TY  - EJOU
AU  - Li, Xuesong 
AU  - Wang, Shuting 
AU  - Luo, Nianmeng 
AU  - Yang, Aodi 
AU  - Yuan, Xing 
AU  - Xie, Xianda 

TI  - GPU-Enabled Isogometric Topology Optimization with Bėzier Element Stiffness Mapping
T2  - Computer Modeling in Engineering \& Sciences

PY  - 2025
VL  - 142
IS  - 2
SN  - 1526-1506

AB  - Due to the high-order B-spline basis functions utilized in isogeometric analysis (IGA) and the repeatedly updating global stiffness matrix of topology optimization, Isogeometric topology optimization (ITO) intrinsically suffers from the computationally demanding process. In this work, we address the efficiency problem existing in the assembling stiffness matrix and sensitivity analysis using Bėzier element stiffness mapping. The Element-wise and Interaction-wise parallel computing frameworks for updating the global stiffness matrix are proposed for ITO with Bėzier element stiffness mapping, which differs from these ones with the traditional Gaussian integrals utilized. Since the explicit stiffness computation formula derived from Bėzier element stiffness mapping possesses a typical parallel structure, the presented GPU-enabled ITO method can greatly accelerate the computation speed while maintaining its high memory efficiency unaltered. Numerical examples demonstrate threefold speedup: 1) the assembling stiffness matrix is accelerated by 10× maximumly with the proposed GPU strategy; 2) the solution efficiency of a sparse linear system is enhanced by up to 30× with Eigen replaced by AMGCL; 3) the efficiency of sensitivity analysis is promoted by 100× with GPU applied. Therefore, the proposed method is a promising way to enhance the numerical efficiency of ITO for both single-patch and multiple-patch design problems.
KW  - Isogeometric analysis; topology optimization; GPU; sparse system solver; Bėzier element stiffness mapping

DO  - 10.32604/cmes.2024.058798