Generalized Parallel Computational Schemes for Time-Consuming Global Optimization
This paper addresses computationally intensive global optimization problems, for solving of which the supercomputing systems with exaflops performance can be required. To overcome such computational complexity, the paper proposes the generalized parallel computational schemes, which may involve numerous efficient parallel algorithms of global optimization. The proposed schemes include various ways of multilevel decomposition of parallel computations to guarantee the computational efficiency of supercomputing systems with shared and distributed memory multiprocessors with thousands of processors to meet global optimization challenges.
Keywords and phrasesGlobal optimization information-statistical theory parallel computations high-performance computing supercomputing technologies
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- 1.C. A. Floudas and M. P. Pardalos, Recent Advances in Global Optimization (Princeton Univ. Press, Princeton, 2016).Google Scholar
- 9.R. G. Strongin, V. P. Gergel, V. A. Grishagin, and K. A. Barkalov, Parallel Computations for Global Optimization Problems (Mosk. Gos. Univ., Moscow, 2013) [in Russian].Google Scholar
- 15.V. Gergel, “An unified approach to use of coprocessors of various types for solving global optimization problems,” in Proceedigns of the 2nd International Conference on Mathematics and Computers in Sciences and in Industry, 2015, pp. 13–18.Google Scholar
- 16.K. Barkalov, V. Gergel, and I. Lebedev, “Solving global optimization problems on GPU cluster,” in Proceedings of the ICNAAM 2015, Ed. by T. E. Simos, AIPConf.Proc. 1738, 400006 (2016).Google Scholar
- 21.V. A. Grishagin, “On convergence conditions for a class of global search algorithms,” in Proceedings of the 3rd All-Union Seminar on Numerical Methods of Nonlinear Programming, Kharkov, 1979, pp. 82–84.Google Scholar
- 28.V. P. Gergel, M. I. Kuzmin, N. A. Solovyov, and V. A. Grishagin, “Recognition of surface defects of coldrolling sheets based on method of localities,” Int. Rev. Autom. Control 8, 51–55 (2015).Google Scholar