dc.creatorGelvez-Almeida, Elkin
dc.creatorBarrientos, Ricardo
dc.creatorVilches-Ponce, Karina
dc.creatorMora, Marco
dc.date2024-01-23T18:21:48Z
dc.date2024-01-23T18:21:48Z
dc.date2023
dc.date.accessioned2024-05-02T20:32:05Z
dc.date.available2024-05-02T20:32:05Z
dc.identifierhttp://repositorio.ucm.cl/handle/ucm/5201
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/9275386
dc.descriptionThe computation of the Moore–Penrose generalized inverse is a commonly used operation in various fields such as the training of neural networks based on random weights. Therefore, a fast computation of this inverse is important for problems where such neural networks provide a solution. However, due to the growth of databases, the matrices involved have large dimensions, thus requiring a significant amount of processing and execution time. In this paper, we propose a parallel computing method for the computation of the Moore–Penrose generalized inverse of large-size full-rank rectangular matrices. The proposed method employs the Strassen algorithm to compute the inverse of a nonsingular matrix and is implemented on a shared-memory architecture. The results show a significant reduction in computation time, especially for high-rank matrices. Furthermore, in a sequential computing scenario (using a single execution thread), our method achieves a reduced computation time compared with other previously reported algorithms. Consequently, our approach provides a promising solution for the efficient computation of the Moore–Penrose generalized inverse of large-size matrices employed in practical scenarios.
dc.languageen
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 Chile
dc.rightshttp://creativecommons.org/licenses/by-nc-nd/3.0/cl/
dc.sourceIEEE Access, 11, 134834-134845
dc.subjectSparse matrices
dc.subjectParallel processing
dc.subjectComputer architecture
dc.subjectPartitioning algorithms
dc.subjectMatrix decomposition
dc.subjectSymmetric matrices
dc.subjectComputational efficiency
dc.titleA parallel computing method for the computation of the Moore-Penrose generalized inverse for shared-memory architectures
dc.typeArticle


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