GPU parallel strategy for parameterized LSM-based topology optimization using isogeometric analysis
发布时间：2020-12-04
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- 论文类型：
- 期刊论文
- 发表刊物：
- Structural and Multidisciplinary Optimization
- 收录刊物：
- SCI
- 学科门类：
- 工学
- 一级学科：
- 机械工程
- 关键字：
- Isogeometric analysis Topology optimization Level set method CUDA GPU parallel computing
- DOI码：
- 10.1007/s00158-017-1672-x
- 摘要：
- 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.