Optimal polynomial smoothers for parallel AMG

In this paper, we explore polynomial accelerators that are well-suited for parallel computations, specifically as smoothers in Algebraic MultiGrid (AMG) preconditioners for symmetric positive definite matrices. These accelerators address a minimax problem, initially formulated in Lottes (Numer. Lin....

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Bibliographic Details
Published in:	Numerical algorithms Vol. 100; no. 4; pp. 1783 - 1812
Main Authors:	D’Ambra, Pasqua, Durastante, Fabio, Filippone, Salvatore, Massei, Stefano, Thomas, Stephen
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.12.2025 Springer Nature B.V
Subjects:	Accelerators Algebra Algorithms Approximation Basic converters Chebyshev approximation Computer Science Effectiveness Graphics processing units Iterative methods Matrices (mathematics) Minimax technique Numeric Computing Numerical Analysis Optimization Partial differential equations Polynomials Propagation Theory of Computation 65F10 AMG Parallel smoothers GPU 65F08 65N55 65Y05 Chebyshev polynomials
ISSN:	1017-1398, 1572-9265
Online Access:	Get full text
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