Abstract
Today, various researchers have developed a set of methods for optimizing parallel algorithms for systems with distributed memory. These methods are optimized for various parameters and taking into account various properties of the algorithm. A distributed computing system has its own characteristics, such as heterogeneity of computing nodes, network bandwidth and others. The studies conducted by the authors of this article show that these characteristics do not interfere with the application of these methods to solving problems in a distributed computing environment. The article shows that there is no need to modify and adapt optimization methods for the use in distributed computing systems. However, it is necessary to take into account the properties of such systems contributed to the emergence of iteration in the application of optimization methods and the increase of the complexity of the process of analysis and optimization of the initial parallel algorithm. The article also describes ways to solve the problem of reducing the time complexity of the iterative application of optimization methods to the initial parallel algorithm. The results of the authors’ research is a method for constructing a special type of graph for a parallel algorithm that takes into account properties of a given computing system and approaches to constructing the schedule of the algorithm.
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Acknowledgments
The paper was prepared within the scope of the state project “Initiative scientific project” of the main part of the state plan of the Ministry of Education and Science of the Russian Federation (task № 2.6553.2017/8.9 BCH Basic Part) and was funded by RFBR according to the research project № 19-07-00784.
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Shichkina, Y., Kupriyanov, M., Awadh, AM.M.H. (2020). Application of Methods for Optimizing Parallel Algorithms for Solving Problems of Distributed Computing Systems. In: Arseniev, D., Overmeyer, L., Kälviäinen, H., Katalinić, B. (eds) Cyber-Physical Systems and Control. CPS&C 2019. Lecture Notes in Networks and Systems, vol 95. Springer, Cham. https://doi.org/10.1007/978-3-030-34983-7_21
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