Abstract
A problem of mapping graphs of parallel programs onto graphs of distributed computer systems by recurrent neural network is formulated. Parameter values providing absence of incorrect solutions are experimentally determined. Optimal solutions are found for mapping a “line”-graph onto a two-dimensional torus due to introduction into Lyapunov function of penalty coefficients for the program graph edges not-mapped onto the system graph edges. For increasing probability of finding optimal mapping, a method for splitting the mapping is proposed. The method essence is a reducing solution matrix to a block-diagonal form. The Wang recurrent neural network is used to exclude incorrect solutions of the problem of mapping the line-graph onto three-dimensional torus. This network converges quicker than the Hopfield one.
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Tarkov, M.S. (2011). On Mapping Graphs of Parallel Programs onto Graphs of Distributed Computer Systems by Recurrent Neural Networks. In: Malyshkin, V. (eds) Parallel Computing Technologies. PaCT 2011. Lecture Notes in Computer Science, vol 6873. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23178-0_31
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DOI: https://doi.org/10.1007/978-3-642-23178-0_31
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