دورية أكاديمية

A Hybrid Parallel Strategy for Isogeometric Topology Optimization via CPU/GPU Heterogeneous Computing.

التفاصيل البيبلوغرافية
العنوان: A Hybrid Parallel Strategy for Isogeometric Topology Optimization via CPU/GPU Heterogeneous Computing.
المؤلفون: Zhaohui Xia, Baichuan Gao, Chen Yu, Haotian Han, Haobo Zhang, Shuting Wang
المصدر: CMES-Computer Modeling in Engineering & Sciences; 2024, Vol. 138 Issue 2, p1103-1137, 35p
مستخلص: This paper aims to solve large-scale and complex isogeometric topology optimization problems that consume significant computational resources. A novel isogeometric topology optimization method with a hybrid parallel strategy of CPU/GPU is proposed, while the hybrid parallel strategies for stiffness matrix assembly, equation solving, sensitivity analysis, and design variable update are discussed in detail. To ensure the high efficiency of CPU/GPU computing, a workload balancing strategy is presented for optimally distributing the workload between CPU and GPU. To illustrate the advantages of the proposed method, three benchmark examples are tested to verify the hybrid parallel strategy in this paper. The results show that the efficiency of the hybrid method is faster than serial CPU and parallel GPU, while the speedups can be up to two orders of magnitude. [ABSTRACT FROM AUTHOR]
Copyright of CMES-Computer Modeling in Engineering & Sciences is the property of Tech Science Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
قاعدة البيانات: Complementary Index
الوصف
تدمد:15261492
DOI:10.32604/cmes.2023.029177