دورية أكاديمية
A Parallel Computing Method for the Computation of the Moore–Penrose Generalized Inverse for Shared-Memory Architectures
| العنوان: | A Parallel Computing Method for the Computation of the Moore–Penrose Generalized Inverse for Shared-Memory Architectures |
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| المؤلفون: | Elkin Gelvez-Almeida, Ricardo J. Barrientos, Karina Vilches-Ponce, Marco Mora |
| المصدر: | IEEE Access, Vol 11, Pp 134834-134845 (2023) |
| بيانات النشر: | IEEE, 2023. |
| سنة النشر: | 2023 |
| المجموعة: | LCC:Electrical engineering. Electronics. Nuclear engineering |
| مصطلحات موضوعية: | High-performance computing, Moore–Penrose generalized inverse matrix, neural networks with random weights, parallel computing, Strassen algorithm, Electrical engineering. Electronics. Nuclear engineering, TK1-9971 |
| الوصف: | The 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. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 2169-3536 61664529 |
| Relation: | https://ieeexplore.ieee.org/document/10336814/; https://doaj.org/toc/2169-3536 |
| DOI: | 10.1109/ACCESS.2023.3338544 |
| URL الوصول: | https://doaj.org/article/b6166452959a482c958b2bd689ec6aec |
| رقم الأكسشن: | edsdoj.b6166452959a482c958b2bd689ec6aec |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 21693536 61664529 |
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| DOI: | 10.1109/ACCESS.2023.3338544 |