求解饱和多孔介质流固耦合动力响应问题的异构并行算法OA
Heterogeneous parallel algorithm for solving the fluid-structure coupling dynamic response problem in saturated porous media
在地震动载荷作用下,饱和土体易发生液化,引发地面沉降、地基失稳、砂土喷砂冒水等次生灾害.用传统的基于计算机的中央处理器(central processing unit,简称CPU)的串行数值计算方法进行饱和介质动力响应分析时,由于耦合模型系数矩阵数目多以及方程之间强耦合等因素,会出现计算效率低、计算精度低等问题.针对超大规模复杂流固耦合模型在传统数值框架下的数值计算瓶颈问题,设计了基于计算机的CPU和图形显卡(graphics processing unit,简称GPU)异构并行的计算框架,通过优化大规模数据的并行计算流程,减少CPU和GPU之间的数据传输,结合数据打包方案,减少不必要的时间开销;采用预处理非装配法直接构建整体矩阵的压缩稀疏行(compressed sparse row,简称CSR)压缩格式,避免传统方法组装整体矩阵时产生的巨量内存消耗,使得程序可以以较少的内存资源计算超大规模的有限元模型,降低了程序计算所需的内存和时间成本;基于 CUDA 内置函数,提出一套新的方程迭代求解方案,构建了适用于多场耦合问题的并行迭代求解器.针对复杂的流固耦合动力响应问题,提出的并行求解器较传统串行计算方法呈现数量级的性能跃升,计算效率提升达2个数量级,计算规模突破千万自由度量级.与ABAQUS软件相比,计算效率提高15倍以上.
Under the influence of ground motion loads,saturated soil is susceptible to liquefaction,leading to secondary disasters such as ground settlement,foundation failure,and sand ejection with water seepage.When performing dynamic response analysis of saturated media using the traditional central processing unit(CPU)-based serial numerical calculation method,the large number of coupled model coefficient matrices and the strong coupling between equations result in issues such as low computational efficiency and precision.To address the numerical computing bottleneck associated with ultra-large-scale complex fluid-structure coupling models under the traditional numerical framework,this study proposes a computational framework based on CPU and graphics processing unit(GPU)heterogeneous parallelism.By optimizing the parallel computing process for large-scale data,minimizing data transfer between the CPU and GPU,and employs a data packaging strategy to reduce unnecessary time consumption.By directly constructing the global matrix in compressed sparse row(CSR)compression format through a preprocessing non-assembly method,it avoids the significant memory consumption typically incurred by traditional assembly methods.This enables the program to compute ultra-large-scale finite element models with reduced memory resources,thereby lowering both memory and time costs.Leveraging an intrinsic CUDA function,a novel set of iterative solution schemes for equations was developed,and a parallel iterative solver tailored for multi-field coupling problems was constructed.For complex fluid-structure interaction dynamic response problems,the proposed parallel solver demonstrates an order of magnitude improvement over traditional serial computation methods.The computational capacity threshold surpasses tens of millions of degrees of freedom.Compared to ABAQUS software,the computational efficiency has increased by more than 15 times.
周清龙;林烷沧
中南大学 资源与安全工程学院,湖南 长沙 410083中南大学 资源与安全工程学院,湖南 长沙 410083
数理科学
有限元GPU并行计算流固耦合动力响应
finite elementGPU parallel computingfluid-structure couplingdynamic response
《岩土力学》 2026 (3)
1078-1095,18
国家自然青年基金(No.52004332). This work was supported by the National Natural Science Foundation of China(52004332).
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