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A Parallel Computing Schema Based on IGA

Jinggang Deng1,2, Bingquan Zuo1,2,*, Huixin Luo1,2, Weikang Xie1,2, Jiashu Yang1,2

1 Key Laboratory of Metallurgical Equipment and Control Technology Ministry of Education, Wuhan University of Science and Technology, Wuhan, 430081, China
2 Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering, Wuhan University of Science and Technology, Wuhan, 430081, China

* Corresponding Author: Bingquan Zuo. Email: email

(This article belongs to the Special Issue: Numerical Methods in Engineering Analysis, Data Analysis and Artificial Intelligence)

Computer Modeling in Engineering & Sciences 2022, 132(3), 965-990. https://doi.org/10.32604/cmes.2022.020631

Abstract

In this paper, a new computation scheme based on parallelization is proposed for Isogeometric analysis. The parallel computing is introduced to the whole progress of Isogeometric analysis. Firstly, with the help of the “tensorproduct” and “iso-parametric” feature, all the Gaussian integral points in particular element can be mapped to a global matrix using a transformation matrix that varies from element. Then the derivatives of Gauss integral points are computed in parallel, the results of which can be stored in a global matrix. And a middle layer is constructed to assemble the final stiffness matrices in parallel. The numerical example results show that: the method presented in the paper can reduce calculation time and improve the use rate of computing resources.

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Cite This Article

APA Style
Deng, J., Zuo, B., Luo, H., Xie, W., Yang, J. (2022). A parallel computing schema based on IGA. Computer Modeling in Engineering & Sciences, 132(3), 965-990. https://doi.org/10.32604/cmes.2022.020631
Vancouver Style
Deng J, Zuo B, Luo H, Xie W, Yang J. A parallel computing schema based on IGA. Comput Model Eng Sci. 2022;132(3):965-990 https://doi.org/10.32604/cmes.2022.020631
IEEE Style
J. Deng, B. Zuo, H. Luo, W. Xie, and J. Yang "A Parallel Computing Schema Based on IGA," Comput. Model. Eng. Sci., vol. 132, no. 3, pp. 965-990. 2022. https://doi.org/10.32604/cmes.2022.020631



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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