Gaoyuan Yu¹, Yunfeng Lou², Hang Dong³, Junjie Li¹, Xianlong Jin^1,*

CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 2795-2816, 2023, DOI:10.32604/cmc.2023.037375

Abstract The strict and high-standard requirements for the safety and stability of major engineering systems make it a tough challenge for large-scale finite element modal analysis. At the same time, realizing the systematic analysis of the entire large structure of these engineering systems is extremely meaningful in practice. This article proposes a multilevel hierarchical parallel algorithm for large-scale finite element modal analysis to reduce the parallel computational efficiency loss when using heterogeneous multicore distributed storage computers in solving large-scale finite element modal analysis. Based on two-level partitioning and four-transformation strategies, the proposed algorithm not only improves the memory access rate through… More >

Gaoyuan Yu¹, Yunfeng Lou², Hang Dong³, Junjie Li¹, Xianlong Jin^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 135-155, 2023, DOI:10.32604/cmes.2023.025166

Abstract Heterogeneous multicore clusters are becoming more popular for high-performance computing due to their great computing power and cost-to-performance effectiveness nowadays. Nevertheless, parallel efficiency degradation is still a problem in large-scale structural analysis based on heterogeneous multicore clusters. To solve it, a hybrid hierarchical parallel algorithm (HHPA) is proposed on the basis of the conventional domain decomposition algorithm (CDDA) and the parallel sparse solver. In this new algorithm, a three-layer parallelization of the computational procedure is introduced to enable the separation of the communication of inter-nodes, heterogeneous-core-groups (HCGs) and inside-heterogeneous-core-groups through mapping computing tasks to various hardware layers. This approach can… More >