The method of constructing a schedule for parallel algorithmexecution is considered in the article. This algorithm takes into account the execution time of each operation of the algorithm and the relationship of oper...
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ISBN:
(纸本)9783319951713;9783319951706
The method of constructing a schedule for parallel algorithmexecution is considered in the article. This algorithm takes into account the execution time of each operation of the algorithm and the relationship of operations on the data. The method is based on an information graph in which the nodes are the operations of the algorithm, and the edges are the directions of the data transfer. As a result of the interchange of operations between computing nodes, it is possible to achieve a reduction in the execution time of the algorithm by reducing the time spent on data transfer between computing nodes and reducing the downtime of computational nodes. The algorithm can be applied both in parallel programming and in adjacent areas, for example, when scheduling tasks in distributed systems.
The article presents the results of studies on the adaptation of methods for optimising parallel algorithms by time and volume of computational resources to queries in relational databases. Research focuses on a metho...
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The article presents the results of studies on the adaptation of methods for optimising parallel algorithms by time and volume of computational resources to queries in relational databases. Research focuses on a method that allows you to improve the executionschedule of a parallel query by execution time due to the redistribution of operations between processes. It leads to a reduction in amount of messages transferred between processors, and to the time spent on transfer of data. It does not affect the amount of computational resources. The method is based on adjacency lists that correspond to the information graph of the algorithm. It can be applied in conjunction with other scheduling methods, for example, focused on computation node count optimisation, to achieve optimal result within multiple parameters.
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