Heterogeneous Implementation of Preconditioners Based on Gauss–Seidel Method for Sparse Block Matrices

In this paper we present a parallel preconditioner algorithm for the Krylov-type iterative method based on the multicolor Gauss–Seidel method and its transferable heterogeneous software implementation using the OpenCL computational standard. A special feature is its application to block sparse matri...

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Bibliographic Details
Published in:Computational mathematics and modeling Vol. 33; no. 4; pp. 438 - 442
Main Authors: Magomedov, A. R., Gorobets, A. V.
Format: Journal Article
Language:English
Published: New York Springer US 01.10.2022
Springer Nature B.V
Subjects:
Algorithms
Applications of Mathematics
Compressibility
Computational Mathematics and Numerical Analysis
Gauss-Seidel method
Hybrid systems
II. Numerical Methods
Iterative methods
Mathematical Modeling and Industrial Mathematics
Mathematics
Mathematics and Statistics
Optimization
Sparse matrices
Gauss–Seidel method
hybrid computing systems
preconditioner
sparse matrices
ISSN:1046-283X, 1573-837X
Online Access:Get full text
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Summary:In this paper we present a parallel preconditioner algorithm for the Krylov-type iterative method based on the multicolor Gauss–Seidel method and its transferable heterogeneous software implementation using the OpenCL computational standard. A special feature is its application to block sparse matrices as part of a numerical technique for modeling compressible turbulent flows. Optimization techniques are described that allow obtaining multiple speedups on graphics processors. Results of performance testing on a hybrid computing system are presented.
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ISSN:1046-283X
1573-837X
DOI:10.1007/s10598-023-09585-2