| Popis: |
Most computational work in Jacobi-Davidson, an iterative method for large scale eigenvalue problems, is due to a so-called correction equation. For this, to reduce wall clock time and local memory requirements, in earlier work a domain decomposition strategy was proposed and further improved. Here we investigate practical aspects for parallel performance of the strategy by scaling experiments on supercomputers. This is of interest for large scale eigenvalue problems that need a massively parallel treatment. |
