Parallel Global Optimization of High-Dimensional Problems

نویسندگان

Siegfried Höfinger

Torsten Schindler

András Aszódi

چکیده

A parallel version of an optimization algorithm for arbitrary functions of arbitrary dimension N has been developed and tested on an IBM-Regatta HPC system equipped with 16 CPUs of Power4 type, each with 1.3 GHz clock frequency. The optimization algorithm follows a simplex-like stochastic search technique aimed at quasi-complete sampling of all the local minima. Parallel functionality is incorporated with the Message Passing Interface MPI version 1.2. The program is applied to typical problems of dimension N=60 and N=512 and the results are analyzed with respect to operability and parallel scalability.

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