Open Access

ARTICLE

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

Zhaohui Xia^1,3, Baichuan Gao³, Chen Yu^2,*, Haotian Han³, Haobo Zhang³, Shuting Wang³

1 The State Key Lab of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China
2 School of Mathematics and Computer Science, Wuhan Polytechnic University, Wuhan, 430048, China
3 School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, 430074, China

* Corresponding Author: Chen Yu. Email:

Computer Modeling in Engineering & Sciences 2024, 138(2), 1103-1137. https://doi.org/10.32604/cmes.2023.029177

Received 06 February 2023; Accepted 21 June 2023; Issue published 17 November 2023

Abstract

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.

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