Structural and Multidisciplinary Optimization

, Volume 56, Issue 2, pp 413–434 | Cite as

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

RESEARCH PAPER
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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.

Keywords

Isogeometric analysis Topology optimization Level set method CUDA GPU parallel computing 

Notes

Acknowledgements

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

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Copyright information

© Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  • Zhaohui Xia
    • 1
  • Yingjun Wang
    • 2
  • Qifu Wang
    • 3
  • Chao Mei
    • 3
  1. 1.Center for Modeling, Simulation and Imaging in Medicine (CeMSIM)Rensselaer Polytechnic InstituteTroyUSA
  2. 2.School of Mechanical and Automotive EngineeringSouth China University of TechnologyGuangzhouChina
  3. 3.National CAD Support Software Engineering Research CenterHuazhong University of Science and TechnologyWuhanChina

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