Parallel preconditioned conjugate gradient optimization of the Rayleigh quotient for the solution of sparse eigenproblems
作者:
Highlights:
•
摘要
A parallel algorithm based on the multidimensional minimization of the Rayleigh quotient is proposed to evaluate the leftmost eigenpairs of the generalized symmetric positive definite eigenproblem. The minimization is performed via a conjugate gradient-like procedure accelerated by a factorized approximate inverse preconditioner (FSAI) and by a number of block preconditioners. The resulting code obtains a high level of parallel efficiency and proves to be comparable with the PARPACK package on a set of large matrices arising from various discretizations of PDEs of elliptic/parabolic type.
论文关键词:
论文评审过程:Available online 25 October 2005.
论文官网地址:https://doi.org/10.1016/j.amc.2005.09.015