Change mechanism of solver performance: With a special focus on time history analysis of supertall buildings

Abstract

SummaryThe correlation between the performance of some commonly used linear system solvers and the characteristics of system matrices, especially in the time history analysis of supertall buildings, is comprehensively identified. Relying on 5 well‐designed structural models with height varying from 47 to 660 m, the supernodal LLT solver and the conjugate gradient (CG) solver with the factorized sparse approximate inverse preconditioner are selected due to their actual efficiency. More importantly, basing on 90 fictitious supertall structural models generated from the parameterized method, the effects of structural characteristics on solver performance and the corresponding mechanism are studied by 3 mathematical indexes with parameters come from the equivalent dynamic stiffness matrices. Impacts of processors on the solvers are also clarified by associating the architectural characteristics of processors with the indexes. The performance of the 2 solvers is affected globally with increasing building size; different variation laws are shown for different structural systems. However, the accuracy of the CG solver does not exhibit distinct variation due to a slight change in the 2‐norm condition number of the matrices. The CG solver is found to be more applicable on GPU processor than the LLT solver due to its smaller gap between computational workload and the amount of data transferred.