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- W2951473715 abstract "Asynchronous iterative methods present a mechanism to improve the performance of parallel algorithms for highly parallel computational platforms by removing the overhead associated with synchronization among computing elements. This paper considers a class of asynchronous iterative linear system solvers that employ randomization to determine the component update orders, and specifically focusing on the effects of non-uniform distributions. Results show that using distributions favoring the selection of components with a larger residual may lead to a faster convergence than that when selecting uniformly. In particular, in the best case of parameter choices, average times for the normal and exponential distributions were, respectively, 13.3% and 17.3% better than the performance with a uniform distribution." @default.
- W2951473715 created "2019-06-27" @default.
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- W2951473715 date "2019-04-01" @default.
- W2951473715 modified "2023-09-25" @default.
- W2951473715 title "Enhancing Asynchronous Linear Solvers Through Randomization" @default.
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- W2951473715 doi "https://doi.org/10.23919/springsim.2019.8732856" @default.
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