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Acceleration of computing and visualization processes with OpenCL for standing sea wave simulation model. / Ivashchenko, Andrei; Belezeko, Alexey; Gankevich, Ivan; Korkhov, Vladimir; Kulabukhova, Nataliia.

In: Lecture Notes in Computer Science, Vol. 10408, 2017, p. 505-518.

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@article{75394184df5a4552813fc34844ba0aa3,
title = "Acceleration of computing and visualization processes with OpenCL for standing sea wave simulation model",
abstract = "In this paper we highlight one of the possible acceleration approaches for the standing wave model simulation model with the use of OpenCL framework for GPGPU computations. We provide a description of the wave{\textquoteright}s mathematical model, an explanation for the technology selection, as well as the identification of the algorithm part that can be accelerated. The text also contains a description of solution{\textquoteright}s performance evaluation stage being compared with CPU-only program. The influence of OpenCL usage for improvements in rendering process is also shown here. Finally, possible ways of application improvement and further development are also considered.",
keywords = "Autoregressive process, Computing, Mathematical modelling, Moving average process, OpenCL, OpenGL, Real-time simulation, Velocity potential field, Visualisation",
author = "Andrei Ivashchenko and Alexey Belezeko and Ivan Gankevich and Vladimir Korkhov and Nataliia Kulabukhova",
year = "2017",
doi = "10.1007/978-3-319-62404-4_38",
language = "English",
volume = "10408",
pages = "505--518",
journal = "Lecture Notes in Computer Science",
issn = "0302-9743",
publisher = "Springer Nature",
note = "17th International Conference on Computational Science and Its Applications, ICCSA 2017 ; Conference date: 02-07-2017 Through 05-07-2017",

}

RIS

TY - JOUR

T1 - Acceleration of computing and visualization processes with OpenCL for standing sea wave simulation model

AU - Ivashchenko, Andrei

AU - Belezeko, Alexey

AU - Gankevich, Ivan

AU - Korkhov, Vladimir

AU - Kulabukhova, Nataliia

N1 - Conference code: 17

PY - 2017

Y1 - 2017

N2 - In this paper we highlight one of the possible acceleration approaches for the standing wave model simulation model with the use of OpenCL framework for GPGPU computations. We provide a description of the wave’s mathematical model, an explanation for the technology selection, as well as the identification of the algorithm part that can be accelerated. The text also contains a description of solution’s performance evaluation stage being compared with CPU-only program. The influence of OpenCL usage for improvements in rendering process is also shown here. Finally, possible ways of application improvement and further development are also considered.

AB - In this paper we highlight one of the possible acceleration approaches for the standing wave model simulation model with the use of OpenCL framework for GPGPU computations. We provide a description of the wave’s mathematical model, an explanation for the technology selection, as well as the identification of the algorithm part that can be accelerated. The text also contains a description of solution’s performance evaluation stage being compared with CPU-only program. The influence of OpenCL usage for improvements in rendering process is also shown here. Finally, possible ways of application improvement and further development are also considered.

KW - Autoregressive process

KW - Computing

KW - Mathematical modelling

KW - Moving average process

KW - OpenCL

KW - OpenGL

KW - Real-time simulation

KW - Velocity potential field

KW - Visualisation

UR - http://www.scopus.com/inward/record.url?scp=85026774789&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-62404-4_38

DO - 10.1007/978-3-319-62404-4_38

M3 - Article

AN - SCOPUS:85026774789

VL - 10408

SP - 505

EP - 518

JO - Lecture Notes in Computer Science

JF - Lecture Notes in Computer Science

SN - 0302-9743

T2 - 17th International Conference on Computational Science and Its Applications, ICCSA 2017

Y2 - 2 July 2017 through 5 July 2017

ER -

ID: 9305714