The paper contains the results of investigation of a parallel global optimization algorithm combined with a dimension reduction scheme. This allows solving multidimensional problems by means of reducing to data-independent subproblems with smaller dimension solved in parallel. The new element implemented in the research consists in using several graphic accelerators at different computing nodes. The paper also includes results of solving problems of well-known multiextremal test class GKLS on Lobachevsky supercomputer using tens of thousands of GPU cores.
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Research Article| June 08 2016
Solving global optimization problems on GPU cluster
AIP Conf. Proc. 1738, 400006 (2016)
Konstantin Barkalov, Victor Gergel, Ilya Lebedev; Solving global optimization problems on GPU cluster. AIP Conf. Proc. 8 June 2016; 1738 (1): 400006. https://doi.org/10.1063/1.4952194
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