面向多尺度拓扑优化的渐进均匀化GPU并行算法研究  

Efficient GPU parallel strategy for multi-scale topology optimization via asymptotic homogenization

作　　者：夏兆辉 刘健力 高百川 聂涛 余琛 陈龙[3] 余金桂[4] XIA Zhaohui;LIU Jianli;GAO Baichuan;NIE Tao;YU Chen;CHEN Long;YU Jingui(School of Mechanical Science and Engineering/National Key Laboratory of Advanced Manufacturing Technology,Huazhong University of Science and Technology,Wuhan 430074,China;School of Mathematics and Computer Science,Wuhan Polytechnic University,Wuhan 430023,China;School of Mechanical Engineering,University of Shanghai for Science and Technology,Shanghai 200093,China;School of Mechanical and Electrical Engineering,Wuhan University of Technology,Wuhan 430070,China)

机构地区：[1]华中科技大学机械科学与工程学院/智能制造装备与技术全国重点实验室,湖北武汉430074 [2]武汉轻工大学数学与计算机学院,湖北武汉430023 [3]上海理工大学机械工程学院,上海200093 [4]武汉理工大学机电工程学院,湖北武汉430070

出　　处：《浙江大学学报（理学版）》2023年第6期722-735,共14页Journal of Zhejiang University（Science Edition）

基　　金：国家自然科学基金青年项目(52005192);国家重点研发计划青年科学家项目(2022YFB3302900).

摘　　要：针对多尺度结构拓扑设计计算效率低等问题,提出了一种基于水平集渐进均匀化的多尺度拓扑优化并行算法。基于通用图形处理器(graphics processing unit,GPU),通过水平集初始化、大型稀疏刚度矩阵方程求解以及本构矩阵并行计算,可大幅提升渐进均匀化算法的效率。实验结果表明,当三维晶胞单元网格细化至分辨率为10万时,多尺度结构拓扑优化GPU并行算法较CPU串行算法快数十倍。In response to the low computational efficiency in the context of multi-scale structural topology design,an efficient asymptotic homogenization GPU parallel strategy is presented.The strategy leverages the graphics processing unit(GPU)and investigates parallel strategies for level set initialization,large sparse stiffness matrix equations solving and constitutive properties computing.Experimental results demonstrate that the computing efficiency of the asymptotic homogenization can be greatly improved by adopting the parallel strategies,in particular,when refining a three-dimensional unit cell grid to a resolution of 100000,the GPU parallel strategy achieves a speedup of two orders of magnitude compared to the CPU serial.

关 键 词：多尺度拓扑优化 渐进均匀化 统一计算设备架构(CUDA) GPU并行计算 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]