Efficient and accurate algorithms for computing matrix trigonometric functions
[EN] Trigonometric matrix functions play a fundamental role in second order differential equations. This work presents an algorithm based on Taylor series for computing the matrix cosine. It uses a backward error analysis with improved bounds. Numerical experiments show that MATLAB implementations o...
| Autores: | , , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2017 |
| País: | España |
| Institución: | Universitat Politècnica de València (UPV) |
| Repositorio: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia |
| Idioma: | inglés |
| OAI Identifier: | oai:riunet.upv.es:10251/82821 |
| Acceso en línea: | https://riunet.upv.es/handle/10251/82821 |
| Access Level: | acceso abierto |
| Palabra clave: | Matrix cosine Matrix sine Scaling and squaring method Taylor series Backward error Parallel implementation CIENCIAS DE LA COMPUTACION E INTELIGENCIA ARTIFICIAL MATEMATICA APLICADA LENGUAJES Y SISTEMAS INFORMATICOS TEORIA DE LA SEÑAL Y COMUNICACIONES |
| Sumario: | [EN] Trigonometric matrix functions play a fundamental role in second order differential equations. This work presents an algorithm based on Taylor series for computing the matrix cosine. It uses a backward error analysis with improved bounds. Numerical experiments show that MATLAB implementations of this algorithm has higher accuracy than other MATLAB implementations of the state of the art in the majority of tests. Furthermore, we have implemented the designed algorithm in language C for general purpose processors, and in CUDA for one and two NVIDIA GPUs. We obtained a very good performance from these implementations thanks to the high computational power of these hardware accelerators and our effort driven to avoid as much communications as possible. All the implemented programs are accessible through the MATLAB environment. (C) 2016 Elsevier B.V. All rights reserved. |
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