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Browsing by Author "Mallayev, Oybek"

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    Parallel Algorithm for Constructing a Cubic Spline on Multi-Core Processors in a Cluster
    (Ieee, 2020) Zaynidinov, Hakimjon; Mallayev, Oybek; Nurmurodov, Javohir; Department of Artificial Intelligence
    The article explores the possibility of computing parallel data compression using cubic spline. For example, ways to parallel the process of digital processing of seismic signals have been considered. The main performance indicators of parallel algorithms have been compared with consecutive algorithms. Spline methods are a versatile signal processing tool. It is more accurate than other mathematical methods, information equality is faster, and maintenance costs are much lower. On the other hand, the equipment used in such systems must also meet high performance requirements. To achieve high speeds, parallel algorithms were developed using OpenMP and MPI technologies and implemented in the architecture of multi-core processors. A mathematical method for the parallel calculation of the coefficients of a cubic spline has been developed and a parallel signal processing algorithm has been developed on its basis. As an example, parallelization is a computation during seismic signal processing. The main indicators of efficiency and acceleration of the parallel algorithm were compared with the sequential algorithm. Explained the relevance of the use of parallel numerical systems, described the main approaches to the distribution of processes and methods of data processing, described the principles of parallel programming technology, studied the basic parameters of parallel algorithms for the initial calculation of the numerical value of cubic spline. The parallel algorithm considered for constructing the cubic spline of defect 1 as p - > n leads to the construction of a local cubic spline on each grid interval omega.
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    Parallel Algorithm for Modeling Temperature Fields Using the Splines Method
    (Ieee, 2021) Zaynidinov, Hakimjon; Mallayev, Oybek; Kuchkarov, Muslimjon; Department of Artificial Intelligence
    The paper is devoted to the construction of an algorithm for parallelization of temperature field modeling processes based on bicubic spline and the problems that arise in it. It takes a lot of time and memory on a computer to model existing large-scale signals of temperature fields in three-dimensional graphical form. Solving these problems on the basis of the proposed parallel algorithm, the development of parallel algorithms and software tools to qualitatively determine the coordinates of high-temperature hotspots of temperature fields and allow them to be monitored continuously, and to calculate the digital processing of existing large-scale signals of temperature fields. Based on this, the article presents a parallel algorithm for digital processing of signals of temperature fields on the basis of bicubic spline and ways to parallel its computational processes using Open MP technology.