Empirical Analysis of Stochastic Methods of Linear Algebra

In this paper we present the results of an empirical study of stochastic projection and stochastic gradient descent methods as means of obtaining approximate inverses and preconditioners for iterative methods. Results of numerical experiments are used to analyse scalability and overall suitability o...

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Detalles Bibliográficos
Autores principales: Şahin, Mustafa Emre, Lebedev, Anton, Alexandrov, Vassil
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7304785/
http://dx.doi.org/10.1007/978-3-030-50436-6_40
Descripción
Sumario:In this paper we present the results of an empirical study of stochastic projection and stochastic gradient descent methods as means of obtaining approximate inverses and preconditioners for iterative methods. Results of numerical experiments are used to analyse scalability and overall suitability of the selected methods as practical tools for treatment of large linear systems of equations. The results are preliminary due to the code being not yet fully optimized.

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