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Published in: Numerical Algorithms 4/2021

18-10-2020 | Original Paper

Asynchronous Richardson iterations: theory and practice

Published in: Numerical Algorithms | Issue 4/2021

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Abstract

We consider asynchronous versions of the first- and second-order Richardson methods for solving linear systems of equations. These methods depend on parameters whose values are chosen a priori. We explore the parameter values that can be proven to give convergence of the asynchronous methods. This is the first such analysis for asynchronous second-order methods. We find that for the first-order method, the optimal parameter value for the synchronous case also gives an asynchronously convergent method. For the second-order method, the parameter ranges for which we can prove asynchronous convergence do not contain the optimal parameter values for the synchronous iteration. In practice, however, the asynchronous second-order iterations may still converge using the optimal parameter values, or parameter values close to the optimal ones, despite this result. We explore this behavior with a multithreaded parallel implementation of the asynchronous methods.

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Footnotes
1
See also [7, 25].
 
2
Gene Golub in his thesis [14] calls this a method of averaging, following the nomenclature used by von Neumann.
 
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Metadata
Title
Asynchronous Richardson iterations: theory and practice
Publication date
18-10-2020
Published in
Numerical Algorithms / Issue 4/2021
Print ISSN: 1017-1398
Electronic ISSN: 1572-9265
DOI
https://doi.org/10.1007/s11075-020-01023-3

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