We propose an eigensolver and the corresponding package, GCGE, for solving large scale eigenvalue problems. This method is the combination of damping idea, subspace projection method and inverse power method with dynamic shifts. To reduce the dimensions of projection subspaces, a moving mechanism is developed when the number of desired eigenpairs is large. The numerical methods, implementing techniques and the structure of the package are presented. Plenty of numerical results are provided to demonstrate the efficiency, stability and scalability of the concerned eigensolver and the package GCGE for computing many eigenpairs of large symmetric matrices arising from applications.
翻译:我们建议使用一个除子体和相应的包件(GCGE),以解决大规模除子值问题。这个方法是将阻断想法、子空间投射方法和反动力法与动态变化相结合。为了减少投影子空间的尺寸,当所需的除子体数量很大时,将开发一个移动机制。提出了该包的数值方法、实施技术和结构。提供了大量的数字结果,以证明有关除子体和GCGE用于计算应用产生的许多大对称矩阵的除子体数量的效率、稳定性和可伸缩性。