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.
Supported in part by the Intel Research Grant “Parallel Computing on Multiprocessor and Multi-computer Systems for Globally Optimal Decision Making"
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Gergel, V.P., Strongin, R.G. (2003). Parallel Computing for Globally Optimal Decision Making. In: Malyshkin, V.E. (eds) Parallel Computing Technologies. PaCT 2003. Lecture Notes in Computer Science, vol 2763. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45145-7_7
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DOI: https://doi.org/10.1007/978-3-540-45145-7_7
Publisher Name: Springer, Berlin, Heidelberg
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