On Bernoulli Matrix Polynomials and Matrix Exponential Approximation
[EN] We present in this paper a new method based on Bernoulli matrix polynomials to approximate the exponential of a matrix. The developed method has given rise to two new algorithms whose efficiency and precision are compared to the most efficient implementations that currently exist. For that, a s...
| Autores: | , , , , |
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| Formato: | artículo |
| Fecha de publicación: | 2022 |
| País: | España |
| Recursos: | Universitat Politècnica de València (UPV) |
| Repositorio: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia |
| Idioma: | inglés |
| OAI Identifier: | oai:riunet.upv.es:10251/192276 |
| Acesso em linha: | https://riunet.upv.es/handle/10251/192276 |
| Access Level: | acceso abierto |
| Palavra-chave: | Bernoulli matrix approximation Matrix exponential function GPU computing MATEMATICA APLICADA CIENCIAS DE LA COMPUTACION E INTELIGENCIA ARTIFICIAL |
| Resumo: | [EN] We present in this paper a new method based on Bernoulli matrix polynomials to approximate the exponential of a matrix. The developed method has given rise to two new algorithms whose efficiency and precision are compared to the most efficient implementations that currently exist. For that, a state-of-the-art test matrix battery, that allows deeply exploring the highlights and downsides of each method, has been used. Since the new algorithms proposed here do make an intensive use of matrix products, we also provide a GPUs-based implementation that allows to achieve a high performance thanks to the optimal implementation of matrix multiplication available on these devices. (c) 2020 Elsevier B.V. All rights reserved |
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