Parallel computing for globally optimal decision making on cluster systems

Authors:
V. P. Gergel;R. G. Strongin
Affiliations:
Nizhni Novgorod State University, Gagarin prosp. 23, Nizhni Novgorod 603950, Russia;Nizhni Novgorod State University, Gagarin prosp. 23, Nizhni Novgorod 603950, Russia
Venue:
Future Generation Computer Systems - Special issue: Parallel computing technologies
Year:
2005

Citing 2
Cited 0

In search of clusters (2nd ed.)

In search of clusters (2nd ed.)
Global Optimization with Non-Convex Constraints - Sequential and Parallel Algorithms (Nonconvex Optimization and its Applications Volume 45) (Nonconvex Optimization and Its Applications)

Global Optimization with Non-Convex Constraints - Sequential and Parallel Algorithms (Nonconvex Optimization and its Applications Volume 45) (Nonconvex Optimization and Its Applications)

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents a new scheme for parallel computations on cluster systems for time-consuming problems of globally optimal decision making. This uniform scheme (without any centralized control processor) is based on the idea of multidimensional problem reduction. Using same new multiple mappings (of the Peano curve type), a multidimensional problem is reduced to a family of univariate problems which can be solved in parallel in such a way that each of these processors shares the information obtained by the other processors.