Publicação
Design and implementation of a library for parallel independent computations in Octave
| Resumo: | This essay aims at developing, implementing and assessing a framework allowing the writing of parallel applications in Octave. The framework will be targeted at the simul- taneous evaluation of multiple instances of the same function with different parameters. The functionality of the frameworks is inspired in MATLAB’s Parallel Computing Tool- box, namely the parfeval function that uses an asynchronous model of computation. The system is developed using Oct-Files that allow the extension of the functionality of Octave; these extensions allow the communication between the Octave interpreter and an infrastructure built in Python that supports parallel executions. The parallel in- frastructure allows the exploitation of both shared-memory multiprocessors and clusters. The system has been evaluated using traditional embarrassing-parallel applications and its performance is good, if we’re able to ensure that the computations last for a time significantly greater than the overhead startup. |
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| Autores principais: | Candeias, Miguel Balão |
| Assunto: | Octave parallel applications in Octave asynchronous computation Oct-Files Python |
| Ano: | 2022 |
| País: | Portugal |
| Tipo de documento: | dissertação de mestrado |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade Nova de Lisboa |
| Idioma: | inglês |
| Origem: | Repositório Institucional da UNL |
| Resumo: | This essay aims at developing, implementing and assessing a framework allowing the writing of parallel applications in Octave. The framework will be targeted at the simul- taneous evaluation of multiple instances of the same function with different parameters. The functionality of the frameworks is inspired in MATLAB’s Parallel Computing Tool- box, namely the parfeval function that uses an asynchronous model of computation. The system is developed using Oct-Files that allow the extension of the functionality of Octave; these extensions allow the communication between the Octave interpreter and an infrastructure built in Python that supports parallel executions. The parallel in- frastructure allows the exploitation of both shared-memory multiprocessors and clusters. The system has been evaluated using traditional embarrassing-parallel applications and its performance is good, if we’re able to ensure that the computations last for a time significantly greater than the overhead startup. |
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