Parallelization of the discrete gradient method of non-smooth optimization and its applications

Authors:
G. Beliakov;J. E. Monsalve Tobon;A. M. Bagirov
Affiliations:
School of Information Technology, Deakin University, Australia;School of Information Technology, Deakin University, Australia;School of Information Technology, Deakin University, Australia
Venue:
ICCS'03 Proceedings of the 2003 international conference on Computational science: PartIII
Year:
2003

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Abstract

We investigate parallelization and performance of the discrete gradient method of nonsmooth optimization. This derivative free method is shown to be an effective optimization tool, able to skip many shallow local minima of nonconvex nondifferentiable objective functions. Although this is a sequential iterative method, we were able to parallelize critical steps of the algorithm, and this lead to a significant improvement in performance on multiprocessor computer clusters. We applied this method to a difficult polyatomic clusters problem in computational chemistry, and found this method to outperform other algorithms.