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Algebraic Multi-level substructuring (AMLS) techniques have demonstrated great success in computing eigen-analysis of extremely large scale matrices arising from structural dynamics applications, such as the vibration of car bodies. In these applications, it is typical that a large number of eigenvalues with relatively low accuracy are required. However, such a lack of accuracy is a cause for concern in some applications. In this talk, we present an algebraic multi-level Krylov substructuring (AMLKS) method, which preserves the mechanism of AMLS techniques, such as efficiency and parallelism, and meanwhile significantly improves the accuracy of computed eigenvalues. The gist of AMLKS method is to replace the eigenmodes of interior substructures by proper Krylov modes of the substructures, which take the coupling among substructures into the account. The accuracy improvement of the AMLKS method are demonstrated by numerical results from electromagnetic and MEMS simulations. This is a joint work with Zhaojun Bai.