A parallel hybrid implementation of the 2D acoustic wave equation

Altybay, Arshyn; Ruzhansky, Michael; Tokmagambetov, Niyaz

doi:10.1515/ijnsns-2019-0227

Cited by 3 publications

(2 citation statements)

References 26 publications

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“…The paper does not consider the problems of the Navier-Stokes equation in doubly connected areas. In [23], a hybrid implementation was developed using the MPI, OpenMP and Compute Unified Device Architecture (CUDA) technologies and showed that this implementation gives good results.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

Development of parallel implementation for the Navier-Stokes equation in doubly connected areas using the fictitious domain method

Temirbekov

Altybay

Temirbekova

et al. 2022

EEJET

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This paper presents a numerical realization of the Navier-Stokes equations in irregular domains using the fictitious domain method with a continuation along with the lowest coefficient. To solve numerous connected issues in irregular regions, the fictitious domain method is broadly used. The advantage of the fictitious domain method is that the problem is solved not in the original complex domain, but in a few other, easier domains. Using the method, computation is done easily for a sufficiently wide class of problems with arbitrary computational domains. The problem is solved using two methods. The primary method is based on the development of a distinct issue in variables of the stream function and the vortex velocity using the pressure uniqueness condition. The second method is to understand the expressed issue by the fictitious domain method with a continuation by lower coefficients. Using the fictitious domain method, a computational algorithm is constructed based on the explicit finite difference schemes. The finite difference scheme is stable and has high computational accuracy and it gives the possibility to parallelize. Temperature distributions and stream functions are presented as numerical results. A parallel algorithm has been developed using Open Multi-Processing (hereinafter OpenMP) and Message Passing Interface (hereinafter MPI) technologies. Within the parallel approach, we used OpenMP technology for parallel calculation of vorticity and stream work, and for calculating temperature we applied MPI technology. The performance analysis on our parallel code shows favorable strong and weak scalability. The test results show that the code running in the parallel approach gives the expected results by comparing our results with those obtained while running the same simulation on the central processing unit (CPU)

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Section: Literature Review and Problem Statementmentioning

confidence: 99%

Development of parallel implementation for the Navier-Stokes equation in doubly connected areas using the fictitious domain method

Temirbekov

Altybay

Temirbekova

et al. 2022

EEJET

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“…The modern world and information systems are data-driven, generated in huge quantities every day [1]. Therefore, to obtain truly valuable results in modern realities in industrial, business or scientific problems, it is very important to be able to effectively process the big data available to us, using the tools available for this, and some scientists use parallel data processing on many computing nodes [2].…”

Section: Introductionmentioning

confidence: 99%

Intelligent Data Analysis on an Analytical Platform

Darkenbayev,

Altybay,

Darkenbayeva

et al. 2024

IAPGOS

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The article discusses methods for processing unstructured data using an analytical platform. The authors analyze existing methods and technologies used to implement data processing and propose new approaches to solving this problem. The possibilities of using analytical platforms to solve the problem of processing source data are considered. The purpose of the article is to explore the possibilities of data import, partial preprocessing, missing data recovery, anomaly removal, spectral processing and noise removal. The authors explored how analytics platforms can function without a data warehouse, obtaining information from any other sources, but the most optimal way is to use them together, and how big data and unstructured data can be processed using an analytics platform. The authors solved a specific problem related to processing problems and proposed ways to solve them using an analytical platform. Particular attention is paid to a complete set of mechanisms that allows you to obtain information from any data source, carry out the entire processing cycle and display the results. Overall, the paper represents an important contribution to the development of raw data processing technologies. The authors plan to continue research in the field of processing big unstructured data.

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