Efficient use of parallelism in algorithmic parameter optimization applications |
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Authors: | C. Audet C.-K. Dang D. Orban |
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Affiliation: | 1. GERAD and Département de Mathématiques et de Génie Industriel, école polytechnique de Montréal, Montreal, Canada
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Abstract: | In the context of algorithmic parameter optimization, there is much room for efficient usage of computational resources. We consider the Opal framework in which a nonsmooth optimization problem models the parameter identification task, and is solved by a mesh adaptive direct search solver. Each evaluation of trial parameters requires the processing of a potentially large number of independent tasks. We describe and evaluate several strategies for using parallelism in this setting. Our test scenario consists in optimizing five parameters of a trust-region method for smooth unconstrained minimization. |
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