A Hybrid Parallel Method for Large Sparse Eigenvalue Problems on a Grid Computing Environment Using Ninf-G/MPI

In the present paper, we propose a hybrid parallel method for large sparse eigenvalue problems in a grid computing environment. A moment-based method that finds several eigenvalues and their corresponding eigenvectors in a given domain is used. This method is suitable for master-worker type parallel programming models. In order to improve the parallel efficiency of the method, we propose a hybrid implementation using a GridRPC system Ninf-G and MPI. We examined the performance of the proposed method in an environment where several PC clusters are used.