection between arithmetic demand and supply, and encountering the limitations of cloud blocking in the upgrading process, in order to solve the challenges of computational complexity and accuracy, as well as the problems of data security and privacy protection, we propose the research of parallel optimization and acceleration technology for new energy power generation large-scale model computation based on localized supercomputing platform. This study enhances efficient parallel algorithms in the prediction process by parallelizing the processing and improving the time complexity of the algorithms, dividing the large-scale computational task into multiple subtasks and executing these subtasks simultaneously, establishing regular performance monitoring and optimization plans, and periodically evaluating the performance of the system. After the optimization measures are implemented, performance testing and validation are carried out, and the experiments show that the computational parallel optimization acceleration of new energy generation capacity prediction is realized on the supercomputing platform. The optimization effect meets the expectation and achieves 100% of the set performance index.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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Rundong Gan, Bin Wang, Chen Luo, Xuepeng Mu, Che Wang, Haibin Su, and Bin Liu "Research on parallel optimization and acceleration technology for new energy power generation large model computing based on localized supercomputing platforms", Proc. SPIE 13403, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2024) , 1340321 (18 November 2024); https://doi.org/10.1117/12.3051633
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KEYWORDS
Mathematical optimization
Data modeling
Data storage
Parallel computing
Computing systems
Parallel processing
Power grids
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