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On the Parallel Strategies in Mathematical Modeling. / Il’in, Valery.

Parallel Computational Technologies - 11th International Conference, PCT 2017, Revised Selected Papers. ред. / L Sokolinsky; M Zymbler. Том 753 Springer-Verlag GmbH and Co. KG, 2017. стр. 73-85 (Communications in Computer and Information Science; Том 753).

Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференцийстатья в сборнике материалов конференциинаучнаяРецензирование

Harvard

Il’in, V 2017, On the Parallel Strategies in Mathematical Modeling. в L Sokolinsky & M Zymbler (ред.), Parallel Computational Technologies - 11th International Conference, PCT 2017, Revised Selected Papers. Том. 753, Communications in Computer and Information Science, Том. 753, Springer-Verlag GmbH and Co. KG, стр. 73-85, 11th International Conference on Parallel Computational Technologies, PCT 2017, Kazan, Российская Федерация, 03.04.2017. https://doi.org/10.1007/978-3-319-67035-5_6

APA

Il’in, V. (2017). On the Parallel Strategies in Mathematical Modeling. в L. Sokolinsky, & M. Zymbler (Ред.), Parallel Computational Technologies - 11th International Conference, PCT 2017, Revised Selected Papers (Том 753, стр. 73-85). (Communications in Computer and Information Science; Том 753). Springer-Verlag GmbH and Co. KG. https://doi.org/10.1007/978-3-319-67035-5_6

Vancouver

Il’in V. On the Parallel Strategies in Mathematical Modeling. в Sokolinsky L, Zymbler M, Редакторы, Parallel Computational Technologies - 11th International Conference, PCT 2017, Revised Selected Papers. Том 753. Springer-Verlag GmbH and Co. KG. 2017. стр. 73-85. (Communications in Computer and Information Science). doi: 10.1007/978-3-319-67035-5_6

Author

Il’in, Valery. / On the Parallel Strategies in Mathematical Modeling. Parallel Computational Technologies - 11th International Conference, PCT 2017, Revised Selected Papers. Редактор / L Sokolinsky ; M Zymbler. Том 753 Springer-Verlag GmbH and Co. KG, 2017. стр. 73-85 (Communications in Computer and Information Science).

BibTeX

@inproceedings{a291e83b2a6e416d945dba7bd58f4487,
title = "On the Parallel Strategies in Mathematical Modeling",
abstract = "The article considers parallel strategies and tactics at different stages of mathematical modeling. These technological steps include geometrical and functional modeling, discretization and approximation, algebraic solvers and optimization methods for inverse problems, postprocessing and visualization of numerical results, as well as decision-making systems. Scalable parallelism can be provided by combined application of MPI tools, multi-thread computing, vectorization, and the use of graphics accelerators. The general method to achieve high-performance computing consists in minimizing data communications, which are the most time and energy consuming. The construction of efficient parallel algorithms and code optimization is based on various approaches at different levels of computational schemes. The implementation of the biggest interdisciplinary direct and inverse problems in cloud computing technologies is considered. The corresponding applied software with a long life cycle is represented as integrated environment oriented to large groups of end users.",
keywords = "Accelerators, Communications, Domain decomposition, Exchange buffers, Hierarchical memory, Multi-thread computing, Runtime, Scalable parallelism, Speedup, Vectorization",
author = "Valery Il{\textquoteright}in",
year = "2017",
month = jan,
day = "1",
doi = "10.1007/978-3-319-67035-5_6",
language = "English",
isbn = "9783319670348",
volume = "753",
series = "Communications in Computer and Information Science",
publisher = "Springer-Verlag GmbH and Co. KG",
pages = "73--85",
editor = "L Sokolinsky and M Zymbler",
booktitle = "Parallel Computational Technologies - 11th International Conference, PCT 2017, Revised Selected Papers",
address = "Germany",
note = "11th International Conference on Parallel Computational Technologies, PCT 2017 ; Conference date: 03-04-2017 Through 07-04-2017",

}

RIS

TY - GEN

T1 - On the Parallel Strategies in Mathematical Modeling

AU - Il’in, Valery

PY - 2017/1/1

Y1 - 2017/1/1

N2 - The article considers parallel strategies and tactics at different stages of mathematical modeling. These technological steps include geometrical and functional modeling, discretization and approximation, algebraic solvers and optimization methods for inverse problems, postprocessing and visualization of numerical results, as well as decision-making systems. Scalable parallelism can be provided by combined application of MPI tools, multi-thread computing, vectorization, and the use of graphics accelerators. The general method to achieve high-performance computing consists in minimizing data communications, which are the most time and energy consuming. The construction of efficient parallel algorithms and code optimization is based on various approaches at different levels of computational schemes. The implementation of the biggest interdisciplinary direct and inverse problems in cloud computing technologies is considered. The corresponding applied software with a long life cycle is represented as integrated environment oriented to large groups of end users.

AB - The article considers parallel strategies and tactics at different stages of mathematical modeling. These technological steps include geometrical and functional modeling, discretization and approximation, algebraic solvers and optimization methods for inverse problems, postprocessing and visualization of numerical results, as well as decision-making systems. Scalable parallelism can be provided by combined application of MPI tools, multi-thread computing, vectorization, and the use of graphics accelerators. The general method to achieve high-performance computing consists in minimizing data communications, which are the most time and energy consuming. The construction of efficient parallel algorithms and code optimization is based on various approaches at different levels of computational schemes. The implementation of the biggest interdisciplinary direct and inverse problems in cloud computing technologies is considered. The corresponding applied software with a long life cycle is represented as integrated environment oriented to large groups of end users.

KW - Accelerators

KW - Communications

KW - Domain decomposition

KW - Exchange buffers

KW - Hierarchical memory

KW - Multi-thread computing

KW - Runtime

KW - Scalable parallelism

KW - Speedup

KW - Vectorization

UR - http://www.scopus.com/inward/record.url?scp=85032509823&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-67035-5_6

DO - 10.1007/978-3-319-67035-5_6

M3 - Conference contribution

AN - SCOPUS:85032509823

SN - 9783319670348

VL - 753

T3 - Communications in Computer and Information Science

SP - 73

EP - 85

BT - Parallel Computational Technologies - 11th International Conference, PCT 2017, Revised Selected Papers

A2 - Sokolinsky, L

A2 - Zymbler, M

PB - Springer-Verlag GmbH and Co. KG

T2 - 11th International Conference on Parallel Computational Technologies, PCT 2017

Y2 - 3 April 2017 through 7 April 2017

ER -

ID: 9753964