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GPU parallel strategy for parameterized LSM-based topology optimization using isogeometric analysis

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Abstract

This paper proposes a new level set-based topology optimization (TO) method using a parallel strategy of Graphics Processing Units (GPUs) and the isogeometric analysis (IGA). The strategy consists of parallel implementations for initial design domain, IGA, sensitivity analysis and design variable update, and the key issues in the parallel implementation, e.g., the parallel assembly race condition, are discussed in detail. The computational complexity and parallelization of the different steps in the TO are also analyzed in this paper. To better demonstrate the advantages of the proposed strategy, we compare efficiency of serial CPU, multi-thread parallel CPU and GPU by benchmark examples, and the speedups achieve two orders of magnitude.

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Acknowledgements

This research was supported by the National Natural Science Foundation of China (51475180).

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Authors and Affiliations

  1. Center for Modeling, Simulation and Imaging in Medicine (CeMSIM), Rensselaer Polytechnic Institute, Troy, NY, 12180, USA

    Zhaohui Xia

  2. School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou, Guangdong, 510641, China

    Yingjun Wang

  3. National CAD Support Software Engineering Research Center, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China

    Qifu Wang & Chao Mei

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  1. Zhaohui Xia
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  2. Yingjun Wang
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  4. Chao Mei
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Correspondence to Yingjun Wang.

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Xia, Z., Wang, Y., Wang, Q. et al. GPU parallel strategy for parameterized LSM-based topology optimization using isogeometric analysis. Struct Multidisc Optim 56, 413–434 (2017). https://doi.org/10.1007/s00158-017-1672-x

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