Big Data meets High Performance Computing: Genomics and Natural Language Processing as case studies
The main objective of this thesis is to clarify a way to the convergence between the Big Data and the High Performance Computing world. In order to do this, a study of the application of this kind of technologies to two real world scientific problems is performed. These two problems are the sequence...
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| Tipo de recurso: | tesis doctoral |
| Fecha de publicación: | 2017 |
| País: | España |
| Institución: | Universidad de Santiago de Compostela (USC) |
| Repositorio: | Minerva. Repositorio Institucional de la Universidad de Santiago de Compostela |
| Idioma: | inglés |
| OAI Identifier: | oai:minerva.usc.gal:10347/16420 |
| Acceso en línea: | http://hdl.handle.net/10347/16420 |
| Access Level: | acceso abierto |
| Palabra clave: | Materias::Investigación::33 Ciencias tecnológicas::3304 Tecnología de los ordenadores::330406 Arquitectura de ordenadores Materias::Investigación::12 Matemáticas::1203 Ciencia de los ordenadores::120323 Lenguajes de programación |
| Sumario: | The main objective of this thesis is to clarify a way to the convergence between the Big Data and the High Performance Computing world. In order to do this, a study of the application of this kind of technologies to two real world scientific problems is performed. These two problems are the sequence alignment in genomics and the natural language processing. These problems have a very big input and output size, and are computationally intensive, requiring a very high execution time. By facing these problems, also new tools that can be used by professionals in the areas are developed. Conclusions about convergence between these two worlds are presented, taking into account results from this study. |
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