An efficient and accurate method to compute the Fiedler vector based on Householder deflation and inverse power iteration
作者：
Highlights：
• We provide a method to compute the Fiedler vector of sparse graphs.
• We introduce preconditioning techniques to accelerate the convergence rate.
• Sparsity is considered in the whole computation process.
• The process is done in parallel with hybrid programming of MPI and OpenMP.
• The method is accurate, robust and efficient compared to novel schemes.
摘要
•We provide a method to compute the Fiedler vector of sparse graphs.•We introduce preconditioning techniques to accelerate the convergence rate.•Sparsity is considered in the whole computation process.•The process is done in parallel with hybrid programming of MPI and OpenMP.•The method is accurate, robust and efficient compared to novel schemes.
论文关键词：68W30,Fiedler vector,Eigenvalue problem,Parallel computing,Sparse linear system,Conjugate gradient iteration,Preconditioner
论文评审过程：Received 24 October 2012, Revised 14 January 2014, Available online 3 April 2014.
论文官网地址：https://doi.org/10.1016/j.cam.2014.03.018
