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Asynchronous Richardson iterations: theory and practice

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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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Notes

  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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Acknowledgments

Work on this paper commenced while the three authors were attending a workshop at the Centre International de Rencontres Mathématiques, Luminy, France, in September 2019. The center’s support for such an event is greatly appreciated.

Funding

Work of the first and third authors was supported in part by the U.S. Department of Energy under grants DE-SC-0016564 and DE-SC-0016578.

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Correspondence to Edmond Chow.

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Chow, E., Frommer, A. & Szyld, D.B. Asynchronous Richardson iterations: theory and practice. Numer Algor 87, 1635–1651 (2021). https://doi.org/10.1007/s11075-020-01023-3

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