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We present a parallel implementation of the Davidson method for the numerical solution of large-scale, sparse, generalized eigenvalue problems. The implementation is done in the context of SLEPc, the Scalable Library for Eigenvalue Problem Computations. In this work, we focus on the Hermitian version of the method, with several optimizations. We compare the developed solver with other available implementations, as well as with Krylov-type eigensolvers already available in SLEPc, particularly in terms of parallel efficiency.

A Parallel Implementation of the Davidson Method for Generalized Eigenproblems